Highlights
- •Traditional ellipsoid measurements overestimate prostate volume versus segmentation.
- •Both methods derived PSA density have similar performance for Gleason >/=7 disease.
- •Segmentation method for PSA density outperforms ellipsoid for high grade cancer.
Abstract
Purpose
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.
Methods
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.
Results
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).
Conclusion
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.
Keywords
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Article Info
Publication History
Published online: September 20, 2021
Accepted:
September 6,
2021
Received in revised form:
August 8,
2021
Received:
June 19,
2021
Identification
Copyright
© 2021 Elsevier Inc. All rights reserved.
