Abnormal brain connectivity in first-episode psychosis: A diffusion MRI tractography study of the corpus callosum

A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the clinical manifestations of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail and we present here a study of patients with first-episode psychosis using this technique. We selected the corpus callosum for this study because there is evidence that it is abnormal in schizophrenia. In addition, the topographical organization of its fibers makes it possible to relate focal abnormalities to specific cortical regions. Eighteen patients with first-episode psychosis and 21 healthy subjects took part in the study. A probabilistic tractography algorithm (PICo) was used to study fractional anisotropy (FA). Seed regions were placed in the genu and splenium to track fiber tracts traversing these regions, and a multi-threshold approach to study the probability of connection was used. Multiple linear regressions were used to explore group differences. FA, a measure of tract coherence, was reduced in tracts crossing the genu, and to a lesser degree the splenium, in patients compared with controls. FA was also lower in the genu in females across both groups, but there was no gender-by-group interaction. The FA reduction in patients may be due to aberrant myelination or axonal abnormalities, but the similar tract volumes in the two groups suggest that severe axonal loss is unlikely at this stage of the illness.
Introduction
Altered connectivity is likely to account for the symptoms and cognitive changes of schizophrenia (Friston and Frith, 1995). A disconnectivity model involving both loss of specialized cortical function and damage to connecting pathways is likely to apply to schizophrenia (Catani and ffytche, 2005). Imaging studies have repeatedly confirmed the presence of cortical abnormalities, especially in prefrontal and temporal heteromodal cortex (Shenton et al., 2001; Bagary et al., 2003; Foong et al., 2001), and synaptic pathology leading to aberrant cortical circuitry has been well documented in neuropathological studies (Harrison and Weinberger, 2005). By comparison, the study of abnormalities in intra- and interhemispheric pathways has received much less attention, although the occurrence of schizophrenia-like symptoms has been documented in diseases involving the white matter (Walterfang et al., 2006).
Among these connecting pathways the corpus callosum is of special interest in schizophrenia. The corpus callosum develops into the third decade of life (Pujol et al., 1993) and the topographical organization of its fibers makes it possible to relate its abnormalities to specific cortical regions. Fibers of small diameter from heteromodal cortex traverse the genu (connecting prefrontal cortex) or the splenium (connecting superior temporal cortex), and larger diameter fibers connecting unimodal motor and sensory cortex traverse the body. A model by Crow (1998), based on the evolutionary aspects of language and the emergence of psychosis in man, postulated that abnormalities in callosal pathways connecting areas of the cortex asymmetrically distributed between the two hemispheres were central to schizophrenia. Since then, conventional MRI studies (Shenton et al., 2001), including those in drug-naive patients with their first episode of schizophrenia (Keshavan et al., 2002), have reported reduction in the size of the corpus callosum, more marked anteriorly, but shape differences in the rostral and mid area of the body containing motor and sensory fibers have also been reported (Goghari et al., 2005). Similar findings have been reported by Bachmann et al. (2003) in a first-episode cohort that included patients with schizophreniform and schizoaffective psychoses. In addition, a longitudinal study of patients with childhood-onset schizophrenia (Keller et al., 2003) has suggested that a failure of normal callosal growth may result in area reductions, particularly in the splenium, by early adulthood. Other imaging studies using voxel-based analysis (Hulshoff Pol et al., 2004) or magnetization transfer imaging (Foong et al., 2001) have also reported abnormalities, predominantly in the genu. In addition Highley et al. (1999a), in a detailed neuropathological study, reported a decrease in axon density in all, but the rostral region of the corpus callosum in female schizophrenics compared to controls. The functional significance of the corpus callosum in schizophrenia has been well documented by studies of interhemispheric transfer of information (Innocenti et al., 2003).
Diffusion tensor imaging (DTI) (Basser et al., 1994) has made it possible to study in vivo the integrity and orientation of neural tissue by measuring water diffusion in the brain. DTI studies have used a region-of-interest (ROI) methodology and have measured the apparent diffusion coefficient (ADC) and/or fractional anisotropy (FA), indices of white matter integrity. An early study from our group (Foong et al., 2000) reported reduced FA in the splenium of the corpus callosum in patients with chronic schizophrenia and similar findings have been reported by others in the splenium (Agartz et al., 2001), or in the structure as a whole (Brambilla et al., 2005; Ardekani et al., 2003; Kubicki et al., 2005). Kumra et al. (2004), on the other hand, failed to find such abnormalities in a small group of patients with early-onset psychosis and the same was the case in the only available study in first-episode patients, also from our group (Price et al., 2005). The clinical correlations of these corpus callosum abnormalities remain uncertain. Brambilla et al. (2005) reported a correlation between DTI changes in the anterior part of the corpus callosum and severity of positive symptoms, but these findings have not been confirmed in other studies.
The information about the direction of diffusion encoded by the eigenvalues and eigenvectors of the diffusion tensor has been used in DTI tractography (Mori et al., 1999) to investigate the continuity of axonal orientation between voxels and thus to infer the paths of fiber tracts in 3 dimensions. DTI tractography has been used in studies of normal subjects (Toosy et al., 2004; Parker and Alexander, 2005; Parker et al., 2005), in patients with multiple sclerosis (Wilson et al., 2003), callosal dysgenesis (Lee et al., 2004) and stroke (Huang et al., 2005). To date only one study (Kanaan et al., 2006) has used tractography to study the corpus callosum in patients with chronic schizophrenia, reporting reduced FA in the genu and it also demonstrated the superiority of this method, over ROI studies, in detecting subtle abnormalities across the whole of a white matter tract.
Here we present, to our knowledge, the first study of the corpus callosum (or indeed any white matter pathway) in patients with first-episode schizophrenia spectrum disorders using diffusion imaging tractography. The main aim of the study was to determine whether subtle abnormalities of interhemispheric connections could be detected using this new technique in a group of patients during the first-episode of psychosis, in whom chronicity-related factors could be excluded. We hypothesized that measures of tract coherence (FA), in white matter traversing the genu and splenium of the corpus callosum, would be significantly reduced in the patient group compared to controls.
Materials and methods
The patients were recruited as part of a prospective, longitudinal study of first-episode psychosis in West London. Patients were eligible to be recruited into the study if they fulfilled the following criteria; age between 16 and 50 years presenting with a psychotic illness for the first time and less than 12 weeks on antipsychotic medication. Patients eligible for the study were screened using the WHO Psychosis Screen (Jablensky et al., 1992). The diagnosis was established using a structured interview, the diagnostic module of the Diagnostic Interview for Psychosis (DIP, Jablensky et al., 2000), which includes items from the Operational Criteria Checklist for Psychosis (OPCRIT, McGuffin et al., 1991) and the World Health Organization Schedules for Clinical Assessment in Neuropsychiatry (SCAN, Wing et al., 1990). Using these data, a computerized algorithm generates diagnoses under several classification systems including DSM-IIIR and ICD-10. DSM-IIIR diagnoses were subsequently checked against DSM-IV criteria by separately entering OPCRIT items into OPCRIT for Windows (http://sgdp.iop.kcl.ac.uk/opcrit/). Exclusion criteria were the presence of a medical or neurological illness that might impair cognitive function including head injury and alcohol or drug dependency.
Eighteen patients with an initial diagnosis of schizophrenia, schizophreniform or schizoaffective disorder took part in this study. Fifteen of these patients were interviewed again a year later to review the diagnosis, and for the remaining three, who could not be interviewed, a final diagnosis was established also a year later by compiling information from clinicians looking after the patients and by reviewing the clinical notes. Thirteen patients received a final diagnosis of schizophrenia and the remaining five received a diagnosis of schizoaffective disorder (one bipolar, two manic and two depressed subtype). The patients had been ill for a mean of 12.6 months (SD = 19.3 months, range 0–72 months) at entry into the study.
The range and severity of symptoms were assessed at each time point with the Scales for the Assessment of Positive Symptoms (Andreasen, 1983) and Negative Symptoms (Andreasen, 1981), The Young Mania Scale (Young et al., 1978) and the Hamilton Rating Scale for Depression (Hamilton, 1960). The onset of psychosis was established using the Symptom Onset in Schizophrenia inventory (Perkins et al., 2000). Alcohol and drug use was assessed as part of the Diagnostic Interview for Psychosis (see above) and criteria for abuse and dependence were established using the Alcohol Use Scale and the Drug Use Scale (Drake et al., 1990).
The mean age of the patient group was 23.6 years (SD = 6.3; range = 17–38 years), composed of 8 males and 10 females. All patients were receiving antipsychotic medication at the time of scanning. Twenty-one healthy subjects with a mean age of 29.4 years (SD = 7.1; range = 16–42 years) with a gender composition of 6 males and 15 females served as controls. Handedness for all subjects was assessed using the Annett scale (Annett, 1970) as it may be associated with DTI findings in the corpus callosum (Westerhausen et al., 2003). Exclusion criteria were the same as in the patient group as well as history of psychiatric illness in themselves or their first-degree relatives. See Table 1 for a description of study subjects. Permission to conduct the study was obtained from Merton, Sutton and Wandsworth, Riverside and Ealing Research Ethics Committees. All participants gave written informed consent and were paid an honorarium for their time.
MRI data acquisition
MRI for all subjects was obtained using a GE Signa 1.5 T scanner (General Electric, Milwaukee, WI, USA), which underwent regular quality-control checks, using a standard quadrature head coil. Each subject had a dual-echo fast spin echo scan (TR = 2000 ms, TE1/TE2 = 19/95 ms, matrix = 256 × 192, field of view [FoV] = 24 × 18 cm2), which provides both proton density and T2-weighted images. Twenty-eight 5-mm slices were collected, in an oblique-axial plane (parallel to the AC/PC line). An axial plane, IR-SPGR sequence was also performed which obtained a series of 156 contiguous axial slices with the following parameters TE = 5.1 ms, matrix = 256 × 128, field of view = 31 × 16 cm2, slice thickness = 1.2 mm, TR = 14.3 ms, flip angle 20°, TI = 450 ms.
Diffusion-weighted single-shot echo planar images (DW-EPI) were acquired in the axial plane (TE = 96 ms, FoV = 22 × 22 cm2, matrix = 96 × 96, slice thickness = 2.3 mm, Δ = 40 ms, δ = 34 ms, resulting in a maximum b factor of 1000 s/mm2). The acquisition of diffusion-weighted images was gated to the cardiac cycle using a pulse oximeter with a gating scheme optimized for diffusion imaging. Gradients for diffusion sensitization were applied in 54 non-collinear directions. Six images with no diffusion weighting (b ≈ 0 s/mm2) were also collected for each slice, giving a total of 60 images per slice. Images were interpolated to a 128 × 128 matrix during reconstruction, yielding a final in-plane resolution of 1.72 mm.
Diffusion processing and analysis
The diffusion tensor was estimated for each voxel according to the method of Basser et al. (1994) and used to compute FA. We also used a model-selection algorithm based on the fit of spherical harmonic series to the diffusion profile (Alexander et al., 2002) to detect the most parsimonious description of diffusion in every voxel. Diffusion within each voxel was classified as isotropic, anisotropic with a single principal direction of diffusion, or anisotropic with more than one direction of diffusion (as in the white matter of the centrum semiovale). The single tensor model was subsequently used for voxels characterized by isotropic diffusion or a single direction of diffusion population. The two-tensor model of diffusion, as described by Parker and Alexander (2003), was used for the remaining voxels.
We used a probabilistic tractography algorithm (PICo or ‘probabilistic index of connectivity’) which considers multiple pathways emanating from a seed point or region (i.e. a group of voxels in a region of interest) (Parker and Alexander, 2003, 2005). Due to the presence of noise in the data, there is some uncertainty associated with the determination of the principal direction of diffusion. The algorithm accounts for this uncertainty by generating a probability density function (PDF) of fiber alignment from the diffusion model of each voxel (which in this case is either the single or the two-tensor model). This provides voxel-wise estimates of confidence in fiber tract alignment, which are then used in the probabilistic tract-tracing procedure. Using the PDFs from a chosen seed point, streamline-based tracking is performed and repeated 10,000 times in a Monte Carlo fashion (sampling each PDF at random on each repeat) to produce tract maps that estimate the probability of connection of every voxel in the brain to a given seed point or region (Parker and Alexander, 2005). Streamlines were propagated using trilinear interpolation of PDFs, as suggested by Behrens et al. (2003), and were terminated if curvature over the scale of a single voxel exceeded 180° or if the path left the brain.
Seed regions were placed in the genu and splenium of the corpus callosum. The genu was defined as the most anterior point of the corpus callosum before it bends downwards and backwards in front of the septum pellucidum, and the splenium as the posterior end of the corpus callosum at its thickest part. Each seed region consisted of a six voxel rectangular shape on a single axial slice. This region size ensured that partial volume effects were completely avoided. Seed regions were placed by displaying the FA maps in three mutually orthogonal orientations using MRIcro (http://www.sph.sc.edu/comd/rorden/) and identifying the sagittal and coronal planes in which the volumes of the genu and splenium were largest. The seed regions were placed on the axial view corresponding to the intersection of these sagittal and coronal planes.
The seed region placement was the only operator-dependent step in the diffusion processing. To assess the inter-rater reliability of the method, a second, independent rater performed the seed region placement in 8 cases, using the same procedure.
The voxel values of the PICo output maps for the corpus callosum range from 0 (no probability of connection) to 1 (certainty of connection) with an intensity resolution step of 0.001 representing the ratio of the number of times that voxel was reached by a streamline originating from the seed point to the total number of iterations in the Monte Carlo process. Each PICo map was thresholded at five probability values ranging from 0.001 (the lowest recorded value of probability of connection) to 0.03, at logarithmically spaced intervals, to generate five objective binary masks (thresholded at 0.001, 0.002, 0.006, 0.013 and 0.03). This multi-threshold approach, previously used in the study of visual pathways (Toosy et al., 2004), allows with increasing degrees of certainty the reconstruction of the core of the tract, where fiber alignment should be greatest, and the exploration of the probability of connection of distant voxels to the seed point. For each threshold the mean tract volume and the mean FA were calculated for each subject.
The spatial variability of the tract across each subject group was characterized as previously described (Toosy et al., 2004; Parker et al., 2005). Firstly the non-diffusion-weighted (b = 0) images (inherently co-registered with PICo output images) were normalized to a stereotactic space (Montréal Neurological Institute, MNI) using the standard echo planar image template in SPM2 (Wellcome Department of Cognitive Neurology, Institute of Neurology, London, UK) running in MATLAB (MathWorks, MA). The normalization parameters thus obtained were then applied to the binary images of the tract obtained by thresholding the probability images at the level that maximized the difference in FA between patients and controls (see below). After normalization, these images were averaged on a voxel-by-voxel basis, producing a map used to display the degree of tract overlap between subjects within each group.
In order to detect the presence of ventricular enlargement in the patient group, which might affect tractography, we performed a voxel-based comparison of CSF maps between the two groups using SPM2 (Wellcome Department of Cognitive Neurology, Institute of Neurology, London, UK). The IR-SPGR images were segmented and normalized using the iterative procedure described in Good et al. (2001), thus performing first a segmentation in native space, next normalizing gray matter images using the standard a priori gray matter template available in SPM2 and applying the same normalization parameters to the whole volume. The normalized volume was then segmented again yielding white matter, gray matter and CSF probability images. Voxel values in segmented images were multiplied by the Jacobian determinants derived from spatial normalization (modulation) to provide intensity correction for induced regional volumetric changes, thus preserving within-voxel volumes that may have been altered during non-linear normalization (Ashburner and Friston, 2000). CSF images were also smoothed to 6 mm (Full-Width-Half-Maximum) Gaussian filter. Smoothing is required to accommodate anatomical variation between subjects and therefore results in more normally distributed data. Global CSF volumes in cm3 were also obtained by integrating the CSF image signal intensity over the whole volume for each subject.
Statistical analysis
Age, gender and handedness distributions in the two groups were compared using t-tests and χ2 tests.
The inter-rater reproducibility of the method was tested by comparing the tract volumes obtained by the two raters. Inter-rater reliability was assessed using the coefficient of variation (CoV), CoV = (σ / μ) × 100%, where σ is the standard deviation and μ is the mean, with lower values indicating better reproducibility.
Multiple linear regressions of mean FA were carried out to compare tract coherence in patients and controls, with gender, age and tract volume as covariates, to control for between-group differences in these covariates. To avoid spurious positive results due to multiple comparisons, the multiple regressions were carried out simultaneously for each of the five thresholds in the genu and the splenium (ten regressions) using Zellner’s seemingly unrelated regression method (Zellner, 1962), which yields a single significance value (from the F-statistic) of the difference between patients and controls across all ten regressions, in addition to individual values for each regression. The F-statistic is obtained by comparing the ten regressions obtained including or excluding group membership and taking into account the correlations between the residuals from all ten equations. This method also allows a test of whether region (genu or splenium) or probability thresholds modify the differences in FA between patients and controls. Similar multiple linear regressions were performed to explore gender differences in FA (when adjusting for group membership, age and tract volume) as well as age differences in FA (adjusting for group membership, gender and tract volume).
A voxel-based statistical comparison between CSF maps from patients and controls was performed in SPM2 based on the General Linear Model and Gaussian random field theory incorporating subject age and gender into this model.
Results
Patients were significantly younger than controls. The mean age for patients was 23.6 years and 29.4 years for controls (t = − 2.7, df = 37, P = 0.011). However, there was an age overlap between the two groups, allowing the results to be adjusted for age. There were no significant differences in gender distribution (χ2 = 0.62, df = 1, P = 0.43) or handedness (χ2 = 1.81, df = 1, P = 0.18) between the groups. All patients were receiving antipsychotic medication and two were on mood stabilizers at the time of the study (see Table 1). The average duration of treatment prior to scanning was 61 days (range 8–153 days).
The coefficient of variation for the tract volume for the 8 repeated measurements performed by two raters was 1.36%, indicating a very high inter-rater reproducibility.
The tract overlap maps for the genu and splenium in patients and controls (Figs. 1 and 2) were compared with reference maps of the corpus callosum to ascertain their anatomical validity.
The estimated tract volumes in patients and controls decreased at higher connection probability thresholds as the core of the tract was progressively isolated. Conversely, FA increased with higher thresholds (Figs. 3A–D).
The results of the multiple regression analysis comparing FA in patients and controls are shown in Table 2.
The single test of significance considering both regions of the corpus callosum at all thresholds was P ≤ 0.02, indicating a significant difference in FA between the two groups in either region, over all thresholds. Inspection of the differences in FA at the individual thresholds indicated that the differences in FA between the groups are due to lower FA in the patient group in the genu at probability thresholds 0.006 and 0.013, and to a lesser extent in the splenium at thresholds 0.013 and 0.03 (see Table 2).
To examine subgroup differences in FA, we performed a regression analysis to compare the 13 schizophrenic and 5 schizoaffective patients. Both subgroups had a lower FA than controls. Results from the regression analysis revealed that in the genu, the schizoaffective group had a lower FA than the schizophrenia group (P = 0.0806), whereas in the splenium, the schizoaffective group had higher FA values than the schizophrenia group (P = 0.0295). This suggests that, although there may be subtle differences between subgroups, they differed from controls in the same direction and amalgamating the subgroups does not obscure the differences between patients and controls.
We performed a separate analysis looking for gender and age differences in FA by considering patients and controls together. In the analysis of gender, a single test of significance considering all thresholds and both regions of the corpus callosum gave a P = 0.0001. This result indicates that there are gender differences in FA irrespective of subject status. Thus FA, adjusted for group membership, was lower in females than males in the genu at thresholds 0.001 and 0.002, but not in the splenium. There was no significant group membership-by-gender interaction (P = 0.2).
With respect to the effects of age, there was no evidence that the difference between patients and controls in FA varied with age (P = 0.791) for the global test over both regions (i.e. the ten equations), after adjusting for gender and tract volume.
Finally, the SPM analysis using a voxel-based comparison of CSF maps between the two groups revealed no differences between patients and controls using a family wise error correction for multiple comparisons, with f = 34.42 and no voxels as an extent threshold. This indicates that no ventricular enlargement was present in the patient group relative to controls. There was no significant difference between the global CSF volumes of patients (287 cm3, SD = 33.6) and controls (283 cm3, SD = 51.6) (t = − 0.85, P = 0.40, CI = [− 41.7–17.2]).
Discussion
Our findings provide evidence of altered interhemispheric connectivity in patients with first-episode schizophrenia spectrum disorders. In the patient group, abnormal tract coherence, as measured by reduction in FA, was present in tracts traversing the genu and, to a lesser extent, in those traversing the splenium. Tract coherence, as measured by FA, was lower in females, both in patients and controls, but we failed to find a gender-by-group interaction.
The genu and the anterior part of the body of the corpus callosum contain mainly connections from prefrontal cortex, cingulate and insula, and pathology in these cortical regions could result in the abnormalities of the corpus callosum described here. Similarly, a decreased thalamic input to the frontal and temporal cortex, perhaps due to excessive synaptic pruning, could also result in decreased cortical connections and hence in abnormalities in the corpus callosum (Innocenti et al., 2003), but it is also possible that primary white matter abnormalities could contribute to our findings (Walterfang et al., 2006). The corpus callosum develops alongside other midline structures, namely the fornix, hippocampus, septum and cingulate cortex, and developmental or maturational abnormalities involving the corpus callosum are also likely to affect these structures known to play a role in schizophrenia.
Our diffusion-MRI-based tractography (PICo) used a probabilistic approach that takes into account branching, crossing and merging of tract fibers and this represents an advantage over previous deterministic approaches that do not take these anatomical features into consideration (Kanaan et al., 2006). In addition the use of different probability thresholds and simultaneous multiple regression analysis (Zellner, 1962) has allowed us to demonstrate evidence, from a single statistical test, that there is some difference in tract coherence between patients and controls and to explore the characteristics of the core of the tract in the genu and the splenium. The group differences in FA become more apparent at intermediate probability thresholds in the genu when fiber alignment in the core of the corpus callosum is greatest and aberrant branching that could have artificially reduced FA (Jones et al., 2005) less likely. The high inter-rater reliability in the placement of the seed points also suggests that the differences in FA between patients and controls are likely to be illness-related rather than artifactual. The same applies to the effects of gender and age, known to affect FA (Price et al., 2005; Jones et al., 2005), that were statistically controlled for in our study as our groups were not closely age matched. Antipsychotic medication may have played a role in reducing FA, although it seems unlikely that medication effects could fully account for the differences between the groups in first-episode patients who had been exposed to medication for short periods. Moreover, others (Flynn et al., 2003) have found no correlation between the presence of white matter abnormalities in first-episode psychosis and exposure to antipsychotic medication. The possible effect of mood stabilizers in explaining our results is likely to be negligible as they were used in only 2 patients.
The gender difference in tract coherence that we found in our subjects, particularly in the genu, supports our previous results in a different sample of first-episode patients and controls using a region-of-interest methodology (Price et al., 2005) and is in keeping with the lower anisotropy in normal females than males reported by Westerhausen et al. (2003). Gender dimorphism and maturational differences are likely to be relevant in explaining this finding. Dubb et al. (2003), in an MRI study of normal subjects, found a larger genu and smaller splenium in men compared with women and attributed the differences to different hormonal influences, to enhanced motor coordination in men (interhemispheric connections crossing the genu) and to greater bihemispheric representation of language in women (tracts crossing the splenium). Adult maturational changes in the corpus callosum, with a peak in the third decade of life, would further accentuate these differences. The differences in age between the two groups are a limitation of the study, although we tried to circumvent the problem using age as a covariate.
The precise neuropathological correlates of FA abnormalities remain to be fully elucidated. Axonal membranes are considered to be the main determinant of anisotropy in neural tissue, and pathological or experimental models of axonal degeneration have lead to reductions in FA. Myelin abnormalities are also responsible for changes in FA, although their contribution may be less important than those of axons or axonal membranes (Beaulieu, 2002). In our study the lower FA in the white matter tracts traversing the corpus callosum may be due, in addition to myelin abnormalities, to differences in axonal membranes, alterations in axonal packing density, mean axonal diameter (for example due to a bias towards axons of greater or lesser diameter in one or other group) or a less coherent fiber alignment in the patient group. The similar tract volumes we found in patients and controls may suggest that severe axonal loss is unlikely at this early stage of the illness. On the other hand, the greater variance in genu tract volumes in the patient group suggests that there may be more branching (i.e. less coherence or alignment) in the core of the tract. We have also excluded the possibility that our findings could be related to ventricular enlargement in the patient group.
The study of patients with first-episode psychosis has the advantage of minimizing the effects of chronicity and lengthy exposure to medication, on the other hand, such patients are diagnostically heterogeneous and this is one of the shortcomings of our study and it remains uncertain whether the changes in corpus callosum described here are a core neuropathological abnormality common to all psychosis or are only present in a subgroup of patients. Support for the former accrues from the study of Bachmann et al. (2003) who reported similar findings in a heterogeneous group of patients with first-episode psychosis. In addition, there is evidence to suggest that corpus callosum abnormalities are also present in patients with bipolar disorder (Brambilla et al., 2003, 2004) and other DTI studies looking at ROIs in frontal white matter, although not specifically at the corpus callosum, have reported low FA in a mixed group of patients with first-episode psychosis (Szeszko et al., 2005) and in those with first-episode mania (Adler et al., 2006). There is also evidence that oligodendrocyte and myelination genes may be downregulated both in schizophrenic and affective psychosis (Tkachev et al., 2003; Iwamoto et al., 2005). It is also likely that the abnormalities described here may also be present in other connecting tracts, as suggested by the neuropathological findings of Highley et al. (1999b) in the anterior commissure, and the results of DTI imaging studies (Kubicki et al., 2005). Our study suggests that the schizophrenia and schizoaffective subgroups may be heterogeneous based on FA, but both these groups differ from controls in the same direction of FA change. An intriguing possibility, in need of further study, is that genetic variability within schizophrenia may be associated with specific patterns of brain morphology including variations in the size and structure of the corpus callosum (Agartz et al., 2006).
Our findings also demonstrate that tractography is capable of detecting subtle pathological abnormalities in patients with psychosis early in the disease that may go undetected using other DTI methods (Price et al., 2005; Kanaan et al., 2006). Tractography is likely to have a role in future psychosis research, in elucidating connections between relevant cortical regions and in giving specific information about white matter abnormalities and their evolution over time.

pico, probabilistic index of connectivity


Bone marrow edema-like lesions change in volume in the majority of patients with osteoarthritis; associations with clinical features

It has been suggested that bone marrow edema-like (BME) lesions in the knee are associated with progression of osteoarthritis (OA). The purpose of our study in patients with OA was to evaluate prospectively changes of BME lesions over 2 years and their relationship with clinical features. Magnetic resonance (MR) images of the knee were obtained from 182 patients (20% male; aged 43–76 years; mean age 59 years) who had been diagnosed with familial symptomatic OA at multiple joint sites. MR images were made at baseline and at 2 years follow-up. BME lesions in 2 years were associated with clinical features assessed by Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores. A total of 327 BME lesions were recorded. Total size of BME lesions changed in 90 patients (66%). Size of individual lesions changed in 147 foci (45%): new lesions appeared in 69 (21%), existing lesions disappeared in 32 (10%), increased in size in 26 (8%) and decreased in size in 20 (6%) lesions. Increase or decrease of BME lesions, over a 2-year time period, was not associated with severity of WOMAC scores. BME lesions fluctuated in the majority of patients with OA over a 2-year time period. These changes were not associated with severity of WOMAC scores at the study end point.
Introduction
Knee osteoarthritis (OA) is a chronic, progressive joint disease, leading to pain and loss of function in a considerable proportion of patients, with great impact and consequences in the ageing population of the industrialized world. Disease markers need to be identified in order to predict and quantify progression. One possible marker in OA is the so-called bone marrow edema-like (BME) lesions [1].
Unfortunately, the role of BME in OA remains controversial, as contradictory results have been reported. BME detected with magnetic resonance (MR) imaging has been associated with clinical symptoms in patients with OA [2, 3]. However, other studies reported no association between BME lesions and clinical symptoms [4–6]. Further, the role of BME as a marker for progression of OA is open to discussion. In a study by Felson et al. [7], BME was associated with progression of OA as assessed by joint space narrowing on conventional radiographs. On the other hand, in a study by Phan et al. [5], changes in BME did not significantly change with progression of disease assessed by Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores.
Since these contradictory results regarding the association between BME and clinical features have been reported, the purpose of our study was to evaluate changes in BME lesions over a 2-year period, and associate them with clinical features.
Patients and methods
Patients
The present prospective study is part of the ongoing GARP (Genetics, Osteoarthritis and Progression) study [8]. The primary goal of the GARP study is the identification of genetic susceptibility determinants to OA and disease progression in middle-aged sibling pairs with OA at multiple joint sites. MR image sets of the knee were obtained in 182 patients at study entry and after 2 years [6]. Only one knee, the most symptomatic, was imaged per patient. In the present, study 39% (71/182) of the patients had symptomatic knee OA in their imaged knee, defined as pain or stiffness on most days in the month prior to study entry, and osteophytes on radiographs. As the purpose of the MR study was to assess progression of OA, no images were made of a knee that already had a maximum Kellgren and Lawrence score of grade 4 [9].
Clinical assessment
Clinical data were assessed by WOMAC to assess pain, stiffness and functional impairment of the imaged knee at the 2-year time point, not at baseline [10].
MR acquisition
Knees were imaged using a transmit-receive four-channel knee coil in a 1.5-T superconducting magnet (Philips Medical Systems, Best, the Netherlands). Each examination consisted of: coronal proton density and T2-weighted dual spin echo (SE) images (with repetition time (TR) of 2,200 ms; echo time (TE) of 20/80 ms; number of excitations per data line (NEX) 2; 5 mm slice thickness; 0.5 mm intersection gap; 160 mm field of view (FOV); 256 × 205 acquisition matrix, 18 slices); sagittal proton density and T2-weighted dual SE images (TR 2,200 ms; TE 20/80 ms; NEX 2; 4 mm slice thickness; 0.4 mm intersection gap; 160 mm (FOV); 256 × 205 acquisition matrix, 20 slices); sagittal 3D T1-weighted spoiled gradient echo (GE) frequency selective fat suppressed images (TR 46 ms; TE 2.5 ms; NEX 1; flip angle 40°; 3.0 mm slice thickness; slice overlap 1.5 mm; no gap; 180 mm (FOV); 256 acquisition matrix, 80 slices); and axial proton density and T2-weighted turbo spin echo (TSE) fat suppressed images (TR 2,500 ms; TE 7.1/40 ms; NEX 2; 2 mm slice thickness; no gap; 180 mm (FOV); 256 acquisition matrix, 62 slices). Total acquisition time (including the initial survey sequence) was 30 min.
MR interpretation
All MR images were analyzed in known chronological order by means of consensus between three experienced readers, using a comprehensive score form [11]. During the assessment, the readers were blinded to radiographic results, patient symptoms and patient age. In cases of disagreement between the readers the more conservative, less severe score was recorded. BME or cysic lesions was assigned to any one or more of the following anatomic locations: the crista patellae, medial or lateral patellar facets, the medial or lateral trochlear articular facets, the medial or lateral femoral condyles, the medial or lateral tibial plateaux.
BME lesions were defined as an ill-defined area of increased signal intensity on T2-weighted images in the subchondral bone, extending away from the articular surface over a variable distance [12]. The lesions were graded as follows: grade 0, absent; grade 1, minimal (diameter <5 mm); grade 2, moderate (diameter 5 mm–20 mm); grade 3, severe (diameter >20 mm). The maximum two-dimensional diameter was measured to grade the lesion. A total BME score of the knee was calculated by adding all grades of each BME lesion in the knee. Maximum possible knee score was 27 (grade 3 times nine anatomic locations). In the total study a maximum of 1,638 BME lesions (182 patients times nine anatomic locations) could be scored.
Subchondral cysts were defined as well-defined foci of high signal intensity, with low signal intensity margins, on T2-weighted images, in the bone underlying the joint cartilage. Their greatest dimension was measured and they were graded as follows: grade 0, absent; grade 1, minimal (<3 mm); grade 2, moderate (3–5 mm); grade 3, severe (>5 mm). A total score of the knee was calculated by adding all grades of each cystic lesion in the knee. Maximum possible knee score was 27 (grade 3 times nine anatomic locations). In the total study a maximum of 1638 cystic lesions (182 patients times nine anatomic locations) could be scored.
Statistical analysis
Odds ratios (ORs) with 99% confidence intervals (CIs) were used to show any association between BME size changes with cystic size changes.
The difference in WOMAC scores between patients without BME lesions (group A) and patients with BME lesions (group B: unchanged BME lesions over 2 years; group C: increasing size of BME lesions over 2 years; group D: decreasing size of BME lesions over 2 years) was calculated by linear mixed models in SPSS for Windows, version 12.0 (SPSS, Chicago, Ill.) with a random intercept to adjust for the familial effect within sib pairs. Adjustments were made for age, sex and body mass index (BMI). Estimates of fixed effects were reported with 95% CIs.
Results
In total 182 patients were monitored over a period of 2 years (Table 1). Forty-six (25%) patients did not have BME lesions; thus, 136 patients (75%) had one or more BME lesions at any time point. In 46 (34%) of patients, BME scores did not fluctuate, whereas they changed in the other 90 (66%) patients. The total BME score per individual patient increased in 54 (40%) patients. It decreased in 27 patients (20%), and total BME score remained unchanged in nine (7%) patients. Individual BME scores did change in this last group without resulting in a change of the total BME score. A total of 327 BME lesions were detected from a possible total of 1,638 lesions (Table 2). One hundred and forty-seven (45%) BME lesions changed: 69 new lesions appeared on the second MR (21%), 26 (8%) increased, 20 (6%) decreased in size, and 32 (10%) were no longer visible on the second MR scan (Fig. 1). It was noted that more lesions appeared or increased than decreased or disappeared.
Table 1Patient characteristics (n = 182) At baselineAge years, median (range)59 (43–76)Female sex, (%)157 (80%)Body mass index (kg/m2), median (range)25.7 (20.2–40.0)Symptomatic knee OA, n (%)a71 (39%)Kellgren & Lawrence Score 0/1/2/3/4, No.59/53/60/10/0Over 2 yearsBone marrow edema-like lesions, n (%)b128 (70%)Grade 0/1/2/3c54/56/62/10Cysts, n (%)b100 (55%)Grade 0/1/2/3c82/60/37/3At 2 yearsWOMAC Pain scores, median (range)d13 (0–99)WOMAC Stiffness scores, median (range)d18 (0–99)WOMAC Function scores, median (range)d14 (0–98)aDefined as pain or stiffness on most days of the month prior to study entry, in combination with osteophytes on radiographsbDuring 2 yearscMaximal grade per patientdn = 157Table 2Cystic and BME lesions per patient changing over 2 years in 182 patients (n = 1,638) BME lesionsNo BMENo changeIncreaseDecreaseTotalCystsNo cyst1,2807738211,416No change24872417152Increase21130346Decrease5531124Totals1,31118095521,638Fig. 1a–d Axial T2-weighted turbo spin echo fat suppressed images. Increase (a at baseline, b after two years) in size of bone marrow edema-like lesions over 2 years at the crista patella (arrow) and at the medial femoral condyle (arrowhead). Decrease (c at baseline, d after two years) in size of bone marrow edema-like lesions over 2 years at the crista and medial part of the patella (open arrowhead)
One hundred (55%) patients had one or more cystic lesions at any time. In 44 patients (44%), total cystic score did not fluctuate over time, whereas in the other 56 patients (56%) the total cystic score changed in size. In 36 of these 56 patients (64%) the cystic score increased, it decreased in 18 patients (32%), and the total cystic score remained unchanged irrespective of changes on the level of individual cysts in two patients (4%). A total of 222 cystic lesions were detected from a possible total of 1,638 sites (Table 2). Seventy cystic lesions (32%) changed: 32 new cysts appeared on the second MR (46%), 14 (20%) increased, six (8%) decreased in size, and 18 (26%) were no longer visible on the second MR (Fig. 2).
Fig. 2a, bAxial T2-weighted turbo spin echo fat suppressed images. Disappearing cyst at the lateral femoral condyle (arrow). a At baseline, b after 2 years
Cystic and BME lesions were both present in the same anatomic location (associated lesions) in 191 cases. A change of BME lesions or cystic lesions was associated with a change in size of an adjacent cystic or BME lesion (OR: 6.2; 95% CI: 3.2–12.3). In 47 cases both BME lesions and cystic lesions changed. When cystic and BME lesions were both present in the same anatomic location, size changes (increase or decrease) were in same direction (OR: 37; 95% CI: 6–210) (Table 2).
One hundred and fifty-seven (86%) patients completed a WOMAC questionnaire of the imaged knee at 2 years. The WOMAC pain and function scores for patients without and with BME lesions over 2 years are shown in Fig. 3a and b, respectively. The mean WOMAC scores did not differ between the different patient groups; even when BME lesions completely disappeared, lower WOMAC scores were not recorded. The mean difference in WOMAC pain scores between patients with unchanged BME lesions, with increasing BME lesions and with decreasing BME lesions compared with patients without BME lesions were 2 (95% CI-8 to 12), 2 (95% CI-8 to 11) and 1 (95% CI-11 to 12) respectively (Fig. 3a). The mean difference in WOMAC function scores between patients with unchanged BME lesions, with increasing BME lesions and with decreasing BME lesions compared to patients without BME lesions were −2 (95CI-12 to 8), −4 (95CI-13 to 6) and −4 (95CI-15 to 8) respectively (Fig. 3b).
Fig. 3Association between WOMAC pain (a) or function (b) scores and bone marrow edema-like lesions. Group A: patients with no bone marrow edema-like lesions; Group B: patients in whom bone marrow edema-like lesions did not change over 2 years; Group C: patients in whom bone marrow edema-like lesions increased in size over 2 years; Group D: patients in whom bone marrow edema-like lesions decreased in size over 2 years. Box plots show the median, interquartile range, minimum and maximum values
Discussion
The majority (75%) of patients with familial OA at multiple sites have BME lesions visualized when two sequential MR scans are made with a 2-year time interval. In the majority (66%) of these patients with BME lesions, the total size of BME changed over this 2-year time period. Our study also demonstrates that cysts and BME fluctuations are associated. However, no association existed between changes in BME lesions and severity of WOMAC scores after 2 years.
The finding, that BME lesions fluctuate in 66% of the patients, indicates that BME is part of a dynamic process in OA. BME is not a constant finding, as opposed to hyaline cartilage loss for example. Thus, it is important to realize that the finding of BME lesions in patients with OA represents only a single snapshot in time. The variability of BME lesions has been noted before [5]. It is also interesting and important to note that 10% of BME lesions disappear completely. This is particularly noteworthy if BME is to be used as an inclusion criterion, outcome parameter or surrogate endpoint in drug trials or clinical outcome studies.
The second finding of the present study is that when cystic lesions and BME lesions are in close proximity; the direction in which they change is identical. This is an interesting finding as the role of cysts in OA is unclear. Their exact pathophysiology is uncertain, as is their prognostic significance. A recent study by Carrino et al. [13] also showed a change in cyst size was accompanied by a change in oedema-like signal size. That study also showed subchondral cysts developing in pre-existing regions of subchondral bone marrow oedema-like signal.
The third finding is that changes in BME lesions did not correlate with severity of WOMAC scores. Patients in whom BME increased did not have a higher WOMAC score than patients with a decrease in BME size. Even when BME completely disappeared, lower WOMAC scores were not recorded. Previous work has demonstrated that pain, as assessed by WOMAC scores, was not related significantly to changes in BME lesions [5]. However, in the studies by Felson et al. [2, 7], BME was associated with progressive radiographic knee OA and pain. Cross sectional associations between BME lesions and clinical findings remain controversial [2–6]. Hence, a lack of clarity about the relationship between changes in BME lesions and WOMAC scores is not surprising. Phan et al. [5] have suggested that the complexity of pain physiology and the difficulty of pain evaluation may explain these findings, as well as the fact that patients experience pain differently. Another important factor might be the stage of OA in the patients being studied. For instance, pain might be associated with BME lesions in a more developed stage of the disease and less so earlier on. Knee OA studied in the population by Felson [2] was more advanced than the GARP population [8]. Also Felson’s population consisted of patients with knee OA only, whereas the GARP population is focused on patients with familial OA at multiple sites. A considerable proportion of patients in the present study did not have symptomatic radiographic knee OA in the imaged knee, and consequently average WOMAC scores in the present population were low (Table 1). Nevertheless, associations between BME lesions and clinical findings are controversial and BME lesions may be excluded ultimately as a factor in pain sensation.
The present study has a number of limitations. Firstly, not all patients with a complete MRI follow-up completed the WOMAC signal knee. Secondly, the inclusion of patients who were first-degree relatives may have introduced an artefact. However, linear regression analysis, with robust standard errors that clustered on pairs, excluded this possibility. Thirdly, although referred pain from the hip may have been a confounder, hip OA occurred in only 7% of the patients and was not thought a contributory factor. Fourthly, 2 years of follow-up may be too short for an early OA population. However, we did find a considerable change in size of both cystic and BME lesions. Finally, the term BME used in this article probably should be described more properly as “ill defined signal intensity abnormalities”, as the so-called BME pattern in OA knees represents on histological examination nonspecific abnormalities such as bone marrow necrosis, bone marrow fibrosis, trabecular abnormalities and only a small amount of bone marrow oedema [1]. Nevertheless, the term BME is a commonly accepted identity and widely used in the OA literature [2].
In conclusion, BME lesions are shown to be a variable parameter when followed over time in patients with knee OA and are not predictive of pain.


Does Practice Make Perfect?

Extensive literature supports the correlation between surgical volume and improved clinical outcome in the management of various cancers. It is this evidence that has catalysed the creation of centres of excellence. However, on closer inspection, many of these studies are poor quality, low weight and use vastly heterogenous end points in assessment of both volume and outcome. We critically appraise the English language literature published over the last ten years pertaining to the volume outcome relationship in the context of cancer care. Future balanced unbiased studies may enable equipoise in planning international cancer management strategies.
No longer is there room for eminence-based complacency or misguided arrogance in healthcare delivery. The day of the autonomous clinician is gone with a vogue towards standardised, evidence-based clinical excellence. Cynics would erroneously attribute this to a parallel increase in litigation but increasing patient knowledge and expectations with a move toward subspecialisation are the main catalysts driving change. When offered operative intervention, the question frequently asked by the patient is “How many of these have you done before?” This article aims to critically analyse recent literature and explore the correlation between volume and clinical outcome in the context of cancer care.
Background
Mortality rates are reported to be influenced by the number of particular operations performed in a given hospital or by a specific surgeon (i.e. outcomes are better in high-volume centres). In 1999, the US National Cancer Policy Board recommended that patients requiring complex procedures be transferred from low- to high-volume hospitals in its report entitled “Ensuring Quality Cancer Care”.1 The following year, the Institute of Medicine held a workshop to discuss cancer care, publishing a document (“Interpreting the Volume-Outcome Relationship in the Context of Cancer Care”2) which concluded that existing evidence was strong enough to recommend the regionalisation of high-risk operations. Hence, the impact of volume on outcome has been assessed in several tumour types but the majority of data relates to gastrointestinal, hepatobiliary, urological, and breast cancers.
The literature
Patients undergoing pancreatic and oesophageal procedures have lower operative mortality and shorter hospital stay in the hands of experienced surgeons in high-volume units.3 With regard to gastric cancer, the findings are less consistent. Some suggest that high-volume centres have lower in-house mortality4 but no change in long-term survival.5 Various end points have been examined in colorectal cancer (Table 1). Schrang and Billingsley both showed that it was surgeon-specific experience combined with multidisciplinary support rather than centre experience that afforded significant survival advantage.6,7Table 1.Colorectal cancer outcome: high- and low-volume unitsHigh volumeLow volumeRef.APR versus LAR↓ APR↑ APRMeyerhardt et al. 19↑ LAR↓ LARSphincter preservation↑ ↑↓Purves et al.2030-day postoperative mortality↔↔Schrag et al.21Survival (overall and cancer specific)↑↓Schrag et al.21Permanent stoma formation↓↑McGrath et al.22Colonic pouch formation↑↓McGrath et al.22APR, abdominoperineal resection; LAR, low anterior resection.↑ increased, ↓ decreased, ↔ no variation.
Comprehensive albeit retrospective studies unequivocally state that patients who undergo radical prostatectomy at lower-volume institutions are at significant risk of requiring adjuvant therapy due to adverse surgical factors, prolonged hospital admission, increased hospital charges and postoperative complications.8 The hospital structure of high-volume units, including easy availability of consultative, diagnostic and ancillary services, were cited as likely contributors to the association between procedure volume and short-term cystectomy outcomes.9 A minimum case load of only 11 radical cystectomies per year was cited to be associated with the lowest mortality rate.10
Less certainty exists in relation to breast cancer but a variety of end points have been examined, including number of visits required to obtain a nonoperative diagnosis, mastectomy rates for <15 mm tumours and rate of referral for adjuvant radiotherapy.11 Skinner et al. were adamant that volume alone could not be used as a surrogate for expertise but, like most studies, conceded that patients with breast cancer operated on in high-volume units compared to very low-volume units had better survival. However there is ambiguity surrounding the exact causal relationship: volume effect alone versus surgical skill versus appropriate use of adjuvant therapy.12
The Flaws
The majority of studies are poor quality, heterogenous and potentially flawed. Even the best literature stems from retrospective review of large databases which are up to 40% inaccurate13 and pertain to selected patient groups. Most papers are published from a few very high-volume US centres, thus introducing immediate potential for bias. No consistent end point is used and, incredibly, few studies explore cancer-specific outcomes. Mortality rates, when not corrected for comorbidities or stage at diagnosis, are poor surrogates for more robust comparators of volume–outcome analysis such as cancer-specific survival, patient satisfaction and quality of life.
American data cannot be used as a basis for the formation of European cancer strategies because so many inherent differences exist. These include earlier disease stage at time of operation (a function of screening),14 wide variance in population15 and socioeconomic status16 as well as insured versus noninsured outcomes.17 Comparison of very high-volume centres and very low-volume centres is as redundant as measuring revenue from a supermarket versus a corner store. Is it not intuitive that analysis of such extremes will yield vastly different results? Looking at the structure–process–outcome model, structure is relatively fixed (health service, institution) but process is entirely variable and volume is but one component of it. Therefore, in the absence of multivariable data, subgroup analysis is entirely inappropriate, rendering the aforementioned studies at best biased, at worst invalid.
The Surgeon
To identify procedure volume in a single institution is easy but not so for quantifying specific operations done by a single surgeon, many of whom practise in several centres. Without asking individuals to record caseload prospectively, obtaining accurate figures may be very difficult. Surely significant bias could occur in that those willing to share details of operations may be confident of their own justification in performing such procedures. Furthermore, who counts as more experienced: a mature surgeon who has performed two colonic resections a week for 20 years but now does only two a month or a younger, specialist trained surgeon who performs three a week? How do you weight lifetime experience against current volume? Should a centralised database of surgeons’ logbooks exist, and should permission to operate be granted or denied based on this? What governing body should be afforded such a task? Should operating surgeons be ranked in their ability or would this border on defamation for the less fortunate ones? Regarding referral pattern, does volume attract quantity or do excellent clinicians attract patients? Many studies have compared the significance of surgeon experience to unit volume with varied conclusions as to which has more impact. Do excellent surgeons naturally aggregate in excellent high-volume units, thus giving a self-propagating explanation for improved outcome?
The Institution
Many papers allude to the importance of the multidisciplinary approach in cancer care. Higher-volume units are far more likely to have subspecialised radiologists, radiation and medical oncologists, high dependency and intensive care units, cancer specialist nurses, dedicated psychologists and palliative care support. Anecdotally, the involvement of such services translates into better patient outcome regardless of unit volume, thus confounding results. The resounding evidence in favour of the volume–outcome relationship pertains to those cancers requiring adjuvant therapy: oesophagus, pancreas and advanced colorectal. It seems, therefore, that good surgical technique or individual surgeon experience do not exclusively guarantee positive outcomes and that much depends on availability of radiation and medical oncology.
More often than not, within a short period of the introduction of a new service, its resources are saturated. At what point does a dedicated unit declare that available services can no longer provide for patient throughput? The worry is that potential exists for patients to receive suboptimal care just before this saturation point is reached (Fig. 1). Surely stretched resources in a high-volume centre are just as dangerous as absence of resources in smaller institution. A study on the difference in time lapse between diagnosis and intervention between institutions with different volumes would be welcome. Would prognosis be improved if a patient with aggressive disease underwent early intervention at a lower-volume centre rather than late intervention at a higher-volume centre? As cancer management is a dynamic process, the question of safety in transferring postoperative follow-up of a patient operated on in a high-volume unit to a less experienced lower-volume local centre is a pertinent one. On the other hand, should surgery be performed in low-volume units and adjuvant therapies in specialist centres? Without a doubt, the idea of hospital units functioning as a syncitium rather than single buildings must be engendered and skill-appropriate tasks assigned to each component, as recommended in breast cancer management by the Clinical Oncology Information Network (COIN) group.18Fig. 1.Volume–outcome relationship.
The Patient
Quality of life and patient satisfaction, apart from in colorectal and prostate cancers, are largely ignored when assessing impact of volume on clinical outcome. Is it preferential for elderly patients to travel long distances for management of a low-grade tumour or would they be better served by treatment in a lower-volume local centre where follow-up will be on their doorstep? Decisions like this are made on a daily basis in the context of primary care and so this begs the question of higher-volume specialist centres receiving selected patient cohorts, thus falsely improving outcome. This is confirmed by Morris et al. who showed that patients treated in the Australian private sector were likely to be younger, male and to have an earlier disease stage.17
The Future
The literature supports a correlation between surgical volume and improved clinical outcome in cancer care. However, a rather simplistic approach is evident in many studies and much potential remains for unbiased, prospective, statistically sound investigations with the aim of numerically stratifying appropriate volume and its impact on disease specific cancer outcomes.
While traditionally graph 1 in Fig. 1 has been used to represent the volume–outcome relationship, it seems probable that it is more accurately represented by graph 2 in Fig. 1, and can be interpreted as an area under a curve rather than a strictly linear relationship.