
Prediction of vascular invasion using a 7‐point scale computed tomography grading system in adrenal tumors in dogs
Author(s) -
Pey Pascaline,
Specchi Swan,
Rossi Federica,
Diana Alessia,
Drudi Ignazio,
Zwingenberger Allison L.,
Mayhew Philipp D.,
Pisoni Luciano,
Mari Daniele,
Massari Federico,
Dalpozzo Boris,
Fracassi Federico,
Nicoli Stefano
Publication year - 2022
Publication title -
journal of veterinary internal medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.356
H-Index - 103
eISSN - 1939-1676
pISSN - 0891-6640
DOI - 10.1111/jvim.16371
Subject(s) - medicine , radiology , grading (engineering) , inferior vena cava , engineering , civil engineering
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.