Should reporting of peri-neural invasion and extra prostatic extension be mandatory in prostate cancer biopsies? correlation with outcome in biopsy cases treated conservatively

Predicting Tumor Perineural Invasion Status in High-Grade Prostate Cancer Based on a Clinical-Radiomics Model Incorporating T2-Weighted and Diffusion-Weighted Magnetic Resonance Images

PURPOSE

To explore the role of bi-parametric MRI radiomics features in identifying PNI in high-grade PCa and to further develop a combined nomogram with clinical information.

METHODS

183 high-grade PCa patients were included in this retrospective study. Tumor regions of interest (ROIs) were manually delineated on T2WI and DWI images. Radiomics features were extracted from lesion area segmented images obtained. Univariate logistic regression analysis and the least absolute shrinkage and selection operator (LASSO) method were used for feature selection. A clinical model, a radiomics model, and a combined model were developed to predict PNI positive. Predictive performance was estimated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves.

RESULTS

The differential diagnostic efficiency of the clinical model had no statistical difference compared with the radiomics model (area under the curve (AUC) values were 0.766 and 0.823 in the train and test group, respectively). The radiomics model showed better discrimination in both the train cohort and test cohort (train AUC: 0.879 and test AUC: 0.908) than each subcategory image (T2WI train AUC: 0.813 and test AUC: 0.827; DWI train AUC: 0.749 and test AUC: 0.734). The discrimination efficiency improved when combining the radiomics and clinical models (train AUC: 0.906 and test AUC: 0.947).

CONCLUSION

The model including radiomics signatures and clinical factors can accurately predict PNI positive in high-grade PCa patients.

The Role of Perineural Invasion in Prostate Cancer and Its Prognostic Significance

Simple Summary

Prostate cancer is one of the most frequently diagnosed cancers in men worldwide. Perineural invasion (PNI), the movement of cancer cells along nerves, is a commonly observed approach to tumor spread and is important in both research and clinical practice of prostate cancer. However, despite many studies reporting on molecules and pathways involved in PNI, understanding its clinical relevance remains insufficient. In this review, we aim to summarize the current knowledge of mechanisms and prognostic significance of PNI in prostate cancer, which may provide new perspectives for future studies and improved treatment.

Abstract

Perineural invasion (PNI) is a common indication of tumor metastasis that can be detected in multiple malignancies, including prostate cancer. In the development of PNI, tumor cells closely interact with the nerve components in the tumor microenvironment and create the perineural niche, which provides a supportive surrounding for their survival and invasion and benefits the nerve cells. Various transcription factors, cytokines, chemokines, and their related signaling pathways have been reported to be important in the progress of PNI. Nevertheless, the current understanding of the molecular mechanism of PNI is still very limited. Clinically, PNI is commonly associated with adverse clinicopathological parameters and poor outcomes for prostate cancer patients. However, whether PNI could act as an independent prognostic predictor remains controversial among studies due to inconsistent research aim and endpoint, sample type, statistical methods, and, most importantly, the definition and inclusion criteria. In this review, we provide a summary and comparison of the prognostic significance of PNI in prostate cancer based on existing literature and propose that a more standardized description of PNI would be helpful for a better understanding of its clinical relevance.

The association between perineural invasion in mpMRI-targeted and/or systematic prostate biopsy and adverse pathological outcomes in robot-assisted radical prostatectomy

INTRODUCTION AND OBJECTIVES

This study aims to investigate the relationship between perineural invasion (PNI) in targeted (TBx) and/or systematic (SBx) prostate needle biopsy and adverse pathological features of prostate cancer (PCa) in prostatectomy specimens.

MATERIALS AND METHODS

A total of 95 male patients who underwent transperineal TBx and/or concomitant SBx subsequently treated with robot-assisted radical prostatectomy for PCa between October 2015 and June 2020 were included. The performance of PNI as a classification test (sensitivity, specificity, positive and negative predictive values) and its correlation with clinically significant PCa, surgical margin positivity, extraprostatic extension, and seminal vesicle invasion in prostatectomy were computed.

RESULTS

The median age of the patients was 65 (60-70) years. TBx and concomitant SBx were performed in 78 (82.1%) patients, while 16 (16.8%) patients underwent SBx alone and one (1.1%) patient underwent TBx alone. The frequency of PNI in TBx and SBx was 17 (21.5%) and 32 (34.0%), respectively. The specificity/negative predictive values of PNI for surgical margin positivity, extraprostatic extension, and seminal vesicle invasion were 79.7/88.7%, 92.5/79.0%, and 83.3/96.8%, in TBx, and 71.1/87.1%, 80.7/74.2%, and 69.5/91.9%, in SBx, respectively. There was also a statistically significant correlation between PNI in biopsy and surgical margin positivity, extraprostatic extension, and seminal vesicle invasion in prostatectomy as well as the ISUP grade group and pT stage.

CONCLUSIONS

The absence of PNI in prostate needle biopsy may predict localized PCa with a pT stage ≤ 2c and negative surgical margins in contrast to its presence which appears to be an indicator of unfavorable factors in final pathology.

Efficient Perineural Invasion Detection of Histopathological Images Using U-Net

Perineural invasion (PNI), a sign of poor diagnosis and tumor metastasis, is common in a variety of malignant tumors. The infiltrating patterns and morphologies of tumors vary by organ and histological diversity, making PNI detection difficult in biopsy, which must be performed manually by pathologists. As the diameters of PNI nerves are measured on a millimeter scale, the PNI region is extremely small compared to the whole pathological image. In this study, an efficient deep learning-based method is proposed for detecting PNI regions in multiple types of cancers using only PNI annotations without detailed segmentation maps for each nerve and tumor cells obtained by pathologists. The key idea of the proposed method is to train the adopted deep learning model, U-Net, to capture the boundary regions where two features coexist. A boundary dilation method and a loss combination technique are proposed to improve the detection performance of PNI without requiring full segmentation maps. Experiments were conducted with various combinations of boundary dilation widths and loss functions. It is confirmed that the proposed method effectively improves PNI detection performance from 0.188 to 0.275. Additional experiments were also performed on normal nerve detection to validate the applicability of the proposed method to the general boundary detection tasks. The experimental results demonstrate that the proposed method is also effective for general tasks, and it improved nerve detection performance from 0.511 to 0.693.

Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies

Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67–0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization.

Impact of uni- or multifocal perineural invasion in prostate cancer at radical prostatectomy

Background

Aim of this study was to correlate perineural invasion (PNI) with other clinical-pathological parameters in terms of prognostic indicators in prostate cancer (PC) cases at the time of radical prostatectomy (RP).

Methods

Prospective study of 288 consecutive PC cases undergoing RP. PNI determination was performed either in biopsy or in RP specimens classifying as uni- and multifocal PNI. The median follow-up time was 22 (range, 6-36) months.

Results

At biopsy PNI was found in 34 (11.8%) cases and in 202 (70.1%) cases at the time of surgery. Among those identified at RP 133 (46.1%) and 69 (23.9%) cases had uni- and multi-PNI, respectively. Presence of PNI was significantly (P<0.05) correlated with unfavorable pathological parameters such higher stage and grade. The percentage of extracapsular extension in PNI negative RP specimens was 18.6% vs. 60.4% of PNI positive specimens. However, the distribution of pathological staging and International Society of Urological Pathology (ISUP) grading did not vary according to whether PNI was uni- or multifocal. The risk of biochemical progression increased 2.3 times in PNI positive cases was significantly associated with the risk of biochemical progression (r=0.136; P=0.04). However, at multivariate analysis PNI was not significantly associated with biochemical progression [hazard ratio (HR): 1.87, 95% confidence interval (CI): 0.68-3.12; P=0.089]. Within patients with intermediate risk disease, multifocal PNI was able to predict cases with lower mean time to biochemical and progression free survival (chi-square 5.95; P=0.04).

Conclusions

PNI at biopsy is not a good predictor of the PNI incidence at the time of RP. PNI detection in surgical specimens may help stratify intermediate risk cases for the risk of biochemical progression.

Perineural invasion in prostate needle biopsy: Prognostic value on radical prostatectomy and active surveillance

PURPOSE

The aim of this study was to evaluate the clinical impact of perineural invasion (PNI) in prostate biopsy in patients submitted to radical prostatectomy and on active surveillance (AS).

MATERIALS AND METHODS

We performed a single center, retrospective, cohort study on patients diagnosed with clinically localized prostate cancer and submitted to radical prostatectomy between January 2010 and December 2016. We evaluated clinical and anatomopathological characteristics from the biopsy and radical prostatectomy specimen and correlated with biochemical recurrence (BCR) using a survival analysis. We also evaluated the impact of PNI in patients with criteria for active surveillance.

RESULTS

The cohort analyzed consists of 107 patients, with a mean age of 63.1 years and a mean PSA prior to biopsy of 7.8 ng/ml. In prostate biopsy, 66.4% of the patients had a Gleason score of 6, 30.9% had a Gleason score of 7, and 2.7% had a Gleason score of 8 or higher, with PNI being detected in 57 (53.3%) of the patients. Regarding the anatomopathological characteristics of the surgical specimen, invasion of the seminal vesicles was observed in 6.5%, lymph nodes involvement in 9.3% and positive surgical margins in 27.1% of the cases. During follow-up, BCR was recorded in 24.3% of cases. Clinicopathological features were stratified according to the presence or absence of PNI, with statistical significance in relation to the Gleason Score (p = 0.001), pathologic T stage (p = 0.001), D'Amico risk (p = 0.002) and upstaging of the Gleason score (p = 0.045). The survival analysis revealed a relationship between PNI and BCR (hazard ratio = 2.98; 95% CI: 1.36-6.58; p = 0.007). Regarding the men potentially eligible for AS, the presence of PNI on the biopsy presented a significant relation with Gleason upgrade (p = 0.004) and extraprostatic extension (p = 0.017).

CONCLUSIONS

The presence of PNI in prostate biopsy is related to adverse anatomopathological factors, being a potential predictor of BCR and have a possible role in the selection of patients for AS.

Perineural invasion on biopsy specimen as predictor of tumor progression in aging male treated with radical prostatectomy. Could we use it for pre-surgical screening?

We aimed to analyze the correlation of perineural invasion on transrectal ultrasound guided prostate biopsy with predictors of biochemical cancer recurrence, as well as its impact on clinical outcomes, for non-metastatic prostate cancer. For the study, patients with perineural invasion (N = 86) were recruited into group I and underwent open retropubic prostatectomy, regardless of clinical stage; cases with prostate cancer but without perineural invasion on biopsy, who received radical prostatectomy as the treatment modality, were placed into group II (n = 90). Perineural invasion was detected preoperatively in 43% of cases that revealed surgical margin positivity postoperatively, while 85% of the remaining cases (group II) had negative surgical margins. There was no correlation on prostate biopsy between perineural invasion and Gleason score or PSA, based on Sperman's rank-order correlation analysis. However, there was strong positive correlation of perineural invasion with clinical stage and patients age. Additionaly, we demonstrated that perineural invasion on biopsy is a non-independent risk factor for metastatic occurrence, although the correlation was significant in univariate analysis. Nevertheless, we found strong correlation between invasion on initial biopsy specimen with biochemical cancer recurrence, suggesting that perineural invasion on prostate biopsy is a significant predictor of worse prognostic outcome.

Perineural invasion by prostate adenocarcinoma in needle biopsies predicts bone metastasis: Ten year data from the TROG 03.04 RADAR Trial

AIMS

Perineural invasion (PNI) by prostatic adenocarcinoma is debated as a prognostic parameter. This study investigates the prognostic predictive value of PNI in a series of patients with locally advanced prostate cancer treated with radiotherapy and androgen deprivation using 10 years outcome data from the TROG 03.04 RADAR trial.

METHODS

Diagnostic prostate biopsies from 976 patients were reviewed and the presence of PNI noted. Patients were followed for 10 years according to the trial protocol or until death. The primary endpoint for the study was time to bone metastasis. Secondary endpoints included time to soft tissue metastasis, transition to castration resistance, prostate cancer-specific mortality and all-cause mortality.

RESULTS

PNI was detected in 449 cases (46%), with 234 cases (24%) having PNI in more than one core. The presence of PNI was significantly associated with higher ISUP grade, clinical T staging category, National Comprehensive Cancer Network risk group, and percent positive biopsy cores. The cumulative probability of bone metastases according to PNI status was significant over the 10 years follow-up interval of the study (log-rank test P < 0.0001). PNI was associated with all endpoints on univariable analysis. After adjusting for baseline clinicopathological and treatment factors, bone metastasis was the only endpoint in which PNI retained its prognostic significance (hazard ratio 1.42, 95% confidence interval 1.05-1.92, P = 0.021).

CONCLUSIONS

The association between PNI and the development of bone metastases supports the inclusion of this parameter as a component of the routine histology report. Further this association suggests that evaluation of PNI may assist in selecting those patients who should be monitored more closely during follow-up.

Tumour innervation and neurosignalling in prostate cancer

Prostate cancer progression has been shown to be dependent on the development of autonomic nerves into the tumour microenvironment. Sympathetic nerves activate adrenergic neurosignalling that is necessary in early stages of tumour progression and for initiating an angiogenic switch, whereas parasympathetic nerves activate cholinergic neurosignalling resulting in tumour dissemination and metastasis. The innervation of prostate cancer seems to be initiated by neurotrophic growth factors, such as the precursor to nerve growth factor secreted by tumour cells, and the contribution of brain-derived neural progenitor cells has also been reported. Current experimental, epidemiological and clinical evidence shows the stimulatory effect of tumour innervation and neurosignalling in prostate cancer. Using nerves and neurosignalling could have value in the management of prostate cancer by predicting aggressive disease, treating localized disease through denervation and relieving cancer-associated pain in bone metastases.

Impact of biopsy perineural invasion on the outcomes of patients who underwent radical prostatectomy: a systematic review and meta-analysis

Objectives: To investigate the association between biopsy perineural invasion (PNI) and oncological outcomes of prostate cancer (PCa) after radical prostatectomy (RP).Materials and methods: A systematic literature search was performed using PubMed, EMBASE and Web of Science up to December 2018 to identify the eligible studies that included localized PCa patients who underwent biopsy and subsequently RP as well as follow-up information. Meta-analyses were conducted using available hazard ratios (HRs) of biopsy PNI from both univariate and multivariate analyses.Results: Eighteen studies including 14,855 patients with treatment follow-up information were included in the current systematic review. The rate of biopsy PNI varied between 7.0% and 33.0%. Seven out of the 18 studies that demonstrated biopsy PNI were associated with adverse pathologic features. Thirteen out of the 18 studies showed biopsy PNI correlated significantly with higher rates of biochemical recurrence (BCR)/cancer progression status or worse prognostic outcomes. With pooled data based on four studies with available univariate analysis results and four studies with multivariate analysis, statistically significant associations were found between biopsy PNI and BCR with univariate analysis (HR = 2.05; 95% CI = 1.57-2.68; p < 0.001) and with multivariate analysis (HR = 1.57; 95% CI = 1.28-1.93; p < 0.001).Conclusion: Evidence from the included observational studies indicated that biopsy PNI was not only correlated with adverse pathologic characteristics but also with worse BCR prognosis of local PCa after RP. The status of biopsy PNI could serve as a promising risk-stratification factor to help the decision-making process, considering active surveillance (AS) or further treatment for PCa patients.

Defining clinically significant prostate cancer on the basis of pathological findings

The definition of clinically significant prostate cancer is a dynamic process that was initiated many decades ago, when there was already evidence that a great proportion of patients with prostate cancer diagnosed at autopsy never had any clinical symptoms. Autopsy studies led to examinations of radical prostatectomy (RP) specimens and the establishment of the definition of significant cancer at RP: tumour volume of 0.5 cm³ , Gleason grade 6 [Grade Group (GrG) 1], and organ-confined disease. RP studies were then used to develop prediction models for significant cancer by the use of needle biopsies. The first such model was used to delineate the first active surveillance (AS) criteria, known as the 'Epstein' criteria, in which patients with a cancer Gleason score of 3 + 3 = 6 (GrG1) involving fewer than two cores, and <50% of any given core, and a prostate-specific antigen density of <0.15 ng/ml per cm³ had a minimal risk of significant cancer at RP. These were adopted as components of the 'very-low-risk category' of the National Comprehensive Cancer Network guidelines, in which AS is supported as a management option. With the increase in the popularity of AS, much research has been carried out to better define significant/insignificant cancer, in order to be able to safely offer AS to a larger proportion of patients without the risk of undertreatment. Research has focused on allowing higher volume tumours, focal extraprostatic extension, and a limited amount of Gleason pattern 4, and the significance of different morphological patterns of Gleason 4. Other areas of research that will probably impact on the field but that are not covered in this review include the molecular classification of tumours and imaging techniques.