Rationale and Objectives
Prostate volume (PV) determination provides important clinical information. We compared PVs determined by digital rectal examination (DRE), transrectal ultrasound (TRUS), magnetic resonance imaging (MRI) with or without three-dimensional (3D) segmentation software, and surgical prostatectomy weight (SPW) and volume (SPV).
Materials and Methods
This retrospective review from 2010 to 2016 included patients who underwent radical prostatectomy ≤1 year after multiparametric prostate MRI. PVs from DRE and TRUS were obtained from urology clinic notes. MRI-based PVs were calculated using bullet and ellipsoid formulas, automated 3D segmentation software (MRI-A3D), manual segmentation by a radiologist (MRI-R3D), and a third-year medical student (MRI-S3D). SPW and SPV were derived from pathology reports. Intraclass correlation coefficients compared the relative accuracy of each volume measurement.
Results
Ninety-nine patients were analyzed. Median PVs were DRE 35 mL, TRUS 35 mL, MRI-bullet 49 mL, MRI-ellipsoid 39 mL, MRI-A3D 37 mL, MRI-R3D 36 mL, MRI-S3D 36 mL, SPW 54 mL, SPV-bullet 47 mL, and SPV-ellipsoid 37 mL. SPW and bullet formulas had consistently large PV, and formula-based PV had a wider spread than PV based on segmentation. Compared to MRI-R3D, the intraclass correlation coefficient was 0.91 for MRI-S3D, 0.90 for MRI-ellipsoid, 0.73 for SPV-ellipsoid, 0.72 for MRI-bullet, 0.71 for TRUS, 0.70 for SPW, 0.66 for SPV-bullet, 0.38 for MRI-A3D, and 0.33 for DRE.
Conclusions
With MRI-R3D measurement as the reference, the most reliable methods for PV estimation were MRI-S3D and MRI-ellipsoid formula. Automated segmentations must be individually assessed for accuracy, as they are not always truly representative of the prostate anatomy. Manual segmentation of the prostate does not require expert training.
Introduction
Prostate volume (PV) determination is an essential component of evaluation and management of prostatic disease, including benign prostatic hypertrophy (BPH) and prostate cancer (PCa). With respect to BPH, PV estimation can provide objective data for the purposes of treatment planning, monitoring response to therapy, and surgical technique. For example, treatment options for lower urinary tract symptoms secondary to BPH depend on gland size, with larger glands (>40 mL) recommended for 5-alpha reductase inhibitors and smaller glands (<30 mL) often treated with alpha-adrenergic receptor blockers alone . PV may be a predictor of BPH complications, such as urinary retention, hydronephrosis, and renal injury, which may also influence therapy . Treatment effectiveness can be evaluated with serial PV estimations and can be stratified based on zonal anatomy as well . Furthermore, PV frequently affects the choice of surgical approach for BPH when considering between ablative procedures, transurethral resection, minimally invasive surgery, and open prostatectomy .
For patients with PCa, PV is helpful for risk stratification during screening and risk assessment, especially when used in conjunction with prostate-specific antigen (PSA). Although PSA values correlate with risk of PCa, elevations in PSA can also be due to BPH and inflammatory benign prostatic diseases, such as prostatitis, limiting the specificity . Biopsies performed based on elevated PSA alone can result in biopsy rates negative for malignancy in up to 76% of cases . In addition, overdiagnosis rates as high as 60% have been reported, as patients may suffer from unnecessary morbidity from treatment of clinically indolent, low-grade PCa . Multiple studies have shown that PSA derivatives that incorporate volume, such as PSA density , outperform PSA in predicting overall and clinically significant PCa , as larger prostates not only have greater rates of smaller volume PCa but also less-aggressive tumors across a variety of pathologic variables . Another PSA derivative is the PV index, equal to the ratio of transitional zone to peripheral zone volume, which is inversely correlated with PCa risk . Use of an approach to risk stratification that includes PV helps to select the most appropriate patients for active surveillance and may reduce overtreatment of low-risk tumors .
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Materials and Methods
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Results
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TABLE 1
Clinical, Radiographic, and Pathologic Characteristics
Variable N (%) or Median (IQR) Median age, y (IQR) 63 (59–68) Median pretreatment PSA, ng/mL (IQR) 6.6 (4.3–11.4) Biopsy Gleason group \* 1 (3 + 3) 29 (32.2%) 2 (3 + 4) 25 (27.8%) 3 (4 + 3) 13 (14.4%) 4 (8) 14 (15.6%) 5 (9–10) 9 (10.0%) Pathologic stage pT2 and below 63 (63.6%) pT3 and above 36 (36.4%) Surgical Gleason group † 1 (3 + 3) 6 (6.1%) 2 (3 + 4) 43 (43.9%) 3 (4 + 3) 28 (28.6%) 4 (8) 11 (11.2%) 5 (9–10) 10 (10.2%) Extraprostatic extension † 30 (30.6%) Seminal vesicle invasion † 12 (12.2%) Lymph node involvement † 22 (22.4%)
IQR, interquartile range; PSA, prostate-specific antigen.
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TABLE 2
Prostate Volume Calculations (mL)
Variable N Mean Standard Deviation Median Lower Quartile Upper Quartile Quartile Range DRE 87 38.0 12.8 35.0 35.0 40.0 5.0 TRUS 85 40.4 18.8 35.0 28.0 46.0 18.0 MRI-A3D 99 46.3 35.2 37.0 29.0 51.0 22.0 MRI-R3D 99 40.8 20.1 36.0 26.0 48.0 22.0 MRI-S3D 99 39.8 18.2 36.0 27.0 47.0 20.0 MRI-ellipse 99 45.1 23.6 39.0 29.0 53.0 24.0 MRI-bullet 99 56.9 29.7 49.0 37.0 66.0 29.0 SPV-ellipse 99 38.9 23.2 37.4 26.2 47.0 20.8 SPV-bullet 99 49.0 29.2 47.1 33.0 59.2 26.2 SPW 89 57.8 21.2 54.0 42.0 65.0 23.0
DRE, digital rectal examination; MRI-A3D, magnetic resonance imaging with automated 3D segmentation software; MRI-R3D, magnetic resonance imaging with manual segmentation by a radiologist; MRI-S3D, magnetic resonance imaging with manual segmentation by a third-year medical student; TRUS, transrectal ultrasound; SPV, surgical prostatectomy volume; SPW, surgical prostatectomy weight.
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TABLE 3
Prostate Volume Measurement Inter-rater Reliability Correlations
Volume Calculation Method Compared to MRI-R3D Shrout-Fleiss Reliability MRI-S3D 0.91 MRI-ellipse 0.90 SPV-ellipse 0.73 MRI-bullet 0.72 TRUS 0.71 SPW 0.70 SPV-bullet 0.66 MRI-A3D 0.38 DRE 0.33
DRE, digital rectal examination; MRI-A3D, magnetic resonance imaging with automated 3D segmentation software; MRI-S3D, magnetic resonance imaging with manual segmentation by a third-year medical student; TRUS, transrectal ultrasound; SPV, surgical prostatectomy volume; SPW, surgical prostatectomy weight.
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Discussion
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Conclusions
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Acknowledgments
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