Evaluation of the Use of Radiomics in Predicting Treatment Response in Oncology: (Review Artical) | ||||
| The Medical Journal of Cairo University | ||||
| Volume 87, December, December 2019, Page 5333-5338 PDF (353.64 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjcu.2019.355448 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| FAHAD MADALLAH ALNUWMASIU and SHAYEM HAMDAN ALHARBI NASSER SIHLI ALSHAMMARY, MOHAMMED NUHAYR ALWAHDANI, FARES MOTALQ ALONAZI, | ||||
| KSA, National Guard Health Affairs | ||||
| Abstract | ||||
| Abstract Background: Radiomics involves the retrieval of numerical information from medical imaging, with the ability to describe the characteristics of a tumor. The radiomics technique has the ability to create prognostic models for therapy response, which is crucial for the advancement of personalized medicine. Aim of Study: This literature review provides a concise overview and assesses the scientific rigor and reporting stand-ards of radiomics research in predicting treatment response in non-small-cell lung cancer (NSCLC). Methods: An extensive literature search was performed us-ing the PubMed database. The radiomics quality score (RQS), a measure specifically designed for radiomics, was used to evalu-ate the scientific and reporting quality, following the parameters set by TRIPOD. Results: The studies included in the analysis revealed sev-eral predictive markers, including first-, second-, and high-or-der features. These characteristics included kurtosis, grey-level uniformity, and wavelet HLL mean, as well as PET-based met-abolic indicators. The studies exhibited significant variability as a result of variations in patient demographics, cancer stage, treatment methods, duration of follow-up, and radiomics pro- cessing protocols. Conclusion: The use of radiomics research in clinical prac- tice has not yet been implemented. To develop radiomic pre-dictors of response that can be reproduced, it is necessary to make efforts toward standardization and cooperation. In order for radiomic models to be used as a clinical decision-making tool for personalized treatment of patients with NSCLC, it is necessary to verify them externally and assess their effect with-in the therapeutic pathway. | ||||
| Keywords | ||||
| Radiomics; Review; Non-Small-Cell Lung Cancer (NSCLC); Radiomics Quality Score; Treatment | ||||
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