Accuracy of 64-slice multidetector computed tomography scan in detection of the point of transition of small bowel obstruction.

PURPOSE: To determine the accuracy of 64-slice multidetector computed tomography scans in detecting the point of transition of small bowel obstruction by using surgical findings as the gold standard. MATERIALS AND METHODS: Cross-sectional study of 59 patients with SBO who underwent 64-slice MDCT scans of the abdomen followed by surgery from 1 June 2008 to 31 January 2010 at a tertiary care center. Point of transition between distended and collapsed small bowel loops were precisely determined on 64-slice MDCT and subsequently correlated with surgical findings. Data analysis was done on SPSS version 16. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy of MDCT in detection of the point of transition were calculated. RESULTS: Out of 59 patients, 64-slice MDCT was able to detect the point of transition of SBO in 90% (53/59) of patients, while in 10% (6/59) of these patients the point of transition was not found on MDCT. Overall for detection of the point of transition of small bowel obstruction 64-slice MDCT has 93% sensitivity, 67% specificity, 98% positive predictive value, 33% negative predictive value and 92% accuracy, respectively. CONCLUSION: Sixty-four-slice MDCT is highly accurate in diagnosing the point of transition of small bowel obstruction with an accuracy of 92%. It can be used as a localizing tool before surgery for small bowel obstruction.

Diagnosis of hepatoma using grayscale and Doppler ultrasound in patients with chronic liver disease.

OBJECTIVE: To determine the diagnostic accuracy of liver ultrasound for the detection of hepatoma in chronic liver disease (CLD) patients by either taking histopathology or serum α-fetoprotein levels or a biphasic computed tomography (CT) scan (whichever is available) as the gold standard. STUDY DESIGN: Cross-sectional. PLACE AND DURATION OF STUDY: Radiology Department, The Aga Khan University Hospital, Karachi, Pakistan, from January 2007 to January 2010. METHODS: A total of 239 patients (156 males and 83 females) with clinical suspicion or surveillance of hepatoma in CLD referred to the radiology department for ultrasound evaluation followed by either liver biopsy and histopathology or serum α-fetoprotein level or biphasic CT scan. RESULTS: The sensitivity of ultrasound for hepatoma detection in CLD was 65%, specificity was 85%, and accuracy was 70%, and positive predictive value and negative predictive value were 92% and 45%, respectively. CONCLUSION: Ultrasound is a relatively quick, safe, reasonably accurate, and noninvasive imaging modality for the detection of hepatoma in CLD and can be complemented with clinical assessment of screening high-risk patients.

Can computer assisted diagnosis (CAD) be used as a screening tool in the detection of pulmonary nodules when using 64-slice multidetector computed tomography?

OBJECTIVES: To evaluate (1) whether or not the addition of computer-assisted diagnosis (CAD) to 64-slice multidetector computed tomography (CT) can be used as a screening tool for detection of pulmonary nodules in routine CT chest examinations and (2) whether or not to advocate the incorporation of CAD as a screening tool into our daily practice. MATERIALS AND METHODS: A retrospective cross-sectional analysis of 109 consecutive patients who had all undergone routine contrast-enhanced CT chest examinations for indications other than lung cancer at the Radiology Department of Aga Khan University Hospital, Karachi, between November 2010 and January 2011. All examinations were evaluated in terms of the detection of pulmonary nodules by a consultant radiologist and CAD (ImageChecker CT Algorithm R2 Technology) software. The ability of CAD software to detect pulmonary nodules was evaluated against the reference standard. In addition, a chest radiologist also calculated the number of pulmonary nodules. The sensitivity and specificity of the CAD software were calculated against the reference standard by using a 2 × 2 table. The Mann-Whitney U test was applied to compare the performances of CAD and the radiologist. RESULTS: CAD detected 610 pulmonary nodules while the radiologist detected only 113. The reference standard declared 198 pulmonary nodules to be true nodules. CAD detected 95% of all true nodules (189/198), whereas the radiologist detected only 57% (113/198). In the detection of true pulmonary nodules, CAD had 98% sensitivity compared with the radiologist who had 57% sensitivity; the statistical difference between their performances had a P value <0.001. CONCLUSION: Considering the high sensitivity of CAD to detect nearly all true pulmonary nodules, we advocate its application as a screening tool in all CT chest examinations for the early detection of pulmonary nodules and lung carcinoma.