Which measurement method should be used for prostate volume for PI-RADS? A comparison of ellipsoid and segmentation methods

Autor: Jason Hafron, Brian Seifman, David Gangwish, Robert Colvin, Kiran R. Nandalur, David Walker, Sirisha R Nandalur
Rok vydání: 2021
Předmět:
Zdroj: Clinical imaging. 80
ISSN: 1873-4499
Popis: Prostate volume and PSA density (PSAd) are important in the risk stratification of suspected prostate cancer (Pca). PI-RADS v2.1 allows for determining volume via segmentation or ellipsoid calculation. The purpose of our study was to compare ellipsoid and segmentation volume calculation methods and evaluate if PSAd diagnostic performance is altered.We retrospectively assessed 397 patients (mean age/standard deviation: 63.7/7.4 years) who underwent MRI and prostate biopsy or prostatectomy, with Pca classified by Gleason ≥3 + 4 and ≥4 + 4 disease. Prostate total volumes were determined with ellipsoid calculations (TVe) and with semi-automated segmentation (TVs), along with inter-rater reliability with intraclass correlation coefficient (ICC). PSAd was calculated for TVe and TVs and ROC curves were created to compare performance for Gleason ≥3 + 4 and ≥4 + 4 disease.TVe was significantly higher than TVs (p 0.0001), with mean TVe = 55.4 mL and TVs = 51.0 mL. ROC area under the curve for PSAd derived with TVe (0.63, 95%CI:0.59-0.68) and TVs (0.64, 95%CI:0.59-0.68) showed no significant difference for Gleason ≥3 + 4 disease (p = 0.45), but PSAd derived with TVs (0.63, 95%CI: 0.58-0.68) significantly outperformed TVe (0.61, 95%CI: 0.57-0.67) for Gleason ≥4 + 4 disease (p = 0.02). Both methods demonstrated excellent inter-rater reliability with TVe with ICC of 0.93(95%CI: 0.92-0.94) and TVs with ICC of 0.98(95%CI: 0.98-0.99).Traditional ellipsoid measurements tend to overestimate total prostate volume compared to segmentation, but both methods demonstrate similar diagnostic performance of derived PSA density for PI-RADS clinically significant disease. For higher grade disease, PSAd derived from segmentation volumes demonstrates statistically significant superior performance. Both methods are viable, but segmentation volume is potentially better.
Databáze: OpenAIRE