Share:
Share this content in WeChat
X
Review
Research progress of magnetic resonance habitat imaging in the prognosis of malignant tumors
CHEN Zeke  WANG Xiaochun 

Cite this article as: CHEN Z K, WANG X C. Research progress of magnetic resonance habitat imaging in the prognosis of malignant tumors[J]. Chin J Magn Reson Imaging, 2025, 16(2): 222-228. DOI:10.12015/issn.1674-8034.2025.02.036.


[Abstract] Traditional radiology has made great progress in evaluating the prognosis of malignant tumors by analyzing the quantitative information in medical images and finding and quantifying the subtle features that are difficult to be recognized by naked eyes. However, there are still some challenges in radiology, which generally treat tumors as a relatively evenly distributed whole internally and cannot fully express tumor heterogeneity. Tumor heterogeneity is the main cause of tumor progression, treatment resistance, and recurrence. By segmenting images, the tumor habitat map can be generated, which can reflect the heterogeneity of tumor tissues, molecules, and their microenvironment. This provides a new perspective for understanding the biological characteristics and therapeutic response of tumors and helps to evaluate the prognosis of malignant tumors. For example, it has been found that in glioblastoma (GBM), pre- and post-treatment volume changes in hyper-vascular cellular habitat and hypo-vascular cellular habitat correlate strongly with tumor progression, providing potential imaging markers for predicting patient survival after surgery. This article reviews the latest research progress of magnetic resonance habitat imaging in the prognosis of malignant tumors.
[Keywords] malignant tumors;habitat imaging;magnetic resonance imaging;prognosis

CHEN Zeke   WANG Xiaochun*  

Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan 030001, China

Corresponding author: WANG X C, E-mail: 2010xiaochun@163.com

Conflicts of interest   None.

Received  2024-11-01
Accepted  2025-02-10
DOI: 10.12015/issn.1674-8034.2025.02.036
Cite this article as: CHEN Z K, WANG X C. Research progress of magnetic resonance habitat imaging in the prognosis of malignant tumors[J]. Chin J Magn Reson Imaging, 2025, 16(2): 222-228. DOI:10.12015/issn.1674-8034.2025.02.036.

[1]
BRAY F, LAVERSANNE M, SUNG H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263. DOI: 10.3322/caac.21834.
[2]
HAN B F, ZHENG R S, ZENG H M, et al. Cancer incidence and mortality in China, 2022[J]. J Natl Cancer Cent, 2024, 4(1): 47-53. DOI: 10.1016/j.jncc.2024.01.006.
[3]
LI S L, DAI Y M, CHEN J Y, et al. MRI-based habitat imaging in cancer treatment: current technology, applications, and challenges[J/OL]. Cancer Imaging, 2024, 24(1): 107 [2024-11-12]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11328409/. DOI: 10.1186/s40644-024-00758-9.
[4]
WU H, TONG H P, DU X S, et al. Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas[J]. Eur Radiol, 2020, 30(6): 3254-3265. DOI: 10.1007/s00330-020-06702-2.
[5]
JUAN-ALBARRACÍN J, FUSTER-GARCIA E, PÉREZ-GIRBÉS A, et al. Glioblastoma: Vascular habitats detected at preoperative dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging predict survival[J]. Radiology, 2018, 287(3): 944-954. DOI: 10.1148/radiol.2017170845.
[6]
PERRIN S L, SAMUEL M S, KOSZYCA B, et al. Glioblastoma heterogeneity and the tumour microenvironment: implications for preclinical research and development of new treatments[J]. Biochem Soc Trans, 2019, 47(2): 625-638. DOI: 10.1042/BST20180444.
[7]
KIM J Y, GATENBY R A. Quantitative clinical imaging methods for monitoring intratumoral evolution[J]. Methods Mol Biol, 2017, 1513: 61-81. DOI: 10.1007/978-1-4939-6539-7_6.
[8]
YANCOVITZ M, LITTERMAN A, YOON J, et al. Intra- and inter-tumor heterogeneity of BRAF(V600E)) mutations in primary and metastatic melanoma[J/OL]. PLoS One, 2012, 7(1): e29336 [2024-10-20]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3250426/. DOI: 10.1371/journal.pone.0029336.
[9]
GERLINGER M, ROWAN A J, HORSWELL S, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing[J]. N Engl J Med, 2012, 366(10): 883-892. DOI: 10.1056/NEJMoa1113205.
[10]
INDA M D M, BONAVIA R, MUKASA A, et al. Tumor heterogeneity is an active process maintained by a mutant EGFR-induced cytokine circuit in glioblastoma[J]. Genes Dev, 2010, 24(16): 1731-1745. DOI: 10.1101/gad.1890510.
[11]
SALA E, MEMA E, HIMOTO Y, et al. Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging[J]. Clin Radiol, 2017, 72(1): 3-10. DOI: 10.1016/j.crad.2016.09.013.
[12]
MARUSYK A, POLYAK K. Tumor heterogeneity: causes and consequences[J]. Biochim Biophys Acta, 2010, 1805(1): 105-117. DOI: 10.1016/j.bbcan.2009.11.002.
[13]
DAGOGO-JACK I, SHAW A T. Tumour heterogeneity and resistance to cancer therapies[J]. Nat Rev Clin Oncol, 2018, 15(2): 81-94. DOI: 10.1038/nrclinonc.2017.166.
[14]
YUAN Y Y. Spatial heterogeneity in the tumor microenvironment[J/OL]. Cold Spring Harb Perspect Med, 2016, 6(8): a026583 [2024-10-20]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4968167/. DOI: 10.1101/cshperspect.a026583.
[15]
CHANG Y C, ACKERSTAFF E, TSCHUDI Y, et al. Delineation of tumor habitats based on dynamic contrast enhanced MRI[J/OL]. Sci Rep, 2017, 7(1): 9746 [2024-10-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575347/. DOI: 10.1038/s41598-017-09932-5.
[16]
CALIFF R M. Biomarker definitions and their applications[J]. Exp Biol Med, 2018, 243(3): 213-221. DOI: 10.1177/1535370217750088.
[17]
QIAO J, KANG H, RAN Q, et al. Metabolic habitat imaging with hemodynamic heterogeneity predicts individual progression-free survival in high-grade glioma[J/OL]. Clin Radiol, 2024, 79(6): e842-e853 [2024-10-21]. https://www.sciencedirect.com/science/article/pii/S0009926024001338. DOI: 10.1016/j.crad.2024.02.011.
[18]
CHO H H, KIM H, NAM S Y, et al. Measurement of perfusion heterogeneity within tumor habitats on magnetic resonance imaging and its association with prognosis in breast cancer patients[J/OL]. Cancers, 2022, 14(8): 1858 [2024-10-23]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025287/. DOI: 10.3390/cancers14081858.
[19]
SLAVKOVA K P, PATEL S H, CACINI Z, et al. Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma[J/OL]. Sci Rep, 2023, 13(1): 2916 [2024-12-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941120/. DOI: 10.1038/s41598-023-30010-6.
[20]
BAILO M, PECCO N, CALLEA M, et al. Decoding the heterogeneity of malignant gliomas by PET and MRI for spatial habitat analysis of hypoxia, perfusion, and diffusion imaging: a preliminary study[J/OL]. Front Neurosci, 2022, 16: 885291 [2024-12-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941120/. DOI: 10.3389/fnins.2022.885291.
[21]
VERMA R, HILL V B, STATSEVYCH V, et al. Stable and discriminatory radiomic features from the tumor and its habitat associated with progression-free survival in glioblastoma: a multi-institutional study[J]. AJNR Am J Neuroradiol, 2022, 43(8): 1115-1123. DOI: 10.3174/ajnr.A7591.
[22]
National Health Commission Medical Administration Bureau. Chin J Neurosurg, 2019, 35(3): 217-239. DOI: 10.3760/cma.j.issn.1001-2346.2019.03.001.
[23]
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.
[24]
TAN A C, ASHLEY D M, LÓPEZ G Y, et al. Management of glioblastoma: State of the art and future directions[J]. CA Cancer J Clin, 2020, 70(4): 299-312. DOI: 10.3322/caac.21613.
[25]
YANG Y, HAN Y, ZHAO S J, et al. Spatial heterogeneity of edema region uncovers survival-relevant habitat of Glioblastoma[J/OL]. Eur J Radiol, 2022, 154: 110423 [2024-10-21]. https://www.sciencedirect.com/science/article/pii/S0720048X2200273X. DOI: 10.1016/j.ejrad.2022.110423.
[26]
CHEN Y X, QU W, TU J H, et al. Implications of advances in studies of O6-methylguanine-DNA- methyltransferase for tumor prognosis and treatment[J/OL]. Front Biosci, 2023, 28(9): 197 [2024-12-30]. https://www.imrpress.com/journal/FBL/28/9/10.31083/j.fbl2809197/htm. DOI: 10.31083/j.fbl2809197.
[27]
JIAO K J, YANG B, CHEN W, et al. Prediction of habitat subregions of the glioblastoma microenvironment based on multimodal MRI radiomics for MGMT promoter methylation expression[J]. Chin J Magn Reson Imag, 2023, 14(11): 25-30, 76. DOI: 10.12015/issn.1674-8034.2023.11.005.
[28]
LAM M S, AW J J, TAN D, et al. Unveiling the influence of tumor microenvironment and spatial heterogeneity on temozolomide resistance in glioblastoma using an advanced human in vitro model of the blood-brain barrier and glioblastoma[J/OL]. Small, 2023, 19(52): e2302280 [2024-11-12]. https://onlinelibrary.wiley.com/doi/10.1002/smll.202302280. DOI: 10.1002/smll.202302280.
[29]
MAHAFFEY B J, FOWLER Z P, LUNG Z, et al. The prognostic effect of mechanical, ultrastructural, and ECM signatures in glioblastoma core and rim[J/OL]. APL Bioeng, 2024, 8(3): 036101 [2024-11-12]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11209891/. DOI: 10.1063/5.0203570.
[30]
KIM M, PARK J E, KIM H S, et al. Spatiotemporal habitats from multiparametric physiologic MRI distinguish tumor progression from treatment-related change in post-treatment glioblastoma[J]. Eur Radiol, 2021, 31(8): 6374-6383. DOI: 10.1007/s00330-021-07718-y.
[31]
PARK J E, KIM H S, KIM N, et al. Low conductivity on electrical properties tomography demonstrates unique tumor habitats indicating progression in glioblastoma[J]. Eur Radiol, 2021, 31(9): 6655-6665. DOI: 10.1007/s00330-021-07976-w.
[32]
SHEN J, LIU J H. Bruton's tyrosine kinase inhibitors in the treatment of primary central nervous system lymphoma: A mini-review[J/OL]. Front Oncol, 2022, 12: 1034668 [2024-10-22]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9713408/. DOI: 10.3389/fonc.2022.1034668.
[33]
FALLAH J, QUNAJ L, OLSZEWSKI A J. Therapy and outcomes of primary central nervous system lymphoma in the United States: analysis of the National Cancer Database[J]. Blood Adv, 2016, 1(2): 112-121. DOI: 10.1182/bloodadvances.2016000927.
[34]
FERRERI A J M, CALIMERI T, CWYNARSKI K, et al. Primary central nervous system lymphoma[J/OL]. Nat Rev Dis Primers, 2023, 9: 29 [2024-10-22]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637780/. DOI: 10.1038/s41572-023-00439-0.
[35]
JEONG S Y, PARK J E, KIM N, et al. Hypovascular cellular tumor in primary central nervous system lymphoma is associated with treatment resistance: tumor habitat analysis using physiologic MRI[J]. AJNR Am J Neuroradiol, 2022, 43(1): 40-47. DOI: 10.3174/ajnr.A7351.
[36]
RICH B J, KWON D, SONI Y S, et al. Survival and yield of surveillance imaging in long-term survivors of brain metastasis treated with stereotactic radiosurgery[J/OL]. World Neurosurg, 2022, 167: e738-e746 [2024-11-12]. https://www.sciencedirect.com/science/article/abs/pii/S1878875022011895?via%3Dihub. DOI: 10.1016/j.wneu.2022.08.079.
[37]
VOGELBAUM M A, BROWN P D, MESSERSMITH H, et al. Treatment for brain metastases: ASCO-SNO-ASTRO guideline[J]. J Clin Oncol, 2022, 40(5): 492-516. DOI: 10.1200/JCO.21.02314.
[38]
BRENNER A W, PATEL A J. Review of current principles of the diagnosis and management of brain metastases[J/OL]. Front Oncol, 2022, 12: 857622 [2024-10-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171239/. DOI: 10.3389/fonc.2022.857622.
[39]
XIAO J P, MA Y C, WANG J, et al. Guidelines for integrated diagnosis and treatment of tumors in China: brain metastasis[J]. Chin J Cancer, 2023, 42(6): 304-318. DOI: 10.20124/j.cnki.1000-467x.2023.06.004.
[40]
LEE D H, PARK J E, KIM N, et al. Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery[J]. Eur Radiol, 2022, 32(1): 497-507. DOI: 10.1007/s00330-021-08204-1.
[41]
LEE D H, PARK J E, KIM N, et al. Tumor habitat analysis using longitudinal physiological MRI to predict tumor recurrence after stereotactic radiosurgery for brain metastasis[J]. Korean J Radiol, 2023, 24(3): 235-246. DOI: 10.3348/kjr.2022.0492.
[42]
ANDRADE DE OLIVEIRA K, SENGUPTA S, YADAV A K, et al. The complex nature of heterogeneity and its roles in breast cancer biology and therapeutic responsiveness[J/OL]. Front Endocrinol (Lausanne), 2023, 14: 1083048 [2024-11-12]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC36909339/. DOI: 10.3389/fendo.2023.1083048.
[43]
DERAKHSHAN F, REIS-FILHO J S. Pathogenesis of triple-negative breast cancer[J]. Annu Rev Pathol, 2022, 17: 181-204. DOI: 10.1146/annurev-pathol-042420-093238.
[44]
ASLEH K, RIAZ N, NIELSEN T O. Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications[J/OL]. J Exp Clin Cancer Res, 2022, 41(1): 265 [2024-10-23]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434975/. DOI: 10.1186/s13046-022-02476-1.
[45]
ZHANG W L, LIANG F R, ZHAO Y, et al. Multiparametric MR-based feature fusion radiomics combined with ADC maps-based tumor proliferative burden in distinguishing TNBC versus non-TNBC[J/OL]. Phys Med Biol, 2024, 69(5) [2024-10-23]. https://iopscience.iop.org/article/10.1088/1361-6560/ad25c0. DOI: 10.1088/1361-6560/ad25c0.
[46]
XU R, YU D, LUO P, et al. Do habitat MRI and fractal analysis help distinguish triple-negative breast cancer from non-triple-negative breast carcinoma[J]. Can Assoc Radiol J, 2024, 75(3): 584-592. DOI: 10.1177/08465371241231573.
[47]
HOUSSAMI N, MACASKILL P, VON MINCKWITZ G, et al. Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy[J]. Eur J Cancer, 2012, 48(18): 3342-3354. DOI: 10.1016/j.ejca.2012.05.023.
[48]
XU C, WANG Z H, WANG A L, et al. Breast cancer: multi-b-value diffusion weighted habitat imaging in predicting pathologic complete response to neoadjuvant chemotherapy[J]. Acad Radiol, 2024, 31(12): 4733-4742. DOI: 10.1016/j.acra.2024.06.004.
[49]
ZHANG Y Y, WANG H L, ZHAO H H, et al. Prognostic significance and value of further classification of lymphovascular invasion in invasive breast cancer: a retrospective observational study[J]. Breast Cancer Res Treat, 2024, 206(2): 397-410. DOI: 10.1007/s10549-024-07318-6.
[50]
HOUVENAEGHEL G, COHEN M, CLASSE J M, et al. Lymphovascular invasion has a significant prognostic impact in patients with early breast cancer, results from a large, national, multicenter, retrospective cohort study[J/OL]. ESMO Open, 2021, 6(6): 100316 [2024-10-24]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8645922/. DOI: 10.1016/j.esmoop.2021.100316.
[51]
PESCIA C, GUERINI-ROCCO E, VIALE G, et al. Advances in early breast cancer risk profiling: from histopathology to molecular technologies[J/OL]. Cancers, 2023, 15(22): 5430 [2024-10-24]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670146/. DOI: 10.3390/cancers15225430.
[52]
WU Z J, LIN Q, SONG H M, et al. Evaluation of lymphatic vessel invasion determined by D2-40 using preoperative MRI-based radiomics for invasive breast cancer[J]. Acad Radiol, 2023, 30(11): 2458-2468. DOI: 10.1016/j.acra.2022.11.024.
[53]
GE W, FAN X, ZENG Y, et al. Exploring habitats-based spatial distributions: improving predictions of lymphovascular invasion in invasive breast cancer[J]. Acad Radiol, 2024, 31(11): 4317-4328. DOI: 10.1016/j.acra.2024.05.043.
[54]
SIEGEL R, GIAQUINTO A N, JEMAL A. Cancer statistics, 2024[J]. CA A Cancer J Clin, 2024, 74: 12-49. DOI: 10.3322/caac.21820.
[55]
VOGEL A, MEYER T, SAPISOCHIN G, et al. Hepatocellular carcinoma[J]. Lancet, 2022, 400(10360): 1345-1362. DOI: 10.1016/s0140-6736(22)01200-4.
[56]
ZHANG Y F, YANG C, SHENG R F, et al. Predicting the recurrence of hepatocellular carcinoma (≤ 5 cm) after resection surgery with promising risk factors: habitat fraction of tumor and its peritumoral micro-environment[J]. Radiol Med, 2023, 128(10): 1181-1191. DOI: 10.1007/s11547-023-01695-6.
[57]
ZHANG Z H, JIANG C, QIANG Z Y, et al. Role of microvascular invasion in early recurrence of hepatocellular carcinoma after liver resection: a literature review[J]. Asian J Surg, 2024, 47(5): 2138-2143. DOI: 10.1016/j.asjsur.2024.02.115.
[58]
ZHENG Z H, GUAN R G, WANG J X, et al. Microvascular invasion in hepatocellular carcinoma: a review of its definition, clinical significance, and comprehensive management[J/OL]. J Oncol, 2022, 2022: 9567041 [2024-10-24]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8986383/. DOI: 10.1155/2022/9567041.
[59]
WANG C, WU F, WANG F, et al. The association between tumor radiomic analysis and peritumor habitat-derived radiomic analysis on gadoxetate disodium-enhanced MRI with microvascular invasion in hepatocellular carcinoma[J]. J Magn Reson Imag, 2025, 61(3): 1428-1439. DOI: 10.1002/jmri.29523.
[60]
ZHANG Y F, CHEN J J, YANG C, et al. Preoperative prediction of microvascular invasion in hepatocellular carcinoma using diffusion-weighted imaging-based habitat imaging[J]. Eur Radiol, 2024, 34(5): 3215-3225. DOI: 10.1007/s00330-023-10339-2.
[61]
MILLER K D, NOGUEIRA L, DEVASIA T, et al. Cancer treatment and survivorship statistics, 2022[J]. CA Cancer J Clin, 2022, 72(5): 409-436. DOI: 10.3322/caac.21731.
[62]
MARGOLIS B, CAGLE-COLON K, CHEN L, et al. Prognostic significance of lymphovascular space invasion for stage IA1 and IA2 cervical cancer[J]. Int J Gynecol Cancer, 2020, 30(6): 735-743. DOI: 10.1136/ijgc-2019-000849.
[63]
BHATLA N, AOKI D, SHARMA D N, et al. Cancer of the cervix uteri[J]. Int J Gynaecol Obstet, 2018, 143(Suppl 2): 22-36. DOI: 10.1002/ijgo.12611.
[64]
WANG S X, LIU X W, WU Y, et al. Habitat-based radiomics enhances the ability to predict lymphovascular space invasion in cervical cancer: a multi-center study[J/OL]. Front Oncol, 2023, 13: 1252074 [2024-10-24]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637586/. DOI: 10.3389/fonc.2023.1252074.
[65]
KIM S I, YOON J H, LEE S J, et al. Prediction of lymphovascular space invasion in patients with endometrial cancer[J]. Int J Med Sci, 2021, 18(13): 2828-2834. DOI: 10.7150/ijms.60718.
[66]
KHATIB S AL, BHATNAGAR A, ELSHAIKH N, et al. The prognostic significance of the depth of cervical stromal invasion in women with FIGO stage Ⅱ uterine endometrioid carcinoma[J]. Am J Clin Oncol, 2023, 46(10): 445-449. DOI: 10.1097/COC.0000000000001033.
[67]
WANG X H, DENG C, KONG R Z, et al. Intratumoral and peritumoral habitat imaging based on multiparametric MRI to predict cervical stromal invasion in early-stage endometrial carcinoma[J/OL]. Acad Radiol, 2024: S1076-6332(24)00689-5 [2024-10-24]. https://www.sciencedirect.com/science/article/abs/pii/S1076633224006895. DOI: 10.1016/j.acra.2024.09.039.
[68]
GILLESSEN S, BOSSI A, DAVIS I D, et al. Management of patients with advanced prostate cancer. part I: intermediate-/ high-risk and locally advanced disease, biochemical relapse, and side effects of hormonal treatment: report of the advanced prostate cancer consensus conference 2022[J]. Eur Urol, 2023, 83(3): 267-293. DOI: 10.1016/j.eururo.2022.11.002.
[69]
HUANG F Y, HUANG Q, LIAO X H, et al. Prediction of high-risk prostate cancer based on the habitat features of biparametric magnetic resonance and the omics features of contrast-enhanced ultrasound[J/OL]. Heliyon, 2024, 10(18): e37955 [2024-10-25]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423289/. DOI: 10.1016/j.heliyon.2024.e37955.

PREV Application of metal-based theranostic magnetic resonance imaging contrast agents in tumor imaging and therapy
NEXT Research progress of quantitative vessel wall imaging with magnetic resonance parameters in carotid atherosclerosis
  



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