Risk stratification and avoiding overtreatment in localized prostate cancer

Standardized template for clinical reporting of PSMA PET/CT scans

PURPOSE

Accurate diagnosis and staging of prostate cancer are crucial to improving patient care. Prostate-specific membrane antigen (PSMA)-targeted positron emission tomography with computed tomography (PET/CT) imaging has demonstrated superiority for initial staging and restaging in patients with prostate cancer. Referring physicians and PET/CT readers must agree on a consistent communication method and application of information derived from this imaging modality. While several guidelines have been published, a single PSMA PET/CT reporting template has yet to be widely adopted. Based on the consensus from community and academic physicians, we developed a standardized PSMA PET/CT reporting template for radiologists and nuclear medicine physicians to report and relay key imaging findings to referring physicians. The aim was to improve the quality, clarity, and utility of imaging results reporting to facilitate patient management decisions.

METHODS

Based on community and expert consensus, we developed a standardized PSMA PET/CT reporting template to deliver key imaging findings to referring clinicians.

RESULTS

Core category components proposed include a summary of any prior treatment history; presence, location, and degree of PSMA radiopharmaceutical uptake in primary and/or metastatic tumor(s), lesions with no uptake, and incidentally found lesions with positive uptake on PET/CT.

CONCLUSIONS

This article provides recommendations on best practices for standardized reporting of PSMA PET/CT imaging. The generated reporting template is a proposed supplement designed to educate and improve data communication between imaging experts and referring physicians.

Clinical Validation of Multiparametric Ultrasound for Detecting Clinically Significant Prostate Cancer Using Computer-Aided Diagnosis: A Direct Comparison with the Magnetic Resonance Imaging Pathway

We present the protocol for a study testing the hypothesis that a computer-aided diagnosis (CAD) system for three-dimensional multiparametric ultrasound (3D mpUS) is noninferior to magnetic resonance imaging (MRI) in guiding prostate biopsies for detection of clinically significant prostate cancer (csPCa). The prospective study has a fully paired design for assessment of diagnostic accuracy and is registered on ClinicalTrials.gov as NCT06281769. A total of 438 biopsy-naïve men scheduled for prostate MRI evaluation because of an abnormal digital rectal examination and/or elevated serum prostate-specific antigen will be included. All patients will undergo both MRI (multiparametric or biparametric) and 3D mpUS with CAD (PCaVision). Suspicious lesions will be independently identified using each imaging technique. MRI targeted biopsy (TBx) and/or PCaVision TBx will be performed if suspicious lesions are identified on imaging. When both PCaVision and MRI identify lesions in an individual patient, the TBx order for this patient will be randomized. Three TBx samples per lesion will be taken for a maximum of two lesions per modality. The primary objective is the detection rate for csPCa (International Society of Urological Pathology grade group [GG] ≥2) with the PCaVision versus the MRI TBx pathway. The noninferiority margin for the absolute difference in detection rates is set at a difference of 5%. Secondary outcomes are the proportion of men in whom TBx could have been safely omitted in each pathway. Additional diagnostic accuracy analyses will be performed for different definitions of PCa (GG ≥3; GG ≥2 with cribriform growth and/or intraductal carcinoma; and GG 1). The frequency of insufficient image quality for the two pathways will also be assessed. Lastly, we will determine the diagnostic performance for csPCa detection at various 3D mpUS image quality thresholds for PCaVision.

Regulatory and memory T lymphocytes infiltrating prostate tumors predict long term clinical outcomes

Introduction

The localization, density but mostly the phenotype of tumor infiltrating lymphocytes (TIL) provide important information on the initial interaction between the host immune system and the tumor. Our objective was to assess the prognostic significance of T (CD3+), T regulatory (Treg) (FoxP3+) and T memory (Tmem) (CD45RO+) infiltrating lymphocytes and of genes associated with TIL in prostate cancer (PCa).

Methods

Immunohistochemistry (IHC) was used to assess the infiltration of CD3+, FoxP3+ and CD45RO+ cells in the tumor area, tumor margin and adjacent normal-like epithelium of a series of 98 PCa samples with long clinical follow-up. Expression of a panel of 31 TIL-associated genes was analyzed by Taqman Low-Density Array (TLDA) technology in another series of 50 tumors with long clinical follow-up. Kaplan-Meier and Cox proportional hazards regression analyses were performed to determine association of these markers with biochemical recurrence (BCR), need for definitive androgen deprivation therapy (ADT) or lethal PCa.

Results

TIL subtypes were present at different densities in the tumor, tumor margin and adjacent normal-like epithelium, but their density and phenotype in the tumor area were the most predictive of clinical outcomes. In multivariate analyses, a high density of Treg (high FoxP3+/CD3+ cell ratio) predicted a higher risk for need of definitive ADT (HR=7.69, p=0.001) and lethal PCa (HR=4.37, p=0.04). Conversely, a high density of Tmem (high CD45RO+/CD3+ cell ratio) predicted a reduced risk of lethal PCa (HR=0.06, p=0.04). TLDA analyses showed that a high expression of FoxP3 was associated with a higher risk of lethal PCa (HR=5.26, p=0.02). Expression of CTLA-4, PD-1, TIM-3 and LAG-3 were correlated with that of FoxP3. Amongst these, only a high expression of TIM-3 was associated with a significant higher risk for definitive ADT in univariate Cox regression analysis (HR=3.11, p=0.01).

Conclusion

These results show that the proportion of Treg and Tmem found within the tumor area is a strong and independent predictor of late systemic progression of PCa. Our results also suggest that inhibition of TIM-3 might be a potential approach to counter the immunosuppressive functions of Treg in order to improve the anti-tumor immune response against PCa.

PI-RADS Version 2.0 Versus Version 2.1: Comparison of Prostate Cancer Gleason Grade Upgrade and Downgrade Rates From MRI-Targeted Biopsy to Radical Prostatectomy

BACKGROUND. Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. OBJECTIVE. The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and downgrade from TBx to radical prostatectomy (RP). METHODS. This study entailed a retrospective post hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of three prospective clinical trials. Trial participants who underwent MRI followed by MRI/US fusion-guided TBx and RP within a 1-year interval were identified. A single genitourinary radiologist performed clinical interpretations of the MRI examinations using PI-RADS v2.0 from May 2015 to March 2019 and PI-RADS v2.1 from April 2019 to March 2023. Upgrade and downgrade rates from TBx to RP were compared using chi-square tests. Clinically significant cancer was defined as ISUP GG2 or greater. RESULTS. The final analysis included 308 patients (median age, 65 years; median PSA density, 0.16 ng/mL2). The v2.0 group (n = 177) and v2.1 group (n = 131) showed no significant difference in terms of upgrade rate (29% vs 22%, respectively; p = .15), downgrade rate (19% vs 21%, p = .76), clinically significant upgrade rate (14% vs 10%, p = .27), or clinically significant downgrade rate (1% vs 1%, p > .99). The upgrade rate and downgrade rate were also not significantly different between the v2.0 and v2.1 groups when stratifying by index lesion PI-RADS category or index lesion zone, as well as when assessed only in patients without a prior PCa diagnosis (all p > .01). Among patients with GG2 or GG3 at RP (n = 121 for v2.0; n = 103 for v2.1), the concordance rate between TBx and RP was not significantly different between the v2.0 and v2.1 groups (53% vs 57%, p = .51). CONCLUSION. Upgrade and downgrade rates from TBx to RP were not significantly different between patients whose MRI examinations were clinically interpreted using v2.0 or v2.1. CLINICAL IMPACT. Implementation of the most recent PI-RADS update did not improve the incongruence in PCa grade assessment between TBx and surgery.

Incorporating VR-RENDER Fusion Software in Robot-Assisted Partial Prostatectomy: The First Case Report

Currently, the active surveillance of men with favorable intermediate-risk localized prostate cancer (PCa) is a longstanding controversy, in terms of their oncological outcomes, and radical prostatectomy would constitute a similar concern of overtreatment, regarding its functional outcomes. Thus, focal therapy could be considered in men belonging to favorable intermediate-risk group. Among all focal therapies, high-intensity focused ultrasound (HIFU) was the most studied methodology in clinical trials. Although HIFU provided better functional outcomes than radical prostatecomy, the oncological outcomes were inferior in men with intermediate-risk localized PCa. Two articles have been published discussing the feasibility and clinical outcomes of robot-assisted partial prostatectomy (RAPP), and both the functional and oncological outcomes were superior than those with HIFU. However, the rate of positive surgical margins (PSMs) was reported as high in the literature. Here, we present a case of favorable intermediate-risk localized PCa with an isolated tumor at the anterior apex. After reconstructing a personal three-dimensional (3D) image, we utilized it in a 3D image-guided precise excise, followed by intraoperative frozen specimen review. We found that this method may present a resolution to the high PSM rate documented in the current literature regarding RAPP. This method merits further study with a well-designed prospective study.

Trends in primary treatment for localized prostate cancer according to the availability of treatment modalities and the impact of introducing robotic surgery

OBJECTIVES

We aimed to investigate the effect of available treatment modalities on primary treatment selection in patients with localized prostate cancer and that of introducing robotic surgery.

METHODS

We retrospectively studied 12 061 patients diagnosed with localized prostate cancer between 2004 and 2018 from 21 institutions. These institutions were divided into five groups according to the availability of surgery and radiotherapy. Differences in primary treatment selection between the institutions were investigated, and the predictive factors involved in the selection were explored.

RESULTS

Surgery, radiotherapy, androgen deprivation therapy, and active surveillance/watchful waiting were selected as primary treatment in 4115, 3621, 3188, and 821 patients, respectively, while the remaining 316 patients selected other modalities. The number of patients, particularly young patients, was much higher in institutions with both surgery and radiotherapy. With the introduction of robotic surgery, open radical prostatectomy has decreased, and robotic surgery made up approximately 70% of all prostatectomies. Institutions with both surgery and radiotherapy tended to treat patients with very low or low risk by surgery or radiotherapy, while institutions without surgery and radiotherapy tended to select active surveillance or watchful waiting. Multivariate analysis revealed that primary treatment selection for prostate cancer was affected not only by clinical factors, but also by the available modalities in each institution.

CONCLUSIONS

Differences in available treatment modalities affect the selection of primary treatment for localized prostate cancer. Introduction of robotic surgery also has a strong influence on the number of patients in each institution.

Diverse PSMA expression in primary prostate cancer: reason for negative [68Ga]Ga-PSMA PET/CT scans? Immunohistochemical validation in 40 surgical specimens

PURPOSE

The purpose of this study was to immunohistochemically validate the primary tumor PSMA expression in prostate cancer (PCa) patients imaged with [⁶⁸Ga]Ga-PSMA PET/CT prior to surgery, with special consideration of PET-negative cases.

METHODS

The study included 40 men with newly diagnosed treatment-naïve PCa imaged with [⁶⁸Ga]Ga-PSMA I&T PET/CT as part of the diagnostic work-up prior to radical prostatectomy. All primary tumors were routinely stained with H&E. In addition, immunohistochemical staining of PSMA was performed and the immunoreactive score (IRS) was computed as semiquantitative measure. Subsequently, imaging findings were correlated to histopathologic results.

RESULTS

Eighty-three percent (33/40) of patients presented focal uptake of [⁶⁸Ga]Ga-PSMA I&T in the primary tumor in at least one prostate lobe. Among PSMA-PET positive patients, one-third had lymph node metastases (LNM) detected by post-operative histopathology, while in PET negative patients, only 1 out of 7 presented with regional LN involvement; PSMA-avid distant lesions, predominantly in bones, were observed in 15% and 0% of patients, respectively. The median IRS classification of PSMA expression in tumor tissue was 2 (range, 1-3) both in PSMA-PET positive and negative prostate lobes, with significantly different interquartile range: 2-3 vs. 2-2, respectively (p = 0.03). The median volume of PSMA-PET positive tumors was 5.4 mL (0.2-32.9) as compared to 1.6 mL (0.3-18.3) of PET-negative tumors (p < 0.001). There was a significant but weak correlation between SUV_max and percentage of PSMA-positive tumor cells (r = 0.46, p < 0.001). A total of 35/44 (~80%) lobes were positive in PSMA-PET imaging, when a cut-off percentage of PSMA-positive cells was ≥ 90%, while 19/36 (~53%) lobes with < 90% PSMA-positive cells were PSMA-PET negative.

CONCLUSION

Positive [⁶⁸Ga]Ga-PSMA I&T PET/CT scan of primary tumor of PCa results from a combination of factors, such as homogeneity and intensity of PSMA expression, tumor volume and grade, with a cutoff value of ≥ 90% PSMA-positive cells strongly determining PET-positivity. Focal accumulation of [⁶⁸Ga]Ga-PSMA in the primary tumor may correlate positively with aggressiveness of prostate cancer, harboring higher risk of regional LN involvement and distant metastatic spread.

Use of TDI during MRI/US fusion-guided biopsy for suspected prostate cancer

BACKGROUND

Tissue Doppler imaging (TDI) uses the Doppler principle to quantify the movement of biological tissues.

OBJECTIVE

To investigate the contribution of TDI parameters derived during magnetic resonance imaging and ultrasound (MRI/US) fusion-guided biopsy for prostate cancer (PCa) discrimination.

METHODS

From March 2016 to Dec. 2018, 75 men with suspected PCa prospectively underwent fusion-guided prostate biopsy. TDI overlaid on predefined target lesion were compared to the confirmed contralateral tumor-free area of the prostate gland (using Image J). Diagnostic value of TDI parameters was assessed using histopathology as standard of reference.

RESULTS

Thirty-seven patients were diagnosed with PCa (49.3%), among them 27 with clinically significant PCa (Gleason score >  3 + 3 = 6 (ISUP 1). The LES/REF ratio was lower in confirmed PCa patients compared to patients without PCa (0.42, IQR, 0.22-0.59 vs. 0.52, IQR, 0.40-0.72, p = 0.017). TDI parameters allowed differentiation of low-risk from high-to-intermediate-risk PCa (ISUP 2 versus ISUP 3) based on lower pixel counts within the target ROI (1340, IQR 596-2430 vs. 2687, IQR 2453-3216, p = 0.004), lower pixel percentage (16.4 IQR 11.4-29.5 vs. 27.3, IQR 22.1-39.5; p = 0.005), and lower LES/REF ratios (0.29, IQR 0.19-0.51 vs. 0.52, IQR 0.47-0.74, p = 0.001).

CONCLUSION

TDI of prostate lesions prelocated by MRI discriminates between cancerous and noncancerous lesions and further seems to enable characterization of PCa aggressiveness. This widely available US technique may improve confidence in target lesion localization for tissue sampling.

Prediction of Pathological Upgrading at Radical Prostatectomy in Prostate Cancer Eligible for Active Surveillance: A Texture Features and Machine Learning-Based Analysis of Apparent Diffusion Coefficient Maps

Objective

To evaluate a combination of texture features and machine learning-based analysis of apparent diffusion coefficient (ADC) maps for the prediction of Grade Group (GG) upgrading in Gleason score (GS) ≤6 prostate cancer (PCa) (GG1) and GS 3 + 4 PCa (GG2).

Materials and methods

Fifty-nine patients who were biopsy-proven to have GG1 or GG2 and underwent MRI examination with the same MRI scanner prior to transrectal ultrasound (TRUS)-guided systemic biopsy were included. All these patients received radical prostatectomy to confirm the final GG. Patients were divided into training cohort and test cohort. 94 texture features were extracted from ADC maps for each patient. The independent sample t-test or Mann−Whitney U test was used to identify the texture features with statistically significant differences between GG upgrading group and GG non-upgrading group. Texture features of GG1 and GG2 were compared based on the final pathology of radical prostatectomy. We used the least absolute shrinkage and selection operator (LASSO) algorithm to filter features. Four supervised machine learning methods were employed. The prediction performance of each model was evaluated by area under the receiver operating characteristic curve (AUC). The statistical comparison between AUCs was performed.

Results

Six texture features were selected for the machine learning models building. These texture features were significantly different between GG upgrading group and GG non-upgrading group (P < 0.05). The six features had no significant difference between GG1 and GG2 based on the final pathology of radical prostatectomy. All machine learning methods had satisfactory predictive efficacy. The diagnostic performance of nearest neighbor algorithm (NNA) and support vector machine (SVM) was better than random forests (RF) in the training cohort. The AUC, sensitivity, and specificity of NNA were 0.872 (95% CI: 0.750−0.994), 0.967, and 0.778, respectively. The AUC, sensitivity, and specificity of SVM were 0.861 (95%CI: 0.732−0.991), 1.000, and 0.722, respectively. There had no significant difference between AUCs in the test cohort.

Conclusion

A combination of texture features and machine learning-based analysis of ADC maps could predict PCa GG upgrading from biopsy to radical prostatectomy non-invasively with satisfactory predictive efficacy.

Combined systematic versus stand-alone multiparametric MRI-guided targeted fusion biopsy: nomogram prediction of non-organ-confined prostate cancer

OBJECTIVE

Based on unfavorable oncological and functional outcomes of non-organ-confined (NOC) prostate cancer (PCa), defined as ≥ pT3, pN1 or both, we aimed to develop a NOC prediction tool based on multiparametric MRI-guided targeted fusion biopsy (TBx).

MATERIALS AND METHODS

Analyses were restricted to 594 patients with simultaneous PCa detection at systematic biopsy (SBx), TBx and subsequent radical prostatectomy (RP) at our institution. Development (n = 396; cohort 1) and validation cohorts (n = 198; cohort 2) were used to develop and validate the NOC nomogram. A head-to-head comparison was performed between stand-alone TBx model and combined TBx/SBx model. Second validation was performed in patients with positive TBx, but negative SBx (n = 193; cohort 3).

RESULTS

The most parsimonious TBx model included three independent predictors of NOC: pretreatment PSA (OR 1.05 95% CI: 1.01-1.08), highest TBx-detected Gleason pattern (3 + 3 [REF] vs. ≥ 4 + 5; OR 9.3 95% CI 3.8-22) and presence of TBx-detected perineural invasion (OR 2.2 95% CI: 1.3-3.6). The combined TBx/SBx model had the same predictors. For the stand-alone TBx and combined TBx/SBx model, external validation yielded accuracy of 76.5% (95% CI: 69.3-83.1) and 76.6% (95% CI: 69.4-83.6) within cohort 2. The external validation of the stand-alone TBx model yielded 72.4% (95% CI: 65.0-79.6) accuracy within cohort 3.

CONCLUSION

Our stand-alone TBx-based nomogram can identify PCa patients at the risk of NOC, using three simple variables, with the similar accuracy as the TBx/SBx-based model. It is non-inferior to combined TBx/SBx-based model and performs with sufficient accuracy in specific patients with positive TBx, but negative SBx.