Department of Medicine, Surgery and Neuroscience, Unit of Diagnostic Imaging, University of Siena, Azienda Ospedaliera Universitaria Senese, Viale Mario Bracci 10, 53100, Siena, Italy.
Unit of Diagnostic Imaging, Azienda Ospedaliera Universitaria Senese, Siena, Italy.
AJR Am J Roentgenol. 2020 Mar;214(3):707-714. doi: 10.2214/AJR.18.20953. Epub 2020 Jan 15.
The objective of this study was to demonstrate the feasibility of dual-energy CT (DECT) for locoregional staging of breast cancer and differentiation of tumor histotypes. From January 2016 to July 2017, a total of 31 patients (mean [± SD] age, 55.8 ± 14.8 years) with breast cancer diagnosed by needle biopsy who underwent preoperative contrast-enhanced DECT for staging purposes were selected from a retrospective review of institutional databases. Monochromatic images obtained at 40 and 70 keV were evaluated by two readers who determining the number of hypervascularized tumors present and the largest tumor diameter for each breast. The attenuation values and iodine concentration of tumors and normal breast tissue and the ratios of these findings in each tissue type were recorded. Cancers were classified as ductal carcinoma in situ, invasive ductal carcinoma, and invasive lobular carcinoma. The reference standard was the final pathologic finding after surgery. A total of 64 tumor lesions were found at histopathologic analysis versus 67 on DECT for 34 breasts (three bilateral cancers were included). Nonparametric statistics were used. The largest lesion diameter observed DECT was 33.2 ± 20.5 mm versus 31.8 ± 20.5 mm on pathologic analysis, and cancer distribution was correctly classified for 31 of 34 (91%) cases. ROC curves derived from lesion iodine concentration showed that the optimal thresholds for distinguishing infiltrating carcinomas (invasive lobular and ductal carcinomas) and from other lesions were 1.70 mg/mL (sensitivity, 94.9%; specificity, 93.0%; AUC value, 0.968). ROC curves derived from the ratio of the iodine concentration in lesions to that in normal breast parenchyma showed that 6.13 was the optimal threshold to distinguish invasive ductal carcinoma from other lesions (sensitivity, 87.0%; specificity, 81.1%; AUC value, 0.914). DECT is feasible and seems to be a reliable tool for locoregional staging of breast cancer.
本研究旨在展示双能 CT(DECT)在乳腺癌局部区域分期和肿瘤组织学分型中的可行性。回顾性分析了 2016 年 1 月至 2017 年 7 月期间,因术前分期目的而接受对比增强 DECT 检查的 31 例经活检诊断为乳腺癌的患者。由两位读者评估在 40keV 和 70keV 获得的单色图像,以确定存在的多血管化肿瘤数量和每个乳房的最大肿瘤直径。记录肿瘤和正常乳腺组织的衰减值和碘浓度,以及每种组织类型中这些发现的比值。癌症分为导管原位癌、浸润性导管癌和浸润性小叶癌。参考标准为手术后的最终病理发现。在组织病理学分析中发现了 64 个肿瘤病变,而在 34 个乳房的 DECT 中发现了 67 个(包括 3 例双侧癌)。使用非参数统计学方法。在 DECT 中观察到的最大病变直径为 33.2±20.5mm,而在病理分析中为 31.8±20.5mm,34 例中的 31 例(91%)正确分类了癌症分布。基于病灶碘浓度的 ROC 曲线表明,区分浸润性癌(浸润性小叶癌和导管癌)与其他病变的最佳阈值为 1.70mg/mL(敏感性为 94.9%;特异性为 93.0%;AUC 值为 0.968)。基于病灶与正常乳腺实质碘浓度比值的 ROC 曲线表明,6.13 是区分浸润性导管癌与其他病变的最佳阈值(敏感性为 87.0%;特异性为 81.1%;AUC 值为 0.914)。DECT 是可行的,似乎是一种可靠的乳腺癌局部区域分期工具。