Comparison of Water, Mannitol and Positive Oral Contrast for Evaluation of Bowel By Computed Tomography

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چکیده

IntrOductIOn Imaging of the bowel has been a challenge to the radiologists. Each imaging modality has its own merits and demerits. The small bowel is always a challenging area for surgeon and gastroenterologist because of its long length and patients with bowel pathology present with vague symptoms. Barium investigation is less sensitive [1,2]. Capsule endoscopy gives a lot of information about bowel but visualization of the outer wall of bowel is not possible and if there is bowel stenosis, capsule gets retained. Ultrasound has an advantage of real time imaging without ionizing radiation and is less expensive and easily available. But it is less sensitive for bowel pathologies especially small bowel because of the scatter of ultrasound beam by air within the bowel. CT with its good spatial and contrast resolution along with its multiplanar reconstruction provides a good platform for the evaluation of bowel. It also has the advantage of evaluation of mesentery which plays an important role in narrowing down differentials. Bowel distension is an important prerequisite in CT evaluation of bowel to open up the collapsed loops which might obscure the underlying pathology [2,3]. Contrast enhanced abdominal scan with oral contrast helps us to evaluate the bowel adequately. In this study we have compared water, 3% mannitol and diluted gastrograffin for assessing intraluminal distention, mucosal fold visualization and mural enhancement. ABStrAct Introduction: Small bowel remains a challenging anatomical site. Imaging approaches like CT-enterography helps in diagnosing non specific clinical presentations and imaging aids in appropriate management. Hence, bowel evaluation by CT requires a oral contrast agent for diagnosing the bowel pathology. Thus, quantitative and qualitative analysis of three oral contrast agents i.e., water, mannitol and positive contrast was done for identification of ideal intraluminal contrast agent.

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تاریخ انتشار 2017