Search

Purpose: To compare the diagnostic efficacy of the Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score with that of the modified O-RADS score on the basis of a simplified contrast-enhanced (CE) MRI protocol in characterizing adnexal masses with solid tissue. The added value of clinical features was evaluated to improve the ability of the scoring system to classify adnexal masses. Methods: A total of 124 patients with 124 adnexal lesions containing solid tissue were included in this two-center retrospective study. Among them, there were 40 benign lesions (40/124, 32.3%) and 84 were malignant lesions (84/124, 67.7%). Three radiologists independently reviewed the images and assigned the O-RADS MRI score and the modified O-RADS score for each adnexal mass. Histopathology was used as the reference standard. The diagnostic efficacy of the two scoring methods was compared. Univariate and multivariate logistic regression were performed to evaluate the value of significant features in the prediction of malignant tumors. Results: The O-RADS MRI score and modified O-RADS score showed sensitivity at 100.0% (95% CI, 95.7–100.0%) and 71.4% (95% CI, 60.5–80.8%), specificity at 12.5% (95% CI, 4.2–26.8%) and 75.0% (95% CI, 58.8–87.3%), respectively. The area under the curve of the modified O-RADS score was higher than the O-RADS score (0.732 [95% CI, 0.645–0.808] vs 0.575 [95% CI, 0.483–0.663]; p < 0.001). Multivariate analysis showed that the modified O-RADS score 4b or 5 combined with patient age > 38.5 years, nullipara, maximum diameter > 40.5 mm and HE4 > 78.9 pmol/L significantly improved the diagnostic efficacy up to 0.954 (95% CI, 0.901–0.984) (p < 0.001). Conclusion: A modified O-RADS score combined with certain clinical features can significantly improve the diagnostic efficacy in predicting malignant tumors. [ABSTRACT FROM AUTHOR]

Background and objective: The assessment and quantification of dopaminergic responsiveness are crucial for the diagnosis and management of Parkinson’s disease (PD). This study aimed to summarize and compare motor improvements in patients with PD and atypical parkinsonian syndromes (APS) across three types of dopaminergic challenge tests, as well as evaluate their diagnostic performance. Methods: PubMed, Embase, Cochrane Library, and Web of Science were searched to identify eligible studies reporting the improvement rate of the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) or MDS-UPDRS-III in dopaminergic challenge tests for PD or APS, or diagnostic outcomes in differential diagnosis between PD and APS. A random-effects model was conducted to pool improvement rates and standardized mean differences (SMDs) in patients with PD or APS during dopaminergic challenge tests. Subgroup analysis and meta-regression were used to investigate the sources of heterogeneity. A bivariate mixed-effects model was employed to evaluate the diagnostic performance of these tests. Results: A total of 58 studies (3641 PD and 711 APS) were included. In the acute levodopa challenge test, patients with PD, APS, and multiple system atrophy (MSA) demonstrated pooled UPDRS-III improvement rates of 41.5% [95% confidence interval (CI) 38.5%–44.5%; I2 = 98.8%], 14.7% (95% CI 6.8%–22.7%; I2 = 96.5%), and 6.3% (95% CI − 4.0% to 16.7%), respectively. Subgroup analyses showed the pooled improvement rate of de novo PD patients (25.9%; 95% CI 15.1%–36.7%) was significantly lower than treated PD patients (42.4%; 95% CI 38.6%–46.2%) (p = 0.005), overlapping with APS patients with off-state H-Y stage ≤ 2.5 (21.2%; 95% CI 14.5%–27.9%). PD patients with off-state H-Y stage ≤ 2.5 (35.4%; 95% CI 31.1%–39.7%) or UPDRS-III score ≤ 30 (30.5%; 95% CI 23.4%–35.7%) had significantly lower improvement rate than PD patients with off-state H-Y stage > 2.5 (44.1%; 95% CI 37.0%–51.3%) (p = 0.041) or UPDRS-III scores > 30 (47.0%; 95% CI 43.7%–50.4%) (p < 0.001). The pooled improvement rate in acute levodopa challenge tests of PD with 100 mg levodopa (17.0%; 95% CI 11.3%–22.8%) was significantly lower than that in tests with 200–250 mg levodopa (34.3%; 95% CI 30.6%–38.0%) (p < 0.001). Meta-regression showed the improvement rate of PD was positively correlated with off-state UPDRS-III scores (p = 0.007). In the acute apomorphine challenge test, PD patients showed a pooled UPDRS-III improvement rate of 40.1% (95% CI 36.9%–43.3%). To differentiate between PD and APS, the pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) for the acute levodopa challenge test were 0.81, 0.77, 13.91, and 0.85; for the acute apomorphine challenge test, they were 0.84, 0.85, 29.94, and 0.91; and for chronic levodopa therapy, they were 0.82, 0.71, 11.54, and 0.72. The pooled sensitivity, specificity, DOR, and AUC of the acute levodopa challenge test for distinguishing PD from MSA were 0.82, 0.78, 15.74, and 0.79; for PD vs. PSP, they were 0.77, 0.78, 11.54, and 0.84; and for PD vs. DLB, they were 0.65, 0.58, 2.65, and 0.64. Conclusions: The overall dopaminergic responsiveness is greater in PD patients compared to those with APS. However, there is significant heterogeneity in the pooled motor improvement of dopaminergic responsiveness within PD or APS, with overlap between de novo PD and early-stage APS. All three types of dopaminergic challenge tests demonstrate moderate diagnostic performance in differentiating PD from APS. [ABSTRACT FROM AUTHOR]

Plasma tau phosphorylated at threonine 181 (p-tau181) and 217 (p-tau217) have demonstrated high accuracy for Alzheimer’s disease (AD) diagnosis, defined by CSF/PET amyloid beta (Aβ) positivity, but most studies have been performed in research cohorts, limiting their generalizability. We studied plasma p-tau217 and p-tau181 for CSF Aβ status discrimination in a cohort of consecutive patients attending an academic memory clinic in Spain (July 2019–June 2024). All patients had CSF AD biomarkers performed as part of their routine clinical assessment. Aβ positivity was defined with a local cut-off of CSF Aβ1–42 < 600 pg/mL; in patients with borderline Aβ1–42 values or when there was a mismatch between the Aβ and the T status (T + if CSF p-tau181 ≥ 65 pg/mL), a ratio Aβ1–42/Aβ1–40 < 0.07 was used. Plasma p-tau217 and p-tau181 were measured retrospectively, from blood samples collected at first visit, with Fujirebio Lumipulse and Quanterix Simoa assays, respectively. We included 468 patients (mean age 67 years, 50% female, 61% Aβ positive). Plasma p-tau217 outperformed plasma p-tau181 in discriminating CSF Aβ status (AUC 0.95 vs 0.90, p = 0.005). A 97.5% sensitivity and specificity plasma p-tau217 algorithm, classifying patients into three groups of Aβ probability (Low, Intermediate and High), resulted in 67% of patients in the Low and High groups, having their Aβ status predicted (as negative and positive, respectively) with 96% accuracy. The remaining 33% in the Intermediate group were candidates to undergo CSF/PET testing. A model with a 10% variation in p-tau217 levels yielded small changes in accuracy (95%). In conclusion, plasma p-tau217 could have discriminated CSF Aβ status in two-thirds of patients with very high accuracy in a memory clinic cohort. These results support the implementation of plasma p-tau217 as an initial diagnostic tool in memory clinics for AD diagnosis, reducing the need for more invasive/expensive testing. [ABSTRACT FROM AUTHOR]

Background: Low malaria parasitaemia is a diagnostic challenge in pregnancy, leading to false negative microscopy and rapid diagnostic test (RDT) results. However, these submicroscopic or subpatent infections could cause adverse pregnancy outcomes. Thus, evaluating the diagnostic performance of microscopy, RDT, and multiplex qPCR in pregnancy is vital for informed decisions. Methods: A total of 835 peripheral blood and 372 placental blood samples were collected from 835 pregnant women attending first antenatal care or admitted for delivery at selected health facilities in northwest Ethiopia between November 2021 and July 2022. In multiplex qPCR, all microscopy and/or RDT positive samples were extracted and amplified individually, whereas all samples negative by both RDT and microscopy were extracted after pooling ten samples together and tested for Plasmodium genus. The diagnostic performance of microscopy, RDT, and multiplex qPCR in pregnancy was compared and evaluated against each other. Results: Using multiplex qPCR as a reference test, microscopy had a sensitivity of 73.8% (95% confidence interval (CI): 65.9–80.7) and 62.2% (95% CI: 46.5–76.2) to detect Plasmodium parasites in peripheral and placental blood samples, respectively, with a 100% (95% CI: 98.9–100) specificity in both samples. Similarly, the RDT had a sensitivity of 67.6% (95% CI: 59.3–75.1) and a specificity of 96.5% (95% CI: 94.9–97.8) for Plasmodium infection diagnosis in peripheral blood and a sensitivity of 62.2% (95% CI: 46.5–76.2) and a specificity of 98.8% (95% CI: 96.9–99.7) in placental blood samples. Considering microscopy as a reference test, multiplex qPCR showed a sensitivity of 100% (95% CI: 96.6–100) and a specificity of 94.8% (95% CI: 93.0–96.3) to diagnose Plasmodium infections in both peripheral and placental blood samples. Pooled multiplex qPCR detected 34 peripheral and 12 placental blood Plasmodium infections from microscopy and RDT negative samples. The pooled assay obviated about half of the reactions and its testing costs. Microscopy showed almost perfect agreement (κ = 0.823) with multiplex qPCR for detecting malaria parasites in pregnancy, whereas the RDT showed a substantial agreement (κ = 0.684). Conclusion: Multiplex qPCR had a better performance for Plasmodium infection diagnosis in pregnancy compared to microscopy and RDT. Pooled multiplex qPCR could be a sensitive and resource-efficient strategy for epidemiological surveillance of Plasmodium infections in pregnancy. [ABSTRACT FROM AUTHOR]

Background: Peritonsillar abscess (PTA) is relatively common but challenging to diagnose clinically. Several clinical signs may be used, with unknown performances. We evaluated and compared the diagnostic performance of individual and combined clinical signs (trismus, edema, pharynx immobility, uvula deviation, hot potato voice, and overall clinical impression) assessed by an otolaryngologist and of contrast-enhanced computed tomography (CT) to detect acute PTA. Methods: Prospective study in 133 consecutive adult patients (77 males, mean age = 33 years) with suspected clinical PTA and CT obtained in the emergency setting of a tertiary care hospital between November 2020 and October 2022. The standard of reference consisted of surgically proven pus within 24 h of CT or a favorable clinical evolution at 48 h without surgical intervention. Results: PTA was present in 117/133 (88%) patients, with no difference between mean age or sex distribution between the groups with and without PTA. None of the evaluated clinical signs were associated with PTA (OR = 1.26–5.43, p > 0.05), whereas the CT finding "abscess" was significantly associated with PTA (OR = 67.2, p < 0.0001). The sensitivity of individual clinical signs varied between 19.7% and 73.5%, and the sensitivity of CT was significantly higher for all clinical signs (95.7%, p < 0.0001) except for overall clinical impression (97.4%, p = 0.7266). The specificity of clinical signs varied between 12.5% and 93.8%, and the specificity of CT was significantly higher (75%, p < 0.05) for overall clinical impression and edema. All clinical signs together yielded an area under the curve (AUC) = 0.677. Conclusions: In adults, clinical assessment alone using independent clinical signs and overall clinical impression does not allow a reliable diagnosis of PTA, even when performed by an otolaryngologist. CT is reliable in diagnosing PTA and, whenever available, should be the examination method of choice for diagnosing PTA, especially by a non-specialist. [ABSTRACT FROM AUTHOR]

Background: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality. Methods: We enrolled a cohort of sixty patients who underwent DL-MRI, conventional MRI, and No-DL MRI examinations to evaluate image quality. Key metrics considered in the assessment included scan duration, overall image quality, quantitative assessments of Relative Signal-to-Noise Ratio (rSNR), Relative Contrast-to-Noise Ratio (rCNR), and diagnostic efficacy. Two experienced radiologists independently assessed image quality using a 5-point scale (5 indicating the highest quality). To gauge interobserver agreement for the assessed pathologies across image sets, we employed weighted kappa statistics. Additionally, the Wilcoxon signed rank test was employed to compare image quality and quantitative rSNR and rCNR measurements. Results: Scan time was significantly reduced with DL-MRI and represented an approximate 66.5% reduction. DL-MRI consistently exhibited superior image quality in both coronal T2WI and axial T2WI when compared to both conventional MRI (p < 0.01) and No-DL-MRI (p < 0.01). Interobserver agreement was robust, with kappa values exceeding 0.735. For rSNR data, coronal fat-saturated(FS) T2WI and axial FS T2WI in DL-MRI consistently outperformed No-DL-MRI, with statistical significance (p < 0.01) observed in all cases. Similarly, rCNR data revealed significant improvements (p < 0.01) in coronal FS T2WI of DL-MRI when compared to No-DL-MRI. Importantly, our findings indicated that DL-MRI demonstrated diagnostic performance comparable to conventional MRI. Conclusion: Integrating deep learning-based reconstruction methods into standard clinical workflows has the potential to the promise of accelerating image acquisition, enhancing image clarity, and increasing patient throughput, thereby optimizing diagnostic efficiency. Trial registration: Retrospectively registered. Key points: Deep learning based reconstruction Magnetic Resonance Imaging (DL-MRI) not only expedites scan times but also significantly enhances imaging quality. [ABSTRACT FROM AUTHOR]

Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning techniques. Clinical data from 2594 samples were obtained and stratified into training and validation datasets in a 7:3 ratio. Key clinical features were identified through differential analysis between KOA and control groups, combined with least absolute shrinkage and selection operator (LASSO) regression. The SHapley Additive Planning (SHAP) method was employed to rank feature importance quantitatively. Based on these rankings, predictive models were constructed using Logistic Regression (LR), Random Forest (RF), eXtreme Gradient Boosting (xGBoost), Naive Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT) algorithms. Models were developed for subsets of variables, including the top 5, top 10, top 15, and all identified features. Receiver operating characteristic (ROC) curves were applied to compare diagnostic performance across models. Additionally, a risk stratification framework for KOA prediction was designed using recursive partitioning analysis (RPA). Using difference analysis and LASSO, 44 critical clinical features were identified. Among these, age, plasma prothrombin time, gender, body mass index (BMI), and prothrombin time and international normalized ratio (PTINR) emerged as the top five features, with SHAP values of 0.1990, 0.0981, 0.0471, 0.0433, and 0.0422, respectively. Machine learning analysis demonstrated that these variables provided robust diagnostic performance for KOA. In the training set, area under the curve (AUC) values for LR, RF, xGBoost, NB, SVM, and DT models were 0.947, 0.961, 0.892, 0.952, 0.885, and 0.779, respectively. Similarly, in the validation dataset, these models achieved AUC values of 0.961, 0.943, 0.789, 0.957, 0.824, and 0.76. Among them, RF consistently exhibited superior diagnostic accuracy for KOA. Additionally, RPA analysis indicated a higher prevalence of KOA among individuals aged 54 years and older. The integration of the top five clinical variables significantly enhanced the diagnostic accuracy for KOA, particularly when employing the RF model. Moreover, the RPA model offered valuable insights to assist clinicians in refining prognostic assessments and optimizing clinical decision-making processes. [ABSTRACT FROM AUTHOR]

To explore the differences between SonoVue and Sonazoid contrast-enhanced ultrasound (CEUS) in evaluating enhancement features of renal masses and determine the diagnostic value of CEUS in clear cell renal cell carcinoma (ccRCC). A total of 57 eligible patients were enrolled and divided into the ccRCC, papillary renal cell carcinoma (pRCC), non-ccRCC and non-pRCC malignancy groups, and benign mass groups based on their postsurgical histopathologic diagnosis. The enhancement features of renal masses following SonoVue and Sonazoid CEUS in each group were analyzed. Diagnostic efficiencies of SonoVue and Sonazoid CEUS for ccRCC and non-ccRCC were determined. There were no significant differences in the enhancement features of renal masses with SonoVue and Sonazoid imaging in the four groups (p >.05). Both SonoVue CEUS and Sonazoid CEUS showed good diagnostic performance for the differential diagnosis of ccRCC and non-ccRCC, with sensitivities of 88.6% and 85.7%, specificities of 76.5% and 88.2%, accuracies of 84.6% and 86.5%, positive predictive values of 88.6% and 93.8%, and negative predictive values of 76.5% and 75%, respectively. There were no statistically significant differences in any of the diagnostic performance indices between the two methods (p >.05). The CEUS features of SonoVue and Sonazoid in evaluating renal masses were similar in the vascular phase. Both SonoVue and Sonazoid CEUS showed good diagnostic performance for the differential diagnosis of ccRCC and non-ccRCC. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to assess the diagnostic capabilities of Diffusion Kurtosis Imaging (DKI) and Intravoxel Incoherent Motion (IVIM) in prostate cancer (PCa) detection and characterization. Materials: A comprehensive search was conducted across PubMed, Scopus, Web of Science, and the Cochrane Library for articles published up to September 10, 2023, that evaluated the diagnostic efficacy of MD, MK, Dt, f, and Dp parameters. Data were pooled using a bivariate mixed-effects regression model and analyzed with R software. Results: In total, 27 studies were included. The analysis revealed distinct diagnostic efficacies for DKI and IVIM. In the overall model, sensitivity and specificity were 0.807 and 0.797, respectively, with prospective studies showing higher specificity (0.858, p = 0.024). The detection model yielded increased sensitivity (0.845) and specificity (0.812), with DKI outperforming IVIM in both metrics (sensitivity: 0.87, p = 0.043; specificity: 0.837, p = 0.26); MD had high sensitivity (0.88) and specificity (0.82), while MK's specificity was significantly higher (0.854, p = 0.04); Dp's sensitivity was significantly lower (0.64, p = 0.016). In characterization, sensitivity and specificity were 0.708 and 0.735, respectively, with no significant differences between DKI and IVIM or Gleason Scores; MK had higher sensitivity (0.78, p = 0.039), and f's sensitivity was significantly lower (0.51, p = 0.019). Conclusion: In summary, the study underscores DKI's enhanced diagnostic accuracy over IVIM in detecting PCa, with MK standing out for its precision. Conversely, Dp and f lag in diagnostic performance. Despite these promising results, the study highlights the imperative for standardized protocols and study designs to achieve reliable and consistent outcomes. [ABSTRACT FROM AUTHOR]

Background/Aim: The recently published Node-Reporting and Data System (Node-RADS) can aid the characterization of lymph nodes in cross-sectional imaging. This study investigated the Node-RADS system in computed tomography (CT) to characterize lymph nodes in esophageal cancer. Patients and Methods: Overall, 126 patients (15 female, 11.9%) with a mean age of 62.1±10.4 years comprised the patient sample. All patients underwent resection with curative intent and the lymph nodes were histopathologically analyzed during clinical routine. For every patient, the locoregional lymph nodes were scored in accordance with the Node-RADS classification. For statistical analysis, receiver-operating characteristics (ROC) with area under the curve (AUC) were used to test for diagnostic accuracy; inter-reader variability was assessed with Cohen's kappa. Results: Overall, 54 patients were nodal positive (42.9%), 72 patients were nodal negative (57.1%). Inter-reader agreement was substantial for the overall Node-RADS scoring (ĸ=0.65, p<0.001). ROC curve analysis for lymph node discrimination (N0 versus N1-3) showed an AUC of 0.69 (95% confidence interval=0.59-0.79). A threshold score of more than 2 resulted in a sensitivity of 0.77 and a specificity of 0.55 for correctly predicting nodal positivity. Node-RADS 1 category had a malignancy rate of 30%, Node-RADS 2 of 14%, Node-RADS 3 of 81%, Node-RADS 4 of 90.1% and Node-RADS 5 of 86.5%. Conclusion: The Node-RADS score on staging CT is associated with the malignancy rate of lymph nodes in patients with EC with only moderate diagnostic accuracy. The inter-reader variability is moderate, which could pose difficulties for translation into clinical routine. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to perform a Bayesian network meta-analysis to assess the comparative diagnostic performance of different imaging modalities in chronic pancreatitis(CP). Methods: The PubMed, Embase and Cochrane Library databases were searched for relevant publications until March 2024. All studies evaluating the head-to-head diagnostic performance of imaging modalities in CP were included. Bayesian network meta-analysis was performed to compare the sensitivity and specificity between the imaging modalities. The Quality Assessment of Diagnostic Performance Studies (QUADAS-2) tool was used to evaluate the quality of studies. Results: This meta-analysis incorporated 17 studies. Network meta-analytic results indicated that endoscopic ultrasonography (EUS) achieved the highest surface under the cumulative ranking (SUCRA) value at 0.86 for sensitivity. Conversely, magnetic resonance imaging (MRI) demonstrated best specificity, recording the highest SUCRA value at 0.99. Ultrasonography (US) displayed comparatively lower sensitivity than endoscopic retrograde cholangiopancreatography (ERCP) (relative risk[RR]: 0.83, 95% Confidence Interval[CI]: 0.69–0.99) and EUS (RR: 0.73, 95% CI: 0.57–0.91). MRI outperformed all other imaging modalities in terms of specificity. Conclusions: It appears that EUS demonstrates higher sensitivity, while MRI exhibits higher specificity in patients with chronic pancreatitis. However, it is crucial to note that our analysis was limited to the diagnostic performance and did not evaluate the cost-effectiveness of these various imaging modalities. Consequently, further extensive studies are needed to assess the benefit-to-risk ratios comprehensively. [ABSTRACT FROM AUTHOR]

Introduction: Diffusion weighted MRI (DWI) has emerged as a promising adjunct to reduce unnecessary biopsies prompted by breast MRI through use of apparent diffusion coefficient (ADC) measures. The purpose of this study was to investigate the effects of different lesion ADC measurement approaches and ADC cutoffs on the diagnostic performance of breast DWI in a high-risk MRI screening cohort to identify the optimal approach for clinical incorporation. Methods: Consecutive screening breast MRI examinations (August 2014–Dec 2018) that prompted a biopsy for a suspicious breast lesion (BI-RADS 4 or 5) were retrospectively evaluated. On DWI, ADC (b=0/100/600/800s/mm2) measures were calculated with three different techniques for defining lesion region-of-interest (ROI; single slice('2D'), whole volume('3D') and lowest ADC region('hotspot')). An optimal data-derived ADC cutoff for each technique was retrospectively identified to reduce benign biopsies while avoiding any false negatives, inherently producing cutoffs with 100% sensitivity in this particular cohort. Further, diagnostic performance of these measures was validated using two prespecified ADC cutoffs: 1.53x10-3mm2/s from the ECOG-ACRIN A6702 trial and 1.30x10-3mm2/s from the international EUSOBI group. Diagnostic performance was compared between ADC maps generated with 2(0/800s/mm2) and 4(0/100/600/800s/mm2) b-values. Benign biopsy reduction rate was calculated (number of benign lesions with ADC >cutoff)/(total number of benign lesions). Results: 137 suspicious lesions (in 121 women, median age 44 years [range, 20-75yrs]) were detected on contrast-enhanced screening breast MRI and recommended for biopsy. Of those, 30(21.9%) were malignant and 107(78.1%) were benign. Hotspot ADC measures were significantly lower (p<0.001) than ADCs from both 2D and 3D ROI techniques. Applying the optimal data-derived ADC cutoffs resulted in comparable reduction in benign biopsies across ROI techniques (range:16.8% -17.8%). Applying the prespecified A6702 and EUSOBI cutoffs resulted in benign biopsy reduction rates of 11.2-19.6%(with 90.0-100% sensitivity) and 36.4-51.4%(with 70.0-83.3% sensitivity), respectively, across ROI techniques. ADC measures and benign biopsy reduction rates were similar when calculated with only 2 b-values (0,800 s/mm2) versus all 4 b-values. Discussion: Our findings demonstrate that with appropriate ADC thresholds, comparable reduction in benign biopsies can be achieved using lesion ADC measurements computed from a variety of approaches. Choice of ADC cutoff depends on ROI approach and preferred performance tradeoffs (biopsy reduction vs sensitivity). [ABSTRACT FROM AUTHOR]

To evaluate the diagnostic value of metagenomic next-generation sequencing (mNGS) and galactomannan (GM) testing in invasive pulmonary aspergillosis (IPA) and to compare mNGS with other diagnostic approaches (serum/bronchoalveolar lavage fluid (BALF)-GM and conventional microbiological tests (CMTs) including sputum smears and culture, BALF fungal culture, and bronchial brushing). In all, 237 patients were enrolled in this retrospective study, including 120 patients with IPA and 117 with non-IPA pulmonary infections treated at Henan Provincial People's Hospital between June 2021 and February 2024. The diagnostic performance of mNGS was compared to conventional diagnostic methods including serum GM, BALF-GM, sputum smear microscopy, sputum culture, bronchial brushings, and BALF culture. The proportion of patients with underlying diseases was significantly higher in the IPA group than in the non-IPA group (P < 0.05). Compared to conventional diagnostic methods for IPA, mNGS showed higher diagnostic efficacy, with a sensitivity of 92.5% and a specificity of 94.02%. The area under the receiver operating characteristic curve (AUC) for BALF-GM for diagnosing IPA was 0.8, with an optimal cutoff value of 0.546, sensitivity of 66.7%, and specificity of 82.1%. The combination of mNGS and BALF-GM testing further improved diagnostic performance (sensitivity of 96.67% and specificity of 78.63%). mNGS testing has excellent diagnostic efficacy for IPA, which is further enhanced by combining it with BALF-GM testing. This approach has considerable potential for the early diagnosis and targeted treatment of IPA. [ABSTRACT FROM AUTHOR]

Ultrasound biomicroscopy (UBM) is the standard for diagnosing plateau iris, but its limited accessibility in routine clinical settings presents challenges. While anterior segment optical coherence tomography (AS-OCT) is more convenient, its effectiveness in detecting plateau iris is limited. Previous research has demonstrated that combining UBM and AS-OCT image pairs through neural style transfer has improved classification accuracy. However, obtaining paired images is impractical in everyday practice. In this study, we propose a novel semi-supervised approach that eliminates the need for paired images. A generative model learns to distinguish plateau and non-plateau features from UBM images. AS-OCT images are input into the generator, which attempts to transform them into corresponding UBM images. The model's performance is measured by loss values, representing the difficulty of transforming AS-OCT images, which are then used to predict plateau iris. The classification baseline, which applies AS-OCT solely without the style-transfer of UBM information, obtained 52.72% sensitivity, 60.82% specificity, and 57.89% accuracy for external validation; in contrast, the classification with neural style transfer of the image pairs respectively obtained 94.54%, 100.00%, and 98.03%, whereas the semi-supervised approach using loss values classification obtained 93.10%, 93.13%, and 93.12%, respectively. This semi-supervised transfer learning model presents a novel technique for detecting plateau iris with AS-OCT. [ABSTRACT FROM AUTHOR]

ABSTRACT Red sea bream iridovirus (RSIV) occurs mainly at high water temperatures and infects more than 30 different species of fish. In Asia, infected fish cause mass mortality every year. Molecular diagnostics is a technology that efficiently detects and identifies a wide range of fish pathogens through rapid and sensitive analysis of their genetic material. Rapid viral detection is essential for effective disease control. In this study, we developed and validated a cross‐priming amplification‐based lateral flow assay (CPA‐LFA) suitable for field diagnosis owing to its short diagnostic time and simple diagnostic process. The CPA‐LFA achieved optimal performance with concentrations of 4 mM MgSO4, 1.2 mM dNTPs and 0.7 M betaine, with the reaction conducted at 60°C for 60 min. The developed CPA‐LFA could specifically identify RSIV without cross‐reactivity with several pathogens commonly reported in various fish cell lines and fish. The 95% limit of detection (LOD95%) of CPA‐LFA was 385.76 copies/μL, which was comparable to that of conventional polymerase chain reaction (PCR). Quantitative PCR (qPCR) was used to identify true‐positive and true‐negative samples from 210 fish samples (160 from cultured fish and 50 from artificially infected fish). Compared with qPCR, CPA‐LFA classified six positive samples as false positives. The viral load of these samples was determined to be less than 195.1 copies/μL. The diagnostic sensitivity and specificity of CPA‐LFA were 94.34% and 100%, respectively. Furthermore, inter‐operator reproducibility testing yielded a kappa value of 1.0, indicating perfect agreement. Therefore, the novel CPA‐LFA is especially well‐suited for field diagnostics owing to its straightforward diagnostic procedure and capability to quickly and accurately detect RSIV. [ABSTRACT FROM AUTHOR]

During periods of high-power operation, proton exchange membrane fuel cell (PEMFC) produce water, which gradually accumulates at the cathode. It causes flooding faults and significantly impacts on PEMFC safety. The data collected by the sensors is a fundamental prerequisite for the flooding faults diagnosis in PEMFC. Consequently, it is critical to select sensors. However, the conventional methods for selecting sensors consider sensitivity and noise immunity, the number of sensors selected and the flood diagnostic performance are not optimized. To solve the above problems, this paper proposes a sensor preference method that combines the Mantel test and Spearman coefficient (MS method). This method first uses the Mantel test to analyze the correlation between two flooding evaluation indicators and the sensors, it identifies suitable sensors for diagnosing flooding faults. Subsequently, the Spearman coefficient eliminates redundant sensors. Additionally, a one-dimensional convolutional neural network is employed to construct a flooding diagnosis model. The MS method is contrasted with two traditional sensor selection methods. The results show that the MS method selected sensors yield superior model training and enhanced accuracy in diagnosing flooding, thereby ensuring PEMFC safety. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess the efficacy of innovative Chemiluminescence Immunoassay (CLIA) in testing Cryptococcal Antigen (CrAg) across two medical centers, employing the FDA-approved CrAg Lateral Flow Assay (LFA) by IMMY as a reference standard. Methods: The study encompassed patients diagnosed with cryptococcosis at West China Hospital of Sichuan University (HX) between July 2022 and May 2023, and Suzhou Fifth People's Hospital (SZ) from September 2020 to September 2023. All specimens underwent simultaneous detection using the LFA (IMMY, Norman, USA) and CLIA (Chuanglan, Suzhou, China). Results: A total of 628 patients were enrolled, revealing a remarkable 99.20% concordance between LFA and CLIA (623/628, 99.20%). The LFA exhibited a sensitivity of 96.83% (244/252) and specificity of 98.35% (179/182). Among the 42 patients with unaltered CrAg titers, the changes of Signal-to-Cut-Off ratio (ΔS/CO) results exhibited a noteworthy discrepancy, with 71.43% (30/42) demonstrating a decreasing trend in ΔS/CO of at least 10%. Conclusions: The CLIA method demonstrated commendable specificity and sensitivity, exhibiting a high level of agreement with the FDA-approved LFA method. Additionally, CLIA demonstrated superior utility for treatment monitoring compared to LFA, offering continuous insight into the fluctuation of CrAg concentrations. [ABSTRACT FROM AUTHOR]

Objective: To investigate the clinical application value of microfluidic-based in vitro diagnostic (IVD) technology in pathogenic detection of respiratory tract infections. Methods: A total of 300 clinical samples, including blood, bronchoalveolar lavage fluid, and pleural effusion, were collected from patients with respiratory tract infections. The samples were randomly divided into three groups: A, B, and C, with 100 cases in each group. Group A used traditional microbiological detection methods, Group B used metagenomic next-generation sequencing (mNGS) technology, and Group C used both microfluidic-based IVD technology and traditional microbiological detection methods to detect pathogenic microorganisms in the clinical samples. The positive detection rate, detection time, and detection cost were compared among the groups. The diagnostic performance of each group was compared using the Receiver Operating Characteristic (ROC) curve. Results: Traditional microbiological detection identified 38 positive samples (38%), including 45 pathogens; mNGS technology identified 95 positive samples (95%), including 210 pathogens; microfluidic-based IVD technology identified 96 positive samples (96%), including 158 pathogens. Microfluidic-based IVD technology had a significantly higher positive detection rate for pathogenic microorganisms compared to traditional culture techniques (96% vs 38%, χ2 = 122.0, P < 0.01), and it was also faster and cheaper than mNGS technology. ROC analysis showed that compared to traditional microbiological culture results, microfluidic-based IVD technology had significantly increased sensitivity and specificity, similar to mNGS technology. Conclusion: In respiratory infectious diseases, microfluidic-based IVD technology had a higher detection rate for pathogenic microorganisms than traditional culture methods, and it had advantages in detection time and cost compared to mNGS technology. It could also detect critical drug-resistant genes of pathogens. Hence, microfluidic-based IVD technology can be a viable option for diagnosis and treatment of respiratory infectious diseases. [ABSTRACT FROM AUTHOR]

Background: The current diagnostic strategy for hepatitis C virus (HCV) infection involves a two-step approach: antibody HCV screening followed by confirmatory nucleic acid testing. This study aimed to evaluate the diagnostic performance of the Abbott ARCHITECT HCV Ag assay in serum/plasma samples as a potential one-step alternative for diagnosing active HCV infection in people living with hepatitis B virus (PLWHB) through a systematic review and meta-analysis. Methods: A systematic review and meta-analysis were conducted following PRISMA-DTA guidelines. This protocol was registered on PROSPERO (CRD42023402093). A comprehensive search of electronic databases identified studies published up to 1 November 2024, comparing the ARCHITECT HCV Ag assay to an HCV-RNA reference standard. Sensitivity, specificity, and likelihood ratios were pooled using a random-effects model within the MIDAS module of Stata software. Study quality was assessed using QUADAS-2. Heterogeneity was evaluated using the Q statistic, quantified using the I², and further explored through meta-regression. Results: Ten studies (n = 494 participants) met inclusion criteria. The Abbott ARCHITECT HCV Ag assay demonstrated high sensitivity [91%, 95% confidence interval (CI): 76–97%] and specificity (99%, 95% CI: 99–100%). The positive likelihood ratio (PLR) was 81.20 (95% CI: 12.34–534.36), and the negative likelihood ratio (NLR) was 0.09 (95% CI: 0.03–0.27). The area under the summary receiver operating characteristic curve (AUC-SROC) was 99% (95% CI 98–100%). In regions with high HCV prevalence (≥ 10%), the test accurately confirmed active HCV infection in over 90% of cases. However, confirmatory testing remains necessary in low-prevalence settings (≤ 5%). The assay demonstrated an excellent ability to identify individuals without HCV infection, with a low false-negative rate (≤ 2%) regardless of HCV prevalence. Heterogeneity analysis revealed moderate to substantial variation in test performance (I² = 72.09% for sensitivity, 35.47% for PLR, and 78.33% for NLR). QUADAS-2 applicability concerns predicted heterogeneity, but differences were likely insignificant due to minimal variations and limited studies. Conclusions: The Abbott ARCHITECT HCV Ag assay exhibited promising accuracy in detecting active HCV infection among PLWHB. This test might help diagnose active HCV infection in high-prevalence scenarios (≥ 10%) but needs further confirmation in low-prevalence settings (≤ 5%). [ABSTRACT FROM AUTHOR]

Purpose: The aim of our study was to assess the diagnostic performance of commercially available AI software for intracranial aneurysm detection and to determine if the AI system enhances the radiologist's accuracy in identifying aneurysms and reduces image analysis time. Methods: TOF-MRA clinical brain examinations were analyzed using commercially available software and by an consultant neuroradiologist for the presence of intracranial aneurysms. The results were compared with the reference standard, to measure the sensitivity and specificity of the software and the consultant neuroradiologist. Furthermore, we examined the time required for the neuroradiologist to analyze the TOF-MRA image set, both with and without use of the AI software. Results: In 500 TOF-MRI brain studies, 106 aneurysms were detected in 85 examinations by combining AI software with neuroradiologist readings. The neuroradiologist identified 98 aneurysms (92.5% sensitivity), while AI detected 77 aneurysms (72.6% sensitivity). Specificity and sensitivity were calculated from the combined effort as reference. Combining AI and neuroradiologist readings significantly improves detection reliability. Additionally, AI integration reduced TOF-MRA analysis time by 19 s (23% reduction). Conclusions: Our findings indicate that the AI-based software can support neuroradiologists in interpreting brain TOF-MRA. A combined reading of the AI-based software and the neuroradiologist demonstrated higher reliability in identifying intracranial aneurysms as compared to reading by either neuroradiologist or software, thus improving diagnostic accuracy of the neuroradiologist. Simultaneously, reading time for the neuroradiologist was reduced by approximately one quarter. [ABSTRACT FROM AUTHOR]

Objective: To examine the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) with Sonazoid (Sonazoid-CEUS) for endometrial lesions. Methods: In this prospective and multicenter study, data were collected from 84 patients with endometrial lesions from 11 hospitals in China. All the patients received a conventional US and Sonazoid-CEUS examination. The lesion characteristics based on US and Sonazoid-CEUS imaging were collected from the case report forms. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were determined using histopathologic diagnosis as the gold standard. Results: Of the 79 patients included, 29 were diagnosed with benign lesions and 50 with endometrial carcinoma (EC). The accuracy, sensitivity, specificity, PPV, and NPV for Sonazoid-CEUS and US at differentiating EC from benign endometrial lesions were 82.2%, 94%, 62.1%, 81.0%, and 85.7%, and 79.7%, 96%, 51.7%, 92.3%, and 88.2%, respectively, with no significant differences observed for any of the values. For Sonazoid-CEUS, the best delineators of EC versus benign lesions were early enhancement and hyperenhancement (74% vs 53.3%, P = 0.029, 68% vs 45%, P < 0.001), and lesion size enlargement (76% vs 48%, P = 0.001). Despite finding no significant difference in the enhancement patterns (P =.367), a faster wash-in pattern with the contrast agent entering before the surrounding myometrium was more common in the EC vs benign cases (92% vs 48.3%). Conclusions: Sonazoid-CEUS has higher accuracy, specificity, and comparable sensitivity for differentiating EC from benign endometrial lesions compared with conventional US. It provides complementary hemodynamics information reflective of tissue vascularization, which may improve the overall diagnostic efficiency. [ABSTRACT FROM AUTHOR]

Pediatric bone injuries are traditionally diagnosed using radiography. However, ultrasonography is emerging as an alternative due to its speed and minimal invasiveness. This study assessed the diagnostic capabilities of ultrasound before radiography in a group of 186 children with suspected long bone fractures at Saint Etienne University Hospital (Saint-Priest-en-Jarez, France). Patients with open trauma and severe deformity were excluded. Ultrasonography demonstrated 88.2% sensitivity and 86.4% specificity, with better results for forearm injuries. Of the 186 cases, 162 were consistent with radiography and 24 varied. Factors influencing an accurate diagnosis included the presence of indirect signs, operator experience, and examination duration, while indirect signs often led to misinterpretation. Although ultrasound cannot completely replace radiography due to its limitations in identifying deeper fractures, this study revealed its substantial efficacy and ease, supporting its potential utility in pediatric trauma emergencies. [ABSTRACT FROM AUTHOR]

Introduction: Timely detection of dementia enables early access to dementia-specific care services and interventions. Various stakeholders brought together to refine Singapore's dementia care strategy identified a lack of a standardised cognitive screening tool and the absence of a comparative review of existing tools. We hence conducted a rapid review to evaluate the diagnostic performance of brief cognitive screening tools in identifying possible dementia among community-dwelling older adults in Singapore. Method: Brief cognitive screening tools were defined as interviews or tests administered in =5 minutes. Studies performed in Singapore on older adults =60 years, which used locally-validated comparators and reported outcomes of clinician-diagnosed dementia were included. Rapid review methodology was used in study screening and selection. Quality Assessment of Diagnostic Accuracy Studies version 2 tool was used for risk-of-bias assessment. A negative likelihood ratio (LR-) of =0.2 was defined a priori as having a moderate effect in shifting post-test probability. Results: Fourteen studies were included in qualitative synthesis: 3 studies evaluated self-/informant-based tools only, 4 evaluated performance-based measures only and 7 evaluated combination approaches. Eight-item Informant Interview to Differentiate Aging and Dementia (AD8) was the most studied self-/informant-based tool. One study found informant AD8 (iAD8) superior to self-rated AD8. Another study found iAD8 superior to Mini-Mental State Examination. Among performance-based measures, Abbreviated Mental Test, Visual Cognitive Assessment Test-Short form version 1 (VCAT-S1), VCAT-S2 and Mini-Cog had LR-<0.2. Minimal improvement of combination approaches compared to iAD8 alone was demonstrated. Conclusion: Our review suggests the limited utility of dementia screening in communities with low dementia prevalence and supports a case-finding approach instead. With a reliable informant, iAD8 alone has sufficient discriminant ability. Further research is needed to specifically assess the diagnostic ability of performance-based tools in community settings. [ABSTRACT FROM AUTHOR]

Objectives. The aim of the present study was to assess the performance of radiolabeled-PSMA PET/CT in a cohort of intermediate-risk prostate cancer (PCa) patients for initial staging. Methods. This is a retrospective, multicenter analysis of patients diagnosed with intermediate-risk PCa who were staged using radiolabeled PSMA PET/CT to evaluate the extent of the disease before initiating appropriate treatment. The study included patients from the Nuclear Medicine Units of the Humanitas group between 2021 and 2024. The change in management due to the PSMA PET/CT examination was assessed. Results. A total of 181 patients were enrolled across all three centers. Histopathological assessment from biopsy revealed that 51.4% of patients had favorable PCa, while 48.6% had unfavorable disease. PET/CT was positive for the primary lesions in all patients, but it revealed a positivity rate in 23 (12.7%) patients for nodes and distant organs, with a positivity rate of 0.21 in the unfavorable group and 0.05 in the favorable group (p < 0.005). Based on follow-up data, diagnostic accuracy was higher than 90% in both the favorable and unfavorable groups for lymph node and distant metastases. The inclusion of PSMA PET/CT in the diagnostic algorithm for patients with intermediate-risk PCa impacted patient management in 24 (13.3%) cases, based on the multidisciplinary team decision. Conclusions. PSMA PET/CT can affect the management of patients with intermediate-risk PCa in up to 13% of cases, mainly for unfavorable diseases. New imaging techniques as a first-line imaging procedure can help to plan the correct therapeutic approach in the intermediate-risk PCa group. [ABSTRACT FROM AUTHOR]

Background: Exploring a biomarker with enhanced sensitivity and specificity for tissue perfusion may facilitate the timely identification of circulatory collapse, and enable more precise resuscitation efforts. Objective: The objective of this study was to ascertain the correlation between whole blood lactate versus plasma renin concentration being a biomarker of tissue perfusion and predictor of mortality among hypotensive critically ill patients. Methods: This prospective, observational cohort study enrolled 84 hypotensive critically ill patients. Plasma renin concentration and blood lactate were measured at enrollment, 24, 48, and 72 hours. The primary outcome is the correlation between the recorded renin, lactate concentrations and mortality rate during hospitalization. Results: The mean plasma renin concentration at enrollment was 61.95 pg/ml in survivors, and 104.45 pg/ml in non-survivors (p = <0.001). The non-survivors exhibited a significant boost in plasma renin concentration after 48 and 72 hours, opposed to the survivors (112 vs 40.89, and 106.64 vs 28.85 pg/ml) respectively. There was a significant positive correlation between plasma renin, blood lactate concentrations and patient mortality (r = 0.389 & 0.601) respectively. Conclusion: Plasma renin and whole blood lactate had positive correlation to mortality, yet plasma renin revealed superior diagnostic accuracy over blood lactate for mortality prediction in hypotensive critically-ill patients. Trial registration: The protocol of this study can be obtained on ClinicalTrials.gov with the id NCT05810415. [ABSTRACT FROM AUTHOR]

Abstract Background Alanine aminotransferase (ALT) is an enzyme crucial for energy and protein metabolism in muscle cells. Despite this, its association with sarcopenia remains inadequately explored. This study aims to investigate the correlation between serum levels of ALT-related indicators (ALT activity, ALT1, ALT2, and ALT1/ALT2 ratio) and sarcopenia measures, as well as to develop a diagnostic model for sarcopenia in older individuals. Methods This retrospective study assessed 653 older adults (aged ≥ 55 years), 109 of whom were studied for the association of ALT1, ALT2, and ALT1/ALT2 ratio with sarcopenia measures. Muscle mass was measured by dual energy X-ray absorptiometry. Hand grip strength (HGS) was measured with a digital dynamometer, and physical performance was assessed through the 6-meter gait speed and the five-times sit-to-stand test (FTSST). Binary logistic regression analysis was used to evaluate associations between ALT-related indicators (ALT activity and ALT1/ALT2 ratio) and sarcopenia. The diagnostic model was developed using binary logistic regression with backward selection, and the diagnostic performance of the model was evaluated by the receiver operator characteristic curve (ROC) curve. Results Older adults with sarcopenia exhibited a lower serum ALT activity and a higher ALT1/ALT2 ratio compared to those without sarcopenia. ALT activity tertiles, but not ALT1 or ALT2 tertiles alone, correlated with HGS, gait speed, FTSST, and appendicular skeletal muscle mass index (ASMI), serving as independent protective factors for low HGS, low physical performance, low ASMI, and sarcopenia. Tertiles of the ALT1/ALT2 ratio were significantly associated with HGS and FTSST, and were proved independent risk factors for low physical performance and sarcopenia by binary logistic regression analysis. An optimal Model A (based on ALT activity) was established for sarcopenia to develop a new Logit_P1 (p

Objective: To compare the diagnostic performance between mDixon sequence and WHCA TFE sequence using SPIR for non-contrast-enhanced coronary MRA in patients with suspected coronary artery disease (CAD). Method: This prospective study recruited 45 patients who were scheduled for X-ray coronary angiography (CAG) with suspected CAD in Yantai Yuhuangding hospital. Patients underwent both 3.0T WHCA TFE using SPIR and mDixon coronary MRA examinations before undergoing CAG. Two radiologists independently assessed coronary arteries in terms of subjective image quality (on a scale of 1~5, with 5 denoting the highest image quality), vessel length, vessel diameter, and presence of significant stenoses. CAG was used as the reference standard for detecting the presence of stenoses. Vessel length and diameter were compared between sequences using paired t-tests. Subjective image quality scores were compared between sequences using Wilcoxon tests. Sensitivity, specificity, and accuracy were compared between sequences using McNemar tests. Positive and negative predictive values were compared between sequences using the joint hypotheses test. Results: Two CMRA examinations were successfully performed in 40 (88.9%) of 45 patients for analysis. The objective image quality of 3.0T mDixon assessed by both radiologists was (3.9±0.9), and the 3.0T WHCA TFE using SPIR was (3.7±0.9). The mDixon sequence exhibited higher sensitivity, specificity, accuracy, positive predictive value, and negative predictive value in per-segment analysis (78.5% vs. 66.1%, 96.5% vs. 93.8%, 91.7% vs. 86.6%, 88.6% vs. 78.9%, and 93.4% vs. 88.7%) and higher sensitivity and accuracy in per-vessel analysis (89.4% vs. 81.6% and 89.1% vs. 83.3%). Conclusion: In comparison with 3.0T WHCA TFE sequence using SPIR, mDixon demonstrated superior diagnostic performance.

Abstract Background Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality. Methods We enrolled a cohort of sixty patients who underwent DL-MRI, conventional MRI, and No-DL MRI examinations to evaluate image quality. Key metrics considered in the assessment included scan duration, overall image quality, quantitative assessments of Relative Signal-to-Noise Ratio (rSNR), Relative Contrast-to-Noise Ratio (rCNR), and diagnostic efficacy. Two experienced radiologists independently assessed image quality using a 5-point scale (5 indicating the highest quality). To gauge interobserver agreement for the assessed pathologies across image sets, we employed weighted kappa statistics. Additionally, the Wilcoxon signed rank test was employed to compare image quality and quantitative rSNR and rCNR measurements. Results Scan time was significantly reduced with DL-MRI and represented an approximate 66.5% reduction. DL-MRI consistently exhibited superior image quality in both coronal T2WI and axial T2WI when compared to both conventional MRI (p

Abstract Purpose We aimed to perform a Bayesian network meta-analysis to assess the comparative diagnostic performance of different imaging modalities in chronic pancreatitis(CP). Methods The PubMed, Embase and Cochrane Library databases were searched for relevant publications until March 2024. All studies evaluating the head-to-head diagnostic performance of imaging modalities in CP were included. Bayesian network meta-analysis was performed to compare the sensitivity and specificity between the imaging modalities. The Quality Assessment of Diagnostic Performance Studies (QUADAS-2) tool was used to evaluate the quality of studies. Results This meta-analysis incorporated 17 studies. Network meta-analytic results indicated that endoscopic ultrasonography (EUS) achieved the highest surface under the cumulative ranking (SUCRA) value at 0.86 for sensitivity. Conversely, magnetic resonance imaging (MRI) demonstrated best specificity, recording the highest SUCRA value at 0.99. Ultrasonography (US) displayed comparatively lower sensitivity than endoscopic retrograde cholangiopancreatography (ERCP) (relative risk[RR]: 0.83, 95% Confidence Interval[CI]: 0.69–0.99) and EUS (RR: 0.73, 95% CI: 0.57–0.91). MRI outperformed all other imaging modalities in terms of specificity. Conclusions It appears that EUS demonstrates higher sensitivity, while MRI exhibits higher specificity in patients with chronic pancreatitis. However, it is crucial to note that our analysis was limited to the diagnostic performance and did not evaluate the cost-effectiveness of these various imaging modalities. Consequently, further extensive studies are needed to assess the benefit-to-risk ratios comprehensively.

Haemophilia presents challenges in joint pathology assessment, prompting exploration of point-of-care ultrasonography (POC-US) as a diagnostic tool. Aims: The study aimed to assess the diagnostic performance of point-of-care ultrasonography (POC-US) compared to magnetic resonance imaging (MRI) in detecting synovial hypertrophy, cartilage abnormality, and bony abnormality among people with haemophilia (PWH) treated at Assam Medical College Hospital.

Abstract Background The contrast-enhanced US (CEUS) Bosniak classification, proposed by the European Federation for Ultrasound in Medicine and Biology (EFSUMB) in 2020, predicts malignancy in cystic renal masses (CRMs). However, intra- and inter-rater reproducibility for CEUS features has not been well investigated. Purpose To explore intra- and inter-rater agreement for US features, identify confounding features, and assess the diagnostic performance of CEUS Bosniak classification. Materials and methods This retrospective study included patients with complex CRMs who underwent CEUS examination from January 2013 to August 2023. Radiologists (3 experts and 3 novices) evaluated calcification, echogenic content, wall, septa, and internal nodules of CRMs using CEUS Bosniak classification. Intra- and inter-rater agreements were assessed using the Gwet agreement coefficient (Gwet’s AC). Linear regression identified features associated with discrepancies in Bosniak category assignment. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Results A total of 103 complex CRMs were analyzed in 103 patients (mean age, 50 ± 15 years; 66 males). Intra-rater agreement for the Bosniak category was substantial to almost perfect (Gwet’s AC 0.73–0.87). Inter-rater agreement was substantial for the Bosniak category (Gwet’s AC 0.75) and moderate to almost perfect for US features (Gwet’s AC 0.44–0.94). Nodule variation (i.e., absence vs. obtuse margin vs. acute margin) explained 84% of the variability in the Bosniak category assignment. CEUS Bosniak classification showed good diagnostic performance, with AUCs ranging from 0.78 to 0.90 for each rater. Conclusions CEUS Bosniak classification demonstrated substantial intra- and inter-rater reproducibility and good diagnostic performance in predicting the malignancy potential of CRMs. Nodule variations significantly predicted differences in Bosniak category assignments. Critical relevance statement Contrast-enhanced US Bosniak classification reliably predicts malignancy in cystic renal masses, demonstrating substantial reproducibility and diagnostic accuracy. This improves clinical decision-making and patient management. Key Points Intra- and inter-rater reproducibility for contrast-enhance US features for Bosniak classification have not been well investigated. Substantial inter-rater agreements for the Bosniak category and variable agreements for determining imaging features were found. Contrast-enhanced US Bosniak classification is reproducible and has good diagnostic performance for predicting malignancy in cystic renal masses. Graphical Abstract

Background: Diagnosing perioperative anaphylaxis (POA) is often challenging. Although a guideline recommends measuring tryptase rather than histamine, there is little evidence for this. We aimed to examine the diagnostic performance and appropriate timing of tryptase and histamine measurements for diagnosing anaphylaxis, and the association between Hypersensitivity Clinical Scoring Scheme (HCSS) scores and elevated biomarkers. Methods: We measured tryptase and histamine levels thrice: 30 min, 2 h, and at least 24 h after an anaphylactic event for patients with suspected anaphylaxis, and at the induction of general anesthesia and 30 min and 2 h after the start of surgery for control patients without a reaction. Absolute values and the magnitude and rate of change from baseline were evaluated. We determined the thresholds of tryptase and histamine levels with the best diagnostic performance and compared their performance. Results: Forty-five patients with perioperative anaphylaxis were included in this study. The control group included 30 patients with uneventful general anesthesia and 12 patients with a suspected but unconfirmed diagnosis of perioperative anaphylaxis. Comparison at the same measurement timings showed that tryptase generally had better diagnostic performance than histamine. Both showed better diagnostic performance when assessed using multiple measurements rather than a single measurement. The best diagnostic performance was seen with the percentage change in the higher tryptase value, whether measured at 30 min or 2 h after anaphylaxis onset, as compared to baseline. However, neither tryptase nor histamine levels correlated with HCSS scores. Conclusions: Overall, tryptase showed better diagnostic performance than histamine. When multiple tryptase measurements are possible, parameters calculated using two acute phase measurements and the baseline level have better diagnostic performance.

Abstract Background A new pathogen detection tool, metagenomic next-generation sequencing (mNGS), has been widely used for infection diagnosis, but the clinical and diagnostic value of mNGS in urinary tract infection (UTI) remains inconclusive. This systematic review with meta-analysis aimed to investigate the efficacy of mNGS in treating UTIs. Methods A comprehensive literature search was performed in PubMed, Web of Science, Embase, and the Cochrane Library, and eligible studies were selected based on the predetermined criteria. The quality of the included studies was assessed via the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, and the certainty of evidence (CoE) was measured by the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) score. Then, the positive detection rate (PDR), pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve of the summary receiver operating characteristic curve (AUROC) was estimated in Review Manager, Stata, and MetaDisc. Subgroup analysis, meta-regression, and sensitivity analysis were performed to reveal the potential factors that influence internal heterogeneity. Results A total of 17 studies were selected for further analysis. The PDR of mNGS was markedly greater than that of culture (odds ratio (OR) = 2.87, 95% confidence interval [CI]: 1.72–4.81, p

Background: The contrast-enhanced US (CEUS) Bosniak classification, proposed by the European Federation for Ultrasound in Medicine and Biology (EFSUMB) in 2020, predicts malignancy in cystic renal masses (CRMs). However, intra- and inter-rater reproducibility for CEUS features has not been well investigated. Purpose: To explore intra- and inter-rater agreement for US features, identify confounding features, and assess the diagnostic performance of CEUS Bosniak classification. Materials and methods: This retrospective study included patients with complex CRMs who underwent CEUS examination from January 2013 to August 2023. Radiologists (3 experts and 3 novices) evaluated calcification, echogenic content, wall, septa, and internal nodules of CRMs using CEUS Bosniak classification. Intra- and inter-rater agreements were assessed using the Gwet agreement coefficient (Gwet's AC). Linear regression identified features associated with discrepancies in Bosniak category assignment. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Results: A total of 103 complex CRMs were analyzed in 103 patients (mean age, 50 ± 15 years; 66 males). Intra-rater agreement for the Bosniak category was substantial to almost perfect (Gwet's AC 0.73–0.87). Inter-rater agreement was substantial for the Bosniak category (Gwet's AC 0.75) and moderate to almost perfect for US features (Gwet's AC 0.44–0.94). Nodule variation (i.e., absence vs. obtuse margin vs. acute margin) explained 84% of the variability in the Bosniak category assignment. CEUS Bosniak classification showed good diagnostic performance, with AUCs ranging from 0.78 to 0.90 for each rater. Conclusions: CEUS Bosniak classification demonstrated substantial intra- and inter-rater reproducibility and good diagnostic performance in predicting the malignancy potential of CRMs. Nodule variations significantly predicted differences in Bosniak category assignments. Critical relevance statement: Contrast-enhanced US Bosniak classification reliably predicts malignancy in cystic renal masses, demonstrating substantial reproducibility and diagnostic accuracy. This improves clinical decision-making and patient management. Key Points: Intra- and inter-rater reproducibility for contrast-enhance US features for Bosniak classification have not been well investigated. Substantial inter-rater agreements for the Bosniak category and variable agreements for determining imaging features were found. Contrast-enhanced US Bosniak classification is reproducible and has good diagnostic performance for predicting malignancy in cystic renal masses. [ABSTRACT FROM AUTHOR]

Acute kidney injury (AKI) constitutes a common complication associated with liver or kidney transplantation, which may significantly impact the graft condition and perioperative mortality. Current AKI diagnostic criteria based on serum creatinine (sCr) and urine output alterations are widely utilized in routine clinical practice. However, the diagnostic value of sCr may be limited by various confounding factors, including age, sex, reduced or increased muscle mass, and pre-existing chronic kidney disease (CKD). Furthermore, sCr is rather a late indicator of AKI, as its concentration tends to increase only when the severity of the injury is enough to decrease the estimated glomerular filtration rate (eGFR). Recent expertise highlights the need for novel biomarkers in post-transplantation AKI diagnosis, prediction of event-associated mortality, or evaluation of indications for renal replacement treatment (RRT). Over the last decade, the diagnostic performance of various AKI biomarkers has been assessed, among which some showed the potential to outperform sCr in AKI diagnosis. Identifying susceptible individuals, early diagnosis, and prompt intervention are crucial for successful transplantation, undisturbed graft function in long-term follow-up, and decreased mortality. However, the research on AKI biomarkers in transplantation still needs to be explored. The field lacks consistent results, rigorous study designs, and external validation. Considering the rapidly growing prevalence of CKD and cirrhosis that are associated with the transplantation at their end-stage, as well as the existing knowledge gap, the aim of this article was to provide the most up-to-date review of the studies on novel biomarkers in the diagnosis of post-transplantation AKI. [ABSTRACT FROM AUTHOR]