Share：
Share this content in WeChat
X
[Chinese][PDF]691
• Review •
Progress in MRI in peritumoral brain zone of brain tumors
ZHAO Endong  SHI Yutong  SONG Xuelin  LOU Shiyun  YANG Chao 

Cite this article as: ZHAO E D, SHI Y T, SONG X L, et al. Progress in MRI in peritumoral brain zone of brain tumors[J]. Chin J Magn Reson Imaging, 2024, 15(6): 172-178. DOI:10.12015/issn.1674-8034.2024.06.027.


[Abstract] Tumors are not single-growing tissues, and the specific tumor microenvironment surrounding them is closely related to their development. Peritumor brain area refers to the adjacent brain area around the primary tumor lesion, and radiologically it usually includes peritumor brain parenchyma and peritumor edema area. Fully understanding and mining the potential radiological information of tumor and peritumoral brain area will benefit the scientific research and clinical diagnosis and treatment of tumor. In this article, we elucidate the definition and formation mechanism of the peritumor brain zone, and review the progress of magnetic resonance imaging-based techniques, including diffusion imaging, perfusion imaging, magnetic resonance spectroscopy, amide proton transfer-weighted imaging, and radiomics, in the application of the peritumor brain zone to intracranial tumors. The aim of this review is to provide new ideas for differential diagnosis, genomolecular typing, exploration of intraoperative resection range, prognosis prediction and monitoring of therapeutic efficacy of intracranial tumors.
[Keywords] brain tumor；peritumor brain zone；magnetic resonance imaging；imaging omics；multimodality

ZHAO Endong1   SHI Yutong3   SONG Xuelin2   LOU Shiyun2   YANG Chao1*  

1 Department of Radiology, the First Hospital of Dalian Medical University, Dalian 116000, China

2 Department of Radiology, the Second Hospital of Dalian Medical University, Dalian 116000, China

3 Department of Neurology, Dalian University Affiliated Xinhua Hospital, Dalian 116000, China

Corresponding author: YANG C, E-mail: dryangchao@163.com

Conflicts of interest   None.

Received  2024-02-26
Accepted  2024-06-05
DOI: 10.12015/issn.1674-8034.2024.06.027
Cite this article as: ZHAO E D, SHI Y T, SONG X L, et al. Progress in MRI in peritumoral brain zone of brain tumors[J]. Chin J Magn Reson Imaging, 2024, 15(6): 172-178. DOI:10.12015/issn.1674-8034.2024.06.027.

[1]
GATENBY R A, GROVE O, GILLIES R J. Quantitative imaging in cancer evolution and ecology[J]. Radiology, 2013, 269(1): 8-15. DOI: 10.1148/radiol.13122697.
[2]
YIN K, TAO J L, WEI M, et al. Research progress of habitat imaging for tumors[J]. Chin J Med Imaging Technol, 2022, 38(9): 1421-1424. DOI: 10.13929/j.issn.1003-3289.2022.09.032.
[3]
TABASSUM M, SUMAN A A, SUERO MOLINA E, et al. Radiomics and machine learning in brain tumors and their habitat: A systematic review[J/OL]. Cancers (Basel), 2023, 15(15): 3845 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37568660/. DOI: 10.3390/cancers15153845.
[4]
TREVISI G, MANGIOLA A. Current knowledge about the peritumoral microenvironment in glioblastoma[J/OL]. Cancers (Basel), 2023, 15(22): 5460 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/38001721/. DOI: 10.3390/cancers15225460.
[5]
GIAMBRA M, DI CRISTOFORI A, VALTORTA S, et al. The peritumoral brain zone in glioblastoma: where we are and where we are going[J]. J Neurosci Res, 2023, 101(2): 199-216. DOI: 10.1002/jnr.25134.
[6]
LEMEE J M, CLAVREUL A, AUBRY M, et al. Characterizing the peritumoral brain zone in glioblastoma: a multidisciplinary analysis[J]. J Neurooncol, 2015, 122(1): 53-61. DOI: 10.1007/s11060-014-1695-8.
[7]
ROEHLECKE C, SCHMIDT M H H. Tunneling nanotubes and tumor microtubes in cancer[J/OL]. Cancers (Basel), 2020, 12(4): 857 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/32244839/. DOI: 10.3390/cancers12040857.
[8]
TAMURA R, OHARA K, SASAKI H, et al. Histopathological vascular investigation of the peritumoral brain zone of glioblastomas[J]. J Neurooncol, 2018, 136(2): 233-241. DOI: 10.1007/s11060-017-2648-9.
[9]
ESCARTIN C, GALEA E, LAKATOS A, et al. Reactive astrocyte nomenclature, definitions, and future directions[J]. Nat Neurosci, 2021, 24(3): 312-325. DOI: 10.1038/s41593-020-00783-4.
[10]
HENRIK HEILAND D, RAVI V M, BEHRINGER S P, et al. Tumor-associated reactive astrocytes aid the evolution of immunosuppressive environment in glioblastoma[J/OL]. Nat Commun, 2019, 10(1): 2541 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/31186414/. DOI: 10.1038/s41467-019-10493-6.
[11]
ROGGENDORF W, STRUPP S, PAULUS W. Distribution and characterization of microglia/macrophages in human brain tumors[J]. Acta Neuropathol, 1996, 92(3): 288-293. DOI: 10.1007/s004010050520.
[12]
TAMURA R, OHARA K, SASAKI H, et al. Difference in immunosuppressive cells between peritumoral area and tumor core in glioblastoma[J/OL]. World Neurosurg, 2018, 120: e601-e610 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/30165233/. DOI: 10.1016/j.wneu.2018.08.133.
[13]
CLAVREUL A, MENEI P. Mesenchymal stromal-like cells in the glioma microenvironment: What are these cells?[J/OL]. Cancers (Basel), 2020, 12(9) : 2628 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/32942567/. DOI: 10.3390/cancers12092628.
[14]
SOLAR P, HENDRYCH M, BARAK M, et al. Blood-brain barrier alterations and edema formation in different brain mass lesions[J/OL]. Front Cell Neurosci, 2022, 16: 922181 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/35910247/. DOI: 10.3389/fncel.2022.922181.
[15]
HE L, ZHANG H, LI T, et al. Distinguishing tumor cell infiltration and vasogenic edema in the peritumoral region of glioblastoma at the voxel level via conventional MRI sequences[J/OL]. Acad Radiol, 2023 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37689557/. DOI: 10.1016/j.acra.2023.08.008.
[16]
EIDEL O, BURTH S, NEUMANN J O, et al. Tumor infiltration in enhancing and non-enhancing parts of glioblastoma: A correlation with histopathology[J/OL]. PLoS One, 2017, 12(1): e0169292 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/28103256/. DOI: 10.1371/journal.pone.0169292.
[17]
SCOLA E, DEL VECCHIO G, BUSTO G, et al. Conventional and advanced magnetic resonance imaging assessment of non-enhancing peritumoral area in brain tumor[J/OL]. Cancers (Basel), 2023, 15(11). 2992 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37296953/. DOI: 10.3390/cancers15112992.
[18]
KOPRIVOVA T, KERKOVSKY M, JUZA T, et al. Possibilities of using multi-b-value diffusion magnetic resonance imaging for classification of brain lesions[J]. Acad Radiol, 2024, 31(1): 261-272. DOI: 10.1016/j.acra.2023.10.002.
[19]
ZAKHAROVA N E, BATALOV A I, POGOSBEKIAN E L, et al. Perifocal zone of brain gliomas: Application of diffusion kurtosis and perfusion MRI values for tumor invasion border determination[J/OL]. Cancers (Basel), 2023, 15(10) : 2760 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37345097/. DOI: 10.3390/cancers15102760.
[20]
TAN Y, WANG X C, ZHANG H, et al. Differentiation of high-grade-astrocytomas from solitary-brain-metastases: Comparing diffusion kurtosis imaging and diffusion tensor imaging[J]. Eur J Radiol, 2015, 84(12): 2618-2624. DOI: 10.1016/j.ejrad.2015.10.007.
[21]
YAN J L, LI C, BOONZAIER N R, et al. Multimodal MRI characteristics of the glioblastoma infiltration beyond contrast enhancement[J/OL]. Ther Adv Neurol Disord, 2019, 12: 1756286419844664 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/31205490/. DOI: 10.1177/1756286419844664.
[22]
MARTIN-NOGUEROL T, MOHAN S, SANTOS-ARMENTIA E, et al. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions[J/OL]. Eur J Radiol, 2021, 143: 109900 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/34412007/. DOI: 10.1016/j.ejrad.2021.109900.
[23]
PIERI V, SANVITO F, RIVA M, et al. Along-tract statistics of neurite orientation dispersion and density imaging diffusion metrics to enhance MR tractography quantitative analysis in healthy controls and in patients with brain tumors[J]. Hum Brain Mapp, 2021, 42(5): 1268-1286. DOI: 10.1002/hbm.25291.
[24]
VAN GARDEREN K A, VAN DER VOORT S R, WIJNENGA M M J, et al. Evaluating the predictive value of glioma growth models for low-grade glioma after tumor resection[J]. IEEE Trans Med Imaging, 2024, 43(1): 253-263. DOI: 10.1109/TMI.2023.3298637.
[25]
WARE J B, SINHA S, MORRISON J, et al. Dynamic contrast enhanced MRI for characterization of blood-brain-barrier dysfunction after traumatic brain injury[J/OL]. Neuroimage Clin, 2022, 36: 103236 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/36274377/. DOI: 10.1016/j.nicl.2022.103236.
[26]
ZHAO M, GUO L L, HUANG N, et al. Quantitative analysis of permeability for glioma grading using dynamic contrast-enhanced magnetic resonance imaging[J]. Oncol Lett, 2017, 14(5): 5418-5426. DOI: 10.3892/ol.2017.6895.
[27]
XIANG L, SUN L H, LIU B, et al. Quantitative dynamic contrast-enhanced magnetic resonance imaging for the analysis of microvascular permeability in peritumor brain edema of fibrous meningiomas[J]. Eur Neurol, 2021, 84(5): 361-367. DOI: 10.1159/000516921.
[28]
LI S H, SHEN N X, WU D, et al. A comparative study between tumor blood vessels and dynamic contrast-enhanced MRI for identifying isocitrate dehydrogenase gene 1 (IDH1) mutation status in glioma[J]. Curr Med Sci, 2022, 42(3): 650-657. DOI: 10.1007/s11596-022-2563-y.
[29]
OZTURK K, SOYLU E, TOLUNAY S, et al. Dynamic contrast-enhanced T1-weighted perfusion magnetic resonance imaging identifies glioblastoma immunohistochemical biomarkers via tumoral and peritumoral approach: A pilot study[J/OL]. World Neurosurg, 2019, 128: e195-e208 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/31003026/. DOI: 10.1016/j.wneu.2019.04.089.
[30]
CHUNG H, SEO H, CHOI S H, et al. Cluster analysis of DSC MRI, dynamic contrast-enhanced MRI, and DWI parameters associated with prognosis in patients with glioblastoma after removal of the contrast-enhancing component: A preliminary study[J]. AJNR Am J Neuroradiol, 2022, 43(11): 1559-1566. DOI: 10.3174/ajnr.A7655.
[31]
JABEHDAR MARALANI P, MELHEM E R, WANG S, et al. Association of dynamic susceptibility contrast enhanced MR Perfusion parameters with prognosis in elderly patients with glioblastomas[J]. Eur Radiol, 2015, 25(9): 2738-2744. DOI: 10.1007/s00330-015-3640-4.
[32]
JUAN-ALBARRACIN J, FUSTER-GARCIA E, PEREZ-GIRBES 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.
[33]
JO S W, CHOI S H, LEE E J, et al. Prognostic prediction based on dynamic contrast-enhanced MRI and dynamic susceptibility contrast-enhanced MRI parameters from non-enhancing, T2-high-signal-intensity lesions in patients with glioblastoma[J]. Korean J Radiol, 2021, 22(8): 1369-1378. DOI: 10.3348/kjr.2020.1272.
[34]
YOO R E, YUN T J, HWANG I, et al. Arterial spin labeling perfusion-weighted imaging aids in prediction of molecular biomarkers and survival in glioblastomas[J]. Eur Radiol, 2020, 30(2): 1202-1211. DOI: 10.1007/s00330-019-06379-2.
[35]
CHEN L, LI T, LI Y, et al. Combining amide proton transfer-weighted and arterial spin labeling imaging to differentiate solitary brain metastases from glioblastomas[J]. Magn Reson Imaging, 2023, 102: 96-102. DOI: 10.1016/j.mri.2023.05.004.
[36]
SOLOZHENTSEVA K, BATALOV A, ZAKHAROVA N, et al. The role of 3D-pCASL MRI in the differential diagnosis of glioblastoma and brain metastases[J/OL]. Front Oncol, 2022, 12: 874924 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/35558515/. DOI: 10.3389/fonc.2022.874924.
[37]
ABDEL RAZEK A A K, TALAAT M, EL-SEROUGY L, et al. Differentiating glioblastomas from solitary brain metastases using arterial spin labeling perfusion- and diffusion tensor imaging-derived metrics[J/OL]. World Neurosurg, 2019, 127: e593-e598 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/30928596/. DOI: 10.1016/j.wneu.2019.03.213.
[38]
YOU S H, YUN T J, CHOI H J, et al. Differentiation between primary CNS lymphoma and glioblastoma: qualitative and quantitative analysis using arterial spin labeling MR imaging[J]. Eur Radiol, 2018, 28(9): 3801-3810. DOI: 10.1007/s00330-018-5359-5.
[39]
GUARNERA A, ROMANO A, MOLTONI G, et al. The role of advanced MRI sequences in the diagnosis and follow-up of adult brainstem gliomas: A neuroradiological review[J]. Tomography, 2023, 9(4): 1526-1537. DOI: 10.3390/tomography9040122.
[40]
CUI Y, ZENG W, JIANG H, et al. Higher Cho/NAA ratio in postoperative peritumoral edema zone is associated with earlier recurrence of glioblastoma[J/OL]. Front Neurol, 2020, 11: 592155 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/33343496/. DOI: 10.3389/fneur.2020.592155.
[41]
ERAKY A M, BECK R T, TREFFY R W, et al. Role of advanced MR imaging in diagnosis of neurological malignancies: Current status and future perspective[J/OL]. J Integr Neurosci, 2023, 22(3): 73 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37258452/. DOI: 10.31083/j.jin2203073.
[42]
FENG A, YUAN P, HUANG T, et al. Distinguishing tumor recurrence from radiation necrosis in treated glioblastoma using multiparametric MRI[J]. Acad Radiol, 2022, 29(9): 1320-1331. DOI: 10.1016/j.acra.2021.11.008.
[43]
VERMA G, CHAWLA S, MOHAN S, et al. Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma[J/OL]. NMR Biomed, 2019, 32(2): e4042 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/30556932/. DOI: 10.1002/nbm.4042.
[44]
YAN G, YI M, LI S, et al. Quantitative metabolic characteristics in the peritumoral region of gliomas at 7T[J]. Technol Health Care, 2021, 29(S1): 509-517. DOI: 10.3233/THC-218048.
[45]
ZHOU J, JIA G. Editorial for "amide proton transfer-weighted imaging could complement apparent diffusion coefficient for more lesion characterization in transition zone of the prostate"[J]. J Magn Reson Imaging, 2022, 56(5): 1320-1321. DOI: 10.1002/jmri.28224.
[46]
KOIKE H, MORIKAWA M, ISHIMARU H, et al. Amide proton transfer-chemical exchange saturation transfer imaging of intracranial brain tumors and tumor-like lesions: Our experience and a review[J/OL]. Diagnostics (Basel), 2023, 13(5): 914 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/36900058/. DOI: 10.3390/diagnostics13050914.
[47]
ZHANG N, ZHANG H, GAO B, et al. 3D amide proton transfer weighted brain tumor imaging with compressed SENSE: Effects of different acceleration factors[J/OL]. Front Neurosci, 2022, 16: 876587 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/35692419/. DOI: 10.3389/fnins.2022.876587.
[48]
SUGAWARA K, MIYATI T, WAKABAYASHI H, et al. Evaluation of brain tumors using amide proton transfer imaging: A comparison of normal amide proton transfer signal with abnormal amide proton transfer signal value[J]. J Comput Assist Tomogr, 2023, 47(1): 121-128. DOI: 10.1097/RCT.0000000000001378.
[49]
TANG P L Y, MENDEZ ROMERO A, JASPERS J P M, et al. The potential of advanced MR techniques for precision radiotherapy of glioblastoma[J]. MAGMA, 2022, 35(1): 127-143. DOI: 10.1007/s10334-021-00997-y.
[50]
HONG X, LIU L, WANG M, et al. Quantitative multiparametric MRI assessment of glioma response to radiotherapy in a rat model[J]. Neuro Oncol, 2014, 16(6): 856-867. DOI: 10.1093/neuonc/not245.
[51]
SAGIYAMA K, MASHIMO T, TOGAO O, et al. In vivo chemical exchange saturation transfer imaging allows early detection of a therapeutic response in glioblastoma[J]. Proc Natl Acad Sci U S A, 2014, 111(12): 4542-4547. DOI: 10.1073/pnas.1323855111.
[52]
LIU D, CHEN J, GE H, et al. Differentiation of malignant brain tumor types using intratumoral and peritumoral radiomic features[J/OL]. Front Oncol, 2022, 12: 848846 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/35965511/. DOI: 10.3389/fonc.2022.848846.
[53]
LI S, SU X, PENG J, et al. Development and external validation of an MRI-based radiomics nomogram to distinguish circumscribed astrocytic gliomas and diffuse gliomas: A multicenter study[J]. Acad Radiol, 2024, 31(2): 639-647. DOI: 10.1016/j.acra.2023.06.033.
[54]
GUO Z, TIAN Z, SHI F, et al. Radiomic features of the edema region may contribute to grading meningiomas with peritumoral edema[J]. J Magn Reson Imaging, 2023, 58(1): 301-310. DOI: 10.1002/jmri.28494.
[55]
ZHU X, HE Y, WANG M, et al. Intratumoral and peritumoral multiparametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in glioblastoma: A two-center study[J/OL]. Acad Radiol, 2023 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37865602/. DOI: 10.1016/j.acra.2023.09.010.
[56]
FAN Y, WANG X, DONG Y, et al. Multiregional radiomics of brain metastasis can predict response to EGFR-TKI in metastatic NSCLC[J]. Eur Radiol, 2023, 33(11): 7902-7912. DOI: 10.1007/s00330-023-09709-7.
[57]
ZHANG H, ZHOU B, ZHANG H, et al. Peritumoral radiomics for identification of telomerase reverse transcriptase promoter mutation in patients with glioblastoma based on preoperative MRI[J/OL]. Can Assoc Radiol J, 2023: 8465371231183309 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/37552107/. DOI: 10.1177/08465371231183309.
[58]
SOHN B, AN C, KIM D, et al. Radiomics-based prediction of multiple gene alteration incorporating mutual genetic information in glioblastoma and grade 4 astrocytoma, IDH-mutant[J]. J Neurooncol, 2021, 155(3): 267-276. DOI: 10.1007/s11060-021-03870-z.
[59]
BEIG N, BERA K, PRASANNA P, et al. Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in glioblastoma[J]. Clin Cancer Res, 2020, 26(8): 1866-1876. DOI: 10.1158/1078-0432.CCR-19-2556.
[60]
CEPEDA S, LUPPINO L T, PEREZ-NUNEZ A, et al. Predicting regions of local recurrence in glioblastomas using voxel-based radiomic features of multiparametric postoperative MRI[J/OL]. Cancers (Basel), 2023, 15(6): 1894 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/36980783/. DOI: 10.3390/cancers15061894.
[61]
MEIßNER A K, GUTSCHE R, GALLDIKS N, et al. Radiomics for the noninvasive prediction of the BRAF mutation status in patients with melanoma brain metastases[J]. Neuro Oncol, 2022, 24(8): 1331-1340. DOI: 10.1093/neuonc/noab294.
[62]
CHARLTON C E, POON M T C, BRENNAN P M, et al. Development of prediction models for one-year brain tumour survival using machine learning: a comparison of accuracy and interpretability[J/OL]. Comput methods programs biomed, 2023, 233: 107482 [2024-02-26]. https://pubmed.ncbi.nlm.nih.gov/36947980/. DOI: 10.1016/j.cmpb.2023.107482.

PREV Research progress on the glymphatic system of patients with central nervous system diseases based on diffusion tensor image analysis along the perivascular space
NEXT Research progress of MRI radiomics in pituitary neuroendocrine tumors
  


LINK


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