Diagnostic Accuracy of Intra-operative Frozen Section in Abdominal Masses: A Prospective Study from a Tertiary Care Hospital
Year: 2026
Type: article
Study design: Observational Study
Abstract: ABSTRACT Aim: To evaluate the diagnostic accuracy of intra-operative frozen section (FS) in the management of abdominal masses and to identify specific technical and interpretive pitfalls that lead to diagnostic discordance. Materials and Methods: This prospective study analyzed 50 cases of abdominal masses at a tertiary care hospital over a two-year period. Intra-operative samples were processed using a cryostat at -20°C to -25°C, stained with Hematoxylin and Eosin, and reported within 30–45 minutes. The FS diagnoses were categorized as benign, malignant, or suspicious and subsequently compared with the gold standard paraffin-embedded sections (PS). Statistical parameters, including sensitivity, specificity, and predictive values, were calculated. Results: Of the 50 cases, 29 (58%) were malignant and 21 (42%) were benign. The gallbladder was the most frequent site of involvement (40%), followed by ovarian and gastrointestinal lesions. FS demonstrated an overall diagnostic accuracy of 98%, with a sensitivity of 96.5% and a specificity of 100% for the detection of malignancy. One case of discordance was noted in a large, multi-loculated ovarian tumor, where a focal borderline component was under-diagnosed as benign on FS due to sampling limitations. The positive predictive value was 100%, and the negative predictive value was 95.4%. Conclusion: Intra-operative frozen section is a highly reliable diagnostic modality for abdominal masses, providing rapid and actionable results that directly influence surgical strategy. While it is nearly infallible for most solid malignancies, cautious interpretation and extensive sampling are required for complex cystic ovarian lesions to minimize the risk of underdiagnosis. Keywords: Frozen section, intraoperative diagnosis, diagnostic accuracy, abdominal masses, histopathology
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7225578485