Effects of "real life" prostate MRI inter-observer variability on total needle samples and indication for biopsy

Developments in Ultrasound-Based Imaging for Prostate Cancer Detection

BACKGROUND

Prostate cancer is a significant health issue worldwide, but methods to screen for and diagnose this disease have significant inherent limitations. Some efforts to address these limitations have involved the use of ultrasound-based imaging methods.

METHODS

This narrative review paper focuses on recent developments in the use of medical imaging, with a focus on ultrasound and related methods, to improve the diagnosis of prostate cancer. These methods include: elastography, contrast-enhanced ultrasound, targeted contrast agents, quantitative ultrasound, multiparametric ultrasound, micro-ultrasound, and photoacoustic imaging.

RESULTS

This paper provides an update on clinically relevant imaging technologies which are in the technical and preclinical literature.

CONCLUSION

Novel methods and their performance are highlighted, including how they address limitations in current clinical care.

Are Patients with Prostate Imaging Reporting and Data System 5 Lesions Eligible for Active Surveillance? A Multicentric European Study

BACKGROUND AND OBJECTIVE

Patients with Prostate Imaging Reporting and Data System (PI-RADS) 5 lesions are at a high risk of clinically significant prostate cancer (PCa), extracapsular extension, and biochemical recurrence (BCR) after local treatment. Managing these patients with active surveillance (AS) can be particularly challenging when targeted biopsies indicate favorable-risk tumors. This study aims to evaluate the outcomes of patients with PI-RADS 5 lesions managed with AS.

METHODS

We analyzed data from 126 patients treated at 16 centers in France, Italy, Switzerland, and Belgium, whose initial magnetic resonance imaging revealed at least one PI-RADS 5 lesion and who subsequently underwent AS. The primary endpoint was BCR-free survival. The secondary endpoints included metastasis-free survival, time to biopsy grade reclassification, and time to AS discontinuation, along with their predictors.

KEY FINDINGS AND LIMITATIONS

After a median follow-up of 36 mo after confirmatory biopsies (95% confidence interval [CI] 23-55), BCR was observed in five patients, with the median time not reached. The 5-yr BCR-free survival rate was 88% (95% CI 79-99%). No metastatic progression was reported. Seventeen patients experienced biopsy grade reclassification (median time not reached), and 55 patients discontinued AS. The median time to AS discontinuation was 55 mo (95% CI 46 mo-not applicable). The 5-yr AS discontinuation-free survival rate was 41% (95% CI 30.8-54.6%). On a multivariate Cox regression analysis, baseline prostate-specific antigen density and the percentage of positive biopsy cores were associated with biopsy grade reclassification, AS discontinuation, and BCR.

CONCLUSIONS AND CLINICAL IMPLICATIONS

With strict monitoring, AS is a safe management option for patients with PI-RADS 5 lesions and favorable-risk PCa. Limitations are mainly inherent to the retrospective design of this study.

Do we need MRI in all biopsy naïve patients? A multicenter cohort analysis

PURPOSE

The combined approach (CB) of magnetic resonance imaging (MRI)-guided biopsy (TB) and systematic biopsy (SB) is strongly recommended based on numerous studies in biopsy naïve men with suspicion of clinically significant prostate cancer (csPCA). However, the unbalanced accessibility of MRI, challenges related to reimbursement and the scarcity of specialized medical practitioners continue to impede a widespread implementation. Therefore, our objective was to determine a subset of men that could undergo SB without an increased risk of underdiagnosis at reduced expenses.

METHODS

A multicenter analysis of 2714 men with confirmed PCA and suspicious MRI who underwent CB were enrolled. Cancer detection rates were compared between the different biopsy routes SB, TB and CB using McNemar paired test. Additionally, Gleason grade up- and down-grading was determined.

RESULTS

CB detected more csPCA than TB and SB (p < 0.001), irrespective of MRI findings or biopsy route (transperineal vs. transrectal). Thereby, single biopsy approaches misgraded > 50% of csPCA. TB showed higher diagnostic efficiency, defined as csPCA detection per biopsy core than CB and SB (p < 0.001). For patients with abnormal DRE and PSA levels > 12.5 ng/ml, PSAD > 0.35 ng/ml/cm3, or > 75 years, SB and CB showed similar csPCA detection rates.

CONCLUSION

Conducting CB provides the highest level of diagnostic certainty and minimizes the risk of underdiagnosis in almost all biopsy-naive men. However, in patients with suspicious DRE and high PSA levels, PSAD, or advanced age solely using SB leads to similar csPCA detection rates. Thus, a reduced biopsy protocol may be considered for these men in case resources are limited.

Combination of DNA methylation biomarkers with multiparametric magnetic resonance and ultrasound imaging fusion biopsy to detect the local spread of prostate cancer

BACKGROUND

This study aimed to investigate the extent of field cancerization adjacent to index lesions in prostate cancer (PCa) by measuring DNA methylation of selected tumor suppressor genes in the perifocal tissue of PCa not visible on multiparametric magnetic resonanse imaging (mpMRI) for the safe zone of focal therapy identification.

METHODS

A total of 272 patients were enrolled in this study, 44 patients' tissue biosamples were included in the field cancerization research, and 272 urine samples were included in the urine-based test development. Targeted biopsies were performed using the mpMRI/ultrasoundimage fusion system.

RESULTS

Quantitative analysis revealed significantly higher DNA methylation levels of RARB, RASSF1, GSTP1 & APC genes in the index lesion compared with perifocal tissue samples 10 mm away from it (p < 0.0001). Notably, the RARB, GSTP1 & APC and RARB, RASSF1, GSTP1 & APC biomarker combinations exhibited the highest sensitivity and specificity comparing the extent of DNA methylation in index lesions and noncancerous prostate tissues 20 mm away (both area under the curve [AUC] = 0.98; p < 0.0001). The analysis of the potential urinary biomarkers showed that the combination of all four DNA methylation biomarkers with prostate-specific antigen (PSA) or PSA density (PSAD) in the blood significantly improves the detection of clinically significant PCa (csPCa). The combination of the four-biomarker test with PSAD allowed the identification of csPCa with ≥90% sensitivity and specificity.

CONCLUSION

Thus, this study suggests that for focal therapy by region target hemi-ablation, the safe distance from the index lesion is no less than 10 mm. Noninvasive urine DNA methylation tests in combination with PSAD could be used for further follow-up of the patients, but larger prospective studies with external validation are needed.

Development and validation of nomogram to improve the specificity of multiparametric MRI for clinically significant prostate cancer

OBJECTIVE

To develop and validate a nomogram to improve the specificity of prostate imaging reporting and data system (PI-RADS) on multiparametric magnetic resonance imaging (MRI) for clinically significant prostate cancer on targeted fusion biopsy.

METHODS

A retrospective review of patients who underwent fusion biopsy for PI-RADS 3-5 lesions using UroNav and Artemis systems between 2016 and 2022 was performed. Patients were divided into those with CS disease on fusion biopsy (Gleason grade group ≥2) versus those without. Multivariable analysis was used to identify variables associated with CS disease. A 100-point nomogram was constructed, and ROC curve was generated.

RESULTS

1485 lesions (1032 patients) were identified, 510 (34%) were PI-RADS 3, 586 (40%) were PI-RADS 4, and 389 (26%) were PI-RADS 5. Of these, 11% of PI-RADS 3, 39% of PI-RADS 4, and 61% of PI-RADS 5 showed CS disease. CS disease was associated with older age (OR 1.04, 95% CI 1.02-1.06, p < 0.01), previous negative biopsy (OR 0.52, 95% CI 0.36-0.74, p < 0.01), presence of multiple PI-RADS 3-5 lesions (OR 0.61, 95% CI 0.45-0.83, p < 0.01), peripheral zone location (OR 1.88, 95% CI 1.30-2.70, p < 0.01), PSA density (OR 1.48 per 0.1 unit, 95% CI 1.33-1.64, p < 0.01), PI-RADS score 4 (OR 3.28, 95% CI 2.21-4.87, p < 0.01), and PI-RADS score 5 (OR 7.65, 95% CI 4.93-11.85, p < 0.01). Area under ROC curve was 82% for nomogram compared to 75% for PI-RADS score alone.

CONCLUSION

We report a nomogram that combines PI-RADS score with other clinical parameters. The nomogram outperforms PI-RADS score for the detection of CS prostate cancer.

Comparison of Prostate-Specific Antigen and Its Density and Prostate Health Index and Its Density for Detection of Prostate Cancer

As the incidence of prostate cancer (PCa) has increased, screening based on prostate-specific antigen (PSA) has become controversial due to the low specificity of PSA. Therefore, we investigated the diagnostic performance of prostate health index (PHI) density (PHID) for the detection of PCa and clinically significant PCa (csPCa) compared to PSA, PSA density (PSAD), and PHI as a triaging test. We retrospectively reviewed 306 men who underwent prostate biopsy for PSA levels of 2.5 to 10 ng/mL between January 2020 and April 2023. Of all cohorts, 86 (28.1%) and 48 (15.7%) men were diagnosed with PCa and csPCa, respectively. In ROC analysis, the highest AUC was identified for PHID (0.812), followed by PHI (0.791), PSAD (0.650), and PSA (0.571) for PCa. A similar trend was observed for csPCa: PHID (AUC 0.826), PHI (AUC 0.796), PSAD (AUC 0.671), and PSA (0.552). When the biopsy was restricted to men with a PHID ≥ 0.56, 26.5% of unnecessary biopsies could be avoided; however, 9.3% of PCa cases and one csPCa case (2.1%) remained undiagnosed. At approximately 90% sensitivity for csPCa, at the given cut-off values of PHI ≥ 36.4, and PHID ≥ 0.91, 48.7% and 49.3% of unnecessary biopsies could be avoided. In conclusion, PHID had a small advantage over PHI, about 3.6%, for the reduction in unnecessary biopsies for PCa. The PHID and PHI showed almost the same diagnostic performance for csPCa detection. PHID can be used as a triaging test in a clinical setting to pre-select the risk of PCa and csPCa.

Reply to Jue, J.S.; Alameddine, M. Role of PSA Density and MRI in PSA Interpretation. Comment on "Lumbreras et al. Variables Associated with False-Positive PSA Results: A Cohort Study with Real-World Data. Cancers 2023, 15, 261"

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Should men undergo MRI before prostate biopsy - CON

Prostate magnetic resonance imaging (MRI) is increasingly used prior to biopsy in response to the overdiagnosis and overtreatment of prostate cancer (CaP) associated with prostate-specific antigen (PSA) based screening. However, technical limitations in the conventional diffusion-weighted imaging (DWI) sequences as well as the high degree of radiologist-to-radiologist variability in interpreting prostate MRI result in inadequate accuracy. Specifically, the insufficient negative predictive value (NPV) of prostate MRI (76%-87%) does not allow biopsy to be omitted in the negative MRI setting. Additionally, the variable, and relatively low positive predictive value (PPV) of MRI (27%-44%) provides only an incremental improvement in risk prediction compared to readily available clinical tools such as the Prostate Cancer Prevention Trial risk calculator. This small benefit is likely confined to the minority of patients with positive MRI findings in a typically under-sampled region of the prostate (e.g., anterior lesions), which may be obviated by newer biopsy approaches and tools such as transperineal prostate biopsy and micro-ultrasound technology. With these considerations in mind, pre-biopsy prostate MRI in its current form is unlikely to provide a clinically significant benefit, and should not be considered as routine practice until its accuracy is sufficiently improved.

Prostate Health Index Density Outperforms Prostate Health Index in Clinically Significant Prostate Cancer Detection

Background

Prostate-specific antigen (PSA) is considered neither sensitive nor specific for prostate cancer (PCa). We aimed to compare total PSA (tPSA), percentage of free PSA (%fPSA), the PSA density (PSAD), Prostate Health Index (PHI), and the PHI density (PHID) to see which one could best predict clinically significant prostate cancer (csPCa): a potentially lethal disease.

Methods

A total of 412 men with PSA of 2-20 ng/mL were prospectively included. Serum biomarkers for PCa was collected before transrectal ultrasound guided prostate biopsy. PHI was calculated by the formula: (p2PSA/fPSA) x √tPSA. PHID was calculated as PHI divided by prostate volume measured by transrectal ultrasound.

Results

Of the 412 men, 134 (32.5%) and 94(22.8%) were diagnosed with PCa and csPCa, respectively. We used the area under the receiver operating characteristic curve (AUC) and decision curve analyses (DCA) to compare the performance of PSA related parameters, PHI and PHID in diagnosing csPCa. AUC for tPSA, %fPSA, %p2PSA, PSAD, PHI and PHID were 0.56、0.63、0.76、0.74、0.77 and 0.82 respectively for csPCa detection. In the univariate analysis, the prostate volume, tPSA, %fPSA, %p2PSA, PHI, PSAD, and PHID were all significantly associated with csPCa, and PHID was the most important predictor (OR 1.41, 95% CI 1.15-1.72). Besides, The AUC of PHID was significantly larger than PHI in csPCa diagnosis (p=0.004). At 90% sensitivity, PHID had the highest specificity (54.1%) for csPCa and could reduce the most unnecessary biopsies (43.7%) and miss the fewest csPCa (8.5%) when PHID ≥ 0.67. In addition to AUC, DCA re-confirmed the clinical benefit of PHID over all PSA-related parameters and PHI in csPCa diagnosis. The PHID cut-off value was positively correlated with the csPCa ratio in the PHID risk table, which is useful for evaluating csPCa risk in a clinical setting.

Conclusion

The PHID is an excellent predictor of csPCa. The PHID risk table may be used in standard clinical practice to pre-select men at the highest risk of harboring csPCa.

ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate

Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observer variability across radiologists, thereby contributing to missed clinically significant cancers, overdiagnosed low-risk cancers, and frequent false positives. Interpretation of MRI could be greatly improved by providing radiologists with an answer key that clearly shows cancer locations on MRI. Registration of histopathology images from patients who had radical prostatectomy to pre-operative MRI allows such mapping of ground truth cancer labels onto MRI. However, traditional MRI-histopathology registration approaches are computationally expensive and require careful choices of the cost function and registration hyperparameters. This paper presents ProsRegNet, a deep learning-based pipeline to accelerate and simplify MRI-histopathology image registration in prostate cancer. Our pipeline consists of image preprocessing, estimation of affine and deformable transformations by deep neural networks, and mapping cancer labels from histopathology images onto MRI using estimated transformations. We trained our neural network using MR and histopathology images of 99 patients from our internal cohort (Cohort 1) and evaluated its performance using 53 patients from three different cohorts (an additional 12 from Cohort 1 and 41 from two public cohorts). Results show that our deep learning pipeline has achieved more accurate registration results and is at least 20 times faster than a state-of-the-art registration algorithm. This important advance will provide radiologists with highly accurate prostate MRI answer keys, thereby facilitating improvements in the detection of prostate cancer on MRI. Our code is freely available at https://github.com/pimed//ProsRegNet.

The role of multiparametric MRI in active surveillance for low-risk prostate cancer: The ROMAS randomized controlled trial

BACKGROUND

We aim to evaluate the impact of multiparametric magnetic resonance imaging and fusion-target biopsy for early reclassification of patients with low-risk Prostate Cancer in a randomized trial.

MATERIALS AND METHODS

Between 2015 and 2018, patients diagnosed with Prostate Cancer after random biopsy fulfilling PRIAS criteria were enrolled and centrally randomized (1:1 ratio) to study group or control group. Patients randomized to study group underwent multiparametric magnetic resonance imaging at 3 months from enrollment: patients with positive findings (PIRADS-v2>2) underwent fusion-target biopsy; patients with negative multiparametric magnetic resonance imaging or confirmed ISUP - Grade Group 1 at fusion-target biopsy were managed according to PRIAS schedule and 12-core random biopsy was performed at 12 months. Patients in control group underwent PRIAS protocol, including a confirmatory 12-core random biopsy at 12 months. Primary endpoint was a reduction of reclassification rate at 12-month random biopsy in study group at least 20% less than controls. Reclassification was defined as biopsy ISUP Grade Group 1 in >2 biopsy cores or disease upgrading.

RESULTS

A total of 124 patients were randomized to study group (n = 62) or control group (n = 62). Around 21 of 62 patients (34%) in study group had a positive multiparametric magnetic resonance imaging, and underwent fusion-target biopsy, with 11 (17.7%) reclassifications. Considering the intention-to-treat population, reclassification rate at 12-month random biopsy was 6.5% for study group and 29% for control group, respectively (P < 0.001).

CONCLUSIONS

The early employment of multiparametric magnetic resonance imaging for active surveillance patients enrolled after random biopsy consents to significantly reduce reclassifications at 12-month random biopsy.