Report for: Noninvasive Image Texture Analysis Differentiates K-ras Mutation from Pan-Wildtype NSCLC and Is Prognostic

Title	Noninvasive Image Texture Analysis Differentiates K-ras Mutation from Pan-Wildtype NSCLC and Is Prognostic
Published in	PLOS ONE, July 2014
DOI	10.1371/journal.pone.0100244
Pubmed ID	24987838
Authors	Glen J. Weiss, Balaji Ganeshan, Kenneth A. Miles, David H. Campbell, Philip Y. Cheung, Samuel Frank, Ronald L. Korn
Abstract	Non-invasive characterization of a tumor's molecular features could enhance treatment management. Quantitative computed tomography (CT) based texture analysis (QTA) has been used to derive tumor heterogeneity information, and the appearance of the tumors has been shown to relate to patient outcome in non-small cell lung cancer (NSCLC) and other cancers. In this study, we examined the potential of tumoral QTA to differentiate K-ras mutant from pan-wildtype tumors and its prognostic potential using baseline pre-treatment non-contrast CT imaging in NSCLC.

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United States	2	100%

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Members of the public	2	100%

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The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Readers by professional status	Count	As %
Student > Ph. D. Student	21	19%
Student > Master	17	15%
Researcher	13	12%
Other	11	10%
Student > Doctoral Student	10	9%
Other	18	16%
Unknown	20	18%

Readers by discipline	Count	As %
Medicine and Dentistry	52	47%
Computer Science	6	5%
Engineering	6	5%
Physics and Astronomy	4	4%
Agricultural and Biological Sciences	3	3%
Other	10	9%
Unknown	29	26%

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