Burgenske DM, Yang J, Decker PA et al (2019) Molecular profiling of long-term IDH-wildtype glioblastoma survivors. Neuro Oncol. https://doi.org/10.1093/neuonc/noz129
Article PubMed PubMed Central Google Scholar
Gritsch S, Batchelor TT, Gonzalez Castro LN (2022) Diagnostic, therapeutic, and prognostic implications of the 2021 World Health Organization classification of tumors of the central nervous system. Cancer. https://doi.org/10.1002/cncr.33918
Komori T (2022) Grading of adult diffuse gliomas according to the 2021 WHO classification of tumors of the central nervous system. Lab Invest. https://doi.org/10.1038/s41374-021-00667-6
Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. https://doi.org/10.1093/neuonc/noab106
Article PubMed PubMed Central Google Scholar
Uribe-Cardenas R, Giantini-Larsen AM, Garton A, Juthani RG, Schwartz TH (2022) Innovations in the diagnosis and surgical management of low-grade gliomas. World Neurosurg. https://doi.org/10.1016/j.wneu.2022.06.070
Szychot E, Youssef A, Ganeshan B et al (2021) Predicting outcome in childhood diffuse midline gliomas using magnetic resonance imaging based texture analysis. J Neuroradiol. https://doi.org/10.1016/j.neurad.2020.02.005
Narvaez O, Svenningsson L, Yon M, Sierra A, Topgaard D (2022) Massively multi-dimensional diffusion-relaxation correlation MRI. Front Phys. https://doi.org/10.3389/fphy.2021.793966
Jalnefjord O, Andersson M, Montelius M et al (2018) Comparison of methods for estimation of the intravoxel incoherent motion (IVIM) diffusion coefficient (D) and perfusion fraction (f). MAGMA. https://doi.org/10.1007/s10334-018-0697-5
Hu LS, Hawkins-Daarud A, Wang L, Li J, Swanson KR (2020) Imaging of intratumoral heterogeneity in high-grade glioma. Cancer Lett. https://doi.org/10.1016/j.canlet.2020.02.025
Article PubMed PubMed Central Google Scholar
Guo D, Jiang B (2023) 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. https://doi.org/10.1016/j.ejrad.2023.110721
Maynard J, Okuchi S, Wastling S et al (2020) World Health Organization grade II/III glioma molecular status: prediction by MRI morphologic features and apparent diffusion coefficient. Radiology. https://doi.org/10.1148/radiol.2020191832
Gu W, Fang S, Hou X, Ma D, Li S (2021) Exploring diagnostic performance of T2 mapping in diffuse glioma grading. Quant Imaging Med Surg. https://doi.org/10.21037/qims-20-916
Article PubMed PubMed Central Google Scholar
Kern M, Auer TA, Picht T, Misch M, Wiener E (2020) T2 mapping of molecular subtypes of WHO grade II/III gliomas. BMC Neurol. https://doi.org/10.1186/s12883-019-1590-1
Article PubMed PubMed Central Google Scholar
Cao M, Ding W, Han X et al (2019) Brain T1ρ mapping for grading and IDH1 gene mutation detection of gliomas: a preliminary study. J Neurooncol. https://doi.org/10.1007/s11060-018-03033-7
Springer E, Cardoso PL, Strasser B et al (2022) MR fingerprinting—a radiogenomic marker for diffuse gliomas. Cancers (Basel). https://doi.org/10.3390/cancers14030723
Article PubMed PubMed Central Google Scholar
Auer TA, Kern M, Fehrenbach U et al (2021) T2 mapping of the peritumoral infiltration zone of glioblastoma and anaplastic astrocytoma. Neuroradiol J. https://doi.org/10.1177/1971400921989325
Article PubMed PubMed Central Google Scholar
Bontempi P, Rozzanigo U, Amelio D et al (2021) Quantitative multicomponent T2 relaxation showed greater sensitivity than flair imaging to detect subtle alterations at the periphery of lower grade gliomas. Front Oncol. https://doi.org/10.3389/fonc.2021.651137
Article PubMed PubMed Central Google Scholar
Toh CH, Chen YL, Hsieh TC et al (2006) Glioblastoma multiforme with diffusion-weighted magnetic resonance imaging characteristics mimicking primary brain lymphoma. case report. J Neurosurg. https://doi.org/10.3171/jns.2006.105.1.132
Kim Y, Lee SK, Kim JY, Kim JH (2023) Pitfalls of diffusion-weighted imaging: clinical utility of T2 shine-through and T2 black-out for musculoskeletal diseases. Diagnostics (Basel). https://doi.org/10.3390/diagnostics13091647
Article PubMed PubMed Central Google Scholar
Chatterjee A, Mercado C, Bourne RM et al (2022) Validation of prostate tissue composition by using hybrid multi-dimensional MRI: correlation with histologic findings. Radiology. https://doi.org/10.1148/radiol.2021204459
Chatterjee A, Antic T, Gallan AJ et al (2022) Histological validation of prostate tissue composition measurement using hybrid multi-dimensional MRI: agreement with pathologists’ measures. Abdom Radiol (NY). https://doi.org/10.1007/s00261-021-03371-7
Lee GH, Chatterjee A, Karademir I et al (2022) Comparing radiologist performance in diagnosing clinically significant prostate cancer with multiparametric versus hybrid multi-dimensional MRI. Radiology. https://doi.org/10.1148/radiol.211895
Article PubMed PubMed Central Google Scholar
Zeng Q, Shi F, Zhang J, Ling C, Dong F, Jiang B (2018) A modified tri-exponential model for multi-b-value diffusion-weighted imaging: a method to detect the strictly diffusion-limited compartment in brain. Front Neurosci. https://doi.org/10.3389/fnins.2018.00102
Article PubMed PubMed Central Google Scholar
Cao M, Wang X, Liu F, Xue K, Dai Y, Zhou Y (2023) 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. https://doi.org/10.1007/s00330-022-09212-5
Article PubMed PubMed Central Google Scholar
Yushkevich PA, Piven J, Hazlett HC et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. https://doi.org/10.1016/j.neuroimage.2006.01.015
Boruah D, Deb P, Srinivas V, Mani NS (2014) Morphometric study of nuclei and microvessels in gliomas and its correlation with grades. Microvasc Res. https://doi.org/10.1016/j.mvr.2014.03.002
Zaccagna F, Riemer F, Priest AN et al (2019) Non-invasive assessment of glioma microstructure using VERDICT MRI: correlation with histology. Eur Radiol. https://doi.org/10.1007/s00330-019-6011-8
Article PubMed PubMed Central Google Scholar
Raja R, Rosenberg GA, Caprihan A (2018) MRI measurements of blood-brain barrier function in dementia: a review of recent studies. Neuropharmacology. https://doi.org/10.1016/j.neuropharm.2017.10.034
Yan H, Parsons DW, Jin G et al (2009) IDH1 and IDH2 mutations in gliomas. N Engl J Med. https://doi.org/10.1056/NEJMoa0808710
Article PubMed PubMed Central Google Scholar
Furtado FS, Mercaldo ND, Vahle T et al (2023) Simultaneous multislice diffusion-weighted imaging versus standard diffusion-weighted imaging in whole-body PET/MRI. Eur Radiol. https://doi.org/10.1007/s00330-022-09275-4
Slator PJ, Palombo M, Miller KL et al (2021) Combined diffusion-relaxometry microstructure imaging: current status and future prospects. Magn Reson Med.
Comments (0)