Prediction of vascular invasion using a 7-point scale computed tomography grading system in adrenal tumors in dogs.
CT
canine
carcinoma
pheochromocytoma
thrombus
Journal
Journal of veterinary internal medicine
ISSN: 1939-1676
Titre abrégé: J Vet Intern Med
Pays: United States
ID NLM: 8708660
Informations de publication
Date de publication:
Mar 2022
Mar 2022
Historique:
revised:
14
01
2022
received:
27
05
2021
accepted:
14
01
2022
pubmed:
3
3
2022
medline:
1
4
2022
entrez:
2
3
2022
Statut:
ppublish
Résumé
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. 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. 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. Dogs with AT that underwent adrenalectomy and had pre- and postcontrast CT. 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. Features of CT may help radiologists predict AT type and provide probabilistic information on vascular invasion.
Sections du résumé
BACKGROUND
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
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
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
METHODS
Dogs with AT that underwent adrenalectomy and had pre- and postcontrast CT.
RESULTS
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
CONCLUSIONS
Features of CT may help radiologists predict AT type and provide probabilistic information on vascular invasion.
Identifiants
pubmed: 35233853
doi: 10.1111/jvim.16371
pmc: PMC8965227
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
713-725Subventions
Organisme : NCI NIH HHS
ID : P30 CA093373
Pays : United States
Informations de copyright
© 2022 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine.
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