Diffuse glioma molecular profiling with arterial spin labeling and dynamic susceptibility contrast perfusion MRI: A comparative study
Status PubMed-not-MEDLINE Jazyk angličtina Země Anglie, Velká Británie Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
39036439
PubMed Central
PMC11259011
DOI
10.1093/noajnl/vdae113
PII: vdae113
Knihovny.cz E-zdroje
BACKGROUND: Evaluation of molecular markers (IDH, pTERT, 1p/19q codeletion, and MGMT) in adult diffuse gliomas is crucial for accurate diagnosis and optimal treatment planning. Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) perfusion MRI techniques have both shown good performance in classifying molecular markers, however, their performance has not been compared side-by-side. METHODS: Pretreatment MRI data from 90 patients diagnosed with diffuse glioma (54 men/36 female, 53.1 ± 15.5 years, grades 2-4) were retrospectively analyzed. DSC-derived normalized cerebral blood flow/volume (nCBF/nCBV) and ASL-derived nCBF in tumor and perifocal edema were analyzed in patients with available IDH-mutation (n = 67), pTERT-mutation (n = 39), 1p/19q codeletion (n = 33), and MGMT promoter methylation (n = 31) status. Cross-validated uni- and multivariate logistic regression models assessed perfusion parameters' performance in molecular marker detection. RESULTS: ASL and DSC perfusion parameters in tumor and edema distinguished IDH-wildtype (wt) and pTERT-wt tumors from mutated ones. Univariate classification performance was comparable for ASL-nCBF and DSC-nCBV in IDH (maximum AUROCC 0.82 and 0.83, respectively) and pTERT (maximum AUROCC 0.70 and 0.81, respectively) status differentiation. The multivariate approach improved IDH (DSC-nCBV AUROCC 0.89) and pTERT (ASL-nCBF AUROCC 0.8 and DSC-nCBV AUROCC 0.86) classification. However, ASL and DSC parameters could not differentiate 1p/19q codeletion or MGMT promoter methylation status. Positive correlations were found between ASL-nCBF and DSC-nCBV/-nCBF in tumor and edema. CONCLUSIONS: ASL is a viable gadolinium-free replacement for DSC for molecular characterization of adult diffuse gliomas.
Center for Lifespan Changes in Brain and Cognition University of Oslo Oslo Norway
Department of Neurosurgery Amsterdam University Medical Center Amsterdam The Netherlands
Department of Neurosurgery Oslo University Hospital Oslo Norway
Department of Oncology Oslo University Hospital Oslo Norway
Department of Pathology Oslo University Hospital Oslo Norway
Department of Pathophysiology 2nd Faculty of Medicine Charles University Prague The Czech Republic
Institute of Clinical Medicine Faculty of Medicine University of Oslo Oslo Norway
Zobrazit více v PubMed
WHO Classification of Tumours Editorial Board. World Health Organization Classification of Tumours of the Central Nervous System. 5th ed. Lyon: International Agency for Research on Cancer; 2021.
Crocetti E, Trama A, Stiller C, et al.; RARECARE Working Group. Epidemiology of glial and non-glial brain tumours in Europe. Eur J Cancer. 2012;48(10):1532–1542. PubMed
Molinaro AM, Taylor JW, Wiencke JK, Wrensch MR.. Genetic and molecular epidemiology of adult diffuse glioma. Nat Rev Neurol. 2019;15(7):405–417. PubMed PMC
Karschnia P, Smits M, Reifenberger G, et al.; Expert Rater Panel. A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups. Lancet Oncol. 2023;24(11):e438–e450. PubMed PMC
Brell M, Ibáñez J, Caral L, Ferrer E.. Factors influencing surgical complications of intra-axial brain tumours. Acta Neurochir (Wien). 2000;142(7):739–750. PubMed
Islam S, Morrison MA, Waldman AD.. Quantitative and physiological magnetic resonance imaging in glioma. In: Faro SH, Mohamed FB, eds. Functional Neuroradiology: Principles and Clinical Applications. Cham: Springer International Publishing; 2023:433–457.
Hirschler L, Sollmann N, Schmitz-Abecassis B, et al.. Advanced MR techniques for preoperative glioma characterization: part 1. J Magn Reson Imaging. 2023;57(6):1655–1675. PubMed PMC
Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, et al.. High-grade glioma treatment response monitoring biomarkers: a position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and the latest bench-to-bedside developments. part 1: perfusion and diffusion techniques. Front Oncol. 2022;12:810263. PubMed PMC
García-Figueiras R, Padhani AR, Beer AJ, et al.. Imaging of tumor angiogenesis for radiologists--part 1: biological and technical basis. Curr Probl Diagn Radiol. 2015;44(5):407–424. PubMed
Zhou J, Li N, Yang G, Zhu Y.. Vascular patterns of brain tumors. Int J Surg Pathol. 2011;19(6):709–717. PubMed
Boxerman JL, Quarles CC, Hu LS, et al.; Jumpstarting Brain Tumor Drug Development Coalition Imaging Standardization Steering Committee. Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas. Neuro-Oncology. 2020;22(9):1262–1275. PubMed PMC
Hernandez-Garcia L, Aramendía-Vidaurreta V, Bolar DS, et al.. Recent technical developments in ASL: a review of the state of the art. Magn Reson Med. 2022;88(5):2021–2042. PubMed PMC
Mallio CA, Rovira A, Parizel PM, Quattrocchi CC.. Exposure to gadolinium and neurotoxicity: current status of preclinical and clinical studies. Neuroradiology. 2020;62(8):925–934. PubMed
Wamelink IJHG, Hempel HL, van de Giessen E, et al.. The patients’ experience of neuroimaging of primary brain tumors: a cross-sectional survey study. J Neurooncol. 2023;162(2):307–315. PubMed PMC
Ma H, Wang Z, Xu K, et al.. Three-dimensional arterial spin labeling imaging and dynamic susceptibility contrast perfusion-weighted imaging value in diagnosing glioma grade prior to surgery. Exp Ther Med. 2017;13(6):2691–2698. PubMed PMC
Xiao HF, Chen ZY, Lou X, et al.. Astrocytic tumour grading: a comparative study of three-dimensional pseudocontinuous arterial spin labelling, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and diffusion-weighted imaging. Eur Radiol. 2015;25(12):3423–3430. PubMed PMC
Weber MA, Zoubaa S, Schlieter M, et al.. Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology. 2006;66(12):1899–1906. PubMed
Hosur B, Ahuja CK, Singla N, Gupta K, Singh P.. Advanced multiparametric MRI-based scoring for isocitrate dehydrogenase mutation prediction of gliomas. Pol J Radiol. 2022;87:e626–e634. PubMed PMC
Chatha G, Dhaliwal T, Castle-Kirszbaum MD, et al.. The utility of arterial spin labelled perfusion-weighted magnetic resonance imaging in measuring the vascularity of high grade gliomas: a prospective study. Heliyon. 2023;9(7):e17615. PubMed PMC
van Santwijk L, Kouwenberg V, Meijer F, Smits M, Henssen D.. A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging. Insights Imaging. 2022;13(1):102. PubMed PMC
Friston K, Ashburner J, Kiebel S, Nichols T, Penny W, eds. Statistical parametric mapping: the analysis of functional brain images. In: Statistical Parametric Mapping: The Analysis of Functional Brain Images. London: Academic Press; 2011.
Isensee F, Jäger PF, Kohl SAA, Petersen J, Maier-Hein KH.. Automated design of deep learning methods for biomedical image s segmentation. Nat Methods. 2021;18(2):203–211. PubMed
Bouget D, Eijgelaar RS, Pedersen A, et al.. Glioblastoma surgery imaging-reporting and data system: validation and performance of the automated segmentation task. Cancers. 2021;13(18):4674. PubMed PMC
Mutsaerts HJMM, Petr J, Groot P, et al.. ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies. Neuroimage. 2020;219:117031. PubMed
Alsop DC, Detre JA, Golay X, et al.. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73(1):102–116. PubMed PMC
Gaser C. Partial volume segmentation with adaptive maximum a posteriori (MAP) approach. Neuroimage. 2009;47:S121.
Bjørnerud A, Emblem KE.. A fully automated method for quantitative cerebral hemodynamic analysis using DSC-MRI. J Cereb Blood Flow Metab. 2010;30(5):1066–1078. PubMed PMC
Zhang L, He L, Lugano R, et al.. IDH mutation status is associated with distinct vascular gene expression signatures in lower-grade gliomas. Neuro-Oncology. 2018;20(11):1505–1516. PubMed PMC
Álvarez-Torres MM, López-Cerdán A, Andreu Z, et al.. Vascular differences between IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 at imaging and transcriptomic levels. NMR Biomed. 2023;36(11):e5004. PubMed
Cindil E, Sendur HN, Cerit MN, et al.. Prediction of IDH mutation status in high-grade gliomas using DWI and high T1-weight DSC-MRI. Acad Radiol. 2022;29:S52–S62. PubMed
Guo D, Binghu J.. Noninvasively evaluating the grade and IDH mutation status of gliomas by using mono-exponential, bi-exponential diffusion-weighted imaging and three-dimensional pseudo-continuous arterial spin labeling. Eur J Radiol. 1107;160(2023):21. PubMed
Siakallis L, Topriceanu C-C, Panovska-Griffiths J, Bisdas S.. The role of DSC MR perfusion in predicting IDH mutation and 1p19q codeletion status in gliomas: meta-analysis and technical considerations. Neuroradiology. 2023;65(7):1111–1126. PubMed PMC
Peng H, Huo J, Li B, . et al.. Predicting isocitrate dehydrogenase (IDH) mutation status in gliomas using multiparameter MRI radiomics features. J Magn Reson Imaging. 2021;53(5):1399–1407. PubMed
Zhang H-W, lyu G-W, He W-J, et al.. DSC and DCE histogram analyses of glioma biomarkers, including IDH, MGMT, and TERT, on differentiation and survival. Acad Radiol. 2020;27(12):e263–e271. PubMed
Wang N, Xie S-Y, Liu H-M, Chen G-Q, Zhang W-D.. Arterial spin labeling for glioma grade discrimination: correlations with IDH1 genotype and 1p/19q status. Transl Oncol. 2019;12(5):749–756. PubMed PMC
Yang X, Lin Y, Xing Z, She D, Su Y, Cao D.. Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas. Acta Radiol. 2021;62(12):1657–1665. PubMed
Yoo R-E, Yun TJ, Hwang I, et al.. Arterial spin labeling perfusion-weighted imaging aids in prediction of molecular biomarkers and survival in glioblastomas. Eur Radiol. 2020;30(2):1202–1211. PubMed
Song S, Shan Y, Wang L, et al.. MGMT promoter methylation status shows no effect on [18F] FET uptake and CBF in gliomas: a stereotactic image-based histological validation study. Eur Radiol. 2022;32(8):5577–5587. PubMed
Fuster-Garcia E, Lorente Estellés D, Álvarez-Torres MM, et al.. MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas. Eur Radiol. 2021;31(3):1738–1747. PubMed PMC
Järnum H, Steffensen EG, Knutsson L, et al.. Perfusion MRI of brain tumours: a comparative study of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast imaging. Neuroradiology. 2010;52(4):307–317. PubMed PMC
Novak J, Withey SB, Lateef S, et al.. A comparison of pseudo-continuous arterial spin labelling and dynamic susceptibility contrast MRI with and without contrast agent leakage correction in paediatric brain tumours. Br J Radiol. 2019;92(1094):20170872. PubMed PMC
Juan-Albarracín J, Fuster-Garcia E, García-Ferrando GA, García-Gómez JM.. ONCOhabitats: A system for glioblastoma heterogeneity assessment through MRI. Int J Med Inform. 2019;128:53–61. PubMed
Iv M, Liu X, Lavezo J, et al.. Perfusion MRI-based fractional tumor burden differentiates between tumor and treatment effect in recurrent glioblastomas and informs clinical decision-making. Am J Neuroradiol. 2019;40(10):1649–1657. PubMed PMC
Lüdemann L, Warmuth C, Plotkin M, et al.. Brain tumor perfusion: Comparison of dynamic contrast enhanced magnetic resonance imaging using T1, T2, and T2* contrast, pulsed arterial spin labeling, and H215O positron emission tomography. Eur J Radiol. 2009;70(3):465–474. PubMed
Ellingson BM, Zaw T, Cloughesy TF, et al.. Comparison between intensity normalization techniques for dynamic susceptibility contrast (DSC)-MRI estimates of cerebral blood volume (CBV) in human gliomas. J Magn Reson Imaging. 2012;35(6):1472–1477. PubMed
Østergaard L, Tietze A, Nielsen T, et al.. The relationship between tumor blood flow, angiogenesis, tumor hypoxia, and aerobic glycolysis. Cancer Res. 2013;73(18):5618–5624. PubMed
Lindner T, Bolar DS, Achten E, et al.; on behalf of the ISMRM Perfusion Study Group. Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging. Magn Reson Med. 2023;89(5):2024–2047. PubMed PMC