Improving the Reproducibility of the Gleason Scores in Small Foci of Prostate Cancer - Suggestion of Diagnostic Criteria for Glandular Fusion

Applications of Topological Data Analysis in Oncology

The emergence of the information age in the last few decades brought with it an explosion of biomedical data. But with great power comes great responsibility: there is now a pressing need for new data analysis algorithms to be developed to make sense of the data and transform this information into knowledge which can be directly translated into the clinic. Topological data analysis (TDA) provides a promising path forward: using tools from the mathematical field of algebraic topology, TDA provides a framework to extract insights into the often high-dimensional, incomplete, and noisy nature of biomedical data. Nowhere is this more evident than in the field of oncology, where patient-specific data is routinely presented to clinicians in a variety of forms, from imaging to single cell genomic sequencing. In this review, we focus on applications involving persistent homology, one of the main tools of TDA. We describe some recent successes of TDA in oncology, specifically in predicting treatment responses and prognosis, tumor segmentation and computer-aided diagnosis, disease classification, and cellular architecture determination. We also provide suggestions on avenues for future research including utilizing TDA to analyze cancer time-series data such as gene expression changes during pathogenesis, investigation of the relation between angiogenic vessel structure and treatment efficacy from imaging data, and experimental confirmation that geometric and topological connectivity implies functional connectivity in the context of cancer.

Automated approach for estimation of grade groups for prostate cancer based on histological image feature analysis

BACKGROUND

There is a low reproducibility of the Gleason scores that determine the grade group of prostate cancer given the intra- and interobserver variability among pathologists. This study aimed to develop an automated approach for estimating prostate cancer grade groups based on features obtained from histological image analysis.

METHODS

Fifty-nine patients who underwent radical prostatectomy were selected under the approval of the institutional review board of our university hospital. For estimation, we followed the grade group criteria provided by the International Society of Urological Pathology in 2014. One hundred eight specimen slides obtained from the patients were digitized to extract 110 regions of interest (ROI) from hematoxylin and eosin-stained histological images using a digital whole slide scanner at ×20 magnification with a pixel size of 0.4 μm. Each color pixel value in the ROI was decomposed into six intensities corresponding to the RGB (red, green, and blue) and HSV (hue, saturation, and value) color models. Image features were extracted by histological image analysis, obtaining 54 features from the ROI based on histogram and texture analyses in the six types of decomposed histological images. Then, 40 representative features were selected from the 324 histological image features based on statistically significant differences (P < .05) between the mean image feature values for high (≥3, Gleason score ≥4 + 3) and low (≤2, Gleason score ≤3 + 4) grade groups. The relationship between grade groups and the most representative image feature (ie, complexity) was approximated using regression to estimate real-number grade groups defined by continuous numerical grading. Finally, the grade groups were expressed as the conventional grade groups (ie, integers from 1 to 5) using a piecewise step function.

RESULTS

The grade groups were correctly estimated by the proposed approach without errors on training (70 ROIs) and validation (40 ROIs) data.

CONCLUSIONS

Our results suggest that the proposed approach may support pathologists during the evaluation of grade groups for prostate cancer, thus mitigating intra- and interobserver variability.

Persistent Homology for the Quantitative Evaluation of Architectural Features in Prostate Cancer Histology

The current system for evaluating prostate cancer architecture is the Gleason grading system which divides the morphology of cancer into five distinct architectural patterns, labeled 1 to 5 in increasing levels of cancer aggressiveness, and generates a score by summing the labels of the two most dominant patterns. The Gleason score is currently the most powerful prognostic predictor of patient outcomes; however, it suffers from problems in reproducibility and consistency due to the high intra-observer and inter-observer variability amongst pathologists. In addition, the Gleason system lacks the granularity to address potentially prognostic architectural features beyond Gleason patterns. We evaluate prostate cancer for architectural subtypes using techniques from topological data analysis applied to prostate cancer glandular architecture. In this work we demonstrate the use of persistent homology to capture architectural features independently of Gleason patterns. Specifically, using persistent homology, we compute topological representations of purely graded prostate cancer histopathology images of Gleason patterns 3,4 and 5, and show that persistent homology is capable of clustering prostate cancer histology into architectural groups through a ranked persistence vector. Our results indicate the ability of persistent homology to cluster prostate cancer histopathology images into unique groups with dominant architectural patterns consistent with the continuum of Gleason patterns. In addition, of particular interest, is the sensitivity of persistent homology to identify specific sub-architectural groups within single Gleason patterns, suggesting that persistent homology could represent a robust quantification method for prostate cancer architecture with higher granularity than the existing semi-quantitative measures. The capability of these topological representations to segregate prostate cancer by architecture makes them an ideal candidate for use as inputs to future machine learning approaches with the intent of augmenting traditional approaches with topological features for improved diagnosis and prognosis.

Active surveillance as a therapeutic option for patients with low-risk prostate cancer according to the 2014 International Society of Urological Pathology grading system: a review

Extended prostate-specific antigen screening and the tightly focused execution of biopsies have resulted in an increased rate of detection, and thereby increased interventional treatment, of prostate cancer (PCa). The potential overdiagnosis and overtreatment of PCa patients have repeatedly been criticized in national and international literature. Controlled monitoring of patients in the setting of active surveillance (AS) can prevent overtreatment and the needless impairment of quality of life. The prerequisite for this treatment strategy is the diagnosis of low-grade/risk PCa. Since 2005, the modified Gleason grading system has been used for the histological assessment of PCa. In 2014, the International Society of Urological Pathology recommended a new prognostic grading system with five grades analogous to the modified Gleason score. This review discusses the importance of pathological histological analysis of PCa, particularly in the face of recent amendments, and sheds light on the significance of the new grading system for the diagnosis of low-grade/risk PCa with regard to the therapeutic option of AS.

Interobserver variability in Gleason histological grading of prostate cancer

OBJECTIVE

The aims of this study were to evaluate the reproducibility of the Gleason grading system and to compare its interobserver variability with the novel Gleason grade grouping proposal using a large sample volume.

MATERIALS AND METHODS

In total, 407 pathology slides of prostate needle biopsies from 34 consecutive patients with prostate cancer were re-evaluated. The International Society of Urological Pathology 2005 modified Gleason grading system with Epstein's modification was used. Two pathologists, blind to each other and to the initial pathology report, performed the pathological evaluation. To determine interobserver concordance, the kappa (κ) coefficient test was used.

RESULTS

Pathologist 1 and pathologist 2 detected a tumor in 202 and 231 cores, respectively (p < 0.001). The two pathologists disagreed on the presence of a tumor in 31 cores. Of these 31 cores, 74% (n = 23/31) were Gleason pattern 3. The mean length of the cancer foci in these 31 disputed cores was 1.54 ± 0.8 mm. Concordance rates between the two observers for primary and secondary Gleason patterns were 63.96% (κ = 0.34) and 63.45% (κ = 0.37), respectively. Concordance with respect to the Gleason sum was 57.9% (κ = 0.43). When the Gleason scores were classified into the novel Gleason grade grouping, concordance was found to be 51.7% (κ = 0.39).

CONCLUSIONS

The agreement between observers on the Gleason sum was moderate. The novel Gleason grade grouping did not improve interobserver agreement. Further studies are needed to confirm these results on interobserver variability.

Gleason grade 4 prostate adenocarcinoma patterns: an interobserver agreement study among genitourinary pathologists

AIMS

To assess the interobserver reproducibility of individual Gleason grade 4 growth patterns.

METHODS AND RESULTS

Twenty-three genitourinary pathologists participated in the evaluation of 60 selected high-magnification photographs. The selection included 10 cases of Gleason grade 3, 40 of Gleason grade 4 (10 per growth pattern), and 10 of Gleason grade 5. Participants were asked to select a single predominant Gleason grade per case (3, 4, or 5), and to indicate the predominant Gleason grade 4 growth pattern, if present. 'Consensus' was defined as at least 80% agreement, and 'favoured' as 60-80% agreement. Consensus on Gleason grading was reached in 47 of 60 (78%) cases, 35 of which were assigned to grade 4. In the 13 non-consensus cases, ill-formed (6/13, 46%) and fused (7/13, 54%) patterns were involved in the disagreement. Among the 20 cases where at least one pathologist assigned the ill-formed growth pattern, none (0%, 0/20) reached consensus. Consensus for fused, cribriform and glomeruloid glands was reached in 2%, 23% and 38% of cases, respectively. In nine of 35 (26%) consensus Gleason grade 4 cases, participants disagreed on the growth pattern. Six of these were characterized by large epithelial proliferations with delicate intervening fibrovascular cores, which were alternatively given the designation fused or cribriform growth pattern ('complex fused').

CONCLUSIONS

Consensus on Gleason grade 4 growth pattern was predominantly reached on cribriform and glomeruloid patterns, but rarely on ill-formed and fused glands. The complex fused glands seem to constitute a borderline pattern of unknown prognostic significance on which a consensus could not be reached.

[Prostate cancer. Part 2: Review of the various tumor grading systems over the years 1966-2015 and future perspectives of the new grading of the International Society of Urological Pathology (ISUP)]

The continued development of methods in needle biopsies and radical prostatectomy for treatment of prostate cancer has given special emphasis to the question of the prognostic relevance of the various systems of grading. The classical purely histological grading system of Gleason has been modified several times in the past decades and cleared the way for a new grading system by the prognostic grading of Epstein. Assessment of the old and also modified combined histological and cytological grading of Mostofi, the World health Organization (WHO) and the urologic-pathological working group of prostate cancer in connection with the Gleason grading (combined Gleason-Helpap grading), has led to considerably improved rates of concordance between biopsy and radical prostatectomy and to improved estimations of prognosis beside its contribution to the development of a more practicable grading system for clinical use.

Diagnosis of "Poorly Formed Glands" Gleason Pattern 4 Prostatic Adenocarcinoma on Needle Biopsy: An Interobserver Reproducibility Study Among Urologic Pathologists With Recommendations

Accurate recognition of Gleason pattern (GP) 4 prostate carcinoma (PCa) on needle biopsy is critical for patient management and prognostication. "Poorly formed glands" are the most common GP4 subpattern. We studied the diagnostic reproducibility and the quantitative threshold of grading GP4 "poorly formed glands" and the criteria to distinguish them from tangentially sectioned GP3 glands. Seventeen urologic pathologists were first queried for the definition of "poorly formed glands" using cases representing a spectrum of PCa glandular differentiation. Cancer glands with no or rare lumens, elongated compressed glands, and elongated nests were considered "poorly formed glands" by consensus. Participants then graded a second set of 23 PCa cases that potentially contained "poorly formed glands" with a fair interobserver agreement (κ = 0.34). The consensus diagnoses, defined as agreement by > 70% participants, were then correlated with the quantitative (≤ 5, 6 to 10, >10) and topographic features of poorly formed glands (clustered, immediately adjacent to, and intermixed with other well-formed PCa glands) in each case. Poorly formed glands immediately adjacent to other well-formed glands regardless of their number and small foci of ≤ 5 poorly formed glands regardless of their location were not graded as GP4. In contrast, large foci of >10 poorly formed glands that were not immediately adjacent to well-formed glands were graded as GP4. Grading "poorly formed glands" is challenging. Some morphologic features are, however, reproducible for and against a GP4 diagnosis. This study represents an important step in standardization of grading of "poorly formed glands" based on quantitative and topographic morphologic features.

Modernizing the diagnostic and decision-making pathway for prostate cancer

PSA has led to a drastic increase in the detection of prostate cancer, rendering this biomarker the gateway for the diagnostic pathway of prostatic neoplasms. However, the increase in incidence has not been mirrored by a similar reduction in mortality. Widespread PSA testing has facilitated the overdiagnosis and overtreatment of indolent disease. To reduce this phenomenon and avoid negative repercussions on the quality of life of men undergoing unnecessary therapies, the diagnostic pathway of prostate cancer needs to be improved. Multiparametric MRI (mp-MRI) can enhance the sensitivity and specificity of PSA, as well as the shortcomings of random biopsy sampling. This novel imaging technique has been proven to identify larger and more aggressive cancer foci, which should be targeted for treatment. New technological developments now allow for fusion of mp-MRI images with real-time ultrasound, opening the way to lesion-targeted biopsies. Furthermore, mp-MRI and targeted biopsies can also improve active surveillance protocols and permit more conservative focal therapy strategies. By implementing targeted biopsies, the diagnostic pathway will focus on clinically significant disease, consequently reducing overdiagnosis and overtreatment. Before this novel protocol becomes the new gold standard, mp-MRI acquisition and interpretation need to be standardized and targeted-biopsy strategies need to be further validated prior to abandoning random-sampling ones. Several multidisciplinary consortiums are already working on the standardization of prostate MRI, and there are ongoing prospective trials on targeted biopsies and MRI. Soon, imaging of prostatic lesions and selected biopsies will modify the diagnostic evaluation of prostate cancer, reducing overtreatment and therapy-derived complications that negatively affect quality of life.

Significance of Gleason grading of low-grade carcinoma of the prostate with therapeutic option of active surveillance

INTRODUCTION

Active surveillance needs a precise grading diagnosis of a low-grade carcinoma of the prostate (Gleason score (GS) 6) within a small organ-confined tumor. However, how accurate is the gold standard of GS 6 in predicting a small pT2 carcinoma? To answer this question, we have analyzed grading systems in this study.

METHODS

Prostatic carcinomas in biopsy and corresponding radical prostatectomy (RP) specimens of 960 patients were graded by the Gleason system in which glandular fusions and nucleolar stage (prominence and location) were considered.

RESULTS

Using the modified Gleason grading, a high upgrading rate from the biopsy to RP specimens (GS 6-7) and in even 30% a non-organ-confined growth pattern (pT3) of GS 6 carcinoma in RP was found. When considering glandular fusion and the incorporation of the state of nucleoli within the Gleason grading, the agreement of score 6 between biopsy and RP specimens as well as the prediction of a pT2a tumor increased from about 80 to 90%.

CONCLUSION

The combination of Gleason grading and grading of the nuclear and nucleolar features may help to identify patients eligible for active surveillance.