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Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma

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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (BrainLes 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10670))

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Abstract

Quantitative research, especially in the field of radio(geno)mics, has helped us understand fundamental mechanisms of neurologic diseases. Such research is integrally based on advanced algorithms to derive extensive radiomic features and integrate them into diagnostic and predictive models. To exploit the benefit of such complex algorithms, their swift translation into clinical practice is required, currently hindered by their complicated nature. brain-CaPTk is a modular platform, with components spanning across image processing, segmentation, feature extraction, and machine learning, that facilitates such translation, enabling quantitative analyses without requiring substantial computational background. Thus, brain-CaPTk can be seamlessly integrated into the typical quantification, analysis and reporting workflow of a radiologist, underscoring its clinical potential. This paper describes currently available components of brain-CaPTk and example results from their application in glioblastoma.

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Acknowledgments

This work was supported by the NIH grants R01-NS042645 and U24-CA189523.

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Authors and Affiliations

  1. Department of Radiology, Perelman School of Medicine, Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA

    Saima Rathore, Spyridon Bakas, Sarthak Pati, Hamed Akbari, Ratheesh Kalarot, Patmaa Sridharan, Martin Rozycki, Mark Bergman, Birkan Tunc, Ragini Verma, Michel Bilello & Christos Davatzikos

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  1. Saima Rathore
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  2. Spyridon Bakas
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  3. Sarthak Pati
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  4. Hamed Akbari
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  5. Ratheesh Kalarot
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  7. Martin Rozycki
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  10. Ragini Verma
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  11. Michel Bilello
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  12. Christos Davatzikos
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Correspondence to Saima Rathore .

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Editors and Affiliations

  1. African Institute of Mathematical Sciences, Cape Town, Ghana

    Alessandro Crimi

  2. University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Spyridon Bakas

  3. University Medical Center Utrecht, Utrecht, The Netherlands

    Hugo Kuijf

  4. Technical University Munich, Munich, Germany

    Bjoern Menze

  5. Universität Bern, Bern, Switzerland

    Mauricio Reyes

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Rathore, S. et al. (2018). Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma. In: Crimi, A., Bakas, S., Kuijf, H., Menze, B., Reyes, M. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Lecture Notes in Computer Science(), vol 10670. Springer, Cham. https://doi.org/10.1007/978-3-319-75238-9_12

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