Yongqiang Tan

TL;DR: Assessment of the reproducibility of a comprehensive, commonly-used set of radiomic features using a unique, same-day repeat computed tomography data set from lung cancer patients suggests that radiomic Features are reproducible over a wide range of imaging settings.

TL;DR: This pilot study shows that radiomic data before treatment is able to predict mutation status and associated gefitinib response non-invasively, demonstrating the potential of radiomics-based phenotyping to improve the stratification and response assessment between tyrosine kinase inhibitors (TKIs) sensitive and resistant patient populations.

TL;DR: GGO volume percentage in tumors with exon 21 missense mutation was significantly higher than that in tumor status with other EGFR mutation status, and can be related to the fact that exon21 missense mutations was significantly more frequent in lepidic predominant adenocarcinomas, according to IASLE/ATS/ERS classification.

TL;DR: The performance of this new segmentation algorithm in delineating tumor contour and measuring tumor size illustrates its potential clinical value for assisting in noninvasive diagnosis of pulmonary nodules, therapy response assessment, and radiation treatment planning.

TL;DR: In this paper, the effects of computed tomography (CT) slice thickness and reconstruction algorithm on quantification of image features to characterize tumors using a chest phantom were explored, and the results showed that thinner (1.25 mm) and thicker (5 mm) slice images should not be used interchangeably.