Lei Wu, Fan Liu, Sisi Li, Xinyi Luo, Yishi Wang, Wen Zhong, Thorsten Feiweier, Junzhong Xu, Haihua Bao, Diwei Shi, Hua Guo
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Time-dependent apparent diffusion coefficients (ADC) and microstructural parameters including cell diameter <b><i>d</i></b> , intracellular volume fraction <b><i>v<sub>in</sub></i> </b> , water exchange rate constant <b><i>k<sub>in</sub></i> </b> , and apparent extracellular diffusivity <b><i>D<sub>ex</sub></i> </b> were calculated. Single- and multi-variable logistic regression analyses were performed to evaluate their performance in identifying immunohistochemistry (IHC) factor status and molecular subtypes. The area under the receiver operating characteristic curve (AUC) was computed.</p><p><strong>Results: </strong>The multi-variable regression models generated from MR cytometry-derived metrics provided higher AUC compared to those from time-dependent ADC metrics, <i>i.e</i>. 0.744 <i>vs</i>. 0.645 for estrogen receptor (ER), 0.727 <i>vs</i>. 0.688 for progesterone receptor (PR), 0.734 <i>vs</i>.0.623 for HER2, and 0.679 <i>vs</i>. 0.633 for Ki67, 0.751 <i>vs</i>. 0.644 for Triple-Negative Breast Cancer (TNBC), 0.819 <i>vs</i>. 0.765 for HER2-enriched, 0.730 <i>vs</i>. 0.659 for Luminal A, 0.633 <i>vs</i>. 0.633 for Luminal B. MR cytometry with transcytolemmal water exchange (JOINT and EXCHANGE) outperformed the original one with the impermeable model (IMPULSED) in predicting PR (0.727 <i>vs</i>. 0.705), HER2 (0.734 <i>vs</i>. 0.689), Ki67 (0.679 <i>vs</i>. 0.646), TNBC (0.751 <i>vs</i>. 0.748) and HER2-enriched (0.819 <i>vs</i>. 0.739), Luminal A (0.730 <i>vs</i>. 0.666), Luminal B (0.633 <i>vs</i>. 0.630).</p><p><strong>Conclusions: </strong>MR cytometry outperformed conventional ADC measurements in clinical breast cancer subtyping. Incorporating transcytolemmal water exchange further enhanced classification accuracy.</p>","PeriodicalId":21034,"journal":{"name":"Radiology and Oncology","volume":" ","pages":"337-348"},"PeriodicalIF":2.2000,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12441884/pdf/","citationCount":"0","resultStr":"{\"title\":\"Comparison of MR cytometry methods in predicting immunohistochemical factor status and molecular subtypes of breast cancer.\",\"authors\":\"Lei Wu, Fan Liu, Sisi Li, Xinyi Luo, Yishi Wang, Wen Zhong, Thorsten Feiweier, Junzhong Xu, Haihua Bao, Diwei Shi, Hua Guo\",\"doi\":\"10.2478/raon-2025-0044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>First evaluation of the performance of MR cytometry incorporating transcytolemmal water exchange in predicting immunohistochemical factor status and molecular subtypes of breast cancer.</p><p><strong>Patients and methods: </strong>We prospectively enrolled 90 breast cancer patients in the study. For each participant, pulsed gradient spin-echo (PGSE) with diffusion time of 70 ms and oscillating gradient spin-echo (OGSE) diffusion-weighted imaging of 25 Hz and 50 Hz were performed on a 3T MRI scanner. Time-dependent apparent diffusion coefficients (ADC) and microstructural parameters including cell diameter <b><i>d</i></b> , intracellular volume fraction <b><i>v<sub>in</sub></i> </b> , water exchange rate constant <b><i>k<sub>in</sub></i> </b> , and apparent extracellular diffusivity <b><i>D<sub>ex</sub></i> </b> were calculated. Single- and multi-variable logistic regression analyses were performed to evaluate their performance in identifying immunohistochemistry (IHC) factor status and molecular subtypes. The area under the receiver operating characteristic curve (AUC) was computed.</p><p><strong>Results: </strong>The multi-variable regression models generated from MR cytometry-derived metrics provided higher AUC compared to those from time-dependent ADC metrics, <i>i.e</i>. 0.744 <i>vs</i>. 0.645 for estrogen receptor (ER), 0.727 <i>vs</i>. 0.688 for progesterone receptor (PR), 0.734 <i>vs</i>.0.623 for HER2, and 0.679 <i>vs</i>. 0.633 for Ki67, 0.751 <i>vs</i>. 0.644 for Triple-Negative Breast Cancer (TNBC), 0.819 <i>vs</i>. 0.765 for HER2-enriched, 0.730 <i>vs</i>. 0.659 for Luminal A, 0.633 <i>vs</i>. 0.633 for Luminal B. MR cytometry with transcytolemmal water exchange (JOINT and EXCHANGE) outperformed the original one with the impermeable model (IMPULSED) in predicting PR (0.727 <i>vs</i>. 0.705), HER2 (0.734 <i>vs</i>. 0.689), Ki67 (0.679 <i>vs</i>. 0.646), TNBC (0.751 <i>vs</i>. 0.748) and HER2-enriched (0.819 <i>vs</i>. 0.739), Luminal A (0.730 <i>vs</i>. 0.666), Luminal B (0.633 <i>vs</i>. 0.630).</p><p><strong>Conclusions: </strong>MR cytometry outperformed conventional ADC measurements in clinical breast cancer subtyping. 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引用次数: 0
摘要
背景：首次评估结合经细胞间膜水交换的MR细胞术在预测乳腺癌免疫组织化学因子状态和分子亚型方面的性能。患者和方法：我们前瞻性地纳入了90例乳腺癌患者。每个参与者在3T MRI扫描仪上进行扩散时间为70 ms的脉冲梯度自旋回波（PGSE）和25 Hz和50 Hz的振荡梯度自旋回波（OGSE）扩散加权成像。计算随时间变化的表观扩散系数（ADC）和微结构参数，包括细胞直径d、细胞内体积分数vin、水交换速率常数kin和细胞外表观扩散系数Dex。采用单变量和多变量logistic回归分析来评估它们在识别免疫组化（IHC）因子状态和分子亚型方面的性能。计算了接收机工作特性曲线下面积（AUC）。结果:与时间依赖性ADC指标相比，由MR细胞术衍生指标生成的多变量回归模型提供了更高的AUC，即雌激素受体（ER）为0.744 vs 0.645，孕激素受体（PR）为0.727 vs 0.688， HER2为0.734 vs.0.623， Ki67为0.679 vs. 0.633，三阴性乳腺癌（TNBC）为0.751 vs. 0.644， HER2丰富者为0.819 vs. 0.765， Luminal A为0.730 vs. 0.659，经细胞膜水交换（JOINT和exchange） MR细胞术在预测PR （0.727 vs. 0.705）、HER2 （0.734 vs. 0.689）、Ki67 （0.679 vs. 0.646）、TNBC （0.751 vs. 0.748）和HER2富集（0.819 vs. 0.739）、Luminal A （0.730 vs. 0.666）、Luminal B （0.633 vs. 0.630）方面优于原始的不渗透模型（pulsed）。结论：磁共振细胞术在临床乳腺癌分型中优于传统的ADC方法。结合经细胞乳水交换进一步提高了分类精度。
Comparison of MR cytometry methods in predicting immunohistochemical factor status and molecular subtypes of breast cancer.
Background: First evaluation of the performance of MR cytometry incorporating transcytolemmal water exchange in predicting immunohistochemical factor status and molecular subtypes of breast cancer.
Patients and methods: We prospectively enrolled 90 breast cancer patients in the study. For each participant, pulsed gradient spin-echo (PGSE) with diffusion time of 70 ms and oscillating gradient spin-echo (OGSE) diffusion-weighted imaging of 25 Hz and 50 Hz were performed on a 3T MRI scanner. Time-dependent apparent diffusion coefficients (ADC) and microstructural parameters including cell diameter d , intracellular volume fraction vin , water exchange rate constant kin , and apparent extracellular diffusivity Dex were calculated. Single- and multi-variable logistic regression analyses were performed to evaluate their performance in identifying immunohistochemistry (IHC) factor status and molecular subtypes. The area under the receiver operating characteristic curve (AUC) was computed.
Results: The multi-variable regression models generated from MR cytometry-derived metrics provided higher AUC compared to those from time-dependent ADC metrics, i.e. 0.744 vs. 0.645 for estrogen receptor (ER), 0.727 vs. 0.688 for progesterone receptor (PR), 0.734 vs.0.623 for HER2, and 0.679 vs. 0.633 for Ki67, 0.751 vs. 0.644 for Triple-Negative Breast Cancer (TNBC), 0.819 vs. 0.765 for HER2-enriched, 0.730 vs. 0.659 for Luminal A, 0.633 vs. 0.633 for Luminal B. MR cytometry with transcytolemmal water exchange (JOINT and EXCHANGE) outperformed the original one with the impermeable model (IMPULSED) in predicting PR (0.727 vs. 0.705), HER2 (0.734 vs. 0.689), Ki67 (0.679 vs. 0.646), TNBC (0.751 vs. 0.748) and HER2-enriched (0.819 vs. 0.739), Luminal A (0.730 vs. 0.666), Luminal B (0.633 vs. 0.630).
Conclusions: MR cytometry outperformed conventional ADC measurements in clinical breast cancer subtyping. Incorporating transcytolemmal water exchange further enhanced classification accuracy.
期刊介绍：
Radiology and Oncology is a multidisciplinary journal devoted to the publishing original and high quality scientific papers and review articles, pertinent to diagnostic and interventional radiology, computerized tomography, magnetic resonance, ultrasound, nuclear medicine, radiotherapy, clinical and experimental oncology, radiobiology, medical physics and radiation protection. Therefore, the scope of the journal is to cover beside radiology the diagnostic and therapeutic aspects in oncology, which distinguishes it from other journals in the field.
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