Share Email Print
cover

Proceedings Paper

Prostate Imaging Self-assessment and Mentoring (PRISM): a prototype self-assessment scheme
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Prostate cancer is the most common cancer in men and a leading cause of morbidity and mortality globally. To ensure that men receive an accurate prostate cancer diagnosis, we developed the PRISM App, a web-based self-assessment platform designed for clinicians to increase their confidence in the use of mpMRI before biopsy. The App, which provided participants with a prostate sector map, anonymous patient’s clinical history and mpMRI technical information, was tested by three radiologists of different mpMRI experience. Participants determined the number of lesions that were present in a set of twenty prostate mpMRI images, by marking and describing their location on the map. They were also asked to decide on the radiological classification, using a five-point Likert scale, and record the T-stage. Participants' screening performance was calculated by two sets of measures based on a) expert’s opinion regarding whether a case should be recalled for further investigation or not and b) the known case pathology regarding whether malignancy was present or not. The results showed that two of the participants had specificity scores at ceiling (100%) whereas the third had a specificity score at the level of change (50%), reflecting the small number of benign cases in the case set (n=6). Participants' comments regarding their experience using the App was positive, indicating that the PRISM scheme could be helpful in building confidence in reading mpMRI cases. Further testing with an appropriate number and variety of cases would be a key element in the success of the PRISM App.

Paper Details

Date Published: 4 March 2019
PDF: 8 pages
Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 1095212 (4 March 2019); doi: 10.1117/12.2511960
Show Author Affiliations
Eleni Michalopoulou, Loughborough Univ. (United Kingdom)
Alastair Gale, Loughborough Univ. (United Kingdom)
Yan Chen, Loughborough Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 10952:
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

© SPIE. Terms of Use
Back to Top