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Real-time diagnosis and Gleason grading of prostate core needle biopsies using nonlinear microscopy

ABSTRACT: Rapid histologic assessment of fresh prostate biopsies may reduce patient anxiety, aid in biopsy sampling, and enable specimen triaging for molecular/genomic analyses and research that could benefit from fresh tissue analysis. Nonlinear microscopy (NLM) is a fluorescence microscopy technique that can produce high-resolution images of freshly excised tissue resembling formalin-fixed paraffin-embedded (FFPE) H&E. NLM enables evaluation of tissue up to ~100 µm below the surface, analogous to serial sectioning, but without requiring microtome sectioning. One hundred and seventy biopsies were collected from 63 patients who underwent in-bore MRI or MRI/ultrasound fusion biopsy procedures. Biopsies were stained in acridine orange and sulforhodamine 101, a nuclear and cytoplasmic/stromal fluorescent dye, for 45 s. Genitourinary pathologists evaluated the biopsies using NLM by translating the biopsies in real time to areas of interest and NLM images were recorded. After NLM evaluation, the biopsies were processed for standard FFPE H&E and similarities and differences between NLM and FFPE H&E were investigated. Accuracies of NLM diagnoses and Gleason scores were calculated using FFPE histology as the gold standard. Pathologists achieved a 92.4% sensitivity (85.0–96.9%, 95% confidence intervals) and 100.0% specificity (94.3–100.0%) for detecting carcinoma compared to FFPE histology. The agreement between the Grade Group determined by NLM versus FFPE histology had an unweighted Cohen’s Kappa of 0.588. The average NLM evaluation time was 2.10 min per biopsy (3.08 min for the first 20 patients, decreasing to 1.54 min in subsequent patients). Further studies with larger patient populations, larger number of pathologists, and multiple institutions are warranted. NLM is a promising method for future rapid evaluation of prostate needle core biopsies.

SUBMITTER: Cahill L

PROVIDER: S-EPMC8560363 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Despite revisions in 2005 and 2014, the Gleason prostate cancer (PCa) grading system still has major deficiencies. Combining of Gleason scores into a three-tiered grouping (6, 7, 8-10) is used most frequently for prognostic and therapeutic purposes. The lowest score, assigned 6, may be misunderstood as a cancer in the middle of the grading scale, and 3+4=7 and 4+3=7 are often considered the same prognostic group.To verify that a new grading system accurately produces a smaller number of grades with the most significant prognostic differences, using multi-institutional and multimodal therapy data.Between 2005 and 2014, 20,845 consecutive men were treated by radical prostatectomy at five academic institutions; 5501 men were treated with radiotherapy at two academic institutions.Outcome was based on biochemical recurrence (BCR). The log-rank test assessed univariable differences in BCR by Gleason score. Separate univariable and multivariable Cox proportional hazards used four possible categorizations of Gleason scores.In the surgery cohort, we found large differences in recurrence rates between both Gleason 3+4 versus 4+3 and Gleason 8 versus 9. The hazard ratios relative to Gleason score 6 were 1.9, 5.1, 8.0, and 11.7 for Gleason scores 3+4, 4+3, 8, and 9-10, respectively. These differences were attenuated in the radiotherapy cohort as a whole due to increased adjuvant or neoadjuvant hormones for patients with high-grade disease but were clearly seen in patients undergoing radiotherapy only. A five-grade group system had the highest prognostic discrimination for all cohorts on both univariable and multivariable analysis. The major limitation was the unavoidable use of prostate-specific antigen BCR as an end point as opposed to cancer-related death.The new PCa grading system has these benefits: more accurate grade stratification than current systems, simplified grading system of five grades, and lowest grade is 1, as opposed to 6, with the potential to reduce overtreatment of PCa.We looked at outcomes for prostate cancer (PCa) treated with radical prostatectomy or radiation therapy and validated a new grading system with more accurate grade stratification than current systems, including a simplified grading system of five grades and a lowest grade is 1, as opposed to 6, with the potential to reduce overtreatment of PCa.

Project description:Background and objectiveGleason grading system is currently the clinical gold standard for determining prostate cancer aggressiveness. Prostate cancer is typically classified into one of 5 different categories with 1 representing the most indolent disease and 5 reflecting the most aggressive disease. Grades 3 and 4 are the most common and difficult patterns to be discriminated in clinical practice. Even though the degree of gland differentiation is the strongest determinant of Gleason grade, manual grading is subjective and is hampered by substantial inter-reader disagreement, especially with regard to intermediate grade groups.MethodsTo capture the topological characteristics and the degree of connectivity between nuclei around the gland, the concept of Homology Profile (HP) for prostate cancer grading is presented in this paper. HP is an algebraic tool, whereby, certain algebraic invariants are computed based on the structure of a topological space. We utilized the Statistical Representation of Homology Profile (SRHP) features to quantify the extent of glandular differentiation. The quantitative characteristics which represent the image patch are fed into a supervised classifier model for discrimination of grade patterns 3 and 4.ResultsOn the basis of the novel homology profile, we evaluated 43 digitized images of prostate biopsy slides annotated for regions corresponding to Grades 3 and 4. The quantitative patch-level evaluation results showed that our approach achieved an Area Under Curve (AUC) of 0.96 and an accuracy of 0.89 in terms of discriminating Grade 3 and 4 patches. Our approach was found to be superior to comparative methods including handcrafted cellular features, Stacked Sparse Autoencoder (SSAE) algorithm and end-to-end supervised learning method (DLGg). Also, slide-level quantitative and qualitative evaluation results reflect the ability of our approach in discriminating Gleason Grade 3 from 4 patterns on H&E tissue images.ConclusionsWe presented a novel Statistical Representation of Homology Profile (SRHP) approach for automated Gleason grading on prostate biopsy slides. The most discriminating topological descriptions of cancerous regions for grade 3 and 4 in prostate cancer were identified. Moreover, these characteristics of homology profile are interpretable, visually meaningful and highly consistent with the rubric employed by pathologists for the task of Gleason grading.

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Real-time diagnosis and Gleason grading of prostate core needle biopsies using nonlinear microscopy

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