Abstract

Abstract Textural and shape analysis is gaining considerable interest in medical imaging, particularly to identify parameters characterizing tumor heterogeneity and to feed radiomic models. Here, we present a free, multiplatform, and easy-to-use freeware called LIFEx, which enables the calculation of conventional, histogram-based, textural, and shape features from PET, SPECT, MR, CT, and US images, or from any combination of imaging modalities. The application does not require any programming skills and was developed for medical imaging professionals. The goal is that independent and multicenter evidence of the usefulness and limitations of radiomic features for characterization of tumor heterogeneity and subsequent patient management can be gathered. Many options are offered for interactive textural index calculation and for increasing the reproducibility among centers. The software already benefits from a large user community (more than 800 registered users), and interactions within that community are part of the development strategy. Significance: This study presents a user-friendly, multi-platform freeware to extract radiomic features from PET, SPECT, MR, CT, and US images, or any combination of imaging modalities. Cancer Res; 78(16); 4786–9. ©2018 AACR.

Keywords

Computer scienceModalitiesHistogramMultimodalityFeature (linguistics)Medical imagingSoftwareMedical physicsModality (human–computer interaction)Artificial intelligenceMedicineImage (mathematics)World Wide Web

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Publication Info

Year
2018
Type
article
Volume
78
Issue
16
Pages
4786-4789
Citations
1056
Access
Closed

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Cite This

Christophe Nioche, Fanny Orlhac, Sarah Boughdad et al. (2018). LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity. Cancer Research , 78 (16) , 4786-4789. https://doi.org/10.1158/0008-5472.can-18-0125

Identifiers

DOI
10.1158/0008-5472.can-18-0125