Li Xue, Chai Weimin, Sun Kun, Fu Caixia, Yan Fuhua
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China.
Application Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China.
Jpn J Radiol. 2022 Dec;40(12):1263-1271. doi: 10.1007/s11604-022-01304-y. Epub 2022 Jul 6.
This study aims to comprehensively evaluate the diagnostic value of quantitative parameters extracted from apparent diffusion coefficient (ADC) maps in distinguishing fibroepithelial tumors using whole-tumor histogram and texture analysis.
This retrospective study included 66 female patients with single phyllodes tumor (PT) and 29 female patients with single fibroadenoma (FA) who underwent preoperative magnetic resonance imaging. By independently performing whole-tumor histogram and texture analysis based on ADC maps, two radiologists extracted seven histogram parameters and four texture parameters. The extracted parameters were compared using univariate analysis to determine their ability to distinguish FAs from PTs, benign PTs from FAs, as well as benign PTs from borderline and malignant PTs.
When FAs and PTs were compared, ADC values of PTs were significantly lower than those of FAs (p < 0.05), whereas other significant extracted parameter values of PTs were significantly higher than those of FAs (p ≤ 0.001); the area under the curve of significant parameters combined was 0.936. Regarding the differences between FAs and benign PTs, ADC, ADC and ADC of FAs were significantly lower than those of benign PT group, and ADC was higher than that of benign PT group (all p < 0.05). Furthermore, ADC, ADC and all texture parameters are significantly higher in the borderline and malignant PT group than in FA and benign PT group (p < 0.05). In addition, ADC of malignant PT group was significantly lower than that of borderline PT group (p = 0.045).
The extracted whole-tumor histogram and texture features of ADC maps can improve differential diagnosis of breast fibroepithelial tumors and contribute to optimal selection for clinical management of patients with fibroepithelial tumors.
本研究旨在利用全肿瘤直方图和纹理分析,全面评估从表观扩散系数(ADC)图中提取的定量参数在鉴别纤维上皮性肿瘤中的诊断价值。
这项回顾性研究纳入了66例接受术前磁共振成像的单发叶状肿瘤(PT)女性患者和29例单发纤维腺瘤(FA)女性患者。两名放射科医生基于ADC图独立进行全肿瘤直方图和纹理分析,提取了七个直方图参数和四个纹理参数。使用单因素分析比较提取的参数,以确定它们区分FA与PT、良性PT与FA以及良性PT与交界性和恶性PT的能力。
比较FA和PT时,PT的ADC值显著低于FA(p < 0.05),而PT的其他显著提取参数值显著高于FA(p≤0.001);显著参数组合的曲线下面积为0.936。关于FA与良性PT的差异,FA的ADC、ADC和ADC显著低于良性PT组,而ADC高于良性PT组(均p < 0.05)。此外,交界性和恶性PT组的ADC、ADC和所有纹理参数均显著高于FA和良性PT组(p < 0.05)。另外,恶性PT组的ADC显著低于交界性PT组(p = 0.045)。
从ADC图中提取的全肿瘤直方图和纹理特征可改善乳腺纤维上皮性肿瘤的鉴别诊断,并有助于为纤维上皮性肿瘤患者的临床管理做出最佳选择。