Sampling the spatial patterns of cancer: Optimized biopsy procedures for estimating prostate cancer volume and Gleason Score

Prostate biopsy is the current gold-standard procedure for prostate cancer diagnosis. Existing prostate biopsy procedures have been mostly focusing on detecting cancer presence. However, they often ignore the potential use of biopsy to estimate cancer volume (CV) and Gleason Score (GS, a cancer grade descriptor), the two surrogate markers for cancer aggressiveness and the two crucial factors for treatment planning. To fill up this vacancy, this paper assumes and demonstrates that, by optimally sampling the spatial patterns of cancer, biopsy procedures can be specifically designed for estimating CV and GS. Our approach combines image analysis and machine learning tools in an atlas-based population study that consists of three steps. First, the spatial distributions of cancer in a patient population are learned, by constructing statistical atlases from histological images of prostate specimens with known cancer ground truths. Then, the optimal biopsy locations are determined in a feature selection formulation, so that biopsy outcomes (either cancer presence or absence) at those locations could be used to differentiate, at the best rate, between the existing specimens having different (high vs. low) CV/GS values. Finally, the optimized biopsy locations are utilized to estimate whether a new-coming prostate cancer patient has high or low CV/GS values, based on a binary classification formulation. The estimation accuracy and the generalization ability are evaluated by the classification rates and the associated receiver-operating-characteristic (ROC) curves in cross validations. The optimized biopsy procedures are also designed to be robust to the almost inevitable needle displacement errors in clinical practice, and are found to be robust to variations in the optimization parameters as well as the training populations

Flaxseed-Derived Enterolactone Is Inversely Associated with Tumor Cell Proliferation in Men with Localized Prostate Cancer

Enterolactone and enterodiol, mammalian lignans derived from dietary sources such as flaxseed, sesame seeds, kale, broccoli, and apricots, may impede tumor proliferation by inhibiting activation of nuclear factor kappa B (NF?B) and vascular endothelial growth factor (VEGF). We examined the associations between urinary enterolactone and enterodiol with prostatic tumor expression of NF?B, VEGF, and Ki67 among 147 patients with prostate cancer who participated in a presurgical trial of flaxseed supplementation (30?g/day) for ?30 days. Urinary enterolignans and tissue biomarkers were determined by high-performance liquid chromatography and immunohistochemistry, respectively. After supplementation, we observed significant correlations between intakes of plant lignan and urinary concentrations of total enterolignans (?=0.677, P<.0001), enterolactone (?=0.676, P<.0001), and enterodiol (?=0.628, P<.0001). Importantly, we observed that total urinary enterolignans and enterolactone were significantly and inversely correlated with Ki67 in the tumor tissue (?=?0.217, P=.011, and ?=?0.230, P=.007, respectively), and a near-significant inverse association was observed for enterodiol (?=?0.159, P=.064). An inverse association was observed between enterolactone and VEGF (?=?0.143, P=.141), although this did not reach statistical significance. We did not observe an association between enterolignans and NF?B. In conclusion, flaxseed-derived enterolignans may hinder cancer cell proliferation via VEGF-associated pathways.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140111/1/jmf.2012.0159.pd

Targeted prostate biopsy using statistical image analysis

Abstract-In this paper, a method for maximizing the probability of prostate cancer detection via biopsy is presented, by combining image analysis and optimization techniques. This method consists of three major steps. First, a statistical atlas of the spatial distribution of prostate cancer is constructed from histological images obtained from radical prostatectomy specimen. Second, a probabilistic optimization framework is employed to optimize the biopsy strategy, so that the probability of cancer detection is maximized under needle placement uncertainties. Finally, the optimized biopsy strategy generated in the atlas space is mapped to a specific patient space using an automated segmentation and elastic registration method. Cross-validation experiments showed that the predictive power of the optimized biopsy strategy for cancer detection reached the 94%-96% levels for 6-7 biopsy cores, which is significantly better than standard random-systematic biopsy protocols, thereby encouraging further investigation of optimized biopsy strategies in prospective clinical studies. Index Terms-Biopsy optimization, prostate cancer, spatial normalization, statistical image analysis

Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate cancer consensus conference 2017

Purpose: Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-dri

Hormone naïve prostate cancer: predicting and maximizing response intervals

Hormone naïve advanced prostate cancer is subdivided into two disease states: biochemical recurrence and traditional M1 (metastatic) prostate cancer and characterized by no prior hormonal therapy or androgen deprivation therapy (ADT). In biochemical recurrence/prostate-specific antigen (PSA) recurrence, men should be risk-stratified based on their PSA doubling time, the Gleason score and the timing of the recurrence. In general, only men who are at high risk should be considered for early/immediate ADT although this is best done using shared decision with the patient. The type of ADT to be used in biochemical recurrence ranging from oral-only peripheral blockade (peripheral androgen deprivation) to complete hormonal therapy (combined androgen blockade [CAB]) remains in debate owing to lack of randomized controlled trials (RCT). However, there is good RCT support for use of intermittent hormonal therapy (IHT). There is also limited research on biomarker response (PSA and testosterone decline) to predict prognosis. On the other hand, in the setting of M1 hormone naïve prostate cancer, there are many more RCT′s to inform our decisions. CAB and gonadotrophin-releasing hormone antagonists perhaps provide a slight efficacy advantage while IHT may be slightly inferior with minimal M1 disease. The PSA nadir at 7 months after starting ADT is a powerful prognostic tool for M1 patients. There is growing recognition that serum testosterone (T) control while on ADT is linked to the development of castrate-resistant prostate cancer. Especially for a M1 patient, maintaining a serum T below 20-30 ng dl−1 prolongs the response to ADT. Novel oral agents (abiraterone and enzalutamide) may soon find use in hormone naïve disease and may alter the treatment landscape. Despite over 75 years of experience with ADT, many questions remain, and the field continues to evolve

Hormone naïve prostate cancer: predicting and maximizing response intervals.

Hormone naïve advanced prostate cancer is subdivided into two disease states: biochemical recurrence and traditional M1 (metastatic) prostate cancer and characterized by no prior hormonal therapy or androgen deprivation therapy (ADT). In biochemical recurrence/prostate-specific antigen (PSA) recurrence, men should be risk-stratified based on their PSA doubling time, the Gleason score and the timing of the recurrence. In general, only men who are at high risk should be considered for early/immediate ADT although this is best done using shared decision with the patient. The type of ADT to be used in biochemical recurrence ranging from oral-only peripheral blockade (peripheral androgen deprivation) to complete hormonal therapy (combined androgen blockade [CAB]) remains in debate owing to lack of randomized controlled trials (RCT). However, there is good RCT support for use of intermittent hormonal therapy (IHT). There is also limited research on biomarker response (PSA and testosterone decline) to predict prognosis. On the other hand, in the setting of M1 hormone naïve prostate cancer, there are many more RCT's to inform our decisions. CAB and gonadotrophin-releasing hormone antagonists perhaps provide a slight efficacy advantage while IHT may be slightly inferior with minimal M1 disease. The PSA nadir at 7 months after starting ADT is a powerful prognostic tool for M1 patients. There is growing recognition that serum testosterone (T) control while on ADT is linked to the development of castrate-resistant prostate cancer. Especially for a M1 patient, maintaining a serum T below 20-30 ng dl-1 prolongs the response to ADT. Novel oral agents (abiraterone and enzalutamide) may soon find use in hormone naïve disease and may alter the treatment landscape. Despite over 75 years of experience with ADT, many questions remain, and the field continues to evolve