role of multi-detector computerized tomography in the evaluation and diagnosis of acute bowel ischemia

ABSTRACT

Acute bowel ischemia [ABI] is a complicated disorder that occurs when blood flow to the intestines is compromised. Multi-detector row CT combines multiple rows of detectors and faster gantry rotation with narrow collimation. Thus, it offers advantages over classic spiral CT for imaging the mesenteric vasculature and small bowel. The aim of this study was to evaluate the sensitivity and specificity of Multi-Detector Row Computerized Tomography technique in patients with suspected mesenteric ischemia. In this study, 72 consecutive patients were prospectively followed and examined at Aseer. Central Hospital [ACH] with clinical suspicion of ABI or having a CT diagnosis of ABI during the period between March 2003 and October 2004. CT scans were evaluated for evidence of criteria suggestive of ABI. Finally, CT findings and radiological diagnoses were compared to the final pathological diagnoses to measure its sensitivity, specificity, predictive value positive and negative predictive values. Acute bowel ischemia was documented in 56 patients. Their ages ranged between 23 and 85 years with the mean age is 62.5 +/- 15.5 years. Patients were divided to two groups [A and B]. From our study, combining the most sensitive and specific criteria; bowel wall thickening, mesenteric stranding, focal lack of bowel wall enhancement and ascities, increased the overall sensitivity of our technique and interpretation to 97% and the overall specificity to 100%. These finding should be considered in the management of acute bowel ischemia. The mortality rate in our study was 26.8% [15/56 patient] regarding patient proved to have ABI during laparotomy. We concluded that biphasic CT with mesenteric CT angiography is a valuable method of diagnosing ABI, with an overall sensitivity of97% and a specificity of 100%. Inspite of the advances and early intervention, the mortality rate of acute bowel ischemia is still high. Moreover, combining diagnostic criteria predicts high mortality rates