Easy-to-use machine learning system for the prediction of IDH mutation and 1p/19q codeletion using MRI images of adult-type diffuse gliomas

Suzuki H, Aoki K, Chiba K et al (2015) Mutational landscape and clonal architecture in grade II and III gliomas. Nat Genet 47:458–468

Article  CAS  PubMed  Google Scholar 

Aoki K, Nakamura H, Suzuki H et al (2018) Prognostic relevance of genetic alterations in diffuse lower-grade gliomas. Neuro Oncol 20:66–77

Article  CAS  PubMed  Google Scholar 

Brat DJ, Verhaak RG, Aldape KD et al (2015) Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med 372:2481–2498

Article  CAS  PubMed  Google Scholar 

Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol 23:1231–1251

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wijnenga MMJ, French PJ, Dubbink HJ et al (2018) The impact of surgery in molecularly defined low-grade glioma: an integrated clinical, radiological, and molecular analysis. Neuro Oncol 20:103–112

Article  CAS  PubMed  Google Scholar 

Ding X, Wang Z, Chen D et al (2018) The prognostic value of maximal surgical resection is attenuated in oligodendroglioma subgroups of adult diffuse glioma: a multicenter retrospective study. J Neurooncol 140:591–603

Article  PubMed  Google Scholar 

Fukuma R, Yanagisawa T, Kinoshita M et al (2019) Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network. Sci Rep 9:20311

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chang K, Bai HX, Zhou H et al (2018) Residual convolutional neural network for the determination of IDH status in low- and high-grade gliomas from MR imaging. Clin Cancer Res 24:1073–1081

Article  CAS  PubMed  Google Scholar 

Chang P, Grinband J, Weinberg BD et al (2018) Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas. AJNR Am J Neuroradiol 39:1201–1207

Article  CAS  PubMed  PubMed Central  Google Scholar 

Matsui Y, Maruyama T, Nitta M et al (2020) Prediction of lower-grade glioma molecular subtypes using deep learning. J Neurooncol 146:321–327

Article  PubMed  Google Scholar 

Nalawade S, Murugesan GK, Vejdani-Jahromi M et al (2019) Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning. J Med Imaging (Bellingham) 6:046003

PubMed  Google Scholar 

Choi YS, Bae S, Chang JH et al (2021) Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics. Neuro Oncol 23:304–313

Article  CAS  PubMed  Google Scholar 

van der Voort SR, Incekara F, Wijnenga MMJ et al (2022) Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning. Neuro Oncol. https://doi.org/10.1093/neuonc/noac166

Article  PubMed Central  Google Scholar 

Kim I, Choi HJ, Ryu JM et al (2019) A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning. Eur J Surg Oncol 45:134–140

Article  PubMed  Google Scholar 

Twarish Alhamazani K, Alshudukhi J, Aljaloud S et al (2021) Implementation of machine learning models for the prevention of kidney diseases (CKD) or their derivatives. Comput Intell Neurosci 2021:3941978

Article  PubMed  PubMed Central  Google Scholar 

Choi S, Park J, Park S et al (2021) Establishment of a prediction tool for ocular trauma patients with machine learning algorithm. Int J Ophthalmol 14:1941–1949

Article  PubMed  PubMed Central  Google Scholar 

Lorenzo AJ, Rickard M, Braga LH et al (2019) Predictive analytics and modeling employing machine learning technology: the next step in data sharing, analysis, and individualized counseling explored with a large, prospective prenatal hydronephrosis database. Urology 123:204–209

Article  PubMed  Google Scholar 

Pawelka D, Laczmanska I, Karpinski P et al (2022) Machine-learning-based Analysis Identifies miRNA expression profile for diagnosis and prediction of colorectal cancer: a preliminary study. Cancer Genomics Proteomics 19:503–511

Article  CAS  PubMed  PubMed Central  Google Scholar 

Park YJ, Bae JH, Shin MH et al (2019) Development of predictive models in patients with epiphora using lacrimal scintigraphy and machine learning. Nucl Med Mol Imaging 53:125–135

Article  PubMed  PubMed Central  Google Scholar 

Makino Y, Arakawa Y, Yoshioka E et al (2021) Prognostic stratification for IDH-wild-type lower-grade astrocytoma by Sanger sequencing and copy-number alteration analysis with MLPA. Sci Rep 11:14408

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jeuken J, Cornelissen S, Boots-Sprenger S et al (2006) Multiplex ligation-dependent probe amplification: a diagnostic tool for simultaneous identification of different genetic markers in glial tumors. J Mol Diagn 8:433–443

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kanda Y (2013) Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant 48:452–458

Article  CAS  PubMed  Google Scholar 

Hrapsa I, Florian IA, Susman S et al (2022) External validation of a convolutional neural network for IDH mutation prediction. Medicina (Kaunas) 58:526

Article  PubMed  Google Scholar 

Xie Y, Zaccagna F, Rundo L et al (2022) Convolutional neural network techniques for brain tumor classification (from 2015 to 2022): review, challenges, and future perspectives. Diagnostics (Basel) 12:1850

Article  PubMed  Google Scholar 

留言 (0)

沒有登入
gif