Radiomics as a personalized medicine tool in lung cancer: Separating the hope from the hype
| Autor: | Corinne Faivre-Finn, James P B O'Connor, I. Fornacon-Wood, Gareth J Price |
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| Rok vydání: | 2020 |
| Předmět: |
Diagnostic Imaging
0301 basic medicine Pulmonary and Respiratory Medicine Cancer Research medicine.medical_specialty Lung Neoplasms Imaging biomarkers ROI region of interest RQS radiomics quality score CI concordance index Article TRIPOD Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis AUC area under the curve 03 medical and health sciences 0302 clinical medicine Radiomics Carcinoma Non-Small-Cell Lung Humans Medicine In patient Medical physics Precision Medicine Lung cancer business.industry food and beverages Reproducibility of Results medicine.disease HR hazard ratio Personalized medicine Clinical Practice 030104 developmental biology Workflow Oncology Computer-aided diagnosis 030220 oncology & carcinogenesis Non small cell business |
| Zdroj: | Lung Cancer (Amsterdam, Netherlands) |
| ISSN: | 0169-5002 |
| Popis: | Highlights • Radiomics studies in NSCLC suffer from a number of limitations. • No single radiomic signature has been translated into clinical use. • Identification of limitations can help future studies to expedite biomarker translation. Radiomics has become a popular image analysis method in the last few years. Its key hypothesis is that medical images harbor biological, prognostic and predictive information that is not revealed upon visual inspection. In contrast to previous work with a priori defined imaging biomarkers, radiomics instead calculates image features at scale and uses statistical methods to identify those most strongly associated to outcome. This builds on years of research into computer aided diagnosis and pattern recognition. While the potential of radiomics to aid personalized medicine is widely recognized, several technical limitations exist which hinder biomarker translation. Aspects of the radiomic workflow lack repeatability or reproducibility under particular circumstances, which is a key requirement for the translation of imaging biomarkers into clinical practice. One of the most commonly studied uses of radiomics is for personalized medicine applications in Non-Small Cell Lung Cancer (NSCLC). In this review, we summarize reported methodological limitations in CT based radiomic analyses together with suggested solutions. We then evaluate the current NSCLC radiomics literature to assess the risk associated with accepting the published conclusions with respect to these limitations. We review different complementary scoring systems and initiatives that can be used to critically appraise data from radiomics studies. Wider awareness should improve the quality of ongoing and future radiomics studies and advance their potential as clinically relevant biomarkers for personalized medicine in patients with NSCLC. |
| Databáze: | OpenAIRE |
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