unenhanced computed tomography ( low - dose ct ) in risk groups for lung cancer , spiral ct demonstrated non - calcified nodules in up to 66% of asymptomatic smokers with no history of malignancy . the proportion of individuals with nodules was higher with thin slice thickness and use of multidetector ct [ 110 ] . the proportion of non - smokers or children with nodules is not precisely known but ct performed in these groups also frequently shows pulmonary nodules . sensitivity for pulmonary nodules differs with different imaging modalities . whereas the sensitivity of chest radiography is relatively low ( solitary nodule rarely detected if < 5 mm , 50% detected if 610 mm , may be missed even if as large as 35 
 mm ) [ 1113 ] , magnetic resonance imaging ( mri ) is more sensitive with sensitivities of > 50% for nodules computed tomography ( ct ) , particularly spiral multidetector ct ( mdct ) is the method of choice for detection of pulmonary nodules . in a study using surgical exploration of deflated lungs as the gold standard , even single slice spiral ct had a sensitivity of 95% for nodules the good sensitivity is maintained with low radiation dose ct 
 protocols [ 1820 ] . on the other hand , not every nodule exhibited by ct nodules may be missed due to errors of detection ( e.g. lack of concentration ) and interpretation ( e.g. confusion between nodules and vascular cross - sections ) [ 11 , 13 ] . it has been demonstrated , that in small nodules ( \documentclass[12pt]{minimal } 
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 \end{document } 10 mm ) the sensitivity of individual readers is only 6070% depending on the nodule size , the expertise of the readers , the time allowed for the assessment , and viewing mode ( monitor vs. film ) [ 2123 ] . furthermore , this proportion has not significantly improved with multidetector technology , thinner slices or monitor reporting  the better spatial resolution may be compensated by the higher number of images . recently , computer - assisted detection ( cad ) of pulmonary nodules has become available ( fig . the technique is based on automatic identification of nodules as relatively round areas of increased density compared to surrounding lung with lower density . adequate software algorithms allow differentiation between nodules and other areas of soft tissue attenuation with different shapes ( vessels , mediastinum , chest wall ) . it has been shown that the application of these tools can increase the sensitivity of individual human readers for pulmonary nodules , particularly when small and central . this applies to readers with different degrees of experience but is most pronounced in relatively inexperienced readers . this is probably due to the fact that humans tend to detect and miss the same nodules whereas cad and humans detect and miss different nodules . at present , automated cad tools should only be used in conjunction with visual reading due to false positive and false negative results [ 2327 ] . screenshot of a commercially available software tool for automated detection ( lungvcar , ge healthcare , milwaukee , wi ) providing : 3d - volume with red dot marking every detected nodule ( top right ) , axial image ( top left ) , thin - slab maximum intensity projection ( ts - mip ) ( bottom left ) , targeted 3d - reconstruction of nodule and adjacent structures ( mid right ) , simulated scout view ( bottom right ) . screenshot of a commercially available software tool for automated detection ( lungvcar , ge healthcare , milwaukee , wi ) providing : 3d - volume with red dot marking every detected nodule ( top right ) , axial image ( top left ) , thin - slab maximum intensity projection ( ts - mip ) ( bottom left ) , targeted 3d - reconstruction of nodule and adjacent structures ( mid right ) , simulated scout view ( bottom right ) . more than a hundred different histological entities may present as pulmonary nodules , however , in clinical practice , the single most important issue is the classification into benign or malignant lesions . malignant nodules usually require therapy such as resection , chemotherapy or radiation therapy , whereas benign nodules are usually not treated . several features have been analysed in the hope of making this differentiation . in subjects with no history of previous malignancy only the person s age ( < 30 years ) , the presence of benign patterns of calcification ( diffuse , peripheral , popcorn ) and the 
 presence of fat ( hamartoma , lipoid pneumonia ) allow reliable exclusion of malignancy . other demographic ( age > 40 , 60 years , etc . , smoking habits ) or morphologic 
 ( well - defined vs. ill - defined , smooth vs. lobulated contour , apical vs. basal or peripheral vs. central localisation etc . nodule diameter , however , correlates with the likelihood of malignancy with a threshold of 10 mm detected empirically : 50% of nodules > 10 mm are malignant , whereas 
 less than 5% of nodules \documentclass[12pt]{minimal } 
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 \end{document } 10 mm are malignant . several studies have shown that malignant nodules usually enlarge over time [ 4 , 29 , 30 ] . typically , the nodule volume doubles within 30400 days , whereas the volume in benign nodules doubles faster ( e.g. inflammatory nodules ) or slower ( e.g. hamartomas ) . there is , however , an overlap in volume doubling times of benign and malignant nodules . in addition , doubling of the volume represents an increase in diameter of only 26% , e.g. growth from 4 to 5 mm , which may be difficult to detect visually . again , computer - assisted diagnosis , namely volumetry can be applied to detect enlargement of nodules more precisely and , thus , earlier ( fig . figure 2computer - assisted volumetry of a pulmonary nodule in a patient with colorectal cancer . ( a ) thin - section ct : well - defined non - calcified pulmonary nodule in the posterobasal segment of the left lower lobe with a diameter of 9 mm ; ( b ) computer - assisted volumetry of the nodule ( lungvcar , ge healthcare , milwaukee , wi ) demonstrating a nodule volume of 436 mm \documentclass[12pt]{minimal } 
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 \end{document } corresponding to an increase in volume of 26% . 
  computer - assisted volumetry of a pulmonary nodule in a patient with colorectal cancer . ( a ) thin - section ct : well - defined non - calcified pulmonary nodule in the posterobasal segment of the left lower lobe with a diameter of 9 mm ; ( b ) computer - assisted volumetry of the nodule ( lungvcar , ge healthcare , milwaukee , wi ) demonstrating a nodule volume of 436 mm \documentclass[12pt]{minimal } 
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 \end{document } corresponding to an increase in volume of 26% . however , it has been shown that accuracy and particularly reproducibility of volumetric measurements differs between different scanning protocols , ct scanners , software tools and versions and also between different nodule types ( well - defined vs. ill - defined , adjacent to chest wall , vessels or surrounded only by pulmonary parenchyma ) [ 31 , 34 , 35 ] . also , two functional imaging techniques have been introduced which are useful for classification of nodules . contrast - enhanced ct ( ce - ct ) is applied to assess the perfusion of the lesions . studies by swensen and co - authors have demonstrated that lack of enhancement has a high negative predictive value for malignancy . positron emission tomography ( pet ) using [ f]fluorodeoxyglucose ( fdg ) has a sensitivity and specificity of 
 > 7080% for malignancy , although false positive ( inflammatory lesions ) and false negative ( well - differentiated adenocarcinoma , carcinoid tumours , lesions 
 < 10 mm ) findings have been reported . unfortunately , these techniques are not appropriate for application in the huge numbers of small nodules due to the use of contrast media ( ce - ct ) , cost , availability , radiation exposure and the limited use in nodules 
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 \end{document } 10 mm ( pet ) . the definitive means to assess the nature of a nodule is histology obtained from bronchoscopic ( in central lesions ) , percutaneous ct - guided ( in peripheral lesions ) biopsies or resection of the nodule at video - assisted thoracoscopic surgery ( vats ) . pulmonary nodules are common . they are mostly small ( \documentclass[12pt]{minimal } 
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 \end{document } 10 mm ) and benign , even in risk groups . detection of nodules is limited at chest radiography , better at mri and best at ct , particularly with multidetector technology . visual reading is limited even when reporting thin - slice mdct scans on a monitor . nodules \documentclass[12pt]{minimal } 
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 \end{document } 10 mm should be followed with unenhanced ct and computer - assisted volumetry applied if possible . > 10 mm a more invasive work - up is 
 usually required , using ce - ct , pet or biopsy . guidelines suggesting the diagnostic algorithm for nodules with different size classes have recently been published .
pulmonary nodules are commonly detected at computed tomography ( ct ) of the chest . 
 more than 95% are \documentclass[12pt]{minimal } 
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 \end{document } 10 mm ; of these more than 95% are benign 
 . visual detection of pulmonary nodules by human readers is suboptimal , particularly with small nodules \documentclass[12pt]{minimal } 
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 \end{document } 10 mm . 
 computer - assisted detection can improve sensitivity and diagnostic confidence . 
 due to the high proportion of malignant lesions in nodules 
 > 10 mm immediate , often invasive work - up is required including contrast - enhanced dynamic ct , positron emission tomography ( pet ) or biopsy . however , in nodules 
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 \end{document } 10 mm the high proportion of benign lesions requires a non - invasive work - up usually based on follow - up with unenhanced ct . 
 invasive procedures are only required for growing nodules . 
 stable nodules require further follow - up and decreasing nodules are considered benign .