Excellent Diagnostic Performance Research Articles

Lisfranc Injury Diagnosis: What Is the Diagnostic Reliability of New Radiographic Signs Using Three-dimensional CT?

Up to one-third of Lisfranc injuries (an injury affecting the normal stability, alignment, and congruency of the tarsometatarsal joints) are misdiagnosed. Delayed diagnosis and improper treatment may lead to long-term, irreversible sequela and functional disability. Recently, the employment of three-dimensional (3D) CT demonstrated higher diagnostic reliability, but there is limited evidence on this, and radiologic features of Lisfranc injuries when using this diagnostic modality are not well described. What is the diagnostic performance of several novel radiographic signs on 3D CT when evaluating for Lisfranc injury, namely the Mercedes sign, the peeking metatarsal sign, and the peeking cuneiform sign, and what is the interobserver and intraobserver reliability of those diagnostic signs? In this retrospective, diagnostic study, video clips of 3D CT reconstructions of 52 feet with intraoperatively confirmed Lisfranc injuries and 50 asymptomatic feet with a normal appearance of the tarsometatarsal joints, as ascertained by a subspecialty-trained foot and ankle surgeon and a musculoskeletal radiologist, were analyzed by two foot and ankle specialists and three orthopaedic residents twice each, with a washout period of 2 weeks. Among the 52 patients with intraoperative evidence of Lisfranc injury, there were 27 male patients and 25 female patients, with a median (IQR) age of 40 years (23 to 58); among the 50 controls, there were 36 male and 14 female patients, with a median age of 38 years (IQR 33 to 49). For each video clip, the presence of all three radiographic signs was documented (each sign was rated in a binary yes/no fashion). Before the evaluations, all observers underwent a short training session by the head of the foot and ankle department. Later, these reading were used to assess for the sensitivity, specificity, and area under the receiver operating characteristic curve in terms of Lisfranc diagnosis against the gold standard of intraoperative testing of tarsometatarsal joint stability. Intraoperatively, the congruency and stability of the second tarsometatarsal joint had been evaluated by direct visualization and by the insertion of a probe into the joint between the base of the second metatarsus and the medial cuneiform and twisting the probe to assess for stability. The individuals evaluating the video clips were unaware of the surgically obtained diagnosis at the time they performed their evaluations. All 3D radiographic signs that were examined had excellent diagnostic reliability in terms of sensitivity and specificity, ranging from 92% to 97% and from 92% to 93%, respectively. When assessing the association between the suggested 3D radiographic signs and Lisfranc injury diagnosis as a function of the area under the receiver operating characteristic curve, the Mercedes sign demonstrated a higher area under the curve than the other signs did (0.91 versus 0.87 versus 0.8; p < 0.001). The mean intraobserver and interobserver reliability (kappa) values were excellent for all 3D radiographic signs that were evaluated. The proposed radiographic findings demonstrated excellent diagnostic performance and were repeatable within and among observers. Three-dimensional CT radiographic signs could function as a valuable diagnostic tool for the evaluation and initial screening for Lisfranc injury in the acute injury phase because obtaining AP bilateral standing radiographs of the foot is often impractical in the acute setting. Further research and comparison with AP weightbearing radiographs of the bilateral feet may be warranted. Level III, diagnostic study.

Altered Lnc-EGFR, SNHG1, and LincRNA-Cox2 Profiles in Patients with Relapsing-Remitting Multiple Sclerosis: Impact on Disease Activity and Progression.

Relapsing-remitting multiple sclerosis (RRMS) is the most prevalent MS subtype. Ample evidence has indicated that long noncoding RNAs (lncRNAs) are crucial players in autoimmune and inflammatory disorders. This study investigated the expression of lnc-EGFR, SNHG1, and lincRNA-Cox2 in RRMS patients during active relapses and in remission. Additionally, the expression of FOXP3, a master transcription factor for regulatory T cells, and NLRP3-inflammasome-related genes were determined. Relationships between these parameters and MS activity and annualized relapse rate (ARR) were also evaluated. The study included 100 Egyptian participants: 70 RRMS patients (35 during relapse and 35 in remission) and 30 healthy controls. RRMS patients showed significant downregulation of lnc-EGFR and FOXP3 and dramatic upregulation of SNHG1, lincRNA-Cox2, NLRP3, ASC, and caspase-1 compared to controls. Lower serum TGF-β1 and elevated IL-1β levels were observed in RRMS patients. Notably, patients during relapses displayed more significant alterations than those in remission. Lnc-EGFR was positively correlated with FOXP3 and TGF-β1 and negatively correlated with ARR, SNHG1, lincRNA-Cox2, and NLRP3 inflammasome components. Meanwhile, SNHG1 and lincRNA-Cox2 were positively correlated with ARR, NLRP3, ASC, caspase-1, and IL-1β. Excellent diagnostic performance for lnc-EGFR, FOXP3, and TGF-β1 was demonstrated, while all biomarkers exhibited strong prognostic potential for predicting relapses. Finally, the differential expression of lnc-EGFR, SNHG1, and lincRNA-Cox2 in RRMS patients, especially during relapses, suggests their involvement in RRMS pathogenesis and activity. Correlation between their expression and ARR implies relationships to disease progression. Our findings also highlight their promising roles as biomarkers for RRMS.

CT Coronary Angiography and Dynamic CT Myocardial Perfusion for Detection of Cardiac Allograft Vasculopathy

BackgroundCardiac allograft vasculopathy (CAV) is a major obstacle limiting long-term graft survival. Effective noninvasive surveillance modalities reflecting both coronary artery and microvascular components of CAV are needed. ObjectivesThe authors evaluated the diagnostic performance of dynamic computed tomography–myocardial perfusion imaging (CT-MPI) and coronary computed tomography angiography (CCTA) for CAV. MethodsA total of 63 heart transplantation patients underwent combined CT-MPI and CCTA plus invasive coronary angiography (ICA) with intravascular ultrasonography (IVUS) between December 2018 and October 2021. The median interval between CT-MPI and heart transplantation was 4.3 years. Peak myocardial blood flow (MBF) of the whole myocardium (MBFglobal) and minimum MBF (MBFmin) among the 16 segments according to the American Heart Association model, except the left ventricular apex, were calculated from CT-MPI. CCTA was assessed qualitatively, and the degree of coronary artery stenosis was recorded. CAV was diagnosed based on both ICA (ISHLT criteria) and IVUS. Patients were followed up for a median time of 2.3 years after CT-MPI and a median time of 5.7 years after transplantation. ResultsAmong the 63 recipients, 35 (55.6%) had diagnoses of CAV. The median MBFglobal and MBFmin were significantly lower in patients with CAV (128.7 vs 150.4 mL/100 mL/min; P = 0.014; and 96.9 vs 122.8 mL/100 mL/min; P < 0.001, respectively). The combined use of coronary artery stenosis on CCTA and MBFmin showed the highest diagnostic performance with an area under the curve of 0.886 (sensitivity: 74.3%, specificity: 96.4%, positive predictive value: 96.3%, and negative predictive value: 75.0%). ConclusionsThe combination of CT-MPI and CCTA demonstrated excellent diagnostic performance for the detection of CAV. One-stop evaluation of the coronary artery and microvascular components involved in CAV using combined CCTA and CT-MPI may be a potent noninvasive screening method for early detection of CAV.

Cross-sectional versus longitudinal cognitive assessments for the diagnosis of symptomatic Alzheimer's disease in adults with Down syndrome.

Down syndrome (DS) is a genetic form of Alzheimer's disease (AD). However, clinical diagnosis is difficult, and experts emphasize the need for detectingintra-individual cognitive decline. To compare the performance of baseline and longitudinal neuropsychological assessments for the diagnosis of symptomatic AD in DS. Longitudinal cohort study of adults with DS. Individuals were classified as asymptomatic, prodromal AD, or AD dementia. We performed receiver operating characteristic curve analyses to compare baseline and longitudinal changes of CAMCOG-DS and mCRT. We included 562 adults with DS. Baseline assessments showed good to excellent diagnostic performance for AD dementia (AUCs between0.82 and 0.99) and prodromal AD, higher than the 1-year intra-individual cognitive decline (area under the ROC curve between0.59 and 0.79for AD dementia, lower for prodromal AD). Longer follow-ups increased the diagnostic performance of the intra-individual cognitive decline. Baseline cognitive assessment outperforms the 1-year intra-individual cognitive decline in adults with DS.

Machine and deep learning-based clinical characteristics and laboratory markers for the prediction of sarcopenia.

Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts. We developed models of sarcopenia using the baseline data from the West China Health and Aging Trend (WCHAT) study. For external validation, we used the Xiamen Aging Trend (XMAT) cohort. We compared the support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGB), and Wide and Deep (W&D) models. The area under the receiver operating curve (AUC) and accuracy (ACC) were used to evaluate the diagnostic efficiency of the models. The WCHAT cohort, which included a total of 4057 participants for the training and testing datasets, and the XMAT cohort, which consisted of 553 participants for the external validation dataset, were enrolled in this study. Among the four models, W&D had the best performance (AUC = 0.916 ± 0.006, ACC = 0.882 ± 0.006), followed by SVM (AUC =0.907 ± 0.004, ACC = 0.877 ± 0.006), XGB (AUC = 0.877 ± 0.005, ACC = 0.868 ± 0.005), and RF (AUC = 0.843 ± 0.031, ACC = 0.836 ± 0.024) in the training dataset. Meanwhile, in the testing dataset, the diagnostic efficiency of the models from large to small was W&D (AUC = 0.881, ACC = 0.862), XGB (AUC = 0.858, ACC = 0.861), RF (AUC = 0.843, ACC = 0.836), and SVM (AUC = 0.829, ACC = 0.857). In the external validation dataset, the performance of W&D (AUC = 0.970, ACC = 0.911) was the best among the four models, followed by RF (AUC = 0.830, ACC = 0.769), SVM (AUC = 0.766, ACC = 0.738), and XGB (AUC = 0.722, ACC = 0.749). The W&D model not only had excellent diagnostic performance for sarcopenia but also showed good economic efficiency and timeliness. It could be widely used in primary health care institutions or developing areas with an aging population. Chictr.org, ChiCTR 1800018895.

Gingival crevicular fluid galectin-3 and interleukin-1 beta levels in stage 3 periodontitis with grade B and C.

This study aims to evaluate GCF Galectin-3 and Interleukin-1 beta (IL-β) levels in different grades (B and C) of stage 3 periodontitis, concurrently, and also to investigate their discriminative efficiencies in periodontal diseases. A total of 80 systemically healthy and non-smoker individuals, 20 stage 3 grade C (S3GC) periodontitis 20 stage 3 grade B (S3GB) periodontitis, 20 gingivitis, and 20 periodontally healthy were enrolled. Clinical periodontal parameters were recorded and GCF Galectin-3 and IL-1β total amounts were measured by ELISA. Receiver operating characteristics curve was used for estimating the area under the curve (AUC). Galectin-3 and IL-1β were detected in all participants. Both periodontitis groups had significantly higher GCF Galectin-3 total amounts than periodontally healthy controls (p <0.05). S3GC periodontitis group had also significantly higher GCF Galectin-3 levels than gingivitis group (p <0.05). GCF IL-1β levels in periodontitis groups were higher than gingivitis and periodontally healthy groups (p <0.05). Galectin-3 exhibited an AUC value of 0.89 with 95% sensitivity to discriminate S3GC periodontitis from periodontal health, an AUC value of 0.87 with 80% sensitivity to discriminate S3GC periodontitis versus gingivitis, while an AUC value of 0.85 with 95% sensitivity to discriminate S3GB periodontitis from healthy controls. GCF Galectin-3 levels are involved in the pathogenesis of periodontal diseases. Galectin-3 showed excellent diagnostic performances to discriminate S3GB and S3GC periodontitis from periodontal health and gingivitis. The present findings suggest that GCF Galectin-3 levels may be useful in the diagnosis of the periodontal diseases.

Abstract 3301: Ultrasensitive compartment-free digital phenotyping of circulating extracellular vesicles for diagnosis of Ewing sarcoma

Abstract Ewing sarcoma (EWS) is the second most common pediatric osseous malignancy in the US. Vague symptoms and high prevalence of metastasis and recurrence present serious obstacles to its clinical management. Current diagnostic and monitoring modalities for EWS, including tissue biopsy, imaging, and cytogenetics have limitations in the early diagnosis and disease monitoring. Thus, EWS patients, as do other solid pediatric cancers, face unique challenges in the lack of non-invasive tests to aid with patient management. Extracellular vesicles (EVs), including exosomes, are emerging as a new paradigm of liquid biopsy for non-invasive cancer diagnosis and monitoring owing to their informative cargoes and imperative biological functions. However, limited progresses have been reported in the field of EWS-related EV diagnostics. To address this gap, we developed a new microfluidics-based digital immunoassay platform, termed μTUNER (microfluidic Topographic modUlation and iNtensification of Enzymatic Reaction), for ultrasensitive single-molecular analysis of EV protein biomarkers and liquid biopsy-based diagnosis of EWS. Through constructing nanoconfinements with tunable sizes, this technology affords programmable patterning and modulation of surface enzymatic reactions in a non-contact manner. Such unique capacity enables us to develop a compartment-free digital immunoassay platform which is conceptually distinct from the existing digital assays. As a proof-of-concept for clinical applications, we adapted the μTUNER digital immunoassay platform to quantitatively evaluate four exo-protein biomarkers (CD99, ENO-2, NGFR, and Ezrin) that we identified by extensive proteomics analysis of EWS cell line-derived EVs (PMID: 32821345). Using protein standards and EWS cell line-derived EVs, we demonstrated that our technology affords sensitive and quantitative detection of exo-protein biomarkers with LODs at the fg/mL level, which warrants subsequent assessment of its adaptability to clinical EWS diagnosis. EV profiling of plasma samples from adult and pediatric EWS patients (n = 16) and matched healthy controls (n = 17) reveals unique expression patterns of the four markers. These exo-protein biomarkers individually afforded excellent diagnostic performance (AUC, CD99: 0.992; ENO-2: 0.985; NGFR: 0.996; Ezrin: 0.978) to differentiate the EWS and control groups. The unweighted SUM signature of the four proteins further improves the diagnostic power to yield an AUC of 1.00. Meanwhile, the distinctive EV signature obtained from the machine learning-based analysis permits further classification of control, adult, and pediatric patients with an overall accuracy of 97%. Based on these results, we envision that our technology combined with the novel exo-protein biomarker signature can be useful clinically to improve the diagnosis of patients with Ewing sarcoma. Citation Format: Yunjie Wen, Vikalp Vishwakarma, Andrew K. Godwin, Yong Zeng. Ultrasensitive compartment-free digital phenotyping of circulating extracellular vesicles for diagnosis of Ewing sarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3301.

Evaluation of Plasma Phosphorylated Tau217 for Differentiation Between Alzheimer Disease and Frontotemporal Lobar Degeneration Subtypes Among Patients With Corticobasal Syndrome

Plasma phosphorylated tau217 (p-tau217), a biomarker of Alzheimer disease (AD), is of special interest in corticobasal syndrome (CBS) because autopsy studies have revealed AD is the driving neuropathology in up to 40% of cases. This differentiates CBS from other 4-repeat tauopathy (4RT)-associated syndromes, such as progressive supranuclear palsy Richardson syndrome (PSP-RS) and nonfluent primary progressive aphasia (nfvPPA), where underlying frontotemporal lobar degeneration (FTLD) is typically the primary neuropathology. To validate plasma p-tau217 against positron emission tomography (PET) in 4RT-associated syndromes, especially CBS. This multicohort study with 6, 12, and 24-month follow-up recruited adult participants between January 2011 and September 2020 from 8 tertiary care centers in the 4RT Neuroimaging Initiative (4RTNI). All participants with CBS (n = 113), PSP-RS (n = 121), and nfvPPA (n = 39) were included; other diagnoses were excluded due to rarity (n = 29). Individuals with PET-confirmed AD (n = 54) and PET-negative cognitively normal control individuals (n = 59) were evaluated at University of California San Francisco. Operators were blinded to the cohort. Plasma p-tau217, measured by Meso Scale Discovery electrochemiluminescence, was validated against amyloid-β (Aβ) and flortaucipir (FTP) PET. Imaging analyses used voxel-based morphometry and bayesian linear mixed-effects modeling. Clinical biomarker associations were evaluated using longitudinal mixed-effect modeling. Of 386 participants, 199 (52%) were female, and the mean (SD) age was 68 (8) years. Plasma p-tau217 was elevated in patients with CBS with positive Aβ PET results (mean [SD], 0.57 [0.43] pg/mL) or FTP PET (mean [SD], 0.75 [0.30] pg/mL) to concentrations comparable to control individuals with AD (mean [SD], 0.72 [0.37]), whereas PSP-RS and nfvPPA showed no increase relative to control. Within CBS, p-tau217 had excellent diagnostic performance with area under the receiver operating characteristic curve (AUC) for Aβ PET of 0.87 (95% CI, 0.76-0.98; P < .001) and FTP PET of 0.93 (95% CI, 0.83-1.00; P < .001). At baseline, individuals with CBS-AD (n = 12), defined by a PET-validated plasma p-tau217 cutoff 0.25 pg/mL or greater, had increased temporoparietal atrophy at baseline compared to individuals with CBS-FTLD (n = 39), whereas longitudinally, individuals with CBS-FTLD had faster brainstem atrophy rates. Individuals with CBS-FTLD also progressed more rapidly on a modified version of the PSP Rating Scale than those with CBS-AD (mean [SD], 3.5 [0.5] vs 0.8 [0.8] points/year; P = .005). In this cohort study, plasma p-tau217 had excellent diagnostic performance for identifying Aβ or FTP PET positivity within CBS with likely underlying AD pathology. Plasma P-tau217 may be a useful and inexpensive biomarker to select patients for CBS clinical trials.

Comparisons of potential values of D-dimer and the neutrophil- to-lymphocyte ratio in patients with suspected acute aortic syndrome

ObjectivesThis study aimed to investigate and compare the discriminative performance and clinical utility of D-dimer and the neutrophil-to-lymphocyte ratio (NLR) in the early differential diagnosis of acute aortic syndrome (AAS). MethodsThe consecutive patients presenting to Tianjin Chest Hospital for suspected AAS were retrospectively investigated between June 2018 and December 2021. The baseline values of D-dimer and NLR were analyzed and compared in the study population. The discriminative ability of D-dimer and NLR was illustrated and compared using the area under the receiver operating characteristic (ROC) curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Clinical utility was evaluated by means of decision curve analysis (DCA). ResultsIn the study period, a total of 697 participants suspected of having AAS were enrolled and 323 had a final diagnosis of AAS. The baseline level of NLR as well as D-dimer was higher in patients with AAS. The use of NLR showed excellent overall diagnostic performance for AAS with a comparable AUC to that of D-dimer (0.845 vs. 0.822, P > 0.05). The reclassification analyses further confirmed that NLR had better discriminative properties for AAS with a significant NRI of 66.1% and IDI of 12.4% (P < 0.001). Moreover, NLR provided higher net benefit than D-dimer as shown by DCA. Similar results were observed in subgroup analyses according to the different classes of AAS. ConclusionsNLR outperformed D-dimer with improved discriminative performance and superior clinical utility in identifying AAS. As a more readily available biomarker, NLR may be a reliable alternative to D-dimer for the screening of suspected AAS in clinical practice.

Cardiac MRI–derived Extracellular Volume Fraction versus Myocardium-to-Lumen R1 Ratio at Postcontrast T1 Mapping for Detecting Cardiac Amyloidosis

To evaluate the diagnostic performance of myocardium-to-lumen R1 (1/T1) ratio on postcontrast T1 maps for the detection of cardiac amyloidosis in a large patient sample. This retrospective study included consecutive patients who underwent MRI-derived extracellular volume fraction (MRI ECV) analysis between March 2017 and July 2021 because of known or suspected heart failure or cardiomyopathy. Pre- and postcontrast T1 maps were generated using the modified Look-Locker inversion recovery sequence. Diagnostic performances of MRI ECV and myocardium-to-lumen R1 ratio on postcontrast T1 maps (a simplified index not requiring a native T1 map and hematocrit level data) for detecting cardiac amyloidosis were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Of 352 patients (mean age, 63 years ± 16 [SD]; 235 men), 136 had cardiac amyloidosis. MRI ECV showed 89.0% (121 of 136; 95% CI: 82%, 94%) sensitivity and 98.6% (213 of 216; 95% CI: 96%, 100%) specificity for helping detect cardiac amyloidosis (cutoff value of 40% [AUC, 0.99 {95% CI: 0.97, 1.00}; P < .001]). Postcontrast myocardium-to-lumen R1 ratio showed 92.6% (126 of 136; 95% CI: 89%, 96%) sensitivity and 93.1% (201 of 216; 95% CI: 89%, 96%) specificity (cutoff value of 0.84 [AUC, 0.98 {95% CI: 0.95, 0.99}; P < .001]). There was no evidence of a difference in AUCs for each parameter (P = .10). Postcontrast myocardium-to-lumen R1 ratio showed excellent diagnostic performance comparable to that of MRI ECV in the detection of cardiac amyloidosis.Keywords: MR Imaging, Cardiac, Heart, Cardiomyopathies Supplemental material is available for this article. © RSNA, 2023.

Diagnostic performance of a novel ultrasound-based quantitative method to assess liver steatosis in histologically identified nonalcoholic fatty liver disease.

To investigate the diagnostic performance of ultrasound-guided attenuation parameter (UGAP) for the detection of hepatic steatosis in nonalcoholic fatty liver disease (NAFLD) cohorts using histopathology as the reference standard andcomparing it with that of various imaging modalities. A total of 87 subjects who underwent UGAP, controlled attenuation parameter (CAP), and magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) between December, 2020 and January, 2022 were enrolled. Of these patients, 38 patients had NAFLD. The association between UGAP and clinical and imaging parameters was assessed using Pearson's or Spearman's correlations. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the diagnostic performance. The UGAP and MRI-logPDFF demonstrated strong positive correlations (correlation coefficient= 0.704, P <0.0001). UGAP showed excellent diagnostic performance for distinguishing steatosis grade ≥1 with an AUROC of 0.821 (95% confidence interval [CI], 0.729-0.913), which was comparable to that of MRI-PDFF (0.829, 95%CI, 0.723-0.936). The AUROCs of BUSG (B-mode ultrasonography) (0.766, 95% CI, 0.767-0.856) and CAP (0.788, 95% CI, 0.684-0.891) were slightly lower than those of UGAP. The AUROCs of UGAP, MRI-PDFF, CAP, and BUSG for detecting steatosis grade ≥2 were 0.796 (95% CI, 0.616-0.975), 0.971 (95% CI, 0.936-1.000), 0.726 (95% CI, 0.561-0.891) and 0.774 (95% CI, 0.612-0.936), respectively. UGAP may be a valuable potential screening tool as a first-line assessment of liver steatosis in patients with NAFLD.

Intelligent fault diagnosis method for rolling bearing using WMNRS and LSSVM

A weighted multi-neighborhood rough set (WMNRS) algorithm is designed to resolve the issue in which the neighborhood radius must be adjusted iteratively and cannot be automatically determined in the neighborhood rough set. This algorithm combined with the least squares support vector machines (LSSVM) is used for analyzing rolling bearing condition monitoring data; consequently, an intelligent fault diagnosis method is proposed. Specifically, the time-domain and frequency-domain features are extracted from the collected vibration signals to construct an original feature set. The WMNRS algorithm is then applied to screen the primary sensitive components from the constructed feature set. Finally, an optimized LSSVM is utilized to recognize the fault types. The developed method is validated on a public dataset and a measured rolling bearing dataset. The results demonstrate that the method achieves excellent diagnostic performance. Furthermore, the proposed method has some supremacy regarding running time.

Development and validation of an online dynamic nomogram based on the atherogenic index of plasma to screen nonalcoholic fatty liver disease

BackgroundNonalcoholic fatty liver disease (NAFLD), a common liver disease worldwide, can be reversed early in life with lifestyle and medical interventions. This study aimed to develop a noninvasive tool to screen NAFLD accurately.MethodsRisk factors for NAFLD were identified using multivariate logistic regression analysis, and an online NAFLD screening nomogram was developed. The nomogram was compared with reported models (fatty liver index (FLI), atherogenic index of plasma (AIP), and hepatic steatosis index (HSI)). Nomogram performance was evaluated through internal and external validation (National Health and Nutrition Examination Survey (NHANES) database).ResultsThe nomogram was developed based on six variables. The diagnostic performance of the present nomogram for NAFLD (area under the receiver operator characteristic curve (AUROC): 0.863, 0.864, and 0.833, respectively) was superior to that of the HSI (AUROC: 0.835, 0.833, and 0.810, respectively) and AIP (AUROC: 0.782, 0.773, and 0.728, respectively) in the training, validation, and NHANES sets. Decision curve analysis and clinical impact curve analysis presented good clinical utility.ConclusionThis study establishes a new online dynamic nomogram with excellent diagnostic and clinical performance. It has the potential to be a noninvasive and convenient method for screening individuals at high risk for NAFLD.

Novel urinary protein panels for the non-invasive diagnosis of nonalcoholic fatty liver disease and fibrosis stages.

There is an unmet clinical need for non-invasive tests to diagnose nonalcoholic fatty liver disease (NAFLD) and individual fibrosis stages. We aimed to test whether urine protein panels could be used to identify NAFLD, NAFLD with fibrosis (stage F≥1), and NAFLD with significant fibrosis (stage F≥2). We collected urine samples from 100 patients with biopsy-confirmed NAFLD and 40 healthy volunteers and proteomics and bioinformatics analyses were performed in this derivation cohort. Diagnostic models were developed for detecting NAFLD (UPNAFLD model), NAFLD with fibrosis (UPfibrosis model), or NAFLD with significant fibrosis (UPsignificant fibrosis model). Subsequently, the derivation cohort was divided into training and testing sets to evaluate the efficacy of these diagnostic models. Finally, in a separate independent validation cohort of 100 patients with biopsy-confirmed NAFLD and 45 healthy controls, urinary enzyme-linked immunosorbent assay analyses were undertaken to validate the accuracy of these newly diagnostic models. The UPfibrosis model and the UPsignificant fibrosis model showed an AUROC of 0.863 (95% CI: 0.725-1.000) and 0.858 (95% CI: 0.712-1.000) in the training set; and 0.837 (95% CI: 0.711-0.963) and 0.916 (95% CI: 0.825-1.000) in the testing set, respectively. The UPNAFLD model showed excellent diagnostic performance and the area under the receiver operator characteristic curve (AUROC) exceeded 0.90 in the derivation cohort. In the independent validation cohort, the AUROC for all three of the above diagnostic models exceeded 0.80. Our newly developed models constructed from urine protein biomarkers have good accuracy for non-invasively diagnosing liver fibrosis in NAFLD.

Transcriptional landscape of myasthenia gravis revealed by weighted gene coexpression network analysis.

Background: As one of the most common autoimmune diseases, myasthenia gravis (MG) severely affects the quality of life of patients. Therefore, exploring the role of dysregulated genes between MG and healthy controls in the diagnosis of MG is beneficial to reveal new and promising diagnostic biomarkers and clinical therapeutic targets. Methods: The GSE85452 dataset was downloaded from the Gene Expression Omnibus (GEO) database and differential gene expression analysis was performed on MG and healthy control samples to identify differentially expressed genes (DEGs). The functions and pathways involved in DEGs were also explored by functional enrichment analysis. Significantly associated modular genes were identified by weighted gene co-expression network analysis (WGCNA), and MG dysregulated gene co-expression modular-based diagnostic models were constructed by gene set variance analysis (GSVA) and least absolute shrinkage and selection operator (LASSO). In addition, the effect of model genes on tumor immune infiltrating cells was assessed by CIBERSORT. Finally, the upstream regulators of MG dysregulated gene co-expression module were obtained by Pivot analysis. Results: The green module with high diagnostic performance was identified by GSVA and WGCNA. The LASSO model obtained NAPB, C5orf25 and ERICH1 genes had excellent diagnostic performance for MG. Immune cell infiltration results showed a significant negative correlation between green module scores and infiltration abundance of Macrophages M2 cells. Conclusion: In this study, a diagnostic model based on the co-expression module of MG dysregulated genes was constructed, which has good diagnostic performance and contributes to the diagnosis of MG.

DNA methylation testing for endometrial cancer detection in urine, cervicovaginal self-samples and cervical scrapes.

Endometrial cancer incidence is rising and current diagnostics often require invasive biopsy procedures. DNA methylation marker analysis of minimally- and non-invasive sample types could provide an easy-to-apply and patient-friendly alternative to determine cancer risk. Here, we compared the performance of DNA methylation markers to detect endometrial cancer in urine, cervicovaginal self-samples and clinician-taken cervical scrapes. Paired samples were collected from 103 patients diagnosed with stage I to IV endometrial cancer. Urine and self-samples were collected at home. All samples were tested for nine DNA methylation markers using quantitative methylation-specific PCR. Methylation levels measured in endometrial cancer patients were compared to unpaired samples of 317 healthy controls. Diagnostic performances were evaluated by univariable and multivariable logistic regression analysis, followed by leave-one-out cross-validation. Each methylation marker showed significantly higher methylation levels in all sample types of endometrial cancer patients compared to healthy controls (P < .01). Optimal three-marker combinations demonstrated excellent diagnostic performances with area under the receiver operating curve values of 0.95 (95% CI: 0.92-0.98), 0.94 (0.90-0.97) and 0.97 (0.96-0.99), for endometrial cancer detection in urine, self-samples and scrapes, respectively. Sensitivities ranged from 89% to 93% at specificities of 90% to 92%. Virtually equal performances were obtained after cross-validation and excellent diagnostic performances were maintained for stage I endometrial cancer detection. Our study shows the value of methylation analysis in patient-friendly sample types for endometrial cancer detection of all stages. This approach has great potential to screen patient populations at risk for endometrial cancer.

Ensemble learning-based gene signature and risk model for predicting prognosis of triple-negative breast cancer.

Although medical science has been fully developed, due to the high heterogeneity of triple-negative breast cancer (TNBC), it is still difficult to use reasonable and precise treatment. In this study, based on local optimization-feature screening and genomics screening strategy, we screened 25 feature genes. In multiple machine learning algorithms, feature genes have excellent discriminative diagnostic performance among samples composed of multiple large datasets. After screening at the single-cell level, we identified genes expressed substantially in myeloid cells (MCGs) that have a potential association with TNBC. Based on MCGs, we distinguished two types of TNBC patients who showed considerable differences in survival status and immune-related characteristics. Immune-related gene risk scores (IRGRS) were established, and their validity was verified using validation cohorts. A total of 25 feature genes were obtained, among which CXCL9, CXCL10, CCL7, SPHK1, and TREM1 were identified as the result after single-cell level analysis and screening. According to these entries, the cohort was divided into MCA and MCB subtypes, and the two subtypes had significant differences in survival status and tumor-immune microenvironment. After Lasso-Cox screening, IDO1, GNLY, IRF1, CTLA4, and CXCR6 were selected for constructing IRGRS. There were significant differences in drug sensitivity and immunotherapy sensitivity among high-IRGRS and low-IRGRS groups. We revealed the dynamic relationship between TNBC and TIME, identified a potential biomarker called Granulysin (GNLY) related to immunity, and developed a multi-process machine learning package called "MPMLearning 1.0" in Python.

Neurofilament-light chain quantification by Simoa and Ella in plasma from patients with dementia: a comparative study

Neurofilament light chains (NfL) are neuron-specific cytoskeletal proteins whose plasmatic concentrations have been explored as a clinically useful marker in several types of dementia. Plasma concentrations of NfL are extremely low, and just two assays are commercially available for their study: one based on the SiMoA technology and one based on Ella. We thus studied plasma levels of NfL with both platforms to check the correlation between them and to assess their potential in the diagnosis of neurodegeneration. Plasma NfL levels were measured on 50 subjects: 18 healthy controls, 20 Alzheimer’s disease, and 12 frontotemporal dementia patients. Ella returned plasmatic NfL levels significantly higher than SiMoA, however the results were strongly correlated (r = 0.94), and a proportional coefficient of 0.58 between the two assays was calculated. Both assays detected higher plasma NfL levels in patients with dementia than in the control group (p < 0.0001) and allowed their discrimination with excellent diagnostic performance (AUC > 0.95). No difference was found between Alzheimer’s and Frontotemporal dementia either using SiMoA or Ella. In conclusion, both the analytical platforms resulted effective in analysing plasma levels of NfL. However, the correct interpretation of results requires the precise knowledge of the assay used.

Diagnostic performances of Schistosoma haematobium and Schistosoma mansoni recombinant proteins, peptides and chimeric proteins antibody based tests. Systematic scoping review.

Traditional diagnostic tests for schistosome infections are suboptimal, particularly when the parasite burden is low. In the present review we sought to identify recombinant proteins, peptides, and chimeric proteins with potential to be used as sensitive and specific diagnostic tools for schistosomiasis. The review was guided by PRISMA-ScR guidelines, Arksey and O'Malley's framework, and guidelines from the Joanna Briggs Institute. Five databases were searched: Cochrane library, PubMed, EMBASE, PsycInfo and CINAHL, alongside preprints. Identified literature were assessed by two reviewers for inclusion. A narrative summary was used to interpret the tabulated results. Diagnostic performances were reported as specificities, sensitivities, and AUC. The AUC for S. haematobium recombinant antigens ranged from 0.65 to 0.98, and 0.69 to 0.96 for urine IgG ELISA. S. mansoni recombinant antigens had sensitivities ranging from 65.3% to 100% and specificities ranging from 57.4% to 100%. Except for 4 peptides which had poor diagnostic performances, most peptides had sensitivities ranging from 67.71% to 96.15% and specificities ranging from 69.23% to 100%. S. mansoni chimeric protein was reported to have a sensitivity of 86.8% and a specificity of 94.2%. The tetraspanin CD63 antigen had the best diagnostic performance for S. haematobium. The tetraspanin CD63 antigen Serum IgG POC-ICTs had a sensitivity of 89% and a specificity of 100%. Peptide Smp_150390.1 (216-230) serum based IgG ELISA had the best diagnostic performance for S. mansoni with a sensitivity of 96.15% and a specificity of 100%. Peptides were reported to demonstrate good to excellent diagnostic performances. S. mansoni multi-peptide chimeric protein further improved the diagnostic accuracy of synthetic peptides. Together with the advantages associated with urine sampling technique, we recommend development of multi-peptide chimeric proteins urine based point of care tools.

Fetal left-atrial posterior-space-to-diagonal ratio at 17-37 weeks' gestation for prediction of total anomalous pulmonary venous connection.

To develop normative data for the left-atrial posterior-space-to-diagonal (LAPSD) ratio and post-left atrium space (PLAS) index in fetuses from 17 to 37 weeks' gestation, and determine the optimal cut-offs of the LAPSD ratio and PLAS index to discriminate between normal fetuses and those with total anomalous pulmonary venous connection (TAPVC). This was a prospective cross-sectional assessment of 428 structurally normal fetuses between 17 and 37 weeks' gestation and a retrospective study of 27 TAPVC fetuses. The fetal LAPSD ratio was calculated by dividing the left atrium-descending aorta distance (LDD) by the left atrial diagonal diameter (LA). The PLAS index was calculated as the ratio of the LDD to the descending aorta diameter (DA). Pearson's correlation analysis was used to examine the correlation of cardiac parameters with gestational age (GA) and fetal somatic growth. The PLAS index and LAPSD ratio were compared between the normal and TAPVC groups to assess their usefulness in the prenatal diagnosis of TAPVC. LDD, LA and DA measures showed moderate to strong positive correlation, whereas both the LAPSD ratio and PLAS index showed a slight decrease with increasing GA and biometric variables. The fetal LAPSD ratio and PLAS index in TAPVC cases were significantly greater compared with those of fetuses with a normal heart (both P < 0.001). There were no significant differences in the PLAS index and LAPSD ratio between the isolated and complex TAPVC groups (both P = 1). No significant associations of the PLAS index and LAPSD ratio with fetal gender, four-chamber view type (apical, basal or lateral) or TAPVC type were found. Using values of ≥ 0.35 for the LAPSD ratio and of ≥ 1 for the PLAS index exhibited similar excellent diagnostic performance, with a sensitivity of 100% and specificity of 97.0% or 95.1% for detecting TAPVC. Our study demonstrates that the LAPSD ratio is a practical and effective screening tool for diagnosing fetal TAPVC, similar to the PLAS index. Incorporating these parameters into routine cardiac scanning may enhance the prenatal detection of TAPVC. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.