Extracting structured information from unstructured histopathology reports using generative pre-trained transformer 4 (GPT-4).

Deep learning applied to whole-slide histopathology images (WSIs) has the potential to enhance precision oncology and alleviate the workload of experts. However, developing these models necessitates large amounts of data with ground truth labels, which can be both time-consuming and expensive to obtain. Pathology reports are typically unstructured or poorly structured texts, and efforts to implement structured reporting templates have been unsuccessful, as these efforts lead to perceived extra workload. In this study, we hypothesised that large language models (LLMs), such as the generative pre-trained transformer 4 (GPT-4), can extract structured data from unstructured plain language reports using a zero-shot approach without requiring any re-training. We tested this hypothesis by utilising GPT-4 to extract information from histopathological reports, focusing on two extensive sets of pathology reports for colorectal cancer and glioblastoma. We found a high concordance between LLM-generated structured data and human-generated structured data. Consequently, LLMs could potentially be employed routinely to extract ground truth data for machine learning from unstructured pathology reports in the future. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Extracting lung cancer staging descriptors from pathology reports: A generative language model approach.

BACKGROUND: In oncology, electronic health records contain textual key information for the diagnosis, staging, and treatment planning of patients with cancer. However, text data processing requires a lot of time and effort, which limits the utilization of these data. Recent advances in natural language processing (NLP) technology, including large language models, can be applied to cancer research. Particularly, extracting the information required for the pathological stage from surgical pathology reports can be utilized to update cancer staging according to the latest cancer staging guidelines. OBJECTIVES: This study has two main objectives. The first objective is to evaluate the performance of extracting information from text-based surgical pathology reports and determining pathological stages based on the extracted information using fine-tuned generative language models (GLMs) for patients with lung cancer. The second objective is to determine the feasibility of utilizing relatively small GLMs for information extraction in a resource-constrained computing environment. METHODS: Lung cancer surgical pathology reports were collected from the Common Data Model database of Seoul National University Bundang Hospital (SNUBH), a tertiary hospital in Korea. We selected 42 descriptors necessary for tumor-node (TN) classification based on these reports and created a gold standard with validation by two clinical experts. The pathology reports and gold standard were used to generate prompt-response pairs for training and evaluating GLMs which then were used to extract information required for staging from pathology reports. RESULTS: We evaluated the information extraction performance of six trained models as well as their performance in TN classification using the extracted information. The Deductive Mistral-7B model, which was pre-trained with the deductive dataset, showed the best performance overall, with an exact match ratio of 92.24% in the information extraction problem and an accuracy of 0.9876 (predicting T and N classification concurrently) in classification. CONCLUSION: This study demonstrated that training GLMs with deductive datasets can improve information extraction performance, and GLMs with a relatively small number of parameters at approximately seven billion can achieve high performance in this problem. The proposed GLM-based information extraction method is expected to be useful in clinical decision-making support, lung cancer staging and research.

Examining the Completeness of Breast Cancer Pathology Reports Registered in the Population-Based Cancer Registration System in Iran during 2016 to 2018.

Background: Ensuring the comprehensive and accurate representation of data within cancer registries holds paramount significance across various facets of public health decision-making. This study delves into the evaluation of data completeness in breast cancer (BC) pathology reports within a population-based cancer registration system in Iran, spanning the period from 2016 to 2018. Methods: Employing a retrospective and descriptive analytical approach, we harnessed secondary data extracted from pathology reports encompassing breast cancer diagnoses, which were duly recorded in the Integrated Cancer Information Management System database during 2016-2018. A total of 4000 pathology reports were thoughtfully selected from each of the three years. The spectrum of pathology information encompassed tumor type, site grade, size (T), and involvement of lymph nodes (N). Summary statistics were provided as percentages of categorical variables and mean with standard deviation of continuous variables. A comparison of categorical variables was performed using the Chi-squared test. Results: The participants' mean age was 51.8±12.5 years. Among the 12,000 studied patients, 5744 (47.9%) were ≤ 50 years old, 5233 (43.6%) were aged 50-69 years, and 1023 (8.5%) were >60 years old. The completeness of BC pathology reports varied for different variables. Interestingly, the completeness of these variables increased with older age groups. The proportion of specific tumor types differed significantly among age groups (P = 0.001). Notably, the prevalence of invasive ductal carcinoma was higher in the ≤ 50 years age group compared to the older cohorts. Likewise, notable variations in tumor sizes were observed (P = 0.009), with a higher prevalence of missing tumor size data noted in the age group ≤ 50 years. On the other hand, pathologic T stage also demonstrated age-dependent variations (P = 0.014), indicating a higher prevalence of missing stages in the ≤ 50 years age group. Finally, tumor grade exhibited a statistically significant difference (P < 0.001), with a higher proportion of grade 1 tumors observed in the 50-69 years age group. Conclusion: Tumor grade had the highest completeness rate, while tumor size, pathologic T stage, and pathologic N stage had the lowest. Therefore, a good understanding of completeness of pathology reports, as well as improvement in the registration of stage, integrated system at the national level for BC is warranted.

Pathology Reports: Discrepancy Patterns of Second Opinions in a Referral Cancer Center.

OBJECTIVE: To evaluate the diagnostic mismatch (discrepancy) of pathology reports in consulted specimens referred for second opinion. MATERIALS AND METHODS: This cross-sectional study was conducted at a major cancer center, Omid Hospital. In this study, 350 primary pathology reports and 350 reviewed pathology reports were extracted from the archives of Omid Hospital from 2011 to 2020 and assessed in terms of the extent of discrepancy, by two pathologists and one oncologist. The required data for each sample were entered into a checklist and then statistically analyzed. Cases with the same diagnosis on both reports were assigned to the matched group and the rest were assigned to the minor or major mismatch (discrepancy) group. Minor mismatches included changes in diagnosis that did not lead to changes in treatment (may lead to changes in prognosis or provide additional information to the oncologist) and major mismatches included changes in diagnosis leading to changes in treatment or remedies. RESULTS: Two hundred seven cases (59.1%) out of three hundred fifty cases had concordant results between the diagnosis of the first pathologist and the reviewing pathologist. In one hundred forty-three cases (40.9%) mismatch (discrepancy) was observed, including eighty- two cases (23.4%) with minor mismatches (discrepancy) and sixty-one cases (17.4%) with major mismatches (discrepancy). In the major mismatch group, fifteen cases (4.3%) changed from malignant to benign, eighteen cases (5.1%) changed from benign to malignant, two cases (0.6%) changed from one stage to another stage of Disease and twenty-six cases (7.4%) had changes in the type of malignancy. In this study, it was found that there was no significant relationship between anatomical areas of sampling and diagnostic mismatch (p = 0.254). The study also found that the rate of diagnostic mismatch in specimens obtained by resection or excisional biopsy was greater than that of small biopsies (eighty cases (22.8%) and sixty-two cases (17.7%, respectively)). There was no significant relationship in this regard (p = 0.077). CONCLUSION: Compared to most similar studies, the present study reported the highest discrepancy between the diagnosis of the first pathologist and the reviewing pathologist (40.9%).

Epidemiology of canine mammary tumours on the Canary Archipelago in Spain.

BACKGROUND: Mammary gland tumours are the most frequently diagnosed tumours in the female dogs but just a few studies have analysed their epidemiology. Therefore, we set out to describe the epidemiology of canine mammary cancer in the Canary Archipelago, Spain. We analysed a pathology tumour registry (PTR) and identified 7362 samples obtained from 5240 female dogs resident on the Canary Archipelago during an 18-year period (2003-2020). Using a case-control study design, we compared mammary tumour affected dogs with the Canarian canine population registry in order to elucidate the breed associations for these tumours. RESULTS: The frequency of a diagnosis of mammary tumours relative to all tumour diagnoses in female dogs decreased during the study period from 62.7% to 48.9%. Contemporaneously, the proportion of dogs diagnosed with mammary tumours who were also neutered increased from 13.6% to 26.9%. There was a negative correlation (R = -0.84) between these changes. Additional findings were that: the proportion of female dogs diagnosed with multiple tumours increased by 23.5% and that the proportion of malignant tumours 89.2% diagnosed has remained stable through the period. Benign mammary tumours were diagnosed at younger ages (9.2 years old) than carcinomas (9.7 years old) and sarcomas (10.4 years old). Epithelial mammary tumours were diagnosed at younger ages in entire female dogs. Samoyed, Schnauzer, Poodle, German Pinscher and Cocker Spaniel were the breeds with the highest odds-ratios (OR) in comparison with the reference (crossbreeds) while Miniature Pinscher, American Staffordshire Terrier, English Pointer as well as some local breeds such as the Canary Warren Hound and the Majorero had the lowest ORs. CONCLUSIONS: This study provides a description of the changing epidemiology of canine mammary cancer in the Canary Archipelago over the last two decades. We found high rates of CMT with a significant predominance of malignant tumours. Exact risk factors are uncertain, but a combination of environmental, regional socioeconomic affecting human and their pets, and animal management factors are likely to play a part. Specifically, neutering was negatively associated with the proportion of epithelial mammary gland tumours and breeds native to the region were at lower risk of mammary tumours. A deeper analysis of all these factors will facilitate a deeper understanding of the epidemiology of mammary gland tumours in both the canine and the human population.

Accurate pattern-based extraction of complex Gleason score expressions from pathology reports.

PURPOSE: The Gleason score is an important grading factor of prostate cancer. Gleason scores can be extracted from pathology report texts using regular expressions, but previously developed programmes have targeted only relatively simple Gleason score expressions. We developed a programme capable of extracting also complex expressions. The programme is relatively easy to adapt to other languages and datasets. METHODS: We developed and evaluated our regular expression-based programme using manually processed pathology reports of prostate cancer cases diagnosed in Finland in 2016-2017. Both simple and complex Gleason score expressions were targeted. We measured the performance of our programme using recall, precision, and the F1. The proportion of complex Gleason score expressions was estimated as the complement of the recall when only addition expressions (e.g. "Gleason 3 + 4") were targeted. RESULTS: The detection of values (scores and score components) is based on mandatory keywords before or after the value. The programme favours precision over recall by primarily allowing for lists of optional expressions between keyword-value pairs and only secondarily allowing for arbitrary expressions. The programme is straightforward to adapt to new datasets by modifying the lists of mandatory and optional expressions. The full and addition-only programmes had 92% (95% CI: [90%, 95%]) and 65% ([61%, 70%]) recall and high precision (98% [97%, 99%] and 100% [99%, 100%]), respectively. The estimated proportion of complex Gleason score expressions was 100-65 = 35%. CONCLUSIONS: Even complex Gleason score expressions can be extracted with high recall and precision using regular expressions. We recommend implementing automated Gleason score extraction where possible by adapting our validated programme.

Quality assurance in dermatopathology: A review of report amendments.

BACKGROUND: Systematic review of amended reports in surgical pathology has been recommended as a valuable exercise in promoting quality assurance and improvement. Examination of report amendments can identify defects in the surgical pathology process and inspire new approaches to decreasing error rates and improving overall patient care. METHODS: We performed a retrospective review of all amended dermatopathology reports over a 1.5-year period at a large academic institution. RESULTS: During the study period, 86 amended reports out of a total 7950 skin-specific reports were issued (1.08%). Of these amended reports, about 59% (51/86) were because of non-interpretative errors (eg, wrong site, chin vs shin, etc.) while 41% (35/86) were diagnostic misinterpretations. Of these 35, 24 were considered major diagnostic changes while six were minor. Five amendments provided additional diagnostic information. Of those amended reports with diagnostic misinterpretations, 14/35 involved melanocytic lesions, 8/35 involved non-melanoma skin cancers or keratinocyte atypia, 10/35 were inflammatory lesions and 3/35 involved other tumors. CONCLUSION: Our review points to several quality improvement areas that can be targeted to potentially avoid diagnostic errors in dermatopathology, including standardizing certain anatomic sites to prevent misidentification and seeking out clinicopathologic correlation in challenging melanocytic cases.

A Transparent and Adaptable Method to Extract Colonoscopy and Pathology Data Using Natural Language Processing.

Key variables recorded as text in colonoscopy and pathology reports have been extracted using natural language processing (NLP) tools that were not easily adaptable to new settings. We aimed to develop a reliable NLP tool with broad adaptability. During 1996-2016, Kaiser Permanente Northern California performed 401,566 colonoscopies with linked pathology. We randomly sampled 1000 linked reports into a Training Set and developed an NLP tool using SAS® PERL regular expressions. The NLP tool captured five colonoscopy and pathology variables: type, size, and location of polyps; extent of procedure; and quality of bowel preparation. We used a Validation Set (N = 3000) to confirm the variables' classifications using manual chart review as the reference. Performance of the NLP tool was assessed using the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen's κ. Cohen's κ ranged from 93 to 99%. The sensitivity and specificity ranged from 95 to 100% across all categories. For categories with prevalence exceeding 10%, the PPV ranged from 97% to 100% except for adequate quality of preparation (prevalence 92%), for which the PPV was 65%. For categories with prevalence below 10%, the PPVs ranged from 62% to 100%. NPVs ranged from 94% to 100% except for the "complete" extent of procedure, for which the NPV was 73%. Using information from a large community-based population, we developed a transparent and adaptable NLP tool for extracting five colonoscopy and pathology variables. The tool can be readily tested in other healthcare settings.

Guidelines of care for the management of primary cutaneous melanoma.

The incidence of primary cutaneous melanoma continues to increase each year. Melanoma accounts for the majority of skin cancer-related deaths, but treatment is usually curative following early detection of disease. In this American Academy of Dermatology clinical practice guideline, updated treatment recommendations are provided for patients with primary cutaneous melanoma (American Joint Committee on Cancer stages 0-IIC and pathologic stage III by virtue of a positive sentinel lymph node biopsy). Biopsy techniques for a lesion that is clinically suggestive of melanoma are reviewed, as are recommendations for the histopathologic interpretation of cutaneous melanoma. The use of laboratory, molecular, and imaging tests is examined in the initial work-up of patients with newly diagnosed melanoma and for follow-up of asymptomatic patients. With regard to treatment of primary cutaneous melanoma, recommendations for surgical margins and the concepts of staged excision (including Mohs micrographic surgery) and nonsurgical treatments for melanoma in situ, lentigo maligna type (including topical imiquimod and radiation therapy), are updated. The role of sentinel lymph node biopsy as a staging technique for cutaneous melanoma is described, with recommendations for its use in clinical practice. Finally, current data regarding pregnancy and melanoma, genetic testing for familial melanoma, and management of dermatologic toxicities related to novel targeted agents and immunotherapies for patients with advanced disease are summarized.

Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry.

SNOMED CT terminology is not backed by standard norms of encoding among pathologists. The vast number of concepts ordered in hierarchies and axes, together with the lack of rules of use, complicates the functionality of SNOMED CT for coding, extracting, and analyzing the data. Defining subgroups of SNOMED CT by discipline could increase its functionality. The challenge lies in how to choose the concepts to be included in a subset from a total of over 300,000. Besides, SNOMED CT does not cover daily need, as the clinical reality is dynamic and changing. To adapt SNOMED CT to needs in a flexible way, the possibility exists to create extensions. In Catalonia, most pathology departments have been migrating from SNOMED II to SNOMED CT in a bid to advance the development of the Catalan Pathology Registry, which was created in 2014 as a repository for all the pathological diagnoses. This article explains the methodology used to: (a) identify the clinico-pathological entities and the molecular diagnostic procedures not included in SNOMED CT; (b) define the theoretical subset and microglossary of pathology; (c) describe the SNOMED CT concepts used by pathologists of 1.17 million samples of the Catalan Pathology Registry; and (d) adapt the theoretical subset and the microglossary according to the actual use of SNOMED CT. Of the 328,365 concepts available for coding the diagnoses (326,732 in SNOMED CT and 1576 in Catalan extension), only 2% have been used. Combining two axes of SNOMED CT, body structure and clinical findings, has enabled coding most of the morphologies.

Design of HL7 FHIR Profiles for Pathology Reports Integrated with Pathology Images.

This paper describes the development of Health Level Seven Fast Healthcare Interoperability Resource (FHIR) profiles for pathology reports integrated with whole slide images and clinical data to create a pathology research database. A report template was designed to collect structured reports, enabling pathologists to select structured terms based on a checklist, allowing for the standardization of terms used to describe tumor features. We gathered and analyzed 190 non-small-cell lung cancer pathology reports in free text format, which were then structured by mapping the itemized vocabulary to FHIR observation resources, using international standard terminologies, such as the International Classification of Diseases, LOINC, and SNOMED CT. The resulting FHIR profiles were published as an implementation guide, which includes 25 profiles for essential data elements, value sets, and structured definitions for integrating clinical data and pathology images associated with the pathology report. These profiles enable the exchange of structured data between systems and facilitate the integration of pathology data into electronic health records, which can improve the quality of care for patients with cancer.

Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

Since the release of the DESTINY-Breast04 (DB-04) trial findings in June 2022, the field of pathology has seen a renaissance of HER2 as a predictive biomarker in breast cancer. The trial focused on patients with metastatic breast cancer who were classified as "HER2-low," i.e., those with immunohistochemistry (IHC) HER2 1 + or 2 + and negative in situ hybridization (ISH) results. The study revealed that treating these patients with trastuzumab deruxtecan (T-DXd) instead of the oncologist's chosen chemotherapy led to outstanding improvements in survival. This has challenged the existing binary HER2 pathological classification system, which categorized tumors as either positive (overexpression/amplification) or negative, as per the ASCO/CAP 2018 guideline reaffirmed by ASCO/CAP 2023 guideline update. Given that DB-04 excluded patients with HER2 IHC score 0 status, the results of the ongoing DB-06 trial may shed further light on the potential benefits of T-DXd therapy for these patients. Roughly half of all breast cancers are estimated to belong to the HER2-low category, which does not represent a distinct or specific subtype of cancer. Instead, it encompasses a diverse group of tumors that exhibit clinical, morphological, immunohistochemical, and molecular variations. However, HER2-low offers a distinctive biomarker status that identifies a specific therapeutic regimen (i.e., T-DXd) linked to a favorable prognosis in breast cancer. This unique association emphasizes the importance of accurately identifying these tumors. Differentiating between a HER2 IHC score 0 and score 1 + has not been clinically significant until now. To ensure accurate classification and avoid misdiagnosis, it is necessary to adopt standardized procedures, guidelines, and specialized training for pathologists in interpreting HER2 expression in the lower spectrum. Additionally, the utilization of artificial intelligence holds promise in supporting this endeavor. Here, we address the current state of the art and unresolved issues in assessing HER2-low status, with a particular emphasis on the score 0. We explore the dilemma surrounding the exclusion of HER2-zero patients from potentially beneficial therapy based on traditional HER2 testing. Additionally, we examine the clinical context, considering that DB-04 primarily involved heavily pretreated late-stage metastatic breast cancers. We also delve into emerging evidence suggesting that extrapolating HER2-low status from the original diagnosis may lead to misleading results. Finally, we provide recommendations for conducting high-quality testing and propose a standardized pathology report in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

Large language model answers medical questions about standard pathology reports.

This study aims to evaluate the feasibility of large language model (LLM) in answering pathology questions based on pathology reports (PRs) of colorectal cancer (CRC). Four common questions (CQs) and corresponding answers about pathology were retrieved from public webpages. These questions were input as prompts for Chat Generative Pretrained Transformer (ChatGPT) (gpt-3.5-turbo). The quality indicators (understanding, scientificity, satisfaction) of all answers were evaluated by gastroenterologists. Standard PRs from 5 CRC patients who received radical surgeries in Shanghai Changzheng Hospital were selected. Six report questions (RQs) and corresponding answers were generated by a gastroenterologist and a pathologist. We developed an interactive PRs interpretation system which allows users to upload standard PRs as JPG images. Then the ChatGPT's responses to the RQs were generated. The quality indicators of all answers were evaluated by gastroenterologists and out-patients. As for CQs, gastroenterologists rated AI answers similarly to non-AI answers in understanding, scientificity, and satisfaction. As for RQ1-3, gastroenterologists and patients rated the AI mean scores higher than non-AI scores among the quality indicators. However, as for RQ4-6, gastroenterologists rated the AI mean scores lower than non-AI scores in understanding and satisfaction. In RQ4, gastroenterologists rated the AI scores lower than non-AI scores in scientificity (P = 0.011); patients rated the AI scores lower than non-AI scores in understanding (P = 0.004) and satisfaction (P = 0.011). In conclusion, LLM could generate credible answers to common pathology questions and conceptual questions on the PRs. It holds great potential in improving doctor-patient communication.

Standardized molecular pathology workflow for ctDNA-based ESR1 testing in HR+/HER2- metastatic breast cancer.

Mutations in the estrogen receptor alpha gene (ESR1) can lead to resistance to endocrine therapy (ET) in hormone receptor-positive (HR+)/ HER2- metastatic breast cancer (MBC). ESR1 mutations can be detected in up to 40 % of patients pretreated with ET in circulating tumor DNA (ctDNA). Data from prospective randomized trials highlight those patients with HR+/HER2- MBC with detectable ESR1 mutations experience better outcomes when receiving novel selective estrogen receptor degraders (SERDs). There is a high need for optimizing ESR1 testing strategies on liquid biopsy samples in HR+/HER2- MBC, including a hugh quality workflow implementation and molecular pathology reporting standardization. Our manuscript aims to elucidate the clinical and biological rationale for ESR1 testing in MBC, while critically examining the currently available guidelines and recommendations for this specific type of molecular testing on ctDNA. The objective will extend to the critical aspects of harmonization and standardization, specifically focusing on the pathology laboratory workflow. Finally, we propose a clear and comprehensive model for reporting ESR1 testing results on ctDNA in HR+/HER2- MBC.

Improving Interdisciplinary Communication and Pathology Reporting for Head and Neck Cancer Resections: 3D Visualizations and Margin Reconciliation.

PURPOSE: Surgical pathology reports play an integral role in postoperative management of head and neck cancer patients. Pathology reports of complex head and neck resections must convey critical information to all involved clinicians. Previously, we demonstrated the utility of 3D specimen and defect scanning for communicating margin status and documenting the location of supplemental margins. We introduce a newly designed permanent pathology report which improves documentation of intraoperative margin mapping and extent of corresponding supplemental margins harvested. METHODS: We test the hypothesis that gaps in understanding exist for head and neck resection pathology reports across providers. A cross-sectional exploratory study using human-centered design was implemented to evaluate the existing permanent pathology report with respect to understanding margin status. Pathologists, surgeons, radiation oncologists, and medical oncologists from United States-based medical institutions were surveyed. The results supported a redesign of our surgical pathology template, incorporating 3D specimen / defect scans and annotated radiographic images indicating the location of inadequate margins requiring supplemental margins, or indicating frankly positive margins discovered on permanent section. RESULTS: Forty-seven physicians completed our survey. Analyzing surgical pathology reports, 28/47 (60%) respondents reported confusion whether re-excised supplemental margins reflected clear margins, 20/47 (43%) reported uncertainty regarding final margin status, and 20/47 (43%) reported the need for clarity regarding the extent of supplemental margins harvested intraoperatively. From this feedback, we designed a new pathology report template; 61 permanent pathology reports were compiled with this new template over a 12-month period. CONCLUSION: Feedback from survey respondents led to a redesigned permanent pathology report that offers detailed visual anatomic information regarding intraoperative margin findings and exact location/size of harvested supplemental margins. This newly designed report reconciles frozen and permanent section results and includes annotated radiographic images such that clinicians can discern precise actions taken by surgeons to address inadequate margins, as well as to understand the location of areas of concern that may influence adjuvant radiation planning.

An Incidental Fallopian Tube Focal Serous Tubal Intraepithelial Lesion (STIL) Discovered on a Postoperative Pathology Report Following Hysterectomy and Salpingectomy: A Case Report.

A focal serous tubal intraepithelial lesion (STIL) is a rare lesion found on fallopian tubes that are characterized by atypical epithelial cells exhibiting morphological abnormalities with the accumulation of mutant p53 proteins. The p53 gene is a tumor suppressor gene, and when mutated gives rise to mutant p53 proteins that promote cancer cell growth and survival. We present a case of a 47-year-old gravida 2, para 2002 (G2P2) female who presented to the outpatient clinic with bilateral lower quadrant abdominal pain and back pain of four years' duration. The patient's history included endometriosis with lysis of adhesions and gynecological laparoscopy, leiomyomata, infertility, ovarian cyst, dysmenorrhea, two full term births, and Essure implants used for contraception; her family history included maternal grandfather with breast cancer. Multiple fibroids and endometriosis were confirmed on pelvic ultrasound (US) and magnetic resonance imaging (MRI). Due to worsening pain, the patient chose to have an elective hysterectomy and Essure implant removal with bilateral salpingectomy. The postoperative pathology report revealed a right fallopian tube with a STIL. Multiple genetic mutations are known to contribute to the development of STILs including p53 and the breast cancer gene (BRCA). There are two BRCA genes, BRCA1 and BRCA2, that have many functions including producing proteins that repair damaged DNA. When mutated, this allows cells to divide and change rapidly, leading to certain types of cancer. Given the patient's family history of breast cancer, the patient was tested for BRCA1 and BRCA2 for which the results were negative. However, even without having a BRCA mutation that is known to increase the risk of ovarian, fallopian tube, and peritoneal cancers, STILs continue to pose an increased risk of high-grade serous ovarian carcinoma (HGSOC). This case demonstrates the reasoning behind prophylactic salpingectomies alongside hysterectomies and the significance of the postoperative pathology report from gynecological procedures.

[Improving the quality of histopathological examination of colorectal cancer specimens through standard protocol implementation]. / Zvýsení kvality histopatologického hodnocení preparátu kolorektálního karcinomu prostrednictvím zavedení standardního protokolu.

INTRODUCTION: Detailed, high-quality histopathological examination of colorectal carcinoma is an essential component of accurate disease staging. The aim of this study was to evaluate the influence of standard pathological protocol implementation on the quality of colorectal cancer specimen evaluation. MATERIAL AND METHODS: The standard protocol for colorectal cancer specimens evaluation was created on the basis of the NCCN guidelines for colorectal carcinoma and in accordance with the American Joint Committee on Cancer (AJCC) recommendations. The protocol has been implemented into the practice of University Hospital Ostrava since 1 January 2013. All patients who underwent resection for colorectal cancer in University Hospital Ostrava between 1 January 2011 and 30 June 2013 were included into the study. Histopathological reports (before and after protocol implementation) were analysed with a focus on the presence of the parameters being monitored; the differences underwent statistical analysis. RESULTS: In total, 235 patients who underwent resection of colorectal cancer (184 patients before and 51 patients after protocol implementation) were included into the study. The mean number of investigated lymph nodes was 12.5±6.3 (colon) and 12.6±6.2 (rectum) before protocol implementation. The mean number of lymph nodes was 15.0±4.6 (colon) and 16.8±6.7 (rectum) after protocol implementation; the differences are statistically significant. Before protocol implementation, the limit of 12 investigated lymph nodes was not reached in 49 patients with colon carcinoma (43.8%) and in 32 patients with rectal carcinoma (44.4%). Statistically significant improvement was noted after protocol implementation - the limit of 12 lymph nodes was not reached in 5 patients (18.5%) with colon and 4 patients (16.7%) with rectal carcinoma. There were also differences in the number of macroscopic mesorectal excision quality evaluation, circumferential resection margin reports and signs of microscopic tumour aggressiveness, in favour of histopathological reports after standard protocol implementation. CONCLUSIONS: Our retrospective study proved that the implementation of the standard protocol for colorectal cancer resection specimens leads to an improved quality of definitive histopathological reports.

One procedure-one report: the Re-Imagine Cytopathology Task Force position paper on small tissue biopsy triage in anatomic pathology.

INTRODUCTION: Endoscopic biopsy procedures increasingly generate multiple tissue samples from multiple sites, and frequently retrieve concurrent cytologic specimens and small core needle biopsies. There is currently lack of consensus in subspecialized practices as to whether cytopathologists or surgical pathologists should review such samples, and whether the pathology findings should be reported together or separately. MATERIALS AND METHODS: In December 2021, the American Society of Cytopathology convened the Re-Imagine Cytopathology Task Force to examine various workflows that would facilitate unified pathology reporting of concurrently obtained biopsies and improve clinical care. RESULTS AND CONCLUSIONS: This position paper summarizes the key points and highlights the advantages, challenges, and resources available to support the implementation of such workflows that result in "one procedure-one report".

A Standardized Pathology Report for Gastric Cancer: 2nd Edition.

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

A standardized pathology report for gastric cancer: 2nd edition.

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.