{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T16:22:08Z","timestamp":1767802928449,"version":"3.49.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T00:00:00Z","timestamp":1764720000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T00:00:00Z","timestamp":1767744000000},"content-version":"vor","delay-in-days":35,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Natural Science Basic Research Program of Shanxi Province","award":["20210302124380"],"award-info":[{"award-number":["20210302124380"]}]},{"name":"Natural Science Basic Research Program of Shanxi Province","award":["20210302124386"],"award-info":[{"award-number":["20210302124386"]}]},{"name":"Central Guidance Funds for Local Science and Technology Development","award":["2022.12Y283"],"award-info":[{"award-number":["2022.12Y283"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Imaging"],"DOI":"10.1186\/s12880-025-02101-5","type":"journal-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T02:34:54Z","timestamp":1764729294000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Histogram analysis of IVIM MRI for differentiating glioma IDH-1 status, grade, and Ki-67 expression: a comparison of bi-exponential models at multiple B-value"],"prefix":"10.1186","volume":"26","author":[{"given":"Yifei","family":"Su","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junhao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ding","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuanchen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochen","family":"Niu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaoju","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunhong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yexin","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongming","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,3]]},"reference":[{"issue":"4","key":"2101_CR1","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1093\/neuonc\/noz009","volume":"21","author":"JE Eckel-Passow","year":"2019","unstructured":"Eckel-Passow JE, Decker PA, Kosel ML, Kollmeyer TM, Molinaro AM, Rice T, Caron AA, Drucker KL, Praska CE, Pekmezci M, et al. Using germline variants to estimate glioma and subtype risks. Neuro Oncol. 2019;21(4):451\u201361.","journal-title":"Neuro Oncol"},{"issue":"6","key":"2101_CR2","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1007\/s00401-016-1545-1","volume":"131","author":"DN Louis","year":"2016","unstructured":"Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW. The 2016 world health organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. 2016;131(6):803\u201320.","journal-title":"Acta Neuropathol"},{"issue":"3","key":"2101_CR3","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1016\/j.cell.2015.12.028","volume":"164","author":"M Ceccarelli","year":"2016","unstructured":"Ceccarelli M, Barthel FP, Malta TM, Sabedot TS, Salama SR, Murray BA, Morozova O, Newton Y, Radenbaugh A, Pagnotta SM, et al. Molecular profiling reveals biologically discrete subsets and pathways of progression in diffuse glioma. Cell. 2016;164(3):550\u201363.","journal-title":"Cell"},{"issue":"2","key":"2101_CR4","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1007\/s13311-017-0519-x","volume":"14","author":"R Chen","year":"2017","unstructured":"Chen R, Smith-Cohn M, Cohen AL, Colman H. Glioma subclassifications and their clinical significance. Neurotherapeutics. 2017;14(2):284\u201397.","journal-title":"Neurotherapeutics"},{"issue":"1","key":"2101_CR5","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1186\/s13000-018-0711-2","volume":"13","author":"LAG Nielsen","year":"2018","unstructured":"Nielsen LAG, Bangs\u00f8 JA, Lindahl KH, Dahlrot RH, Hjelmborg JVB, Hansen S, Kristensen BW. Evaluation of the proliferation marker Ki-67 in gliomas: interobserver variability and digital quantification. Diagn Pathol. 2018;13(1):38.","journal-title":"Diagn Pathol"},{"key":"2101_CR6","doi-asserted-by":"publisher","first-page":"696037","DOI":"10.3389\/fonc.2022.696037","volume":"12","author":"Z Zhang","year":"2022","unstructured":"Zhang Z, Gu W, Hu M, Zhang G, Yu F, Xu J, Deng J, Xu L, Mei J, Wang C, Qiu F. Based on clinical Ki-67 expression and serum infiltrating lymphocytes related nomogram for predicting the diagnosis of glioma-grading. Front Oncol. 2022;12:696037.","journal-title":"Front Oncol"},{"issue":"2","key":"2101_CR7","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/s11060-023-04342-2","volume":"163","author":"P Tini","year":"2023","unstructured":"Tini P, Yavoroska M, Mazzei MA, Miracco C, Pirtoli L, Tomaciello M, Marampon F, Minniti G. Low expression of Ki-67\/MIB-1 labeling index in IDH wild type glioblastoma predicts prolonged survival independently by MGMT methylation status. J Neurooncol. 2023;163(2):339\u201344.","journal-title":"J Neurooncol"},{"issue":"5","key":"2101_CR8","doi-asserted-by":"publisher","first-page":"1513","DOI":"10.1111\/cas.13579","volume":"109","author":"K Sumiyoshi","year":"2018","unstructured":"Sumiyoshi K, Koso H, Watanabe S. Spontaneous development of intratumoral heterogeneity in a transposon-induced mouse model of glioma. Cancer Sci. 2018;109(5):1513\u201323.","journal-title":"Cancer Sci"},{"key":"2101_CR9","doi-asserted-by":"publisher","first-page":"703764","DOI":"10.3389\/fonc.2021.703764","volume":"11","author":"A Comba","year":"2021","unstructured":"Comba A, Faisal SM, Varela ML, Hollon T, Al-Holou WN, Umemura Y, Nunez FJ, Motsch S, Castro MG, Lowenstein PR. Uncovering Spatiotemporal heterogeneity of High-Grade gliomas: from disease biology to therapeutic implications. Front Oncol. 2021;11:703764.","journal-title":"Front Oncol"},{"issue":"4","key":"2101_CR10","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1158\/1541-7786.MCR-17-0680","volume":"16","author":"DH Heiland","year":"2018","unstructured":"Heiland DH, Gaebelein A, B\u00f6rries M, W\u00f6rner J, Pompe N, Franco P, Heynckes S, Bartholomae M, hAil\u00edn D, Carro MS, et al. Microenvironment-Derived regulation of HIF signaling drives transcriptional heterogeneity in glioblastoma multiforme. Mol Cancer Res. 2018;16(4):655\u201368.","journal-title":"Mol Cancer Res"},{"issue":"1","key":"2101_CR11","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1002\/mrm.1910270116","volume":"27","author":"D Le Bihan","year":"1992","unstructured":"Le Bihan D, Turner R. The capillary network: a link between IVIM and classical perfusion. Magn Reson Med. 1992;27(1):171\u20138.","journal-title":"Magn Reson Med"},{"issue":"4","key":"2101_CR12","doi-asserted-by":"publisher","first-page":"2871","DOI":"10.1007\/s00330-022-09212-5","volume":"33","author":"M Cao","year":"2023","unstructured":"Cao M, Wang X, Liu F, Xue K, Dai Y, Zhou Y. A three-component multi-b-value diffusion-weighted imaging might be a useful biomarker for detecting microstructural features in gliomas with differences in malignancy and IDH-1 mutation status. Eur Radiol. 2023;33(4):2871\u201380.","journal-title":"Eur Radiol"},{"key":"2101_CR13","doi-asserted-by":"publisher","first-page":"110721","DOI":"10.1016\/j.ejrad.2023.110721","volume":"160","author":"D Guo","year":"2023","unstructured":"Guo D, Jiang B. 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. 2023;160:110721.","journal-title":"Eur J Radiol"},{"key":"2101_CR14","doi-asserted-by":"publisher","first-page":"432","DOI":"10.3389\/fnagi.2017.00432","volume":"9","author":"M Cao","year":"2017","unstructured":"Cao M, Suo S, Han X, Jin K, Sun Y, Wang Y, Ding W, Qu J, Zhang X, Zhou Y. Application of a simplified method for estimating perfusion derived from Diffusion-Weighted MR imaging in glioma grading. Front Aging Neurosci. 2017;9:432.","journal-title":"Front Aging Neurosci"},{"issue":"1","key":"2101_CR15","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1093\/neuonc\/nov147","volume":"18","author":"O Togao","year":"2016","unstructured":"Togao O, Hiwatashi A, Yamashita K, Kikuchi K, Mizoguchi M, Yoshimoto K, Suzuki SO, Iwaki T, Obara M, Van Cauteren M, Honda H. Differentiation of high-grade and low-grade diffuse gliomas by intravoxel incoherent motion MR imaging. Neuro Oncol. 2016;18(1):132\u201341.","journal-title":"Neuro Oncol"},{"issue":"3","key":"2101_CR16","doi-asserted-by":"publisher","first-page":"216","DOI":"10.2463\/mrms.mp.2019-0061","volume":"19","author":"S Chabert","year":"2020","unstructured":"Chabert S, Verdu J, Huerta G, Montalba C, Cox P, Riveros R, Uribe S, Salas R, Veloz A. Impact of b-Value sampling scheme on brain IVIM parameter Estimation in healthy subjects. Magn Reson Med Sci. 2020;19(3):216\u201326.","journal-title":"Magn Reson Med Sci"},{"issue":"1","key":"2101_CR17","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.crad.2016.09.007","volume":"72","author":"C Wang","year":"2017","unstructured":"Wang C, Ren D, Guo Y, Xu Y, Feng Y, Zhang X, Mei Y, Chen M, Xiao X. Distribution of intravoxel incoherent motion MRI-related parameters in the brain: evidence of interhemispheric asymmetry. Clin Radiol. 2017;72(1):94. e91-94 e96.","journal-title":"Clin Radiol"},{"issue":"1","key":"2101_CR18","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1002\/mrm.28708","volume":"86","author":"W Lee","year":"2021","unstructured":"Lee W, Kim B, Park H. Quantification of intravoxel incoherent motion with optimized b-values using deep neural network. Magn Reson Med. 2021;86(1):230\u201344.","journal-title":"Magn Reson Med"},{"issue":"11","key":"2101_CR19","doi-asserted-by":"publisher","first-page":"4516","DOI":"10.1007\/s00330-017-4867-z","volume":"27","author":"H Yu","year":"2017","unstructured":"Yu H, Lou H, Zou T, Wang X, Jiang S, Huang Z, Du Y, Jiang C, Ma L, Zhu J, et al. Applying protein-based amide proton transfer MR imaging to distinguish solitary brain metastases from glioblastoma. Eur Radiol. 2017;27(11):4516\u201324.","journal-title":"Eur Radiol"},{"issue":"4","key":"2101_CR20","doi-asserted-by":"publisher","first-page":"2142","DOI":"10.1007\/s00330-019-06548-3","volume":"30","author":"M Kim","year":"2020","unstructured":"Kim M, Jung SY, Park JE, Jo Y, Park SY, Nam SJ, Kim JH, Kim HS. Diffusion- and perfusion-weighted MRI radiomics model May predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma. Eur Radiol. 2020;30(4):2142\u201351.","journal-title":"Eur Radiol"},{"key":"2101_CR21","unstructured":"fminsearchbnd fminsearchcon. [https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/8277-fminsearchbnd-fminsearchcon]."},{"issue":"10","key":"2101_CR22","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1097\/PAI.0000000000000702","volume":"27","author":"DD Gondim","year":"2019","unstructured":"Gondim DD, Gener MA, Curless KL, Cohen-Gadol AA, Hattab EM, Cheng L. Determining IDH-Mutational status in gliomas using IDH1-R132H antibody and polymerase chain reaction. Appl Immunohistochem Mol Morphol. 2019;27(10):722\u20135.","journal-title":"Appl Immunohistochem Mol Morphol"},{"issue":"2","key":"2101_CR23","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s10014-011-0023-7","volume":"28","author":"S Takano","year":"2011","unstructured":"Takano S, Tian W, Matsuda M, Yamamoto T, Ishikawa E, Kaneko MK, Yamazaki K, Kato Y, Matsumura A. Detection of IDH1 mutation in human gliomas: comparison of immunohistochemistry and sequencing. Brain Tumor Pathol. 2011;28(2):115\u201323.","journal-title":"Brain Tumor Pathol"},{"issue":"10","key":"2101_CR24","doi-asserted-by":"publisher","first-page":"7003","DOI":"10.1007\/s00330-023-09695-w","volume":"33","author":"X Yang","year":"2023","unstructured":"Yang X, Hu C, Xing Z, Lin Y, Su Y, Wang X, Cao D. Prediction of Ki-67 labeling index, ATRX mutation, and MGMT promoter methylation status in IDH-mutant Astrocytoma by morphological MRI, SWI, DWI, and DSC-PWI. Eur Radiol. 2023;33(10):7003\u201314.","journal-title":"Eur Radiol"},{"issue":"1","key":"2101_CR25","doi-asserted-by":"publisher","first-page":"100","DOI":"10.3340\/jkns.2020.0071","volume":"64","author":"HMB Bolly","year":"2021","unstructured":"Bolly HMB, Faried A, Hermanto Y, Lubis BP, Tjahjono FP, Hernowo BS, Arifin MZ. Analysis of mutant isocitrate dehydrogenase 1 Immunoexpression, Ki-67 and programmed death ligand 1 in diffuse astrocytic tumours: study of single center in Bandung, Indonesia. J Korean Neurosurg Soc. 2021;64(1):100\u20139.","journal-title":"J Korean Neurosurg Soc"},{"issue":"8","key":"2101_CR26","doi-asserted-by":"publisher","first-page":"3397","DOI":"10.1016\/j.acra.2024.02.009","volume":"31","author":"J Ni","year":"2024","unstructured":"Ni J, Zhang H, Yang Q, Fan X, Xu J, Sun J, Zhang J, Hu Y, Xiao Z, Zhao Y, et al. Machine-Learning and Radiomics-Based preoperative prediction of Ki-67 expression in glioma using MRI data. Acad Radiol. 2024;31(8):3397\u2013405.","journal-title":"Acad Radiol"},{"issue":"1","key":"2101_CR27","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s11060-017-2506-9","volume":"134","author":"K Leu","year":"2017","unstructured":"Leu K, Ott GA, Lai A, Nghiemphu PL, Pope WB, Yong WH, Liau LM, Cloughesy TF, Ellingson BM. Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II-III diffuse gliomas. J Neurooncol. 2017;134(1):177\u201388.","journal-title":"J Neurooncol"},{"issue":"8","key":"2101_CR28","doi-asserted-by":"publisher","first-page":"e576","DOI":"10.1016\/j.crad.2022.03.015","volume":"77","author":"Z Xing","year":"2022","unstructured":"Xing Z, Huang W, Su Y, Yang X, Zhou X, Cao D. Non-invasive prediction of p53 and Ki-67 labelling indices and O-6-methylguanine-DNA methyltransferase promoter methylation status in adult patients with isocitrate dehydrogenase wild-type glioblastomas using diffusion-weighted imaging and dynamic susceptibility contrast-enhanced perfusion-weighted imaging combined with conventional MRI. Clin Radiol. 2022;77(8):e576\u201384.","journal-title":"Clin Radiol"},{"issue":"2","key":"2101_CR29","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1007\/s00234-015-1606-5","volume":"58","author":"R Yan","year":"2016","unstructured":"Yan R, Haopeng P, Xiaoyuan F, Jinsong W, Jiawen Z, Chengjun Y, Tianming Q, Ji X, Mao S, Yueyue D, et al. Non-Gaussian diffusion MR imaging of glioma: comparisons of multiple diffusion parameters and correlation with histologic grade and MIB-1 (Ki-67 labeling) index. Neuroradiology. 2016;58(2):121\u201332.","journal-title":"Neuroradiology"},{"issue":"2","key":"2101_CR30","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s11060-024-04609-2","volume":"167","author":"M Yu","year":"2024","unstructured":"Yu M, Ge Y, Wang Z, Zhang Y, Hou X, Chen H, Chen X, Ji N, Li X, Shen H. The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study. J Neurooncol. 2024;167(2):305\u201313.","journal-title":"J Neurooncol"},{"key":"2101_CR31","doi-asserted-by":"crossref","unstructured":"Gihr G, Horvath-Rizea D, Kohlhof-Meinecke P, Ganslandt O, Henkes H, H\u00e4rtig W, Donitza A, Skalej M, Schob S. Diffusion weighted imaging in gliomas: a histogram-based approach for tumor characterization. Cancers (Basel) 2022;14(14).","DOI":"10.3390\/cancers14143393"},{"key":"2101_CR32","doi-asserted-by":"publisher","first-page":"1099019","DOI":"10.3389\/fnins.2022.1099019","volume":"16","author":"Z Xie","year":"2022","unstructured":"Xie Z, Li J, Zhang Y, Zhou R, Zhang H, Duan C, Liu S, Niu L, Zhao J, Liu Y, et al. The diagnostic value of ADC histogram and direct ADC measurements for coexisting isocitrate dehydrogenase mutation and O6-methylguanine-DNA methyltransferase promoter methylation in glioma. Front Neurosci. 2022;16:1099019.","journal-title":"Front Neurosci"},{"issue":"2","key":"2101_CR33","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1007\/s00330-023-10071-x","volume":"34","author":"R Kurokawa","year":"2024","unstructured":"Kurokawa R, Hagiwara A, Kurokawa M, Ellingson BM, Baba A, Moritani T. Diffusion histogram profiles predict molecular features of grade 4 in histologically lower-grade adult diffuse gliomas following WHO classification 2021. Eur Radiol. 2024;34(2):1367\u201375.","journal-title":"Eur Radiol"},{"issue":"2","key":"2101_CR34","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1148\/radiol.2015142173","volume":"278","author":"Y Bai","year":"2016","unstructured":"Bai Y, Lin Y, Tian J, Shi D, Cheng J, Haacke EM, Hong X, Ma B, Zhou J, Wang M. Grading of gliomas by using Monoexponential, Biexponential, and stretched exponential diffusion-weighted MR imaging and diffusion kurtosis MR imaging. Radiology. 2016;278(2):496\u2013504.","journal-title":"Radiology"},{"issue":"3","key":"2101_CR35","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1002\/jmri.25191","volume":"44","author":"N Shen","year":"2016","unstructured":"Shen N, Zhao L, Jiang J, Jiang R, Su C, Zhang S, Tang X, Zhu W. Intravoxel incoherent motion diffusion-weighted imaging analysis of diffusion and microperfusion in grading gliomas and comparison with arterial spin labeling for evaluation of tumor perfusion. J Magn Reson Imaging. 2016;44(3):620\u201332.","journal-title":"J Magn Reson Imaging"},{"key":"2101_CR36","doi-asserted-by":"publisher","first-page":"111140","DOI":"10.1016\/j.ejrad.2023.111140","volume":"168","author":"J Guo","year":"2023","unstructured":"Guo J, Fu X, Li Y, Ming H, Lin Y, Yu S, Wei H, Sun C, Zhang K, Yang X. Ultra high b-value diffusion weighted imaging enables better molecular grading stratification over histological grading in adult-type diffuse glioma. Eur J Radiol. 2023;168:111140.","journal-title":"Eur J Radiol"},{"issue":"10","key":"2101_CR37","doi-asserted-by":"publisher","first-page":"6751","DOI":"10.1007\/s00330-024-10708-5","volume":"34","author":"X Wang","year":"2024","unstructured":"Wang X, Shu X, He P, Cai Y, Geng Y, Hu X, Sun Y, Xiao H, Zheng W, Song Y, et al. Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. Eur Radiol. 2024;34(10):6751\u201362.","journal-title":"Eur Radiol"},{"issue":"7","key":"2101_CR38","doi-asserted-by":"publisher","first-page":"9948","DOI":"10.18632\/aging.202751","volume":"13","author":"T Gu","year":"2021","unstructured":"Gu T, Yang T, Huang J, Yu J, Ying H, Xiao X. Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI. Aging. 2021;13(7):9948\u201359.","journal-title":"Aging"},{"key":"2101_CR39","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.mri.2022.04.003","volume":"90","author":"N Mori","year":"2022","unstructured":"Mori N, Inoue C, Tamura H, Nagasaka T, Ren H, Sato S, Mori Y, Miyashita M, Mugikura S, Takase K. Apparent diffusion coefficient and intravoxel incoherent motion-diffusion kurtosis model parameters in invasive breast cancer: correlation with the histological parameters of whole-slide imaging. Magn Reson Imaging. 2022;90:53\u201360.","journal-title":"Magn Reson Imaging"},{"issue":"1121","key":"2101_CR40","doi-asserted-by":"publisher","first-page":"20201321","DOI":"10.1259\/bjr.20201321","volume":"94","author":"H Luo","year":"2021","unstructured":"Luo H, He L, Cheng W, Gao S. The diagnostic value of intravoxel incoherent motion imaging in differentiating high-grade from low-grade gliomas: a systematic review and meta-analysis. Br J Radiol. 2021;94(1121):20201321.","journal-title":"Br J Radiol"},{"issue":"10","key":"2101_CR41","doi-asserted-by":"publisher","first-page":"2299","DOI":"10.1016\/j.acra.2022.11.016","volume":"30","author":"S Fang","year":"2023","unstructured":"Fang S, Yang Y, Tao J, Yin Z, Liu Y, Duan Z, Liu W, Wang S. Intratumoral heterogeneity of fibrosarcoma xenograft models: Whole-Tumor histogram analysis of DWI and IVIM. Acad Radiol. 2023;30(10):2299\u2013308.","journal-title":"Acad Radiol"},{"issue":"4","key":"2101_CR42","doi-asserted-by":"publisher","first-page":"642","DOI":"10.14218\/JCTH.2021.00254","volume":"10","author":"Y Deng","year":"2022","unstructured":"Deng Y, Li J, Xu H, Ren A, Wang Z, Yang D, Yang Z. Diagnostic accuracy of the apparent diffusion coefficient for microvascular invasion in hepatocellular carcinoma: A Meta-analysis. J Clin Transl Hepatol. 2022;10(4):642\u201350.","journal-title":"J Clin Transl Hepatol"},{"issue":"6","key":"2101_CR43","doi-asserted-by":"publisher","first-page":"2373","DOI":"10.1002\/mrm.26598","volume":"78","author":"PT While","year":"2017","unstructured":"While PT. A comparative simulation study of bayesian fitting approaches to intravoxel incoherent motion modeling in diffusion-weighted MRI. Magn Reson Med. 2017;78(6):2373\u201387.","journal-title":"Magn Reson Med"},{"key":"2101_CR44","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.ejmp.2021.07.025","volume":"89","author":"E Scalco","year":"2021","unstructured":"Scalco E, Mastropietro A, Bodini A, Marzi S, Rizzo G. A Multi-Variate framework to assess reliability and discrimination power of bayesian Estimation of intravoxel incoherent motion parameters. Phys Med. 2021;89:11\u20139.","journal-title":"Phys Med"},{"issue":"3","key":"2101_CR45","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/s00401-021-02401-4","volume":"143","author":"SM Markwell","year":"2022","unstructured":"Markwell SM, Ross JL, Olson CL, Brat DJ. Necrotic reshaping of the glioma microenvironment drives disease progression. Acta Neuropathol. 2022;143(3):291\u2013310.","journal-title":"Acta Neuropathol"},{"issue":"3","key":"2101_CR46","doi-asserted-by":"publisher","first-page":"e4201","DOI":"10.1002\/nbm.4201","volume":"33","author":"E Lanzarone","year":"2020","unstructured":"Lanzarone E, Mastropietro A, Scalco E, Vidiri A, Rizzo G. A novel bayesian approach with conditional autoregressive specification for intravoxel incoherent motion diffusion-weighted MRI. NMR Biomed. 2020;33(3):e4201.","journal-title":"NMR Biomed"},{"key":"2101_CR47","doi-asserted-by":"publisher","first-page":"104978","DOI":"10.1016\/j.ejmp.2025.104978","volume":"133","author":"E Scalco","year":"2025","unstructured":"Scalco E, Rizzo G, Bertolino N, Mastropietro A. Leveraging deep learning for improving parameter extraction from perfusion MR images: A narrative review. Phys Med. 2025;133:104978.","journal-title":"Phys Med"},{"issue":"2","key":"2101_CR48","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1097\/RLI.0000000000000207","volume":"51","author":"EE ter Voert","year":"2016","unstructured":"ter Voert EE, Delso G, Porto M, Huellner M, Veit-Haibach P. Intravoxel incoherent motion protocol evaluation and data quality in normal and malignant liver tissue and comparison to the literature. Invest Radiol. 2016;51(2):90\u20139.","journal-title":"Invest Radiol"},{"issue":"5","key":"2101_CR49","doi-asserted-by":"publisher","first-page":"1209","DOI":"10.1002\/jmri.24693","volume":"41","author":"B Leporq","year":"2015","unstructured":"Leporq B, Saint-Jalmes H, Rabrait C, Pilleul F, Guillaud O, Dumortier J, Scoazec JY, Beuf O. Optimization of intra-voxel incoherent motion imaging at 3.0 Tesla for fast liver examination. J Magn Reson Imaging. 2015;41(5):1209\u201317.","journal-title":"J Magn Reson Imaging"},{"issue":"2","key":"2101_CR50","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1148\/radiology.168.2.3393671","volume":"168","author":"D Le Bihan","year":"1988","unstructured":"Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology. 1988;168(2):497\u2013505.","journal-title":"Radiology"},{"issue":"3","key":"2101_CR51","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1148\/radiol.2493081301","volume":"249","author":"D Le Bihan","year":"2008","unstructured":"Le Bihan D. Intravoxel incoherent motion perfusion MR imaging: a wake-up call. Radiology. 2008;249(3):748\u201352.","journal-title":"Radiology"},{"key":"2101_CR52","doi-asserted-by":"crossref","unstructured":"Bihan L D. What can we see with IVIM MRI? NeuroImage. 2019;187:56\u201367.","DOI":"10.1016\/j.neuroimage.2017.12.062"},{"key":"2101_CR53","doi-asserted-by":"crossref","unstructured":"Das JM. High-grade gliomas. In: Das JM, editor. Neuro-oncology explained through multiple choice questions. Cham: Springer International Publishing; 2023. p. 147-156.","DOI":"10.1007\/978-3-031-13253-7_15"},{"issue":"7","key":"2101_CR54","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1093\/neuonc\/nou087","volume":"16","author":"QT Ostrom","year":"2014","unstructured":"Ostrom QT, Bauchet L, Davis FG, Deltour I, Fisher JL, Langer CE, Pekmezci M, Schwartzbaum JA, Turner MC, Walsh KM, et al. The epidemiology of glioma in adults: a state of the science review. Neuro Oncol. 2014;16(7):896\u2013913.","journal-title":"Neuro Oncol"},{"issue":"1","key":"2101_CR55","doi-asserted-by":"publisher","first-page":"145","DOI":"10.4103\/jcrt.jcrt_2405_23","volume":"21","author":"V Kumar","year":"2025","unstructured":"Kumar V, Raghuvanshi S, Bhalla S, Rawat S, Ojha BK, Srivastava C, Goel MM. Immunohistochemical expression of PDL1 and Ki67 in glioma and its correlation with treatment and overall survival. J Cancer Res Ther. 2025;21(1):145\u201350.","journal-title":"J Cancer Res Ther"},{"key":"2101_CR56","doi-asserted-by":"publisher","first-page":"393","DOI":"10.2147\/IJGM.S397550","volume":"16","author":"D Priambada","year":"2023","unstructured":"Priambada D, Thohar Arifin M, Saputro A, Muzakka A, Karlowee V, Sadhana U, Bakhtiar Y, Prihastomo KT, Risdianto A, Brotoarianto HK, et al. Immunohistochemical expression of IDH1, ATRX, Ki67, GFAP, and prognosis in Indonesian glioma patients. Int J Gen Med. 2023;16:393\u2013403.","journal-title":"Int J Gen Med"},{"issue":"5","key":"2101_CR57","doi-asserted-by":"publisher","first-page":"217","DOI":"10.5414\/NP300422","volume":"30","author":"M Preusser","year":"2011","unstructured":"Preusser M, Capper D, Hartmann C. IDH testing in diagnostic neuropathology: review and practical guideline Article invited by the Euro-CNS research committee. Clin Neuropathol. 2011;30(5):217\u201330.","journal-title":"Clin Neuropathol"}],"container-title":["BMC Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-025-02101-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12880-025-02101-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-025-02101-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T14:05:01Z","timestamp":1767794701000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12880-025-02101-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,3]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["2101"],"URL":"https:\/\/doi.org\/10.1186\/s12880-025-02101-5","relation":{},"ISSN":["1471-2342"],"issn-type":[{"value":"1471-2342","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,3]]},"assertion":[{"value":"29 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Shanxi Provincial people\u2019s hospital (2024 Research Review, Date 2025-01-03\n                      \/\n                      No. 942). Informed consent was obtained from all individual participants included in the study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"10"}}