Prediction of vascular invasion using a 7-point scale computed tomography grading system in adrenal tumors in dogs

Background: Previous studies evaluating the accuracy of computed tomography (CT) in detecting caudal vena cava (CVC) invasion by adrenal tumors (AT) used a binary system and did not evaluate for other vessels. Objective: Test a 7-point scale CT grading system for accuracy in predicting vascular invasion and for repeatability among radiologists. Build a decision tree based on CT criteria to predict tumor type. Methods: Retrospective observational cross-sectional case study. Abdominal CT studies were analyzed by 3 radiologists using a 7-point CT grading scale for vascular invasion and by 1 radiologist for CT features of AT. Animals: Dogs with AT that underwent adrenalectomy and had pre- and postcontrast CT. Results: Ninety-one dogs; 45 adrenocortical carcinomas (50%), 36 pheochromocytomas (40%), 9 adrenocortical adenomas (10%) and 1 unknown tumor. Carcinoma and pheochromocytoma differed in pre- and postcontrast attenuation, contralateral adrenal size, tumor thrombus short- and long-axis, and tumor and thrombus mineralization. A decision tree was built based on these differences. Adenoma and malignant tumors differed in contour irregularity. Probability of vascular invasion was dependent on CT grading scale, and a large equivocal zone existed between 3 and 6 scores, lowering CT accuracy to detect vascular invasion. Radiologists' agreement for detecting abnormalities (evaluated by chance-corrected weighted kappa statistics) was excellent for CVC and good to moderate for other vessels. The quality of postcontrast CT study had a negative impact on radiologists' performance and agreement. Conclusions and Clinical Importance: Features of CT may help radiologists predict AT type and provide probabilistic information on vascular invasion