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BACKGROUND: Despite improved awareness of blunt traumatic hollow viscus and mesenteric injuries (THVMI), the accuracy of contrast-enhanced CT (CECT) varies considerably among studies. This systematic review and meta-analysis of test accuracy aims to explore the diagnostic performance of CECT in detecting THVMI in blunt trauma. METHODS: The study was conducted according to the Cochrane recommendations searching the PubMed, Scopus, and Cochrane Library datasets from 2000 to 8 September 2023 (PROSPERO ID: CRD42023473041). Surgical exploration, autopsy, and discharge from the hospital after monitoring were set as reference standard. To explore the diagnostic accuracy of CECT in detecting THVMI hierarchical models were developed. The risk of bias in individual studies was assessed with the QUADAS-2 tool. Sensitivity analysis was conducted to detect sources of heterogeneity. RESULTS: Twelve studies, for a total of 4537 patients, were deemed eligible. After identification of outliers and sensitivity analysis, the pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were 0.85 (95% CI: 0.69-0.93), 0.94 (95% CI: 0.8-0.98), 14.65 (95% CI: 4.22-50.85), 0.16 (95% CI: 0.07-0.34), 92.3 (95% CI: 29.75-286.34), respectively. The Area under the HSROC curve was 0.95 (95% CI: 0.92-0.96). Meta-regression analysis identified the year of publication as a covariate significantly associated with heterogeneity. A high risk of bias was detected in the "patient selection" domains. CONCLUSION: CECT has a fundamental role in identifying THVMI with high specificity but suboptimal sensitivity. Clinical criteria are still of paramount importance, especially in cases of ambiguous initial CECT images.

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While HC2 and GP5+/6+ PCR-EIA were pivotal in test validation of new HPV assays, they represent the first generation of comparator tests based upon technologies that are not in widespread use anymore. In the current guideline, criteria for second-generation comparator tests are presented that include more detailed resolution of HPV genotypes. Second-generation comparator tests should preferentially target only the 12 genotypes classified as carcinogenic (IARC-group I), and show consistent non-inferior sensitivity for CIN2+ and CIN3+ and specificity for ≤CIN1 compared to one of the first-generations comparators, in at least three validation studies using benchmarks of 0.95 for relative sensitivity and 0.98 for relative specificity. Validation should take into account used storage media and other sample handling procedures. Meta-analyses were conducted to identify the assays that fulfill these stringent criteria. Four tests fulfilled the new criteria: (1) RealTime High-Risk HPV Test (Abbott), (2) Cobas-4800 HPV test (Roche Molecular System), (3) Onclarity HPV Assay (BD Diagnostics), and (4) Anyplex II HPV HR Detection (Seegene), each evaluated in three to six studies. Whereas the four assays target 14 carcinogenic genotypes, the first two identify separately HPV16 and 18, the third assay identifies five types separately and the fourth identifies all the types separately.

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Brain cancer is a substantial factor in the mortality associated with cancer, presenting difficulties in the timely identification of the disease. The precision of diagnoses is significantly dependent on the proficiency of radiologists and neurologists. Although there is potential for early detection with computer-aided diagnosis (CAD) algorithms, the majority of current research is hindered by its modest sample sizes. This meta-analysis aims to comprehensively assess the diagnostic test accuracy (DTA) of computer-aided design (CAD) models specifically designed for the detection of brain cancer utilizing hyperspectral (HSI) technology. We employ Quadas-2 criteria to choose seven papers and classify the proposed methodologies according to the artificial intelligence method, cancer type, and publication year. In order to evaluate heterogeneity and diagnostic performance, we utilize Deeks' funnel plot, the forest plot, and accuracy charts. The results of our research suggest that there is no notable variation among the investigations. The CAD techniques that have been examined exhibit a notable level of precision in the automated detection of brain cancer. However, the absence of external validation hinders their potential implementation in real-time clinical settings. This highlights the necessity for additional studies in order to authenticate the CAD models for wider clinical applicability.

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Background: Strain and shear wave elastography which is commonly used with concurrent real-time imaging known as real-time ultrasound shear/strain wave elastography is a new diagnostic technique that has been reported to be useful in the diagnosis of nodules in several organs. There is conflicting evidence regarding its benefit over ultrasound-guided fine-needle aspiration cytology alone in thyroid nodules. Objectives: To determine if ultrasound strain and shear wave elastography in conjunction with fine-needle aspiration cytology will reduce the number of patients who have a non-diagnostic first fine-needle aspiration cytology results as compared to conventional ultrasound-only guided fine-needle aspiration cytology. Design: A pragmatic, unblinded, multicentre randomised controlled trial. Setting: Eighteen centres with a radiology department across England. Participants: Adults who had not undergone previous fine-needle aspiration cytology with single or multiple nodules undergoing investigation. Interventions: Ultrasound shear/strain wave elastography-ultrasound guided fine-needle aspiration cytology (intervention arm) - strain or shear wave elastography-guided fine-needle aspiration cytology. Ultrasound-only guided fine-needle aspiration cytology (control arm) - routine ultrasound-only guided fine-needle aspiration cytology (the current standard recommended by the British Thyroid Association guidelines). Main outcome measure: The proportion of patients who have a non-diagnostic cytology (Thy 1) result following the first fine-needle aspiration cytology. Randomisation: Patients were randomised at a 1 : 1 ratio to the interventional or control arms. Results: A total of 982 participants (80% female) were randomised: 493 were randomised to ultrasound shear/strain wave elastography-ultrasound guided fine-needle aspiration cytology and 489 were randomised to ultrasound-only guided fine-needle aspiration cytology. There was no evidence of a difference between ultrasound shear/strain wave elastography and ultrasound in non-diagnostic cytology (Thy 1) rate following the first fine-needle aspiration cytology (19% vs. 16% respectively; risk difference: 0.030; 95% confidence interval -0.007 to 0.066; p = 0.11), the number of fine-needle aspiration cytologies needed (odds ratio: 1.10; 95% confidence interval 0.82 to 1.49; p = 0.53) or in the time to reach a definitive diagnosis (hazard ratio: 0.94; 95% confidence interval 0.81 to 1.10; p = 0.45). There was a small, non-significant reduction in the number of thyroid operations undertaken when ultrasound shear/strain wave elastography was used (37% vs. 40% respectively; risk difference: -0.02; 95% confidence interval -0.06 to 0.009; p = 0.15), but no difference in the number of operations yielding benign histology - 23% versus 24% respectively, p = 0.70 (i.e. no increase in identification of malignant cases) - or in the number of serious adverse events (2% vs. 1%). There was no difference in anxiety and depression, pain or quality of life between the two arms. Limitations: The study was not powered to detect differences in malignancy. Conclusions: Ultrasound shear/strain wave elastography does not appear to have additional benefit over ultrasound-guided fine-needle aspiration cytology in the diagnosis of thyroid nodules. Future work: The findings of the ElaTION trial suggest that further research into the use of shear wave elastography in the diagnostic setting of thyroid nodules is unlikely to be warranted unless there are improvements in the technology. The diagnostic difficulty in distinguishing between benign and malignant lesions still persists. Future studies might examine the role of genomic testing on fine-needle aspiration samples. There is growing use of targeted panels of molecular markers, particularly aimed at improving the diagnostic accuracy of indeterminate (i.e. Thy3) cytology results. The application of these tests is not uniform, and their cost effectiveness has not been assessed in large-scale trials. Study registration: This study is registered as ISRCTN (ISRCTN18261857). Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 12/19/04) and is published in full in Health Technology Assessment; Vol. 28, No. 46. See the NIHR Funding and Awards website for further award information.

About half the population will have lumps in their thyroid if examined by an ultrasound scan but may not know they have one. About one in twenty people will feel a thyroid lump in their neck at some time in their life, with about one in twenty of those being malignant. Currently, the recommended way of getting a diagnosis of thyroid nodules is by using ultrasound to guide a needle to get cells from the lump, called ultrasound-guided fine-needle aspiration cytology. These cells are examined to determine the cause of the lump. If there are enough cells, Doctors can then make a diagnosis of whether the lump is benign or malignant. If not, patients will undergo another ultrasound-guided fine-needle aspiration cytology. One in five ultrasound-guided fine-needle aspiration cytologies are non-diagnostic with an overall false-positive rate of approximately 24%. This means one in five patients, with benign disease, may undergo unnecessary diagnostic operations. Thyroid surgery carries risks of complications, which could be avoided if we had better ways to diagnose which patients actually need an operation. We conducted a randomised trial, ElaTION, to determine if a new technology called strain and shear wave elastography, commonly known as real-time elastography, would be better at helping the radiologist take a sufficient sample of cells and reduce the number of non-diagnostic results, reducing the number of fine-needle aspiration cytologies required to make a definitive diagnosis. Nine hundred eighty-two patients were recruited between 2015 and 2018 and followed up until the end of the trial. Patients were randomised into two groups: 489 patients received the standard ultrasound-guided fine-needle aspiration cytology alone, and 493 patients received ultrasound-guided fine-needle aspiration cytology + shear wave elastography. Ultrasound shear/strain wave elastography did not reduce non-diagnostic cytology at first fine-needle aspiration cytology or improve the likelihood of determining whether the lump is benign or malignant. The results of ElaTION do not support the use of shear wave elastography-fine-needle aspiration cytology in the diagnosis of thyroid nodules.

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The summary receiver operating characteristic (SROC) curve has been recommended as one important meta-analytical summary to represent the accuracy of a diagnostic test in the presence of heterogeneous cutoff values. However, selective publication of diagnostic studies for meta-analysis can induce publication bias (PB) on the estimate of the SROC curve. Several sensitivity analysis methods have been developed to quantify PB on the SROC curve, and all these methods utilize parametric selection functions to model the selective publication mechanism. The main contribution of this article is to propose a new sensitivity analysis approach that derives the worst-case bounds for the SROC curve by adopting nonparametric selection functions under minimal assumptions. The estimation procedures of the worst-case bounds use the Monte Carlo method to approximate the bias on the SROC curves along with the corresponding area under the curves, and then the maximum and minimum values of PB under a range of marginal selection probabilities are optimized by nonlinear programming. We apply the proposed method to real-world meta-analyses to show that the worst-case bounds of the SROC curves can provide useful insights for discussing the robustness of meta-analytical findings on diagnostic test accuracy.

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The development of new statistical models for the meta-analysis of diagnostic test accuracy studies is still an ongoing field of research, especially with respect to summary receiver operating characteristic (ROC) curves. In the recently published updated version of the "Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy", the authors point to the challenges of this kind of meta-analysis and propose two approaches. However, both of them come with some disadvantages, such as the nonstraightforward choice of priors in Bayesian models or the requirement of a two-step approach where parameters are estimated for the individual studies, followed by summarizing the results. As an alternative, we propose a novel model by applying methods from time-to-event analysis. To this task we use the discrete proportional hazard approach to treat the different diagnostic thresholds, that provide means to estimate sensitivity and specificity and are reported by the single studies, as categorical variables in a generalized linear mixed model, using both the logit- and the asymmetric cloglog-link. This leads to a model specification with threshold-specific discrete hazards, avoiding a linear dependency between thresholds, discrete hazard, and sensitivity/specificity and thus increasing model flexibility. We compare the resulting models to approaches from the literature in a simulation study. While the estimated area under the summary ROC curve is estimated comparably well in most approaches, the results depict substantial differences in the estimated sensitivities and specificities. We also show the practical applicability of the models to data from a meta-analysis for the screening of type 2 diabetes.

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Aim: To assess the accuracy and technical characteristics of CYP2C19 point of care tests (POCTs).Patients & methods: Systematic review of primary studies, in any population or setting, that evaluated POCTs for detecting CYP2C19 loss of function (LOF) alleles.Results: Eleven studies provided accuracy data (eight Spartan; one Genomadix Cube; one GMEX; one Genedrive). The POCTs had very high sensitivity and specificity for the alleles they tested for. Twenty-two studies reported technical characteristics: POCTs were easy to operate and provided results quickly. Limited data were reported for test failure rate and cost.Conclusion: CYP2C19 POCTs may be a useful alternative to laboratory-based testing to guide antiplatelet therapy. Further data are required on accuracy (GMEX; Genedrive), test failure and cost (all POCT).

[Box: see text].

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PURPOSE: To evaluate the diagnostic value of ultrasound elastography (USE) for characterizing hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). METHODS: The protocol was pre-registered a priori at ( https://osf.io/namvk/ ). Using PubMed, Web of Science, Embase, and Cochrane Library, we found studies up to April 20, 2024 by searching HCC, ICC, and USE as keywords. Parameters of USE were directly compared between HCC and ICC patients using random-effects bivariate model on STATA 17.0, MedCalc 20.0, and Psychometrica. Trim & fill method and sensitivity analysis were also performed. RESULTS: Eighteen studies were included with 1057 patients, consisting of 863 HCC lesions, 188 ICC lesions, and 6 mixed lesions. The pooled Emean values of HCC and ICC were 28.3 (CI = 19.8 to 36.8) and 44.0 (CI = 20.9 to 67.2). HCC tumors were 34.3% softer than ICC while peritumoral tissue in HCC lesions was 75% stiffer than ICC lesions based on Emean. The strain value index (tumoral-to-peritumoral ratio) in HCC patients was 49.4% less than that of ICC patients. USE demonstrated a pool sensitivity of 87% (CI = 73-95%), specificity of 82% (CI = 65-92%), positive likelihood ratio of 4.8 (CI = 2.2 to 10.3), negative likelihood ratio of 0.16 (CI = 0.07 to 0.37), and diagnostic odds ratio of 31 (CI = 7 to 127) in differentiation of ICC from HCC. CONCLUSION: By evaluating tumoral and pre-tumoral stiffness, along with strain value index, USE may provide a valuable quantitative diagnostic tool for accurately differentiating HCC and ICC.

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OBJECTIVE: To perform a systematic review and meta-analysis of the diagnostic performance of contrast enhancement to differentiate benign and malignant renal lesions using CT and MRI. MATERIAL AND METHODS: A systematic literature search of databases was performed between January 1, 1980 and September 26, 2022. We included studies reporting the accuracy of CE thresholds on CT and MRI indeterminate renal lesions, with pathologic examination and follow-up as the reference standard. Studies meeting the inclusion criteria underwent quality assessment with the Cochrane recommendation for diagnostic accuracy study Quality Assessment 2. We excluded studies with high risk of bias. Summary estimates of diagnostic performance were obtained with the bivariate Bayesian model for CT and MRI. Effects of different thresholds and index test modalities were investigated through subgroup analysis. RESULTS: Eleven studies (1372 patients) using CT and six studies (218 patients) using MRI were included. Of the eleven studies, 15 parts from 9 studies were considered for the CT meta-analysis, and 6 parts from 3 studies for the MRI meta-analysis. Diagnostic performance meta-analysis on enhancement found a 96% summary sensitivity (95% CI 92, 98) and a 92% summary specificity (95% CI 85, 96) in 2056 renal lesions for CT; and 82% summary sensitivity (95% CI 65, 89) and an 89% summary specificity (95% CI 77, 95) in 634 lesions for MRI. CONCLUSION: CT and MRI have high accuracy to determine enhancement and classify renal lesions, and both modalities can be used with confidence for this purpose. There are still some controversies about the optimal thresholds. Future research should evaluate outcomes and decision-making pathways to determine whether basing clinical decisions on a specific threshold on CT and MRI would do more harm than good.

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Background/Objectives: The aim of this study was to assess the diagnostic accuracy of the AI-driven platform Diagnocat for evaluating endodontic treatment outcomes using cone beam computed tomography (CBCT) images. Methods: A total of 55 consecutive patients (15 males and 40 females, aged 12-70 years) referred for CBCT imaging were included. CBCT images were analyzed using Diagnocat's AI platform, which assessed parameters such as the probability of filling, adequate obturation, adequate density, overfilling, voids in filling, short filling, and root canal number. The images were also evaluated by two experienced human readers. Diagnostic accuracy metrics (accuracy, precision, recall, and F1 score) were assessed and compared to the readers' consensus, which served as the reference standard. Results: The AI platform demonstrated high diagnostic accuracy for most parameters, with perfect scores for the probability of filling (accuracy, precision, recall, F1 = 100%). Adequate obturation showed moderate performance (accuracy = 84.1%, precision = 66.7%, recall = 92.3%, and F1 = 77.4%). Adequate density (accuracy = 95.5%, precision, recall, and F1 = 97.2%), overfilling (accuracy = 95.5%, precision = 86.7%, recall = 100%, and F1 = 92.9%), and short fillings (accuracy = 95.5%, precision = 100%, recall = 86.7%, and F1 = 92.9%) also exhibited strong performance. The performance of AI for voids in filling detection (accuracy = 88.6%, precision = 88.9%, recall = 66.7%, and F1 = 76.2%) highlighted areas for improvement. Conclusions: The AI platform Diagnocat showed high diagnostic accuracy in evaluating endodontic treatment outcomes using CBCT images, indicating its potential as a valuable tool in dental radiology.

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Background: Most neovascular age-related macular degeneration treatments involve long-term follow-up of disease activity. Home monitoring would reduce the burden on patients and those they depend on for transport, and release clinic appointments for other patients. The study aimed to evaluate three home-monitoring tests for patients to use to detect active neovascular age-related macular degeneration compared with diagnosing active neovascular age-related macular degeneration by hospital follow-up. Objectives: There were five objectives: Estimate the accuracy of three home-monitoring tests to detect active neovascular age-related macular degeneration. Determine the acceptability of home monitoring to patients and carers and adherence to home monitoring. Explore whether inequalities exist in recruitment, participants' ability to self-test and their adherence to weekly testing during follow-up. Provide pilot data about the accuracy of home monitoring to detect conversion to neovascular age-related macular degeneration in fellow eyes of patients with unilateral neovascular age-related macular degeneration. Describe challenges experienced when implementing home-monitoring tests. Design: Diagnostic test accuracy cohort study, stratified by time since starting treatment. Setting: Six United Kingdom Hospital Eye Service macular clinics (Belfast, Liverpool, Moorfields, James Paget, Southampton, Gloucester). Participants: Patients with at least one study eye being monitored by hospital follow-up. Reference standard: Detection of active neovascular age-related macular degeneration by an ophthalmologist at hospital follow-up. Index tests: KeepSight Journal: paper-based near-vision tests presented as word puzzles. MyVisionTrack®: electronic test, viewed on a tablet device. MultiBit: electronic test, viewed on a tablet device. Participants provided test scores weekly. Raw scores between hospital follow-ups were summarised as averages. Results: Two hundred and ninety-seven patients (mean age 74.9 years) took part. At least one hospital follow-up was available for 317 study eyes, including 9 second eyes that became eligible during follow-up, in 261 participants (1549 complete visits). Median testing frequency was three times/month. Estimated areas under receiver operating curves were < 0.6 for all index tests, and only KeepSight Journal summary score was significantly associated with the lesion activity (odds ratio = 3.48, 95% confidence interval 1.09 to 11.13, p = 0.036). Older age and worse deprivation for home address were associated with lower participation (χ2 = 50.5 and 24.3, respectively, p < 0.001) but not ability or adherence to self-testing. Areas under receiver operating curves appeared higher for conversion of fellow eyes to neovascular age-related macular degeneration (0.85 for KeepSight Journal) but were estimated with less precision. Almost half of participants called a study helpline, most often due to inability to test electronically. Limitations: Pre-specified sample size not met; participants' difficulties using the devices; electronic tests not always available. Conclusions: No index test provided adequate test accuracy to identify lesion diagnosed as active in follow-up clinics. If used to detect conversion, patients would still need to be monitored at hospital. Associations of older age and worse deprivation with study participation highlight the potential for inequities with such interventions. Provision of reliable electronic testing was challenging. Future work: Future studies evaluating similar technologies should consider: Independent monitoring with clear stopping rules based on test performance. Deployment of apps on patients' own devices since providing devices did not reduce inequalities in participation and complicated home testing. Alternative methods to summarise multiple scores over the period preceding a follow-up. Trial registration: This trial is registered as ISRCTN79058224. Funding: This award was funded by the National Institute of Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 15/97/02) and is published in full in Health Technology Assessment; Vol. 28, No. 32. See the NIHR Funding and Awards website for further award information.

Treatment for neovascular age-related macular degeneration, the most common cause of sight loss in those over 50 years, involves regular eye injections and frequent follow-up appointments. This is inconvenient for patients and causes capacity issues in the hospital eye service. Finding tests that could be undertaken at home that could detect if a further injection and hospital appointment was required or not would increase capacity to see those at highest risk of sight loss and also reduce the burden on patients and their carers. We investigated three different visual function tests, one paper-based and two applications on an iPod Touch_TM tablet (Apple, Cupertino, CA, USA). We wanted to see if they could detect an increase in disease activity that would require treatment, compared to the decision by a retinal specialist at a traditional hospital eye outpatient visit based on clinical examination and retinal imaging. To encourage those without a smartphone or home internet to participate, we provided both an iPod Touch and Mobile Wireless-Fidelity device with a mobile contract. None of the tests performed well enough to safely monitor patients at home. Those who were willing to participate tended to be younger, had previous experience of using smartphones, sending e-mail and internet access and were more well-off than those who chose not to participate. Some participants also experienced difficulties with the devices provided and successfully uploading the data which were not related to the extent of previous information technology experience. There were also significant technical challenges for the research team. The study helpline was used heavily, considerably more than we anticipated. These tests are not ready to be used in this context. Future studies involving mobile health technology need to carefully consider how to reach those unlikely to participate and provide sufficient technical support to support long-term follow-up.

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BACKGROUND: Acute respiratory distress syndrome (ARDS) is a life-threatening respiratory condition with high mortality rates, accounting for 10% of all intensive care unit admissions. Lung ultrasound (LUS) as diagnostic tool for acute respiratory failure has garnered widespread recognition and was recently incorporated into the updated definitions of ARDS. This raised the hypothesis that LUS is a reliable method for diagnosing ARDS. OBJECTIVES: We aimed to establish the accuracy of LUS for ARDS diagnosis and classification of focal versus non-focal ARDS subphenotypes. METHODS: This systematic review and meta-analysis used a systematic search strategy, which was applied to PubMed, EMBASE and cochrane databases. Studies investigating the diagnostic accuracy of LUS compared to thoracic CT or chest radiography (CXR) in ARDS diagnosis or focal versus non-focal subphenotypes in adult patients were included. Quality of studies was evaluated using the QUADAS-2 tool. Statistical analyses were performed using "Mada" in Rstudio, version 4.0.3. Sensitivity and specificity with 95% confidence interval of each separate study were summarized in a Forest plot. RESULTS: The search resulted in 2648 unique records. After selection, 11 reports were included, involving 2075 patients and 598 ARDS cases (29%). Nine studies reported on ARDS diagnosis and two reported on focal versus non-focal ARDS subphenotypes classification. Meta-analysis showed a pooled sensitivity of 0.631 (95% CI 0.450-0.782) and pooled specificity of 0.942 (95% CI 0.856-0.978) of LUS for ARDS diagnosis. In two studies, LUS could accurately differentiate between focal versus non-focal ARDS subphenotypes. Insufficient data was available to perform a meta-analysis. CONCLUSION: This review confirms the hypothesis that LUS is a reliable method for diagnosing ARDS in adult patients. For the classification of focal or non-focal subphenotypes, LUS showed promising results, but more research is needed.

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Introduction  Fine-needle aspiration cytology (FNAC) has become widely used as a first-line diagnostic tool in the evaluation of cervical lymphadenopathies (LADs). However, there are conflicting reports regarding its accuracy in differentiating between malignant and benign pathologies. In this study, we aim to determine the reliability of FNAC in distinguishing between benign and malignant pathologies causing cervical LAD. Methods This is a cross-sectional study reviewing the electronic medical records of all patients who underwent both FNAC and excisional biopsy of cervical LADs between January 2016 and December 2023 at a tertiary care center in the Kingdom of Bahrain. A comparison was conducted between the cytopathological results obtained by FNAC and the histopathological results obtained by excisional biopsy to determine the diagnostic accuracy of FNAC. Results In the study period, 83 patient records were reviewed and included in the data analysis. Fine-needle aspiration cytology yielded a sensitivity of 89.3%, a specificity of 55.6%, a positive predictive value (PPV) of 72.4%, a negative predictive value (NPV) of 80.0%, and an overall accuracy of 74.7% in diagnosing cervical LADs. Conclusion Despite FNAC being accessible, convenient, and cost-effective, it has certain limitations that can restrict its accuracy in diagnosing lymphomas. We recommend further studies to research these limitations and the possible tools, such as ancillary testing, that may be useful in overcoming them.

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Background/Objectives: The purpose of this preliminary study was to evaluate the diagnostic performance of an AI-driven platform, Diagnocat (Diagnocat Ltd., San Francisco, CA, USA), for assessing endodontic treatment outcomes using panoramic radiographs (PANs). Materials and Methods: The study included 55 PAN images of 55 patients (15 males and 40 females, aged 12-70) who underwent imaging at a private dental center. All images were acquired using a Hyperion X9 PRO digital cephalometer and were evaluated using Diagnocat, a cloud-based AI platform. The AI system assessed the following endodontic treatment features: filling probability, obturation adequacy, density, overfilling, voids in filling, and short filling. Two human observers independently evaluated the images, and their consensus served as the reference standard. The diagnostic accuracy metrics were calculated. Results: The AI system demonstrated high accuracy (90.72%) and a strong F1 score (95.12%) in detecting the probability of endodontic filling. However, the system showed variable performance in other categories, with lower accuracy metrics and unacceptable F1 scores for short filling and voids in filling assessments (8.33% and 14.29%, respectively). The accuracy for detecting adequate obturation and density was 55.81% and 62.79%, respectively. Conclusions: The AI-based system showed very high accuracy in identifying endodontically treated teeth but exhibited variable diagnostic accuracy for other qualitative features of endodontic treatment.

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Background: This study evaluates the diagnostic accuracy of an AI-assisted tool in assessing the proximity of the mandibular canal (MC) to the root apices (RAs) of mandibular teeth using computed tomography (CT). Methods: This study involved 57 patients aged 18-30 whose CT scans were analyzed by both AI and human experts. The primary aim was to measure the closest distance between the MC and RAs and to assess the AI tool's diagnostic performance. The results indicated significant variability in RA-MC distances, with third molars showing the smallest mean distances and first molars the greatest. Diagnostic accuracy metrics for the AI tool were assessed at three thresholds (0 mm, 0.5 mm, and 1 mm). Results: The AI demonstrated high specificity but generally low diagnostic accuracy, with the highest metrics at the 0.5 mm threshold with 40.91% sensitivity and 97.06% specificity. Conclusions: This study underscores the limited potential of tested AI programs in reducing iatrogenic damage to the inferior alveolar nerve (IAN) during dental procedures. Significant differences in RA-MC distances between evaluated teeth were found.

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Background: Serum carbohydrate antigen 50 (CA50) is an auxiliary diagnostic marker for various solid tumors, but it remains unclear whether CA50 in pleural fluid can assist in the diagnosis of malignant pleural effusion (MPE). This study aimed to evaluate the diagnostic accuracy of pleural fluid CA50 for MPE in pleural effusion patients with undetermined causes. Methods: This study prospectively recruited pleural effusion patients with undetermined causes who visited the Affiliated Hospital of Inner Mongolia Medical University between September 2018 and July 2021. We measured pleural fluid CA50 level with an electrochemiluminescence assay. We analyzed the diagnostic accuracy of CA50 and carcinoembryonic antigen (CEA) for MPE with the receiver operating characteristic (ROC) curve. The net benefits of CA50 and CEA were analyzed using the decision curve analysis (DCA). Results: We enrolled 66 MPEs and 87 benign pleural effusions (BPEs). MPE patients had significantly higher CA50 and CEA than BPE patients. The area under the ROC curve (AUC) of CA50 was 0.72 (95% CI: 0.63-0.80). CA50 had a sensitivity of 0.30 (95% CI: 0.19-0.41) and a specificity of 1.00 (95% CI: 1.00-1.00) at the threshold of 15 IU/mL. The decision curve of CA50 was above the reference line at the calculated risk probability of between 0.30 and 1.00. Venn diagram indicated that some patients with low CEA (<50 or <150 ng/mL) and/or negative cytology can be identified by positive CA50 (>15 IU/mL). Conclusions: Pleural fluid CA50 has moderate accuracy and net benefit for detecting MPE. CA50 >15 IU/mL can be used to diagnose MPE. The combination of CA50 and CEA improves the diagnostic sensitivity for MPE.

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BACKGROUND: Lipid accumulation product (LAP) is a novel predictor index of central lipid accumulation associated with metabolic and cardiovascular diseases. This study aims to investigate the accuracy of LAP for the screening of metabolic syndrome (MetS) in general adult males and females and its comparison with other lipid-related indicators. METHODS: A systematic literature search was conducted in PubMed, Scopus, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and ProQuest for eligible studies up to May 8, 2024. Outcomes were pooled mean difference (MD), odds ratio (OR), and diagnostic accuracy parameters (sensitivity, specificity, and area under the summary receiver operating characteristic [AUSROC] curve). Comparative analysis was conducted using Z-test. RESULTS: Forty-three studies involving 202,313 participants (98,164 males and 104,149 females) were included. Pooled MD analysis showed that LAP was 45.92 (P < 0.001) and 41.70 units (P < 0.001) higher in men and women with MetS, respectively. LAP was also significantly associated with MetS, with pooled ORs of 1.07 (P < 0.001) in men and 1.08 (P < 0.001) in women. In men, LAP could detect MetS with a pooled sensitivity of 85% (95% CI: 82%-87%), specificity of 81% (95% CI: 80%-83%), and AUSROC curve of 0.88 (95% CI: 0.85-0.90), while in women, LAP had a sensitivity of 83% (95% CI: 80%-86%), specificity of 80% (95% CI: 78%-82%), and AUSROC curve of 0.88 (95% CI: 0.85-0.91). LAP had a significantly higher AUSROC curve (P < 0.05) for detecting MetS compared to body mass index (BMI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), body roundness index (BRI), a body shape index (ABSI), body adiposity index (BAI), conicity index (CI) in both genders, and waist circumference (WC) and abdominal volume index (AVI) in females. CONCLUSION: LAP may serve as a simple, cost-effective, and more accurate screening tool for MetS in general adult male and female populations.

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Introduction Serous effusion cytopathology is a minimally invasive, cost-effective procedure and plays a crucial role in diagnosing a spectrum of pathological conditions, ranging from benign to malignant. The International System for Reporting Serous Fluid Cytopathology (ISRSFC) offers a standardized framework for reporting serous effusions, aiding in better communication and clinical decision-making. Aims and objectives This study aimed to categorize effusions using the ISRSFC reporting system. In addition, we sought to estimate the risk of malignancy (ROM) for each diagnostic category and evaluate the diagnostic performance of conventional smear versus cell block techniques. Materials and methods This cross-sectional study was conducted in the Department of Pathology over one year. We applied the ISRSFC criteria to serous effusions and categorized them accordingly. The ROM for each category was assessed with histopathology serving as the gold standard. Then, the diagnostic performance including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy was evaluated using conventional smear and cell block techniques. Results The study included 185 serous effusion cases, with ages ranging from two months to 85 years. The male-to-female ratio was 1.1:1. Most effusions were pleural fluids constituting about 133 cases (71.9%), followed by peritoneal fluids (47 cases, 25.4%) and pericardial fluids (five cases, 2.7%). Among the fluids, four (2.2%) were diagnosed as non-diagnostic (ND), 152 (82.2%) as negative for malignancy (NFM), four (2.2%) as atypia of undetermined significance (AUS), nine (4.8%) as suspicious for malignancy (SFM), and 16 (8.6%) as malignant (MAL). The overall ROM was 25% for ND, 8.5% for NFM, 50% for AUS, 77% for SFM, and 100% for MAL. The sensitivity, negative predictive value (NPV), and diagnostic accuracy were superior when combining conventional smear with the cell block technique. Conclusions Our findings underscore the use of ISRSFC in categorizing effusion samples, assessing the ROM, and guiding clinical management. Moreover, our study highlights the benefits of employing a combined approach using conventional smears and cell blocks for enhanced diagnostic accuracy in serous effusions.

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Background/Objectives: Periapical lesions (PLs) are frequently detected in dental radiology. Accurate diagnosis of these lesions is essential for proper treatment planning. Imaging techniques such as orthopantomogram (OPG) and cone-beam CT (CBCT) imaging are used to identify PLs. The aim of this study was to assess the diagnostic accuracy of artificial intelligence (AI) software Diagnocat for PL detection in OPG and CBCT images. Methods: The study included 49 patients, totaling 1223 teeth. Both OPG and CBCT images were analyzed by AI software and by three experienced clinicians. All the images were obtained in one patient cohort, and findings were compared to the consensus of human readers using CBCT. The AI's diagnostic accuracy was compared to a reference method, calculating sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and F1 score. Results: The AI's sensitivity for OPG images was 33.33% with an F1 score of 32.73%. For CBCT images, the AI's sensitivity was 77.78% with an F1 score of 84.00%. The AI's specificity was over 98% for both OPG and CBCT images. Conclusions: The AI demonstrated high sensitivity and high specificity in detecting PLs in CBCT images but lower sensitivity in OPG images.