NDLI: CADOnc ⓒ: An integrated toolkit for evaluating radiation therapy related changes in the prostate using multiparametric MRI

Content Provider	IEEE Xplore Digital Library
Author	Viswanath, S. Tiwari, P. Chappelow, J. Toth, R. Kurhanewicz, J. Madabhushi, A.
Copyright Year	2011
Description	Author affiliation: Rutgers, the State University of New Jersey, Dept. of Biomedical Engineering, Piscataway, USA (Viswanath, S.; Tiwari, P.; Chappelow, J.; Toth, R.; Madabhushi, A.) \|\| Department of Radiology, University of California, San Francisco, USA (Kurhanewicz, J.)
Abstract	The use of multi-parametric Magnetic Resonance Imaging (T2-weighted, MR Spectroscopy (MRS), Diffusion-weighted (DWI)) has recently shown great promise for diagnosing and staging prostate cancer (CaP) in vivo. Such imaging has also been utilized for evaluating the early effects of radiotherapy (RT) (e.g. intensity-modulated radiation therapy (IMRT), proton beam therapy, brachytherapy) in the prostate with the overarching goal being to successfully predict short- and long-term patient outcome. Qualitative examination of post-RT changes in the prostate using MRI is subject to high inter- and intra-observer variability. Consequently, there is a clear need for quantitative image segmentation, registration, and classification tools for assessing RT changes via multi-parametric MRI to identify (a) residual disease, and (b) new foci of cancer (local recurrence) within the prostate. In this paper, we present a computerized image segmentation, registration, and classification toolkit called CADOnc ⓒ, and leverage it for evaluating (a) spatial extent of disease pre-RT, and (b) post-RT related changes within the prostate. We demonstrate the applicability of CADOnc ⓒ in studying IMRT-related changes using a cohort of 7 multi-parametric (T2w, MRS, DWI) prostate MRI patient datasets. First, the different MRI protocols from pre- and post-IMRT MRI scans are affinely registered (accounting for gland shrinkage), followed by automated segmentation of the prostate capsule using an active shape model. A number of feature extraction schemes are then applied to extract multiple textural, metabolic, and functional MRI attributes on a per-voxel basis. An AUC of 0.7132 was achieved for automated detection of CaP on pre-IMRT MRI (via integration of T2w, DWI, MRS features); evaluated on a per-voxel basis against radiologist-derived annotations. CADOnc ⓒ also successfully identified a total of 40 out of 46 areas where disease-related changes (both absence and recurrence) occurred post-IMRT, based on changes in the expression of quantitative MR imaging biomarkers. CADOnc ⓒ thus provides an integrated platform of quantitative analysis tools to evaluate treatment response in vivo, based on multi-parametric MRI data.
Starting Page	2095
Ending Page	2098
File Size	233142
Page Count	4
File Format	PDF
ISBN	9781424441273
ISSN	19457928
DOI	10.1109/ISBI.2011.5872825
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Prostate cancer Medical treatment Feature extraction Biomedical applications of radiation Image segmentation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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