Automated measurement of brain and white matter lesion volume in type 2 diabetes mellitus Aims/hypothesis Type 2 diabetes mellitus has been associated with brain atrophy and cognitive decline , but the association with ischaemic white matter lesions is unclear . Previous neuroimaging studies have mainly used semiquantitative rating scales to measure atrophy and white matter lesions -LRB- WMLs -RRB- . In this study we used an automated segmentation technique to investigate the association of type 2 diabetes , several diabetes-related risk factors and cognition with cerebral tissue and WML volumes . Introduction Diabetes mellitus type 2 is associated with accelerated cognitive impairment and an increased incidence of dementia -LSB- 1 -RSB- . Recently , we have demonstrated that cognitive impairments in patients with type 2 diabetes are accompanied by brain atrophy and ischaemic white matter lesions -LRB- WMLs -RRB- -LSB- 2 -RSB- . Other neuroimaging studies have also demonstrated that type 2 diabetes is associated with a moderate degree of cerebral atrophy -LSB- 3 -- 5 -RSB- and with an increased occurrence of cerebral infarcts -LSB- 6 -RSB- . These studies have used either semiquantitative rating scales -LSB- 3 , 4 -RSB- or cerebrospinal fluid to brain ratios -LSB- 2 , 4 -RSB- to assess atrophy . Quantitative assessment of volumes of grey matter , white matter , lateral ventricle , and cerebrospinal fluid in patients with type 2 diabetes has not been performed . The association between WMLs and type 2 diabetes is debated . Although several studies found an association between type 2 diabetes and WML severity or progression -LSB- 2 , 7 -- 13 -RSB- , others did not -LSB- 4 , 5 , 14 -- 18 -RSB- . These inconsistencies are probably due to the use of different , mostly semiquantitative , WML grading methods , and differences in study design and population selection . Furthermore , even within the population of healthy elderly the variance in WML severity is large -LSB- 19 -RSB- . The present study aimed to determine quantitatively the effects of type 2 diabetes on cerebral tissue volumes and WML severity by using an accurate magnetic resonance -LRB- MR -RRB- imaging-based automated segmentation algorithm -LSB- 20 -RSB- in a large , representative , cross-sectional , population-based sample of patients with type 2 diabetes and control participants . A second aim was to study the association of several diabetes-related variables and cognition with cerebral tissue volumes and WML severity . Subjects and methods Participants Participants were recruited between September 2002 and November 2004 as part of the Utrecht Diabetic Encephalopathy Study -LRB- UDES -RRB- , a cross-sectional , population-based study on determinants of impaired cognition in type 2 diabetes -LSB- 2 -RSB- . The UDES study aimed to identify potential risk factors for cognitive impairment in type 2 diabetes . Therefore , patients were not selected for the presence or absence of diabetic complications , comorbid conditions -LRB- e.g. hypertension -RRB- or exposure to other risk factors -LRB- e.g. smoking -RRB- . For inclusion in the present study , participants had to be 55 -- 80 years of age , functionally independent , and Dutch-speaking . Type 2 diabetes patients -LRB- n = 122 ; 56 -- 80 years of age -RRB- were recruited through their general practitioner and had a diabetes duration of at least 1 year . Controls -LRB- n = 57 , 55 -- 78 years of age -RRB- were recruited among the spouses and acquaintances of the patients . Exclusion criteria for all participants were a psychiatric or neurological disorder unrelated to diabetes that could influence cognitive functioning , a history of alcohol or substance abuse , and dementia . Controls with a fasting blood glucose ≥ 7.0 mol/l were also excluded . Twice as many patients as controls were included to increase the statistical power of within-group analyses in the type 2 diabetes group . The study was approved by the medical ethics committee of the University Medical Center Utrecht and each participant signed an informed consent form.In a standardised interview , participants were questioned about diabetes duration , height and weight , history of hypertension and smoking , level of education -LRB- seven categories , corresponding to years of education : < 6 , 6 -- 7 , 8 , 9 , 10 -- 11 , 12 -- 18 and > 18 , respectively -LSB- 21 -RSB- -RRB- , medication use and history of vascular disease . Furthermore , all participants measured their blood pressure at home at nine different time points during the day . These measurements were used to calculate the mean arterial pressure . Hypertension was defined as an average systolic blood pressure ≥ 160 mmHg and/or diastolic blood pressure ≥ 95 mmHg and/or self-reported use of blood pressure-lowering drugs . BMI , fasting glucose and HbA1c were also determined . Hypercholesterolaemia was defined as a cholesterol : HDL-cholesterol ratio greater than 5 -LSB- 22 -RSB- or the use of cholesterol-lowering drugs . All subjects underwent a neuropsychological evaluation , including 11 different tests addressing the cognitive domains of visuo-construction , attention and executive function , information processing speed , memory and abstract reasoning -LSB- 2 -RSB- . For further analysis , the raw scores of the different tests were standardised into z-scores per domain . For the present study , these z-scores were averaged into one composite cognitive z-score . Brain MR images were acquired as part of the study . In 23 participants with type 2 diabetes and 11 control participants no MR images were available for automated analysis : in 14 cases -LRB- five controls , nine diabetic patients -RRB- an MR image had not been performed because of MR contraindications and in 20 cases -LRB- six controls , 14 diabetic patients -RRB- the scan could not be analysed automatically because of technical problems , such as failure to retrieve the digital MR images or incompleteness of the series of images , or because image quality did not allow automated processing . Data for 99 patients with type 2 diabetes and 46 controls were analysed . Age , sex and duration of diabetes for the excluded subjects were similar to those for the included subjects -LRB- control subjects , average age 64.6 years , five men and six women ; diabetic subjects , average age 66.5 years , 13 men , ten women , average diabetes duration 8.7 years -RRB- . MR imaging Brain MR images were acquired on a Philips Gyroscan ACS-NT 15 whole-body system operating at 1.5 T -LRB- Philips Medical Systems , Best , The Netherlands -RRB- with a standardised MR protocol -LRB- slice thickness 4 mm , 38 contiguous slices , 230 × 230 mm field of view , 256 × 256 scan matrix -RRB- . Axial T1 , inversion recovery -LRB- IR -RRB- , T2 , proton density -LRB- PD -RRB- and fluid attenuated inversion recovery -LRB- FLAIR -RRB- scans were made : T1 , 234/2 ms -LRB- repetition/echo time -RRB- ; IR , 2919/410/22 ms -LRB- repetition/inversion/echo time -RRB- ; T2 , 2200/100 ms -LRB- repetition/echo time -RRB- ; PD , 2200/11 ms -LRB- repetition/echo time -RRB- ; FLAIR , 6000/2000/100 ms -LRB- repetition/inversion/echo time -RRB- . Image processing Preprocessing consisted of intrasubject registration of the five MR sequences and extraction of a brain mask . Registration was performed using an affine nine-parameter mutual information-based algorithm -LSB- 23 -RSB- with the FLAIR image as reference.Brain masks were constructed to exclude the skull , skin and background during classification . The masks were extracted by k-means clustering of the T1 , IR , T2 , PD and FLAIR images using eight clusters . The clusters containing cerebrospinal fluid and brain were combined . Holes in the mask were filled and appending structures , such as eyes , were removed using morphological operators . Dilation of the brain mask by three voxels ensured the inclusion of all cerebrospinal fluid . One mask had to be edited manually because appending structures were included . The final brain masks contained the whole brain including the cerebellum and brainstem.Segmentation of the MR IR and FLAIR images into white matter , cortical and subcortical grey matter , lateral ventricles , cerebrospinal fluid not including the lateral ventricles -LRB- CSF -RRB- and WML was executed fully automatically by means of a probabilistic k-nearest neighbour -LRB- KNN -RRB- - based classification algorithm -LSB- 20 -RSB- . The algorithm was trained on expert manual segmentations of ten subjects who had varying degrees of WML , who were similar in age to the participants of this study and scanned using the same protocol , but who did not participate in this study . Manual segmentation of grey matter and white matter was performed on MR IR images , because these provide optimal tissue contrast for the assessment of the grey matter -- white matter boundary , and manual segmentation of lateral ventricles , CSF and WML was performed on MR FLAIR images . All MR images were available to the expert for reference . Performance of the classification algorithm was validated previously using a leave-one-out procedure and resulted in similarity indexes of at least 0.808 , indicating excellent agreement -LSB- 20 -RSB- . For each participant , classification produces five separate images of white matter , grey matter , lateral ventricles , CSF and WML probability per voxel . As an example , the result of the classification of the MR FLAIR and inversion recovery images of a diabetes patient is shown in Fig. 1 . White matter , grey matter , CSF and lateral ventricle volumes were calculated by summing over the probability image and multiplying with the voxel dimensions . WML volume calculation deviated slightly . A threshold of 0.5 was applied on the WML probability image and all unconnected voxels were removed . Then , WML volume was calculated by summation over the image and multiplication with the voxel dimensions . The intracranial volume was calculated as the sum of white matter , grey matter , lateral ventricles , CSF and WML volumes ; total brain as white matter plus grey matter volume ; and total CSF as CSF plus lateral ventricle volume . Volumes of automatically segmented tissues for the male control participants of the present study did not differ from the tissue volumes found for the manually segmented men -LRB- manually segmented men , n = 8 ; women , n = 2 -LSB- not compared with female controls -RSB- -RRB- . Furthermore , all segmentations were carefully reviewed by one of the authors -LRB- C. Jongen -RRB- . During this process , the author was blinded to the diabetes mellitus status of the participants . Twelve WML segmentations were manually edited to be sure that infarcted tissue was excluded and ten were edited because of artefacts in the FLAIR image . Fig. 1MR FLAIR -LRB- a -RRB- and inversion recovery image -LRB- b -RRB- of a diabetes patient with relatively severe WMLs . On the MR FLAIR image , the WMLs are clearly visible as white areas , whereas on the inversion recovery image the boundary between grey and white matter is much better defined . -LRB- c -RRB- The result of segmentation using the automated KNN-based algorithm . The colours indicate the different tissue classes : grey matter -LRB- yellow -RRB- , white matter -LRB- dark blue -RRB- , lateral ventricles -LRB- green -RRB- , CSF -LRB- red -RRB- and WML -LRB- light blue -RRB- Statistical analysis Differences in demographic data and risk factors between control participants and those with type 2 diabetes were analysed using a univariate general linear model or logistic regression adjusting for age and sex . A univariate general linear model was used to analyse differences in tissue volume between type 2 diabetes and control participants adjusting for age , sex , intracranial volume and level of education . Additionally , separate analyses for men and women were performed , because cerebral tissue volumes are different among men and women . Kolmogorov -- Smirnov tests showed that WML volume was not normally distributed . Therefore , we used a natural log transformation of WML volumes in the analyses . Lateral ventricle volume distribution was slightly non-normal . Using natural log-transformed volumes gave similar results to using untransformed volumes . For ease of interpretation , results for untransformed volumes are reported . Additionally , the associations of age with tissue volumes were analysed . Furthermore , associations between the tissue volumes with the composite cognitive performance were analysed for type 2 diabetes and control participants separately , adjusting for age , sex , intracranial volume and level of education . Within the group of type 2 diabetes patients associations between MR volume measures and diabetes duration , HbA1c , hypertension , mean arterial pressure , history of macrovascular disease , and hypercholesterolaemia were determined , adjusting for age , sex , intracranial volume and level of education . All data were analysed using SPSS 12.0.1 -LRB- SPSS Inc. , Chicago , IL , USA -RRB- . Results Patient characteristics are shown in Table 1 . Table 2 shows the brain tissue and WML volumes unadjusted for differences in age or intracranial volume . Table 3 shows the results of the analysis of the tissue volume differences between controls and patients with type 2 diabetes . Diabetes patients had significantly smaller grey matter volume -LRB- estimated volume difference − 21.8 ml ; 95 % CI − 34.2 , − 9.4 ; p = 0.001 ; F = 12.091 -RRB- and significantly larger lateral ventricle volume than controls -LRB- estimated volume difference 7.1 ml ; 95 % CI 2.3 , 12.0 ; p = 0.004 ; F = 8.441 -RRB- . Total CSF volume was also larger in diabetes patients , but not significantly so -LRB- estimated volume difference 9.5 ml , 95 % CI − 0.4 , 19.5 ; p = 0.060 ; F = 3.594 -RRB- . White matter volume was unaffected -LRB- estimated volume difference 2.8 ml , 95 % CI − 3.2 , 8.8 ; NS ; F = 0.844 -RRB- . WML volume was significantly larger in type 2 diabetes patients -LRB- 56.5 % ; 95 % CI 4.0 , 135.8 ; p = 0.032 ; F = 4.684 -RRB- . The cumulative distribution of WML volume is shown in Fig. 2 . All participants had at least some WML . However , in type 2 diabetes patients a smaller proportion of the subjects had very small lesion volumes -LRB- < 0.5 ml -RRB- -LRB- Pearson χ2 with continuity correction , p = 0.014 -RRB- . Such very small volumes mostly reflect pencil-thin lining and capping , which is often considered to be a normal finding in this age group -LSB- 19 -RSB- . The regression analyses were repeated for men and women separately -LRB- Table 3 -RRB- . Although the direction of the effect of type 2 diabetes was similar in the two sexes , significant associations of type 2 diabetes with tissue volume were only found in women . Table 1Demographics of participants and risk factors Control participantsType 2 diabetes patientsMean difference -LRB- 95 % CI -RRB- aOdds ratio -LRB- 95 % CI -RRB- aMen/women20/2649 / 50 -- 1.3 -LRB- 0.6 , 2.6 -RRB- Age -LRB- years -RRB- Men66 .4 -LRB- 6.3 -RRB- 65.9 -LRB- 6.0 -RRB- − 0.5 -LRB- − 2.8 , 3.7 -RRB- -- Women63 .8 -LRB- 5.0 -RRB- 65.9 -LRB- 5.2 -RRB- 2.1 -LRB- − 0.4 , 4.5 -RRB- -- Level of educationb4 -LRB- 3 -- 5 -RRB- 4 -LRB- 3 -- 5 -RRB- -- -- Diabetes duration -LRB- years -RRB- -- 8.7 -LRB- 6.1 -RRB- -- -- HbA1c -LRB- % -RRB- 5.5 -LRB- 0.3 -RRB- 6.8 -LRB- 1.2 -RRB- 1.4 -LRB- 1.0 , 1.7 -RRB- *** -- Use of insulin -LRB- % -RRB- -- 29.3 -- -- Hypertension -LRB- % -RRB- c28 .370.76.2 -LRB- 2.8 , 13.5 -RRB- *** Mean arterial pressure -LRB- mmHg -RRB- 97.5 -LRB- 10.6 -RRB- 102.6 -LRB- 11.5 -RRB- 4.8 -LRB- 0.9 , 8.8 -RRB- * -- History of macrovascular disease -LRB- % -RRB- 4.327.3 -- 8.3 -LRB- 1.8 , 37.0 -RRB- ** Hypercholesterolaemia -LRB- % -RRB- 42.269.4 -- 3.7 -LRB- 1.7 , 8.1 -RRB- ** Smoking ever -LRB- % -RRB- 47.866.3 -- 2.2 -LRB- 1.0 , 4.7 -RRB- * BMI -LRB- kg/m2 -RRB- 27.2 -LRB- 4.4 -RRB- 28.0 -LRB- 4.4 -RRB- 0.8 -LRB- − 0.8 , 2.4 -RRB- -- Cognition -LRB- composite z-score -RRB- 0.13 -LRB- 0.45 -RRB- − 0.10 -LRB- 0.63 -RRB- − 0.22 -LRB- − 0.40 , − 0.05 -RRB- * d -- Data in first two columns are mean -LRB- SD -RRB- except for level of education , which is given as median -LRB- interquartile range -RRB- * p < 0.05 ; ** p < 0.01 ; *** p < 0.001 aAdjusted for age and sexbSeven categories , corresponding to years of education : < 6 , 6 -- 7 , 8 , 9 , 10 -- 11 , 12 -- 18 and > 18 , respectivelycAll controls with hypertension and 96 % of diabetic patients with hypertension used antihypertensive drugsdAdjusted for age , sex and level of educationTable 2Volumes of cerebral compartments -LRB- ml -RRB- unadjusted for age or intracranial volume Control participantsType 2 diabetes patientsMenWomenMenWomenWhite matter688 .0 -LRB- 49.3 -RRB- 621.8 -LRB- 46.9 -RRB- 687.2 -LRB- 56.5 -RRB- 601.0 -LRB- 56.5 -RRB- Grey matter401 .7 -LRB- 47.8 -RRB- 404.4 -LRB- 40.8 -RRB- 388.3 -LRB- 48.8 -RRB- 360.1 -LRB- 35.6 -RRB- Total brain1 ,090 -LRB- 81.0 -RRB- 1,026 -LRB- 72.9 -RRB- 1,076 -LRB- 91.0 -RRB- 961.1 -LRB- 71.0 -RRB- Lateral ventricle33 .9 -LRB- 18.7 -RRB- 22.1 -LRB- 8.66 -RRB- 36.9 -LRB- 17.4 -RRB- 29.8 -LRB- 13.9 -RRB- Lateral ventriclea30 .1 -LRB- 23.9 -- 36.6 -RRB- 20.3 -LRB- 16.6 -- 28.0 -RRB- 33.8 -LRB- 24.9 -- 42.6 -RRB- 26.7 -LRB- 20.6 -- 35.3 -RRB- CSF excluding lateral ventricles273 .3 -LRB- 27.1 -RRB- 222.1 -LRB- 25.1 -RRB- 279.7 -LRB- 37.8 -RRB- 229.4 -LRB- 35.9 -RRB- Total CSF307 .2 -LRB- 32.3 -RRB- 244.2 -LRB- 26.3 -RRB- 316.5 -LRB- 42.4 -RRB- 259.2 -LRB- 41.2 -RRB- WML3 .89 -LRB- 5.76 -RRB- 2.98 -LRB- 4.70 -RRB- 3.66 -LRB- 5.37 -RRB- 6.19 -LRB- 14.2 -RRB- WMLa1 .81 -LRB- 0.47 -- 3.48 -RRB- 1.00 -LRB- 0.48 -- 3.20 -RRB- 2.16 -LRB- 0.91 -- 3.86 -RRB- 2.56 -LRB- 0.86 -- 4.46 -RRB- Intracranial volume1 ,403 -LRB- 90.7 -RRB- 1,275 -LRB- 82.2 -RRB- 1,398 -LRB- 104.2 -RRB- 1,228 -LRB- 93.7 -RRB- aLateral ventricle and WML volumes are median -LRB- interquartile range -RRB- ; other data are mean -LRB- SD -RRB- Between-group comparisons and statistical analyses are presented in Table 3Table 3Adjusted tissue volume differences between participants with type 2 diabetes and control participants Estimated volume difference -LRB- ml -RRB- F valueAll White matter2 .8 -LRB- − 3.2 , 8.8 -RRB- 0.844 Grey matter − 21.8 -LRB- − 34.2 , − 9.4 -RRB- ** 12.091 Total brain − 19.0 -LRB- − 29.9 , − 8.1 -RRB- ** 11.863 Lateral ventricles7 .1 -LRB- 2.3 , 12.0 -RRB- ** 8.441 CSF not including lateral ventricles9 .5 -LRB- − 0.4 , 19.5 -RRB- 3.594 Total CSF16 .7 -LRB- 6.8 , 26.5 -RRB- ** 11.247 LN WML0 .45 -LRB- 0.04 , 0.86 -RRB- a * 4.684 Men White matter1 .8 -LRB- − 7.4 , 11.0 -RRB- 0.157 Grey matter − 14.5 -LRB- − 33.6 , 4.6 -RRB- 2.315 Total brain − 12.7 -LRB- − 30.6 , 5.2 -RRB- 2.026 Lateral ventricles4 .9 -LRB- − 3.7 , 13.5 -RRB- 1.283 CSF not including lateral ventricles6 .9 -LRB- − 10.2 , 24.0 -RRB- 0.650 Total CSF11 .8 -LRB- − 4.9 , 28.5 -RRB- 1.993 LN WML0 .37 -LRB- − 0.19 , 0.93 -RRB- b1 .781 Women White matter7 .0 -LRB- − 1.5 , 15.6 -RRB- 2.696 Grey matter − 37.1 -LRB- − 54.1 , − 20.1 -RRB- *** 19.062 Total brain − 30.1 -LRB- − 44.9 , 15.4 -RRB- *** 16.695 Lateral ventricles9 .0 -LRB- 3.2 , 14.8 -RRB- ** 9.563 CSF not including lateral ventricles17 .2 -LRB- 4.9 , 29.4 -RRB- ** 7.802 Total CSF26 .1 -LRB- 13.6 , 38.7 -RRB- *** 17.215 LN WML0 .54 -LRB- − 0.11 , 1.20 -RRB- c2 .745 LN WML Natural log of WML volumeData are mean -LRB- 95 % CI -RRB- adjusted for age , sex , intracranial volume and level of education -LRB- data missing for one woman with type 2 diabetes -RRB- * p < 0.05 ; ** p < 0.01 ; *** p < 0.001 a56 .5 % -LRB- 95 % CI 4.0 , 135.8 -RRB- b44 .9 % -LRB- 95 % CI − 17.0 , 154.7 -RRB- c72 .4 % -LRB- 95 % CI − 10.6 , 232.4 -RRB- Fig. 2Cumulative distribution of WML volume -LRB- control men , closed squares ; men with type 2 diabetes , closed triangles ; control women , open squares ; women with type 2 diabetes , open triangles -RRB- . Very small lesion volumes -LRB- < 0.5 ml -RRB- were significantly more frequent among controls -LRB- p = 0.014 -RRB- than participants with type 2 diabetes Within the patients with type 2 diabetes , no significant associations between MR volumes and diabetes duration , hypertension , mean arterial pressure or hypercholesterolaemia were found . Higher HbA1c levels were associated with larger grey matter volume -LRB- 6.479 ml per unit HbA1c -LRB- % -RRB- ; 95 % CI 0.2 , 12.8 ; p = 0.043 ; F = 4.203 -RRB- , but not with any other volume abnormalities . A history of macrovascular disease was associated with a larger total CSF volume -LRB- 12.4 ml ; 95 % CI 2.6 , 28.7 ; p = 0.020 ; F = 5.659 -RRB- and a smaller total brain volume -LRB- − 15.0 ml ; 95 % CI − 29.8 , − 0.2 ; p = 0.047 ; F = 4.057 -RRB- . In the diabetic participants lower composite cognitive performance was associated with significantly smaller total brain volume -LRB- − 15.4 ml per unit of the composite cognitive z-score ; 95 % CI − 27.6 , − 3.1 ; p = 0.015 ; F = 6.199 -RRB- , larger WML volume -LRB- 57.4 % ; 95 % CI 2.2 , 142.4 ; p = 0.040 ; F = 4.370 -RRB- and non-significantly larger total CSF volume -LRB- 11.0 ml ; 95 % CI − 0.6 , 22.1 ; p = 0.051 ; F = 3.911 -RRB- . In the control group exploratory analyses showed an association between higher BMI and larger total CSF volume -LRB- 2.0 ml ; 95 % CI 0.34 , 3.6 ; p = 0.017 ; F = 6.287 -RRB- . No other significant associations were found within the control group . Across the whole population , age was significantly associated with reduced grey matter and total brain volumes and larger lateral ventricle , CSF , total CSF and WML volumes -LRB- p < 0.001 ; F > 20.424 ; adjusted for diabetic status , sex , intracranial volume and level of education -RRB- . Age was the most powerful predictor of WML and lateral ventricle volumes and it came second after intracranial volume for predicting grey matter , CSF , total brain and total CSF volumes . No significant interactions between age and type 2 diabetes were found -LRB- all p > 0.14 -RRB- . The interaction between age and sex showed a trend towards significance , men having more grey matter decrease -LRB- − 1.8 ml/year ; 95 % CI − 3.9 , 0.3 ; p = 0.092 ; F = 2.888 -RRB- and women having more white matter decrease -LRB- − 0.9 ml/year ; 95 % CI − 1.9 , 0.1 ; p = 0.079 ; F = 3.134 -RRB- with age -LRB- other volumes p > 0.26 -RRB- . Discussion Our MR image-based segmentation paradigm showed that type 2 diabetes was significantly associated with smaller grey matter volumes and larger lateral ventricle and WML volumes , whereas white matter volume was not affected . A smaller grey matter volume suggests cortical atrophy , whereas a larger lateral ventricle volume may indicate subcortical atrophy . Separate analysis for men and women showed significantly smaller grey matter and total brain volumes and significantly larger lateral ventricle , CSF and total CSF volumes in female but not in male diabetic patients . The apparent differential effects of diabetes on brain volumes in men and women were an unexpected finding . Previous studies on cognitive functioning or dementia in patients with diabetes have provided no clear indications that the effects of diabetes on the brain might be sex-specific -LSB- 24 -RSB- , although it should be noted that the role of sex has not yet been studied systematically . In the general population , intracranial volume and relative and absolute grey matter and white matter volumes are known to differ between men and women -LSB- 25 -RSB- . Sex also influences the effects of ageing -LSB- 26 -- 28 -RSB- , men being more severely affected by age-related grey matter decrease than women -LSB- 29 , 30 -RSB- , which was also found in this study . WML volumes among male and female controls were similar , but in female type 2 diabetes patients we found significantly larger WML volumes than in male type 2 diabetes patients . In conditions other than diabetes , more severe WMLs in women than in men have been reported -LSB- 15 , 31 -- 33 -RSB- , but similar WML severity in both sexes has also been reported -LSB- 19 -RSB- . Diabetic women had non-significantly smaller age-adjusted total intracranial volumes than control women . However , the expected effects of these intracranial volume differences on brain tissue volumes were smaller than the observed differences in effects on grey matter , CSF and lateral ventricle volumes . Age is a very important predictor of brain tissue and WML volumes and age effects may have confounded the effects of type 2 diabetes in men and women in this study . Hence , the implications of the effect of sex observed in the present study remain to be determined . No statistically significant associations between MR image measures and hypertension or mean arterial pressure within the group of type 2 diabetes patients were found . Similar results were obtained with manual measurements of atrophy and with WML grading in the same study population -LSB- 2 -RSB- , and in a study that assessed the relation between type 2 diabetes , blood pressure and temporal lobe atrophy -LSB- 5 -RSB- . In contrast , another study reported that hypertension was an important determinant of cortical atrophy in patients with type 2 diabetes -LSB- 4 -RSB- . We found an association between glycosylated haemoglobin and a slight increase in grey matter volume in type 2 diabetes patients . This counterintuitive finding may be due to chance . Other studies in subjects without diabetes have linked increased glycosylated haemoglobin with cerebral atrophy -LSB- 34 -RSB- and WMLs -LSB- 35 -RSB- . Cognitive impairment was associated with smaller total brain volume and larger WML volumes in type 2 diabetes patients . This is in line with observations from another recent study that reported an association between WMLs and subcortical brain atrophy and cognitive performance , in particular the speed of information processing -LSB- 36 -RSB- . This suggests that atrophy as well as WMLs have a negative impact on cognition . Previous studies that analysed WML volume or progression in type 2 diabetes patients have reported inconsistent results -LSB- 4 , 5 , 7 -- 18 -RSB- . Several methodological factors may have contributed to these inconsistencies . First , techniques to measure WML severity have varied widely , from noting lesion presence or absence -LSB- 12 -RSB- to volumetric measurements -LSB- 13 , 18 -RSB- . The majority of studies applied semiquantitative ordinal grading scales . It has been shown that these scales can give variable results -LSB- 37 -RSB- and some scales are relatively insensitive to mild to moderate WMLs . Second , the examined populations and the study design varied considerably -LSB- 38 -RSB- . Only a small proportion of the studies had a true population-based setting , whereas the majority of studies were hospital-based , involving cohorts of patients with stroke , hypertension or other forms of cardiovascular disease . Furthermore , several studies involved fewer than 20 type 2 diabetes patients -LSB- 8 , 11 -- 13 , 18 -RSB- . These small sample sizes may have reduced statistical power . The present study used volumetric measurements in a large population-based sample . The combination of increased atrophy and increased WML volume indicates that type 2 diabetes is associated with mixed pathology in the brain . The association with vascular lesions , such as WML , is not surprising because diabetes is a well-known risk factor for cerebrovascular disease -LSB- 39 -RSB- . Indeed , previous imaging studies -LSB- 38 -RSB- , as well as autopsy studies -LSB- 40 -RSB- , have reported an increased occurrence of vascular lesions , in particular infarcts , in diabetic patients relative to controls . The mechanisms underlying accelerated brain atrophy in diabetic patients are less clear . Several processes related to glucose toxicity , abnormalities in cerebral insulin homeostasis , and microvascular abnormalities have been implicated -LSB- 41 -RSB- , but their exact contributions to abnormalities in cerebral function and structure in diabetes still need to be elucidated . A limitation of our quantitative automated volumetric segmentation algorithm is slight overestimation of the CSF and slight underestimation of the lateral ventricle volume in subjects with markedly enlarged occipital horns . Some misclassification of interhemispheric CSF as lateral ventricle might also occur . However , the misclassified volumes are small compared with ventricle -LRB- about 2 % and 6 % -RRB- and CSF -LRB- about 0.3 % and 0.4 % -RRB- volumes and total CSF volumes are not affected . The artefacts were proportionally distributed across men and women and between type 2 diabetes patients and controls . Therefore , it is unlikely that these inaccuracies affected the analyses . Furthermore , all segmentations were inspected visually , so results will not have been affected by other segmentation errors . Our algorithm did not classify WMLs into deep and periventricular lesions . Such automated subclassification may provide valuable information ; however , it is hard to achieve . WMLs tend to extend smoothly from the ventricular wall -LSB- 42 -RSB- and periventricular WMLs are often connected to deep WMLs on MR images . Therefore , defining meaningful boundary criteria that can be consistently and reproducibly applied automatically is difficult . Other published methods have used T1 and T2 -LSB- 25 -RSB- , PD and T2 -LSB- 26 -RSB- , T1 only -LSB- 27 -RSB- , or T1 , PD and T2 -LSB- 30 -RSB- MR images for segmentation . However , in a previous study it was shown that the use of IR and FLAIR images is highly preferable in brain tissue segmentation and that optimal performance of the automated KNN classification algorithm is achieved with this combination of images -LSB- 20 -RSB- . Furthermore , the learning data were segmented manually on the basis of IR and FLAIR images with the T1 , T2 and PD images available to the expert for reference . Thus , our KNN classifier retrieves its learning data from expert segmentations based on all available information and segments using the optimal image combination for tissue classification . Our automated segmentation method offers major advantages over manual methods by enabling precise , objective and reproducible volumetric measurements of cerebral tissues in large numbers of patients . In future studies , this method might be used to quantify the progression of abnormalities on MR images in patients with type 2 diabetes , as well as in patients with other conditions . Such studies using quantitative MR data should focus not only on the differences between groups of patients and controls , but also on differences within a patient group to identify determinants of structural brain changes . Electronic supplementary material Below is the link to the electronic supplementary material .

O O O B O B I I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O

brain
diabetes mellitus type 2
white matter lesion

image analysis
computer-assisted
leukoaraiosis
magnetic resonance imaging


Problem behavior in a community sample of 14 - and 19-month-old children Few studies have examined the presence , structure , and stability of behavior problems in a community sample of 14 - and 19-month-old infants . A questionnaire with items on emotional , attentional , and impulsive behavior and social communication was completed by the parents of 6,491 infants aged 14 months and 1,803 infants aged 19 months . Particularly externalizing behavior problems were reported to present sometimes or often for 50 % of more of the sample and could be considered as common . In contrast , social communication problems were reported to be present in less than 10 % of the sample . Overall , boys showed more problem behaviors than girls . Principal component analysis at the 14 months data revealed seven factors , which could all be replicated in the 19 months data . Pearson correlations between scores at 14 months and 19 months were highest for oppositional and attention factors -LRB- 0.68 and 0.63 -RRB- and lowest for the inhibiton factor -LRB- 0.38 -RRB- . More than 50 % of those scoring in the top 10 % for total problem score at 14 months were in the top 10 % at 19 months . These results will facilitate the recognition of psychopathology at very early age and the study of its development over time . Introduction Psychopathological research has only recently started to focus on the expression of problematic development at a very young age , i.e. , younger than 18 months , and few data are available on the expression of problem behavior in somewhat older children between 1 - and 3-year-old -LSB- 5 , 9 , 23 -RSB- . Indeed , the lack of normative data for normal and deviant development in children younger than 18 months may lead to inadequate early recognition of serious behavior problems -LSB- 8 , 33 , 34 -RSB- . The differentiation of normal behavior from problem behavior is particularly challenging in young children -LSB- 19 -RSB- . Many symptoms of psychiatric disorders in childhood and adolescence are considered to be relatively normal in preschool-age children . For example , during the preschool years , aggressive , hyperactive , and non-compliance behaviors and separation problems are relatively common and can be viewed as relatively normal within a developmental perspective -LSB- 6 -RSB- . Still , these behaviors can be quite stressing for parents and are generally referred to as problem behaviors . Children younger than 18 months are learning to control themselves , to become attached to people and objects , and to explore , and are only beginning to form stable behavior patterns . Earlier studies reported that problem behavior affected between 7.3 % and 24 % of 2 - and 3-year-old children -LSB- 5 , 12 , 14 , 18 , 20 , 22 , 24 , 26 , 27 , 31 , 32 -RSB- , but there are few data for children younger than this age . One developmental screening study reported that about 10 % of infants had emotional and behavioral problems in the first year of life -LSB- 15 -RSB- , and another study reported that about 6 % of the 1-year-old children had high scores on the Difficult Child domain of the Parenting Stress Index -LSB- 5 -RSB- . An important reason to study behavior at a young age is that it may predict problem behavior at a later age . For example , indices of temperament at 3 years were found to predict the presence and the type of psychiatric disorder in young adulthood -LSB- 10 -RSB- , and behavior problems at 2 years , such as aggression , non-compliance , and difficult temperament , were valuable predictors of lasting problems at a later stage of development -LSB- 17 -RSB- . Approximately 50 % of the 2 - and 3-year-old children with externalizing psychiatric disorders continued to have these problems later in life -LSB- 6 , 21 -RSB- . Such problems appear to be stable from an age of 18 months onward -LSB- 23 -RSB- , but to our knowledge stability has not been evaluated in younger children . More knowledge on the expression and stability of problem behaviors before the age of 18 months would be advantageous , especially for doctors and nurses working in well baby clinics . In the Netherlands , infants visit well baby clinics according to a fixed scheme . At 14 months there is a relatively extensive check up . Since this is a moment for vaccination the attendance rate for this check up is high . Therefore , more knowledge on problem behaviors at especially 14-month-old was desirable . The current study was designed to investigate behaviors at this young age and had the following aims . The first aim was to examine the occurrence of problem behaviors or lack of competences at younger age that are considered to be psychopathological in later childhood . A second aim was to examine whether the constructs of problem behaviors and competences usually found in older children are already present at 14 and 19 months of age . A third aim was to examine the short-term stability of parent-reported problem behavior and lack of competences between age 14 and 19 months . To achieve these aims , we used a questionnaire with 55 items on mainly externalizing and social communication behaviors . Method Sampling The sample was a total population birth cohort of children born between August 2000 and August 2001 -LRB- N = 12,297 -RRB- in the province of Utrecht in the Netherlands . The province has a population of about 1.117.997 and includes rural and highly urbanized areas . Parents of 14-month-old children received a request from the provincial inoculation center to complete our questionnaire concerning infant problem behavior . This request was accompanied by an information brochure that explained the purpose of this study -LRB- at time t1 -RRB- . Parents of 6,491 infants -LRB- i.e. , 53 % of the 12,297 infants eligible -RRB- returned the questionnaire and consented to participate . About equal numbers of boys and girls participated . Unfortunately , we were not allowed access to information on non-responders , and so we investigated potential selection bias by comparing the data of responders to demographic data for the province of Utrecht -LSB- 25 -RSB- . Responders lived somewhat less often in urban areas -LRB- responders 46.6 % , province of Utrecht 48.1 % -RRB- and had a higher educational level , which was defined as parents with at least a high school or college degree -LRB- responders sample : mothers 43.4 % ; fathers 44.2 % ; province of Utrecht : mothers 38.9 % ; and fathers 36.0 % -RRB- . Chi-square test for differences confirmed significant differences with respect to urbanization grade -LRB- χ2 = 86.437 , df 4 , P < 0.000 -RRB- and educational level of the mother -LRB- χ2 = 328.56 , df 2 , P < 0.000 -RRB- and of the father -LRB- χ2 = 313.18 , df 2 , P < 0.000 -RRB- . Further , our sample contained significantly fewer children -LRB- responder sample : 5.3 % , province of Utrecht : 17.94 % -RRB- of non-Dutch descent -LRB- χ2 = 695.785 , df 5 , P < 0.000 -RRB- . To parents of children born in June , July , and August 2001 -LRB- N = 4,051 -RRB- who had also received the questionnaire at 14 months and had returned the questionnaire the first time , the questionnaire was sent again -LRB- at time t2 -RRB- when the children were 19 months of age . This time 1,803 subjects -LRB- 44 % , 919 boys , 889 girls -RRB- participated . There were no significant differences in demographic characteristics between the 19-month-old group and the 14-month-old group . For further analyses of the 14 - and 19-month-old data , we used the 14-month-old data -LRB- N = 6,491 -RRB- , and the 19-month-old sample -LRB- N = 1,803 -RRB- , respectively . When both samples were compared we used the combined sample -LRB- N = 1,803 -RRB- . Description of participants Approximately 88 % of the parents were Dutch , 1.3 % were Turkish , 1.8 % were Moroccan , 1.3 % were from the Caribbean -LRB- Surinam or the Dutch Antilles -RRB- , 0.4 % were from other Western countries , and 0.5 % were of non-Western origin . Questionnaires were completed by mothers -LRB- 80.5 % -RRB- , fathers -LRB- 10.7 % -RRB- , and by both -LRB- 0.6 % -RRB- . Mean child age was 14.80 months -LRB- SD = 1.84 -RRB- . The mean number of children in the family was 1.80 -LRB- SD = 1.03 -RRB- . Mean birth weight was 3,537.5 g -LRB- SD = 823.9 -RRB- . Of all infants , 1 % had a physical or mental disability , 4.1 % had a physical disease , and 6.3 % used medication . Parental education level varied : 43.8 % had a high level of education , 38.1 % had a medium level of education , and 15.5 % had a low level of education . Measures Behavior problem questionnaire We used a combination of 55 items on a 3-point Likert scale -LRB- 0 `` never , '' 1 `` sometimes , '' 2 `` often '' -RRB- focusing primarily on externalizing behavior , social communication problems , and internalizing items . In selecting items , we first composed a large pool of potentially interesting items concerning children younger than 18 months by reviewing instruments for older children , namely The Infant-Toddler Social and Emotional Assessment ; The Child Behavior Checklist for 1.5 -- 5 ; and the Vineland Social-Emotional Early Childhood Scales -LSB- 1 , 7 , 29 , 30 -RSB- and based on our clinical experience with very young children . Then a multidisciplinary panel of experts with clinical and research experience with infants and toddlers made a final selection of items based on two criteria , namely , the item had to be specific for externalizing , social communication or internalizing problem behaviors and to be usable for infants younger than 18 months . The final selection included items that covered attentional problems , hyperactivity , oppositional behavior , aggressive behavior , verbal and non-verbal aspects of social communication -LRB- such as initiating and responding -RRB- and internalizing behaviors such as problems with eating or sleeping . Data analyses Items were recoded in such way that a score of two represented the complete presence of an unwanted behavior or the complete absence of a wanted behavior . Common and uncommon problems were identified using the approach of Koot and Verhulst -LSB- 18 -RSB- . Common problems were defined as all items that scored 1 -LRB- present sometimes -RRB- or 2 -LRB- present often -RRB- for 50 % or more of the sample . Uncommon problems were defined as all items that scored 1 or 2 for less than 10 % of the sample . The structure of problem behavior was examined by entering all items in a principal component analysis -LRB- PCA -RRB- with varimax rotation . The number of factors was based on the scree test -LSB- 13 -RSB- . Items with a minimum factor loading of ≥ 0.30 were included -LSB- 2 , 4 -RSB- . To validate the findings , PCA was performed on two split half samples Pearson correlations were calculated to examine the interrelationship between the factor sumscores . Finally , in order to examine possible two higher-order factors , PCA was performed requiring all items to load on two factors and Pearson correlations were calculated to examine their interrelationship . Stability was examined parametrically by calculating Pearson correlations between scores at 14 and 19 months . Further , stability was examined non-parametrically by examining how many children with high scores -LRB- above the 75th or 90th percentile -RRB- on Total Problem scores and single factor scores at 14 months still had high scores at 19 months . ANOVA was performed to assess the effect of sex on the scores of each problem item and for the factor sum scores . Cohen 's d value is reported as an index of effect size -LRB- small , d = 0.2 ; medium , d = 0.5 ; or large , d > 0.8 -RRB- -LSB- 11 -RSB- . All analyses were two-tailed and a 0.05 level of significance was used . These analyses were performed using the Statistical Package for Social Sciences -LRB- SPSS for Windows , version 11.5 -RRB- . Results Frequencies Common and uncommon problem behaviors and their frequency of occurrence are shown in Table 1 . Almost all common problem behaviors were externalizing items , whereas uncommon problems were social communication and internalizing items . Seven of 13 common behavior problems and two of eight uncommon behavior problems were more common among boys than among girls . Table 1Common and uncommon problem behavior at 14 months % With score 1 -LRB- sometimes -RRB- % With score 2 -LRB- often -RRB- % With score 1 or 2Common problem behavior Quickly shifts from one thing to othera61 .926.087.9 Angry moodsa63 .59.673.1 Demands must be met56 .814.170.9 Ca n't stand waiting , wants everything now51 .116.267.3 Uses toys for fantasy playa35 .229.865.0 Wants a lot of attention50 .314.464.7 Accident prone56 .46.462.8 Stays close to parent54 .04.558.5 Easily upset46 .37.553.8 Does n't sit still during storya39 .414.053.4 Wo n't share toys or other thingsa46 .15.952.0 Does n't keep trying46 .75.151.8 Ca n't sit still , restless , hyperactivea40 .011.051.0 Uncommon problem behavior Fails to follow with eyes8 .01.49.4 Does n't show interest in new objects7 .10.67.7 Does n't make happy noises6 .70.87.5 Does n't make noises spontaneously5 .81.16.9 Has less fun than others4 .51.56.0 Does n't react at calling namea5 .30.65.9 Seems unhappy without good reason4 .90.75.6 Does n't imitate simple gesturesa4 .30.95.2 Note : Common is defined as > 50 % with score 1 or 2 . Uncommon is defined as < 10 % with score 1 or 2 . Please note further that items covering lack of competences were recoded in such way that a score of 2 represented the complete presence of an unwanted behavior or the complete absence of a wanted behavior . This explains why all items have the same-sign factor loadingsa Significantly more boys -LRB- P < 0.001 -RRB- Factor structure of problem behavior The principal component analysis with varimax rotation with eigenvalues > 1.5 for two equally sized split half samples resulted in two very similar solutions . The scree test suggested a seven-factor PCA solution -LRB- eigenvalue > 1.5 -RRB- with a percentage explained variance of 34.6 % -LRB- see Appendix to this paper for details -RRB- . The PCA for the 19-month-old children showed the same factors as the analysis at 14 months , with 37.7 % of explained variance . Five of the 55 items had higher loadings at 19 months on other factors than at 14 months . Pearson correlations between the factor scores -LRB- Table 2a -RRB- suggested a higher-order division into two problem domains , one reflecting total problem behaviors and one reflecting competences . Oppositional problem behavior at 14 months of age was mostly related to the factors Attention , Inhibition , and Dysregulation , with r values varying between 0.37 and 0.52 and the factor Language Development was mostly related to the factors Explorative Behavior and Communicative Intent -LRB- r values of 0.41 and 0.42 , respectively -RRB- . Indeed , principal component analysis confirmed the underlying structure of the higher-order factors when all items were forced to load on two factors and were named Total Problem Behavior -LRB- eigenvalue 6.9 , explained variance 11.5 % -RRB- and Competences -LRB- eigenvalue 4.5 , explained variance 7.5 % -RRB- . Pearson correlation of these higher order constructs revealed a low correlation -LRB- 0.12 -RRB- . Table 2Pearson correlation matrix of factor sumscores of -LRB- a -RRB- 14-month-old and -LRB- b -RRB- 14 - and 19-month-oldQuestionnaire domainsOppositional behaviorLanguage developmentAttentionExplorative behaviorCommunicative intentDysregulationInhibition14 monthsaOppositional behavior1Language development − 0.0011 Attention0 .522 ** 0.106 ** 1Explorative behavior0 .0050.412 ** 0.167 ** 1Communicative intent0 .102 ** 0.422 ** 0.142 ** 0.351 ** 1Dysregulation0 .436 ** 0.0220.3150.060 ** 0.124 ** 1Inhibition0 .379 ** 0.098 ** 0.235 ** 0.076 ** 0.308 ** 0.308 ** 114 months19 monthsbOppositional behavior0 .678 Language development0 .0290.476 ** Attention0 .498 ** 0.112 ** 0.625 ** Explorative behavior0 .0890.264 ** 0.188 ** 0.452 ** Communicative intent0 .057 ** 0.255 ** 0.131 ** 0.206 ** 0.466 ** Dysregulation0 .353 ** 0.069 ** 0.300 ** 0.080 ** 0.127 ** 0.445 ** Inhibition0 .306 ** 0.100 ** 0.247 ** 0.086 ** 0.120 ** 0.226 ** 0.380 Note . * Correlation is significant at the 0.05 level -LRB- 2-tailed -RRB- ** Correlation is significant at the 0.01 level -LRB- 2-tailed -RRB- A significant sex difference -LRB- boys had higher scores than girls -RRB- was found on several factors , namely Oppositional Behavior -LRB- F = 15.20 , df 1 , P < 0.000 -RRB- , Language Development -LRB- F = 108.88 , df 1 , P < 0.000 -RRB- , Attention -LRB- F = 22.56 , df 1 , P < 0.000 -RRB- , Explorative Behavior -LRB- F = 18.05 , df 1 , P < 0.000 -RRB- , and Communicative Intent -LRB- F = 15.76 , df 1 , P < 0.000 -RRB- . The effect sizes were small -LRB- Oppositional Behavior , d = 0.09 ; Language Development , d = 0.26 ; Attention , d = 0.11 ; Communicative Intent , d = 0.10 -RRB- . No significant sex differences were found for Dysregulation and Inhibition . At 19 months , the same sex differences were found , except for Communicative Intent . Stability over 5 months Pearson correlations between the factor sum scores at 14 and 19 months varied between 0.38 and 0.68 , with the highest correlation being found for the Oppositional -LRB- 0.68 -RRB- and the Attention factors -LRB- 0.63 -RRB- and the lowest for the Inhibition factor -LRB- 0.38 -RRB- . This indicates moderate stability of the constructs of problem behavior over the 5-month period -LRB- See Table 2b -RRB- . The most stable problems were problems of Communicative Intent , Oppositional Behavior , and Attention -LRB- see Table 3 -RRB- . At least half of the group with scores at or above the 75th percentile range at 14-month-old had high scores on problem behaviors at 19 months . With regard to the Total Problem sum scores , 75.5 % of the group with scores at and above the 90th percentile of the Total Problem score at 14 months still had problem behaviors at 19 months within the75th percentile range . Also , 53.1 % of the children at or above the 90th percentile still had high scores within the highest range 5 months later . On the other hand , about 88.1 % of the children with scores below the 75th percentile at 14 months remained below the 75th percentile at 19 months . However , 3.4 % of the infants with the least problems on the Total Problem score at 14 months scored at or above the 90th percentile at 19 months -LRB- see Fig. 1 -RRB- . Table 3Mean factor scores at t1 -LRB- 14 months -RRB- and t2 -LRB- 19 months -RRB- and percentage of children with scores above 90th and 75th percentile on both 14 months t1 and 19 months t2 -LRB- N = 1,803 -RRB- Behavioral dimensionMean factor scores at t1 and t2 % Of children scoring > 90th percentile at both t1 and t2 % Of children scoring > 75th percentile at both t1 and t2Oppositional behavior0 .370.4244.860.3 Language development0 .470.4431.355.8 Explorative behavior0 .420.4434.250.3 Attention0 .420.4245.056.7 Inhibition0 .640.6529.043.7 Communicative intent0 .500.9246.851.3 Dysregulation0 .730.3527.551.1 Note . The columns represent the percentage , of those children scoring more than 90th/75th percentile at t1 , who were also above 90th/75th percentile at t2Fig . 1Transitions -LRB- expressed as percentages of children -RRB- between 14 months and 19 months for the 90th and 75th percentile cutoff of the total problem behavior score Discussion Recently , more interest has been paid to the manifestation of early problem behavior in infants and toddlers . As expected , we found externalizing behaviors to be among the most common problem behaviors in 14-month-old infants . Indeed , more than 70 % of the parents reported that their children often or very often showed behavioral items such as `` quickly shifts activities , '' `` angry moods , '' and `` demands must be met immediately . '' These rates are fairly comparable with the prevalence rates reported earlier for somewhat older children -LSB- 18 -RSB- . Although these and other common oppositional behaviors are symptoms of DSM-IV axis-I disorders such as Attention Deficit Hyperactivity Disorder , Oppositional Defiant Disorder , and Conduct Disorder at older ages , these high scores for 14-month-old infants are not necessarily psychopathological -LSB- 6 , 18 -RSB- . Instead , the high occurrence of parent-reported problem behaviors at this early age can best be interpreted as `` relatively normal '' -LSB- 18 , 23 -RSB- . While the symptoms and frequency of externalizing problem behaviors change with age , it is of interest to categorize these changes by their severity and to study their developmental trajectories in order to classify expected abnormal outcomes -LSB- 3 -RSB- . Further work should therefore focus on longitudinal studies to decide where the cut-off point is and then start to index a risk for psychopathology . Lack of competences in social communication and internalizing problem behaviors were relatively rare , occurring in about 5 -- 9 % of the community sample . These results confirm that internalizing symptoms with possible underlying constructs of withdrawal and depression are less prevalent at this early age -LSB- 4 -RSB- . This is not to say that these behaviors are unimportant or should be neglected . For example , other social communication items such as `` failure to follow with the eyes , '' `` does not react to calling name , '' and `` does not imitate simple gestures '' may indicate the presence of more serious psychopathology , such as autistic spectrum disorder . It would be interesting to determine whether the risk of later psychopathology is significantly higher for a combination of problem behaviors and for which combination this accounts . Also , the frequency or severity of these social communication problems is associated with a serious risk of problems later in development . Principal component analysis of the data for the 14-month-old children indicated that seven factors could identify important behavioral dimensions . The observation that PCA revealed the same factor solutions for the original as well as for both split half samples is strong evidence for the presence of these distinct behavioral dimensions at 14 months . While the CBCL 1.5 -- 5 -LSB- 1 -RSB- can detect externalizing problem behavior in 18-month-old children , our study indicates that these behaviors are present at an even younger age , 14 months . The two behavioral dimensions with the highest explained variance were dimensions describing problems in oppositional behaviors and language development . The dimension Language Development was correlated with the behavioral dimension Communicative Intent , which covers items of more nonverbal-related behaviors , and with Explorative Behavior . Ever since the work of Piaget , explorative behavior has been considered crucial for cognitive development . Explorative behavior is also an important construct in the field of attachment theory , where the infant is thought to use the attachment figure as a secure base for exploring its environment . Interestingly , the finding of a separate attentional factor refers to the emergence of attentional systems of higher-level control at 12 -- 36 months , which contribute to the development of more goal-oriented behaviors and the ability to inhibit actions -LSB- 28 -RSB- . The behavioral dimension termed Inhibition consisted of items consistent with the construct of passive inhibition , namely items focusing on inhibition to novelty , separation distress , and affect-relating internalizing behaviors -LSB- 16 -RSB- . Eating and sleeping problems as well as more anxiety-related problem behavior formed a Dysregulation dimension , as found in other studies -LSB- 4 -RSB- . Our findings suggest that even at this young age the structures that underlie behavior problems are becoming clearer . These behavioral dimensions are in line with dimensions described in other questionnaires . For example , our Oppositional Behavior dimension includes many items found in the Aggressive behavior factor of the CBCL 1.5 -- 5 -LSB- 1 -RSB- . Items of the Communication scale of the Vineland are found in our dimension Language Development and Communicative Intent in our analysis . The latter dimension also includes some items of the Socialization scale of the Vineland -LSB- 29 , 30 -RSB- . Next , our dimension measuring Attention consists of items from Attention dimensions of other scales -LRB- the Attention Problems of the CBCL 1.5 -- 5 and the Attention scale of the ITSEA -RRB- -LSB- 7 -RSB- . Also , our dimension Explorative behavior is partly in line with ITSEA 's Mastery motivation and partly with the Socialization scale of the Vineland . Furthermore , our dimension Dysregulation consists mainly of items of the Internalizing dimension of the CBCL 1.5 -- 5 . Finally , most of the items seen in our dimension Inhibition are found in the Other Problem dimension of the CBCL 1.5 -- 5 and some are from the Internalizing and Competence domain of the ITSEA . Inspection of the factorsumscores correlation matrix suggested two higher-order dimensions , one consisting of problems behaviors -LRB- Oppositional behavior , Attention , Dysregulation , and Inhibition -RRB- and a second one covering competences -LRB- Language Development , Explorative Behavior , and Communicative Intent -RRB- . This higher order division was confirmed in a factor analysis forcing a two-factor solution . The two higher-order factors Total Problem Behavior and Competences correlated only very weakly with each other -LRB- 0.12 -RRB- , suggesting a fairly amount of independence . Apparently a relative high level of problem behaviors is not necessarily accompanied by a relative low level of competences and vice versa . This finding is in accordance with studies using the ITSEA in older children . In these studies too , competences emerged as a separate factor from factors on problem behaviors -LSB- 4 , 5 , 9 -RSB- . For the clinical practice our result indicates that even at a very young age , a thorough evaluation of a child 's functioning should include both an investigation of problem behaviors and an evaluation of competences . With regard to sex differences , boys were reported to have significantly more problem behaviors than girls on all factors , except for dysregulation and inhibition , consistent with the finding that boys show more externalizing behaviors -LSB- 18 -RSB- . We found no sex differences in dysregulation and inhibition , whereas other studies report girls to be more fearful and to have more sleeping problems than boys -LSB- 14 , 27 -RSB- . Boys were reported to have more problems in social communication behaviors , which suggests that boys acquire these competencies later than girls . This could play a role in the emergence of problem behavior among boys , whereas the early acquisition of competencies could be a protective factor for girls -LSB- 4 -RSB- . Contradictory reports on the presence of sex differences in problem behaviors may also be due to cultural or social factors , such as social role expectancy issues , and these may well complicate the interpretation of results . Problems of communicative intent , oppositional problems , and attentional problems had the highest correlations and remained moderately stable over the 5-month period between 14 and 19 months of age . The least stable were inhibition and dysregulation problems , perhaps reflecting a more temporary nature of these behaviors , as reported earlier by Briggs-Gowan and Carter -LSB- 4 -RSB- . At least 53 % of the infants with scores within the 90th percentile of each factor sum score at 14 months still exhibited these problem behaviors at 19 months of age . These results are in accordance with other studies that have also shown substantial stability in problem behavior -LSB- 21 , 23 -RSB- . These studies investigated children older than 19 months of age , whereas our results suggest that these problem behaviors are already moderately stable at an even younger age , emphasizing the need for early assessment . We can only speculate on the determinants of this stability , such as the child 's temperament , family environment , or parental variables . It would be interesting to investigate these determinants in relation to the frequency , severity , and pervasiveness of behavior problems over a longer period of time , for example , at 14 , 19 , and 36 months of age , in order to gather information on how problem behavior evolves . Limitations One should note that we did not aim to present a new instrument to measure problem behaviors at this young age . Instead , we wanted to report on common and uncommon problem behaviors in this young age group . Although the study population was large and community based , it was not fully representative of the general population . Our sample contained more parents with a higher socioeconomic status than expected compared to the general population . Thus scores for problem behaviors might have been higher in the non-responder group . A second limitation is that we only used parent reports . Information from other sources can be of additional value to evaluate the level of problem behavior -LSB- 8 , 18 -RSB- . Future work should include measures of impairment of functioning and should focus on more in-depth assessments of psychopathology and level of cognitive development . Finally , it may be informative to compare a population-based sample with a clinically referred group . Clinical implications This study underlines the growing need to identify problem behavior in early development . A better understanding of what is normal and abnormal in early infant-toddler development is of great value for the recognition of early psychopathology . Normative data for the prevalence and stability of behavior problems of 1 - and 2-year-old children in a normal population may make it possible to provide early effective preventive intervention programs , in addition to background information for clinicians and researchers in order to develop such programs . In summary , externalizing behaviors were the most common , and social communication the least common , problems reported in a population sample of 14-month-old children . Boys were reported to show significantly more problems of externalizing behavior and competences . These behaviors were moderately stable over a 5-month period , between the ages of 14 and 19 months .

B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O