Department of Radiology, Armed Forces Daejeon Hospital, Daejeon, South Korea.
Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
Abdom Radiol (NY). 2024 Dec;49(12):4341-4351. doi: 10.1007/s00261-024-04317-5. Epub 2024 Aug 2.
This study investigated radiologic features on preoperative MRI to differentiate urothelial carcinoma with squamous differentiation (UCSD) from conventional urothelial carcinoma (UC) in muscle-invasive bladder carcinoma.
Ninety-nine patients who underwent radical cystectomy and a preoperative bladder MRI scan within three months before surgery were retrospectively enrolled. Various MRI features, including tumor length, location, multiplicity, long-to-short axis ratio, morphology, radiologic stage, and degree of severe necrosis, were analyzed. Univariable and multivariable logistic regression analyses were performed to identify MRI features predictive of UCSD. The diagnostic performance of a significant MRI feature was assessed using 5-fold cross-validation.
Among the MRI features, significant radiologic findings associated with UCSD in the univariable analysis included heterogeneous tumor signal intensity in T2-weighted images (odds ratio [OR], 3.365; 95% confidence interval [CI], 1.213-9.986; P = 0.022) and contrast-enhanced T1-weighted images (OR, 4.428; 95% CI, 1.519-12.730; P = 0.007), as well as marked (≥ 50%) severe necrosis (OR, 17.100; 95% CI, 4.699-73.563; P < 0.001). In the multivariable analysis, marked (≥ 50%) severe necrosis (odds ratio [OR], 13.755; 95% confidence interval [CI], 2.796-89.118; P = 0.004) was a significant predictor of UCSD. Marked (≥ 50%) severe necrosis showed a high specificity of 95.0% with a precision of 65.0% for diagnosing UCSD based on 5-fold cross-validation.
Preoperative bladder MRI revealing marked severe necrosis may be indicative of UCSD and can assist in distinguishing it from conventional UC.
本研究旨在探讨术前 MRI 的影像学特征，以区分肌层浸润性膀胱癌中的尿路上皮癌伴鳞状分化（UCSD）与普通尿路上皮癌（UC）。
回顾性分析了 99 例在术前三个月内行根治性膀胱切除术和术前膀胱 MRI 扫描的患者。分析了各种 MRI 特征，包括肿瘤长度、位置、多发性、长轴与短轴之比、形态、影像学分期和严重坏死程度。采用单变量和多变量逻辑回归分析来识别预测 UCSD 的 MRI 特征。使用 5 倍交叉验证评估显著 MRI 特征的诊断性能。
在 MRI 特征中，单变量分析中与 UCSD 相关的显著影像学发现包括 T2 加权图像上不均匀的肿瘤信号强度（优势比 [OR]，3.365；95%置信区间 [CI]，1.213-9.986；P=0.022）和对比增强 T1 加权图像（OR，4.428；95%CI，1.519-12.730；P=0.007），以及明显（≥50%）严重坏死（OR，17.100；95%CI，4.699-73.563；P<0.001）。在多变量分析中，明显（≥50%）严重坏死（OR，13.755；95%置信区间 [CI]，2.796-89.118；P=0.004）是 UCSD 的显著预测因子。基于 5 倍交叉验证，明显（≥50%）严重坏死对 UCSD 的诊断具有 95.0%的高特异性和 65.0%的精准度。
术前膀胱 MRI 显示明显的严重坏死可能提示 UCSD，并有助于将其与普通 UC 区分开来。
