A crucial aspect of prostate cancer grading, especially in low- and intermediate-risk cancer, is the accurate identification of Gleason pattern 4 glands, which includes ill-formed or fused glands. However, there is notable inconsistency among pathologists in recognizing these glands, especially when mixed with pattern 3 glands. This inconsistency has significant implications for patient management and treatment decisions. Conversely, the recognition of glomeruloid and cribriform architecture has shown higher reproducibility. Cribriform architecture, in particular, has been linked to the worst prognosis among pattern 4 subtypes. Intraductal carcinoma of the prostate (IDC-P) is also associated with high-grade cancer and poor prognosis. Accurate identification, classification, and tumor size evaluation by pathologists are vital for determining patient treatment. This review emphasizes the importance of prostate cancer grading, highlighting challenges like distinguishing between pattern 3 and pattern 4 and the prognostic implications of cribriform architecture and intraductal proliferations. It also addresses the inherent grading limitations due to interobserver variability and explores the potential of computational pathology to enhance pathologist accuracy and consistency.
Humans ; Prostatic Neoplasms/pathology* ; Male ; Neoplasm Grading ; Prognosis ; Observer Variation ; Prostate/pathology* ; Reproducibility of Results

OBJECTIVE: To validate the effectiveness of a novel comprehensive classification for intertrochanteric fracture (ITF). METHODS: The study included 616 patients with ITF, including 279 males (45.29%) and 337 females (54.71%); the age ranged from 23 to 100 years, with an average of 72.5 years. Two orthopaedic residents (observers Ⅰ and Ⅱ) and two senior orthopaedic surgeons (observers Ⅲ and Ⅳ) were selected to classify the CT imaging data of 616 patients in a random order by using the AO/Orthopaedic Trauma Association (AO/OTA) classification of 1996/2007 edition, the AO/OTA classification of 2018 edition, and the novel comprehensive classification method at an interval of 1 month. Kappa consistency test was used to evaluate the intra-observer and inter-observer consistency of the three ITF classification systems. RESULTS: The inter-observer consistency of the three classification systems evaluated by 4 observers twice showed that the 3 classification systems had strong inter-observer consistency. Among them, the κ value of the novel comprehensive classification was higher than that of the AO/OTA classification of 1996/2007 edition and 2018 edition, and the experience of observers had a certain impact on the classification results, and the inter-observer consistency of orthopaedic residents was slightly better than that of senior orthopaedic surgeons. The intra-observer consistency of two evaluations of three classification systems by 4 observers showed that the consistency of the novel comprehensive classification was better for the other 3 observers, except that the consistency of observer Ⅳ in the AO/OTA classification of 2018 version was slightly higher than that of the novel comprehensive classification. The results showed that the novel comprehensive classification has higher repeatability, and the intra-observer consistency of senior orthopaedic surgeons was better than that of orthopaedic residents. CONCLUSION The novel comprehensive classification system has good intra- and inter-observer consistency, and has high validity in the classification of CT images of ITF patients; the experience of observers has a certain impact on the results of the three classification systems, and those with more experiences have higher intra-observer consistency.
Male ; Female ; Humans ; Young Adult ; Adult ; Middle Aged ; Aged ; Aged, 80 and over ; Observer Variation ; Reproducibility of Results ; Hip Fractures/surgery* ; Tomography, X-Ray Computed/methods* ; Radiography

INTRODUCTION: In view of the important role of the environment in improving population health, implementation of health promotion programmes is recommended in living and working environments. Assessing the prevalence of such community health-promoting practices is important to identify gaps and make continuous and tangible improvements to health-promoting environments. We aimed to evaluate the inter-rater reliability of a composite scorecard used to assess the prevalence of community health-promoting practices in Singapore. METHODS: Inter-rater reliability for the use of the composite health promotion scorecards was evaluated in eight residential zones in the western region of Singapore. The assessment involved three raters, and each zone was evaluated by two raters. Health-promoting practices in residential zones were assessed based on 44 measurable elements under five domains - community support and resources, healthy behaviours, chronic conditions, mental health and common medical emergencies - in the composite scorecard using weighted kappa. The strength of agreement was determined based on Landis and Koch's classification method. RESULTS: A high degree of agreement (almost perfect-to-perfect) was observed between both raters for the measurable elements from most domains and subdomains. An exception was observed for the community support and resources domain, where there was a lower degree of agreement between the raters for a few elements. CONCLUSION The composite scorecard demonstrated a high degree of reliability and yielded similar scores for the same residential zone, even when used by different raters.
Health Promotion ; Humans ; Observer Variation ; Public Health ; Reproducibility of Results ; Singapore

Objective: To evaluate the inter-observer agreement of the severity of oral epithelial dysplasia in oral leukoplakia, providing a theoretical basis for the development of a more objective grading system. Methods: This study included 60 digital pathological slides of oral leukoplakia from Oral Medicine Department of West China Hospital of Stomatology, Sichuan University, and 239 tissue microarray images of oral leukoplakia from State Key Laboratory of Oral Diseases, Sichuan University, to evaluate the agreement of grading. Besides, 1 000 patches were generated from the 60 digital pathological slides and were divided into 500 small-sized patches (224 pixel×224 pixel) and 500 large-sized patches (1 024 pixel×1 024 pixel), to evaluate the agreement of feature detection. Gradings and feature detections were completed by three pathological experts from the oral pathology departments of two Grade 3, Class A stomatological hospitals in China. Kappa coefficient was used to quantify the inter-observer agreement among pathologists. Results: Minimal agreement was found in the grading of oral epithelial dysplasia among pathologists (Kappa=0.30 in the pathological slide group, Kappa=0.30 in the tissue microarray group). None agreement was found in feature detection within the small-sized patches group (median Kappa=0.14 for architectural features, median Kappa=0.18 for cytological features), and minimal agreement was found in feature detection within the large-sized patches group (median Kappa=0.25 for architectural features, median Kappa=0.25 for cytological features). Conclusions: Generally, the agreement of grading and feature detection of oral epithelial dysplasia in oral leukoplakia is poor. Development of a more objective grading system of oral epithelial dysplasia based on artificial intelligence may be helpful to improve the agreement.
Artificial Intelligence ; China ; Humans ; Leukoplakia, Oral ; Observer Variation ; Precancerous Conditions

Objectives: To evaluate the diagnostic consistency of working lengths by observing endodontic files in root canals and periapical subtle structures in digital intraoral radiographs presented in two smartphones, a tablet and a laptop computer. Methods: A dried human skull embedded in an acrylic compound was used for exposing radiographs of the upper and lower second premolars and first molars with two endodontic files (Kerr files size 10 and 15) positioned to the full length of the roots or 1.5 mm short of apexes. A total of 100 radiographs were taken for each of the file sizes. Five observers were asked to assess all the 200 digital radiographs according to a 5-category scale in smartphone A (HUAWEI P9 Plus), smartphjone B (Apple iPhone 7), tablet (Apple iPad 2018) and laptop computer (Lenovo Thinkpad E480), respectively. The gold standard for receiver operating characteristic curve (ROC) analysis was determined with the endodontic Kerr file size 20. A total of 150 roots with files were radiographed, 75 of which with files reaching the radiographic apexes of the respective roots and 75 of which with files 1.5 mm short of the radiographic apexes for each endodontic file size. Results from ROC analysis was analyzed with one-way ANOVA and independent sample t test. Results: For the Kerr file size 10, the area under the ROC curve for laptop, tablet and two smartphones were 0.891±0.037, 0.869±0.037, 0.870±0.017 and 0.849±0.037, while for the Kerr file size 15 the ROC values were 0.957±0.02, 0.961±0.02, 0.961±0.01 and 0.961±0.02, respectively. There were no significant differences for diagnostic accuracy for observing endodontic file positions among digital radiographs presented in the two smartphones, one tablet and one laptop devices (endodontic file size 10: F=1.39, P=0.281; endodontic file size 15: F=0.05, P=0.985). A significant difference was found in the diagnostic accuracy of endodontic file positions between size 10 and 15 files in different display devices (t=-10.65, P<0.001). Conclusions: There was a high diagnostic consistency in the determination of working length and periapical subtle structures of roots by observing digital radiographs displayed on smartphones, tablet and laptop computer.
Dental Instruments ; Dental Pulp Cavity/diagnostic imaging* ; Electronics ; Humans ; Molar ; Observer Variation ; Root Canal Preparation

Objective To investigate the intra-and inter-observer reproducibility of iodine concentrations of abdominal parenchymal organs based on spectral CT.Methods The water-free iodine images of the venous phase were retrospectively obtained from 50 patients with abdominal dynamic spectral CT scans.The iodine concentrations were measured in the left,right and caudate lobes of liver,spleen,pancreas and bilateral kidneys.Intraclass correlation coefficient(ICC)and Bland-Altman plot were employed to analyze the intra-and inter-observer reproducibility.Results The intra-observer ICCs of the left,right and caudate lobes of liver,spleen,pancreas,and left and right kidneys were 0.938(0.894,0.965),0.932(0.884,0.961),0.939(0.895,0.965),0.947(0.909,0.970),0.912(0.851,0.949),0.946(0.906,0.969)and 0.907(0.842,0.946),which indicated good intra-observer reproducibility.The inter-observer ICCs of the left,right and caudate lobes of liver,spleen,pancreas,and left and right kidneys were 0.947(0.909,0.970),0.927(0.875,0.958),0.943(0.902,0.968),0.956(0.924,0.975),0.934(0.887,0.962),0.927(0.875,0.958)and 0.892(0.818,0.937),which indicated good inter-observer reproducibility.Bland-Altman plots presented that more than 95% points of the intra-observer differences located within 95% CI of limits of agreement for the caudate lobe of liver,spleen,pancreas and bilateral kidneys,which was same as inter-observer differences of the caudate lobe of liver,spleen and right kidney.Conclusion The iodine concentration measurement based on the spectral CT presented good intra-and inter-observer reproducibility for the caudate lobe of liver and spleen.
Humans ; Iodine ; Observer Variation ; Reproducibility of Results ; Retrospective Studies ; Tomography, X-Ray Computed

Cardiovascular disease (CVD) is considered a primary driver of global mortality and is estimated to be responsible for approximately 17.9 million deaths annually. Consequently, a substantial body of research related to CVD has developed, with an emphasis on identifying strategies for the prevention and effective treatment of CVD. In this review, we critically examine the existing CVD literature, and specifically highlight the contribution of Mendelian randomization analyses in CVD research. Throughout this review, we assess the extent to which research findings agree across a range of studies of differing design within a triangulation framework. If differing study designs are subject to non-overlapping sources of bias, consistent findings limit the extent to which results are merely an artefact of study design. Consequently, broad agreement across differing studies can be viewed as providing more robust causal evidence in contrast to limiting the scope of the review to a single specific study design. Utilising the triangulation approach, we highlight emerging patterns in research findings, and explore the potential of identified risk factors as targets for precision medicine and novel interventions.
Artifacts ; Bias (Epidemiology) ; Cardiovascular Diseases ; Mendelian Randomization Analysis ; Mortality ; Precision Medicine ; Random Allocation ; Risk Factors

Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.
Adenocarcinoma ; Classification ; Dataset ; Diagnosis ; Learning ; Observer Variation ; Stomach

Arm ; Asian Continental Ancestry Group ; Bias (Epidemiology) ; Carboplatin ; Disease-Free Survival ; Doxorubicin ; Drug Therapy ; Follow-Up Studies ; Humans ; Maintenance Chemotherapy ; Ovarian Neoplasms ; Prognosis ; Quality of Life ; Recombination, Genetic ; Sample Size

bias of 0.005 (95% CI −0.011 to 0.021) with 95% limits of agreement of −0.16 to 0.17 between vFFR and FFR. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 78.0%, 87.1%, 72.5%, 58.7%, and 92.6%, respectively, using the FFR cutoff of 0.80. They were 87.0%, 95.0%, 80.0%, 54.3%, and 98.5%, respectively, with the FFR cutoff of 0.75. The area under the receiver-operating characteristics curve of vFFR versus obstructive CTA stenosis was 0.88 versus 0.61 for the FFR cutoff of 0.80, respectively; it was 0.94 versus 0.62 for the FFR cutoff of 0.75.CONCLUSION: Our novel, fully automated, on-site vFFR technology showed excellent diagnostic performance for the detection of lesion-specific ischemia.]]>
Angiography ; Bias (Epidemiology) ; Constriction, Pathologic ; Coronary Angiography ; Fractional Flow Reserve, Myocardial ; Humans ; Ischemia ; Patient-Specific Modeling ; Sensitivity and Specificity