Utility of a Rule-Based Algorithm in the Assessment of Standardized Reporting in PI-RADS

Adoption of the Prostate Imaging Reporting & Data System (PI-RADS) has been shown to increase detection of clinically significant prostate cancer on prostate mpMRI. We propose that a rule-based algorithm based on Regular Expression (RegEx) matching can be used to automatically categorize prostat...

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Bibliographic Details
Published in:Academic radiology Vol. 30; no. 6; p. 1141
Main Authors: Zhang, Dylan, Neely, Ben, Lo, Joseph Y, Patel, Bhavik N, Hyslop, Terry, Gupta, Rajan T
Format: Journal Article
Language:English
Published: United States 01.06.2023
Subjects:
Algorithms
Humans
Image-Guided Biopsy - methods
Magnetic Resonance Imaging - methods
Male
Multiparametric Magnetic Resonance Imaging
Prostate - pathology
Prostatic Neoplasms - diagnostic imaging
Prostatic Neoplasms - pathology
Retrospective Studies
prostate cancer
standardized reporting
MRI
quality improvement
imaging informatics
ISSN:1878-4046, 1878-4046
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Summary:Adoption of the Prostate Imaging Reporting & Data System (PI-RADS) has been shown to increase detection of clinically significant prostate cancer on prostate mpMRI. We propose that a rule-based algorithm based on Regular Expression (RegEx) matching can be used to automatically categorize prostate mpMRI reports into categories as a means by which to assess for opportunities for quality improvement. All prostate mpMRIs performed in the Duke University Health System from January 2, 2015, to January 29, 2021, were analyzed. Exclusion criteria were applied, for a total of 5343 male patients and 6264 prostate mpMRI reports. These reports were then analyzed by our RegEx algorithm to be categorized as PI-RADS 1 through PI-RADS 5, Recurrent Disease, or "No Information Available." A stratified, random sample of 502 mpMRI reports was reviewed by a blinded clinical team to assess performance of the RegEx algorithm. Compared to manual review, the RegEx algorithm achieved overall accuracy of 92.6%, average precision of 88.8%, average recall of 85.6%, and F1 score of 0.871. The clinical team also reviewed 344 cases that were classified as "No Information Available," and found that in 150 instances, no numerical PI-RADS score for any lesion was included in the impression section of the mpMRI report. Rule-based processing is an accurate method for the large-scale, automated extraction of PI-RADS scores from the text of radiology reports. These natural language processing approaches can be used for future initiatives in quality improvement in prostate mpMRI reporting with PI-RADS.
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ISSN:1878-4046
1878-4046
DOI:10.1016/j.acra.2022.06.024