NGHIÊN CỨU GIÁ TRỊ CỦA CẮT LỚP VI TÍNH ĐA DÃY TRONG CHẨN ĐOÁN UNG THƯ ĐẠI TRÀNG CÓ BIẾN CHỨNG TẮC RUỘT

Abstract

Purpose: Describe the imaging characteristics and value of multidetector CT in assessing colonic cancer complications of intestinal obstruction. Subjective and method: A retrospective cross-sectional descriptive study of 65 patients diagnosed with intestinal obstruction due to colon cancer after surgery, with sufficient preoperative multi-detector CT scans and pathological records at the 115 People's Hospital  from January 13, 2015 to April 2, 2018. Variables are collected according to medical records and algorithms using SPSS software to produce research results. Results: Evaluation of the rate of accurate diagnosis of tumour location by MDCT compared to the surgical report description shows that MDCT scans accurately diagnose tumour location in all segments of the colorectal setting except the colon segment. The correct diagnosis rate of tumour in splenic angle is 85.7%. In general, the localization diagnosis rate of the scanner is 98.5%. The diagnostic accuracy of tumour location according to tumour size indicates that the accurate diagnosis rate depends on tumour size (χ2, p < 0.05). Ability to diagnose T stage: sensitivity 100%, specificity 95.0%, accuracy rate 95.4%, positive predictive value 97.4%, negative predictive value 100%. Ability to detect lymph node metastases: sensitivity 63.2%, specificity 63.2%, positive predictive value 46.2%, negative predictive value 77.4%; The accurate diagnosis rate was 67.7% according to N stage (p < 0.001). Ability to detect distant metastases: Sensitivity 53.8%, specificity 97.7%, positive predictive value 87.5%, negative predictive value 87.8%; The accurate diagnosis rate is 87.7%, depending on stage M (p < 0.01). Conclusion: Multi-detector CT is the optimal choice for patients with colonic cancer-associated intestinal obstruction with high sensitivity and specificity, reducing complications. In addition, multi-detector CT also accurately diagnoses the stage of colon cancer, helping to predict patient prognosis and choose better treatment options.