The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas
Open accessAbstract
Background.: High-grade gliomas with mutations in the isocitrate dehydrogenase (IDH) gene family confer longer overall survival relative to their IDH-wild-type counterparts. Accurate determination of the IDH genotype preoperatively may have both prognostic and diagnostic value. The current study used a machine-learning algorithm to generate a model predictive of IDH genotype in high-grade gliomas based on clinical variables and multimodal features extracted from conventional MRI. Methods.: Preoperative MRIs were obtained for 120 patients with primary grades III (n = 35) and IV (n = 85) glioma in this retrospective study. IDH genotype was confirmed for grade III (32/35, 91%) and IV (22/85, 26%) tumors by immunohistochemistry, spectrometry-based mutation genotyping (OncoMap), or multiplex exome sequencing (OncoPanel). IDH1 and IDH2 mutations were mutually exclusive, and all mutated tumors were collapsed into one IDH-mutated cohort. Cases were randomly assigned to either the training (n = 90) or validation cohort (n = 30). A total of 2970 imaging features were extracted from pre- and postcontrast T1-weighted, T2-weighted, and apparent diffusion coefficient map. Using a random forest algorithm, nonredundant features were integrated with clinical data to generate a model predictive of IDH genotype. Results.: Our model achieved accuracies of 86% (area under the curve [AUC] = 0.8830) in the training cohort and 89% (AUC = 0.9231) in the validation cohort. Features with the highest predictive value included patient age as well as parametric intensity, texture, and shape features. Conclusion.: Using a machine-learning algorithm, we achieved accurate prediction of IDH genotype in high-grade gliomas with preoperative clinical and MRI features.
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Amin, J., Sharif, M., Haldorai, A., Yasmin, M., & Nayak, R. S. (2022) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00563-y · Cited by 503
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Senders, J. T., Arnaout, O., Karhade, A. V., Dasenbrock, H. H., Gormley, W. B., Broekman, M. L., & Smith, T. R. (2018) · Neurosurgery · doi:10.1093/neuros/nyx384 · Cited by 264
Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma
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Metadata
- Authors
- Zhang, B., Chang, K., Ramkissoon, S., Tanguturi, S., Bi, W. L., Reardon, D. A., Ligon, K. L., Alexander, B. M., Wen, P. Y., & Huang, R. Y.
- Venue
- Neuro-Oncology
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-06-26
- Volume
- 19
- Issue
- 1
- Pages
- 109-117
- ISSN
- 1522-8517 (ISSN-L)
- 1523-5866
- OpenAlex
- W2460918282
- Cited by
- 263
- References
- 50
- FWCI
- 23.13
- Type
- journal article
- Language
- en
- Open access
- green
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- Zhang, B., Chang, K., Ramkissoon, S., Tanguturi, S., Bi, W. L., Reardon, D. A., Ligon, K. L., Alexander, B. M., Wen, P. Y., & Huang, R. Y. (2017). Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas. Neuro-Oncology. https://doi.org/10.1093/neuonc/now121
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