18 April 2018 Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography
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Abstract
Differentiation between benign and malignant nodules is a problem encountered by radiologists when visualizing computed tomography (CT) scans. Adenocarcinomas and granulomas have a characteristic spiculated appearance and may be fluorodeoxyglucose avid, making them difficult to distinguish for human readers. In this retrospective study, we aimed to evaluate whether a combination of radiomic texture and shape features from noncontrast CT scans can enable discrimination between granulomas and adenocarcinomas. Our study is composed of CT scans of 195 patients from two institutions, one cohort for training (N  =  139) and the other (N  =  56) for independent validation. A set of 645 three-dimensional texture and 24 shape features were extracted from CT scans in the training cohort. Feature selection was employed to identify the most informative features using this set. The top ranked features were also assessed in terms of their stability and reproducibility across the training and testing cohorts and between scans of different slice thickness. Three different classifiers were constructed using the top ranked features identified from the training set. These classifiers were then validated on the test set and the best classifier (support vector machine) yielded an area under the receiver operating characteristic curve of 77.8%.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Mahdi Orooji, Mahdi Orooji, Mehdi Alilou, Mehdi Alilou, Sagar Rakshit, Sagar Rakshit, Niha G. Beig, Niha G. Beig, Mohammadhadi Khorrami, Mohammadhadi Khorrami, Prabhakar Rajiah, Prabhakar Rajiah, Rajat Thawani, Rajat Thawani, Jennifer Ginsberg, Jennifer Ginsberg, Christopher Donatelli, Christopher Donatelli, Michael Yang, Michael Yang, Frank Jacono, Frank Jacono, Robert C. Gilkeson, Robert C. Gilkeson, Vamsidhar Velcheti, Vamsidhar Velcheti, Philip Linden, Philip Linden, Anant Madabhushi, Anant Madabhushi, } "Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography," Journal of Medical Imaging 5(2), 024501 (18 April 2018). https://doi.org/10.1117/1.JMI.5.2.024501 . Submission: Received: 25 August 2017; Accepted: 1 March 2018
Received: 25 August 2017; Accepted: 1 March 2018; Published: 18 April 2018
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