Share:
Share this content in WeChat
X
Review
Research progress in the application of diffusion-weighted imaging in hematological malignancies
BAI Haoxue  NIU Jinliang 

DOI:10.12015/issn.1674-8034.2025.11.035.


[Abstract] Hematological malignancies mainly include lymphoma, leukemia and multiple myeloma. The characteristics of their tumor cells not being restricted by tissue barriers and thus easily invading multiple organs, as well as the tumor heterogeneity caused by multiple gene mutations, pose challenges to the diagnosis and treatment of hematological malignancies. Diffusion weighted imaging (DWI) is a commonly used magnetic resonance functional imaging technique in clinical practice. The quantitative parameter apparent diffusion coefficient value can reflect the local cell density changes caused by tumor cell proliferation and the resulting abnormal water molecule diffusion in the early stage. In addition, whole-body diffusion weighted imaging technology can detect tiny lesions that are easily overlooked in conventional imaging examinations. In recent years, its related technologies include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion tensor imaging imaging (DTI) and time-dependent diffusion MRI (TDD-MRI) techniques have made significant progress in the tumors themselves of malignant hematological diseases and the organs involved throughout the body. Although DWI has become an important imaging tool in clinical practice due to its high sensitivity and specificity in detecting bone marrow infiltration and extramedullary lesions, most existing studies focus on a single technique and lack in-depth summaries of the comprehensive application of DWI technology in various hematological malignancies. This article focuses on discussing the correlation between quantitative parameters of DWI and the early diagnosis, therapeutic effect evaluation and prognosis of hematological malignancies, and analyzes the limitations of current research.
[Keywords] diffusion weighted imaging;intravoxel incoherent motion;diffusion kurtosis imaging;diffusion tensor imaging;hematological malignancies;leukemia;lymphoma;multiple myeloma

BAI Haoxue1   NIU Jinliang2*  

1 School of Medical Imaging, Shanxi Medical University, Taiyuan 030000, China

2 Department of Imaging, the Second Hospital of Shanxi Medical University, Taiyuan 030000, China

Corresponding author: NIU J L, E-mail: sxlscjy@163.com

Conflicts of interest   None.

Received  2025-07-14
Accepted  2025-10-24
DOI: 10.12015/issn.1674-8034.2025.11.035
DOI:10.12015/issn.1674-8034.2025.11.035.

[1]
HUANG S M, WAN C L, WU D P, et al. Progress in application of evaluation methods of treatment tolerance for hematological malignancies[J]. China Cancer, 2025, 34(1): 73-80. DOI: 10.11735/j.issn.1004-0242.2025.01.A012.
[2]
LI Q Y, ZHANG X Y, KE R Q. Spatial transcriptomics for tumor heterogeneity analysis[J/OL]. Front Genet, 2022, 13: 906158 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/35899203/. DOI: 10.3389/fgene.2022.906158.
[3]
CAO L X, CHEN Z P, CHEN X D, et al. Technical advances in diffusion weighted imaging[J]. Chin J CT MRI, 2024, 22(9): 173-176. DOI: 10.3969/j.issn.1672-5131.2024.09.056.
[4]
FUJIWARA S, OGASAWARA K, CHIDA K, et al. Feasibility of diffusion-weighted imaging (DWI) for assessing cerebrospinal fluid dynamics: DWI-fluidography in the brains of healthy subjects[J]. Magn Reson Med Sci, 2025, 24(2): 166-175. DOI: 10.2463/mrms.mp.2022-0152.
[5]
WU Y Y, YE Z, YANG T, et al. Simultaneous multislice echo-planar diffusion-weighted imaging (DWI) in patients with focal liver lesions: a comparative study with conventional DWI[J]. Quant Imaging Med Surg, 2024, 14(9): 6684-6697. DOI: 10.21037/qims-24-341.
[6]
ALYAMI A S. Current update on DWI-MRI and its radiomics in liver fibrosis-a review of the literature[J/OL]. Tomography, 2025, 11(6): 63 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/40560009/. DOI: 10.3390/tomography11060063.
[7]
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.
[8]
SHEN P X, TAN Y. Research progress in predicting molecular typing of lower grade glioma by functional magnetic resonance imaging[J]. Chin J Magn Reson Imag, 2023, 14(2): 168-173. DOI: 10.12015/issn.1674-8034.2023.02.030.
[9]
WANG M, LIU Y, WANG Y L, et al. Diagnostic value of whole-body diffusion weighted imaging in multiple myeloma[J]. J Hebei Med Univ, 2022, 43(2): 198-202. DOI: 10.3969/j.issn.1007-3205.2022.02.015.
[10]
XIA Z Y, MO X X, WANG C S, et al. The clinical value of IVIM-DWI imaging in diagnosis of multiple myeloma[J]. J Clin Radiol, 2025, 44(9): 1739-1743. DOI: 10.13437/j.cnki.jcr.2025.09.021.
[11]
ZHANG B, ZHANG L, BIAN B Y, et al. Diagnostic value of WB-DWI versus 18F-FDG PET/CT for the detection of multiple myeloma[J]. Indian J Cancer, 2023, 60(3): 303-309. DOI: 10.4103/ijc.IJC_1129_20.
[12]
ZHAO X F. Application and clinical guidance value of whole body diffusion weighted imaging scanning in tumor diagnosis[J]. China Med Pharm, 2021, 11(11): 169-172. DOI: 10.3969/j.issn.2095-0616.2021.11.044.
[13]
WU F Y, LIU Y K, JIANG C P, et al. Progress in diagnosis and treatment of whole-body magnetic resonance imaging in hematologic malignancies[J]. Chin J Magn Reson Imag, 2025, 16(1): 228-234. DOI: 10.12015/issn.1674-8034.2025.01.037.
[14]
LIU J, ZHAO X. Analysis of the clinical value of apparent diffusion coefficient diffusion-weighted imaging with different b values in the differential diagnosis of rectal tumors[J]. J Pract Med Imag, 2023, 24(5): 342-345. DOI: 10.16106/j.cnki.cn14-1281/r.2023.05.005.
[15]
HUANG X M, XU X, SUN Y F, et al. Ultra-high b value DWI in distinguishing fresh gray matter ischemic lesions from white matter ones: a comparative study with routine and high b value DWI[J]. Quant Imaging Med Surg, 2021, 11(11): 4583-4593. DOI: 10.21037/qims-20-1241.
[16]
CUI J N, ZHENG J, NIU W R, et al. Quantitative IVIM parameters evaluating perfusion changes in brain parenchyma in patients newly diagnosed with acute leukemia: Compared with healthy participants[J/OL]. Front Neurol, 2023, 14: 1093003 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/36816571/. DOI: 10.3389/fneur.2023.1093003.
[17]
YANG W Y, ZHU X F. Present situation and prospect of diagnosis and treatment of acute leukemia in children in China[J]. Chinese Medical Journal, 2024(27): 2477-2482. DOI: 10.3760/cma.j.cn112137-20231211-01347.
[18]
KIM E H, IM S A, LEE J W, et al. Extramedullary infiltration in pediatric acute myeloid leukemia on surveillance magnetic resonance imaging and its relationship with established risk factors[J/OL]. J Pediatr Hematol Oncol, 2022, 44(3): e713-e718 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/35319510/. DOI: 10.1097/MPH.0000000000002353.
[19]
DONNERS R, YIIN R S Z, KOH D M, et al. Whole-body diffusion-weighted MRI in lymphoma-comparison of global apparent diffusion coefficient histogram parameters for differentiation of diseased nodes of lymphoma patients from normal lymph nodes of healthy individuals[J]. Quant Imaging Med Surg, 2021, 11(8): 3549-3561. DOI: 10.21037/qims-21-50.
[20]
DE PAEPE K N, VAN KEERBERGHEN C A, AGAZZI G M, et al. Quantitative whole-body diffusion-weighted MRI after one treatment cycle for aggressive non-Hodgkin lymphoma is an independent prognostic factor of outcome[J/OL]. Radiol Imaging Cancer, 2021, 3(2): e200061 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/33817648/. DOI: 10.1148/rycan.2021200061.
[21]
TALARICO M, BARBATO S, CATTABRIGA A, et al. Diagnostic Innovations: Advances in imaging techniques for diagnosis and follow-up of multiple myeloma[J/OL]. J Bone Oncol, 2025, 51: 100669 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/40124904/. DOI: 10.1016/j.jbo.2025.100669.
[22]
RODRÍGUEZ-LAVAL V, LUMBRERAS-FERNÁNDEZ B, AGUADO-BUENO B, et al. Imaging of multiple myeloma: present and future[J/OL]. J Clin Med, 2024, 13(1): 264 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/38202271/. DOI: 10.3390/jcm13010264.
[23]
CHAKRABORTY R, HILLENGASS J, LENTZSCH S. How do we image patients with multiple myeloma and precursor states?[J]. Br J Haematol, 2023, 203(4): 536-545. DOI: 10.1111/bjh.18880.
[24]
QIAN X D, YAO S L, GUAN J. Progress on clinical application of whole-body diffusion weighted imaging in multiple myeloma[J]. J Clin Med Pract, 2020, 24(1): 19-23. DOI: 10.7619/jcmp.202001005.
[25]
LI P, WANG G Q. Application value of WB-DWI in the diagnosis and efficacy evaluation of newly-diagnosed multiple myeloma[J]. Chin J CT MRI, 2021, 19(3): 148-150, 170. DOI: 10.3969/j.issn.1672-5131.2021.03.049.
[26]
DONG H Z, HUANG W Y, JI X D, et al. Prediction of early treatment response in multiple myeloma using MY-RADS total burden score, ADC, and fat fraction from whole-body MRI: impact of Anemia on predictive performance[J]. AJR Am J Roentgenol, 2022, 218(2): 310-319. DOI: 10.2214/AJR.21.26534.
[27]
TAKASU M, KONDO S, AKIYAMA Y, et al. Assessment of early treatment response on MRI in multiple myeloma: Comparative study of whole-body diffusion-weighted and lumbar spinal MRI[J/OL]. PLoS One, 2020, 15(2): e0229607 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/32106239/. DOI: 10.1371/journal.pone.0229607.
[28]
WANG L Y, LI X Z, LI Y, et al. Lumbar spine marrow MR T1 mapping radiomics for predicting clinical risk of acute lymphoblastic leukemia in children[J]. Chin J Med Imag Technol, 2024, 40(9): 1284-1288. DOI: 10.13929/j.issn.1003-3289.2024.09.002.
[29]
HOU M D, HUANG Y N, YAN J S, et al. Quantitative Dixon and intravoxel incoherent motion diffusion magnetic resonance imaging parameters in lumbar vertebrae for differentiating aplastic Anemia and acute myeloid leukemia[J/OL]. Front Oncol, 2023, 13: 1277978 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/38111525/. DOI: 10.3389/fonc.2023.1277978.
[30]
WANG L, ZHANG X Q, YANG S, et al. Diagnostic value of functional magnetic resonance DWI in lymph node metastasis of upper abdominal tumor[J]. Chin J CT MRI, 2021, 19(7): 134-137. DOI: 10.3969/j.issn.1672-5131.2021.07.043.
[31]
ZHANG Y, LUO D H, GUO W, et al. Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy[J]. Jpn J Radiol, 2023, 41(7): 712-722. DOI: 10.1007/s11604-023-01399-x.
[32]
WANG Y, NIU J L, ZHANG L C, et al. Study on bone marrow microstructure of acute myeloid leukemia by IVIM-DWI[J]. J Imag Res Med Appl, 2019, 3(1): 46-47. DOI: 10.3969/j.issn.2096-3807.2019.01.025.
[33]
FAN R, ZHU H, NIU J L, et al. Correlation of histological marrow characteristics and intravoxel incoherent motion-derived parameters in benign and malignant hematological disorders[J/OL]. Eur J Radiol, 2020, 123: 108745 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/31899061/. DOI: 10.1016/j.ejrad.2019.108745.
[34]
LI J T, LI W J, NIU J L, et al. Intravoxel incoherent motion diffusion-weighted MRI of infiltrated marrow for predicting overall survival in newly diagnosed acute myeloid leukemia[J]. Radiology, 2020, 295(1): 155-161. DOI: 10.1148/radiol.2020191693.
[35]
LI J, WANG Q, XUE H D, et al. Application progress of MRI in the prognostic prediction of multiple myeloma[J]. Chin J Magn Reson Imag, 2023, 14(8): 192-196. DOI: 10.12015/issn.1674-8034.2023.08.034.
[36]
BIAN W J, HUANG Q Q, ZHANG J L, et al. Intravoxel incoherent motion diffusion-weighted MRI for the evaluation of early spleen involvement in acute leukemia[J]. Quant Imaging Med Surg, 2024, 14(1): 98-110. DOI: 10.21037/qims-23-856.
[37]
BIAN W J, ZHANG J L, HUANG Q Q, et al. Quantitative tumor burden imaging parameters of the spleen at MRI for predicting treatment response in patients with acute leukemia[J/OL]. Heliyon, 2023, 9(10): e20348 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/37810872/. DOI: 10.1016/j.heliyon.2023.e20348.
[38]
ZHANG H, HU L, QIN F H, et al. Synthetic MRI and diffusion-weighted imaging for differentiating nasopharyngeal lymphoma from nasopharyngeal carcinoma: combination with morphological features[J]. Br J Radiol, 2024, 97(1159): 1278-1285. DOI: 10.1093/bjr/tqae095.
[39]
YU X P, HOU J, LI F P, et al. Intravoxel incoherent motion diffusion weighted magnetic resonance imaging for differentiation between nasopharyngeal carcinoma and lymphoma at the primary site[J]. J Comput Assist Tomogr, 2016, 40(3): 413-418. DOI: 10.1097/RCT.0000000000000391.
[40]
LIAO C C, QIN Y Y, TANG Q, et al. Multi-b value diffusion-weighted magnetic resonance imaging and intravoxel incoherent motion modeling: Differentiation of aggressive lymphoma lesions on initial treatment and activity assessment after chemotherapy[J/OL]. Medicine (Baltimore), 2019, 98(6): e14459 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/30732212/. DOI: 10.1097/MD.0000000000014459.
[41]
JO A, JUNG J Y, LEE S Y, et al. Prognosis prediction in initially diagnosed multiple myeloma patients using intravoxel incoherent motion-diffusion weighted imaging and multiecho Dixon imaging[J]. J Magn Reson Imaging, 2021, 53(2): 491-501. DOI: 10.1002/jmri.27321.
[42]
FERRAZZOLI V, MINOSSE S, PICCHI E, et al. Multiparametric MRI in primary cerebral lymphoma: Correlation between diffusion kurtosis imaging (DKI), dynamic contrast enhanced (DCE) and dynamic Susceptibility contrast (DSC) MRI techniques[J/OL]. Phys Med, 2025, 129: 104864 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/39631134/. DOI: 10.1016/j.ejmp.2024.104864.
[43]
CUI Y Y, WANG X H, WANG Y, et al. Restriction spectrum imaging and diffusion kurtosis imaging for assessing proliferation status in rectal carcinoma[J]. Acad Radiol, 2025, 32(1): 201-209. DOI: 10.1016/j.acra.2024.08.021.
[44]
LU J Y, ZHOU C, PU J L, et al. Brain microstructural changes in essential tremor patients and correlations with clinical characteristics: a diffusion kurtosis imaging study[J]. J Neurol, 2023, 270(4): 2106-2116. DOI: 10.1007/s00415-023-11557-w.
[45]
HUANG S H, HUANG C X, LI M J, et al. White matter abnormalities and cognitive deficit after mild traumatic brain injury: comparing DTI, DKI, and NODDI[J/OL]. Front Neurol, 2022, 13: 803066 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/35359646/. DOI: 10.3389/fneur.2022.803066.
[46]
FOLLIN C, SVÄRD D, VAN WESTEN D, et al. Microstructural white matter alterations associated to neurocognitive deficits in childhood leukemia survivors treated with cranial radiotherapy - a diffusional kurtosis study[J]. Acta Oncol, 2019, 58(7): 1021-1028. DOI: 10.1080/0284186X.2019.1571279.
[47]
YIN H, YAN C X. The progress of diffusion-kurtosis imaging in the assessment of nervous system diseases[J]. Geriatr Res, 2024, 5(4): 22-26. DOI: 10.3969/j.issn.2096-9058.2024.04.005.
[48]
WANG X Q, LIU L F. Clinical analysis of 102 cases of head and neck lymphoma[J]. J Clin Otorhinolaryngol Head Neck Surg, 2020, 34(2): 177-180. DOI: 10.13201/j.issn.1001-1781.2020.02.019.
[49]
GAO B, WANG X B, PAN X Y, et al. Diagnostic value of diffusion kurtosis imaging in head and neck lymphoma[J]. J China Clin Med Imag, 2020, 31(8): 563-567. DOI: 10.12117/jccmi.2020.08.009.
[50]
LIU L H, ZHANG H W, ZHANG H B, et al. Distinctive magnetic resonance imaging features in primary central nervous system lymphoma: a case report[J]. World J Radiol, 2023, 15(9): 274-280. DOI: 10.4329/wjr.v15.i9.274.
[51]
XIE S H, LANG R, LI B, et al. Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI[J]. Neuroradiology, 2023, 65(1): 55-64. DOI: 10.1007/s00234-022-03000-0.
[52]
PANG H P, DANG X F, REN Y, et al. Diffusion kurtosis imaging differs between primary central nervous system lymphoma and high-grade glioma and is correlated with the diverse nuclear-to-cytoplasmic ratio: a histopathologic, biopsy-based study[J]. Eur Radiol, 2020, 30(4): 2125-2137. DOI: 10.1007/s00330-019-06544-7.
[53]
WU R, SUO S T, WU L M, et al. Assessment of chemotherapy response in non-Hodgkin lymphoma involving the neck utilizing diffusion kurtosis imaging: a preliminary study[J]. Diagn Interv Radiol, 2017, 23(3): 245-249. DOI: 10.5152/dir.2017.16184.
[54]
WANG F Q, CHEN Y H, SUN Y, et al. A preliminary study on quantitative parameter prediction of HIF-1α in pancreatic ductal adenocarcinoma using diffusion kurtosis imaging[J]. Chin J Magn Reson Imag, 2025, 16(5): 37-43. DOI: 10.12015/issn.1674-8034.2025.05.006.
[55]
FANG J G, LIU B, CHEN L J, et al. ROC analysis of PET-like imaging based on DKI sequence in the diagnosis of multiple myeloma[J]. China Foreign Med Treat, 2019, 38(4): 178-180, 192. DOI: 10.16662/j.cnki.1674-0742.2019.04.178.
[56]
JIANG Y L, LI J, ZHANG P F, et al. Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models[J]. World J Gastroenterol, 2024, 30(9): 1164-1176. DOI: 10.3748/wjg.v30.i9.1164.
[57]
ZHAO K, MA X Y, CHENG J L, et al. The value of DKI and DTI in the differential diagnosis of low-grade gliomas and encephalitis[J]. Chin J Magn Reson Imag, 2024, 15(2): 1-6, 55. DOI: 10.12015/issn.1674-8034.2024.02.001.
[58]
WANG G J. Application and progress of magnetic resonance DTI in central nervous system diseases[J]. China Med Devices, 2024, 39(2): 171-178. DOI: 10.3969/j.issn.1674-1633.2024.02.029.
[59]
MA L, ZENG S Y, FANG X M. Research progress in the diffusion tensor imaging of white matter microstructural abnormalities in patients with cerebral small vessel disease-related cognitive impairment[J]. Int J Med Radiol, 2023, 46(3): 289-292, 298. DOI: 10.19300/j.2023.Z20306.
[60]
WÜRTEMBERGER U, DIEBOLD M, RAU A, et al. Advanced diffusion imaging reveals microstructural characteristics of primary CNS lymphoma, allowing differentiation from glioblastoma[J/OL]. Neurooncol Adv, 2024, 6(1): vdae093 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/38946879/. DOI: 10.1093/noajnl/vdae093.
[61]
CHICHE D, TAILLANDIER L, BLONSKI M, et al. DTI analysis of the peritumoral zone of diffuse low-grade gliomas in progressing patients[J/OL]. World Neurosurg, 2025, 194: 123382 [2025-07-14]. https://pubmed.ncbi.nlm.nih.gov/39489335/. DOI: 10.1016/j.wneu.2024.10.111.
[62]
RAMLI N, LIM C H, RAJAGOPAL R, et al. Assessing changes in microstructural integrity of white matter tracts in children with leukaemia following exposure to chemotherapy[J]. Pediatr Radiol, 2020, 50(9): 1277-1283. DOI: 10.1007/s00247-020-04717-x.

PREV Progress in non-invasive elastography techniques for the diagnosis and assessment of metabolic dysfunction-associated steatotic liver disease
NEXT Research progress in the application of diffusion-weighted imaging in hematological malignancies
  



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