Toide Masahiro, Tanaka Hajime, Kobayashi Masaki, Fujiwara Motohiro, Nakamura Yuki, Fukuda Shohei, Kimura Koichiro, Waseda Yuma, Yoshida Soichiro, Tateishi Ukihide, Fujii Yasuhisa
Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan.
Department of Radiology, Tokyo Medical and Dental University, Tokyo, Japan.
Int J Urol. 2024 Jul;31(7):778-784. doi: 10.1111/iju.15464. Epub 2024 Apr 17.
To validate the diagnostic accuracy of a stepwise algorithm to differentiate fat-poor angiomyolipoma (fp-AML) from renal cancer in small renal masses (SRMs).
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.
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.
This study confirmed the high diagnostic accuracy for differentiating fp-AMLs. These findings may help in the management of patients with SRMs.
验证一种逐步算法在鉴别小肾肿块（SRM）中乏脂性血管平滑肌脂肪瘤（fp-AML）与肾癌方面的诊断准确性。
我们前瞻性纳入了223例实性肾肿块<4 cm且在平扫计算机断层扫描（CT）上未见明显脂肪的患者。采用一种逐步利用动态CT和磁共振成像（MRI）结果的算法对患者进行评估。在通过手术或活检确诊组织学的患者中评估该算法的诊断准确性。进一步分析患者的临床病程。
该算法分别将151例（68%）/42例（19%）/30例（13%）患者分为低/中/高AML概率组。对183例患者进行了病理诊断，其中包括10例（5.5%）fp-AML。其中，135例（74%）/36例（20%）/12例（6.6%）被分为低/中/高AML概率组，每组分别包括1例（0.7%）/3例（8.3%）/6例（50%）fp-AML，预测AML的曲线下面积为0.889。低和中AML概率组通常选择手术作为初始治疗方法（分别为84%和64%），而高AML概率组则选择监测（为63%）。在56个月的随访期间，44例最初接受监测的患者中有36例（82%），低/中/高AML概率组分别为18例中的13例（72%）、7例中的6例（86%）和19例中的17例（89%），继续接受监测且无任何进展。
本研究证实了该算法在鉴别fp-AML方面具有较高的诊断准确性。这些发现可能有助于小肾肿块患者的管理。
