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Abstract Quantitative imaging is an emerging field that may allow prediction of oncological outcomes. We investigate whether radiomics and deep learning can predict outcomes in metastatic non-small cell lung cancer utilizing randomized trials of PD-1 inhibitors + /− stereotactic ablative body radiotherapy: PEMBRO-RT(NCT02492568), NIVORAD(ACTRN12616000352404) and MDACC(NCT02444741).
Nowadays, lung cancer is the leading cause of cancer death despite the notable changes in epidemiology and prevention occurred over the past decade [1]. Lung cancer can be divided into two main types: Non-Small Cell Lung Cancer (NSCLC) that affects 85% of the patients and Small-Cell Lung Cancer that affects the remaining 15% of the patients. NSCLC, in turn, is divided into three main types: adenocarcinoma, squamous cell carcinoma and large cell carcinoma [2].
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