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Modern Pathology : An Official Journal... Oct 2023We have developed an artificial intelligence (AI)-based digital pathology model for the evaluation of histologic features related to eosinophilic esophagitis (EoE). In...
We have developed an artificial intelligence (AI)-based digital pathology model for the evaluation of histologic features related to eosinophilic esophagitis (EoE). In this study, we evaluated the performance of our AI model in a cohort of pediatric and adult patients for histologic features included in the Eosinophilic Esophagitis Histologic Scoring System (EoEHSS). We collected a total of 203 esophageal biopsy samples from patients with mucosal eosinophilia of any degree (91 adult and 112 pediatric patients) and 10 normal controls from a prospectively maintained database. All cases were assessed by a specialized gastrointestinal (GI) pathologist for features in the EoEHSS at the time of original diagnosis and rescored by a central GI pathologist (R.K.M.). We subsequently analyzed whole-slide image digital slides using a supervised AI model operating in a cloud-based, deep learning AI platform (Aiforia Technologies) for peak eosinophil count (PEC) and several histopathologic features in the EoEHSS. The correlation and interobserver agreement between the AI model and pathologists (Pearson correlation coefficient [r] = 0.89 and intraclass correlation coefficient [ICC] = 0.87 vs original pathologist; r = 0.91 and ICC = 0.83 vs central pathologist) were similar to the correlation and interobserver agreement between pathologists for PEC (r = 0.88 and ICC = 0.91) and broadly similar to those for most other histologic features in the EoEHSS. The AI model also accurately identified PEC of >15 eosinophils/high-power field by the original pathologist (area under the curve [AUC] = 0.98) and central pathologist (AUC = 0.98) and had similar AUCs for the presence of EoE-related endoscopic features to pathologists' assessment. Average eosinophils per epithelial unit area had similar performance compared to AI high-power field-based analysis. Our newly developed AI model can accurately identify, quantify, and score several of the main histopathologic features in the EoE spectrum, with agreement regarding EoEHSS scoring which was similar to that seen among GI pathologists.
PubMed: 37474003
DOI: 10.1016/j.modpat.2023.100285 -
Pathology, Research and Practice Jan 2024Diagnostic workup of cancer patients is highly reliant on the science of pathology using cytopathology, histopathology, and other ancillary techniques like... (Review)
Review
Diagnostic workup of cancer patients is highly reliant on the science of pathology using cytopathology, histopathology, and other ancillary techniques like immunohistochemistry and molecular cytogenetics. Data processing and learning by means of artificial intelligence (AI) has become a spearhead for the advancement of medicine, with pathology and laboratory medicine being no exceptions. ChatGPT, an artificial intelligence (AI)-based chatbot, that was recently launched by OpenAI, is currently a talk of the town, and its role in cancer diagnosis is also being explored meticulously. Pathology workflow by integration of digital slides, implementation of advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond a microscopic slide and enables effective integration, assimilation, and utilization of knowledge that is beyond human limits and boundaries. Despite of it's numerous advantages in the pathological diagnosis of cancer, it comes with several challenges like integration of digital slides with input language parameters, problems of bias, and legal issues which have to be addressed and worked up soon so that we as a pathologists diagnosing malignancies are on the same band wagon and don't miss the train.
Topics: Humans; Artificial Intelligence; Neoplasms; Algorithms; Cytogenetics; Pathologists
PubMed: 38056135
DOI: 10.1016/j.prp.2023.154989 -
Pathologie (Heidelberg, Germany) Feb 2024Awards provide their recipients with fame and recognition, and subsequently facilitate publications and acquisition of external funding through increased visibility. We...
BACKGROUND
Awards provide their recipients with fame and recognition, and subsequently facilitate publications and acquisition of external funding through increased visibility. We hypothesize that despite increasing representation in pathology, women are underrepresented as awardees in the German Society of Pathology and consequently there is an associated imbalance between genders.
MATERIAL AND METHODS
Published data from the German Society of Pathology on female awardees during the period from 2000 to 2022 were examined. Only awards specifically dedicated to the field of pathology were considered. In addition, the publicly available data of the German Medical Association on gender and age distribution of pathologists in Germany were considered as reference material.
RESULTS
A total of six different awards were included in the analysis. Among the 143 awardees across 150 individual awards in the period from 2000 to 2022, 55 (38.4%) of the awardees were female compared to an average percentage of 31% of women working in the field of pathology in the 23-year period under consideration. Consequently, female awardees in pathology were not underrepresented when compared to the national figures on the proportion of women in the field of pathology. However, the distribution of female awardees across individual awards suggests that women were increasingly represented in less prestigious research and doctoral awards, while men made up a large proportion of awardees of honorary awards (0% women) and prestigious awards (17% women).
Topics: Humans; Male; Female; Societies, Medical; Physicians; Publications; Awards and Prizes; Pathologists
PubMed: 37861701
DOI: 10.1007/s00292-023-01239-9 -
Archives of Pathology & Laboratory... Jan 2024Clinical management of endometrial carcinoma largely depends on the morphologic parameters ascertained based on the pathologic evaluation of surgical resection... (Review)
Review
CONTEXT.—
Clinical management of endometrial carcinoma largely depends on the morphologic parameters ascertained based on the pathologic evaluation of surgical resection specimens. However, there are numerous controversial and nonstandardized aspects of both the macroscopic and microscopic assessment of surgical specimens, including grossing, adequate sampling, diagnosis, staging, reporting, and ancillary testing.
OBJECTIVE.—
To provide a comprehensive practical review of standardized grossing, key morphologic findings for reporting and staging, and diagnostic and prognostic use of ancillary testing in endometrial carcinomas.
DATA SOURCES.—
The existing literature, recommendations of the International Society of Gynecological Pathologists, and specialty consensus guidelines.
CONCLUSIONS.—
This review article summarizes important aspects of the grossing and sampling of surgical resection specimens for microscopic examination, key morphologic parameters that are required for reporting and staging, and morphologic features and immunoprofiles helpful in the differential diagnosis of low-grade and high-grade endometrial carcinomas, as well as the current status of the molecular classification of endometrial carcinoma and human epidermal growth factor receptor 2 testing in serous carcinoma. The information presented herein can be helpful in overcoming diagnostic challenges and issues related to the pathology reporting of endometrial carcinoma to practicing anatomic pathologists.
Topics: Female; Humans; Endometrial Neoplasms; Gynecology; Prognosis; Societies, Medical; Pathologists
PubMed: 36943242
DOI: 10.5858/arpa.2022-0280-RA -
ESMO Open Aug 2023Biomarker tests in lung cancer have been traditionally ordered by the treating oncologist upon confirmation of an appropriate pathological diagnosis. The delay this...
Biomarker tests in lung cancer have been traditionally ordered by the treating oncologist upon confirmation of an appropriate pathological diagnosis. The delay this introduces prolongs yet further what is already a complex, multi-stage, pre-treatment pathway and delays the start of first-line systemic treatment, which is crucially informed by the results of such analysis. Reflex testing, in which the responsibility for testing for an agreed range of biomarkers lies with the pathologist, has been shown to standardise and expedite the process. Twelve experts discussed the rationale and considerations for implementing reflex testing as standard clinical practice.
Topics: Humans; Carcinoma, Non-Small-Cell Lung; Lung Neoplasms; Consensus; Pathologists; Biomarkers, Tumor; Reflex
PubMed: 37356358
DOI: 10.1016/j.esmoop.2023.101587 -
EClinicalMedicine May 2024The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and...
An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study.
BACKGROUND
The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value.
METHODS
In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed.
FINDINGS
In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64-73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953-0.998) to 0.992 (0.982-1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908-1.000]) surpassed that of two junior pathologists (0.862 [0.746-0.939], = 0.023; 0.879 [0.767-0.950], = 0.041) by 10-12% and showed no difference to that of two senior pathologists (both 0.983 [0.908-1.000], both > 0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both = 0.041) to the level of senior pathologists (both > 0.99), and substantially reduced the four pathologists' slide reviewing time (-31%, < 0.0001; -34%, < 0.0001; -29%, < 0.0001; and -27%, = 0.00031).
INTERPRETATION
ProCaLNMD demonstrated high diagnostic capabilities for identifying LNM in prostate cancer, reducing the likelihood of missed diagnoses by pathologists and decreasing the slide reviewing time, highlighting its potential for clinical application.
FUNDING
National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, the Guangdong Provincial Clinical Research Centre for Urological Diseases, and the Science and Technology Projects in Guangzhou.
PubMed: 38618206
DOI: 10.1016/j.eclinm.2024.102580 -
Archives of Pathology & Laboratory... Aug 2023With the adoption of Epic/Beaker at our institution, surgical pathology specimens are assigned a Current Procedural Terminology (CPT) charge code at the time of... (Review)
Review
CONTEXT.—
With the adoption of Epic/Beaker at our institution, surgical pathology specimens are assigned a Current Procedural Terminology (CPT) charge code at the time of accessioning, and pathologists have been made responsible for verifying the accuracy of the code before signing out the case.
OBJECTIVE.—
To determine with what frequency attending pathologists reassigned the correct charge code to a specimen when the code assigned at accessioning was incorrect, as well as to estimate the potential financial impact of missed changes.
DESIGN.—
We reviewed all specimens received for frozen section during a 7-month period, identified specimens where the default charge code that our departmental protocol assigns at frozen section (88305) was incorrect, and assessed the rate of successful code change by pathologists and the potential financial cost of each missed change.
RESULTS.—
Three hundred fifty-two of 2191 frozen section specimens (16%) required a change in the 88305 charge code. The codes for 195 specimens (55%) were correctly changed by the attending pathologist, while 157 (45%) were not changed (149) or were changed to an incorrect charge code (8). Individual pathologist change rates ranged from 0% to 100%, with a mean and median change rate of 43% and 24%, respectively. Using average code reimbursements at our institution, the loss in revenue from the 157 missed and incorrect frozen section changes was estimated at $13 788 ($1970 per month).
CONCLUSIONS.—
Pathologists showed highly variable rates of correcting CPT charge codes when the incorrect code had been previously assigned to a case, with associated loss of revenue from missed and incorrect code changes.
Topics: Humans; Frozen Sections; Pathologists; Pathology, Surgical
PubMed: 36287188
DOI: 10.5858/arpa.2022-0158-OA -
Biomedicines Oct 2023Renal cell carcinoma is a significant health burden worldwide, necessitating accurate and efficient diagnostic methods to guide treatment decisions. Traditional... (Review)
Review
Renal cell carcinoma is a significant health burden worldwide, necessitating accurate and efficient diagnostic methods to guide treatment decisions. Traditional pathology practices have limitations, including interobserver variability and time-consuming evaluations. In recent years, digital pathology tools emerged as a promising solution to enhance the diagnosis and management of renal cancer. This review aims to provide a comprehensive overview of the current state and potential of digital pathology in the context of renal cell carcinoma. Through advanced image analysis algorithms, artificial intelligence (AI) technologies facilitate quantification of cellular and molecular markers, leading to improved accuracy and reproducibility in renal cancer diagnosis. Digital pathology platforms empower remote collaboration between pathologists and help with the creation of comprehensive databases for further research and machine learning applications. The integration of digital pathology tools with other diagnostic modalities, such as radiology and genomics, enables a novel multimodal characterization of different types of renal cell carcinoma. With continuous advancements and refinement, AI technologies are expected to play an integral role in diagnostics and clinical decision-making, improving patient outcomes. In this article, we explored the digital pathology instruments available for clear cell, papillary and chromophobe renal cancers from pathologist and data analyst perspectives.
PubMed: 38001875
DOI: 10.3390/biomedicines11112875 -
Modern Pathology : An Official Journal... Apr 2024We review B-cell neoplasms in the 5th edition of the World Health Organization classification of hematolymphoid tumors (WHO-HEM5). The revised classification is based on... (Review)
Review
We review B-cell neoplasms in the 5th edition of the World Health Organization classification of hematolymphoid tumors (WHO-HEM5). The revised classification is based on a multidisciplinary approach including input from pathologists, clinicians, and other experts. The WHO-HEM5 follows a hierarchical structure allowing the use of family (class)-level definitions when defining diagnostic criteria are partially met or a complete investigational workup is not possible. Disease types and subtypes have expanded compared with the WHO revised 4th edition (WHO-HEM4R), mainly because of the expansion in genomic knowledge of these diseases. In this review, we focus on highlighting changes and updates in the classification of B-cell lymphomas, providing a comparison with WHO-HEM4R, and offering guidance on how the new classification can be applied to the diagnosis of B-cell lymphomas in routine practice.
Topics: Humans; Lymphoma, B-Cell; World Health Organization; Pathologists; Hematologic Neoplasms
PubMed: 38309432
DOI: 10.1016/j.modpat.2024.100441 -
Indian Journal of Pathology &... Jul 2023Medication resins are often encountered in gastrointestinal biopsy specimens of patients being treated for renal compromise. As important as they are for the electrolyte...
Medication resins are often encountered in gastrointestinal biopsy specimens of patients being treated for renal compromise. As important as they are for the electrolyte equilibrium of the patients, they often come with a cost of fatal but reversible damage to the gastrointestinal tract. This often manifests as inflammatory bowel disease in the affected individuals. This misleading manifestation coupled with the lack of patient history further masks resin-related colitis from a pathologist's eyes. Through this report, we convey how meticulous history-taking, representative endoscopic sampling, and recognition under the microscope are vital for timely reporting in conditions like this.
PubMed: 38391327
DOI: 10.4103/ijpm.ijpm_627_22