scholarly journals Interchangeability of light and virtual microscopy for histopathological evaluation of prostate cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Renata Zelic ◽  
Francesca Giunchi ◽  
Luca Lianas ◽  
Cecilia Mascia ◽  
Gianluigi Zanetti ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Virtual Microscopy ◽  
Observer Agreement ◽  
Gleason Grade ◽  
Gleason Grading ◽  
Gleason Pattern ◽  
Inter Observer Variability ◽  
Histopathological Evaluation ◽  
Good Repeatability ◽  
Repeatability And Reproducibility

AbstractVirtual microscopy (VM) holds promise to reduce subjectivity as well as intra- and inter-observer variability for the histopathological evaluation of prostate cancer. We evaluated (i) the repeatability (intra-observer agreement) and reproducibility (inter-observer agreement) of the 2014 Gleason grading system and other selected features using standard light microscopy (LM) and an internally developed VM system, and (ii) the interchangeability of LM and VM. Two uro-pathologists reviewed 413 cores from 60 Swedish men diagnosed with non-metastatic prostate cancer 1998–2014. Reviewer 1 performed two reviews using both LM and VM. Reviewer 2 performed one review using both methods. The intra- and inter-observer agreement within and between LM and VM were assessed using Cohen’s kappa and Bland and Altman’s limits of agreement. We found good repeatability and reproducibility for both LM and VM, as well as interchangeability between LM and VM, for primary and secondary Gleason pattern, Gleason Grade Groups, poorly formed glands, cribriform pattern and comedonecrosis but not for the percentage of Gleason pattern 4. Our findings confirm the non-inferiority of VM compared to LM. The repeatability and reproducibility of percentage of Gleason pattern 4 was poor regardless of method used warranting further investigation and improvement before it is used in clinical practice.

scholarly journals Gleason Score and Lethal Prostate Cancer: Does 3 + 4 = 4 + 3?

2009 ◽  
Vol 27 (21) ◽  
pp. 3459-3464 ◽  
Author(s):  
Jennifer R. Stark ◽  
Sven Perner ◽  
Meir J. Stampfer ◽  
Jennifer A. Sinnott ◽  
Stephen Finn ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gleason Score ◽  
Predictive Ability ◽  
Fold Increase ◽  
Health Study ◽  
Prognostic Information ◽  
Gleason Grading ◽  
Gleason Pattern ◽  
C Statistic ◽  
Bony Metastases

Purpose Gleason grading is an important predictor of prostate cancer (PCa) outcomes. Studies using surrogate PCa end points suggest outcomes for Gleason score (GS) 7 cancers vary according to the predominance of pattern 4. These studies have influenced clinical practice, but it is unclear if rates of PCa mortality differ for 3 + 4 and 4 + 3 tumors. Using PCa mortality as the primary end point, we compared outcomes in Gleason 3 + 4 and 4 + 3 cancers, and the predictive ability of GS from a standardized review versus original scoring. Patients and Methods Three study pathologists conducted a blinded standardized review of 693 prostatectomy and 119 biopsy specimens to assign primary and secondary Gleason patterns. Tumor specimens were from PCa patients diagnosed between 1984 and 2004 from the Physicians' Health Study and Health Professionals Follow-Up Study. Lethal PCa (n = 53) was defined as development of bony metastases or PCa death. Hazard ratios (HR) were estimated according to original GS and standardized GS. We compared the discrimination of standardized and original grading with C-statistics from models of 10-year survival. Results For prostatectomy specimens, 4 + 3 cancers were associated with a three-fold increase in lethal PCa compared with 3 + 4 cancers (95% CI, 1.1 to 8.6). The discrimination of models of standardized scores from prostatectomy (C-statistic, 0.86) and biopsy (C-statistic, 0.85) were improved compared to models of original scores (prostatectomy C-statistic, 0.82; biopsy C-statistic, 0.72). Conclusion Ignoring the predominance of Gleason pattern 4 in GS 7 cancers may conceal important prognostic information. A standardized review of GS can improve prediction of PCa survival.

scholarly journals Quantitative Analysis of Benign and Malignant Tumors in Histopathology: Predicting Prostate Cancer Grading Using SVM

2019 ◽  
Vol 9 (15) ◽  
pp. 2969 ◽  
Author(s):  
Bhattacharjee ◽  
Park ◽  
Kim ◽  
Prakash ◽  
Madusanka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Features ◽  
Morphological Features ◽  
Support Vector ◽  
Epithelial Tissue ◽  
Gleason Grade ◽  
Svm Classification ◽  
Gleason Grading ◽  
Grade 5 ◽  
Grade 3

An adenocarcinoma is a type of malignant cancerous tissue that forms from a glandular structure in epithelial tissue. Analyzed stained microscopic biopsy images were used to perform image manipulation and extract significant features for support vector machine (SVM) classification, to predict the Gleason grading of prostate cancer (PCa) based on the morphological features of the cell nucleus and lumen. Histopathology biopsy tissue images were used and categorized into four Gleason grade groups, namely Grade 3, Grade 4, Grade 5, and benign. The first three grades are considered malignant. K-means and watershed algorithms were used for color-based segmentation and separation of overlapping cell nuclei, respectively. In total, 400 images, divided equally among the four groups, were collected for SVM classification. To classify the proposed morphological features, SVM classification based on binary learning was performed using linear and Gaussian classifiers. The prediction model yielded an accuracy of 88.7% for malignant vs. benign, 85.0% for Grade 3 vs. Grade 4, 5, and 92.5% for Grade 4 vs. Grade 5. The SVM, based on biopsy-derived image features, consistently and accurately classified the Gleason grading of prostate cancer. All results are comparatively better than those reported in the literature.

scholarly journals First-Stage Prostate Cancer Identification on Histopathological Images: Hand-Driven versus Automatic Learning

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 356 ◽  
Author(s):  
Gabriel García ◽  
Adrián Colomer ◽  
Valery Naranjo
Keyword(s):  
Prostate Cancer ◽  
Contextual Information ◽  
Support Vector ◽  
Learning Approach ◽  
Gleason Grade ◽  
Gleason Grading ◽  
Histopathological Image ◽  
Histopathological Images ◽  
Grade 3 ◽  
First Time

Analysis of histopathological image supposes the most reliable procedure to identify prostate cancer. Most studies try to develop computer aid-systems to face the Gleason grading problem. On the contrary, we delve into the discrimination between healthy and cancerous tissues in its earliest stage, only focusing on the information contained in the automatically segmented gland candidates. We propose a hand-driven learning approach, in which we perform an exhaustive hand-crafted feature extraction stage combining in a novel way descriptors of morphology, texture, fractals and contextual information of the candidates under study. Then, we carry out an in-depth statistical analysis to select the most relevant features that constitute the inputs to the optimised machine-learning classifiers. Additionally, we apply for the first time on prostate segmented glands, deep-learning algorithms modifying the popular VGG19 neural network. We fine-tuned the last convolutional block of the architecture to provide the model specific knowledge about the gland images. The hand-driven learning approach, using a nonlinear Support Vector Machine, reports a slight outperforming over the rest of experiments with a final multi-class accuracy of 0.876 ± 0.026 in the discrimination between false glands (artefacts), benign glands and Gleason grade 3 glands.

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

Life ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1172
Author(s):  
Richard Y. Ball ◽  
Ryan Cardenas ◽  
Mark S. Winterbone ◽  
Marcelino Y. Hanna ◽  
Chris Parker ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Large Volume ◽  
Tumor Volume ◽  
Statistical Significance ◽  
Biological Significance ◽  
Tumor Burden ◽  
Gleason Grade ◽  
Grade Group ◽  
Gleason Pattern ◽  
The Impact

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.

scholarly journals Understanding the gleason grading system and its changes

2019 ◽  
Vol 9 (2) ◽  
pp. 1580-1585
Author(s):  
Sujata Pudasaini ◽  
Neeraj Subedi
Keyword(s):  
Prostatic Carcinoma ◽  
World Health ◽  
Grading System ◽  
Pathology Report ◽  
Gleason Grade ◽  
High Grade ◽  
Grade Group ◽  
Gleason Grading ◽  
Gleason Pattern ◽  
Health Organization

Gleason Grading System is the most widely used grading system used for prostatic carcinoma. The five basic grade patterns are used to generate a histologic score, which can range from 2 to 10 (including primary and secondary patterns). The original Gleason Grading System was used to grade acinar adenocarcinoma based on architectural features and it has been correlated with excellent clinical outcomes. Since 1960s, after the discovery of the original Gleason Grading System, a modified version of the Gleason Grading System was introduced in the International Society of Urological Pathology 2005 which came up with many changes including elimination of Gleason pattern 1. The ISUP 2005 was further updated in 2014 to provide more accurate stratification of prostatic carcinoma. The new Gleason Grade Group 1 to 5 has been introduced and it has little resemblance to the original Gleason system. This Gleason Grade Group has been accepted by the 2016 World Health Organization classification of tumors of the prostate. For a needle biopsy, high grade component of any quantity should be included in the Gleason score as it indicates a high probability of finding significant high grade tumor in the prostate. By understanding the principles and practice of this grading system, the pathology report has to clearly indicate which system is adopted in the reporting. This review discusses GGS and its recent development focusing on major changes over the years that led to the new Grade Group system proposed by the 2014 ISUP consensus.

scholarly journals Inter-observer variability of cribriform architecture and percent Gleason pattern 4 in prostate cancer: relation to clinical outcome

2020 ◽  
Author(s):  
Margaretha A. van der Slot ◽  
Eva Hollemans ◽  
Michael A. den Bakker ◽  
Robert Hoedemaeker ◽  
Mike Kliffen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Outcome ◽  
Observer Variability ◽  
Gleason Pattern ◽  
Inter Observer Variability

scholarly journals Automated Gleason Grading and Gleason Pattern Region Segmentation Based on Deep Learning for Pathological Images of Prostate Cancer

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 117714-117725
Author(s):  
Yuchun Li ◽  
Mengxing Huang ◽  
Yu Zhang ◽  
Jing Chen ◽  
Haixia Xu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Deep Learning ◽  
Region Segmentation ◽  
Gleason Grading ◽  
Gleason Pattern

Differential levels of serum PSA related to volume of benign, Gleason pattern 3 and pattern 4 prostate tissue.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 164-164
Author(s):  
Ciro Andolfi ◽  
Andrew Vickers ◽  
Matthew R. Cooperberg ◽  
Peter Carroll ◽  
Janet E. Cowan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Cancer Screening ◽  
Early Stage ◽  
Prostate Tissue ◽  
Gleason Grade ◽  
Primary Analysis ◽  
Grade Group ◽  
Gleason Pattern ◽  
Benign Tissue ◽  
Group 1

164 Background: PSA is an essential component of prostate cancer screening, management, and oncologic risk. We evaluated how serum levels of PSA vary by volume of benign tissue, Gleason pattern 3 (GP3), and Gleason pattern 4 (GP4). Methods: Consecutive men undergoing radical prostatectomy at two academic institutions for pT2N0, Gleason grade group 1-4, and undetectable postoperative PSA were reviewed. For each man, estimated volume (cc) of benign, GP3, and GP4 were extracted from the prostatectomy specimen. The primary analysis evaluated the association between pre-operative PSA and volume of each type of prostate tissue using multivariable linear regression with adjustment for age. An assessment of predictiveness (R2) for PSA level was performed with each predictor and associated non-linear terms were removed from the model. Results: Estimated contribution to serum PSA for institutions A and B was 0.04-0.05 ng/ml/cc for benign, 0.08-0.11 ng/ml/cc for GP3, and 0.62-0.83 ng/ml/cc for GP4 (Table). We did not see a difference between PSA levels per cc of GP3 vs. benign tissue (p=0.4). R2decreased only slightly when removing age (0.006-0.010), benign tissue (0.049-0.051) or GP3 (0.011-0.023) from the model. When GP4 was removed, R2 decreased 0.063-0.310. R2 was far higher for GP4 than for Grade Group alone and was equal or superior to Grade Group plus total prostate volume. Conclusions: In early stage Grade Group 1-4 prostate cancer, one cc of Gleason pattern 4 was associated with 6 to 20-fold more serum PSA than one cc of Gleason pattern 3 or benign tissue. No difference in PSA per cc was observed between Gleason pattern 3 and benign tissue which has clinical implications for screening and active surveillance. [Table: see text]

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