Measurement of Prostate Volume with MRI (A Guide for the Perplexed): Biproximate Method with Analysis of Precision and Accuracy

Prostate volume on computed tomography correlates well with magnetic resonance imaging measurements and is reproducible across rater training levels

BACKGROUND

Data are lacking for the accuracy of computed tomography (CT) in measuring prostate size, which can streamline care and prevent invasive procedures. We evaluate agreement and intra/inter-observer variability in prostate sizing between CT and magnetic resonance imaging (MRI) planimetry for a wide range of gland sizes.

METHODS

We retrospectively reviewed 700 patients who underwent MRI fusion biopsy at a single institution and identified 89 patients that had a CT within 2 years of the MRI. Six reviewers from different training levels were categorized as student, resident, or attending and each measured prostate size on CT by the prolate ellipse method. Bland-Altman analysis determined the degree of agreement between CT and MRI. Inter- and intra-observer reliability was calculated for CT.

RESULTS

Mean CT volume was higher than MRI volume in the < 60 g group (51.5 g vs. 44.5 g, p = 0.004), but not in the ≥ 60 g group (101 g vs. 100 g, p = 0.458). The bias for overestimation of prostate volume by CT was 4.1 g across prostate volumes, but the proportional agreement between modalities improved with size. The Pearson correlation coefficient between CT/MRI and inter/intra-rater reliability for CT increased in the ≥ 60 g vs. the < 60 g group for all training levels.

CONCLUSIONS

Our data show that there is greater clinical utility for prostate size estimation by CT than previously established, particularly for larger glands where accurate size estimation may influence therapeutic decisions. In larger glands, prostate size estimation by CT is also reproducible across various training levels.

Analysis of the Performance and Accuracy of a PSA and PSA Ratio-Based Nomogram to Predict the Probability of Prostate Cancer in a Cohort of Patients with PIRADS 3 Findings at Multiparametric Magnetic Resonance Imaging

BACKGROUND

PIRADS score 3 represents a challenge in prostate cancer (PCa) detection with MRI. Our study aimed to evaluate the application of a nomogram on a cohort of patients with PIRADS 3.

METHODS

We analyzed 286 patients undergoing fusion prostate biopsy from January 2020 to February 2024. Only PIRADS 3 patients were included. Two nomograms, previously developed and based on clinical variables such as age, total PSA (specifically 2-10 ng/mL) and PSA ratio were applied to estimate the probability (Nomograms A and B) for PCa Grade Group (GG) > 3 and GG < 3.

RESULTS

Out of the 70 patients available for analysis, 14/70 patients (20%) had PCa, 4/14 were GG 1 (28.6%), 1/14 were GG 2 (7.1%), 5/14 were GG 3 (35.8%), 2/14 were GG 4 (14.3%) and 2/14 were GG 5 (14.3%). The median probability of PCa GG > 3 and GG < 3 was 5% and 33%, respectively. A significant difference (p = 0.033) was found between patients with negative versus positive biopsy for Nomogram B. There was a significant difference (p = 0.029) for Nomogram B comparing patients with GG < 3 and GG > 3. Using a cut-off of 40% for Nomogram B, sensitivity and specificity were 70% and 80%, respectively.

CONCLUSIONS

This cohort has a low probability of harboring PCa especially ISUP > 3. Nomogram B has good accuracy for discriminating patients with PCa from those with negative biopsy.

Integration of Multiparameter MRI into Conventional Pretreatment Risk Factors to Predict Positive Surgical Margins After Radical Prostatectomy

INTRODUCTION/BACKGROUND

Positive surgical margins (PSMs) after radical prostatectomy (RP) can increase the risk of biochemical recurrence in prostate cancer (PCa) patients. However, the prediction of the likelihood of PSMs in patients undergoing similar surgical procedures remains a challenge. We aim to develop a predictive model for PSMs in patients undergoing non-nerve-sparing RP.

PATIENTS AND METHODS

In this retrospective study, we analyzed data from PCa patients who underwent minimally invasive non-nerve-sparing RP at our hospital between June 2017 and June 2021. We identified independent risk factors associated with PSMs using clinical and MRI-based parameters in univariate and multivariate logistic regression analyzes. These factors were then used to develop a nomogram for predicting the probability of PSMs. The predictive performance was validated using calibration and receiver operating characteristic curve, area under the curve ,and decision curve analysis.

RESULTS

Multivariate analyzes revealed prostate-specific antigen density, tumor size, tumor location at the apex, tumor contact length, extracapsular extension (ECE) level, and apparent diffusion coefficient value as independent risk factors. A nomogram was developed and validated with high accuracy (C-index = 0.78). Furthermore, we found that 44.2% of patients diagnosed with organ-confined disease had ECE after surgery, and 29.1% of patients with Gleason scores ≤7 had higher pathological scores. Interestingly, the tumor burden calculated from PCa biopsy cores was overestimated when compared to postoperative PCa specimens.

CONCLUSION

We developed a reliable nomogram for predicting the risk of PSMs in PCa patients undergoing non-nerve-sparing RP. The study highlights the importance of incorporating these parameters in personalized surgical management.

Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies

We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging. Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers (Queen Mary Hospital and Princess Margaret Hospital, Hong Kong, China) between January 2017 and June 2022 were included. Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing. Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed. Out of the 747 patients, 47.3% had Prostate Imaging Reporting and Data System score 3 lesions only. The detection rate of clinically significant prostate cancer in this group was 15.0%. The cancer detection rates of clinically significant prostate cancer had statistically significant differences 5.3% in prostate health index <25.0, 7.4% in prostate health index 25.0-34.9, 17.9% in prostate health index 35.0-54.9, and 52.6% in prostate health index ≥55.0 (P < 0.01). Among the patients, 26.9% could have avoided a biopsy with a prostate health index <25.0, at the expense of a 5.3% risk of missing clinically significant prostate cancer. Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions. Biopsies could be avoided in patients with low prostate health index, with a small risk of missing clinically significant prostate cancer.

Using a Recurrent Neural Network To Inform the Use of Prostate-specific Antigen (PSA) and PSA Density for Dynamic Monitoring of the Risk of Prostate Cancer Progression on Active Surveillance

The global uptake of prostate cancer (PCa) active surveillance (AS) is steadily increasing. While prostate-specific antigen density (PSAD) is an important baseline predictor of PCa progression on AS, there is a scarcity of recommendations on its use in follow-up. In particular, the best way of measuring PSAD is unclear. One approach would be to use the baseline gland volume (BGV) as a denominator in all calculations throughout AS (nonadaptive PSAD, PSAD_NA), while another would be to remeasure gland volume at each new magnetic resonance imaging scan (adaptive PSAD, PSAD_A). In addition, little is known about the predictive value of serial PSAD in comparison to PSA. We applied a long short-term memory recurrent neural network to an AS cohort of 332 patients and found that serial PSAD_NA significantly outperformed both PSAD_A and PSA for follow-up prediction of PCa progression because of its high sensitivity. Importantly, while PSAD_NA was superior in patients with smaller glands (BGV ≤55 ml), serial PSA was better in men with larger prostates of >55 ml.

Patient summary

Repeat measurements of prostate-specific antigen (PSA) and PSA density (PSAD) are the mainstay of active surveillance in prostate cancer. Our study suggests that in patients with a prostate gland of 55 ml or smaller, PSAD measurements are a better predictor of tumour progression, whereas men with a larger gland may benefit more from PSA monitoring.

Assessment of Prostate Volume and Prostate-specific Antigen Density With the Segmentation Method on Magnetic Resonance Imaging

BACKGROUND/AIM

This study aimed to compare the prostate volume (PV) and prostate-specific antigen density (PSAD) obtained using the ellipsoid volume formula or segmentation methods on magnetic resonance imaging (MRI) and further predict prostate cancer (PCa).

PATIENTS AND METHODS

Retrospectively, the enrolled patients underwent prostate MRI and had PSA levels between 4 and 10 ng/ml. The PV was measured with both the ellipsoid volume formula (PVe) and the segmentation method (PVs). The transitional zone volume (TZV) was measured with the segmentation method. The PSADe, PSADs, and PSAD_TZV were calculated. Bland-Altman plots were used to compare the agreements. ROC curve analysis was used to compare the diagnostic accuracies to predict PCa. The results were also compared between the PCa and the no-PCa groups, and among tumors with different locations and different Gleason scores (GS).

RESULTS

Seventy-six of the 117 enrolled patients were classified into the PCa group. There were high agreements between PVs and PVe as well as between PSADs and PSADe, while several outliers were mainly due to post-transurethral resection of the prostate changes and irregular hyperplastic nodules. The diagnostic accuracy of PSADe (AUC: 0.732) was slightly higher than that of PSADs (AUC: 0.729) and PSAD_TZV (AUC: 0.715). The PSADe and PSADs were not different among different tumor locations but were higher in GS ≥7 lesions (both p=0.006).

CONCLUSION

The segmentation method can be an alternative method to measure PV and calculate PSAD before prostate biopsy, particularly in post-transurethral resection of the prostate patients or those with irregular hyperplastic nodules.

Prostate gland volume estimation: anteroposterior diameters measured on axial versus sagittal ultrasonography and magnetic resonance images

PURPOSE

The aim of this study was to evaluate the accuracy of prostate volume estimates calculated from the ellipsoid formula using the anteroposterior (AP) diameter measured on axial and sagittal images obtained through ultrasonography (US) and magnetic resonance imaging (MRI).

METHODS

This retrospective study included 456 patients with transrectal US and MRI from two university hospitals. Two radiologists independently measured the prostate gland diameters on US and MRI: AP diameters on axial and sagittal images, transverse, and longitudinal diameters on midsagittal images. The volume estimates, volumeax and volumesag, were calculated from the ellipsoid formula by using the AP diameter on axial and sagittal images, respectively. The prostate volume extracted from MRI-based whole-gland segmentation was considered the gold standard. The intraclass correlation coefficient (ICC) was used to evaluate the inter-method agreement between volumeax and volumesag, and agreement with the gold standard. The Wilcoxon signedrank test was used to analyze the differences between the volume estimates and the gold standard.

RESULTS

The prostate gland volume estimates showed excellent inter-method agreement, and excellent agreement with the gold standard (ICCs >0.9). Compared with the gold standard, the volume estimates were significantly larger on MRI and significantly smaller on US (P<0.001). The volume difference (segmented volume-volume estimate) was greater in patients with larger prostate glands, especially on US.

CONCLUSION

Volumeax and volumesag showed excellent inter-method agreement and excellent agreement with the gold standard on both US and MRI. However, prostate volume was overestimated on MRI and underestimated on US.

Influence of transurethral enucleation with bipolar of the prostate on erectile function: Prospective analysis of 51 patients at 12-month follow-up

Background

Transurethral enucleation with bipolar (TUEB) is a safe and effective surgery for benign prostatic obstruction (BPO). However, few data exist concerning the influence of TUEB on erectile function (EF) in patients with BPO.

Objective

To evaluate the influence of TUEB on EF in patients with BPO at 3- and 12-month follow-up.

Material and methods

We prospectively enrolled 51 patients who underwent TUEB from June 2016 to April 2020. We evaluated maximum urinary flow rate (Qmax), postvoid residual urine (PVR), International Prostate Symptom Score (IPSS), quality of life (QoL), and International Index of Erectile Function-5 (IIEF-5) preoperatively and at 3- and 12-month follow-up. We classified the patients according to their preoperative IIEF-5 score into group 1 (IIEF-5 ≥10; n = 24) and group 2 (IIEF-5 <10; n = 27), and for further evaluation of EF, into subgroups a: severe (IIEF-5 5–7), b: moderate (8–11), c: mild to moderate (12–16), d: mild (17–21), and e: no erectile dysfunction (22–25). Data are displayed as median or median (interquartile range).

Results

The study comprised 51 patients with a median age of 75 (70.5–79.5) years. Median prostate and transition zone volumes were 69.5 (46.5–78.8) mL and 30.5 (19–43) mL, respectively. Urinary function improved significantly when comparing respective preoperative, 3-month, and 12-month follow-up values: Qmax (7.6, 12.9, 15.2 mL/s), PVR (50, 0, 0 mL), IPSS (20.5, 9, 6), and QoL (5, 2, 2), respectively. There was no significant change in IIEF-5 score across the three time points: 9, 7, 8. The IIEF-5 score slightly but significantly increased between the preoperative and 12-month follow-up values in group 2 (5, 5, 6) and subgroup a (5, 5, 5).

Conclusion

TUEB was effective and safe surgery for patients with BPO and showed no significant influence on EF at 12-month follow-up after TUEB in patients with BPO.

Prostate volume prediction on MRI: tools, accuracy and variability

OBJECTIVE

A reliable estimation of prostate volume (PV) is essential to prostate cancer management. The objective of our multi-rater study was to compare intra- and inter-rater variability of PV from manual planimetry and ellipsoid formulas.

METHODS

Forty treatment-naive patients who underwent prostate MRI were selected from a local database. PV and corresponding PSA density (PSAd) were estimated on 3D T2-weighted MRI (3 T) by 7 independent radiologists using the traditional ellipsoid formula (TEF), the newer biproximate ellipsoid formula (BPEF), and the manual planimetry method (MPM) used as ground truth. Intra- and inter-rater variability was calculated using the mixed model-based intraclass correlation coefficient (ICC).

RESULTS

Mean volumes were 67.00 (± 36.61), 66.07 (± 35.03), and 64.77 (± 38.27) cm³ with the TEF, BPEF, and MPM methods, respectively. Both TEF and BPEF overestimated PV relative to MPM, with the former presenting significant differences (+ 1.91 cm³, IQ = [- 0.33 cm³, 5.07 cm³], p val = 0.03). Both intra- (ICC > 0.90) and inter-rater (ICC > 0.90) reproducibility were excellent. MPM had the highest inter-rater reproducibility (ICC = 0.999). Inter-rater PV variation led to discrepancies in classification according to the clinical criterion of PSAd > 0.15 ng/mL for 2 patients (5%), 7 patients (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 robust method for PV assessment and PSAd calculation, with the lowest variability. TEF showed a high degree of concordance with MPM but a slight overestimation of PV. Precise anatomic landmarks as defined with the BPEF led to a more accurate PV estimation, but also to a higher variability.

KEY POINTS

• Manual planimetry used for prostate volume estimation is robust and reproducible, with the lowest variability between readers. • Ellipsoid formulas are accurate and reproducible but with higher variability between readers. • The traditional ellipsoid formula tends to overestimate prostate volume.

Estimation of the Prostate Volume from Abdominal Ultrasound Images by Image-Patch Voting

Estimation of the prostate volume with ultrasound offers many advantages such as portability, low cost, harmlessness, and suitability for real-time operation. Abdominal Ultrasound (AUS) is a practical procedure that deserves more attention in automated prostate-volume-estimation studies. As the experts usually consider automatic end-to-end volume-estimation procedures as non-transparent and uninterpretable systems, we proposed an expert-in-the-loop automatic system that follows the classical prostate-volume-estimation procedures. Our system directly estimates the diameter parameters of the standard ellipsoid formula to produce the prostate volume. To obtain the diameters, our system detects four diameter endpoints from the transverse and two diameter endpoints from the sagittal AUS images as defined by the classical procedure. These endpoints are estimated using a new image-patch voting method to address characteristic problems of AUS images. We formed a novel prostate AUS data set from 305 patients with both transverse and sagittal planes. The data set includes MRI images for 75 of these patients. At least one expert manually marked all the data. Extensive experiments performed on this data set showed that the proposed system results ranged among experts’ volume estimations, and our system can be used in clinical practice.

Comparison of PI-RADS Versions 2.0 and 2.1 for MRI-based Calculation of the Prostate Volume

RATIONALE AND OBJECTIVES

Prostate gland volume (PGV) should be routinely included in MRI reports of the prostate. The recently updated Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 includes a change in the recommended measurement method for PGV compared to version 2.0. The purpose of this study was to evaluate the agreement of MRI-based PGV calculations with the volumetric manual slice-by-slice prostate segmentation as a reference standard using the linear measurements per PI-RADS versions 2.0 and 2.1. Furthermore, to assess inter-reader agreement for the different measurement approaches, determine the influence of an enlarged transition zone on measurement accuracy and to assess the value of the bullet formula for PGV calculation.

MATERIALS AND METHODS

Ninety-five consecutive treatment-naive patients undergoing prostate MRI were retrospectively analyzed. Prostates were manually contoured and segmented on axial T2-weighted images. Four different radiologists independently measured the prostate in three dimensions according to PI-RADS v2.0 and v2.1, respectively. MRI-based PGV was calculated using the ellipsoid and bullet formulas. Calculated volumes were compared to the reference manual segmentations using Wilcoxon signed-rank test. Inter-reader agreement was calculated using intraclass correlation coefficient (ICC).

RESULTS

Inter-reader agreement was excellent for the ellipsoid and bullet formulas using PI-RADS v2.0 (ICC 0.985 and 0.987) and v2.1 (ICC 0.990 and 0.994), respectively. The median difference from the reference standard using the ellipsoid formula derived PGV was 0.4 mL (interquartile range, -3.9 to 5.1 mL) for PI-RADS v2.0 (p = 0.393) and 2.6 mL (interquartile range, -1.6 to 7.3 mL) for v2.1 (p < 0.001) with a median difference of 2.2 mL. The bullet formula overestimated PGV by a median of 13.3 mL using PI-RADS v2.0 (p < 0.001) and 16.0 mL using v2.1 (p < 0.001). In the presence of an enlarged transition zone the PGV tended to be higher than the reference standard for PI-RADS v2.0 (median difference of 4.7 mL; p = 0.018) and for v2.1 (median difference of 5.7 mL, p < 0.001) using the ellipsoid formula.

CONCLUSION

Inter-reader agreement was excellent for the calculated PGV for both methods. PI-RADS v2.0 measurements with the ellipsoid formula yielded the most accurate volume estimates. The differences between PI-RADS v2.0 and v2.1 were statistically significant although small in absolute numbers but may be of relevance in specific clinical scenarios like prostate-specific antigen density calculation. These findings validate the use of the ellipsoid formula and highlight that the bullet formula should not be used for prostate volume estimation due to systematic overestimation.

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

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.

Initial phantom studies for an office-based low-field MR system for prostate biopsy

Purpose

Prostate cancer is the second most prevalent cancer in US men, with about 192,000 new cases and 33,000 deaths predicted for 2020. With only a 31% 5-year survival rate for patients with an initial diagnosis of stage-four prostate cancer, the necessity for early screening and diagnosis is clear. In this paper, we present navigation accuracy results for Promaxo’s MR system intended to be used in a physician’s office for image-guided transperineal prostate biopsy.

Methods

The office-based low-field MR system was used to acquire images of prostate phantoms with needles inserted through a transperineal template. Coordinates of the estimated sample core locations in the office-based MR system were compared to ground truth needle coordinates identified in a 1.5T external reference scan. The error was measured as the distance between the planned target and the ground truth core center and as the shortest perpendicular distance between the planned target and the ground truth trajectory of the whole core.

Results

The average error between the planned target and the ground truth core center was 2.57 ± 1.02 mm, [1.93–3.21] 95% CI. The average error between the planned target to the actual core segment was 2.05 ± 1.24 mm, [1.53–2.56] 95% CI.

Conclusion

The average navigation errors were below the clinically significant threshold of 5 mm. The initial phantom results demonstrate the feasibility of the office-based system for prostate biopsy.

Prostatic peripheral zone thickness: what is normal on magnetic resonance imaging?

PURPOSE

To report the precision of a technique of measuring the PZ thickness on T2-weighted MRI and report normal parameters in patients with normal-sized prostates. We also wanted to establish the mean and second standard deviations (2SD) above and below the mean as criteria for abnormally narrow or expanded PZ thickness.

METHODS

Of the initial 1566 consecutive cohort referred for evaluation for carcinoma based on elevated PSA (prostate specific antibody) or DRE (digital rectal examination), 132 separate subjects with normal-sized prostates were selected for this study. Mean age was 58.2 years (15-82). Median serum PSA was 6.2 ng/mL (range 0.3-145). Most were asymptomatic for lower urinary tract symptoms (LUTS). Inclusion criteria in this study required technically adequate T2-weighted MRI and total prostatic volume (TPV) ≤ 25 cc. Exclusion criteria included post-prostatic surgical and radiation patients, patients having had medical management or minimally invasive therapy for BPH, those being treated for prostatitis. Patients with suspected tumor expanding or obscuring measurement boundaries were also not considered. Transition zone (TZ) and peripheral zone (PZ) volumes were determined using the prolate ellipsoid model. Posterolateral measurement of the PZ was obtained at the axial level of maximal transverse diameter of the prostate on a line drawn from the outer boundary of the TZ to the inner boundary of the external prostatic capsule (EPC). The data were normally distributed. Therefore, it was analyzed using the 2-sided student t-test and Pearson product correlation statistic.

RESULTS

Mean pooled (composite) measurement for the posterolateral PZ (PLPZ) was 10 mm (CI 9.5-10.5 mm) with SD of 2.87 mm. Means were statistically the same for the 2 observers (p = 0.75). Pearson correlation between the two observers was 0.63.

CONCLUSIONS

In a prostate ≤ 25 cc volume , the posterolateral PZ should be no thicker than 15.8 mm and averages 10.0 mm when measured in the maximal axial plane on MRI. These norms were independent of age or use of endorectal coil. The technique measurement demonstrated clinically useful precision.

Prostate cancer measurements on serial MRI during active surveillance: it's time to be PRECISE

OBJECTIVE

The PRECISE criteria for reporting multiparametric MRI in patients on active surveillance (AS) for prostate cancer (PCa) score the likelihood of clinically significant change over time using a 1-5 scale, where 4 or 5 indicates radiological progression. According to the PRECISE recommendations, the index lesion size can be reported using different definitions of volume (planimetry or ellipsoid formula) or by measuring one or two diameters. We compared different measurements using planimetry as the reference standard and stratified changes according to the PRECISE scores.

METHODS

We retrospectively analysed 196 patients on AS with PCa confirmed by targeted biopsy who had two MR scans (baseline and follow-up). Lesions were measured on T₂ weighted imaging (T₂WI) according to all definitions. A PRECISE score was assessed for each patient.

RESULTS

The ellipsoid formula exhibited the highest correlation with planimetry at baseline (ρ = 0.97) and follow-up (ρ = 0.98) imaging, compared to the biaxial measurement and single maximum diameter. There was a significant difference (p < 0.001) in the yearly percentage volume change between radiological regression/stability (PRECISE 2-3) and progression (PRECISE 4-5) for planimetry (39.64%) and for the ellipsoid formula (46.78%).

CONCLUSION

The ellipsoid formula could be used to monitor tumour growth during AS. Evidence of a significant yearly percentage volume change between radiological regression/stability (PRECISE 2-3) and progression (PRECISE 4-5) has been also observed.

ADVANCES IN KNOWLEDGE

The ellipsoid formula is a reasonable surrogate for planimetry in capturing tumour volume changes on T₂WI in patients on imaging-led AS. This is also associated with radiological changes using the PRECISE recommendations.