%0 Journal Article %@ 1929-0748 %I JMIR Publications %V 14 %N %P e66579 %T Feasibility of a Progesterone-Modified Natural Protocol for Frozen Embryo Transfer: Protocol for a Pilot Cohort Study %A Churchill,Alexandra %A Georgiou,Ektoras %A Abruzzo,Veronica %A Polyakov,Alex %A Teh,Wan Tinn %+ Reproductive Services Unit, The Royal Women's Hospital, 20 Flemington Rd, Parkville, Melbourne, VIC 3050, Australia, 61 (03) 8345 2000, Wan.Teh@thewomens.org.au %K frozen embryo transfer %K fertility care %K reproductive health %K infertility %K progesterone-modified natural cycle protocol %K in vitro fertilization %D 2025 %7 11.4.2025 %9 Protocol %J JMIR Res Protoc %G English %X Background: With the existence of various frozen embryo transfer (FET) methods currently used in the field of assisted reproductive technologies, the debate surrounding which of these is superior remains. All FET protocols aim to prime the endometrium and time embryo transfer during the window of implantation. Current methods include the true natural cycle FET (tNFET), modified natural cycle FET, artificial cycle FET, and ovulation induction. Each of these harbors, distinct advantages and disadvantages, namely, surrounding the timing of transfer and flexibility conferred through this process. More recently, a newer approach has been used whereby the need to monitor or trigger ovulation is circumvented, with luteal phase support commenced once a certain follicle diameter and endometrial thickness criteria are met but before ovulation. However, the research into this protocol has certain important limitations that our study seeks to address. Objective: This study aims to assess the feasibility of a progesterone-modified natural cycle protocol for FET. The primary outcome will be the presence of a corpus luteum on ultrasound scans on the day of embryo transfer. The secondary outcomes will include the number of clinic visits required per patient undergoing the protocol, biochemical pregnancy rate, and clinical pregnancy rate. Methods: We will conduct a prospective cohort study, recruiting 20 women undertaking FET at the Public Fertility Care of The Royal Women’s Hospital in Melbourne, Australia. These women will be matched to a control group who have undergone the tNFET protocol within the preceding 12 months of the study start date. Results: This project received ethics approval on July 17, 2024, with commencement of the study in September 2024, aiming for a duration of completion of 9 months. The completion of the follow-up and submission of the study for publication are anticipated for September 2025. Conclusions: After this preliminary study, the aim would be to progress to a noninferiority randomized controlled trial to compare the progesterone-modified natural cycle protocol for FET to the tNFET. International Registered Report Identifier (IRRID): PRR1-10.2196/66579 %M 40215104 %R 10.2196/66579 %U https://www.researchprotocols.org/2025/1/e66579 %U https://doi.org/10.2196/66579 %U http://www.ncbi.nlm.nih.gov/pubmed/40215104 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e59591 %T Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study %A Lewis,Claire %A Groarke,Jenny %A Graham-Wisener,Lisa %A James,Jacqueline %+ School of Medicine Dentistry and Biomedical Sciences, Queen's University Belfast, University Road, Belfast, BT7 1NN, United Kingdom, 44 2890972804, claire.lewis@qub.ac.uk %K artificial intelligence %K AI %K public opinion %K pathology %K health care %K public awareness %K survey %D 2025 %7 2.4.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One of the most promising areas of research that has potential clinical utility is the use of AI in pathology to aid cancer diagnosis and management. While the value of using AI to improve the efficiency and accuracy of diagnosis cannot be underestimated, there are challenges in the development and implementation of such technologies. Notably, questions remain about public support for the use of AI to assist in pathological diagnosis and for the use of health care data, including data obtained from tissue samples, to train algorithms. Objective: This study aimed to investigate public awareness of and attitudes toward AI in pathology research and practice. Methods: A nationally representative, cross-sectional, web-based mixed methods survey (N=1518) was conducted to assess the UK public’s awareness of and views on the use of AI in pathology research and practice. Respondents were recruited via Prolific, an online research platform. To be eligible for the study, participants had to be aged >18 years, be UK residents, and have the capacity to express their own opinion. Respondents answered 30 closed-ended questions and 2 open-ended questions. Sociodemographic information and previous experience with cancer were collected. Descriptive and inferential statistics were used to analyze quantitative data; qualitative data were analyzed thematically. Results: Awareness was low, with only 23.19% (352/1518) of the respondents somewhat or moderately aware of AI being developed for use in pathology. Most did not support a diagnosis of cancer (908/1518, 59.82%) or a diagnosis based on biomarkers (694/1518, 45.72%) being made using AI only. However, most (1478/1518, 97.36%) supported diagnoses made by pathologists with AI assistance. The adjusted odds ratio (aOR) for supporting AI in cancer diagnosis and management was higher for men (aOR 1.34, 95% CI 1.02-1.75). Greater awareness (aOR 1.25, 95% CI 1.10-1.42), greater trust in data security and privacy protocols (aOR 1.04, 95% CI 1.01-1.07), and more positive beliefs (aOR 1.27, 95% CI 1.20-1.36) also increased support, whereas identifying more risks reduced the likelihood of support (aOR 0.80, 95% CI 0.73-0.89). In total, 3 main themes emerged from the qualitative data: bringing the public along, the human in the loop, and more hard evidence needed, indicating conditional support for AI in pathology with human decision-making oversight, robust measures for data handling and protection, and evidence for AI benefit and effectiveness. Conclusions: Awareness of AI’s potential use in pathology was low, but attitudes were positive, with high but conditional support. Challenges remain, particularly among women, regarding AI use in cancer diagnosis and management. Apprehension persists about the access to and use of health care data by private organizations. %M 40173441 %R 10.2196/59591 %U https://www.jmir.org/2025/1/e59591 %U https://doi.org/10.2196/59591 %U http://www.ncbi.nlm.nih.gov/pubmed/40173441 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 14 %N %P e66286 %T Current Status and Future Directions of Ferroptosis Research in Breast Cancer: Bibliometric Analysis %A Luo,Jia-Yuan %A Deng,Yu-Long %A Lu,Shang-Yi %A Chen,Si-Yan %A He,Rong-Quan %A Qin,Di-Yuan %A Chi,Bang-Teng %A Chen,Gang %A Yang,Xia %A Peng,Wei %+ , Department of Oncology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China, 86 15977779804, pengwei@stu.gxmu.edu.cn %K breast cancer %K ferroptosis %K bibliometric %K malignancy %K cancer studies %K treatment %K bibliometric analysis %K VOSviewer %K China %K United States %K breast carcinoma %K mammary cancer %K strategy %K trends %K bibliography %K review %K disparities %K forecast %K treatment strategies %K advancements %D 2025 %7 26.2.2025 %9 Original Paper %J Interact J Med Res %G English %X Background: Ferroptosis, as a novel modality of cell death, holds significant potential in elucidating the pathogenesis and advancing therapeutic strategies for breast cancer. Objective: This study aims to comprehensively analyze current ferroptosis research and future trends, guiding breast cancer research advancements and innovative treatment strategies. Methods: This research used the R package Bibliometrix (Department of Economic and Statistical Sciences at the University of Naples Federico II), VOSviewer (Centre for Science and Technology Studies at Leiden University), and CiteSpace (Drexel University’s College of Information Science and Technology), to conduct a bibliometric analysis of 387 papers on breast cancer and ferroptosis from the Web of Science Core Collection. The analysis covers authors, institutions, journals, countries or regions, publication volumes, citations, and keywords. Results: The number of publications related to this field has surged annually, with China and the United States collaborating closely and leading in output. Sun Yat-sen University stands out among the institutions, while the journal Frontiers in Oncology and the author Efferth T contribute significantly to the field. Highly cited papers within the domain primarily focus on the induction of ferroptosis, protein regulation, and comparisons with other modes of cell death, providing a foundation for breast cancer treatment. Keyword analysis highlights the maturity of glutathione peroxidase 4-related research, with breast cancer subtypes emerging as motor themes and the tumor microenvironment, immunotherapy, and prognostic models identified as basic themes. Furthermore, the application of nanoparticles serves as an additional complement to the basic themes. Conclusions: The current research status in the field of ferroptosis and breast cancer primarily focuses on the exploration of relevant theoretical mechanisms, whereas future trends and mechanisms emphasize the investigation of therapeutic strategies, particularly the clinical application of immunotherapy related to the tumor microenvironment. Nanotherapy has demonstrated significant clinical potential in this domain. Future research directions should deepen the exploration in this field and accelerate the clinical translation of research findings to provide new insights and directions for the innovation and development of breast cancer treatment strategies. %M 40009842 %R 10.2196/66286 %U https://www.i-jmr.org/2025/1/e66286 %U https://doi.org/10.2196/66286 %U http://www.ncbi.nlm.nih.gov/pubmed/40009842 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 14 %N %P e70075 %T Histopathological Comparison and Expression Analysis of COL1A1, COL3A1, and ELN in the Proximal and Distal Ventral Dartos of Patients With Hypospadias: Protocol for Prospective Case-Control Study %A Raharja,Putu Angga Risky %A Birowo,Ponco %A Rachmadi,Lisnawati %A Wibowo,Heri %A Kekalih,Aria %A Duarsa,Gede Wirya Kusuma %A Abbas,Tariq %A Wahyudi,Irfan %+ Department of Urology, Faculty of Medicine, Cipto Mangunkusumo Hospital, University of Indonesia, Jalan Diponegoro No. 71, Jakarta, 10430, Indonesia, 62 21 150 0135, anggariskyraharja@gmail.com %K chordee %K superficial chordee %K COL1A1 %K COL3A1 %K dartos tissue %K dartos fascia %K ELN %K elastin %K histopathological %D 2025 %7 18.2.2025 %9 Protocol %J JMIR Res Protoc %G English %X Background: The exact cause of penile curvature in hypospadias remains unknown. Resection of the dartos fascia has been observed to straighten the penis, indicating the involvement of the dartos fascia in the superficial chordee. However, the characteristics of dartos tissue in the distal territory of the ventral penile shaft may differ from those in the proximal aspect of the penile shaft. Objective: This study aims to investigate the distinct histopathological profiles and expression of COL1A1 (collagen type 1), COL3A1 (collagen type 3), and ELN (elastin) in proximal and distal ventral dartos of patients with hypospadias compared to those without hypospadias. Methods: This prospective case-control study compares the ventral dartos tissue of patients with hypospadias at different locations with that of patients without hypospadias. Dartos samples will be taken during surgery, with age matching. Histopathology examination uses hematoxylin and eosin and Masson’s trichrome stain. The mRNA expression of COL1A1, COL3A1, and ELN will be quantified using a 2-step reverse transcription–polymerase chain reaction analysis. Results: Previous studies have documented different characteristics of dartos tissue between patients with hypospadias and those without hypospadias. Some studies even suggest resection of the dartos tissue during hypospadias repair. However, this is the first study to compare the characteristics of ventral dartos tissue in patients with hypospadias based on its location along the penile shaft, suggesting potential differences between the distal and proximal locations. We have obtained ethical approval to conduct a prospective case-control study aimed at elucidating these differences in dartos tissue characteristics. The findings of the study are anticipated to be available by 2025. Conclusions: Differences in the characteristics of dartos fascia based on its location may require tailored surgical strategies. If the properties of distal dartos tissue closely mirror those of typical dartos tissue, the possibility of avoiding its excision during hypospadias surgery could be considered. International Registered Report Identifier (IRRID): DERR1-10.2196/70075 %M 39964742 %R 10.2196/70075 %U https://www.researchprotocols.org/2025/1/e70075 %U https://doi.org/10.2196/70075 %U http://www.ncbi.nlm.nih.gov/pubmed/39964742 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e62851 %T Artificial Intelligence in Lymphoma Histopathology: Systematic Review %A Fu,Yao %A Huang,Zongyao %A Deng,Xudong %A Xu,Linna %A Liu,Yang %A Zhang,Mingxing %A Liu,Jinyi %A Huang,Bin %+ Department of Pathology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, South Renmin Road, Chengdu, 610041, China, 86 18236170185, 18236170185@163.com %K lymphoma %K artificial intelligence %K bias %K histopathology %K tumor %K hematological %K lymphatic disease %K public health %K pathologists %K pathology %K immunohistochemistry %K diagnosis %K prognosis %D 2025 %7 14.2.2025 %9 Review %J J Med Internet Res %G English %X Background: Artificial intelligence (AI) shows considerable promise in the areas of lymphoma diagnosis, prognosis, and gene prediction. However, a comprehensive assessment of potential biases and the clinical utility of AI models is still needed. Objective: Our goal was to evaluate the biases of published studies using AI models for lymphoma histopathology and assess the clinical utility of comprehensive AI models for diagnosis or prognosis. Methods: This study adhered to the Systematic Review Reporting Standards. A comprehensive literature search was conducted across PubMed, Cochrane Library, and Web of Science from their inception until August 30, 2024. The search criteria included the use of AI for prognosis involving human lymphoma tissue pathology images, diagnosis, gene mutation prediction, etc. The risk of bias was evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Information for each AI model was systematically tabulated, and summary statistics were reported. The study is registered with PROSPERO (CRD42024537394) and follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 reporting guidelines. Results: The search identified 3565 records, with 41 articles ultimately meeting the inclusion criteria. A total of 41 AI models were included in the analysis, comprising 17 diagnostic models, 10 prognostic models, 2 models for detecting ectopic gene expression, and 12 additional models related to diagnosis. All studies exhibited a high or unclear risk of bias, primarily due to limited analysis and incomplete reporting of participant recruitment. Most high-risk models (10/41) predominantly assigned high-risk classifications to participants. Almost all the articles presented an unclear risk of bias in at least one domain, with the most frequent being participant selection (16/41) and statistical analysis (37/41). The primary reasons for this were insufficient analysis of participant recruitment and a lack of interpretability in outcome analyses. In the diagnostic models, the most frequently studied lymphoma subtypes were diffuse large B-cell lymphoma, follicular lymphoma, chronic lymphocytic leukemia, and mantle cell lymphoma, while in the prognostic models, the most common subtypes were diffuse large B-cell lymphoma, follicular lymphoma, chronic lymphocytic leukemia, and Hodgkin lymphoma. In the internal validation results of all models, the area under the receiver operating characteristic curve (AUC) ranged from 0.75 to 0.99 and accuracy ranged from 68.3% to 100%. In models with external validation results, the AUC ranged from 0.93 to 0.99. Conclusions: From a methodological perspective, all models exhibited biases. The enhancement of the accuracy of AI models and the acceleration of their clinical translation hinge on several critical aspects. These include the comprehensive reporting of data sources, the diversity of datasets, the study design, the transparency and interpretability of AI models, the use of cross-validation and external validation, and adherence to regulatory guidance and standardized processes in the field of medical AI. %M 39951716 %R 10.2196/62851 %U https://www.jmir.org/2025/1/e62851 %U https://doi.org/10.2196/62851 %U http://www.ncbi.nlm.nih.gov/pubmed/39951716 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 14 %N %P e46007 %T An Automated Clinical Laboratory Decision Support System for Test Utilization, Medical Necessity Verification, and Payment Processing %A Beqaj,Safedin %A Shrestha,Rojeet %A Hamill,Tim %+ Medical Database, Inc, 1 Post, Suite 200, Irvine, CA, 92618, United States, 1 8477693701, sajo@medicaldatabase.com %K clinical decision system %K CDSS %K laboratory decision system %K laboratory testing %K test utilization %K test ordering %K lab test %K laboratory %K testing %K payment %K decision-making %K user %K utilization %K processing %K decision %D 2025 %7 11.2.2025 %9 Viewpoint %J Interact J Med Res %G English %X Physicians could improve the efficiency of the health care system if a reliable resource were available to aid them in better understanding, selecting, and interpreting the diagnostic laboratory tests. It has been well established and widely recognized that (1) laboratory testing provides 70%-85% of the objective data that physicians use in the diagnosis and treatment of their patients; (2) orders for laboratory tests in the United States have increased, with an estimated volume of 4-5 billion tests per year; (3) there is a lack of user-friendly tools to guide physicians in their test selection and ordering; and (4) laboratory test overutilization and underutilization continue to represent a pervasive source of inefficiency in the health care system. These inappropriate test orders not only lead to slower or incorrect diagnoses for patients but also add a significant financial burden. In addition, many ordered tests are not reimbursed by Medicare because they are inappropriate for the medical condition or were ordered with the incorrect International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnostic code, not meeting the medical necessity. Therefore, current clinical laboratory test ordering procedures experience a quality gap. Often, providers do not have access to an appropriate tool that uses evidence-based guidelines or algorithms to ensure that tests are not duplicated, overused, or underused. This viewpoint lays out the potential use of an automated laboratory clinical decision support system that helps providers order the right test for the right disease and documents the right reason or medical necessity to pay for the testing. %M 39808833 %R 10.2196/46007 %U https://www.i-jmr.org/2025/1/e46007 %U https://doi.org/10.2196/46007 %U http://www.ncbi.nlm.nih.gov/pubmed/39808833 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 7 %N %P e50401 %T Lichen Planus Pigmentosus and Vitiligo in a 61-Year-Old Filipino Man: Case Report %A Belizario,Maria Isabel %A Gatmaitan,Julius Garcia %A Dayrit,Johannes %K lichen planus pigmentosus %K vitiligo %K autoimmune %K isotretinoin %K tacrolimus %K skin %K melanin %K hyperpigmentation %K LPP %D 2024 %7 29.11.2024 %9 %J JMIR Dermatol %G English %X Pigmentary disorders have been implicated in causing psychosocial turmoil in patients as they can cause some degree of cosmetic disfigurement. Lichen planus pigmentosus (LPP) presents as ashy, dermatosis-like eruptions on sun-exposed areas, particularly on the head, neck, and earlobes. On the other hand, vitiligo is a chronic disorder that appears as depigmented patches on the skin. A 61-year-old man with Fitzpatrick skin phototype IV presented to us initially with LPP but eventually also developed vitiligo. The patient was treated with low-dose oral isotretinoin for LPP and topical tacrolimus 0.1% ointment for both LPP and vitiligo with a good clinical outcome. One case of segmental vitiligo and zosteriform LPP, affecting a 22-year-old Indian woman, has been previously reported in the English-language literature. An autoimmune etiology that causes melanocytorrhagy may be a plausible hypothesis for the coexistence of these 2 conditions. %R 10.2196/50401 %U https://derma.jmir.org/2024/1/e50401 %U https://doi.org/10.2196/50401 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e65033 %T Exploring the Potential of Claude 3 Opus in Renal Pathological Diagnosis: Performance Evaluation %A Li,Xingyuan %A Liu,Ke %A Lang,Yanlin %A Chai,Zhonglin %A Liu,Fang %+ Department of Nephrology, West China Hospital, Sichuan University, 37 Guoxue Alley, Wuhou District, Chengdu, 610041, China, 86 13890790651, liufangfh@163.com %K artificial intelligence %K Claude 3 Opus %K renal pathology %K diagnostic performance %K large language model %K LLM %K performance evaluation %K medical diagnosis %K AI language model %K diagnosis %K pathology images %K pathologist %K clinical relevance %K accuracy %K language fluency %K pathological diagnosis %D 2024 %7 15.11.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Artificial intelligence (AI) has shown great promise in assisting medical diagnosis, but its application in renal pathology remains limited. Objective: We evaluated the performance of an advanced AI language model, Claude 3 Opus (Anthropic), in generating diagnostic descriptions for renal pathological images. Methods: We carefully curated a dataset of 100 representative renal pathological images from the Diagnostic Atlas of Renal Pathology (3rd edition). The image selection aimed to cover a wide spectrum of common renal diseases, ensuring a balanced and comprehensive dataset. Claude 3 Opus generated diagnostic descriptions for each image, which were scored by 2 pathologists on clinical relevance, accuracy, fluency, completeness, and overall value. Results: Claude 3 Opus achieved a high mean score in language fluency (3.86) but lower scores in clinical relevance (1.75), accuracy (1.55), completeness (2.01), and overall value (1.75). Performance varied across disease types. Interrater agreement was substantial for relevance (κ=0.627) and overall value (κ=0.589) and moderate for accuracy (κ=0.485) and completeness (κ=0.458). Conclusions: Claude 3 Opus shows potential in generating fluent renal pathology descriptions but needs improvement in accuracy and clinical value. The AI’s performance varied across disease types. Addressing the limitations of single-source data and incorporating comparative analyses with other AI approaches are essential steps for future research. Further optimization and validation are needed for clinical applications. %M 39547661 %R 10.2196/65033 %U https://medinform.jmir.org/2024/1/e65033 %U https://doi.org/10.2196/65033 %U http://www.ncbi.nlm.nih.gov/pubmed/39547661 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e62877 %T Noninvasive, Multimodal Inflammatory Biomarker Discovery for Systemic Inflammation (NOVA Study): Protocol for a Cross-Sectional Study %A Shim,Jinjoo %A Muraru,Sinziana %A Dobrota,Rucsandra %A Fleisch,Elgar %A Distler,Oliver %A Barata,Filipe %+ Centre for Digital Health Interventions, ETH Zurich, Weinbergstrasse 56/58, Zurich, 8006, Switzerland, 41 765457890, jshim@ethz.ch %K systemic inflammation %K chronic inflammation %K inflammatory biomarkers %K biofluids %K serum %K urine %K sweat %K saliva %K exhaled breath %K stool %K C-reactive protein %K interleukin %K IL-1β %K IL-6 %K IL-8 %K IL-10 %K tumor necrosis factor %K TNF-α %K fractional exhaled nitric oxide %K calprotectin %K core body temperature %K noninvasive biomarker %K multimodal biomarker %K remote monitoring %K surrogate biomarker %K rheumatology %K chronic inflammatory disease %D 2024 %7 5.11.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Prolonged systemic inflammation is recognized as a major contributor to the development of various chronic inflammatory diseases. Daily measurements of inflammatory biomarkers can significantly improve disease monitoring of systemic inflammation, thus contributing to reducing the burden on patients and the health care system. There exists, however, no scalable, cost-efficient, and noninvasive biomarker for remote assessment of systemic inflammation. To this end, we propose a novel, multimodal, and noninvasive approach for measuring inflammatory biomarkers. Objective: This study aimed to evaluate the relationship between the levels of inflammatory biomarkers in serum (gold standard) and those measured noninvasively in urine, sweat, saliva, exhaled breath, stool, and core body temperature in patients with systemic inflammation. Methods: This study is a single-center, cross-sectional study and includes a total of 20 participants (10 patients with systemic inflammation and 10 control patients). Eligible participants provide serum, urine, sweat, saliva, exhaled breath, and stool samples for biomarker analyses. Core body temperature is measured using a sensor. The primary end point is the level of C-reactive protein (CRP). The secondary end points are interleukin (IL)–1β, IL-6, IL-8, IL-10, and tumor necrosis factor-α levels. The tertiary end points are fractional exhaled nitric oxide, calprotectin, and core body temperature. Samples will be collected in 2 batches, enabling preliminary analysis of the first batch (patients 1-5 from each group). The full analysis will include both batches. CRP and cytokine levels will be measured using enzyme-linked immunosorbent assay and electrochemiluminescence immunoassay. For statistical analysis, the Shapiro-Wilk test will be used to evaluate the normality of the distribution in each variable. We will perform the 2-tailed t test or Wilcoxon rank sum test to compare the levels of inflammatory biomarkers between patients with systemic inflammations and control patients. Pearson and Spearman correlation coefficients will assess the relationship between inflammatory biomarkers from noninvasive methods and serum biomarkers. Using all-subset regression analysis, we will determine the combination of noninvasive methods yielding the highest predictive accuracy for serum CRP levels. Participants’ preferences for sampling methods will be assessed through a questionnaire. Results: The study received ethics approval from the independent research ethics committee of Canton Zurich on October 28, 2022. A total of 20 participants participated in the study measurements. Data collection started on February 22, 2023, and was completed on September 22, 2023. Participants were on average 52.8 (SD 14.4; range 24-82) years of age, and 70% (14/20) of them were women. The analysis results reporting findings are expected to be published in 2025. Conclusions: This study aims to evaluate the feasibility of noninvasive, multimodal assessment of inflammatory biomarkers in patients with systemic inflammation. Promising results could lead to the creation of noninvasive and potentially digital biomarkers for systemic inflammation, enabling continuous monitoring and early diagnosis of inflammatory activity in a remote setting. International Registered Report Identifier (IRRID): DERR1-10.2196/62877 %M 39499914 %R 10.2196/62877 %U https://www.researchprotocols.org/2024/1/e62877 %U https://doi.org/10.2196/62877 %U http://www.ncbi.nlm.nih.gov/pubmed/39499914 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e58149 %T AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Protocol for a Scoping Review %A von Bahr,Joar %A Diwan,Vinod %A Mårtensson,Andreas %A Linder,Nina %A Lundin,Johan %+ Department of Global Public Health, Karolinska Institutet, Tomtebodavägen 18A, Stockholm, 17177, Sweden, 46 708561007, joar.von.bahr@ki.se %K AI %K artificial intelligence %K convolutional neural network %K deep learning %K diagnosis %K digital diagnostics %K machine learning %K pathology %K primary health care %K whole slide images %D 2024 %7 1.11.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Digital microscopy combined with artificial intelligence (AI) is increasingly being implemented in health care, predominantly in advanced laboratory settings. However, AI-supported digital microscopy could be especially advantageous in primary health care settings, since such methods could improve access to diagnostics via automation and lead to a decreased need for experts on site. To our knowledge, no scoping or systematic review had been published on the use of AI-supported digital microscopy within primary health care laboratories when this scoping review was initiated. A scoping review can guide future research by providing insights to help navigate the challenges of implementing these novel methods in primary health care laboratories. Objective: The objective of this scoping review is to map peer-reviewed studies on AI-supported digital microscopy in primary health care laboratories to generate an overview of the subject. Methods: A systematic search of the databases PubMed, Web of Science, Embase, and IEEE will be conducted. Only peer-reviewed articles in English will be considered, and no limit on publication year will be applied. The concept inclusion criteria in the scoping review include studies that have applied AI-supported digital microscopy with the aim of achieving a diagnosis on the subject level. In addition, the studies must have been performed in the context of primary health care laboratories, as defined by the criteria of not having a pathologist on site and using simple sample preparations. The study selection and data extraction will be performed by 2 independent researchers, and in the case of disagreements, a third researcher will be involved. The results will be presented in a table developed by the researchers, including information on investigated diseases, sample collection, preparation and digitization, AI model used, and results. Furthermore, the results will be described narratively to provide an overview of the studies included. The proposed methodology is in accordance with the JBI methodology for scoping reviews. Results: The scoping review was initiated in January 2023, and a protocol was published in the Open Science Framework in January 2024. The protocol was completed in March 2024, and the systematic search will be performed after the protocol has been peer reviewed. The scoping review is expected to be finalized by the end of 2024. Conclusions: A systematic review of studies on AI-supported digital microscopy in primary health care laboratories is anticipated to identify the diseases where these novel methods could be advantageous, along with the shared challenges encountered and approaches taken to address them. International Registered Report Identifier (IRRID): PRR1-10.2196/58149 %M 39486020 %R 10.2196/58149 %U https://www.researchprotocols.org/2024/1/e58149 %U https://doi.org/10.2196/58149 %U http://www.ncbi.nlm.nih.gov/pubmed/39486020 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e53828 %T Economic Burden of Community-Acquired Antibiotic-Resistant Urinary Tract Infections: Systematic Review and Meta-Analysis %A Zhu,Nina Jiayue %A Weldegiorgis,Misghina %A Carter,Emma %A Brown,Colin %A Holmes,Alison %A Aylin,Paul %K cost-effectiveness %K urinary tract infection %K antibiotic resistance %K mortality %K hospital length of stay %D 2024 %7 9.10.2024 %9 %J JMIR Public Health Surveill %G English %X Background: Antibiotic resistance (ABR) poses a major burden to global health and economic systems. ABR in community-acquired urinary tract infections (CA-UTIs) has become increasingly prevalent. Accurate estimates of ABR’s clinical and economic burden are needed to support medical resource prioritization and cost-effectiveness evaluations of urinary tract infection (UTI) interventions. Objective: This study aims to systematically synthesize the evidence on the economic costs associated with ABR in CA-UTIs, using published studies comparing the costs of antibiotic-susceptible and antibiotic-resistant cases. Methods: We searched the PubMed, Ovid MEDLINE and Embase, Cochrane Review Library, and Scopus databases. Studies published in English from January 1, 2008, to January 31, 2023, reporting the economic costs of ABR in CA-UTI of any microbe were included. Independent screening of titles/abstracts and full texts was performed based on prespecified criteria. A quality assessment was performed using the Integrated Quality Criteria for Review of Multiple Study Designs (ICROMS) tool. Data in UTI diagnosis criteria, patient characteristics, perspectives, resource costs, and patient and health economic outcomes, including mortality, hospital length of stay (LOS), and costs, were extracted and analyzed. Monetary costs were converted into 2023 US dollars. Results: This review included 15 studies with a total of 57,251 CA-UTI cases. All studies were from high- or upper-middle-income countries. A total of 14 (93%) studies took a health system perspective, 13 (87%) focused on hospitalized patients, and 14 (93%) reported UTI pathogens. Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa are the most prevalent organisms. A total of 12 (80%) studies reported mortality, of which, 7 reported increased mortality in the ABR group. Random effects meta-analyses estimated an odds ratio of 1.50 (95% CI 1.29-1.74) in the ABR CA-UTI cases. All 13 hospital-based studies reported LOS, of which, 11 reported significantly higher LOS in the ABR group. The meta-analysis of the reported median LOS estimated a pooled excess LOS ranging from 1.50 days (95% CI 0.71-4.00) to 2.00 days (95% CI 0.85-3.15). The meta-analysis of the reported mean LOS estimated a pooled excess LOS of 2.45 days (95% CI 0.51‐4.39). A total of 8 (53%) studies reported costs in monetary terms—none discounted the costs. All 8 studies reported higher medical costs spent treating patients with ABR CA-UTI in hospitals. The highest excess cost was observed in UTIs caused by carbapenem-resistant Enterobacterales. No meta-analysis was performed for monetary costs due to heterogeneity. Conclusions: ABR was attributed to increased mortality, hospital LOS, and economic costs among patients with CA-UTI. The findings of this review highlighted the scarcity of research in this area, particularly in patient morbidity and chronic sequelae and costs incurred in community health care. Future research calls for a cost-of-illness analysis of infections, standardizing therapy-pathogen combination comparators, medical resources, productivity loss, intangible costs to be captured, and data from community sectors and low-resource settings and countries. %R 10.2196/53828 %U https://publichealth.jmir.org/2024/1/e53828 %U https://doi.org/10.2196/53828 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 13 %N %P e46570 %T Biochemical Changes in Adult Male Gamers During Prolonged Gaming: Pilot Study %A Krarup,Kasper Bygum %A Riis,Johannes %A Mørk,Morten %A Nguyen,Hien Thi Thu %A Søkilde Pedersen,Inge %A Risom Kristensen,Søren %A Handberg,Aase %A Krarup,Henrik Bygum %+ Department of Geriatrics, Aalborg University Hospital, Reberbansgade 15, Aalborg, 9000, Denmark, 45 61781289, kasper.krarup@rn.dk %K long gaming sessions %K local area network party %K biochemistry %K cortisol %K glucose %K gaming %K biochemical %K blood sample %K hematology %K hematological %K games %K gamers %K hemoglobin %K adults %K males %K men %K blood %D 2024 %7 8.7.2024 %9 Original Paper %J Interact J Med Res %G English %X Background: Gaming has become an integrated part of life for children and adults worldwide. Previous studies on the impact of gaming on biochemical parameters have primarily addressed the acute effects of gaming. The literature is limited, and the study designs are very diverse. The parameters that have been investigated most thoroughly are blood glucose and cortisol. Objective: This exploratory study is the first to investigate the effects of long gaming sessions on the biochemical parameters of healthy male adults. The extensive testing allowed us to observe short-term changes (within 6 hours), long-term changes during the duration of the gaming sessions, and follow-up after 1 week to determine whether any changes were longer lasting. Methods: In total, 9 experienced gamers completed 2 back-to-back 18-hour gaming sessions interspersed with a 6-hour rest period. All participants adhered to a structured sleep pattern due to daytime employment or attending university. Blood, saliva, and urine samples were collected from the participants every 6 hours. Linear mixed-effect models were used to analyze the repeated-measures data accumulated during the study. A total of 51 biochemical parameters were investigated. Results: In total, 12 of the 51 biochemical parameters significantly changed during the study: alkaline phosphatase, aspartate aminotransferase, bilirubin, chloride, creatinine, glucose, hemoglobin, immature reticulocyte fraction, lactate, methemoglobin, sodium, and thrombocytes. All changes were within the normal range. The mean glucose level of the participants was 4.39 (SD 0.07) mmol/L at baseline, which increased significantly by 0.24 (SD 0.07) mmol/L per 6 hours during the first period and by 0.38 (SD 0.07) mmol/L per 6 hours in the second period (P<.001). The glucose levels during the second session increased even though the participants had little energy intake. Cortisol levels did not change significantly, although the cortisol pattern deviated from the typical circadian rhythm. During both gaming sessions, we observed increasing cortisol levels from 6 AM until noon. The participants were relatively dehydrated at the start of the study. The patients were asked to fast before the first blood sampling. Within the first 6 hours of the study, the participants rehydrated, followed by relative dehydration during the remainder of the study. This pattern was identified using the following parameters: albumin, creatinine, hemoglobin, erythrocytes, potassium, and platelets. Conclusions: This study is the first of its kind, and many of the analyses in the study yielded novel results. The study was designed to emulate the behavior of gamers during the weekend and other long gaming sessions. At this point, we are not able to determine the difference between the effects of gaming and behavior during gaming. Regardless, the results of this study suggest that healthy gamers can partake in long gaming sessions, with ample amounts of unhealthy foods and little rest, without acute impacts on health. %M 38976326 %R 10.2196/46570 %U https://www.i-jmr.org/2024/1/e46570 %U https://doi.org/10.2196/46570 %U http://www.ncbi.nlm.nih.gov/pubmed/38976326 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e56726 %T Linking Dementia Pathology and Alteration in Brain Activation to Complex Daily Functional Decline During the Preclinical Dementia Stages: Protocol for a Prospective Observational Cohort Study %A De Sanctis,Pierfilippo %A Mahoney,Jeannette R %A Wagner,Johanna %A Blumen,Helena M %A Mowrey,Wenzhu %A Ayers,Emmeline %A Schneider,Claudia %A Orellana,Natasha %A Molholm,Sophie %A Verghese,Joe %+ Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, 1225 Morris Park Avenue, Bronx, NY, 10461-0000, United States, 1 7188621828, pierfilippo.sanctis@einsteinmed.edu %K EEG %K electroencephalographic %K mobility %K preclinical dementia stages %D 2024 %7 6.6.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Progressive difficulty in performing everyday functional activities is a key diagnostic feature of dementia syndromes. However, not much is known about the neural signature of functional decline, particularly during the very early stages of dementia. Early intervention before overt impairment is observed offers the best hope of reducing the burdens of Alzheimer disease (AD) and other dementias. However, to justify early intervention, those at risk need to be detected earlier and more accurately. The decline in complex daily function (CdF) such as managing medications has been reported to precede impairment in basic activities of daily living (eg, eating and dressing). Objective: Our goal is to establish the neural signature of decline in CdF during the preclinical dementia period. Methods: Gait is central to many CdF and community-based activities. Hence, to elucidate the neural signature of CdF, we validated a novel electroencephalographic approach to measuring gait-related brain activation while participants perform complex gait-based functional tasks. We hypothesize that dementia-related pathology during the preclinical period activates a unique gait-related electroencephalographic (grEEG) pattern that predicts a subsequent decline in CdF. Results: We provide preliminary findings showing that older adults reporting CdF limitations can be characterized by a unique gait-related neural signature: weaker sensorimotor and stronger motor control activation. This subsample also had smaller brain volume and white matter hyperintensities in regions affected early by dementia and engaged in less physical exercise. We propose a prospective observational cohort study in cognitively unimpaired older adults with and without subclinical AD (plasma amyloid-β) and vascular (white matter hyperintensities) pathologies. We aim to (1) establish the unique grEEG activation as the neural signature and predictor of decline in CdF during the preclinical dementia period; (2) determine associations between dementia-related pathologies and incidence of the neural signature of CdF; and (3) establish associations between a dementia risk factor, physical inactivity, and the neural signature of CdF. Conclusions: By establishing the clinical relevance and biological basis of the neural signature of CdF decline, we aim to improve prediction during the preclinical stages of ADs and other dementias. Our approach has important research and translational implications because grEEG protocols are relatively inexpensive and portable, and predicting CdF decline may have real-world benefits. International Registered Report Identifier (IRRID): DERR1-10.2196/56726 %M 38842914 %R 10.2196/56726 %U https://www.researchprotocols.org/2024/1/e56726 %U https://doi.org/10.2196/56726 %U http://www.ncbi.nlm.nih.gov/pubmed/38842914 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 5 %P e35706 %T An Agreement of Antigen Tests on Oral Pharyngeal Swabs or Less Invasive Testing With Reverse Transcription Polymerase Chain Reaction for Detecting SARS-CoV-2 in Adults: Protocol for a Prospective Nationwide Observational Study %A Schneider,Uffe Vest %A Knudsen,Jenny Dahl %A Koch,Anders %A Kirkby,Nikolai Søren %A Lisby,Jan Gorm %+ Department of Clinical Microbiology, Copenhagen University Hospital Hvidovre, Kettegaard Alle 30, Hvidovre, 2650, Denmark, 45 38623189, uffe.vest.schneider@regionh.dk %K SARS-CoV-2 %K COVID-19 %K point of care %K PoC %K antigen test %K anatomic sampling location %K Reverse Transcription Polymerase Chain Reaction %K RT-PCR %K rapid antigen test %K RAT %K testing %K antigen %K sampling %K PCR %K rapid %K protocol %K prospective %K observational %K agreement %K oral %K adult %K sensitivity %K specificity %K test location %K anatomy %K saliva %K swab %K nasopharyngeal %K nasal %D 2022 %7 4.5.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: The SARS-CoV-2 pandemic has resulted in an unprecedented level of worldwide testing for epidemiologic and diagnostic purposes, and due to the extreme need for tests, the gold-standard Reverse Transcription Polymerase Chain Reaction (RT-PCR) testing capacity has been unable to meet the overall worldwide testing demand. Consequently, although the current literature has shown the sensitivity of rapid antigen tests (RATs) to be inferior to RT-PCR, RATs have been implemented on a large scale without solid data on performance. Objective: This study will compare analytical and clinical sensitivities and specificities of 50 lateral flow– or laboratory-based RATs and 3 strand invasion–based amplification (SIBA)-RT-PCR tests from 30 manufacturers to RT-PCR testing of samples obtained from the deep oropharynx. In addition, the study will compare sensitivities and specificities of the included RATs as well as RT-PCR on clinical samples obtained from the deep oropharynx, the anterior nasal cavity, saliva, the deep nasopharynx, and expired air to RT-PCR on deep oropharyngeal samples. Methods: In the prospective part of the study, 200 individuals found SARS-CoV-2 positive and 200 individuals found SARS-CoV-2 negative by routine RT-PCR testing will be retested with each RAT, applying RT-PCR as the reference method. In the retrospective part of the study, 304 deep oropharyngeal cavity swabs divided into 4 groups based on RT-PCR quantification cycle (Cq) levels will be tested with each RAT. Results: The results will be reported in several papers with different aims. The first paper will report retrospective (analytical sensitivity, overall and stratified into different Cq range groups) and prospective (clinical sensitivity) data for RATs, with RT-PCR as the reference method. The second paper will report results for RAT based on anatomical sampling location. The third paper will compare different anatomical sampling locations by RT-PCR testing. The fourth paper will focus on RATs that rely on central laboratory testing. Tests from 4 different manufacturers will be compared for analytical performance data on retrospective deep oropharyngeal swab samples. The fifth paper will report the results of 4 RATs applied both as professional use and as self-tests. The last paper will report the results from 2 breath tests in the study. A comparison of sensitivity and specificity between RATs will be conducted using the McNemar test for paired samples and the chi-squared test for unpaired samples. Comparison of the positive predictive value (PPV) and negative predictive value (NPV) between RATs will be performed by the bootstrap test, and 95% CIs for sensitivity, specificity, PPV, and NPV will be calculated as bootstrap CIs. Conclusions: The study will compare the sensitivities of a large number of RATs for SARS-CoV-2 to with those of RT-PCR and will address whether lateral flow–based RATs differ significantly from laboratory-based RATs. The anatomical test locations for both RATs and RT-PCR will also be compared. Trial Registration: ClinicalTrials.gov NCT04913116; https://clinicaltrials.gov/ct2/show/NCT04913116 International Registered Report Identifier (IRRID): DERR1-10.2196/35706 %M 35394449 %R 10.2196/35706 %U https://www.researchprotocols.org/2022/5/e35706 %U https://doi.org/10.2196/35706 %U http://www.ncbi.nlm.nih.gov/pubmed/35394449 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e27210 %T A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study %A Mitchell,Joseph Ross %A Szepietowski,Phillip %A Howard,Rachel %A Reisman,Phillip %A Jones,Jennie D %A Lewis,Patricia %A Fridley,Brooke L %A Rollison,Dana E %+ Department of Health Data Services, H Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, United States, 1 813 745 6530, Dana.Rollison@moffitt.org %K natural language processing %K NLP %K BERT %K transformer %K pathology %K ICD-O-3 %K deep learning %K cancer %D 2022 %7 23.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Information in pathology reports is critical for cancer care. Natural language processing (NLP) systems used to extract information from pathology reports are often narrow in scope or require extensive tuning. Consequently, there is growing interest in automated deep learning approaches. A powerful new NLP algorithm, bidirectional encoder representations from transformers (BERT), was published in late 2018. BERT set new performance standards on tasks as diverse as question answering, named entity recognition, speech recognition, and more. Objective: The aim of this study is to develop a BERT-based system to automatically extract detailed tumor site and histology information from free-text oncological pathology reports. Methods: We pursued three specific aims: extract accurate tumor site and histology descriptions from free-text pathology reports, accommodate the diverse terminology used to indicate the same pathology, and provide accurate standardized tumor site and histology codes for use by downstream applications. We first trained a base language model to comprehend the technical language in pathology reports. This involved unsupervised learning on a training corpus of 275,605 electronic pathology reports from 164,531 unique patients that included 121 million words. Next, we trained a question-and-answer (Q&A) model that connects a Q&A layer to the base pathology language model to answer pathology questions. Our Q&A system was designed to search for the answers to two predefined questions in each pathology report: What organ contains the tumor? and What is the kind of tumor or carcinoma? This involved supervised training on 8197 pathology reports, each with ground truth answers to these 2 questions determined by certified tumor registrars. The data set included 214 tumor sites and 193 histologies. The tumor site and histology phrases extracted by the Q&A model were used to predict International Classification of Diseases for Oncology, Third Edition (ICD-O-3), site and histology codes. This involved fine-tuning two additional BERT models: one to predict site codes and another to predict histology codes. Our final system includes a network of 3 BERT-based models. We call this CancerBERT network (caBERTnet). We evaluated caBERTnet using a sequestered test data set of 2050 pathology reports with ground truth answers determined by certified tumor registrars. Results: caBERTnet’s accuracies for predicting group-level site and histology codes were 93.53% (1895/2026) and 97.6% (1993/2042), respectively. The top 5 accuracies for predicting fine-grained ICD-O-3 site and histology codes with 5 or more samples each in the training data set were 92.95% (1794/1930) and 96.01% (1853/1930), respectively. Conclusions: We have developed an NLP system that outperforms existing algorithms at predicting ICD-O-3 codes across an extensive range of tumor sites and histologies. Our new system could help reduce treatment delays, increase enrollment in clinical trials of new therapies, and improve patient outcomes. %M 35319481 %R 10.2196/27210 %U https://www.jmir.org/2022/3/e27210 %U https://doi.org/10.2196/27210 %U http://www.ncbi.nlm.nih.gov/pubmed/35319481 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 8 %P e20815 %T The Use and Effectiveness of an Online Diagnostic Support System for Blood Film Interpretation: Comparative Observational Study %A Hutchinson,Claire %A Brereton,Michelle %A Adams,Julie %A De La Salle,Barbara %A Sims,Jon %A Hyde,Keith %A Chasty,Richard %A Brown,Rachel %A Rees-Unwin,Karen %A Burthem,John %+ Manchester Foundation Trust, Oxford Road, Manchester, M13 9PL, United Kingdom, 44 1617011909, John.Burthem@mft.nhs.uk %K blood cell morphology %K decision support %K external quality assessment in hematology %K diagnosis %K digital morphology %K morphology education %D 2021 %7 9.8.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The recognition and interpretation of abnormal blood cell morphology is often the first step in diagnosing underlying serious systemic illness or leukemia. Supporting the staff who interpret blood film morphology is therefore essential for a safe laboratory service. This paper describes an open-access, web-based decision support tool, developed by the authors to support morphological diagnosis, arising from earlier studies identifying mechanisms of error in blood film reporting. The effectiveness of this intervention was assessed using the unique resource offered by the online digital morphology Continuing Professional Development scheme (DM scheme) offered by the UK National External Quality Assessment Service for Haematology, with more than 3000 registered users. This allowed the effectiveness of decision support to be tested within a defined user group, each of whom viewed and interpreted the morphology of identical digital blood films. Objective: The primary objective of the study was to test the effectiveness of the decision support system in supporting users to identify and interpret abnormal morphological features. The secondary objective was to determine the pattern and frequency of use of the system for different case types, and to determine how users perceived the support in terms of their confidence in decision-making. Methods: This was a comparative study of identical blood films evaluated either with or without decision support. Selected earlier cases from the DM scheme were rereleased as new cases but with decision support made available; this allowed a comparison of data sets for identical cases with or without decision support. To address the primary objectives, the study used quantitative evaluation and statistical comparisons of the identification and interpretation of morphological features between the two different case releases. To address the secondary objective, the use of decision support was assessed using web analytical tools, while a questionnaire was used to assess user perceptions of the system. Results: Cases evaluated with the aid of decision support had significantly improved accuracy of identification for relevant morphological features (mean improvement 9.8%) and the interpretation of those features (mean improvement 11%). The improvement was particularly significant for cases with higher complexity or for rarer diagnoses. Analysis of website usage demonstrated a high frequency of access for web pages relevant to each case (mean 9298 for each case, range 2661-24,276). Users reported that the decision support website increased their confidence for feature identification (4.8/5) and interpretation (4.3/5), both within the context of training (4.6/5) and also in their wider laboratory practice (4.4/5). Conclusions: The findings of this study demonstrate that directed online decision support for blood morphology evaluation improves accuracy and confidence in the context of educational evaluation of digital films, with effectiveness potentially extending to wider laboratory use. %M 34383663 %R 10.2196/20815 %U https://www.jmir.org/2021/8/e20815 %U https://doi.org/10.2196/20815 %U http://www.ncbi.nlm.nih.gov/pubmed/34383663 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 2 %P e24266 %T Digital Pathology During the COVID-19 Outbreak in Italy: Survey Study %A Giaretto,Simone %A Renne,Salvatore Lorenzo %A Rahal,Daoud %A Bossi,Paola %A Colombo,Piergiuseppe %A Spaggiari,Paola %A Manara,Sofia %A Sollai,Mauro %A Fiamengo,Barbara %A Brambilla,Tatiana %A Fernandes,Bethania %A Rao,Stefania %A Elamin,Abubaker %A Valeri,Marina %A De Carlo,Camilla %A Belsito,Vincenzo %A Lancellotti,Cesare %A Cieri,Miriam %A Cagini,Angelo %A Terracciano,Luigi %A Roncalli,Massimo %A Di Tommaso,Luca %+ Department of Pathology, Humanitas Clinical and Research Center – IRCCS, via Manzoni 56, Rozzano (MI), 20089, Italy, 39 0282244787, salvatore.renne@hunimed.eu %K COVID19 %K digital pathology %K Bayesian data analysis %K probabilistic modeling %D 2021 %7 22.2.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Transition to digital pathology usually takes months or years to be completed. We were familiarizing ourselves with digital pathology solutions at the time when the COVID-19 outbreak forced us to embark on an abrupt transition to digital pathology. Objective: The aim of this study was to quantitatively describe how the abrupt transition to digital pathology might affect the quality of diagnoses, model possible causes by probabilistic modeling, and qualitatively gauge the perception of this abrupt transition. Methods: A total of 17 pathologists and residents participated in this study; these participants reviewed 25 additional test cases from the archives and completed a final psychologic survey. For each case, participants performed several different diagnostic tasks, and their results were recorded and compared with the original diagnoses performed using the gold standard method (ie, conventional microscopy). We performed Bayesian data analysis with probabilistic modeling. Results: The overall analysis, comprising 1345 different items, resulted in a 9% (117/1345) error rate in using digital slides. The task of differentiating a neoplastic process from a nonneoplastic one accounted for an error rate of 10.7% (42/392), whereas the distinction of a malignant process from a benign one accounted for an error rate of 4.2% (11/258). Apart from residents, senior pathologists generated most discrepancies (7.9%, 13/164). Our model showed that these differences among career levels persisted even after adjusting for other factors. Conclusions: Our findings are in line with previous findings, emphasizing that the duration of transition (ie, lengthy or abrupt) might not influence the diagnostic performance. Moreover, our findings highlight that senior pathologists may be limited by a digital gap, which may negatively affect their performance with digital pathology. These results can guide the process of digital transition in the field of pathology. %M 33503002 %R 10.2196/24266 %U https://www.jmir.org/2021/2/e24266 %U https://doi.org/10.2196/24266 %U http://www.ncbi.nlm.nih.gov/pubmed/33503002 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 4 %P e15963 %T A Hematologist-Level Deep Learning Algorithm (BMSNet) for Assessing the Morphologies of Single Nuclear Balls in Bone Marrow Smears: Algorithm Development %A Wu,Yi-Ying %A Huang,Tzu-Chuan %A Ye,Ren-Hua %A Fang,Wen-Hui %A Lai,Shiue-Wei %A Chang,Ping-Ying %A Liu,Wei-Nung %A Kuo,Tai-Yu %A Lee,Cho-Hao %A Tsai,Wen-Chiuan %A Lin,Chin %+ Graduate Institute of Life Sciences, National Defense Medical Center, No 161, Min-Chun E Rd, Sec 6, Neihu, Taipei, 114, Taiwan, 886 287923100 ext 18574, xup6fup0629@gmail.com %K artificial intelligence %K bone marrow examination %K leukemia %K myelodysplastic syndrome %K deep learning %D 2020 %7 8.4.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: Bone marrow aspiration and biopsy remain the gold standard for the diagnosis of hematological diseases despite the development of flow cytometry (FCM) and molecular and gene analyses. However, the interpretation of the results is laborious and operator dependent. Furthermore, the obtained results exhibit inter- and intravariations among specialists. Therefore, it is important to develop a more objective and automated analysis system. Several deep learning models have been developed and applied in medical image analysis but not in the field of hematological histology, especially for bone marrow smear applications. Objective: The aim of this study was to develop a deep learning model (BMSNet) for assisting hematologists in the interpretation of bone marrow smears for faster diagnosis and disease monitoring. Methods: From January 1, 2016, to December 31, 2018, 122 bone marrow smears were photographed and divided into a development cohort (N=42), a validation cohort (N=70), and a competition cohort (N=10). The development cohort included 17,319 annotated cells from 291 high-resolution photos. In total, 20 photos were taken for each patient in the validation cohort and the competition cohort. This study included eight annotation categories: erythroid, blasts, myeloid, lymphoid, plasma cells, monocyte, megakaryocyte, and unable to identify. BMSNet is a convolutional neural network with the YOLO v3 architecture, which detects and classifies single cells in a single model. Six visiting staff members participated in a human-machine competition, and the results from the FCM were regarded as the ground truth. Results: In the development cohort, according to 6-fold cross-validation, the average precision of the bounding box prediction without consideration of the classification is 67.4%. After removing the bounding box prediction error, the precision and recall of BMSNet were similar to those of the hematologists in most categories. In detecting more than 5% of blasts in the validation cohort, the area under the curve (AUC) of BMSNet (0.948) was higher than the AUC of the hematologists (0.929) but lower than the AUC of the pathologists (0.985). In detecting more than 20% of blasts, the AUCs of the hematologists (0.981) and pathologists (0.980) were similar and were higher than the AUC of BMSNet (0.942). Further analysis showed that the performance difference could be attributed to the myelodysplastic syndrome cases. In the competition cohort, the mean value of the correlations between BMSNet and FCM was 0.960, and the mean values of the correlations between the visiting staff and FCM ranged between 0.952 and 0.990. Conclusions: Our deep learning model can assist hematologists in interpreting bone marrow smears by facilitating and accelerating the detection of hematopoietic cells. However, a detailed morphological interpretation still requires trained hematologists. %M 32267237 %R 10.2196/15963 %U http://medinform.jmir.org/2020/4/e15963/ %U https://doi.org/10.2196/15963 %U http://www.ncbi.nlm.nih.gov/pubmed/32267237 %0 Journal Article %@ 1929-073X %I JMIR Publications Inc. %V 4 %N 2 %P e11 %T A Virtual Microscope for Academic Medical Education: The Pate Project %A Brochhausen,Christoph %A Winther,Hinrich B %A Hundt,Christian %A Schmitt,Volker H %A Schömer,Elmar %A Kirkpatrick,C James %+ Laboratory for Regenerative Pathology and Interface Research (REPAIR-Lab), Institute of Pathology, University Medical Centre, Institut für Pathologie, Langenbeckstraße 1, Mainz, 55131, Germany, 49 6131 17 7307, brochhausen@pathologie.klinik.uni-mainz.de %K whole-slide imaging %K WSI %K virtual microscopy %K telepathology %K e-learning %K databases %K Internet %K microscopy %D 2015 %7 11.05.2015 %9 Original Paper %J Interact J Med Res %G English %X Background: Whole-slide imaging (WSI) has become more prominent and continues to gain in importance in student teaching. Applications with different scope have been developed. Many of these applications have either technical or design shortcomings. Objective: To design a survey to determine student expectations of WSI applications for teaching histological and pathological diagnosis. To develop a new WSI application based on the findings of the survey. Methods: A total of 216 students were questioned about their experiences and expectations of WSI applications, as well as favorable and undesired features. The survey included 14 multiple choice and two essay questions. Based on the survey, we developed a new WSI application called Pate utilizing open source technologies. Results: The survey sample included 216 students—62.0% (134) women and 36.1% (78) men. Out of 216 students, 4 (1.9%) did not disclose their gender. The best-known preexisting WSI applications included Mainzer Histo Maps (199/216, 92.1%), Histoweb Tübingen (16/216, 7.4%), and Histonet Ulm (8/216, 3.7%). Desired features for the students were latitude in the slides (190/216, 88.0%), histological (191/216, 88.4%) and pathological (186/216, 86.1%) annotations, points of interest (181/216, 83.8%), background information (146/216, 67.6%), and auxiliary informational texts (113/216, 52.3%). By contrast, a discussion forum was far less important (9/216, 4.2%) for the students. Conclusions: The survey revealed that the students appreciate a rich feature set, including WSI functionality, points of interest, auxiliary informational texts, and annotations. The development of Pate was significantly influenced by the findings of the survey. Although Pate currently has some issues with the Zoomify file format, it could be shown that Web technologies are capable of providing a high-performance WSI experience, as well as a rich feature set. %M 25963527 %R 10.2196/ijmr.3495 %U http://www.i-jmr.org/2015/2/e11/ %U https://doi.org/10.2196/ijmr.3495 %U http://www.ncbi.nlm.nih.gov/pubmed/25963527