关键词: Imaging sequences Kidney Magnetic resonance imaging Neoplasms-primary Urinary

来  源:   DOI:10.25259/JCIS_124_2022   PDF(Pubmed)

Abstract:
UNASSIGNED: In the last decade, the incidence of renal cell carcinoma (RCC) has been rising, with the greatest increase observed for solid tumors. Magnetic resonance imaging (MRI) protocols and algorithms have recently been available for classifying RCC subtypes and benign subtypes. The objective of this study was to prospectively validate the MRI algorithm presented by Cornelis et al. for RCC classification.
UNASSIGNED: Over a 7-month period, 38 patients with 44 renal tumors were prospectively included in the study and received an MRI examination in addition to the conventional investigation program. The MRI sequences were: T2-weighted, dual chemical shift MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced T1-weighted in wash-in and wash-out phases. The images were evaluated according to the algorithm by two experienced, blinded radiologists, and the histopathological diagnosis served as the gold standard.
UNASSIGNED: Of 44 tumors in 38 patients, only 8 tumors (18.2%) received the same MRI diagnosis according to the algorithm as the histopathological diagnosis. MRI diagnosed 16 angiomyolipoma, 14 clear cell RCC (ccRCC), 12 chromophobe RCC (chRCC), and two papillary RCC (pRCC), while histopathological examination diagnosed 24 ccRCC, four pRCC, one chRCC, and one mixed tumor of both pRCC and chRCC. Malignant tumors were statistically significantly larger than the benign (3.16 ± 1.34 cm vs. 2.00 ± 1.04 cm, P = 0.006).
UNASSIGNED: This prospective study could not reproduce Cornelis et al.\'s results and does not support differentiating renal masses using multiparametric MRI without percutaneous biopsy in the future. The MRI algorithm showed few promising results to categorize renal tumors, indicating histopathology for clinical decisions and follow-up regimes of renal masses are still required.
摘要:
未经批准:在过去的十年中,肾细胞癌(RCC)的发病率一直在上升,实体瘤的增幅最大。磁共振成像(MRI)协议和算法最近可用于分类RCC亚型和良性亚型。本研究的目的是前瞻性验证Cornelis等人提出的MRI算法。用于RCC分类。
未经批准:在7个月的时间内,前瞻性地将38例44例肾脏肿瘤患者纳入研究,并在常规调查计划的基础上接受了MRI检查。MRI序列为:T2加权,双重化学位移磁共振成像,弥散加权成像(DWI),在洗入和洗出阶段动态对比增强T1加权。根据算法由两名有经验的人对图像进行评估,失明的放射科医生,组织病理学诊断是金标准。
未经证实:在38例患者的44个肿瘤中,根据算法,只有8例(18.2%)肿瘤接受了与组织病理学诊断相同的MRI诊断.MRI诊断血管平滑肌脂肪瘤16例,14clearcellRCC(ccRCC),12发色细胞RCC(chRCC),和两个乳头状RCC(pRCC),而组织病理学检查诊断为24ccRCC,四个pRCC,一个chRCC,和一个pRCC和chRCC的混合瘤。恶性肿瘤在统计学上显着大于良性(3.16±1.34cmvs.2.00±1.04cm,P=0.006)。
未经评估:这项前瞻性研究无法重现Cornelis等人。的结果,不支持在未来使用多参数MRI而不进行经皮活检来区分肾脏肿块。MRI算法显示出很少有希望的结果来分类肾肿瘤,提示肾肿块的临床决策和随访方案的组织病理学仍是必需的.
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