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Stepwise algorithm using computed tomography and magnetic resonance imaging for differential diagnosis of fat‐poor angiomyolipoma in small renal masses: A prospective validation study.
- Source :
-
International Journal of Urology . Jul2024, Vol. 31 Issue 7, p778-784. 7p. - Publication Year :
- 2024
-
Abstract
- Objectives: To validate the diagnostic accuracy of a stepwise algorithm to differentiate fat‐poor angiomyolipoma (fp‐AML) from renal cancer in small renal masses (SRMs). Methods: We prospectively enrolled 223 patients with solid renal masses <4 cm and no visible fat on unenhanced computed tomography (CT). Patients were assessed using an algorithm that utilized the dynamic CT and MRI findings in a stepwise manner. The diagnostic accuracy of the algorithm was evaluated in patients whose histology was confirmed through surgery or biopsy. The clinical course of the patients was further analyzed. Results: The algorithm classified 151 (68%)/42 (19%)/30 (13%) patients into low/intermediate/high AML probability groups, respectively. Pathological diagnosis was made for 183 patients, including 10 (5.5%) with fp‐AML. Of these, 135 (74%)/36 (20%)/12 (6.6%) were classified into the low/intermediate/high AML probability groups, and each group included 1 (0.7%)/3 (8.3%)/6 (50%) fp‐AMLs, respectively, leading to the area under the curve for predicting AML of 0.889. Surgery was commonly opted in the low and intermediate AML probability groups (84% and 64%, respectively) for initial management, while surveillance was selected in the high AML probability group (63%). During the 56‐month follow‐up, 36 (82%) of 44 patients initially surveyed, including 13 of 18 (72%), 6 of 7 (86%), and 17 of 19 (89%) in the low/intermediate/high AML probability groups, respectively, continued surveillance without any progression. Conclusions: This study confirmed the high diagnostic accuracy for differentiating fp‐AMLs. These findings may help in the management of patients with SRMs. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09198172
- Volume :
- 31
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- International Journal of Urology
- Publication Type :
- Academic Journal
- Accession number :
- 178296487
- Full Text :
- https://doi.org/10.1111/iju.15464