PET-CT Based Non-Invasive Radiomic Biomarkers as a Part of Precision Medicine Initiative to Predict Local Recurrences in Oral Cancers
Journal Title: Biomedical Journal of Scientific & Technical Research (BJSTR) - Year 2017, Vol 1, Issue 3
Abstract
75-80% of patients who are diagnosed with cancer in India have advanced disease(Stage III and Stage IV) that is not amenable to curative treatment, which means that they are likely to have pain and other symptoms and psychosocial concerns. These burdens vary with the economic and political situations and are affected by such factors as legal restrictions on access to drugs to relieve pain, and a medical culture in which quality-of-life considerations are undervalued in relation to imperatives to treat. These issues could be ameliorated by increased investment in cancer screening, removal of restrictions on prescription of opioids, and improvements in medical education to increase recognition of treatment futility.Oral cancer is the sixth most common cancer worldwide and continues to be most prevalent cancer related to the consumption of tobacco, alcohol and other carcinogenic products. Nevertheless, significant reduction in mortality has been achieved by advances in early diagnosis and implementation of multidisciplinary treatment programs leading to improvement of survivorship and better quality of life [1]. Even with recent advances in cancer diagnosis and therapy, treatment outcomes for many cancers remain dismal. Patients often show different response to the same therapy regimen, supporting the development of precision medicine. There has been increased use of positron emission tomography (PET) using [18F] Fluoro-2-deoxy-d-glucose (FDG),a glucose metabolism analog, for prediction of outcomes and guiding the precision medicine in tumor detection, staging, and treatment planning and surveillance post therapy in head and neck cancer sites [2]. Accumulating evidence of recent literature suggests that pre-treatment FDG uptake could be used as a prognostic factor for predicting treatment outcomes and is motivated by the fact that radiotracer uptake in the tumor is dependent on the characteristics of the microenvironment, quantitative analysis of FDG uptake is based on changes in the standardized uptake value (SUV) [3], However, sole SUV measurements are potentially impacted by the initial FDG uptake kinetics and radiotracer distribution and there is significant inter and intra observer variability in interpreting the results [4]. Recent development in Radiomics provides a promising objective way for tumor assessment, which uses computerized tools to extract a large number of image features that capture additional information not currently used in clinic that has prognostic value [5]. Radiomics is a process designed to extract a large number of quantitative features from digital images, place these data in shared databases, and subsequently mine the data for hypothesis generation, testing, or both. Radiomics is designed to develop decision support tools; therefore, it involves combining radiomic data with other patient characteristics, as available, to increase the power of the decision support models [6].
Authors and Affiliations
Lohith G, Suthirth Vaidya, Shivkumar Swamy, Vishal Rao, Sudhakar Sampangi,, Kallur KG, Basavalinga Ajai kumar
Keywords
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- EP ID EP570595
- DOI 10.26717/BJSTR.2017.01.000272
- Views 173
- Downloads 0
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