Prostate volume prediction on MRI: tools, accuracy and variability - Archive ouverte HAL Access content directly
Journal Articles European Radiology Year : 2022

Prostate volume prediction on MRI: tools, accuracy and variability

Abstract

OBJECTIVE: A reliable estimation of prostate volume (PV) is essential to prostate cancer management. Theobjective of our multi-rater study was to compare intra and inter-rater variability of PV frommanual planimetry and ellipsoid formulas.METHODS: Forty treatment-naive patients who underwent prostate MRI were selected from a localdatabase. PV and corresponding PSA density (PSAd) were estimated on 3D T2-weighted MRI(3T) by 7 independent radiologists using the traditional ellipsoid formula (TEF),the newerbiproximate ellipsoid formula (BPEF), and the manual planimetry method (MPM) used asground truth. Intra and inter-rater variability was calculated using the mixed model basedintraclass correlation coefficient (ICC).RESULTS: Mean volumes were 67.00 (±36.61), 66.07(±35.03), and 64.77(±38.27)cm 3 with the TEF,BPEF, and MPM methods respectively. Both TEF and BPEF overestimated PV relative toMPM, with the former presenting significant differences (+1.91cm3, IQ=[-0.33cm3, 5.07cm3],p-val=0.03). Both intra (ICC>0.90) and inter-rater (ICC>0.90) reproducibility were excellent. MPM had thehighest inter-rater reproducibility (ICC=0.999). Inter-rater PV variation led to discrepancies inclassification according to the clinical criterion of PSAd>0.15ng/mL for 2 patients (5%), 7patients (17.5%), and 9 patients (22.5%) when using MPM, TEF, and BPEF respectively.CONCLUSION: PV measurements using ellipsoid formulas and MPM are highly reproducible. MPM is a robustmethod for PV assessment and PSAd calculation, with the lowest variability. TEF showed ahigh degree of concordance with MPM but a slight overestimation of PV. Precise anatomiclandmarks as defined with the BPEF led to a more accurate PV estimation, but also to a highervariability.
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Dates and versions

hal-03409262 , version 1 (04-01-2022)

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Dimitri Hamzaoui, Sarah Montagne, Benjamin Granger, Alexandre Allera, Malek Ezziane, et al.. Prostate volume prediction on MRI: tools, accuracy and variability. European Radiology, 2022, ⟨10.1007/s00330-022-08554-4⟩. ⟨hal-03409262⟩
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