Optimal reconstructed section thickness for the detection of liver lesions with multidetector CT. 2010

G Soo, and K K Lau, and T Yik, and P Kutschera
Diagnostic Imaging, Southern Health, Monash Medical Centre, Clayton, Victoria, Australia. soogeoffrey@gmail.com

OBJECTIVE To evaluate the impact of different reconstructed section thicknesses on liver lesion detection using multidetector computed tomography (CT). METHODS Fifty-three patients were examined using a 16-section CT machine with axial reconstructions provided at 2.5, 5, 7.5, and 10mm section thicknesses. Images of different reconstructed section thicknesses from different patients were presented in random order to three independent, blinded radiologists for review at multiple sessions. All images were then reviewed by three radiologists in a common session. Consensus was reached following review of the previous interpretation results and results of follow-up imaging regarding the number of true liver lesions (n=101) for comparison. RESULTS Mean detection rates were as follows: 93/101 lesions detected with the 2.5mm section thickness, 98/101 lesions detected at the 5mm section thickness, 78/101 lesions detected at the 7.5mm section thickness, and 54/101 lesions detected at the 10mm section thickness. Lesions missed at the 2.5mm section thickness were due to masking by image noise. There was particular difficulty detecting subcapsular lesions and lesions adjacent to fissures or the gall bladder at the 7.5mm and 10mm section thicknesses. CONCLUSIONS The optimal reconstructed section thickness for lesion detection in the liver was 5mm.

UI MeSH Term Description Entries
D007091 Image Processing, Computer-Assisted A technique of inputting two-dimensional or three-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer. Biomedical Image Processing,Computer-Assisted Image Processing,Digital Image Processing,Image Analysis, Computer-Assisted,Image Reconstruction,Medical Image Processing,Analysis, Computer-Assisted Image,Computer-Assisted Image Analysis,Computer Assisted Image Analysis,Computer Assisted Image Processing,Computer-Assisted Image Analyses,Image Analyses, Computer-Assisted,Image Analysis, Computer Assisted,Image Processing, Biomedical,Image Processing, Computer Assisted,Image Processing, Digital,Image Processing, Medical,Image Processings, Medical,Image Reconstructions,Medical Image Processings,Processing, Biomedical Image,Processing, Digital Image,Processing, Medical Image,Processings, Digital Image,Processings, Medical Image,Reconstruction, Image,Reconstructions, Image
D008107 Liver Diseases Pathological processes of the LIVER. Liver Dysfunction,Disease, Liver,Diseases, Liver,Dysfunction, Liver,Dysfunctions, Liver,Liver Disease,Liver Dysfunctions
D008113 Liver Neoplasms Tumors or cancer of the LIVER. Cancer of Liver,Hepatic Cancer,Liver Cancer,Cancer of the Liver,Cancer, Hepatocellular,Hepatic Neoplasms,Hepatocellular Cancer,Neoplasms, Hepatic,Neoplasms, Liver,Cancer, Hepatic,Cancer, Liver,Cancers, Hepatic,Cancers, Hepatocellular,Cancers, Liver,Hepatic Cancers,Hepatic Neoplasm,Hepatocellular Cancers,Liver Cancers,Liver Neoplasm,Neoplasm, Hepatic,Neoplasm, Liver
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D003560 Cysts Any fluid-filled closed cavity or sac that is lined by an EPITHELIUM. Cysts can be of normal, abnormal, non-neoplastic, or neoplastic tissues. Cyst
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly

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