Trimarchi Renato, Migliaccio Nicola, Bucolo Giuseppe Mauro, Abate Claudia, Aricò Francesco Marcello, Ascenti Velio, Portaluri Antonio, Rossanese Marta, Zagami Paola, D'Angelo Tommaso, Piacentino Filippo, Venturini Massimo, Ascenti Giorgio
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital "Policlinico G. Martino", Messina, 98124, Italy.
Department of Radiology, ASST Bergamo Ovest, Ospedale Treviglio-Caravaggio, Treviglio, BG, 24047, Italy.
Abdom Radiol (NY). 2025 May;50(5):2232-2240. doi: 10.1007/s00261-024-04683-0. Epub 2024 Nov 19.
To investigate the potential role of dual-energy spectral computer tomography (CT) quantitative parameters in the definition of bladder cancer (BCa) pathological grading.
This retrospective study evaluated the use of spectral CT imaging features for BCa. From 2021 to 2023, 63 patients with histologically-confirmed BCa diagnosis were examined at our Institution. The patients were pathologically divided, following international guidelines, into two groups: low-grade (n = 24) and high-grade urothelial carcinoma group (n = 39). The iodine concentrations (IC), the normalized iodine concentrations (NIC), and the slope of the spectrum curve (SLOPE) were calculated along with the measure of each lesion CT value on the monochromatic image from 40 to 120 keV. The diagnostic performance was assessed by Receiver operator characteristic curve (ROC) analysis.
The high-grade group showed significantly higher mean values of IC, SLOPE, and HU in 40 KeV monoenergetic images (VMI HU). AUC values for NIC, SLOPE, IC, and VMI HU were 0,677, 0,745, 0,745, and 0,755 respectively. In multivariate logistic regression models with backward stepwise, including all quantitative parameters, only VMI HU remained statistically significant to correlate with high-grade tumors.
Preliminary data shows that quantitative parameters of dual-energy spectral CT can be helpful to characterize low-grade and high-grade urothelial bladder tumors. The prediction of high-grade BCa with non-invasive methods (e.g. dlCT) can aid in early detection of muscle-invasive and worse prognostic tumors that need more aggressive and timely treatments, personalizing the management on the risk of recurrence.
探讨双能量谱计算机断层扫描(CT)定量参数在膀胱癌(BCa)病理分级定义中的潜在作用。
这项回顾性研究评估了光谱CT成像特征在BCa中的应用。2021年至2023年,我院对63例经组织学确诊为BCa的患者进行了检查。按照国际指南,将患者病理分为两组:低级别(n = 24)和高级别尿路上皮癌组(n = 39)。计算碘浓度(IC)、归一化碘浓度(NIC)和光谱曲线斜率(SLOPE),并测量40至120 keV单色图像上每个病变的CT值。通过受试者操作特征曲线(ROC)分析评估诊断性能。
高级别组在40 keV单能图像(VMI HU)中的IC、SLOPE和HU平均值显著更高。NIC、SLOPE、IC和VMI HU的AUC值分别为0.677、0.745、0.745和0.755。在包含所有定量参数的多变量逻辑回归模型中,采用向后逐步法,只有VMI HU与高级别肿瘤的相关性仍具有统计学意义。
初步数据表明,双能量谱CT的定量参数有助于区分低级别和高级别尿路上皮膀胱肿瘤。用非侵入性方法(如双能量CT)预测高级别BCa有助于早期发现需要更积极及时治疗的肌层浸润性和预后较差的肿瘤,实现复发风险管理的个性化。