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BACKGROUND Recent evidence has identified pre-existing type 2 diabetes mellitus (T2DM) as a risk factor for the development of PAC, but relatively little is known about its effects on survival. Our aim was to determine the effect of varying durations of pre-existing T2DM on survival in patients with PAC. METHODS We conducted a retrospective cohort study(More)
BACKGROUND AND PURPOSE Radiomics can quantify tumor phenotype characteristics non-invasively by applying advanced imaging feature algorithms. In this study we assessed if pre-treatment radiomics data are able to predict pathological response after neoadjuvant chemoradiation in patients with locally advanced non-small cell lung cancer (NSCLC). MATERIALS(More)
PURPOSE In advanced non-small cell lung cancer (NSCLC) patient, metastasis can spread from the primary tumor to the lymph nodes and hence could have a distinct phenotype compared to unaffected nodes. In this study we investigated the complementary information of radiomics extracted from lymph nodes and the primary tumor in order to predict pathological(More)
PURPOSE Stereotactic body radiation therapy (SBRT) is the standard of care for medically inoperable non-small cell lung cancer (NSCLC) patients and has demonstrated excellent local control and survival. However, some patients still develop distant metastases and local recurrence, and therefore, there is a clinical need to identify patients at high-risk of(More)
BACKGROUND Radiomics uses a large number of quantitative imaging features that describe the tumor phenotype to develop imaging biomarkers for clinical outcomes. Radiomic analysis of pre-treatment computed-tomography (CT) scans was investigated to identify imaging predictors of clinical outcomes in early stage non-small cell lung cancer (NSCLC) patients(More)
INTRODUCTION Noninvasive biomarkers that capture the total tumor burden could provide important complementary information for precision medicine to aid clinical decision making. We investigated the value of radiomic data extracted from pretreatment computed tomography images of the primary tumor and lymph nodes in predicting pathological response after(More)
PURPOSE To compare the complementary value of quantitative radiomic features to that of radiologist-annotated semantic features in predicting EGFR mutations in lung adenocarcinomas. METHODS Pre-operative CT images of 258 lung adenocarcinoma patients were available. Tumors were segmented using the sing-click ensemble segmentation algorithm. A set of(More)
PURPOSE To develop radiomic biomarkers for non-invasive response assessment of Bevacizumab (Avastin; Genentech) treatment in recurrent glioblastoma multiforme (GBM). METHODS We analyzed prospectively acquired data from the BRAIN trial. For 167 patients, we extracted 71 radiomic features each from normalized post-contrast T1-weighted and fluid attenuation(More)
PURPOSE There is a clinical need to identify patients who are at highest risk of recurrence after being treated with stereotactic body radiation therapy (SBRT). Radiomics offers a non-invasive approach by extracting quantitative features from medical images based on tumor phenotype that is predictive of an outcome. Lung cancer patients treated with SBRT(More)