Assessment of prognostic factors of prostate cancer : limitations and possibilities of morphology

Prostate cancer is a leading cause of cancer morbidity and mortality. It is a morphologically, genetically, and clinically heterogeneous disease. Stage and grade are important predictors of patient outcome. Extraprostatic extension (EPE) of prostate cancer is a key component of staging but it is not fully understood how its histopathological characteristics correlate with outcome. Gleason grading takes the morphological heterogeneity into account and is considered one of the best prognostic factors of prostate cancer. The grading system has evolved considerably over time and it is essential to understand how this affects its utility. The aim of this thesis was to classify patients with EPE into prognostic groups and to evaluate Gleason grading trends over time and how grading reproducibility can be improved. We reviewed 1051 radical prostatectomy (RP) specimens and found 470 cases with EPE. Men with EPE had a higher risk of biochemical recurrence. When stratified by the extent and other pathological features of EPE, radial extent predicted recurrence, while perineural invasion at the site of EPE and circumferential extent did not. We analyzed trends in Gleason grading practices in Sweden and assessed the impact of the 2005 International Society of Urological Pathology (ISUP) revision. Data on 97,168 men with a primary diagnosis of prostate cancer in needle biopsy from 1998 to 2011 were obtained from the National Prostate Cancer Register (NPCR). There was a shift towards higher Gleason scores (GS) at diagnosis over the period but more evident after the ISUP revision. The trend remained when stage migration was factored in. This grade inflation has consequences for therapy decisions, such as the eligibility for curative treatment or active surveillance. The concordance between GS in biopsies and subsequent RP specimens was analyzed in 15,598 men registered by the NPCR between 2000 and 2012. The agreement improved from 55% to 68% during the period, but most of the improvement occurred before 2005. When adjusted for GS and year of diagnosis, the GS prediction became less accurate over time. A limitation of Gleason grading is that it is subjective and suffers from interobserver variability. We analyzed causes of disagreement in 87 prostate cancer biopsies, included in a reference image database for standardization of pathology. A group of 23 international experts failed to reach consensus in 41% of cases. The most frequent cause of disagreement was between GS 3+3 with tangential cutting artifacts and GS 3+4 with poorly formed or fused glands. An artificial intelligence (AI) system trained in grading assessed the grades of non-consensus cases and obtained a weighted kappa value of 0.53 compared to 0.50 for the pathologists, placing AI as the sixth most reproducible observer. In conclusion, prostate cancer is a heterogeneous disease calling for individualized diagnosis and treatment. These studies have highlighted some limitations of histopathological prognostic factors and suggested more standardized assessments. In a near future, AI may serve as a decision support for more consistent diagnoses

Single setting 3D MRI-US guided frozen section and focal cryoablation of the index lesion in low/intermediate risk prostate cancer

Objectives: To explore the reliability of frozen sections to diagnose prostate cancer (PCa) and to describe surgical steps of a 3D magnetic resonance imaging (MRI)– ultrasound (US)-guided prostate biopsy (PB) and focal cryoablation of the index lesion in a single setting procedure. Patients and Methods: Patients with suspicious PCa, based on prostatic specific antigen (PSA) value and on a PIRADS 4 or 5 single lesion, as well as the steadfastness of avoiding any kind of radical treatment, were considered for enrolment. IRB and written informed consent were obtained from the patients. The entire procedure was performed transperineally, in two consecutive surgical phases: 3D MRI–US-guided plus systematic template PB and real-time TRUS-guided focal cryoablation. Three cores were taken from the index lesion (one for frozen section and two for final pathology), three cores from the surrounding area and systematic sampling was performed for the rest of the gland. Focal cryoablation of the index lesion was performed once confirmation of PCa was obtained by means of frozen sections. Follow-up schedule included PSA test at 3-mo interval, MRI 3-mo and 1-yr postoperatively and prostate biopsy of the treated area at 1-yr. 31 Results: This report includes 14 patients with a minimum follow up time of 12 months. All patients were potent before treatment, complained no severe low urinary tract symptoms and denied consent to any radical treatment. PCa diagnosis was histologically confirmed in all patients by frozen sections. All other cores were negative. At final histology, there was a Gleason score upgrade in three patients, from 3+3 to 3+4. The postoperative course was uneventful and all patients were discharged on the first postoperative day. Mean PSA value decreased from 6.37 (baseline) to 0.83 ng/mL at 3-mo evaluation. Three-mo postoperative MRI images showed complete ablation of the index lesion in all patients. Urinary continence and erectile function were preserved in all patients, without clinically meaningful changes at EPIC questionnaire. At one-yr follow-up, eleven patients showed no signs of persistent or recurrent disease at MRI imaging and treated area biopsies; three patients had a suspicious area at MRI and they needed treatment for confirmed disease at biopsy. Conclusion: Single setting 3D MRI–US-guided frozen section and focal cryoablation of the index lesion could represent a step forward towards a “patient-tailored” minimally invasive approach to diagnosis and cure of low and intermediate risk PCa

Automatic detection of malignant prostatic gland units in cross-sectional microscopic images

Prostate cancer is the second most frequent cause of cancer deaths among men in the US. In the most reliable screening method, histological images from a biopsy are examined under a microscope by pathologists. In an early stage of prostate cancer, only relatively few gland units in a large region become malignant. Discovering such sparse malignant gland units using a microscope is a labor-intensive and error-prone task for pathologists. In this paper, we develop effective image segmentation and classification methods for automatic detection of malignant gland units in microscopic images. Both segmentation and classification methods are based on carefully designed feature descriptors, including color histograms and texton co-occurrence tables. © 2010 IEEE.published_or_final_versionThe 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, 26-29 September 2010. In Proceedings of the 17th ICIP, 2010, p. 1057-106

Digital image analysis for tumor cellularity and gleason grade to tumor volume analysis in prostate cancer

PURPOSE: This study was undertaken to compare HALO™ software image analysis measurements of cellularity with visual estimations from the pathologist and to outline a protocol for future experimental determinations of cellularity using HALO™. Secondly, this study investigated the clinically challenging prostate cancers of Gleason score 7 by analyzing a large database of radical prostatectomy (RP) specimens with regard to their Gleason grade composition and percentage tumor volume composition. The importance of these values of tumor cellularity, prostate volume, and tumor volume data were discussed in terms of future diagnostic endeavors. Finally, this study provided a brief background on prostate cancer, prostate cancer epidemiology, digital pathology, and the limitations and difficulties in the technological transition to digital pathology. All work for this study was done at Dana-Farber Cancer Institute (Boston, MA). METHODS: In the first part of this study, histological slides were acquired by radical prostatectomy (RP) and contained 12 tumor foci of varying degrees and sizes. These slides were scanned and imported into the HALO™ image analysis software. The tumor foci, previously demarcated by a pathologist, were annotated by hand in HALO™. An algorithm for image analysis was created by training classifiers to recognize and differentiate between epithelial tissue, stromal tissue, glass, and other. This process was accomplished by classifying 62 regions which were tested for accuracy before becoming the components of an algorithm to analyze the entire annotation layer. Each tumor focus was analyzed individually, and the results were exported into Microsoft® Excel from which relevant data were extracted. Cellularity was calculated by the percentage of tumor area that the algorithm characterized as epithelial. Cellularity values derived from HALO™ measurements for each tumor focus were compared with the visual estimations of cellularity provided by the pathologist using Pearson's correlation analysis. In the second part of this study, a database of 1386 slides containing tumors with Gleason scores between 6 and 9 was compiled from 140 RP cases. The average percentages of Gleason grades 3, 4, and 5 in each case were determined. The percentage of each slide that was occupied by the tumor was also averaged for each case, yielding an average percentage of tumor volume for each case. The average Gleason grade 3, 4, or 5 percentage for each case was plotted against the associated average tumor volume percentage of that case. The cases of Gleason score 7 (3+4, 4+3) were then isolated and plotted in a similar manner. Pearson’s correlation analysis was used to determine the degree of linear correlation between the two variables in each plot. Results: In the first part of this study, a statistically significant positive correlation between the cellularity estimations of the pathologist and the HALO™ cellularity measurements was found (r = 0.92, p < 0.01, n =12). In the second part of this study, there was a statistically significant negative correlation between average Gleason grade 3 percentage per case and average tumor volume percentage per case (r = -0.55, p <0.001, n = 140). There was also a statistically significant positive correlation between average Gleason grade 4 percentage per case and average tumor volume percentage per case (r = 0.55, p <0.001, n = 140). After slides containing Gleason score 6 (3+3) tumor were removed from the data, a statistically significant negative correlation remained between average Gleason grade 3 percentage per case and average tumor volume percentage per case (r = -0.51, p <0.001, n = 78), and a statistically significant positive correlation remained between average Gleason grade 4 percentage per case and average tumor volume percentage per case (r = 0.5, p <0.001, n = 101). A statistically significant relationship between average Gleason grade 5 percentage and average tumor volume percentage was not found (r = 0.32, p = 0.14, n = 23). CONCLUSIONS: In the first part of this study, the strong positive correlation between HALO™ cellularity values and visual estimations by the pathologist suggests that image analysis may be an effective tool for determining cellularity in digital histological images. More research using larger sample sizes is recommended to further validate the correlation between algorithm-derived cellularity from HALO™ and visual estimation by the pathologist. In the second part of this study, it appears that the volume of prostate tumors of Gleason score 7 may have prognostic power, considering that an increased percentage composition of Gleason grade 4 correlated with larger tumor volumes. Because this result may have significant clinical implications, further research specifically on tumors of Gleason score 7 is suggested to verify this relationship

Multiparametric 3 Tesla magnetic resonance imaging as a clinical tool to characterize prostate cancer

Scientists have come a long way in understanding prostate cancer as a disease and how its progression affects the men who develop it. Prostate adenocarcinoma may be present without causing clinical symptoms. Prostate cancer may metastasize, which increases the likelihood of fatality. The cause of the disease is still not completely clear, but genetics, race, tissue damage, history of previous infections, diet, and environmental influences appear to play a role in its development. Magnetic resonance imaging (MRI) has become an excellent clinical tool to characterize prostate cancer without the use of ionizing radiation or surgery. It is concluded that MRI is the optimal imaging modality to achieve detection, characterization, and staging of intracapsular and extracapsular prostate disease. The advances in MRI technology, particularly 3 Tesla, allows for reduced surgical intervention thus improving quality of life for patients with the disease

Prognostic factors in prostate cancer

Prognostic factors in organ confined prostate cancer will reflect survival after surgical radical prostatectomy. Gleason score, tumour volume, surgical margins and Ki-67 index have the most significant prognosticators. Also the origins from the transitional zone, p53 status in cancer tissue, stage, and aneuploidy have shown prognostic significance. Progression-associated features include Gleason score, stage, and capsular invasion, but PSA is also highly significant. Progression can also be predicted with biological markers (E-cadherin, microvessel density, and aneuploidy) with high level of significance. Other prognostic features of clinical or PSA-associated progression include age, IGF-1, p27, and Ki-67. In patients who were treated with radiotherapy the survival was potentially predictable with age, race and p53, but available research on other markers is limited. The most significant published survival-associated prognosticators of prostate cancer with extension outside prostate are microvessel density and total blood PSA. However, survival can potentially be predicted by other markers like androgen receptor, and Ki-67-positive cell fraction. In advanced prostate cancer nuclear morphometry and Gleason score are the most highly significant progression-associated prognosticators. In conclusion, Gleason score, capsular invasion, blood PSA, stage, and aneuploidy are the best markers of progression in organ confined disease. Other biological markers are less important. In advanced disease Gleason score and nuclear morphometry can be used as predictors of progression. Compound prognostic factors based on combinations of single prognosticators, or on gene expression profiles (tested by DNA arrays) are promising, but clinically relevant data is still lacking