Schaff LR, Mellinghoff IK. Glioblastoma and Other Primary Brain Malignancies in Adults: A Review. JAMA. 2023;329:574–87.
Mohammed S, Dinesan M, Ajayakumar T. Survival and quality of life analysis in glioblastoma multiforme with adjuvant chemoradiotherapy: a retrospective study. Reports of Practical Oncology and Radiotherapy. 2022;27:1026.
Article PubMed PubMed Central Google Scholar
Gatto L, Franceschi E, Tosoni A, Di Nunno V, Tonon C, Lodi R, et al. Beyond Imaging and Genetic Signature in Glioblastoma: Radiogenomic Holistic Approach in Neuro-Oncology. Biomedicines. 2022;10:3205.
Article CAS PubMed PubMed Central Google Scholar
Shergalis A, Bankhead A, Luesakul U, Muangsin N, Neamati N. Current challenges and opportunities in treating glioblastomas. Pharmacol Rev. 2018;70:412–45.
Article CAS PubMed PubMed Central Google Scholar
Hanif F, Muzaffar K, Perveen K, Malhi SM, Simjee SU. Glioblastoma Multiforme: A Review of its Epidemiology and Pathogenesis through Clinical Presentation and Treatment. Asian Pac J Cancer Prev. 2017;18:3.
PubMed PubMed Central Google Scholar
Fink JR, Carr RB, Matsusue E, Iyer RS, Rockhill JK, Haynor DR, et al. Comparison of 3 Tesla proton MR spectroscopy, MR perfusion and MR diffusion for distinguishing glioma recurrence from posttreatment effects. J Magn Reson Imaging. 2012;35:56–63.
Kumar M, Nanga RPR, Chawla S. Editorial: Structural, Metabolic, and Physiologic MR Imaging to Study Glioblastomas. Front Neurol. 2022;13:887027.
Article PubMed PubMed Central Google Scholar
Chawla S, Bukhari S, Afridi OM, Wang S, Yadav SK, Akbari H, et al. Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma. NMR Biomed. 2022;35:e4719.
Article PubMed PubMed Central Google Scholar
Gonçalves FG, Chawla S, Mohan S. Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma. J Magn Reson Imaging. 2020;52:978.
Article PubMed PubMed Central Google Scholar
Aabedi AA, Young JS, Chang EF, Berger MS, Hervey-Jumper SL. Involvement of White Matter Language Tracts in Glioma: Clinical Implications, Operative Management, and Functional Recovery After Injury. Front Neurosci. 2022;16:932478.
Article PubMed PubMed Central Google Scholar
Bonm AV, Ritterbusch R, Throckmorton P, Graber JJ. Clinical Imaging for Diagnostic Challenges in the Management of Gliomas: A Review. J Neuroimaging. 2020;30:139–45.
Article PubMed PubMed Central Google Scholar
Prager AJ, Martinez N, Beal K, Omuro A, Zhang Z, Young RJ. Diffusion and Perfusion MRI to Differentiate Treatment-Related Changes Including Pseudoprogression from Recurrent Tumors in High-Grade Gliomas with Histopathologic Evidence. AJNR Am J Neuroradiol. 2015;36:877.
Article CAS PubMed PubMed Central Google Scholar
Deo RC. Machine Learning in Medicine. Circulation. 2015;132:1920.
Article PubMed PubMed Central Google Scholar
Beig N, Bera K, Tiwari P. Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges. Neurooncol Adv. 2020;2:iv3.
Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJWL. Artificial intelligence in radiology. Nat Rev Cancer. 2018;18:500.
Article CAS PubMed PubMed Central Google Scholar
Alzubaidi L, Zhang J, Humaidi AJ, Al-Dujaili A, Duan Y, Al-Shamma O, et al. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J Big Data. 2021;8:1–74.
Jiang Y, Yang M, Wang S, Li X, Sun Y. Emerging role of deep learning-based artificial intelligence in tumor pathology. Cancer Commun. 2020;40:154.
Martin P, Holloway L, Metcalfe P, Koh ES, Brighi C. Challenges in Glioblastoma Radiomics and the Path to Clinical Implementation. Cancers (Basel). 2022;14:3897.
Article PubMed PubMed Central Google Scholar
Chaddad A, Kucharczyk MJ, Daniel P, Sabri S, Jean-Claude BJ, Niazi T, et al. Radiomics in Glioblastoma: Current Status and Challenges Facing Clinical Implementation. Front Oncol. 2019;9:374.
Article PubMed PubMed Central Google Scholar
Lohmann P, Galldiks N, Kocher M, Heinzel A, Filss CP, Stegmayr C, et al. Radiomics in neuro-oncology: Basics, workflow, and applications. Methods. 2021;188:112–21.
Article CAS PubMed Google Scholar
Gevaert O, Mitchell LA, Achrol AS, Xu J, Echegaray S, Steinberg GK, et al. Glioblastoma multiforme: Exploratory radiogenomic analysis by using quantitative image features. Radiology. 2014;273:168–74.
Aftab K, Aamir FB, Mallick S, Mubarak F, Pope WB, Mikkelsen T, et al. Radiomics for precision medicine in glioblastoma. J Neurooncol. 2022;156:217–31.
Fathi Kazerooni A, Bakas S, Saligheh Rad H, Davatzikos C. Imaging signatures of glioblastoma molecular characteristics: A radiogenomics review. J Magn Reson Imaging. 2020;52:54–69.
Jansen RW, van Amstel P, Martens RM, Kooi IE, Wesseling P, de Langen AJ, et al. Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis. Oncotarget. 2018;9:20134–55.
Article PubMed PubMed Central Google Scholar
Altieri R, Zenga F, Ducati A, Melcarne A, Cofano F, Mammi M, et al. Tumor location and patient age predict biological signatures of high-grade gliomas. Neurosurg Rev. 2018;41:599–604.
Choi YS, Bae S, Chang JH, Kang SG, Kim SH, Kim J, et al. Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics. Neuro Oncol. 2021;23:304.
Article CAS PubMed Google Scholar
Liu D, Chen J, Hu X, Yang K, Liu Y, Hu G, et al. Imaging-Genomics in Glioblastoma: Combining Molecular and Imaging Signatures. Front Oncol. 2021;11:1.
Wei J, Yang G, Hao X, Gu D, Tan Y, Wang X, et al. A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication. Eur Radiol. 2019;29:877.
Korfiatis P, Kline TL, Lachance DH, Parney IF, Buckner JC, Erickson BJ. Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. J Digit Imaging. 2017;30:622.
Article PubMed PubMed Central Google Scholar
Chen X, Zeng M, Tong Y, Zhang T, Fu Y, Li H, et al. Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis. Biomed Res Int. 2020;2020:9258649.
PubMed PubMed Central Google Scholar
Liu TT, Achrol AS, Mitchell LA, Rodriguez SA, Feroze A, Iv M, et al. Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment. Neuro Oncol. 2017;19:997.
Park JE, Kim HS, Park SY, Nam SJ, Chun SM, Jo Y, et al. Prediction of Core Signaling Pathway by Using Diffusion- and Perfusion-based MRI Radiomics and Next-generation Sequencing in Isocitrate Dehydrogenase Wild-type Glioblastoma. Radiology. 2020;294:388–97.
Heimberger AB, Hlatky R, Suki D, Yang D, Weinberg J, Gilbert M, et al. Prognostic effect of epidermal growth factor receptor and EGFRvIII in glioblastoma multiforme patients. Clin Cancer Res. 2005;11:1462–6.
留言 (0)