Advantages of time-dependent diffusion MRI for quantitative microstructural mapping in breast tumors.

IF 3.5 3区医学 Q2 ONCOLOGY

Frontiers in Oncology Pub Date : 2025-03-25 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1537529

Lei Bao, Sijie Li, Zhuo Wang, Yang Sun, Ying Qiu, Zhiwei Shen, Xiaoxiao Zhang, Xue Chen, Xiaoxiao Zhang, Junyu Zhang, Tiefeng Ji

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引用次数: 0

Abstract

Objectives: Time-dependent diffusion MRI (TD-MRI) can measure tumor tissue microstructure, but its effectiveness in differentiating benign from malignant breast tumors is unclear. This study aims to investigate the diagnostic value of TD-MRI microstructural features for distinguishing between benign and malignant breast tumors.

Methods: This prospective study included 44 patients with malignant breast tumors and 28 with benign tumors. All subjects underwent the IMPULSED protocol on a 3.0-T MRI scanner. Imaging data were analyzed using least squares fitting in MATLAB, yielding Dex (extracellular diffusivity), Vin (intracellular volume fraction), Dmean (cell diameter), Vin/Dmean, and ADC values. The molecular subtypes of breast cancer are classified based on immunohistochemistry (IHC) results.

Results: Malignant tumors exhibited significantly lower Dmean (17.37 ± 2.74 µm vs. 22.47 ± 3.85µm, p<0.0001), higher Vin (0.41 ± 0.13% vs. 0.19 ± 0.10%, p<0.0001), and higher Vin/Dmean (2.13 ± 0.66 vs. 0.93 ± 0.61, p<0.0001) compared to benign tumors. No significant difference was found in Dex (2.15 ± 0.28 um²/ms vs. 2.25 ± 0.31 um²/ms, p>0.05). Strong correlations were observed: positive between ADC and Dmean, and negative between ADC and both Vin and Vin/Dmean. AUC values for Vin (0.92; 95% CI: 0.86-0.99), and Vin/Dmean (0.91; 95% CI: 0.83-0.98) surpassed those for ADC.

Conclusion: TD-MRI microstructure mapping effectively differentiates benign from malignant breast tumors, highlighting its potential to improve diagnostic accuracy for lesions.

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时间依赖扩散MRI在乳腺肿瘤定量显微结构定位中的优势。

目的：时间依赖性弥散磁共振成像（TD-MRI）可测量肿瘤组织的微观结构，但其在区分良性和恶性乳腺肿瘤方面的有效性尚不明确。本研究旨在探讨 TD-MRI 微结构特征对区分良性和恶性乳腺肿瘤的诊断价值：这项前瞻性研究包括 44 名恶性乳腺肿瘤患者和 28 名良性肿瘤患者。所有受试者均在 3.0-T 磁共振成像扫描仪上接受了 IMPULSED 方案检查。使用 MATLAB 中的最小二乘法拟合分析了成像数据，得出了 Dex（细胞外扩散率）、Vin（细胞内体积分数）、Dmean（细胞直径）、Vin/Dmean 和 ADC 值。根据免疫组化（IHC）结果对乳腺癌分子亚型进行分类：结果：恶性肿瘤的 Dmean 值明显较低（17.37 ± 2.74 µm vs. 22.47 ± 3.85µm，pvs.0.19 ± 0.10%, pvs.0.93 ± 0.61，p2/ms vs. 2.25 ± 0.31 um2/ms，p>0.05）。观察到强烈的相关性：ADC 与 Dmean 之间为正相关，ADC 与 Vin 和 Vin/Dmean 之间为负相关。Vin（0.92；95% CI：0.86-0.99）和 Vin/Dmean （0.91；95% CI：0.83-0.98）的 AUC 值超过 ADC：结论：TD-MRI微结构成像能有效区分良性和恶性乳腺肿瘤，凸显了其提高病变诊断准确性的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research

CiteScore

6.20

自引率

10.60%

发文量

6641

审稿时长

14 weeks

期刊介绍： Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.