Evidence map›Paper›PMID 42021417›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026

Time-dependent diffusion MRI as in vivo histology: microstructural biomarkers for breast cancer diagnosis and prognostic stratification.

Yu Zhou, Suyu Liu, Wei Chen, Wenbo Sun, Hao Mei, Xiaohui Chen, Jinfeng Lv, Xuan Li, Thorsten Feiweier, Ming Deng and 1 more

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Yu Zhou *Department of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Suyu Liu *Department of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Wei ChenMR Research Collaboration Team, Siemens Healthineers Ltd, Guangzhou, China.
Wenbo SunDepartment of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Hao MeiDepartment of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Xiaohui ChenDepartment of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Jinfeng LvDepartment of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Xuan LiDepartment of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
Thorsten FeiweierNeurology Applications Development, Siemens Healthcare GmbH, Erlangen, Germany.
Ming Deng *Department of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China. dr_dengming@whu.edu.cn.
Liying Xu *Department of Radiology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China. aying0923@foxmail.com.

Funding

and Technology Innovation Platform of Zhongnan Hospital, Wuhan University PTXM2025003the General Project of the Health Commission of Hubei Province WJ2025M141the Medical Science and Technology Innovation Platform of Zhongnan Hospital, Wuhan University PTXM2024015the National Natural Science Foundation of China no. 82172055
6 · The paper itself

Abstract

backgroundTime-dependent diffusion MRI (TD-dMRI) holds potential for characterizing tumor cell properties; however, its utility in diagnosing various breast lesions and evaluating Ki-67 expression remains unexplored. This study aimed to assess the utility of TD-dMRI for distinguishing benign breast lesions, ductal carcinoma in situ (DCIS) and invasive breast carcinoma (IBC), and correlating its derived parameters with molecular subtypes and histopathological features.

methodsThis retrospective study enrolled participants with breast lesions who underwent oscillating and pulsed gradient encoded TD-dMRI and conventional multi-parametric MRI from May 2024 to January 2025. The imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) model was used to extract microstructural parameters, including mean cell diameter (Dmean), cellularity, intracellular volume fraction (Vin), and extracellular diffusivity (Dex). Histopathological results (molecular subtypes, Nottingham grade, and Ki-67 index) served as the reference standard. Statistical analyses comprised receiver operating characteristic (ROC) curve analysis, correlation tests, and intergroup comparisons.

resultsThis study included 104 patients with 108 breast lesions. Significant differences were observed in TD-dMRI parameters among benign breast lesions, DCIS and IBC, and between high and low expression of Ki-67 (P < .05). IBC exhibited the highest cellularity (3.30 ± 0.77 μm− 1), the largest Dmean (10.26 ± 1.53 μm), the highest Vin (30.42% ± 7.33%), and the lowest ADC value (0.83 ± 0.10 × 10− 3mm2/s). High Ki-67 expression exhibited higher cellularity (3.38 ± 0.70 μm− 1), Dmean (10.51 ± 1.38 μm), Vin (31.10 ± 6.97%) and lower Dex (2.11 ± 0.22 µm2/ms) and ADC value (0.84 ± 0.11 × 10− 3mm2/s) compared to low Ki-67 expression. ADCDWI demonstrated the highest diagnostic performance in identifying benign lesions (AUC = 0.886) and IBC (AUC = 0.917). Vin showed considerable efficacy in distinguishing high Ki-67 expression from low Ki-67 expression (AUC = 0.801). Luminal B tumors displayed higher Dmean (10.63 ± 1.47 μm), Vin (31.48 ± 7.96%), lower ADC (0.82 ± 0.11 × 10− 3mm2/s) and Dex (2.07 ± 0.28 µm2/ms).

conclusionTD-dMRI noninvasively quantifies microstructural features of breast lesions, improving diagnostic accuracy and providing valuable correlations with molecular subtypes and proliferative activity, with promise for clinical translation in precision oncology.

trial registrationRegistry: Zhongnan Hospital of Wuhan University, TRN: 2,025,221 K, registration date: 27 August 2025, retrospectively registered.

Indexed as

Breast NeoplasmsCarcinoma, Intraductal, NoninfiltratingDiffusion Magnetic Resonance ImagingAdultAgedBiomarkers, TumorFemaleHumansKi-67 AntigenMiddle AgedPrognosisRetrospective StudiesBiomarkers, TumorKi-67 AntigenBreast lesionsDiagnostic performanceMicrostructural parametersMolecular subtypesTime-dependent diffusion MRI

Identifiers

PMID42021417
PMCPMC13235015

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.