Development and evaluation of an open-source software package "cGITA" for quantifying tumor heterogeneity with molecular images

Yu Hua Dean Fang, Chien Yu Lin, Meng Jung Shih, Hung Ming Wang, Tsung Ying Ho, Chun Ta Liao, Tzu Chen Yen

Research output: Contribution to journalArticlepeer-review

81 Citations (Scopus)

Abstract

Background. The quantification of tumor heterogeneity with molecular images, by analyzing the local or global variation in the spatial arrangements of pixel intensity with texture analysis, possesses a great clinical potential for treatment planning and prognosis. To address the lack of available software for computing the tumor heterogeneity on the public domain, we develop a software package, namely, Chang-Gung Image Texture Analysis (CGITA) toolbox, and provide it to the research community as a free, open-source project. Methods. With a user-friendly graphical interface, CGITA provides users with an easy way to compute more than seventy heterogeneity indices. To test and demonstrate the usefulness of CGITA, we used a small cohort of eighteen locally advanced oral cavity (ORC) cancer patients treated with definitive radiotherapies. Results. In our case study of ORC data, we found that more than ten of the current implemented heterogeneity indices outperformed SUVmean for outcome prediction in the ROC analysis with a higher area under curve (AUC). Heterogeneity indices provide a better area under the curve up to 0.9 than the SUVmean and TLG (0.6 and 0.52, resp.). Conclusions. CGITA is a free and open-source software package to quantify tumor heterogeneity from molecular images. CGITA is available for free for academic use at http://code.google.com/ p/cgita.

Original languageEnglish
Article number248505
JournalBioMed research international
Volume2014
DOIs
Publication statusPublished - 2014

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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