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BACKGROUND: The 24-h urine protein (24-hUP) excretion is the gold standard for evaluating proteinuria. This study aimed to evaluate the diagnostic efficacy of protein/creatinine ratio (PCR) for estimating 24-hUP at various levels of renal function and proteinuria levels. METHODS: A cross-sectional study was conducted between December 2021 and December 2023 in Salvador, Bahia-Brazil, as an extension of previously published data from the TUNARI study. The study included 217 samples from 152 patients with various levels of renal function and proteinuria. PCR in isolated samples and 24-hUP were determined conventionally within a 24-h timeframe. Patients were classified into three groups according to the level of renal function (Group 1 = 10 to  60 mL/min) and level of proteinuria ( 3.5 g/day). The data were analyzed using the Spearman correlation (rs), coefficient of determination (r2), Bland-Altman plots and receiver operating characteristic (ROC) curve. Likelihood ratios, positive (LR +), and negative (LR-) were derived from the sensitivity and specificity of PCR. RESULTS: Mean age was 41.5 ± 15.7 years, 61.8% were women, 36.8% Black and 52% Mixed-race. Glomerulopathies constituted 80.3%; 46.1% with lupus nephritis. Of the total urine samples, we observed a high correlation between PCR in the total sample of 24-hUP sample (rs = 0.86, p  0.3-3.5 g/day, the sensitivity was 64.1%, the specificity was 84.6%, and the AUC was 0.76 (95% CI = 0.67; 0.84), PCR detected all cases > 3.5 g/day. CONCLUSIONS: PCR is a suitable measure to be used as an indicator of 24-hUP at different levels of renal function, but may have limitations at higher levels of proteinuria. Analysis of PCR by proteinuria level found that agreement as well as sensitivity decreases at higher levels, but it maintains good specificity and is able to identify nephrotic range proteinuria.

Liquid biopsies have the potential to revolutionize cancer care through non-invasive early detection of tumors. Developing a robust liquid biopsy test requires collecting high-dimensional data from a large number of blood samples across heterogeneous groups of patients. We propose that the generative capability of variational auto-encoders enables learning a robust and generalizable signature of blood-based biomarkers. In this study, we analyze orphan non-coding RNAs (oncRNAs) from serum samples of 1050 individuals diagnosed with non-small cell lung cancer (NSCLC) at various stages, as well as sex-, age-, and BMI-matched controls. We demonstrate that our multi-task generative AI model, Orion, surpasses commonly used methods in both overall performance and generalizability to held-out datasets. Orion achieves an overall sensitivity of 94% (95% CI: 87%-98%) at 87% (95% CI: 81%-93%) specificity for cancer detection across all stages, outperforming the sensitivity of other methods on held-out validation datasets by more than  ~ 30%.

Tools for rapid identification of novel and/or emerging viruses are urgently needed for clinical diagnosis of unexplained infections and pandemic preparedness. Here we developed and clinically validated a largely automated metagenomic next-generation sequencing (mNGS) assay for agnostic detection of respiratory viral pathogens from upper respiratory swab and bronchoalveolar lavage samples in

UNLABELLED: Given the challenges that SARS-CoV-2 variants have caused in terms of rapid spread and reduced vaccine efficacy, a rapid and cost-effective assay that can detect new and emerging variants is greatly needed worldwide. We have successfully applied the xenonucleic acid-based molecular-clamping technology to develop a multiplex reverse-transcription quantitative real-time PCR assay for SARS-CoV-2 multivariant detection. The assay was used to test 649 nasopharyngeal swab samples that were collected for clinical diagnosis or surveillance. The assay was able to correctly identify all 36 Delta variant samples as it accurately detected the D614G, T478K, and L452R mutations. In addition, the assay was able to correctly identify all 34 Omicron samples by detecting the K417N, T478K, N501Y, and D614G mutations. This technique reliably detects a variety of variants and has an analytical sensitivity of 100 copies/mL. In conclusion, this novel assay can serve as a rapid and cost-effective tool to facilitate large-scale detection of SARS-CoV-2 variants. IMPORTANCE: We have developed a multiplex reverse-transcription quantitative real-time PCR (RT-qPCR) testing platform for the rapid detection of SARS-CoV-2 variants using the xenonucleic acid (XNA)-based molecular-clamping technology. The XNA-based RT-qPCR assay can achieve high sensitivity with a limit of detection of about 100 copies/mL for variant detection which is much better than the next-generation sequencing (NGS) assay. Its turnaround time is about 4 hours with lower cost and a lot of Clinical Laboratory Improvement Amendments (CLIA) labs own the instrument and meet skillset requirements. This assay provides a rapid, reliable, and cost-effective testing platform for rapid detection and monitoring of known and emerging SARS-CoV-2 variants. This testing platform can be adopted by laboratories that perform routine SARS-CoV-2 PCR testing, providing a rapid and cost-effective method in lieu of NGS-based assays, for detecting, differentiating, and monitoring SARS-CoV-2 variants. This assay is easily scalable to any new variant(s) should it emerge.

INTRODUCTION: Biomarkers for Alzheimers disease neuropathologic change (ADNC) have been instrumental in developing effective disease-modifying therapeutics. However, to prevent/treat dementia effectively, we require biomarkers for non-AD neuropathologies; for this, neuropathologic examinations and annotated tissue samples are essential. METHODS: We conducted clinicopathologic correlation for the first 100 Alzheimers Disease Neuroimaging Initiative (ADNI) Neuropathology Core (NPC) cases. RESULTS: Clinical syndromes in this cohort showed 95% sensitivity and 79% specificity for predicting high/intermediate ADNC, a 21% false positive rate, and a ∼44% false negative rate. In addition, 60% with high/intermediate ADNC harbored additional potentially dementing co-pathologies. DISCUSSION: These results suggest that clinical presentation imperfectly predicts ADNC and that accurate prediction of high/intermediate ADNC does not exclude co-pathology that may modify presentation, biomarkers, and therapeutic responses. Therefore, new biomarkers are needed for non-AD neuropathologies. The ADNI NPC supports this mission with well-characterized tissue samples (available through ADNI and the National Institute on Aging) and gold-standard diagnostic information (soon to include digital histology). HIGHLIGHTS: The Alzheimers Disease Neuroimaging Initiative (ADNI) Neuropathology Core (NPC) brain donation cohort now exceeds 200 cases. ADNI NPC data in National Alzheimers Coordinating Center format are available through the Laboratory of Neuro Imaging. Digitized slide files from the ADNI NPC will be available in 2025. Requests for ADNI brain tissue samples can be submitted online for ADNI/National Institute on Aging evaluation. Clinical diagnoses of Alzheimers disease (AD)/AD and related dementias (ADRD) do not always predict post mortem neuropathology. Neuropathology is essential for the development of novel AD/ADRD biomarkers.

PurposeThis study compared the classification performance of normalized apparent diffusion coefficient (nADC) with percentage T2-FLAIR mismatch-volume (%T2FM-volume) for differentiating between IDH-mutant astrocytoma (IDHm-A) and other glioma molecular subtypes.MethodsA total of 105 non-enhancing gliomas were studied. T2-FLAIR digital subtraction maps were used to identify T2FM and T2-FLAIR non-mismatch (T2FNM) subregions within tumor volumes of interest (VOIs). Median nADC from the whole tumor, T2FM, and T2NFM subregions and %T2FM-volume were obtained. IDHm-A classification analyses using receiver-operating characteristic curves and multiple logistic regression were performed in addition to exploratory survival analyses.ResultsT2FM subregions had significantly higher nADC than T2FNM subregions within IDHm-A with ≥ 25% T2FM-volume (P

BACKGROUND: Cerebrospinal fluid (CSF) oligoclonal bands (OCB) are a diagnostic biomarker in multiple sclerosis (MS). The central vein sign (CVS) is an imaging biomarker for MS that may improve diagnostic accuracy. OBJECTIVES: The objective of the study is to examine the diagnostic performance of simplified CVS methods in comparison to OCB in participants with clinical or radiological suspicion for MS. METHODS: Participants from the CentrAl Vein Sign in MS (CAVS-MS) pilot study with CSF testing were included. Select-3 and Select-6 (counting up to three or six CVS+ lesions per scan) were rated on post-gadolinium FLAIR* images. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value for Select-3, Select-6, OCB, and combinations thereof were calculated for MS diagnosis at baseline and at 12 months. RESULTS: Of 53 participants, 25 were OCB+. At baseline, sensitivity for MS diagnosis was 0.75 for OCB, 0.83 for Select-3, and 0.71 for Select-6. Specificity for MS diagnosis was 0.76 for OCB, 0.48 for Select-3, and 0.86 for Select-6. At 12 months, PPV for MS diagnosis was 0.95 for Select-6 and 1.00 for Select-6 with OCB+ status. DISCUSSION: Results suggest similar diagnostic performance of simplified CVS methods and OCB. Ongoing studies will refine whether CVS could be used in replacement or in conjunction with OCB.

BACKGROUND: One-fifth of the global population is infected with soil-transmitted helminths (STH). Mass drug administration (MDA) with deworming medication is widely implemented to control morbidity associated with STH infections. However, surveillance of human infection prevalence by collecting individual stool samples is time-consuming, costly, often stigmatized, and logistically challenging. Current methods of STH detection are poorly sensitive, particularly in low-intensity and low-prevalence populations. METHODOLOGY/PRINCIPAL FINDINGS: We aimed to develop a sensitive and specific molecular method for detecting STH DNA in large volumes of soil (20 g) by conducting laboratory and proof of concept studies across field sites in Kenya, Benin, and India. We collected human stool (n = 669) and soil (n = 478) from 322 households across the three study sites. We developed protocols for DNA extraction from 20 g of soil and qPCR to detect Ascaris lumbricoides, Trichuris trichiura, Necator americanus, and Ancylostoma duodenale. Agreement between detection of STH via qPCR, digital droplet PCR (ddPCR), and microscopy-based methods was assessed using the Cohens Kappa statistic. Finally, we estimated associations between soil characteristics and detection of STH in soil by qPCR, as well as between STH detected in soil and STH detected in stool from matched households, adjusting for soil characteristics. The overall prevalence of STH in soil by qPCR was 31% for A. lumbricoides, 3% for T. trichiura, and 13% for any hookworm species. ddPCR and qPCR performed similarly. However, there was poor agreement between STH detected in soil by qPCR versus light microscopy. Microscopy underestimated the prevalence of A. lumbricoides and N. americanus and overestimated T. trichiura. Detection of an STH species in household soil was strongly associated with increased odds of a household member being infected with that same species. CONCLUSIONS/SIGNIFICANCE: Soil surveillance for STH has several benefits over stool-based surveillance, including lower cost and higher success rates for sample collection. Considering that delivery of MDA occurs at the community level, environmental surveillance using molecular methods could be a cost-effective alternate strategy for monitoring STH in these populations.

PurposeCirculating tumor DNA (ctDNA) testing has become a promising tool to guide first-line (1L) targeted treatment for advanced non-small cell lung cancer (aNSCLC). This study aims to estimate the clinical validity (CV) and clinical utility (CU) of ctDNA-based next-generation sequencing (NGS) for oncogenic driver mutations to inform 1L treatment decisions in aNSCLC through a systematic literature review and meta-analysis.MethodsA systematic literature search was conducted in PubMed/MEDLINE and Embase to identify randomized control trials or observational studies reporting CV/CU on ctDNA testing in patients with aNSCLC. Meta-analyses were performed using bivariate random-effects models to estimate pooled sensitivity and specificity. Progression-free/overall survival (PFS/OS) was summarized for CU studies.ResultsA total of 20 studies were identified: 17 CV only, 2 CU only, and 1 both, and 13 studies were included for the meta-analysis on multi-gene detection. The overall sensitivity and specificity for ctDNA detection of any mutation were 0.69 (95% CI 0.63-0.74) and 0.99 (95% CI 0.97-1.00), respectively. However, sensitivity varied greatly by driver gene, ranging from 0.29 (95% CI 0.13-0.53) for ROS1 to 0.77 (95% CI 0.63-0.86) for KRAS. Two studies that compared PFS with ctDNA versus tissue-based testing followed by 1L targeted therapy found no significant differences. One study reported OS curves on ctDNA-matched and tissue-matched therapies but no hazard ratios were provided.ConclusionsctDNA testing demonstrated an overall acceptable diagnostic accuracy in patients with aNSCLC, however, sensitivity varied greatly by driver mutation. Further research is needed, especially for uncommon driver mutations, to better understand the CU of ctDNA testing in guiding targeted treatments for aNSCLC.

Point-of-care serological and direct antigen testing offers actionable insights for diagnosing challenging illnesses, empowering distributed health systems. Here, we report a POC-compatible serologic test for Lyme disease (LD), leveraging synthetic peptides specific to LD antibodies and a paper-based platform for rapid, and cost-effective diagnosis. Antigenic epitopes conserved across Borrelia burgdorferi genospecies, targeted by IgG and IgM antibodies, are selected to develop a multiplexed panel for detection of LD antibodies from patient sera. Multiple peptide epitopes, when combined synergistically with a machine learning-based diagnostic model achieve high sensitivity without sacrificing specificity. Blinded validation with 15 LD-positive and 15 negative samples shows 95.5% sensitivity and 100% specificity. Blind testing with the CDCs LD repository samples confirms the test accuracy, matching lab-based two-tier results, correctly differentiating between LD and look-alike diseases. This LD diagnostic test could potentially replace the cumbersome two-tier testing, improving diagnosis and enabling earlier treatment while facilitating immune monitoring and surveillance.

IntroductionAlzheimer's disease (AD) pathology is defined by β-amyloid (Aβ) plaques and neurofibrillary tau, but Lewy bodies (LBs; ?-synuclein aggregates) are a common co-pathology for which effective biomarkers are needed.MethodsA validated α-synuclein Seed Amplification Assay (SAA) was used on recent cerebrospinal fluid (CSF) samples from 1638 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 78 with LB-pathology confirmation at autopsy. We compared SAA outcomes with neuropathology, Aβ and tau biomarkers, risk-factors, genetics, and cognitive trajectories.ResultsSAA showed 79% sensitivity and 97% specificity for LB pathology, with superior performance in identifying neocortical (100%) compared to limbic (57%) and amygdala-predominant (60%) LB-pathology. SAA+ rate was 22%, increasing with disease stage and age. Higher Aβ burden but lower CSF p-tau181 associated with higher SAA+ rates, especially in dementia. SAA+ affected cognitive impairment in MCI and Early-AD who were already AD biomarker positive.DiscussionSAA is a sensitive, specific marker for LB-pathology. Its increase in prevalence with age and AD stages, and its association with AD biomarkers, highlights the clinical importance of α-synuclein co-pathology in understanding AD's nature and progression.HighlightsSAA shows 79% sensitivity, 97% specificity for LB-pathology detection in AD. SAA positivity prevalence increases with disease stage and age. Higher Aβ burden, lower CSF p-tau181 linked with higher SAA+ rates in dementia. SAA+ impacts cognitive impairment in early disease stages. Study underpins need for wider LB-pathology screening in AD treatment.

A neural network was developed to detect and characterize bowel obstruction, a common cause of acute abdominal pain. In this retrospective study, 202 CT scans of 165 patients with bowel obstruction from March to June 2022 were included and partitioned into training and test data sets. A multi-channel neural network was trained to segment the gastrointestinal tract, and to predict the diameter and the longitudinal position (longitude) along the gastrointestinal tract using a novel embedding. Its performance was compared to manual segmentations using the Dice score, and to manual measurements of the diameter and longitude using intraclass correlation coefficients (ICC). ROC curves as well as sensitivity and specificity were calculated for diameters above a clinical threshold for obstruction, and for longitudes corresponding to small bowel. In the test data set, Dice score for segmentation of the gastrointestinal tract was 78 ± 8%. ICC between measured and predicted diameters was 0.72, indicating moderate agreement. ICC between measured and predicted longitude was 0.85, indicating good agreement. AUROC was 0.90 for detection of dilated bowel, and was 0.95 and 0.90 for differentiation of the proximal and distal gastrointestinal tract respectively. Overall sensitivity and specificity for dilated small bowel were 0.83 and 0.90. Since obstruction is diagnosed based on the diameter and longitude of the bowel, this neural network and embedding may enable detection and characterization of this important disease on CT.

Nucleocapsid antibody assays can be used to estimate SARS-CoV-2 infection prevalence in regions implementing spike-based COVID-19 vaccines. However, poor sensitivity of nucleocapsid antibody assays in detecting infection after vaccination has been reported. We derived a lower cutoff for identifying previous infections in a large blood donor cohort (N = 142,599) by using the Ortho VITROS Anti-SARS-CoV-2 Total-N Antibody assay, improving sensitivity while maintaining specificity >98%. We validated sensitivity in samples donated after self-reported swab-confirmed infections diagnoses. Sensitivity for first infections in unvaccinated donors was 98.1% (95% CI 98.0-98.2) and for infection after vaccination was 95.6% (95% CI 95.6-95.7) based on the standard cutoff. Regression analysis showed sensitivity was reduced in the Delta compared with Omicron period, in older donors, in asymptomatic infections,

Purpose To assess the performance of a local open-source large language model (LLM) in various information extraction tasks from real-life emergency brain MRI reports. Materials and Methods All consecutive emergency brain MRI reports written in 2022 from a French quaternary center were retrospectively reviewed. Two radiologists identified MRI scans that were performed in the emergency department for headaches. Four radiologists scored the reports conclusions as either normal or abnormal. Abnormalities were labeled as either headache-causing or incidental. Vicuna (LMSYS Org), an open-source LLM, performed the same tasks. Vicunas performance metrics were evaluated using the radiologists consensus as the reference standard. Results Among the 2398 reports during the study period, radiologists identified 595 that included headaches in the indication (median age of patients, 35 years [IQR, 26-51 years]; 68% [403 of 595] women). A positive finding was reported in 227 of 595 (38%) cases, 136 of which could explain the headache. The LLM had a sensitivity of 98.0% (95% CI: 96.5, 99.0) and specificity of 99.3% (95% CI: 98.8, 99.7) for detecting the presence of headache in the clinical context, a sensitivity of 99.4% (95% CI: 98.3, 99.9) and specificity of 98.6% (95% CI: 92.2, 100.0) for the use of contrast medium injection, a sensitivity of 96.0% (95% CI: 92.5, 98.2) and specificity of 98.9% (95% CI: 97.2, 99.7) for study categorization as either normal or abnormal, and a sensitivity of 88.2% (95% CI: 81.6, 93.1) and specificity of 73% (95% CI: 62, 81) for causal inference between MRI findings and headache. Conclusion An open-source LLM was able to extract information from free-text radiology reports with excellent accuracy without requiring further training. Keywords: Large Language Model (LLM), Generative Pretrained Transformers (GPT), Open Source, Information Extraction, Report, Brain, MRI Supplemental material is available for this article. Published under a CC BY 4.0 license. See also the commentary by Akinci DAntonoli and Bluethgen in this issue.

PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians' performance using artificial intelligence (AI) vs standard-of-care methods for tumor delineation. MATERIALS AND METHODS: Cases were interpreted by 7 urologists and 3 radiologists from 5 institutions with 2 to 23 years of experience. Each reader evaluated 50 prostatectomy cases retrospectively eligible for focal therapy. Each case included a T2-weighted MRI, contours of the prostate and region(s) of interest suspicious for cancer, and a biopsy report. First, readers defined cancer contours cognitively, manually delineating tumor boundaries to encapsulate all clinically significant disease. Then, after ≥ 4 weeks, readers contoured the same cases using AI software. Using tumor boundaries on whole-mount histopathology slides as ground truth, AI-assisted, cognitively-defined, and hemigland cancer contours were evaluated. Primary outcome measures were the accuracy and negative margin rate of cancer contours. All statistical analyses were performed using generalized estimating equations. RESULTS: The balanced accuracy (mean of voxel-wise sensitivity and specificity) of AI-assisted cancer contours (84.7%) was superior to cognitively-defined (67.2%) and hemigland contours (75.9%; P < .0001). Cognitively-defined cancer contours systematically underestimated cancer extent, with a negative margin rate of 1.6% compared to 72.8% for AI-assisted cancer contours (P < .0001). CONCLUSIONS: AI-assisted cancer contours reduce underestimation of prostate cancer extent, significantly improving contouring accuracy and negative margin rate achieved by physicians. This technology can potentially improve outcomes, as accurate contouring informs patient management strategy and underpins the oncologic efficacy of treatment.

BACKGROUND: Serum AFP-L3%, AFP, and DCP are useful biomarkers for HCC detection, but their utility in assessing treatment response remains unknown. We aim to evaluate the accuracy of a biomarker model in the detection of posttreatment viable tumors. METHODS: For model derivation, recipients with HCC undergoing liver transplant from 2018 to 2022 who had biomarkers collected within 3 months before transplant were included. We developed a generalized linear model for detecting posttreatment viable tumors with the 3 biomarkers as covariates, which we termed the LAD Score. An independent cohort of 117 patients with HCC was used for external validation. RESULTS: Among 205 recipients of transplant, 70.2% had evidence of viable tumor on explant. The median LAD score was higher among patients with viable versus nonviable tumors (1.06 vs. 0.465, p < 0.001). The LAD score had a sensitivity of 55.6% and a specificity of 85.1% at the cutoff of 0.927, which was more accurate than imaging for detecting posttreatment viable tumors (AUROC 0.736 vs. 0.643, respectively; p = 0.045). The superior performance of the LAD score over imaging is primarily driven by its greater accuracy in detecting tumors

UNLABELLED: Invasive mold infections (IMIs) are associated with high morbidity, particularly in immunocompromised patients, with mortality rates between 40% and 80%. Early initiation of appropriate antifungal therapy can substantially improve outcomes, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high-resolution melting (U-dHRM) analysis may enable rapid and robust diagnoses of IMI. A universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these pathogen curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons. U-dHRM achieved 97% overall fungal organism identification accuracy and a turnaround time of ~4 hrs. U-dHRM detected pathogenic molds (Aspergillus, Mucorales, Lomentospora, and Fusarium) in 73% of 30 samples classified as IMI, including mixed infections. Specificity was optimized by requiring the number of pathogenic mold curves detected in a sample to be >8 and a sample volume to be 1 mL, which resulted in 100% specificity in 21 at-risk patients without IMI. U-dHRM showed promise as a separate or combination diagnostic approach to standard mycological tests. U-dHRMs speed, ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples, and detect emerging opportunistic pathogens may aid treatment decisions, improving patient outcomes. IMPORTANCE: Improvements in diagnostics for invasive mold infections are urgently needed. This work presents a new molecular detection approach that addresses technical and workflow challenges to provide fast pathogen detection, identification, and quantification that could inform treatment to improve patient outcomes.

Tuberculosis (TB) remains a leading cause of death from an infectious disease worldwide, partly due to a lack of effective strategies to screen and triage individuals with potential TB. Whole blood RNA signatures have been tested as biomarkers for TB, but have failed to meet the World Health Organizations (WHO) optimal target product profiles (TPP). Here, we use RNA sequencing and machine-learning to investigate the utility of plasma cell-free RNA (cfRNA) as a host-response biomarker for TB in cohorts from Uganda, Vietnam and Philippines. We report a 6-gene cfRNA signature, which differentiates TB-positive and TB-negative individuals with AUC = 0.95, 0.92, and 0.95 in test, training and validation, respectively. This signature meets WHO TPPs (sensitivity: 97.1% [95% CI: 80.9-100%], specificity: 85.2% [95% CI: 72.4-100%]) regardless of geographic location, sample collection method and HIV status. Overall, our results identify plasma cfRNA as a promising host response biomarker to diagnose TB.

We herein present a multifunctional self-priming hairpin probe-based isothermal amplification, termed MSH, enabling one-pot detection of target nucleic acids. The sophisticatedly designed multifunctional self-priming hairpin (MSH) probe recognizes the target and rearranges to prime itself, triggering the amplification reaction powered by the continuously repeated extension, nicking, and target recycling. As a consequence, a large number of double-stranded DNA (dsDNA) amplicons are produced that could be monitored in real-time using a dsDNA-intercalating dye. Based on this unique design approach, the nucleocapsid (N) and the open reading frame 1 ab (ORF1ab) genes of SARS-CoV-2 were successfully detected down to 1.664 fM and 0.770 fM, respectively. The practical applicability of our method was validated by accurately diagnosing 60 clinical samples with 93.33% sensitivity and 96.67% specificity. This isothermal one-pot MSH technique holds great promise as a point-of-care testing protocol for the reliable detection of a wide spectrum of pathogens, particularly in resource-limited settings.

BackgroundS100A8 is a melanoma biomarker expressed in the melanoma-associated epidermal keratinocytes, but its diagnostic utility has not been compared with other biomarkers, including PRAME.ObjectivesTo compare the utility of S100A8 and PRAME immunohistochemistry (IHC) in the differential diagnosis of melanoma and naevi in a case-control study.MethodsA previously described cohort of 209 melanomas (case samples) and naevi (control samples) dual-immunostained for S100A8 and PRAME were included. For S100A8, previously reported scores indicating the proportion of tumour-associated epidermis stained (0 = indeterminate; 1 = 0-4%; 2 = 5-25%; 3 = 26-50%; 4 = 51-75%; 5 = > 75%) were utilized. PRAME IHC was reviewed by at least two reviewers and a consensus score assigned, with score indicating the proportion of tumour stained (0 = indeterminate; 1 = 0%; 2 = 1-50%; 3 = > 50%). A positive test was defined as > 50% staining.ResultsThe area under the receiver operating characteristic curves for S100A8 (0.833) and PRAME (0.874) were not significantly different from each other (P = 0.22). The diagnostic sensitivity and specificity were 42.4% [95% confidence interval (CI) 32.6-52.8%] and 98.2% (95% CI 93.6-99.8%) for S100A8, and 79.8% (95% CI 70.5-87.2%) and 87.3% (95% CI 79.6-92.9%) for PRAME, respectively. A combined test requiring both S100A8 and PRAME IHC positivity had a sensitivity of 39.4% (95% CI 29.7-49.7%) and specificity of 99.1% (95% CI 95.0-100.0%).ConclusionsS100A8 and PRAME have utility in the diagnostic workup of melanoma, with S100A8 being more specific and PRAME being more sensitive when using this threshold. Our findings suggest that these two immunohistochemical markers may favourably complement one another to improve the detection of melanoma.

BackgroundSputum-based testing is a barrier to increasing access to molecular diagnostics for tuberculosis (TB). Many people with TB are unable to produce sputum, and sputum processing increases assay complexity and cost. Tongue swabs are emerging as an alternative to sputum, but performance limits are uncertain.MethodsFrom June 2022 to July 2023, we enrolled 397 consecutive adults with cough >2 weeks at 2 health centers in Kampala, Uganda. We collected demographic and clinical information, sputum for TB testing (Xpert MTB/RIF Ultra and 2 liquid cultures), and tongue swabs for same-day quantitative polymerase chain reaction (qPCR) testing. We evaluated tongue swab qPCR diagnostic accuracy versus sputum TB test results, quantified TB targets per swab, assessed the impact of serial swabbing, and compared 2 swab types (Copan FLOQSWAB and Steripack spun polyester).ResultsAmong 397 participants, 43.1% were female, median age was 33 years, 23.5% were diagnosed with human immunodeficiency virus, and 32.0% had confirmed TB. Sputum Xpert Ultra and tongue swab qPCR results were concordant for 98.2% (95% confidence interval [CI]: 96.2-99.1) of participants. Tongue swab qPCR sensitivity was 92.6% (95% CI: 86.5 to 96.0) and specificity was 99.1% (95% CI: 96.9 to 99.8) versus microbiological reference standard. A single tongue swab recovered a 7-log range of TB copies, with a decreasing recovery trend among 4 serial swabs. Swab types performed equivalently.ConclusionsTongue swabs are a promising alternative to sputum for molecular diagnosis of TB, with sensitivity approaching sputum-based molecular tests. Our results provide valuable insights for developing successful tongue swab-based TB diagnostics.

IntroductionLewy body disease (LBD) is a common primary or co-pathology in neurodegenerative syndromes. An alpha-synuclein seed amplification assay (αSyn-SAA) is clinically available, but clinical performance, especially lower sensitivity in amygdala-predominant cases, is not well understood.MethodsAntemortem CSF from neuropathology-confirmed LBD cases was tested with αSyn-SAA (N = 56). Diagnostic performance and clinicopathological correlations were examined.ResultsSimilar to prior reports, sensitivity was 100% for diffuse and transitional LBD (9/9), and overall specificity was 96.3% (26/27). Sensitivity was lower in amygdala-predominant (6/14, 42.8%) and brainstem-predominant LBD (1/6, 16.7%), but early spread outside these regions (without meeting criteria for higher stage) was more common in αSyn-SAA-positive cases (6/7, 85.7%) than negative (2/13, 15.4%).DiscussionIn this behavioral neurology cohort, αSyn-SAA had excellent diagnostic performance for cortical LBD. In amygdala- and brainstem-predominant cases, sensitivity was lower, but positivity was associated with anatomical spread, suggesting αSyn-SAA detects early LBD progression in these cohorts.HighlightsA cerebrospinal fluid alpha-synuclein assay detects cortical LBD with high sensitivity/specificity. Positivity in prodromal stages of LBD was associated with early cortical spread. The assay provides precision diagnosis of LBD that could support clinical trials. The assay can also identify LBD co-pathology, which may impact treatment responses.

Viral outbreaks can cause widespread disruption, creating the need for diagnostic tools that provide high performance and sample versatility at the point of use with moderate complexity. Current gold standards such as PCR and rapid antigen tests fall short in one or more of these aspects. Here, we report a label-free and amplification-free nanopore sensor platform that overcomes these challenges via direct detection and quantification of viral RNA in clinical samples from a variety of biological fluids. The assay uses an optofluidic chip that combines optical waveguides with a fluidic channel and integrates a solid-state nanopore for sensing of individual biomolecules upon translocation through the pore. High specificity and low limit of detection are ensured by capturing RNA targets on microbeads and collecting them by optical trapping at the nanopore location where targets are released and rapidly detected. We use this device for longitudinal studies of the viral load progression for Zika and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in marmoset and baboon animal models, respectively. The up to million-fold trapping-based target concentration enhancement enables amplification-free RNA quantification across the clinically relevant concentration range down to the assay limit of RT-qPCR as well as cases in which PCR failed. The assay operates across all relevant biofluids, including semen, urine, and whole blood for Zika and nasopharyngeal and throat swab, rectal swab, and bronchoalveolar lavage for SARS-CoV-2. The versatility, performance, simplicity, and potential for full microfluidic integration of the amplification-free nanopore assay points toward a unique approach to molecular diagnostics for nucleic acids, proteins, and other targets.

Screening for psychosis spectrum disorders in primary care could improve early identification and reduce the duration of untreated psychosis. However, the accuracy of psychosis screening in this setting is unknown. To address this, we conducted a diagnostic accuracy study of screening for psychosis spectrum disorders in eight behavioral health services integrated into primary care clinics. Patients attending an integrated behavioral health appointment at their primary care clinic completed the Prodromal Questionnaire - Brief (PQ-B) immediately prior to their intake assessment. This was compared to a diagnostic phone interview based on the Structured Interview for Psychosis Risk Syndromes (SIPS). In total, 145 participants completed all study procedures, of which 100 screened positive and 45 negative at a provisional PQ-B threshold of ≥20. The PQ-B was moderately accurate at differentiating psychosis spectrum from no psychosis spectrum disorders; a PQ-B distress score of ≥27 had a sensitivity and specificity of 71.2 % and 57.0 % respectively. In total, 66 individuals (45.5 %) met criteria for a psychosis spectrum disorder and 24 (16.7 %) were diagnosed with full psychosis, indicating a high prevalence of psychosis in the sample. Overall, screening for psychosis spectrum disorders in an IBH primary care setting identified a relatively high number of individuals and may identify people that would otherwise be missed. The PQ-B performed slightly less well than in population-based screening in community mental health settings. However, the findings suggest this may represent an effective way to streamline the pathway between specialty early psychosis programs and primary care clinics for those in need.

BACKGROUND: A rapid and affordable point-of-care test is a priority for Neisseria gonorrhoeae control. WHO and Foundation for Innovative New Diagnostics (FIND) have a target product profile for a non-molecular N gonorrhoeae rapid point-of-care test that requires a clinical sensitivity of greater than 80% and a specificity over 95% to be considered useful in syndromic management; test turnaround time should be 30 min or under, and the test should cost less than US$3. A novel lateral flow assay (LFA) was developed to achieve that profile. METHODS: In this cross-sectional study we evaluated the performance of the novel N gonorrhoeae lateral flow assay (NG-LFA) at the primary health-care level in South Africa. Male patients with urethral discharge syndrome and female patients with vaginal discharge syndrome were recruited from five primary health-care facilities in the Buffalo City Metropolitan Municipality health district of South Africa. First-void urine specimens and nurse-collected vaginal swabs were tested in-facility with the NG-LFA and Xpert CT/NG PCR assay. N gonorrhoeae multi-antigen sequence typing (NG-MAST) was performed on all LFA positive specimens. FINDINGS: Between March 7, and Sept 19, 2022, we enrolled 200 male patients with urethral discharge and 200 female patients with vaginal discharge. The median age of male patients was 24 years (IQR 21-31 years), and the median age of female patients was 25 years (IQR 21-32 years). In addition, 23 male patients and 12 female patients who presented at the facility with a partner notification slip were enrolled of whom one (4%) and five (42%) were symptomatic, respectively. NG-LFA and Xpert results were available for all participants. In urine specimens, NG-LFA sensitivity was 96·1% (Wilson 95% CI 91·2-98·3; 123 LFA-positive among 128 PCR-positive specimens) and 91·7% in vaginal swab specimens (78·2-97·1; 33 LFA-positive among 36 PCR-positive). The specificity was 97·2% in urine specimens (90·4-99·2; 70 LFA-negative among 72 PCR-negative) and 96·3% in vaginal specimens (92·2-98·3; 158 LFA-negative among 164 PCR-negative). In 156 LFA-positive specimens, NG-MAST showed 93 different sequence types. INTERPRETATION: The novel NG-LFA had excellent clinical sensitivity and specificity in symptomatic male and female patients. The test met the optimal requirement for sensitivity and the minimal requirement for specificity specified in the target product profile. NG-LFA could provide an important tool to optimise clinical management and reduce excess antibiotic use in settings without direct access to laboratory testing. FUNDING: Global Antimicrobial Resistance Innovation Fund (GAMRIF) via FIND and National Institutes of Health.

BackgroundNon-sputum-based triage tests for tuberculosis are a priority for ending tuberculosis. We aimed to evaluate the diagnostic accuracy of the late-prototype Xpert MTB Host Response (Xpert HR) blood-based assay.MethodsWe conducted a prospective diagnostic accuracy study among outpatients with presumed tuberculosis in outpatient clinics in Viet Nam, India, the Philippines, Uganda, and South Africa. Eligible participants were aged 18 years or older and reported cough lasting at least 2 weeks. We excluded those receiving tuberculosis treatment in the preceding 12 months and those who were unwilling to consent. Xpert HR was performed on capillary or venous blood. Reference standard testing included sputum Xpert MTB/RIF Ultra and mycobacterial culture. We performed receiver operating characteristic (ROC) analysis to identify the optimal cutoff value for the Xpert HR to achieve the target sensitivity of 90% or more while maximising specificity, then calculated diagnostic accuracy using this cutoff value. This study was prospectively registered with ClinicalTrials.gov, NCT04923958.FindingsBetween July 13, 2021, and Aug 15, 2022, 2046 adults with at least 2 weeks of cough were identified, of whom 1499 adults (686 [45·8%] females and 813 [54·2%] males) had valid Xpert HR and reference standard results. 329 (21·9%) had microbiologically confirmed tuberculosis. Xpert HR had an area under the ROC curve of 0·89 (95% CI 0·86-0·91). The optimal cutoff value was less than or equal to -1·25, giving a sensitivity of 90·3% (95% CI 86·5-93·3; 297 of 329) and a specificity of 62·6% (95% CI 59·7-65·3; 732 of 1170). Sensitivity was similar across countries, by sex, and by subgroups, although specificity was lower in people living with HIV (45·1%, 95% CI 37·8-52·6) than in those not living with HIV (65·9%, 62·8-68·8; difference of 20·8%, 95% CI 13·0-28·6; p

IntroductionIn high-burden settings, low-complexity screening tests for tuberculosis (TB) could expand the reach of community-based case-finding efforts. The potential costs and cost-effectiveness of approaches incorporating these tests are poorly understood.MethodsWe developed a microsimulation model assessing 3 approaches to community-based case-finding in hypothetical populations (India-, South Africa-, The Philippines-, Uganda-, and Vietnam-like settings) with TB prevalence 4 times that of national estimates: (1) screening with a point-of-care C-reactive protein (CRP) test, (2) screening with a more sensitive "Hypothetical Screening test" (95% sensitive for Xpert Ultra-positive TB, 70% specificity; equipment/labor costs similar to Xpert Ultra, but using a $2 cartridge) followed by sputum Xpert Ultra if positive, or (3) testing all individuals with sputum Xpert Ultra. Costs are expressed in 2023 US dollars and include treatment costs.ResultsUniversal Xpert Ultra was estimated to cost a mean $4.0 million (95% uncertainty range: $3.5 to $4.6 million) and avert 3200 (2600 to 3900) TB-related disability-adjusted life years (DALYs) per 100 000 people screened ($670 [The Philippines] to $2000 [Vietnam] per DALY averted). CRP was projected to cost $550 (The Philippines) to $1500 (Vietnam) per DALY averted but with 44% fewer DALYs averted. The Hypothetical Screening test showed minimal benefit compared to universal Xpert Ultra, but if specificity were improved to 95% and per-test cost to $4.5 (all-inclusive), this strategy could cost $390 (The Philippines) to $940 (Vietnam) per DALY averted.ConclusionsScreening tests can meaningfully improve the cost-effectiveness of community-based case-finding for TB but only if they are sensitive, specific, and inexpensive.

BackgroundEnamel is highly transparent at short wavelength infrared imaging (SWIR) wavelengths allowing the detection of dental decay without the need for ionizing radiation. The purpose of this study was to use SWIR imaging methods including cross polarization optical coherence tomography (CP-OCT), occlusal transillumination (SWIR-OT), proximal transillumination (SWIR-PT), and occlusal reflectance (SWIR-R) to image interproximal lesions in vivo and compare the sensitivity with radiography.MethodsParticipants (n = 30) aged 18-80 each with a radiopositive interproximal lesion scheduled for restoration were enrolled in the study. Studies have shown that the opposing proximal surfaces across the contact will likely also have lesions. SWIR images were acquired of the adjoining teeth at each contact with an interproximal lesion scheduled for restoration. Lesion presence and depth were assessed on each side of the contact for radiography and each SWIR imaging method. Lesions on radiographs and in CP-OCT images were identified by a single examiner while lesions in SWIR images were identified by a contrast threshold via semi-automatic image segmentation.ResultsAll SWIR imaging methods had significantly higher sensitivity (P

PURPOSE: This study aims to explore the potential subgroups of sarcoidosis-associated uveitis (SAU) within a multicenter cohort of uveitis participants. DESIGN: Cross-sectional study. PARTICIPANTS: A cohort of 826 uveitis patients from a uveitis registry from 19 clinical centers in 12 countries between January 2011 and April 2015. METHODS: We employed a latent class analysis (LCA) incorporating recommended tests and clinical signs from the revised International Workshop on Ocular Sarcoidosis (IWOS) to identify potential SAU subgroups within the multicenter uveitis cohort. Additionally, we assessed the performance of the individual tests and clinical signs in classifying the potential subclasses. MAIN OUTCOME MEASURES: Latent subtypes of SAU. RESULTS: Among 826 participants included in this analysis, the 2-class LCA model provided a best fit, with the lowest Bayesian information criteria of 7218.7 and an entropy of 0.715. One class, consisting of 548 participants, represented the non-SAU, whereas the second class, comprised of 278 participants, was most representative of SAU. Snowballs/string of pearls vitreous opacities had the best test performance for classification, followed by bilaterality and bilateral hilar lymphadenopathy (BHL). The combination of 4 tests with the highest classification importance, including snowballs/string of pearls vitreous opacities, periphlebitis and/or macroaneurysm, bilaterality, and BHL, demonstrated a sensitivity of 84.8% and a specificity of 95.4% in classifying the SAU subtypes. In the exploratory analysis of the 3-class LCA model, which had comparable fit indices as the 2-class model, we identified a candidate non-SAU subtype, candidate SAU subtype with pulmonary involvement, and a candidate SAU with less pulmonary involvement. CONCLUSIONS: Latent class modeling, incorporating tests and clinical signs from the revised IWOS criteria, effectively identified a subset of participants with clinical features indicative of SAU. Though the sensitivity of individual ocular signs or tests was not perfect, using a combination of tests provided a satisfactory performance in classifying the SAU subclasses identified by the 2-class LCA model. Notably, the classes identified by the 3-class LCA model, including a non-SAU subtype, an SAU subtype with pulmonary involvement, and an SAU subtype with less pulmonary involvement, may have potential implication for clinical practice, and hence should be validated in further research. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

In patients with peripheral pulmonary lesions (PPLs), nondiagnostic bronchoscopy results are not uncommon. The conventional approach to estimate the probability of cancer (pCA) after bronchoscopy relies on dichotomous test assumptions, using prevalence, sensitivity, and specificity to determine negative predictive value. However, bronchoscopy is a multidisease test, raising concerns about the accuracy of dichotomous methods. By how much does calculating pCA using a dichotomous approach (pCA dichotomous) underestimate the true pCA when applied to multidisease tests like bronchoscopy for the diagnosis of PPL? In this meta-analysis of cohort studies involving radial endobronchial ultrasound for PPL, Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed, constructing 2 × 2 contingency tables for calculating pCA dichotomous. For the multidisease test approach, 3 × 3 contingency tables for calculating probability of malignancy for a test that can have different categories of results and can diagnose multiple diseases (pCA multidisease) using the likelihood ratio (LR) method for nondiagnostic results (LR(T 0)) was used. Observed malignancy rates in patients with nondiagnostic results were compared with pCA dichotomous and pCA multidisease. In 46 studies (7,506 patients), malignancy was the underlying diagnosis in 76% of cases, another specific disease in 13% of cases, and nonspecific fibrosis or scar in 10% of cases. The percentage of patients with nondiagnostic results who had malignancy matched pCA multidisease across all studies. In contrast, pCA dichotomous consistently underestimated cancer risk (median difference, 0.12; interquartile range, 0.06-0.23), particularly in studies with a higher prevalence of nonmalignant disease. The pooled LR(T 0) was 0.46 (95% CI, 0.40-0.52; I 2 = 76%; P <.001) and correlated with the prevalence of nonmalignant diseases (P =.001). Conventional dichotomous methods for estimating pCA after nondiagnostic bronchoscopies underestimate the likelihood of malignancy. Physicians should opt for the multidisease test approach when interpreting bronchoscopy results. [ABSTRACT FROM AUTHOR]

Otosclerosis is a common cause of hearing loss, yet diagnosing it remains a challenge. Wideband Tympanometry Absorbance (WTA) has been proposed as a potential tool for improving diagnostic accuracy. The aim of study was to investigate the diagnostic value of WTA in diagnosing otosclerosis by comparing its results in patients with clinically diagnosed otosclerosis and a normal control group. This prospective study was conducted in Mashhad, Iran, from 2022 to 2023, involving 64 participants including otosclerosis and control. Inclusion criteria for the otosclerosis group included a clinical diagnosis of otosclerosis confirmed by audiometric tests and conventional tympanometry, and eligibility for surgical intervention. The control group consisted of individuals with normal clinical audiometric and tympanometric results. Both groups underwent conventional and WTA tympanometric assessments. The evaluation of WTA involved 64 participants, divided evenly between otosclerosis a normal ears group. Conventional tympanometry at 226 Hz showed significant differences in compliance between otosclerosis and normal ears (p = 0.02). In contrast, at 1000 Hz did not demonstrate significant differences in compliance (p = 0.2). Also, WTA did not demonstrate significant differences in compliance (p > 0.9). Measurements of gradient and resonance across both 226 and 1000Hz frequencies showed no statistically significant differences. The sensitivity and specificity of WTA, evaluated through compliance, were 72% and 40%, respectively, with an area under the curve of 0.50. The study illustrates that while conventional tympanometry is effective in distinguishing otosclerosis from normal tympanic conditions, WTA shows limited diagnostic efficacy. The moderate sensitivity and specificity of WTA suggest that it should not be relied upon as the sole diagnostic tool. [ABSTRACT FROM AUTHOR]

Background: Ancillary immunohistochemistry testing for p16 loss has been proposed as a diagnostic tool for melanoma, but its accuracy remains uncertain. Methods: A systematic review and meta‐analysis were conducted on 26 studies involving 979 melanomas and 974 nevi. Results: Through bivariate analysis of data across all cut‐off values, the sensitivity and specificity were calculated to be 0.55 (95% confidence interval [CI]: 0.38, 0.70) and 0.85 (95% CI: 0.70, 0.94), respectively. Summary estimates of diagnostic accuracy fell below recommended thresholds for effective tests, but subgroup analysis suggested that p16 loss could aid in diagnosing ambiguous lesions as melanoma in certain scenarios. However, the presence of p16 expression in these contexts does not definitively rule out melanoma. The findings were limited by underpowered exploratory study designs at risk for bias in patient selection and test interpretation. Conclusions: While the use of p16 immunohistochemistry for detecting melanoma is not universally reliable, it may serve as a confirmatory test in differential diagnoses involving common, congenital, acral, Spitz, and deep penetrating nevi. Nevertheless, further studies are needed to validate its utility. Until then, the application of p16 immunohistochemistry in melanoma diagnosis should be regarded as experimental. [ABSTRACT FROM AUTHOR]

Key summary points: Aim: To compare the performance of different case-finding tools (SARC-F, SARC-CalF, calf circumference (CC), and BMI-adjusted CC) for sarcopenia in community-dwelling older adults. Findings: CC was the best tool for sarcopenia case-finding. The best performance was found for CC cut-off point of ≤ 34 cm in women and ≤ 36 cm in men. Message: In clinical practice, measurement of CC is a simple, inexpensive, and reliable tool to identify individuals at risk for sarcopenia for further assessment. Purpose: We compared the performance of SARC-F, SARC-CalF, calf circumference (CC), and body mass index (BMI)-adjusted CC for sarcopenia case-finding in community-dwelling older adults. Methods: Data of Finnish participants (women/men n = 192/36, mean age (SD) of 76.9 (4.8) years) recruited in the SPRINTT trial (NCT02582138) were used. Sarcopenia was determined as a combination of low muscle function (chair-stand-test) and low appendicular lean mass (ALM) detected by whole-body dual-energy X-ray absorptiometry. Associations of case-finding tools with sarcopenia were analysed using ROC curves and logistic regression. Results: The rates of probable and confirmed sarcopenia were 95% and 18% in women and 94% and 36% in men, respectively. Performance of CC for sarcopenia (women AUC 0.85 [95% CI 0.78–0.92]/ men 0.85 [95% CI 0.71–1.0]) was superior to that of other tools; (AUC in women/men for SARC-F was 0.57/0.50, for SARC-CalF 0.76/0.79, and for BMI-adjusted CC 0.68/0.66). The best performance was found for a CC cut-off point of ≤ 34 cm in women with sensitivity/specificity 82.4/75.3% and ≤ 36 cm in men with sensitivity/specificity 76.9/87.0%. For each cm decrease in CC, adjusted for age and BMI, there was a 30% increase in the odds of sarcopenia in women (OR 1.30, 95% CI 1.09─1.56). Although there was a similar pattern in men, the results did not reach statistical significance (OR 1.34, 95% CI 0.84- 2.14). Conclusions: CC was superior to other tools for sarcopenia case-finding. The best performance was found for a CC cut-off point of ≤ 34 cm in women and ≤ 36 cm in men. [ABSTRACT FROM AUTHOR]

An alarming increase in hypertension is a hazard to global health that poses severe implications for the body’s vital organs. To prevent serious repercussions, hypertension should be monitored continuously for early detection. It is well known that physiological signals, such as the photoplethysmogram (PPG) and electrocardiogram (ECG), carry essential information about the vitals of the human body. Considering this, numerous machine learning-based models based on ECG-PPG have been proposed for monitoring hypertension; however, such models are “non-explainable” and lack clinical interpretation. This work proposes a formal method-based runtime verification approach for hypertension monitoring using ECG and PPG sensing, which is explainable. The pulse arrival time (PAT) feature extracted using both signals is employed to implement a decision tree to infer hypertension patterns/policies defined in PAT, based on which a runtime monitor is synthesized to classify hypertension. Using the MIMIC II dataset, the proposed scheme’s performance is assessed, and the accuracy, sensitivity, and specificity are determined to be 95.7%, 93.9%, and 97.6%, respectively. [ABSTRACT FROM AUTHOR]

Background: Multiple differentials exist for pediatric liver tumors under 2 years. Accurate imaging diagnosis may obviate the need for tissue sampling in most cases. Objective: To evaluate the imaging features and diagnostic accuracy of computed tomography (CT) in liver tumors in children under 2 years. Methods: Eighty-eight children under 2 years with treatment naive liver neoplasms and baseline contrast-enhanced CT were included in this institutional review board approved retrospective study. Two blinded onco-radiologists assessed these tumors in consensus. Findings assessed included enhancement pattern, lobulated appearance, cystic change, calcifications, central scar-like appearance, and metastases. The radiologists classified the lesion as hepatoblastoma, infantile hemangioma, mesenchymal hamartoma, rhabdoid tumor, or indeterminate, first based purely on imaging and then after alpha-fetoprotein (AFP) correlation. Multivariate analysis and methods of comparing means and frequencies were used for statistical analysis wherever applicable. Diagnostic accuracy, sensitivity, and positive predictive values were analyzed. Results: The mean age of the sample was 11.4 months (95% CI, 10.9–11.8) with 50/88 (57%) boys. The study included 72 hepatoblastomas, 6 hemangiomas, 4 mesenchymal hamartomas, and 6 rhabdoid tumors. Presence of calcifications, multilobular pattern of arterial enhancement, lobulated morphology, and central scar-like appearance was significantly associated with hepatoblastomas (P-value < 0.05). Fourteen out of eighty-eight lesions were called indeterminate based on imaging alone; six lesions remained indeterminate after AFP correlation. Pure radiology-based diagnostic accuracy was 81.8% (95% CI, 72.2–89.2%), which increased to 92.1% (95% CI, 84.3–96.7%) (P-value > 0.05) after AFP correlation, with one hepatoblastoma misdiagnosed as a rhabdoid tumor. If indeterminate lesions were excluded for biopsy, the accuracy would be 98.8% (95% CI, 93.4–99.9%). Conclusion: CT had high accuracy for diagnosing liver neoplasms in the under 2-year age population after AFP correlation. Certain imaging features were significantly associated with the diagnosis of hepatoblastoma. A policy of biopsying only indeterminate lesions after CT and AFP correlation would avoid sampling in the majority of patients. [ABSTRACT FROM AUTHOR]

Background/Aim. Serum tumor markers (TMs) are commonly combined with imaging examinations to differentiate benign and malignant breast nodules (BNs), but there are still limitations. The aim of the study was to determine the value of real-time tissue elastography (RTE) diffusion quantitative analysis combined with serum TMs for the differential diagnosis of benign and malignant BNs. Methods. A total of 149 patients with BNs were included in this study. They were assigned to the benign BN group (n = 87) and malignant BN group (n = 62). All patients were examined using RTE diffusion quantitative analysis. Venous blood was collected to detect the levels of TMs carcinoembryonic antigen-CAE, cancer antigen (CA) 153, and CA 199. The value of RTE diffusion quantitative analysis parameters, TMs, and their combination for the differentiation of benign and malignant BNs was analyzed using the receiver operating characteristic-ROC curve. Results. Among all the above indicators, the area ratio of the blue region (AREA%) had the highest differential value, with an area under the curve (AUC) of 0.916 [95% confidence interval (CI): 0.812-0.967], while sensitivity and specificity were 88.90% and 86.79%, respectively (p < 0.05). Compared to RTE diffusion quantitative analysis parameters or TMs alone, the combination of the two showed the highest value for the differentiation of benign and malignant BNs, with an AUC of 0.957 (95% CI: 0.834-0.982), while sensitivity and specificity were 95.50% and 94.33%, respectively (p < 0.05). Conclusion. RTE diffusion quantitative analysis combined with TMs has a high value for the differentiation of benign and malignant BNs. [ABSTRACT FROM AUTHOR]

Background: Identifying language disorders earlier can help children receive the support needed to improve developmental outcomes and quality of life. Despite the prevalence and impacts of persistent language disorder, there are surprisingly no robust predictor tools available. This makes it difficult for researchers to recruit young children into early intervention trials, which in turn impedes advances in providing effective early interventions to children who need it. Aims: To validate externally a predictor set of six variables previously identified to be predictive of language at 11 years of age, using data from the Longitudinal Study of Australian Children (LSAC) birth cohort. Also, to examine whether additional LSAC variables arose as predictive of language outcome. Methods & Procedures: A total of 5107 children were recruited to LSAC with developmental measures collected from 0 to 3 years. At 11–12 years, children completed the Clinical Evaluation of Language Fundamentals, 4th Edition, Recalling Sentences subtest. We used SuperLearner to estimate the accuracy of six previously identified parent‐reported variables from ages 2–3 years in predicting low language (sentence recall score ≥ 1.5 SD below the mean) at 11–12 years. Random forests were used to identify any additional variables predictive of language outcome. Outcomes & Results: Complete data were available for 523 participants (52.20% girls), 27 (5.16%) of whom had a low language score. The six predictors yielded fair accuracy: 78% sensitivity (95% confidence interval (CI) = [58, 91]) and 71% specificity (95% CI = [67, 75]). These predictors relate to sentence complexity, vocabulary and behaviour. The random forests analysis identified similar predictors. Conclusions & Implications: We identified an ultra‐short set of variables that predicts 11–12‐year language outcome with 'fair' accuracy. In one of few replication studies of this scale in the field, these methods have now been conducted across two population‐based cohorts, with consistent results. An imminent practical implication of these findings is using these predictors to aid recruitment into early language intervention studies. Future research can continue to refine the accuracy of early predictors to work towards earlier identification in a clinical context. WHAT THIS PAPER ADDS: What is already known on the subject: There are no robust predictor sets of child language disorder despite its prevalence and far‐reaching impacts. A previous study identified six variables collected at age 2–3 years that predicted 11–12‐year language with 75% sensitivity and 81% specificity, which warranted replication in a separate cohort. What this study adds to the existing knowledge: We used machine learning methods to identify a set of six questions asked at age 2–3 years with ≥ 71% sensitivity and specificity for predicting low language outcome at 11–12 years, now showing consistent results across two large‐scale population‐based cohort studies. What are the potential or clinical implications of this work?: This predictor set is more accurate than existing feasible methods and can be translated into a low‐resource and time‐efficient recruitment tool for early language intervention studies, leading to improved clinical service provision for young children likely to have persisting language difficulties. [ABSTRACT FROM AUTHOR]

Introduction: Objective of this study was to assess the diagnostic efficacy of the most commonly used radiological evaluation in form of contrast enhanced computed tomography of abdomen with adrenal protocol, basic functional evaluation and surgical outcomes of primary adrenal masses. Material and methods: We have retrospectively analysed the institutional records of 108, patients admitted from August 2017 to September 2023, who had underwent surgical intervention for their adrenal mass after thorough evaluation and stabilization. Results: Flank pain was the most common symptoms in 44 (40.74%) patients. Non-functional adrenal adenoma was found in 36 (33.33%) patients. Pheochromocytoma was the most the common functional adrenal mass found in 24 (22.22%) patients. CECT abdomen had suggested features of malignancy in 16(14.81%) patients. In final histopathological report 26(24.07%) patients had pheochromocytoma and 12 (11.11%) patients had adrenocortical carcinoma. CECT abdomen had sensitivity of 75%, specificity of 95.6%. Plasma free metanephrines and normetanephrine analysis had shown sensitivity of 90%, specificity of 92.86%, aldosterone to renin ratio had sensitivity of 92%, specificity of 100%. Sensitivity and specificity of the low-dose dexamethasone suppression test and plasma dehydroepiandrosterone was 100% in our study. Eighty patients (74.07%) were operated with laparoscopic adrenalectomy, 20 (18.52%) patients with open adrenalectomy. Eight patients (7.41%) were converted from laparoscopic to open. Laparoscopic approach had significantly lesser mean operating time, lesser blood loss, lesser hospitalization and lesser post-operative complications. Conclusion: Radiological analysis and functional analysis has shown good sensitivity and high specificity. Laparoscopic approach has advantage of lesser operative time, lesser hospitalization and lesser post-operative complications. [ABSTRACT FROM AUTHOR]

Background and Purpose: The definitive diagnosis of gastroesophageal reflux disease (GERD) often requires invasive investigations like upper gastrointestinal endoscopy or reflux monitoring. We aimed to explore the relationship between salivary pepsin and GERD and its value as a non‐invasive diagnostic tool. Methods: Databases (PubMed, Web of Science, Cochran Library, and EMBASE) were searched from their inception to January 22, 2024 to explore the correlation of salivary pepsin with GERD. The meta‐analysis data retrieved were summarized, including the salivary pepsin concentration, sensitivity of diagnosis (SEN), specificity of diagnosis (SPE), negative likelihood ratio, positive likelihood ratio, diagnostic odds ratio, and receiver operating characteristic (ROC) curve. Results: The meta‐analysis comparing salivary pepsin concentration in two groups (proven GERD and non‐GERD) with 18 studies revealed that the proven GERD group had higher salivary pepsin concentration than the non‐GERD group (SMD = 1.74 [95% CI 1.14–2.34]). The meta‐analysis of salivary pepsin diagnostic value for proven GERD incorporated 23 studies. The results showed pooled SEN (0.73 [95% CI 0.66–0.80]), SPE (0.72 [95% CI 0.65–0.78]), positive likelihood ratio (2.61 [95% CI 2.02–3.39]), negative likelihood ratio (0.37 [95% CI 0.28–0.50]), diagnostic odds ratio (7.03 [95% CI 4.24–11.66]) and area under the SROC curve (0.79 [95% CI 0.75–0.82]). Conclusion: GERD patients presented a higher salivary pepsin concentration. Salivary pepsin is both sensitive and specific in identifying GERD, making it a promising non‐invasive marker for diagnosis. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to determine and compare the capability of several B-mode ultrasound (US) and shear wave elastography (SWE) metrics to differentiate subjects with chronic non-specific neck pain from asymptomatic subjects. Methods: A diagnostic accuracy study recruiting a sample of patients with chronic neck pain and asymptomatic controls was conducted. Data collection included sociodemographic information (i.e., gender, age, height, weight and body mass index), clinical information (pain intensity assessed using the Visual Analogue Scale and pain-related disability using the Neck Disability Index) and B-mode ultrasound and shear wave elastography features of the cervical multifidus muscle (cross-sectional area, perimeter, mean echo intensity, fat infiltration, shear wave speed and Young's modulus). After analyzing between-group differences for left/right sides, cases and controls, and males and females, the area under the receiver operating characteristic (ROC) curve, the optimal cut-off point, the sensitivity, the specificity, the positive likelihood ratio (LR) and negative LR for each metric were calculated. A total of 316 individuals were recruited in this study (n = 174 cases with neck pain and n = 142 asymptomatic controls). Results: No significant differences (p > 0.05) were found between cases and controls for most variables, except for fatty infiltration, which was significantly higher in chronic neck pain cases (p < 0.001). Gender differences were significant across all US and SWE metrics (all, p < 0.001 except p = 0.015 for fatty infiltrates). A slight asymmetry was observed between the left and right sides for area (p = 0.038). No significant interactions between group, gender and side (all metrics, p > 0.008) were identified. Fatty infiltration was the most effective discriminator, with a ROC value of 0.723, indicating acceptable discrimination. The optimal cut-off point for fatty infiltration was 25.77, with a moderate balance between sensitivity (59.8%) and specificity (20.5%). However, its positive likelihood ratio (LR) of 0.75 suggests limited usefulness in confirming the condition. Conclusions: Fatty infiltration was significantly higher in individuals with chronic idiopathic neck pain compared to those without symptoms, while other muscle metrics were similar between both groups. However, since fat infiltration had moderate diagnostic accuracy and the other metrics showed poor discriminatory power, US cannot be used solely to discriminate patients with idiopathic neck pain. [ABSTRACT FROM AUTHOR]

Objective: Diagnosis of spondylodiscitis is usually possible radiographically with magnetic resonance imaging (MRI). However, the first imaging method evaluated in daily practice is conventional radiography. The aim of the study was to determine the sensitivity and specificity of detecting infectious or rheumatological spondylodiscitis in the lumbar region with conventional radiography by rheumatologists. Methods: Among 102 patients with spondylodiscitis on lumbosacral (LS) MRI, 23 patients who also underwent simultaneous conventional LS radiography were included. TThe control group consisted of 52 outpatients with no evidence of spondylodiscitis on LS MRI. Eleven rheumatologists blindly evaluated conventional LS radiographs. Sensitivity, specificity, positive, and negative predictive values of LS conventional radiography were calculated. Results: While the cause was infection in 8/23 (34.7%) of spondylodiscitis patients, it was spondyloarthritis in 15/23 (65.2%). According to LS MRI findings, 23 patients had spondylodiscitis in a total of 31 vertebral units. When we evaluated the detection of spondylodiscitis according to the vertebral unit level, it was mostly at one level [14 (60.8%)], primarily at the L4-5 vertebral unit [13 (56.5%)]. The sensitivity of detecting LS spondylodiscitis on conventional radiography was found to be 52% (30-65), and the specificity was 86% (59-94). While the median (minimum-maximum) sensitivity was 75.0 (50.0-87.5) in patients with infectious spondylodiscitis, it was 46.6 (13.3-76.9) in patients with spondylodiscitis due to spondyloarthritis. Conclusion: Clinicians can miss spondylodiscitis. Although it is evaluated with conventional radiography in the first stage in the presence of appropriate clinical findings, the clinician should be careful and consider more advanced approaches.

Objective(s): Although the psychometric properties of the Persian version of the short form of the Female Sexual Function Scale (FSFI-6) was studied, the sensitivity and specificity of the Persian version of this instrument have not been investigated. The present study aimed to assess the sensitivity, specificity and clinical cut-off point of the FSFI-6 in Iranian women. Methods:This descriptive cross-sectional study was conducted on 165 women with and 131 women without sexual dysfunction. In addition to a demographic questionnaire, the Female Sexual Function Index (FSFI-19) questionnaire was administered. Using the Receiver-Operating Characteristic curve (ROC) analysis and indicating cut-off point, sensitivity and specificity were determined Results: Based on the short form of the original instrument, which included questions 4, 2, 7, 11, 16, and 17 from the longer version, the cut-off point for the FSFI-6 was 18.5 and the sensitivity and specificity were 61% and 52%, respectively. Considering that the calculated sensitivity and specificity of the index was relatively low and had a significant difference compared to the reported sensitivity and specificity for this instrument in the literature. Therefore, questions 5, 8, 12, and 18 were replaced with questions 4, 7, 11, and 17 and the analysis was repeated. Based on the replaced questions, the cut-off point was 20.5 and the sensitivity and specificity of the tool was 90%. Conclusion: The findings suggest that the Persian version of FSFI-6 with questions 2, 5, 8, 12, 16, and 18 has a better performance for diagnosing sexual dysfunction in Iranian women.

Objective To investigate the value of real-time tissue elastography (RTE) in evaluating donor liver quality and postoperative early allograft dysfunction (EAD) in liver transplantation patients. Methods A total of 58 patients who received liver transplantation in Organ Transplantation Center of our hospital from October 2020 to January 2022 were enrolled, and according to the recovery of liver function in the early stage after surgery, the patients were divided into EAD group and non-EAD group. The two groups were compared in terms of the indicators such as the routine ultrasound examination and RTE measurement of donor liver before liver transplantation, liver function and coagulation function of recipients before and after liver transplantation, and preoperative Model for End-Stage Liver Disease (MELD) score. The logistic regression analysis was performed for the indicators with significant differences, and the receiver operating characteristic (ROC) curve was plotted to calculate the area under the ROC curve (AUC) and assess the performance of related factors. Results Compared with the non-EAD group, the EAD group had significantly higher liver fibrosis (LF) index of donor liver and MELD score of recipients (t=4.822, 2.902,P1.645 was a risk factor for EAD after liver transplantation, and the ROC curve analysis showed that donor liver LF index had an AUC of 0.840 in predicting EAD after surgery, with a sensitivity of 82.4%, a specificity of 73.2%, and a cut-off value of 1.645. Conclusion High LF index of donor liver before liver transplantation is a risk factor for EAD in recipients after liver transplantation, and RTE measurement for LF index of donor liver before li-ver transplantation has a certain value in assessing the quality of donor liver and predicting the onset of EAD.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is the most severe form of tuberculosis. Inadequate diagnostic testing and treatment regimens adapted from pulmonary tuberculosis without consideration of the unique nature of TBM are among the potential drivers. This review focuses on the progress being made in relation to both diagnosis and treatment of TBM, emphasizing promising future directions. RECENT FINDINGS: The molecular assay GeneXpert MTB/Rif Ultra has improved sensitivity but has inadequate negative predictive value to rule-out TBM. Evaluations of tests focused on the host response and bacterial components are ongoing. Clinical trials are in progress to explore the roles of rifampin, fluoroquinolones, linezolid, and adjunctive aspirin. Though diagnosis has improved, novel modalities are being explored to improve the rapid diagnosis of TBM. Multiple ongoing clinical trials may change current therapies for TBM in the near future.

Bacterial commensals of the human genitourinary tract, Mycoplasma hominis and Ureaplasma species (parvum and urealyticum) can be sexually transmitted, and may cause nongonococcal urethritis, pelvic inflammatory disease, and infertility. Mycoplasma hominis and Ureaplasma species may also cause severe invasive infections in immunocompromised patients. Current culture-based methods for Mycoplasma/Ureaplasma identification are costly and laborious, with a turnaround time between 1 and 2 weeks. We developed a high-throughput, real-time multiplex PCR assay for the rapid detection of M. hominis and Ureaplasma species in urine, genital swab, body fluid, and tissue. In total, 282 specimens were tested by PCR and compared with historic culture results; a molecular reference method was used to moderate discrepancies. Overall result agreement was 99% for M. hominis (97% positive percentage agreement and 100% negative percentage agreement) and 96% for Ureaplasma species (96% positive percentage agreement and 97% negative percentage agreement). Specimen stability was validated for up to 7 days at room temperature. This multiplex molecular assay was designed for implementation in a high-complexity clinical microbiology laboratory. With this method, >90 samples can be tested in one run, with a turnaround time of 4 to 5 hours from specimen extraction to reporting of results. This PCR test is also more labor effective and cheaper than the conventional culture-based test, thus improving laboratory efficiency and alleviating labor shortages.

GeneXpert MTB/RIF, a tool widely used for diagnosing tuberculosis, has limitations for detecting rifampin resistance in certain variants. We report transmission of a pre-extensively drug-resistant variant in Botswana that went undetected by GeneXpert. The public health impact of misdiagnosis emphasizes the need for comprehensive molecular testing to identify resistance and guide treatment.

BACKGROUND: Although susceptibility-weighted imaging (SWI) is the gold standard for visualizing cerebral microbleeds (CMBs) in the brain, the required phase data are not always available clinically. Having a postprocessing tool for generating SWI contrast from T2*-weighted magnitude images is therefore advantageous. PURPOSE: To create synthetic SWI images from clinical T2*-weighted magnitude images using deep learning and evaluate the resulting images in terms of similarity to conventional SWI images and ability to detect radiation-associated CMBs. STUDY TYPE: Retrospective. POPULATION: A total of 145 adults (87 males/58 females; 43.9 years old) with radiation-associated CMBs were used to train (16,093 patches/121 patients), validate (484 patches/4 patients), and test (2420 patches/20 patients) our networks. FIELD STRENGTH/SEQUENCE: 3D T2*-weighted, gradient-echo acquired at 3 T. ASSESSMENT: Structural similarity index (SSIM), peak signal-to-noise-ratio (PSNR), normalized mean-squared-error (nMSE), CMB counts, and line profiles were compared among magnitude, original SWI, and synthetic SWI images. Three blinded raters (J.E.V.M., M.A.M., B.B. with 8-, 6-, and 4-years of experience, respectively) independently rated and classified test-set images. STATISTICAL TESTS: Kruskall-Wallis and Wilcoxon signed-rank tests were used to compare SSIM, PSNR, nMSE, and CMB counts among magnitude, original SWI, and predicted synthetic SWI images. Intraclass correlation assessed interrater variability. P values

Objectives: [18F]Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is a non-invasive imaging modality used in the differential diagnosis of splenic lesions, although ideal parameters and thresholds remain unclear. The present study evaluated the ability of [18F]FDG PET/CT, including its visual and quantitative parameters, to differentiate between benign and malignant splenic lesions. Methods: Patients who underwent [18F]FDG PET/CT following the detection of splenic lesions on contrast-enhanced CT were retrospectively analysed. Visual parameters assessed on [18F]FDG PET/CT included whole spleen uptake intensity, lesion multiplicity, and lesion uptake, and quantitative parameters included maximum standardised uptake value (SUVmax), lesion-to-background ratio (LBR), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and lesion size. Parameters differentiating between benign and malignant lesions were evaluated by Pearson's chi-square test, Mann–Whitney U-test, and receiver operating characteristics (ROC) curve analysis. Results: Splenic lesion uptake (p = 0.001) was the only visual parameter significantly distinguishing between benign and malignant lesions. ROC curve analysis demonstrated that SUVmax had the largest area under the ROC, 0.91 (p < 0.001), with an optimal cut-off > 5.3 having a sensitivity of 90.3% and a specificity of 80.6%. Subgroup analysis of malignant lesions showed that SUVmax (p = 0.013), LBR (p = 0.012), and TLG (p = 0.034) were significantly higher in splenic lymphomas than in splenic metastases. Conclusion: Of the [18F]FDG PET/CT parameters investigated, SUVmax had the highest accuracy in diagnosing malignant splenic lesions and was significantly higher in splenic lymphomas than in splenic metastases. Visual determination of [18F]FDG uptake by splenic lesions may be an easily evaluated parameter. Clinical relevance statement: SUVmax and visual grade of [18F]FDG PET/CT help to differentiate spleen lesions. [18F]FDG PET/CT is useful for discriminating between benign and malignant spleen lesions. Key Points: Many splenic lesions are difficult to diagnose on anatomical imaging, with histopathologic analyses are required. SUVmax of PET/CT provided the diagnostic ability to differentiate between benign and malignant splenic lesions. More than normal spleen uptake can be a convenient parameter to diagnose malignant spleen lesions. [ABSTRACT FROM AUTHOR]

Abstract Background Although clinical guidelines exist for diagnosing abnormal uterine bleeding, there is a significant lack of agreement on the best management strategies for women presenting with symptom, particularly in diagnosing endometrial cancer. This study aimed to develop a preoperative risk model that utilizes demographic factors and transvaginal ultrasonography of the endometrium to assess and predict the risk of malignancy in females with endometrial cancer. Methods In this retrospective study, a logistic regression model was developed to predict endometrial carcinoma using data from 356 postmenopausal women with endometrial lesions and an endometrial thickness (ET) of 5 mm or more. These patients had undergone transvaginal ultrasonography prior to surgery, with findings including 247 benign and 109 malignant cases. The model’s predictive performance was evaluated using receiver operating characteristic (ROC) curve analysis and compared with post-surgical pathological diagnoses. Results Our model incorporates several predictors for endometrial carcinoma, including age, history of hypertension, history of diabetes, body mass index (BMI), duration of vaginal bleeding, endometrial thickness, completeness of the endometrial line, and endometrial vascularization. It demonstrated a strong prediction with an area under the curve (AUC) of 0.905 (95% CI, 0.865–0.945). At the optimal risk threshold of 0.33, the model achieved a sensitivity of 82.18% and a specificity of 92.80%. Conclusions The established model, which integrates ultrasound evaluations with demographic data, provides a specific and sensitive method for assessing and predicting endometrial carcinoma.

Abstract Sample size, namely the number of subjects that should be included in a study to reach the desired endpoint and statistical power, is a fundamental concept of scientific research. Indeed, sample size must be planned a priori, and tailored to the main endpoint of the study, to avoid including too many subjects, thus possibly exposing them to additional risks while also wasting time and resources, or too few subjects, failing to reach the desired purpose. We offer a simple, go-to review of methods for sample size calculation for studies concerning data reliability (repeatability/reproducibility) and diagnostic performance. For studies concerning data reliability, we considered Cohen’s κ or intraclass correlation coefficient (ICC) for hypothesis testing, estimation of Cohen’s κ or ICC, and Bland-Altman analyses. With regards to diagnostic performance, we considered accuracy or sensitivity/specificity versus reference standards, the comparison of diagnostic performances, and the comparisons of areas under the receiver operating characteristics curve. Finally, we considered the special cases of dropouts or retrospective case exclusions, multiple endpoints, lack of prior data estimates, and the selection of unusual thresholds for α and β errors. For the most frequent cases, we provide example of software freely available on the Internet. Relevance statement Sample size calculation is a fundamental factor influencing the quality of studies on repeatability/reproducibility and diagnostic performance in radiology. Key points • Sample size is a concept related to precision and statistical power. • It has ethical implications, especially when patients are exposed to risks. • Sample size should always be calculated before starting a study. • This review offers simple, go-to methods for sample size calculations. Graphical Abstract