Clinical strategy of repeat biopsy in patients with atypical small acinar proliferation (ASAP)

Atypical small acinar proliferation (ASAP) occurs in approximately 5% of prostate biopsies. Approximately 30–40% of patients with ASAP have biopsy detectable prostate cancer (PCa) within 5 years. Current guidelines recommend a repeat biopsy within 3–6 months after the initial diagnosis. The aim of the present study was to examine the association between ASAP and subsequent diagnosis of clinically significant PCa (csPCa). The need for immediate repeat biopsy was also evaluated. We identified 212 patients with an ASAP diagnosis on their first biopsy at our institution between February 2006 and March 2018. Of these patients, 102 (48.1%) had at least one follow-up biopsy. Clinicopathologic features including rates of subsequent PCa and csPCa were assessed. Thirty-five patients subsequently underwent radical prostatectomy (RP). Their pathologic results were reviewed. csPCa was defined as the presence of Gleason score (GS) ≥ 3 + 4 in ≥ 1 biopsy core. Adverse pathology (AP) was defined as high-grade (primary Gleason pattern ≥ 4) or non-organ-confined disease (pT3/N1) after RP. Of 102 patients, 87 (85.3%), 13 (12.7%), and 2 (2.0%) had one, two, and three follow-up biopsies, respectively. Median time from the initial ASAP diagnosis to the 2nd follow-up biopsy and the last follow-up biopsy were 21.9 months (range 1–129 months) and 27.7 months (range 1–129 months), respectively. Of these patients, 46 (45.1%) were subsequently diagnosed with PCa, including 20 (19.6%) with csPCa. Only 2 (2.0%) patients had GS ≥ 8 disease. Five (4.9%) patients had number of positive cores > 3. Of 35 patients who subsequently underwent RP, seven (20%) had AP after RP and 17 (48.6%) showed GS upgrading. Of these 17 patients, the vast majority (16/17, 94.1%) had GS upgrading from 3 + 3 to 3 + 4. 45.1% of patients with an initial diagnosis of ASAP who had repeat prostate biopsy were subsequently diagnosed with PCa and 19.6% were found to have csPCa. Our findings add further evidence that after a diagnosis of ASAP, a repeat biopsy is warranted and that the repeat biopsy should not be postponed.

Variance of Tumor Grade at Radical Prostatectomy With Assessment of Each Tumor Nodule Versus Global Grading

Context.— Multifocal prostate cancer at radical prostatectomy (RP) may be graded with assessment of each individual tumor nodule (TN) or global grading of all TNs in aggregate. Objective.— To assess case-level grade variability between these 2 grading approaches. Design.— We reviewed 776 RPs with multifocal prostate cancer with 2 or more separate TNs of different Grade Groups (GGs). Two separate grades were assigned to each RP: one based on the TN with the highest grade and a global grade based on the Gleason pattern volumes for all TNs. We then compared the results of these 2 methods. Results.— The case-level grade changed by 1 or more GGs between the 2 grading methods in 35% (132 of 374) of GG3 through GG5 cases. Twelve percent (37 of 309) of GG2 cases with Gleason pattern 4 more than 5% based on individual TN grading decreased their Gleason pattern 4 to less than 5% based on the global approach. Minor tertiary pattern 5 (Gleason pattern 5 <5%) was observed in 6.8% (11 of 161) of GG4 (Gleason score 3 + 5 = 8 and 5 + 3 = 8) and GG5 cases with global grading. The risk of grade discrepancy between the 2 methods was associated with the highest-grade TN volume (inverse relationship), patient age, and number of TNs (P < .001, P = .003, and P < .001, respectively). Conclusions.— The global grading approach resulted in a lower grade in 35% of GG3 through GG5 cases compared with grading based on the highest-grade TN. Two significant risk factors for this discrepancy with a global grading approach occur when the highest-grade TN has a relatively small tumor volume and with the higher number of TNs per RP. The observed grade variability between the 2 grading schemes most likely limits the interchangeability of post-RP multi-institutional databases if those institutions use different grading approaches.

The Urine Biomarker PUR-4 Is Positively Associated with the Amount of Gleason 4 in Human Prostate Cancers

The Prostate Urine Risk (PUR) biomarker is a four-group classifier for predicting outcome in patients prior to biopsy and for men on active surveillance. The four categories correspond to the probabilities of the presence of normal tissue (PUR-1), D’Amico low-risk (PUR-2), intermediate-risk (PUR-3), and high-risk (PUR-4) prostate cancer. In the current study we investigate how the PUR-4 status is linked to Gleason grade, prostate volume, and tumor volume as assessed from biopsy (n = 215) and prostatectomy (n = 9) samples. For biopsy data PUR-4 status alone was linked to Gleason Grade group (GG) (Spearman’s, ρ = 0.58, p < 0.001 trend). To assess the impact of tumor volume each GG was dichotomized into Small and Large volume cancers relative to median volume. For GG1 (Gleason Pattern 3 + 3) cancers volume had no impact on PUR-4 status. In contrast for GG2 (3 + 4) and GG3 (4 + 3) cancers PUR-4 levels increased in large volume cancers with statistical significance observed for GG2 (p = 0.005; Games-Howell). These data indicated that PUR-4 status is linked to the presence of Gleason Pattern 4. To test this observation tumor burden and Gleason Pattern were assessed in nine surgically removed and sectioned prostates allowing reconstruction of 3D maps. PUR-4 was not correlated with Gleason Pattern 3 amount, total tumor volume or prostate size. A strong correlation was observed between amount of Gleason Pattern 4 tumor and PUR-4 signature (r = 0.71, p = 0.034, Pearson’s). These observations shed light on the biological significance of the PUR biomarker and support its use as a non-invasive means of assessing the presence of clinically significant prostate cancer.

A Deep Learning Pipeline for Grade Groups Classification Using Digitized Prostate Biopsy Specimens

Prostate cancer is a significant cause of morbidity and mortality in the USA. In this paper, we develop a computer-aided diagnostic (CAD) system for automated grade groups (GG) classification using digitized prostate biopsy specimens (PBSs). Our CAD system aims to firstly classify the Gleason pattern (GP), and then identifies the Gleason score (GS) and GG. The GP classification pipeline is based on a pyramidal deep learning system that utilizes three convolution neural networks (CNN) to produce both patch- and pixel-wise classifications. The analysis starts with sequential preprocessing steps that include a histogram equalization step to adjust intensity values, followed by a PBSs’ edge enhancement. The digitized PBSs are then divided into overlapping patches with the three sizes: 100 × 100 (CNNS), 150 × 150 (CNNM), and 200 × 200 (CNNL), pixels, and 75% overlap. Those three sizes of patches represent the three pyramidal levels. This pyramidal technique allows us to extract rich information, such as that the larger patches give more global information, while the small patches provide local details. After that, the patch-wise technique assigns each overlapped patch a label as GP categories (1 to 5). Then, the majority voting is the core approach for getting the pixel-wise classification that is used to get a single label for each overlapped pixel. The results after applying those techniques are three images of the same size as the original, and each pixel has a single label. We utilized the majority voting technique again on those three images to obtain only one. The proposed framework is trained, validated, and tested on 608 whole slide images (WSIs) of the digitized PBSs. The overall diagnostic accuracy is evaluated using several metrics: precision, recall, F1-score, accuracy, macro-averaged, and weighted-averaged. The (CNNL) has the best accuracy results for patch classification among the three CNNs, and its classification accuracy is 0.76. The macro-averaged and weighted-average metrics are found to be around 0.70–0.77. For GG, our CAD results are about 80% for precision, and between 60% to 80% for recall and F1-score, respectively. Also, it is around 94% for accuracy and NPV. To highlight our CAD systems’ results, we used the standard ResNet50 and VGG-16 to compare our CNN’s patch-wise classification results. As well, we compared the GG’s results with that of the previous work.

Treatment Strategies for High-Risk Localized and Locally Advanced and Oligometastatic Prostate Cancer

Despite the significant advances in the treatment of high-risk prostate cancer, patients with very high-risk features such as being locally advanced (clinical stage T3–4 or minimal nodal involvement), having a high Gleason pattern, or with oligometastasis may still have a poor prognosis despite aggressive treatment. Multidisciplinary treatment with both local and systemic therapies is thought to be effective, however, unfortunately, there is still no standard treatment. However, in recent years, local definitive therapy using a combination of radiotherapy and androgen deprivation is being supported by several randomized clinical trials. This study reviews the current literature with a focus on the definition of very high-risk prostate cancer, the role of modern imaging, and its treatment options.

Risk of adverse pathological features for intermediate risk prostate cancer: Clinical implications for definitive radiation therapy

Background Intermediate risk prostate cancer represents a largely heterogeneous group with diverse disease extent. We sought to establish rates of adverse pathological features important for radiation planning by analyzing surgical specimens from men with intermediate risk prostate cancer who underwent immediate radical prostatectomy, and to define clinical pathologic features that may predict adverse outcomes. Materials and methods A total of 1552 men diagnosed with intermediate risk prostate cancer who underwent immediate radical prostatectomy between 1/1/2005 and 12/31/2015 were reviewed. Inclusion criteria included available preoperative PSA level, pathology reports of transrectal ultrasound-guided prostate biopsy, and radical prostatectomy. Incidences of various pathological adverse features were evaluated. Patient characteristics and clinical disease features were analyzed for their predictive values. Results Fifty percent of men with high risk features (defined as PSA >10 but <20 or biopsy primary Gleason pattern of 4) had pathological upstage to T3 or higher disease. The incidence of upgrade to Gleason score of 8 or higher and the incidence of lymph node positive disease was low. Biopsy primary Gleason pattern of 4, and PSA greater than 10 but less than 20, affected adverse pathology in addition to age and percent positive biopsy cores. Older age and increased percentage of positive cores were significant risk factors of adverse pathology. Conclusion Our findings underscore the importance of comprehensive staging beyond PSA level, prostate biopsy, and CT/bone scan for men with intermediate risk prostate cancer proceeding with radiation in the era of highly conformal treatment.