From the Department of Radiology (X.Z., Y.Q., W.J., Z.Y., J.S.), Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center (X.Z., Y.Q., W.J., Z.Y., Q.L., Y.L., J.S.), and Department of Pathology (Q.L., Y.L.), Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120, People's Republic of China; Department of Radiology, the First People's Hospital of Kashi Prefecture, Kashi, People's Republic of China (Y.Q.); Department of MR Scientific Marketing, Siemens Healthineers, Guangzhou, People's Republic of China (M.W., X.Y.); and Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, People's Republic of China (G.Y.).
Radiol Imaging Cancer. 2024 Jul;6(4):e230165. doi: 10.1148/rycan.230165.
Purpose To determine whether metrics from mean apparent propagator (MAP) MRI perform better than apparent diffusion coefficient (ADC) value in assessing the tumor-stroma ratio (TSR) status in breast carcinoma. Materials and Methods From August 2021 to October 2022, 271 participants were prospectively enrolled (ClinicalTrials.gov identifier: NCT05159323) and underwent breast diffusion spectral imaging and diffusion-weighted imaging. MAP MRI metrics and ADC were derived from the diffusion MRI data. All participants were divided into high-TSR (stromal component < 50%) and low-TSR (stromal component ≥ 50%) groups based on pathologic examination. Clinicopathologic characteristics were collected, and MRI findings were assessed. Logistic regression was used to determine the independent variables for distinguishing TSR status. The area under the receiver operating characteristic curve (AUC) and sensitivity, specificity, and accuracy were compared between the MAP MRI metrics, either alone or combined with clinicopathologic characteristics, and ADC, using the DeLong and McNemar test. Results A total of 181 female participants (mean age, 49 years ± 10 [SD]) were included. All diffusion MRI metrics differed between the high-TSR and low-TSR groups ( < .001 to = .01). Radial non-Gaussianity from MAP MRI and lymphovascular invasion were significant independent variables for discriminating the two groups, with a higher AUC (0.81 [95% CI: 0.74, 0.87] vs 0.61 [95% CI: 0.53, 0.68], < .001) and accuracy (138 of 181 [76%] vs 106 of 181 [59%], < .001) than that of the ADC. Conclusion MAP MRI may serve as a better approach than conventional diffusion-weighted imaging in evaluating the TSR of breast carcinoma. MR Diffusion-weighted Imaging, MR Imaging, Breast, Oncology ClinicalTrials.gov Identifier: NCT05159323 © RSNA, 2024.
旨在评估平均表观扩散系数（ADC）值与表观扩散系数（MAP）MRI 指标在评估乳腺癌肿瘤-基质比（TSR）状态方面的优劣。
2021 年 8 月至 2022 年 10 月，前瞻性纳入 271 名参与者（ClinicalTrials.gov 标识符：NCT05159323）并进行乳腺扩散光谱成像和扩散加权成像。从扩散 MRI 数据中得出 MAP MRI 指标和 ADC。所有参与者均根据病理检查分为高 TSR（基质成分＜50%）和低 TSR（基质成分≥50%）组。收集临床病理特征，评估 MRI 结果。使用逻辑回归确定区分 TSR 状态的独立变量。采用 DeLong 和 McNemar 检验比较 MAP MRI 指标（单独或与临床病理特征相结合）与 ADC 之间的受试者工作特征曲线（AUC）下面积、敏感性、特异性和准确性。
共纳入 181 名女性参与者（平均年龄 49 岁±10[标准差]）。高 TSR 和低 TSR 组之间的所有扩散 MRI 指标均有差异（<.001 至 =.01）。MAP MRI 径向非高斯性和脉管侵犯是区分两组的显著独立变量，具有更高的 AUC（0.81[95%CI：0.74，0.87]比 0.61[95%CI：0.53，0.68]，<.001）和准确性（181 例中有 138 例[76%]比 181 例中有 106 例[59%]，<.001），优于 ADC。
与常规扩散加权成像相比，MAP MRI 可能是评估乳腺癌 TSR 的更好方法。
磁共振弥散加权成像；磁共振成像；乳腺；肿瘤学
ClinicalTrials.gov 标识符：NCT05159323
©RSNA，2024
