Four-step formula for the Siewert classification of adenocarcinomas of the esophagogastric junction: a computed tomography-based quantitative model

This study aimed to develop a novel quantitative methodology to classify the Siewert type on multiplanar reconstructed (MPR) computed tomography (CT) and subsequently guide the diagnosis of adenocarcinoma of the esophagogastric junction. Patients in the retrospective development and prospective validation cohort 1 were recruited from Peking University Cancer Hospital. Patients in prospective validation cohort 2 were recruited from Changzhi People’s Hospital. A streamlined method determined axial/coronal CT slice numbers for the esophagogastric junction (EGJ) and tumor center; then using these slices formulated a Siewert classification system. The CT-based four-step formula for Siewert type (CT-FSFS) is: STEP 1: determining the axial level of the EGJ; STEP 2: distinguishing Type III from Type I/II; STEP 3: predicting Type III misclassified as II; STEP 4: correcting the misclassification using the deflection angle. The CT-FSFS method demonstrated robust accuracy across all three cohorts: 89.5% in the development cohort, 91.0% in validation cohort 1 and 89.7% in validation cohort 2. In differentiating Type I/II from Type III, the formula demonstrated high specificity (96.9%) and positive predictive value (97.1%) in the development cohort. This study presents a reproducible, quantitative Siewert classification method on MPR CT, it may aid preoperative surgical planning.