Image Analysis Tools for mpMRI Prostate Cancer Diagnosis Using PI-RADS

ABSTRACTProstate cancerPCais one of the most commonly occurring forms of canceraccounting forof all
cancer in menMulti parametric magnetic resonance imagingmpMRIhas led to improved capabilities for
detectinglocalizingand staging PCaCombined with image guided prostate biopsympMRI has helped to
improve diagnosis of clinically significant PCawhich helps to reduce mortality as well as unnecessary biopsies
or treatmentsUntil recentlythe diagnostic capabilities of mpMRI were limited by lack of standardization in
imaginginterpretationand reporting methodswhich are all subject to high interand intra observer variabilityTo address these problemsthe Prostate Imaging Reporting and Data SystemPI RADSwas designed
to standardize the reporting of PCaPI RADS aims to standardize imaging acquisition parameters for mpMRIsimplify radiological reportingand develop assessment categories to stratify levels of PCaA recent metaanalysis reported the diagnostic performance of PI RADS to have a high pooled sensitivity ofand specificity
ofunfortunatelythere is still high variability in these resultsThe current clinical practice for interpreting mpMRI has limitations that may contribute to this variationCurrentlyno image registration exists between the imagesand radiologists rely on mental alignment of the
images while reading a set of mpMR imageswhich introduces a potential source of variability into PCa
diagnosisLocalization and reporting of PCa is specified with respect to the PI RADS sector atlasand this is
another source of operator variationAn explicit manual delineation of the prostate into its constituent PI RADS
sectors would reduce variationbut this is time consuming and infeasible in the clinical settingThe overarching goal of this proposal is to reduce the interand intra observer variability while interpreting
mpMRI images using the PI RADS protocol to improve consistency and accuracy of PCa diagnosisThe primary
innovation is creation of a population of PI RADS sector atlases and their application to automatically segment
anatomical prostate images with respect to this atlas label protocolThis project is significant in that it has the
potential to reduce the variability in PCa interpretation and reporting by providing automated image analysis
toolsWhile radiological results are currently communicated in a non standardized formatthe proposed work
will facilitate development of automated electronic report generation capabilities to foster data sharing and
collaborationsUltimatelyenhancements from this project will create a novel feature for Eigen sthe applicant
company sFDAkcleared imaging productProFusethat should improve the diagnosis of PCaIn Aimof this projecta tool to co register and visualize multi parametric prostate MR imaging will be
developedIn Aiman image segmentation method to automatically localize the anatomical PI RADS sector
map standard within the prostate will be developedBoth aims will utilize a database of existing mpMRI images
to develop and validate the algorithms and validate their accuracy PROJECT NARRATIVE
Prostate cancer accounts forof all cancer in menThe Prostate Imaging Reporting and Data SystemPIRADSwas designed to standardize the reporting of prostate cancer based on medical imagingbut there is still
high variability involved due to interand intra observer variabilityThis project proposes to develop image
analysis tools to automate and standardize the interpretation and reporting of radiological prostate cancer
diagnosisThis system will be developed by automating components of the PI RADS protocol and integrating
these features into an already effective prostate cancer software system that is used for fusion guided biopsies