Year: 2026
Type: article
Study design: Observational Study
Abstract: Introduction: Accurate preoperative staging is fundamental for selecting appropriate treatment in rectal cancer. Magnetic resonance imaging (MRI) is widely used for local staging, although its diagnostic performance should be validated against postoperative histopathology to optimize clinical decision-making and improve patient outcomes. Objective: To evaluate the correlation between preoperative magnetic resonance imaging findings and postoperative histopathological results in patients with rectal cancer. Methods: This prospective cohort study was conducted at Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh, from July 2021 to June 2022. Purposively selected 65 patients with histologically confirmed rectal cancer underwent standardized preoperative pelvic MRI followed by definitive surgical resection. MRI findings were compared with postoperative histopathology. Data were analyzed using SPSS version 23.0. Results: The mean age was 54.8±11.6 years, with males predominating (61.5%). MRI demonstrated excellent correlation with histopathology for T staging (κ=0.77, p<0.001) and very strong correlation for nodal staging (κ=0.72, p<0.001). Overall diagnostic accuracy was impressively high at 84.6% for T stage and 83.1% for nodal stage, with remarkable sensitivity of 94.4% for detecting advanced T stage and perfect sensitivity (100%) for node-positive disease. Mesorectal fascia involvement was correctly identified in 92.3% of cases (p<0.001), while circumferential resection margin status showed 90.8% concordance with pathological findings (p<0.001). Conclusion: Preoperative MRI demonstrates highly significant and clinically robust correlation with histopathology for local rectal cancer staging. Despite limited performance in detecting advanced tumor spread, MRI remains an indispensable preoperative tool with statistically validated diagnostic accuracy across multiple critical parameters. Medicine Today 2026, Vol.38 (2): 174-179
Source: Medicine Today
Institution: Bangladesh Medical University
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7225119672