Share:
Share this content in WeChat
X
Review
Advances in time-dependent diffusion MRI for noninvasive prediction of tumor molecular biomarkers
ZHAO Min  LI Xuemeng  WANG Aoyang  LIU Mengxiao  GAO Fei 

DOI:10.12015/issn.1674-8034.2026.01.034.


[Abstract] Time-dependent diffusion MRI (TDD-MRI) is an emerging noninvasive imaging technique with a unique capability for the quantitative interrogation of tissue and cellular microstructure. Pathological alterations in tumors are frequently accompanied by abnormalities in cellular microarchitecture, whereas conventional clinical assessments of tumor molecular biomarkers still largely depend on invasive procedures, which are limited by poor timeliness and difficulties in dynamic or longitudinal monitoring. The advent of TDD-MRI provides new opportunities for the noninvasive and in vivo evaluation of molecular biomarkers. Current studies suggest that TDD-MRI shows considerable potential in the assessment of tumor molecular biomarkers and may enable the characterization of differences in molecular mechanisms within the tumor microenvironment. However, TDD-MRI remains at an early stage of development. Major challenges include the absence of a standardized framework for parameter definitions, a lack of unified acquisition and analysis protocols, and insufficient integration with multimodal approaches such as radiomics. In this review, we systematically summarize recent advances in the application of TDD-MRI to tumor molecular biomarker evaluation, identify shared characteristics observed across studies within the same cancer type, and further analyze the sources of inter-study differences from the perspectives of parameter-specific mechanisms, tumor heterogeneity, and cross-cancer features. Finally, we delineate the limitations of current research and propose future directions to facilitate methodological standardization, expand cross-cancer applications, and promote clinical translation, thereby supporting the development of precision oncology.
[Keywords] time-dependent diffusion magnetic resonance imaging;oscillating gradient spin echo;biomarker;magnetic resonance imaging;tumor

ZHAO Min1   LI Xuemeng2   WANG Aoyang1   LIU Mengxiao3   GAO Fei4*  

1 Graduate School, Wannan Medical College, Wuhu 241000, China

2 Graduate School, Bengbu Medical University, Bengbu 233030, China

3 Research Cooperation Department, Siemens Healthineers Ltd., Shanghai 201318, China

4 Department of Radiology, the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital), Hefei 230001, China

Corresponding author: GAO F, E-mail: 15956912758@163.com

Conflicts of interest   None.

Received  2025-10-15
Accepted  2026-01-04
DOI: 10.12015/issn.1674-8034.2026.01.034
DOI:10.12015/issn.1674-8034.2026.01.034.

[1]
LOUIS D N, PERRY A, WESSELING P, et al. The 2021 WHO classification of tumors of the central nervous system: a summary[J]. Neuro Oncol, 2021, 23(8): 1231-1251. DOI: 10.1093/neuonc/noab106.
[2]
HU P, JIANG H X, WANG L, et al. Advances in artificial intelligence in the non-invasive diagnosis of molecular markers of glioma[J]. Chin J Exp Surg, 2024, 41(5): 1123-1128. DOI: 10.3760/cma.j.cn421213-20230327-00175.
[3]
WU S F, SUN M C, ZENG L L, et al. An assay for the rapid detection of EGFR and KRAS gene mutation in cancer[J]. Chin J Pathol, 2025, 54(1): 75-77. DOI: 10.3760/cma.j.cn112151-20240425-00283.
[4]
CANBERK S, ENGELS M. Cytology samples and molecular biomarker testing in lung cancer-advantages and challenges[J]. Virchows Arch, 2021, 478(1): 45-57. DOI: 10.1007/s00428-020-02995-2.
[5]
RAJAMOHAN N, KAPOOR H, KHURANA A, et al. MR imaging of penile pathology and prostheses[J]. Abdom Radiol, 2025, 50(1): 305-318. DOI: 10.1007/s00261-024-04417-2.
[6]
LEE Y, YOON S, PAEK M, et al. Advanced MRI techniques in abdominal imaging[J]. Abdom Radiol, 2024, 49(10): 3615-3636. DOI: 10.1007/s00261-024-04369-7.
[7]
LE BIHAN D, BRETON E, LALLEMAND D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders[J]. Radiology, 1986, 161(2): 401-407. DOI: 10.1148/radiology.161.2.3763909.
[8]
LE BIHAN D. What can we see with IVIM MRI [J/OL]. NeuroImage, 2019, 187: 56-67 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/29277647/. DOI: 10.1016/j.neuroimage.2017.12.062.
[9]
YANG C, WEI X Q, ZHENG J, et al. A correlative study between IVIM-DWI parameters and VEGF and MMPs expression in hepatocellular carcinoma[J]. Quant Imaging Med Surg, 2023, 13(3): 1887-1898. DOI: 10.21037/qims-22-271.
[10]
IIMA M. Perfusion-driven intravoxel incoherent motion (IVIM) MRI in oncology: applications, challenges, and future trends[J]. Magn Reson Med Sci, 2021, 20(2): 125-138. DOI: 10.2463/mrms.rev.2019-0124.
[11]
SU Y, QIU Y, HUANG X K, et al. Benign and malignant breast lesions: differentiation using microstructural metrics derived from time-dependent diffusion MRI[J/OL]. Radiol Imaging Cancer, 2025, 7(3): e240287 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/40214515/. DOI: 10.1148/rycan.240287.
[12]
EJIMA F, FUKUKURA Y, KAMIMURA K, et al. Oscillating gradient diffusion-weighted MRI for risk stratification of uterine endometrial cancer[J]. J Magn Reson Imaging, 2024, 60(1): 67-77. DOI: 10.1002/jmri.29106.
[13]
ZHANG X L, WANG J. Advances in diffusion MRI based on oscillating gradient spin echo[J]. Chin J Magn Reson Imag, 2023, 14(9): 198-202. DOI: 10.12015/issn.1674-8034.2023.09.036.
[14]
LI Y W, CHEN X L. Advances in time-dependent diffusion MRI for tumor diagnosis and treatment response evaluation[J]. Chin J Magn Reson Imag, 2025, 16(3): 228-234. DOI: 10.12015/issn.1674-8034.2025.03.039.
[15]
BA R C, WANG X X, ZHANG Z L, et al. Diffusion-time dependent diffusion MRI: effect of diffusion-time on microstructural mapping and prediction of prognostic features in breast cancer[J]. Eur Radiol, 2023, 33(9): 6226-6237. DOI: 10.1007/s00330-023-09623-y.
[16]
PENG S Y, SUN P, LIU J, et al. Imaging microstructural parameters of breast tumor in patient using time-dependent diffusion: a feasibility study[J/OL]. Diagnostics, 2025, 15(7): 823 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/40218173/. DOI: 10.3390/diagnostics15070823.
[17]
WU D, JIANG K W, LI H, et al. Time-dependent diffusion MRI for quantitative microstructural mapping of prostate cancer[J]. Radiology, 2022, 303(3): 578-587. DOI: 10.1148/radiol.211180.
[18]
XU J Z. Probing neural tissues at small scales: Recent progress of oscillating gradient spin echo (OGSE) neuroimaging in humans[J/OL]. J Neurosci Methods, 2021, 349: 109024 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/33333089/. DOI: 10.1016/j.jneumeth.2020.109024.
[19]
JIANG X Y, LI H, XIE J P, et al. Quantification of cell size using temporal diffusion spectroscopy[J]. Magn Reson Med, 2016, 75(3): 1076-1085. DOI: 10.1002/mrm.25684.
[20]
WANG X Y, ZHANG Y, CHENG J L, et al. Microstructural diffusion MRI for differentiation of breast tumors and prediction of prognostic factors in breast cancer[J/OL]. Front Oncol, 2025, 15: 1498691 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/40110196/. DOI: 10.3389/fonc.2025.1498691.
[21]
WU D, ZHANG J Y. Evidence of the diffusion time dependence of intravoxel incoherent motion in the brain[J]. Magn Reson Med, 2019, 82(6): 2225-2235. DOI: 10.1002/mrm.27879.
[22]
ZHAO Y, ZHAO F, CHENG M, et al. Risk stratification prediction of endometrial cancer using microstructural mapping based on time-dependent diffusion MRI[J]. Cancer Sci, 2025, 116(6): 1627-1637. DOI: 10.1111/cas.70036.
[23]
LI X, YI Y Q, WU Y L, et al. Conventional, time-dependent, and continuous-time random-walk diffusion-weighted imaging models in microstructural characterization of breast lesions at 3.0T: a prospective analysis[J/OL]. Med Phys, 2025, 52(9): e17960 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/40908518/. DOI: 10.1002/mp.17960.
[24]
CAO Y W, LU Y, SHAO W H, et al. Time-dependent diffusion MRI-based microstructural mapping for differentiating high-grade serous ovarian cancer from serous borderline ovarian tumor[J/OL]. Eur J Radiol, 2024, 178: 111622 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/39018648/. DOI: 10.1016/j.ejrad.2024.111622.
[25]
PANAGIOTAKI E, WALKER-SAMUEL S, SIOW B, et al. Noninvasive quantification of solid tumor microstructure using VERDICT MRI[J]. Cancer Res, 2014, 74(7): 1902-1912. DOI: 10.1158/0008-5472.CAN-13-2511.
[26]
REYNAUD O, WINTERS K V, HOANG D M, et al. Pulsed and oscillating gradient MRI for assessment of cell size and extracellular space (POMACE) in mouse gliomas[J]. NMR Biomed, 2016, 29(10): 1350-1363. DOI: 10.1002/nbm.3577.
[27]
CATALANO O A, HORN G L, SIGNORE A, et al. PET/MR in invasive ductal breast cancer: correlation between imaging markers and histological phenotype[J]. Br J Cancer, 2017, 116(7): 893-902. DOI: 10.1038/bjc.2017.26.
[28]
WANG X X, BA R C, HUANG Y, et al. Time-dependent diffusion MRI helps predict molecular subtypes and treatment response to neoadjuvant chemotherapy in breast cancer[J/OL]. Radiology, 2024, 313(1): e240288 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/39436292/. DOI: 10.1148/radiol.240288.
[29]
WANG X X, HUANG Y, CAO Y, et al. Time-dependent diffusion MRI-based microstructural mapping for characterizing HER2-zero, -low, -ultra-low, and-positive breast cancer[J]. J Magn Reson Imaging, 2025, 62(6): 1754-1767. DOI: 10.1002/jmri.70074.
[30]
SINGH G, MANJILA S, SAKLA N, et al. Radiomics and radiogenomics in gliomas: a contemporary update[J]. Br J Cancer, 2021, 125(5): 641-657. DOI: 10.1038/s41416-021-01387-w.
[31]
INCHINGOLO R, MAINO C, CANNELLA R, et al. Radiomics in colorectal cancer patients[J]. World J Gastroenterol, 2023, 29(19): 2888-2904. DOI: 10.3748/wjg.v29.i19.2888.
[32]
LU Z J, YANG J, FENG Y, et al. Integrated proteomics and transcriptomics analysis reveals key regulatory genes between ER-positive/PR-positive and ER-positive/PR-negative breast cancer[J/OL]. BMC Cancer, 2025, 25(1): 1048 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/40597935/. DOI: 10.1186/s12885-025-14451-y.
[33]
JIANG X Y, LI H, DEVAN S P, et al. MR cell size imaging with temporal diffusion spectroscopy[J/OL]. Magn Reson Imaging, 2021, 77: 109-123 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/33338562/. DOI: 10.1016/j.mri.2020.12.010.
[34]
SHI D W, WANG X X, LI S S, et al. Comprehensive characterization of tumor therapeutic response via simultaneous mapping of cell size, density, and transcytolemmal water exchange[J/OL]. Magn Reson Imag, 2025, 122: 110433 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/40460946/. DOI: 10.1016/j.mri.2025.110433.
[35]
JIANG X Y, DEVAN S P, XIE J P, et al. Improving MR cell size imaging by inclusion of transcytolemmal water exchange[J/OL]. NMR Biomed, 2022, 35(12): e4799 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/35794795/. DOI: 10.1002/nbm.4799.
[36]
WU L, LIU F, LI S S, et al. Comparison of MR cytometry methods in predicting immunohistochemical factor status and molecular subtypes of breast cancer[J]. Radiol Oncol, 2025, 59(3): 337-348. DOI: 10.2478/raon-2025-0044.
[37]
BAI J, QI Q R, LI Y, et al. Estrogen receptors and estrogen-induced uterine vasodilation in pregnancy[J/OL]. Int J Mol Sci, 2020, 21(12): 4349 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/32570961/. DOI: 10.3390/ijms21124349.
[38]
SCHULER L A, MURDOCH F E. Endogenous and therapeutic estrogens: maestro conductors of the microenvironment of ER+ breast cancers[J/OL]. Cancers, 2021, 13(15): 3725 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/34359625/. DOI: 10.3390/cancers13153725.
[39]
ZHANG A L, WANG X J, FAN C F, et al. The role of Ki67 in evaluating neoadjuvant endocrine therapy of hormone receptor-positive breast cancer[J/OL]. Front Endocrinol, 2021, 12: 687244 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/34803903/. DOI: 10.3389/fendo.2021.687244.
[40]
OSADA Y, SAITO R, SHIBAHARA I, et al. H3K27M and TERT promoter mutations are poor prognostic factors in surgical cases of adult thalamic high-grade glioma[J/OL]. Neurooncol Adv, 2021, 3(1): vdab038 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/34013205/. DOI: 10.1093/noajnl/vdab038.
[41]
ZHAO J X, YANG S X, CUI X T, et al. A novel compound EPIC-0412 reverses temozolomide resistance via inhibiting DNA repair/MGMT in glioblastoma[J]. Neuro Oncol, 2023, 25(5): 857-870. DOI: 10.1093/neuonc/noac242.
[42]
ZHANG H X, LIU K Y, BA R C, et al. Histological and molecular classifications of pediatric glioma with time-dependent diffusion MRI-based microstructural mapping[J]. Neuro Oncol, 2023, 25(6): 1146-1156. DOI: 10.1093/neuonc/noad003.
[43]
WANG Y, FENG L L, JI P G, et al. Clinical features and molecular markers on diffuse midline gliomas with H3K27M mutations: a 43 cases retrospective cohort study[J/OL]. Front Oncol, 2021, 10: 602553 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/33659209/. DOI: 10.3389/fonc.2020.602553.
[44]
LIANG X J, ZHANG Y, FU Y G, et al. Feasibility of time-dependent diffusion MRI-based indicators for identifying MGMT promoter methylation in glioblastomas[J]. Chin J Magn Reson Imag, 2024, 15(11): 67-74. DOI: 10.12015/issn.1674-8034.2024.11.011.
[45]
SHI Z F, LI K K, LIU A P, et al. Rare pediatric cerebellar high-grade gliomas mimic medulloblastomas histologically and transcriptomically and show p53 mutations[J/OL]. Cancers, 2024, 16(1): 232 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/38201659/. DOI: 10.3390/cancers16010232.
[46]
Tunthanathip T, Sangkhathat S, Tanvejsilp P, et al. Prognostic impact of the combination of MGMT methylation and TERT promoter mutation in glioblastoma[J/OL]. J Neurosci Rural Pract, 2021 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/34744391/. DOI: 10.1055/s-0041-1735821.
[47]
SYLVIA M T, KUMAR S, DASARI P. The expression of immunohistochemical markers estrogen receptor, progesterone receptor, Her-2-neu, p53 and Ki-67 in epithelial ovarian tumors and its correlation with clinicopathologic variables[J]. Indian J Pathol Microbiol, 2012, 55(1): 33-37. DOI: 10.4103/0377-4929.94852.
[48]
YANG Z H, YANG X, LIU X Y, et al. Clinical characteristics and prognostic characterization of endometrial carcinoma: a comparative analysis of molecular typing protocols[J/OL]. BMC Cancer, 2023, 23(1): 243 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/36918828/. DOI: 10.1186/s12885-023-10706-8.
[49]
BACON E R, IHLE K, GUO W H, et al. Tumor heterogeneity and clinically invisible micrometastases in metastatic breast cancer-a call for enhanced surveillance strategies[J/OL]. NPJ Precis Oncol, 2024, 8(1): 81 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/38553598/. DOI: 10.1038/s41698-024-00572-3.
[50]
BATEMAN N W, ABULEZ T, SOLTIS A R, et al. Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities[J/OL]. NPJ Precis Oncol, 2024, 8(1): 68 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/38480868/. DOI: 10.1038/s41698-024-00519-8.
[51]
DI PALMA T, ZANNINI M. PAX8 as a potential target for ovarian cancer: what we know so far[J/OL]. Onco Targets Ther, 2022, 15: 1273-1280 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/36275185/. DOI: 10.2147/OTT.S361511.
[52]
LEI Z N, TENG Q X, WU Z X, et al. Overcoming multidrug resistance by knockout of ABCB1 gene using CRISPR/Cas9 system in SW620/Ad300 colorectal cancer cells[J]. MedComm, 2021, 2(4): 765-777. DOI: 10.1002/mco2.106.
[53]
RICHIARDONE E, ROUMI R AL, LARDINOIS F, et al. MCT1-dependent lactate recycling is a metabolic vulnerability in colorectal cancer cells upon acquired resistance to anti-EGFR targeted therapy[J/OL]. Cancer Lett, 2024, 598: 217091 [2025-10-14]. https://pubmed.ncbi.nlm.nih.gov/38964730/. DOI: 10.1016/j.canlet.2024.217091.
[54]
JIANG X Y, LI H, XIE J P, et al. In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy[J]. Magn Reson Med, 2017, 78(1): 156-164. DOI: 10.1002/mrm.26356.

PREV Progress in clinical applications of MRI based on electromagnetic metamaterials
NEXT Multinuclear magnetic resonance imaging in oncology: research progress
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn