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Progress in diagnosis and treatment of whole-body magnetic resonance imaging in hematologic malignancies
WU Fanyu  LIU Yuankang  JIANG Cuiping  XIA Yuxuan  XU Xiangyang 

Cite this article as: 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 Imaging, 2025, 16(1): 228-234. DOI:10.12015/issn.1674-8034.2025.01.037.


[Abstract] Hematologic malignancies, being systemic tumors with multiple foci, require early lesion screening and diagnosis for effective treatment and prognosis. Whole-body magnetic resonance imaging (WB-MRI) is a non-ionizing radiation imaging technique with high soft tissue resolution that offers advantages in detecting early lesions of hematologic malignancies, including micro-lesions and metastatic lesions. WB-MRI has gradually been applied in the early screening, diagnostic staging, treatment response evaluation and recurrence prediction of hematologic malignancies. This article reviews the advances in the diagnosis, treatment, and prognosis of hematologic malignancies, such as multiple myeloma (MM), lymphoma, and leukemia through the application of WB-MRI. Furthermore, it analyzes the similarities and differences in the WB-MRI characteristics of these three hematologic malignancies and discusses the utilization prospects of machine learning and deep learning technologies in the analysis of WB-MRI images, with the aim of providing a reference for clinical diagnosis and treatment of hematologic tumors and for future investigative efforts.
[Keywords] whole-body magnetic resonance imaging；hematologic malignancies；multiple myeloma；lymphoma；leukemia；diagnosis；treatment response；prognostic evaluation；machine learning；deep learning

WU Fanyu   LIU Yuankang   JIANG Cuiping   XIA Yuxuan   XU Xiangyang*  

Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China

Corresponding author: XU X Y, E-mail: 1993ly0538@hust.edu.cn

Conflicts of interest   None.

Received  2024-07-04
Accepted  2024-12-10
DOI: 10.12015/issn.1674-8034.2025.01.037
Cite this article as: 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 Imaging, 2025, 16(1): 228-234. DOI:10.12015/issn.1674-8034.2025.01.037.

[1]
ABEL G A, KLEPIN H D. Frailty and the management of hematologic malignancies[J]. Blood, 2018, 131(5): 515-524. DOI: 10.1182/blood-2017-09-746420.
[2]
ZHANG N, WU J X, WANG Q, et al. Global burden of hematologic malignancies and evolution patterns over the past 30 years[J/OL]. Blood Cancer J, 2023, 13(1): 82 [2024-10-23]. https://pubmed.ncbi.nlm.nih.gov/37193689/. DOI: 10.1038/s41408-023-00853-3.
[3]
LATIFOLTOJAR A, HUMPHRIES P D, MENEZES L J, et al. Whole-body magnetic resonance imaging in paediatric Hodgkin lymphoma - evaluation of quantitative magnetic resonance metrics for nodal staging[J]. Pediatr Radiol, 2019, 49(10): 1285-1298. DOI: 10.1007/s00247-019-04463-9.
[4]
FROLLI A, VARVELLO S, BALBO MUSSETTO A, et al. A radiation-free approach based on the whole-body MRI has shown a high level of accuracy in the follow-up of lymphoma patients-a single center retrospective study[J/OL]. J Clin Med, 2024, 13(13): 3637 [2024-10-23]. https://pubmed.ncbi.nlm.nih.gov/38999203/. DOI: 10.3390/jcm13133637.
[5]
VULASALA S S, VIRARKAR M, KARBASIAN N, et al. Whole-body MRI in oncology: A comprehensive review[J/OL]. Clin Imaging, 2024, 108: 110099 [2024-10-23]. https://pubmed.ncbi.nlm.nih.gov/38401295/. DOI: 10.1016/j.clinimag.2024.110099.
[6]
LIN G S, ZONG X D, LI Y W, et al. Whole-body MRI is an effective imaging modality for hematological malignancy treatment response assessment: A systematic review and meta-analysis[J/OL]. Front Oncol, 2022, 12: 827777 [2024-04-07]. https://pubmed.ncbi.nlm.nih.gov/35251996/. DOI: 10.3389/fonc.2022.827777.
[7]
SUMMERS P, SAIA G, COLOMBO A, et al. Whole-body magnetic resonance imaging: technique, guidelines and key applications[J/OL]. Ecancermedicalscience, 2021, 15: 1164 [2024-04-03]. https://pubmed.ncbi.nlm.nih.gov/33680078/. DOI: 10.3332/ecancer.2021.1164.
[8]
ALBANO D, MICCI G, PATTI C, et al. Whole-body magnetic resonance imaging: current role in patients with lymphoma[J/OL]. Diagnostics, 2021, 11(6): 1007 [2024-04-02]. https://pubmed.ncbi.nlm.nih.gov/34073062/. DOI: 10.3390/diagnostics11061007.
[9]
AHLAWAT S, DEBS P, AMINI B, et al. Clinical applications and controversies of whole-body MRI: AJR expert panel narrative review[J]. AJR Am J Roentgenol, 2023, 220(4): 463-475. DOI: 10.2214/AJR.22.28229.
[10]
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 [2024-10-23]. https://pubmed.ncbi.nlm.nih.gov/38202271/. DOI: 10.3390/jcm13010264.
[11]
LECOUVET F E, CHABOT C, TAIHI L, et al. Present and future of whole-body MRI in metastatic disease and myeloma: how and why you will do it[J]. Skeletal Radiol, 2024, 53(9): 1815-1831. DOI: 10.1007/s00256-024-04723-2.
[12]
ZUGNI F, MARIANI L, LAMBREGTS D M J, et al. Whole-body MRI in oncology: acquisition protocols, current guidelines, and beyond[J]. Radiol Med, 2024, 129(9): 1352-1368. DOI: 10.1007/s11547-024-01851-6.
[13]
Magnetic Resonance Application Professional Committee of China Association of Medical Equipment, Osteoarthrography Group of Chinese Society of Radiology of Chinese Medical Association, Editorial Board of Chinese Journal of Magnetic Resonance Imaging. Expert consensus on whole-body magnetic resonance imaging in multiple myeloma[J]. Chin J Magn Reson Imaging, 2024, 15(7): 1-6. DOI: 10.12015/issn.1674-8034.2024.07.001.
[14]
GALIA M, ALBANO D, NARESE D, et al. Whole-body MRI in patients with lymphoma: collateral findings[J]. Radiol Med, 2016, 121(10): 793-800. DOI: 10.1007/s11547-016-0658-x.
[15]
CHIABAI O, VAN NIEUWENHOVE S, VEKEMANS M C, et al. Whole-body MRI in oncology: can a single anatomic T2 Dixon sequence replace the combination of T1 and STIR sequences to detect skeletal metastasis and myeloma?[J]. Eur Radiol, 2023, 33(1): 244-257. DOI: 10.1007/s00330-022-09007-8.
[16]
IPPOLITO D, GIANDOLA T, MAINO C, et al. Diagnostic value of whole-body MRI short protocols in bone lesion detection in multiple myeloma patients[J/OL]. Diagnostics, 2021, 11(6): 1053 [2024-03-24]. https://pubmed.ncbi.nlm.nih.gov/34201122/. DOI: 10.3390/diagnostics11061053.
[17]
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.
[18]
Hematological Oncology Committee of China Anti-Cancer Association, Chinese Society of Hematology of Chinese Medical Association. The guidelines for diagnosis and treatment of myeloma bone disease in China (2022)[J]. Chin J Hematol, 2022, 43(12): 979-985. DOI: 10.3760/cma.j.issn.0253-2727.2022.12.002.
[19]
HEIDEMEIER A, THURNER A, METZ C, et al. Whole-body MRI with an ultrahigh b-value of 2000 s/mm2 improves the specificity of diffusion-weighted imaging in patients with plasma cell dyscrasias[J/OL]. Acad Radiol, 2022, 29(1): e1-e8 [2024-04-08]. https://pubmed.ncbi.nlm.nih.gov/33139155/. DOI: 10.1016/j.acra.2020.09.016.
[20]
SUN M T, CHENG J L, REN C P, et al. Differentiation of diffuse infiltration pattern in multiple myeloma from hyperplastic hematopoietic bone marrow: qualitative and quantitative analysis using whole-body MRI[J]. J Magn Reson Imaging, 2022, 55(4): 1213-1225. DOI: 10.1002/jmri.27934.
[21]
SUN M T, CHENG J L, REN C P, et al. Evaluation of diffuse bone marrow infiltration pattern in monoclonal plasma cell Diseases by Quantitative whole-body magnetic resonance imaging[J]. Acad Radiol, 2022, 29(4): 490-500. DOI: 10.1016/j.acra.2021.06.015.
[22]
SUN M T, WANG L L, WANG C, et al. Quantitative analysis of whole-body MRI for accessing the degree of diffuse infiltration patterns and identifying high risk cases of newly diagnosed multiple myeloma[J]. J Magn Reson Imaging, 2024, 59(6): 2035-2045. DOI: 10.1002/jmri.28962.
[23]
WANG Q, ZHANG L, LI S, et al. Histogram analysis based on apparent diffusion coefficient maps of bone marrow in multiple myeloma: an independent predictor for high-risk patients classified by the revised international staging system[J/OL]. Acad Radiol, 2022, 29(6): e98-e107 [2024-03-11]. https://pubmed.ncbi.nlm.nih.gov/34452820/. DOI: 10.1016/j.acra.2021.07.010.
[24]
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.
[25]
QI Q Y, DONG H Z, JI X D, et al. More accurate prediction of treatment response than meanapparent diffusion coefficient value in multiple myeloma using whole bodyMRI histogram analysis[J]. Future Oncol, 2023, 19(17): 1175-1185. DOI: 10.2217/fon-2023-0205.
[26]
ZHANG B, BIAN B Y, ZHANG Y J, et al. The apparent diffusion coefficient of diffusion-weighted whole-body magnetic resonance imaging affects the survival of multiple myeloma independently[J/OL]. Front Oncol, 2022, 12: 780078 [2024-03-11]. https://pubmed.ncbi.nlm.nih.gov/35311101/. DOI: 10.3389/fonc.2022.780078.
[27]
LECOUVET F E, VEKEMANS M C, VAN DEN BERGHE T, et al. Imaging of treatment response and minimal residual disease in multiple myeloma: state of the art WB-MRI and PET/CT[J]. Skeletal Radiol, 2022, 51(1): 59-80. DOI: 10.1007/s00256-021-03841-5.
[28]
WANG K W, LEE E, KENIS S, et al. Application of diffusion-weighted whole-body MRI for response monitoring in multiple myeloma after chemotherapy: a systematic review and meta-analysis[J]. Eur Radiol, 2022, 32(4): 2135-2148. DOI: 10.1007/s00330-021-08311-z.
[29]
SATCHWELL L, WEDLAKE L, GREENLAY E, et al. Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study[J/OL]. BMJ Open, 2022, 12(10): e067140 [2024-11-19]. https://pubmed.ncbi.nlm.nih.gov/36198471/. DOI: 10.1136/bmjopen-2022-067140.
[30]
WENNMANN M, KLEIN A, BAUER F, et al. Combining deep learning and radiomics for automated, objective, comprehensive bone marrow characterization from whole-body MRI: A multicentric feasibility study[J]. Invest Radiol, 2022, 57(11): 752-763. DOI: 10.1097/RLI.0000000000000891.
[31]
WENNMANN M, NEHER P, STANCZYK N, et al. Deep learning for automatic bone marrow apparent diffusion coefficient measurements from whole-body magnetic resonance imaging in patients with multiple myeloma: A retrospective multicenter study[J]. Invest Radiol, 2023, 58(4): 273-282. DOI: 10.1097/RLI.0000000000000932.
[32]
HEIDEMEIER A, SCHLOETELBURG W, THURNER A, et al. Multi-parametric whole-body MRI evaluation discerns vital from non-vital multiple myeloma lesions as validated by 18F-FDG and 11C-methionine PET/CT[J/OL]. Eur J Radiol, 2022, 155: 110493 [2024-11-19]. https://pubmed.ncbi.nlm.nih.gov/36027759/. DOI: 10.1016/j.ejrad.2022.110493.
[33]
TUNARIU N, BLACKLEDGE M, MESSIOU C, et al. What's new for clinical whole-body MRI (WB-MRI) in the 21st century[J/OL]. Br J Radiol, 2020, 93(1115): 20200562 [2024-05-19]. https://pubmed.ncbi.nlm.nih.gov/32822545/. DOI: 10.1259/bjr.20200562.
[34]
CHESON B D, FISHER R I, BARRINGTON S F, et al. Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification[J]. J Clin Oncol, 2014, 32(27): 3059-3068. DOI: 10.1200/JCO.2013.54.8800.
[35]
MACCIONI F, ALFIERI G, ASSANTO G M, et al. Whole body MRI with Diffusion Weighted Imaging versus 18F-fluorodeoxyglucose-PET/CT in the staging of lymphomas[J]. Radiol Med, 2023, 128(5): 556-564. DOI: 10.1007/s11547-023-01622-9.
[36]
SPIJKERS S, NIEVELSTEIN R A J, KEIZER B D, et al. Fused high b-value diffusion weighted and T2-weighted MR images in staging of pediatric Hodgkin's lymphoma: A pilot study[J/OL]. Eur J Radiol, 2019, 121: 108737 [2024-03-29]. https://pubmed.ncbi.nlm.nih.gov/31734638/. DOI: 10.1016/j.ejrad.2019.108737.
[37]
SPIJKERS S, LITTOOIJ A S, KWEE T C, et al. Whole-body MRI versus an [18F]FDG-PET/CT-based reference standard for early response assessment and restaging of paediatric Hodgkin's lymphoma: A prospective multicentre study[J]. Eur Radiol, 2021, 31(12): 8925-8936. DOI: 10.1007/s00330-021-08026-1.
[38]
LATIFOLTOJAR A, PUNWANI S, LOPES A, et al. Whole-body MRI for staging and interim response monitoring in paediatric and adolescent Hodgkin's lymphoma: a comparison with multi-modality reference standard including 18F-FDG-PET-CT[J]. Eur Radiol, 2019, 29(1): 202-212. DOI: 10.1007/s00330-018-5445-8.
[39]
MORAKOTE W, BARATTO L, RAMASAMY S K, et al. Comparison of diffusion-weighted MRI and [18F]FDG PET/MRI for treatment monitoring in pediatric Hodgkin and non-Hodgkin lymphoma[J]. Eur Radiol, 2024, 34(1): 643-653. DOI: 10.1007/s00330-023-10015-5.
[40]
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 [2024-03-31]. https://pubmed.ncbi.nlm.nih.gov/33817648/. DOI: 10.1148/rycan.2021200061.
[41]
ALBANO D, CUOCOLO R, PATTI C, et al. Whole-body MRI radiomics model to predict relapsed/refractory Hodgkin Lymphoma: a preliminary study[J]. Magn Reson Imaging, 2022, 86: 55-60. DOI: 10.1016/j.mri.2021.11.005.
[42]
FERJAOUI R, CHERNI M A, BOUJNAH S, et al. Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images[J/OL]. Comput Methods Programs Biomed, 2021, 209: 106320 [2024-11-19]. https://pubmed.ncbi.nlm.nih.gov/34390938/. DOI: 10.1016/j.cmpb.2021.106320.
[43]
LUITJENS J, BAUR-MELNYK A. Skelettveränderungen Bei hämatologischen systemerkrankungen[J]. Der Radiol, 2021, 61(12): 1068-1077. DOI: 10.1007/s00117-021-00934-z.
[44]
AVERILL L W, ACIKGOZ G, MILLER R E, et al. Update on pediatric leukemia and lymphoma imaging[J]. Semin Ultrasound CT MR, 2013, 34(6): 578-599. DOI: 10.1053/j.sult.2013.05.004.
[45]
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 [2024-10-25]. https://pubmed.ncbi.nlm.nih.gov/35319510/. DOI: 10.1097/MPH.0000000000002353.
[46]
YOON H M, KIM J R, JUNG A Y, et al. Whole body MR imaging: a useful imaging modality in the management of children with acute myeloid leukemia[J]. Clin Lymphoma Myeloma Leuk, 2017, 17(4): 231-237. DOI: 10.1016/j.clml.2017.02.004.
[47]
HARADA N, NISHIMOTO M, IKEMOTO A, et al. Recurrence of acute lymphoblastic leukemia with bone marrow necrosis: a case report and review of the literature on the MRI features of bone marrow necrosis[J]. Intern Med, 2021, 60(7): 1083-1088. DOI: 10.2169/internalmedicine.5815-20.
[48]
ALGUDKAR A, EL-SHARKAWI D, CROSS M, et al. Whole body-diffusion weighted imaging for the assessment of treatment response in hairy cell leukaemia: a positive first step[J]. EJHaem, 2021, 2(2): 311-312. DOI: 10.1002/jha2.158.
[49]
MIETTUNEN P M, LAFAY-COUSIN L, GUILCHER G M, et al. Widespread osteonecrosis in children with leukemia revealed by whole-body MRI[J]. Clin Orthop Relat Res, 2012, 470(12): 3587-3595. DOI: 10.1007/s11999-012-2579-x.
[50]
TAKASU M, HIGASHINO R, SUEOKA T, et al. Prediction of mobilized hematopoietic stem cell yield in patients with multiple myeloma: Usefulness of whole-body MRI-derived indices[J/OL]. PLoS One, 2023, 18(3): e0283241 [2024-02-20]. https://pubmed.ncbi.nlm.nih.gov/37000837/. DOI: 10.1371/journal.pone.0283241.
[51]
HONG G S, CHAE E J, RYU J S, et al. Assessment of naive indolent lymphoma using whole-body diffusion-weighted imaging and T2-weighted MRI: results of a prospective study in 30 patients[J/OL]. Cancer Imaging, 2021, 21(1): 5 [2024-03-27]. https://pubmed.ncbi.nlm.nih.gov/33413685/. DOI: 10.1186/s40644-020-00371-6.
[52]
WENNMANN M, HIELSCHER T, KINTZELÉ L, et al. Analyzing longitudinal wb-MRI data and clinical course in a cohort of former smoldering multiple myeloma patients: Connections between MRI findings and clinical progression patterns[J/OL]. Cancers, 2021, 13(5): 961 [2023-12-03]. https://pubmed.ncbi.nlm.nih.gov/33668879/. DOI: 10.3390/cancers13050961.
[53]
BAUER F, SAUER S, WEINHOLD N, et al. (Smoldering) multiple myeloma: mismatch between tumor load estimated from bone marrow biopsy at iliac crest and tumor load shown by MRI[J]. Skeletal Radiol, 2023, 52(12): 2513-2518. DOI: 10.1007/s00256-023-04383-8.
[54]
SHAPIRA-ZALTSBERG G, WILSON N, TREJO PEREZ E, et al. Whole-body diffusion-weighted MRI compared to 18 FFDG PET/CT in initial staging and therapy response assessment of Hodgkin lymphoma in pediatric patients[J]. J L'association Can Des Radiol, 2020, 71(2): 217-225. DOI: 10.1177/0846537119888380.
[55]
WINZER R, HOBERÜCK S, ZÖPHEL K, et al. Diffusion-weighted MRI for initial staging in Hodgkin`s lymphoma: comparison with FDG PET[J/OL]. Eur J Radiol, 2020, 123: 108775 [2024-03-27]. https://pubmed.ncbi.nlm.nih.gov/31864143/. DOI: 10.1016/j.ejrad.2019.108775.
[56]
MORITA K, KARASHIMA S, TERAO T, et al. 3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients with Multiple Myeloma using Whole-body MRI[J/OL]. J Med Syst, 2024, 48(1): 30 [2024-11-19]. https://pubmed.ncbi.nlm.nih.gov/38456950/. DOI: 10.1007/s10916-024-02040-8.

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