Strong Diagnostic Performance Research Articles

Diagnostic Accuracy of Raman Spectroscopy Integrated With Polarized Light Microscopy for Calcium Pyrophosphate-Associated Arthritis.

We studied the performance of integrated Raman polarized light microscopy (iRPolM) for the identification of calcium pyrophosphate (CPP)-associated arthritis (CPPD). This is a diagnostic accuracy study including 400 consecutive synovial fluid samples from a single hospital in the Netherlands. Accuracy measures were calculated against polarized light microscopy (PLM) and the 2023 American College of Rheumatology (ACR)/EULAR criteria set for CPPD. The interrater reliability between iRPolM and the 2023 ACR/EULAR criteria set for CPPD was strong (κ = 0.88). The diagnostic performance of iRPolM compared to the 2023 ACR/EULAR criteria set was sensitivity 86.0% (95% confidence interval [CI] 73.3-94.2), specificity 99.1% (95% CI 97.5-99.8), positive likelihood ratio 100.33 (95% CI 32.3-311.3), negative likelihood ratio 0.14 (95% CI 0.07-0.28), positive predictive value 93.5% (95% CI 82.2-97.8), negative predictive value 98.0% (95% CI 82.2-97.8), and accuracy 97.5% (95% CI 95.5-98.8). We allowed rheumatologists to rate the certainty of their microscopic identification of CPP and found a large correspondence between iRPolM and a certain identification (κ = 0.87), whereas only 10% of the uncertain CPP identifications could be confirmed with iRPolM. We identified several novel particle types in synovial fluid analysis, including calcium carbonate crystals, deposited carotenoids, microplastics, and three types of Maltese cross birefringent objects. iRPolM can easily identify CPP crystals with a strong diagnostic performance. PLM alone is not specific enough to reliably resolve complicated cases, and the implementation of Raman spectroscopy in rheumatology practice can be of benefit to patients with suspected CPPD.

Human epididymal protein 4 and its combined detection show good diagnostic value in lung cancer: A retrospective study.

This study aimed to assess the diagnostic value of human epididymal protein 4 (HE4), a potential novel biomarker for lung cancer, and its combined detection with five other conventional biomarkers in lung cancer diagnosis and subtyping. In this retrospective study, 115 lung cancer patients, 50 patients with benign pulmonary disease, and 50 healthy controls were included. Serum HE4, progastrin-releasing peptide (ProGRP), squamous cell carcinoma (SCC) antigen, cytokeratin-19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and carcinoembryonic antigen (CEA) were analyzed using the electrochemiluminescence immunoassay and chemiluminescence immunoassay. The receiver operating characteristic curve was performed to analyze the diagnostic efficacy of individual biomarkers in identifying both lung cancer and its histologic subtypes. All six biomarkers showed significantly elevated levels in the lung cancer group compared to both benign pulmonary disease and control groups (P < 0.05). Among the biomarkers evaluated, HE4 exhibited the highest diagnostic performance for lung cancer, lung adenocarcinoma, and lung squamous cell carcinoma with area under the curve (AUC) values of 0.921, 0.891, and 0.937, respectively. ProGRP was the optimal biomarker for small cell lung cancer with an AUC of 0.973. The combination of all six biomarkers yielded the largest AUCs in the diagnosis of lung cancer subtypes (0.937 for lung adenocarcinoma, 0.998 for lung squamous cell carcinoma, and 0.985 for small cell lung cancer). Furthermore, specific combinations, such as HE4 + CEA, HE4 + SCC, and ProGRP + HE4 + NSE, showed strong diagnostic performance in lung cancer. HE4 and its combined detection held substantial clinical significance in the diagnosis of lung cancer and its histologic subtyping, especially for lung adenocarcinoma and lung squamous cell carcinoma.

Comparative study of ultrasound attenuation analysis and controlled attenuation parameter in the diagnosis and grading of liver steatosis in non-alcoholic fatty liver disease patients

PurposeTo assess the diagnostic performance of Ultrasound Attenuation Analysis (USAT) in the diagnosis and grading of hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD) using Controlled Attenuation Parameters (CAP) as a reference.Materials and methodsFrom February 13, 2023, to September 26, 2023, participants underwent CAP and USAT examinations on the same day. We used manufacturer-recommended CAP thresholds to categorize the stages of hepatic steatosis: stage 1 (mild) − 240 dB/m, stage 2 (moderate) − 265 dB/m, stage 3 (severe) − 295 dB/m. Receiver Operating Characteristic curves were employed to evaluate the diagnostic accuracy of USAT and determine the thresholds for different levels of hepatic steatosis.ResultsUsing CAP as the reference, we observed that the average USAT value increased with the severity of hepatic steatosis, and the differences in USAT values among the different hepatic steatosis groups were statistically significant (p < 0.05). There was a strong positive correlation between USAT and CAP (r = 0.674, p < 0.0001). When using CAP as the reference, the optimal cut-off values for diagnosing and predicting different levels of hepatic steatosis with USAT were as follows: the cut-off value for excluding the presence of hepatic steatosis was 0.54 dB/cm/MHz (AUC 0.96); for mild hepatic steatosis, it was 0.59 dB/cm/MHz (AUC 0.86); for moderate hepatic steatosis, it was 0.73 dB/cm/MHz (AUC 0.81); and for severe hepatic steatosis, it was 0.87 dB/cm/MHz (AUC 0.87).ConclusionUSAT exhibits strong diagnostic performance for hepatic steatosis and shows a high correlation with CAP values.

Combined Orbital and Cranial Vessel Wall Magnetic Resonance Imaging for the Assessment of Disease Activity in Giant Cell Arteritis.

Acute visual impairment is the most feared complication of giant cell arteritis (GCA) but is challenging to predict. Magnetic resonance imaging (MRI) evaluates orbital pathology not visualized by an ophthalmologic examination. This study combined orbital and cranial vessel wall MRI to assess both orbital and cranial disease activity in patients with GCA, including patients without visual symptoms. Patients with suspected active GCA who underwent orbital and cranial vessel wall MRI were included. In 14 patients, repeat imaging over 12 months assessed sensitivity to change. Clinical diagnosis of ocular or nonocular GCA was determined by a rheumatologist and/or ophthalmologist. A radiologist masked to clinical data scored MRI enhancement of structures. Sixty-four patients with suspected GCA were included: 25 (39%) received a clinical diagnosis of GCA, including 12 (19%) with ocular GCA. Orbital MRI enhancement was observed in 83% of patients with ocular GCA, 38% of patients with nonocular GCA, and 5% of patients with non-GCA. MRI had strong diagnostic performance for both any GCA and ocular GCA. Combining MRI with a funduscopic examination reached 100% sensitivity for ocular GCA. MRI enhancement significantly decreased after treatment (P < 0.01). In GCA, MRI is a sensitive tool that comprehensively evaluates multiple cranial structures, including the orbits, which are the most concerning site of pathology. Orbital enhancement in patients without visual symptoms suggests that MRI may detect at-risk subclinical ocular disease in GCA. MRI scores decreased following treatment, suggesting scores reflect inflammation. Future studies are needed to determine if MRI can identify patients at low risk for blindness who may receive less glucocorticoid therapy.

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.

Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using computed tomography (CT). In this study, we investigated the diagnostic accuracy of a new 256-row multidetector CT with a low tube-voltage single energy scan and deep-learning-image reconstruction (DLIR) in detecting abnormal late enhancement (LE) in LVM. Methods We evaluated the diagnostic performance of CT for detecting LE in LVM and compared the results with those of MRI as a reference. We also measured the ECV of the LVM on CT and compared the results with those on MRI. Patients or Materials We analyzed 50 consecutive patients who underwent cardiac CT, including a late-phase scan and MRI, within three months of suspected cardiomyopathy. All patients underwent 256-slice CT (Revolution CT Apex; GE Healthcare) with a low tube-voltage (70 kV) single energy scan and DLIR for a late-phase scan. Results In patient- and segment-based analyses, the sensitivity, specificity, and accuracy of detection of LE on CT were 94% and 85%, 100% and 95%, and 96% and 93%, respectively. The ECV of LVM per patient on CT and MRI was 33.0% ±6.2% and 35.9% ±6.1%, respectively. These findings were extremely strongly correlated, with a correlation coefficient of 0.87 (p <0.0001). The effective radiation dose on late-phase scanning was 2.4±0.9 mSv. Conclusion The diagnostic performance of 256-row multislice CT with a low tube voltage and DLIR for detecting LE and measuring ECV in LVM is credible.

The potential serum sphingolipid biomarkers for distinguishing Wilson disease

BackgroundThe diagnosis of Wilson's disease (WD) remains a challenging endeavor in clinical practice. Serum sphingolipids play a significant role in the development of liver disease. In this study, we examined the serum sphingolipid profile in patients with WD and explored the potential diagnostic utility of serum sphingolipid metabolites. These metabolites may aid in distinguishing WD patients from healthy controls and identifying those with a risk of cirrhosis. MethodsThis study consecutively enrolled 26 WD patients and 88 healthy controls. We utilized high-performance liquid chromatography–tandem mass spectrometry to analyze a panel of 88 serum sphingolipid metabolites. The data were analyzed by multivariate statistical methods. ResultsAmong the 88 sphingolipids metabolites analyzed, 17 sphingolipids were observed significant differences between WD and HC groups (all P < 0.05). Notably, five sphingolipids, namely S1P (d18:1), Cer (d18:2/21:0), SM41:2, sph(d18:1), and Cer (d18:2/22:0), each with an AUC exceeding 0.9, emerged as potential biomarkers for WD. Additionally, in the comparison between WD patients with and without cirrhosis, 24 sphingolipid metabolites exhibited significant differences (all P < 0.05). We identified Cer(d18:1/20:0), Cer(d18:2/22:0), Cer(d18:2/24:0), Cer(d18:2/20:0), and Cer(d18:2/18:0), each with an AUC exceeding 0.9, as potential serological markers for WD patients with cirrhosis. ConclusionFor enhanced clinical applicability, we propose considering Cer (d18:2/22:0) as a predictive marker applicable to both WD patients and their susceptibility to cirrhosis. This particular ceramide has exhibited strong diagnostic and predictive performance. These findings have the potential to facilitate non-invasive WD diagnosis.

Association of quantitative radiomic shape features with functional outcome after surgery for primary sporadic dorsal spinal meningiomas.

Spinal meningiomas (SM) account for 25%-46% of all primary spinal tumors and show an excellent long-term disease control in case of complete resection. Therefore, the postoperative functional outcome is of high importance. To date, reports on dorsally located SM are scarce. Moreover, the impact of radiomics shape features on the functional outcome after surgery for primary dorsal SMs has not been analyzed yet. We retrospectively performed an analysis of shape-based radiomic features in 3D slicer software and quantified the tumor volume, surface area, sphericity, surface area to volume ratio and tumor canal ratio. Subsequently, we evaluated the correlation between the radinomic parameters and the postoperative outcome according to Modified Japanese Orthopedic Association (mJOA) score. Between 2010 and 2022, we identified 24 Females and 2 Males operated on dorsal SMs in our institutional database. The most common SM localization was thoracic spine (n = 20), followed by cervical (n = 4), and lumbar (n = 2). The univariate analysis and the receiver operating characteristic (ROC) analysis showed a strong diagnostic performance of sphericity in the prediction of postoperative functional outcome based on mJOA score (AUC of 0.79, sphericity cut-of value 0.738; p = 0.01). Subsequently, the patients were divided into two groups (mJOA improved vs. mJOA stable/worsened). Patients with improved mJOA score showed significantly higher sphericity (0.79 ± 0.1 vs. 0.70 ± 1.0; p = 0.03). Finally, we divided the cohort based on sphericity (<0.738 and ≥0.738). The group with higher sphericity exhibited a significantly higher positive mJOA difference 3 months postoperatively (16.6 ± 1.4 vs. 14.8 ± 3.7; p = 0.03). In our study investigating primary sporadic dorsal SMs, we demonstrated that a higher degree of sphericity may be a positive predictor of postoperative improvement, as indicated by the mJOA score.

Pretreatment parameters associated with hemorrhagic transformation among successfully recanalized medium vessel occlusions.

Although pretreatment radiographic biomarkers are well established for hemorrhagic transformation (HT) following successful mechanical thrombectomy (MT) in large vessel occlusion (LVO) strokes, they are yet to be explored for medium vessel occlusion (MeVO) acute ischemic strokes. We aim to investigate pretreatment imaging biomarkers representative of collateral status, namely the hypoperfusion intensity ratio (HIR) and cerebral blood volume (CBV) index, and their association with HT in successfully recanalized MeVOs. A prospectively collected registry of acute ischemic stroke patients with MeVOs successfully recanalized with MT between 2019 and 2023 was retrospectively reviewed. A multivariate logistic regression for HT of any subtype was derived by combining significant univariate predictors into a forward stepwise regression with minimization of Akaike information criterion. Of 60 MeVO patients successfully recanalized with MT, HT occurred in 28.3% of patients. Independent factors for HT included: diabetes mellitus history (p = 0.0005), CBV index (p = 0.0071), and proximal versus distal occlusion location (p = 0.0062). A multivariate model with these factors had strong diagnostic performance for predicting HT (area under curve [AUC] 0.93, p < 0.001). Lower CBV indexes, distal occlusion location, and diabetes history are significantly associated with HT in MeVOs successfully recanalized with MT. Of note, HIR was not found to be significantly associated with HT.

Biomarkers for distinguishing tuberculous pleural effusion from non-tuberculosis effusion: a retrospective study

BackgroundPleural effusion (PE) is a common clinical feature that presents a diagnostic challenge for clinicians. In this retrospective study, we aimed to assess the biomarkers, ratios, and multiple indicators in serum and Pleural effusion for the differential diagnosis of tuberculous pleural effusion (TPE) from non-tuberculosis effusion (non-TPE).MethodsThe participants, who were divided into two groups: TPE and non-TPE (MPE and PPE), from Ningbo First Hospital, were incorporated in this study. The clinical and laboratory features were collected and analyzed using logistic regression analysis. Twelve biomarkers and their ratios in serum and PE were investigated for TPE versus non-TPE. Additionally, the value of multiple indicators for joint diagnosis was estimated.ResultsBiomarkers and ratios showed good diagnostic performance. The five variables including Serum ADA, IGRA, Effusion ADA, Effusion ADA/Serum ADA and Effusion LDH/Effusion ADA were identified as valuable parameters for differential diagnosis of TPE from non-TPE. The combined diagnosis of the five indexes yielded the highest diagnostic accuracy for TPE with an AUC (0.919), sensitivity (90.30%), and specificity (94.50%).ConclusionsThe biomarkers and ratios demonstrated strong diagnostic performance, and the utilization of multiple indicators for joint diagnosis can improve the diagnostic efficacy of tuberculous pleurisy.

Diagnostic potential of soluble ST2 and D-dimer for Stanford Type B aortic dissection and intramural aortic hematoma

ObjectiveType B aortic dissection (TBAD) and intramural aortic hematoma (IMH) are common manifestations of Acute Aortic Syndrome (AAS), exhibiting overlapping clinical features. The timely and accurate diagnosis and differentiation between TBAD and IMH are critical for appropriate management. Tumorigenicity 2 (sST2) and D-dimer have been shown to elevate levels in both TBAD and IMH, making them valuable as “rule-out” markers. Hence, we aimed to assess the diagnostic utility of sST2 and D-dimer in distinguishing TBAD from IMH. MethodsIn this retrospective study, we analyzed serum levels of sST2 and D-dimer in 182 AAS patients, comprising 90 TBAD cases, 92 IMH cases, and 90 non-AAS cases. Serial measurements were taken at 1 h, 6 h, 12 h, 24 h, and 72 h post-admission. Comparative analyses were conducted between TBAD and non-AAS cases, IMH and non-AAS cases, and TBAD and IMH cases. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of sST2 and D-dimer in identifying TBAD or IMH cases. ResultsBoth TBAD and IMH patients displayed elevated levels of sST2 and D-dimer compared to non-AAS cases. Notably, sST2 levels were significantly higher in TBAD patients than in IMH patients, whereas D-dimer levels exhibited moderate differences. TBAD patients tended to exhibit elevated levels of either sST2 or D-dimer, with a modest correlation between the two (Pearson correlation coefficient = 0.3614). In contrast, IMH patients showed elevations in both markers, with a positive correlation between them (Pearson correlation coefficient = 0.6814). The ROC analysis revealed that both sST2 (AUC, 0.657; 95 % CI, 0.552–0.753; cutoff value, 27.54 ng/ml) and D-dimer (AUC, 0.695; 95 % CI, 0.591–0.787, cutoff value, 1.215 ng/ml) demonstrated favorable diagnostic performance for TBAD. sST2 exhibited a sensitivity of 80.92 % and a specificity of 75.00 %, while D-dimer showed a sensitivity of 80.92 % and a specificity of 75.00 %. For the diagnosis of IMH, the combined assessment of sST2 and D-dimer (AUC, 0.674; 95 % CI, 0.599–0.768; sensitivity, 69.20 %; specificity, 80.00 %) proved effective. ConclusionsOur results indicate that both sST2 and D-dimer show diagnostic potential for TBAD. Elevated levels of either serve as an indicator of TBAD onset. However, concurrent elevation of both markers seems to be indicative of IMH. The combination of increased sST2 and D-dimer levels demonstrates strong diagnostic performance in identifying IMH cases.

Validating the Edinburgh Postnatal Depression Scale Against the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition for Use in Uganda.

The Edinburgh Postnatal Depression Scale (EPDS) is a widely acknowledged screening tool for postpartum depression (PPD) globally, but its validation in Uganda has been lacking. This study aimed to assess the EPDS's accuracy as a PPD screening tool in Uganda compared to the Mini-International Neuropsychiatric Interview (MINI 7.0.2) based on the DSM-5. This was a descriptive cross-sectional study conducted at a referral hospital and two peri-urban primary care postpartum clinics in rural southwestern Uganda. We enrolled 287 mothers aged 18 to 49 at their six-week postpartum visit. The EPDS was used for initial screening, and the MINI 7.0.2 was employed for clinical diagnosis. The study used the Runyankore-Rukiga language version of the EPDS and collected data from November 11, 2019, to June 10, 2020, with the MINI 7.0.2 as the reference standard. The overall PPD prevalence was 29.5%, as opposed to 26.5% with EPDS and MINI 7.0.2 DSM-5 criteria (p = 0.239). The EPDS demonstrated a sensitivity of 86.8%, specificity of 92.1%, positive predictive value of 80.5%, and negative predictive value of 94.9%. A cutoff score of ≥10 was found to be the most effective acceptable point after drawing the AUC of ROC and determining the most appropriate point using Youden's index. The area under the ROC curve, indicating the scale's overall performance against MINI 7.0.2, was 0.89 for Bwizibwera HCIV, 0.97 for Kinoni HCIV, and 0.84 for MRRH. In conclusion, the EPDS can effectively screen for postpartum depression in southwestern Uganda using a cutoff score of ≥10. It exhibits strong diagnostic performance in correctly identifying PPD in postpartum mothers.

Characterization of pulmonary arterial stiffness using cardiac MRI.

Pulmonary arterial stiffness (PAS) is a pathologic hallmark of all types of pulmonary hypertension (PH). Cardiac MRI (CMR), a gold-standard imaging modality for the evaluation of pulmonary flow, biventricular morphology and function has been historically reserved for the longitudinal clinical follow-up, PH phenotyping purposes, right ventricular evaluation, and research purposes. Over the last two decades, numerous indices combining invasive catheterization and non-invasive CMR have been utilized to phenotype the character and severity of PAS in different types of PH and to assess its clinically prognostic potential with encouraging results. Many recent studies have demonstrated a strong role of CMR derived PAS markers in predicting long-term clinical outcomes and improving currently gold standard risk assessment provided by the REVEAL calculator. With the utilization of a machine learning strategies, strong diagnostic and prognostic performance of CMR reported in multicenter studies, and ability to detect PH at early stages, the non-invasive assessment of PAS is on verge of routine clinical utilization. In this review, we focus on appraising important CMR studies interrogating PAS over the last 20 years, describing the benefits and limitations of different PAS indices, and their pathophysiologic relevance to pulmonary vascular remodeling. We also discuss the role of CMR and PAS in clinical surveillance and phenotyping of PH, and the long-term future goal to utilize PAS as a biomarker to aid with more targeted therapeutic management.

Systematic Assessment of Shock Severity in Postoperative Cardiac Surgery Patients

BackgroundThe Society for Cardiovascular Angiography and Interventions (SCAI) shock classification has been shown to provide robust mortality risk stratification in a variety of cardiovascular patients. ObjectivesThis study sought to evaluate the SCAI shock classification in postoperative cardiac surgery intensive care unit (CSICU) patients. MethodsThis study retrospectively analyzed 26,792 postoperative CSICU admissions at a heart center between 2012 and 2022. Patients were classified into SCAI shock stages A to E using electronic health record data. Moreover, the impact of late deterioration (LD) as an additional risk modifier was investigated. ResultsThe proportions of patients in SCAI shock stages A to E were 24.4%, 18.8%, 8.4%, 35.5%, and 12.9%, and crude hospital mortality rates were 0.4%, 0.6%, 3.3%, 4.9%, and 30.2%, respectively. Similarly, the prevalence of postoperative complications and organ dysfunction increased across SCAI shock stages. After multivariable adjustment, each higher SCAI shock stage was associated with increased hospital mortality (adjusted OR: 1.26-16.59) compared with SCAI shock stage A, as was LD (adjusted OR: 8.2). The SCAI shock classification demonstrated a strong diagnostic performance for hospital mortality (area under the receiver operating characteristic: 0.84), which noticeably increased when LD was incorporated into the model (area under the receiver operating characteristic: 0.90). ConclusionsThe SCAI shock classification effectively risk-stratifies postoperative CSICU patients for mortality, postoperative complications, and organ dysfunction. Its application could, therefore, be extended to the field of cardiac surgery as a triage tool in postoperative care and as a selection criterion in research.

Maternal body fluid lncRNAs serve as biomarkers to diagnose ventricular septal defect: from amniotic fluid to plasma.

Background: Maternal body fluids contain abundant cell-free fetal RNAs which have the potential to serve as indicators of fetal development and pathophysiological conditions. In this context, this study aimed to explore the potential diagnostic value of maternal circulating long non-coding RNAs (lncRNAs) in ventricular septal defect (VSD). Methods: The potential of lncRNAs as non-invasive prenatal biomarkers for VSD was evaluated using quantitative polymerase chain reaction (qPCR) and receiver operating characteristic (ROC) curve analysis. The biological processes and regulatory network of these lncRNAs were elucidated through bioinformatics analysis. Results: Three lncRNAs (LINC00598, LINC01551, and GATA3-AS1) were found to be consistent in both maternal plasma and amniotic fluid. These lncRNAs exhibited strong diagnostic performance for VSD, with AUC values of 0.852, 0.957, and 0.864, respectively. The bioinformatics analysis revealed the involvement of these lncRNAs in heart morphogenesis, actin cytoskeleton organization, cell cycle regulation, and protein binding through a competitive endogenous RNA (ceRNA) network at the post-transcriptional level. Conclusion: The cell-free lncRNAs present in the amniotic fluid have the potential to be released into the maternal circulation, making them promising candidates for investigating epigenetic regulation in VSD.

Development and validation of asthma risk prediction models using co-expression gene modules and machine learning methods

Asthma is a heterogeneous respiratory disease characterized by airway inflammation and obstruction. Despite recent advances, the genetic regulation of asthma pathogenesis is still largely unknown. Gene expression profiling techniques are well suited to study complex diseases including asthma. In this study, differentially expressed genes (DEGs) followed by weighted gene co-expression network analysis (WGCNA) and machine learning techniques using dataset generated from airway epithelial cells (AECs) and nasal epithelial cells (NECs) were used to identify candidate genes and pathways and to develop asthma classification and predictive models. The models were validated using bronchial epithelial cells (BECs), airway smooth muscle (ASM) and whole blood (WB) datasets. DEG and WGCNA followed by least absolute shrinkage and selection operator (LASSO) method identified 30 and 34 gene signatures and these gene signatures with support vector machine (SVM) discriminated asthmatic subjects from controls in AECs (Area under the curve: AUC = 1) and NECs (AUC = 1), respectively. We further validated AECs derived gene-signature in BECs (AUC = 0.72), ASM (AUC = 0.74) and WB (AUC = 0.66). Similarly, NECs derived gene-signature were validated in BECs (AUC = 0.75), ASM (AUC = 0.82) and WB (AUC = 0.69). Both AECs and NECs based gene-signatures showed a strong diagnostic performance with high sensitivity and specificity. Functional annotation of gene-signatures from AECs and NECs were enriched in pathways associated with IL-13, PI3K/AKT and apoptosis signaling. Several asthma related genes were prioritized including SERPINB2 and CTSC genes, which showed functional relevance in multiple tissue/cell types and related to asthma pathogenesis. Taken together, epithelium gene signature-based model could serve as robust surrogate model for hard-to-get tissues including BECs to improve the molecular etiology of asthma.

Comparison of two artificial intelligence-augmented ECG approaches: Machine learning and deep learning.

Artificial intelligence-augmented ECG (AI-ECG) refers to the application of novel AI solutions for complex ECG interpretation tasks. A broad variety of AI-ECG approaches exist, each having differing advantages and limitations relating to their creation and application. To provide illustrative comparison of two general AI-ECG modeling approaches: machine learning (ML) and deep learning (DL). Two AI-ECG algorithms were developed to carry out two separate tasks using ML and DL, respectively. ML modeling techniques were used to create algorithms designed for automatic wide QRS complex tachycardia differentiation into ventricular tachycardia and supraventricular tachycardia. A DL algorithm was formulated for the task of comprehensive 12‑lead ECG interpretation. First, we describe the ML models for WCT differentiation, which rely upon expert domain knowledge to identify and formulate ECG features (e.g., percent monophasic time-voltage area [PMonoTVA]) that enable strong diagnostic performance. Second, we describe the DL method for comprehensive 12‑lead ECG interpretation, which relies upon the independent recognition and analysis of a virtually incalculable number of ECG features from a vast collection of standard 12‑lead ECGs. We have showcased two different AI-ECG methods, namely ML and DL respectively. In doing so, we highlighted the strengths and weaknesses of each approach. It is essential for investigators to understand these differences when attempting to create and apply novel AI-ECG solutions.

VCAM-1 complements CA-125 in detecting recurrent ovarian cancer

BackgroundClose to three-quarters of ovarian cancer cases are frequently diagnosed at an advanced stage, with more than 70% of them failing to respond to primary therapy and relapsing within 5 years. There is an urgent need to identify strategies for early detection of ovarian cancer recurrence, which may lead to earlier intervention and better outcomes.MethodsA customized magnetic bead-based 8-plex immunoassay was evaluated using a Bio-Plex 200 Suspension Array System. Target protein levels were analyzed in sera from 58 patients diagnosed with advanced ovarian cancer (including 34 primary and 24 recurrent tumors) and 46 healthy controls. The clinical performance of these biomarkers was evaluated individually and in combination for their ability to detect recurrent ovarian cancer.ResultsAn 8-plex immunoassay was evaluated with high analytical performance suitable for biomarker validation studies. Logistic regression modeling selected a two-marker panel of CA-125 and VCAM-1 that improved the performance of CA-125 alone in detecting recurrent ovarian cancer (AUC: 0.813 versus 0.700). At a fixed specificity of 83%, the two-marker panel significantly improved sensitivity in separating primary from recurrent tumors (70.8% versus 37.5%, P = 0.004), demonstrating that VCAM-1 was significantly complementary to CA-125 in detecting recurrent ovarian cancer.ConclusionsA two-marker panel of CA-125 and VCAM-1 showed strong diagnostic performance and improvement over the use of CA-125 alone in detecting recurrent ovarian cancer. The experimental results warrant further clinical validation to determine their role in the early detection of recurrent ovarian cancer.

Abstract 5713: Assessing the real-world utility of cell-free microbial DNA in diagnosing early-stage lung cancer

Abstract Introduction: Links between cancer and microbes date back four millennia (Sepich-Poore et al. 2021. Science). Recently, we found that microbial DNA is detectable in tumor tissues and patient blood from many human cancer types (Poore et al. 2020. Nature). These intratumoral and bloodborne microbiomes were distinct between cancer types, between normal and malignant tissues, and present in cell-free plasma samples. However, the practical utility of cell-free microbial DNA (cf-mbDNA) as a bona fide liquid biopsy diagnostic, including its applicability in early-stage disease in treatment-naïve individuals, distinguishing histological subtypes, and discriminating against non-cancer-but-diseased patients remains unknown. Thus, we constructed an age and sex-matched cohort of &amp;gt;1000 individuals with lung cancer, lung disease, and no disease (healthy) to evaluate the utility of a cf-mbDNA-driven liquid biopsy diagnostic. Methods: Shallow shotgun metagenomic sequencing with gold-standard positive and negative controls was performed using 400 µL of patient plasma. Direct genome alignments separated human and microbial reads, and generated genome-wide binned and species-level abundances, respectively. Novel taxonomic diversity was captured by additionally performing de novo co-assemblies in tandem with tumor and blood samples from The Cancer Genome Atlas (TCGA). Multi-modal, stacked machine learning classifiers then evaluated the diagnostic performance of microbial-only and multi-species (microbial + human) information. Results: Cf-mbDNA provides strong diagnostic performance in treatment-naïve, cancer-bearing individuals versus age and sex-matched healthy controls, as early as stage I disease (AUROCs≥0.90). Furthermore, cf-mbDNA outperforms histological classification compared to human genomic information. Multi-species models paired with routinely-available clinicodemographic information provided robust discrimination of lung cancer versus lung diseases (AUROC≥0.80). Importantly, the addition of cell-free microbial information produced an integrated model surpassing the diagnostic performance of PET-CT and clinical risk models for lung nodule malignancy determination in a blinded validation cohort of Stage I lung cancer and non-cancer lung disease samples. Conclusion: Cf-mbDNA features comprise a novel class of biomarkers that are combinable with host analytes, and show promise for real-world, early-stage, lung cancer diagnosis. Citation Format: Serena Fraraccio, Stephen Wandro, Akanksha Singh-Taylor, Sandrine Miller-Montgomery, Eddie Adams, Rob Knight, Leopoldo N. Segal, Harvey I. Pass, Gregory D. Sepich-Poore. Assessing the real-world utility of cell-free microbial DNA in diagnosing early-stage lung cancer. [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 5713.

Performance and Prospects of [68Ga]Ga-FAPI PET/CT Scans in Lung Cancer.

Fibroblast activation protein (FAP) could be a promising target for tumor imaging and therapy, as it is expressed in &gt;90% of epithelial cancers. A high level of FAP-expression might be associated with worse prognosis in several cancer types, including lung cancer. FAPI binds this protein and allows for labelling to Gallium-68, as well as several therapeutic radiopharmaceuticals. As FAP is only expressed at insignificant levels in adult normal tissue, FAPI provides a highly specific tumor-marker for many epithelial cancers. In this review, current information on the use of [68Ga]Ga-FAPI PET/CT in lung cancer is presented. [68Ga]Ga-FAPI shows a high uptake (standardized uptake value = SUVmax) and tumor-to-background ratio (TBR) in primary lung cancer lesions, as well as in metastatic lesions of other tumor types located in the lung and in lung cancer metastases located throughout the body. Where a comparison was made to [18F]FDG PET/CT, [68Ga]Ga-FAPI showed a similar or higher SUVmax and TBR. In brain and bone metastases, [68Ga]Ga-FAPI PET/CT outperformed [18F]FDG PET/CT. In addition to this strong diagnostic performance, a possible prognostic value of [68Ga]Ga-FAPI PET/CT in lung cancer is proposed.

Adapted echocardiography screening methods for prevention of rheumatic heart disease in Sub-Saharan Africa: a systematic review

Echocardiography is the current gold standard used in diagnosing rheumatic heart disease and its associated sequelae, but utilization is currently limited in resource-poor settings. Decentralized diagnostic methods in these areas are crucial to improving cardiac health outcomes. A systematic review was undertaken to evaluate the diagnostic performance of adapted echocardiography screening methods in countries of sub-Saharan Africa. A literature search was conducted via the PubMed, Embase, and African Healthline databases. Studies were included in the review if they assessed the diagnostic accuracy of an adapted screening method as compared to the reference standard of hospital-based echocardiogram by trained cardiologists. Diagnostic performances of handheld echocardiography and task-shifting to non-physician roles, were assessed. For HAND techniques, the pooled sensitivity, specificity and diagnostic odds ratio was 81.2%, 91.7%, and 48.01% respectively. Task-shifting and simplified protocol diagnostic performance was also analyzed; pooled sensitivity, specificity and diagnostic OR was 74.8%, 89.5%, and 25.37% respectively. This review demonstrates strong specificity with moderate sensitivity among both methods of adapted screening. HAND methods using the standard prescribed WHO protocol had stronger diagnostic performance overall. These studies present a first step towards validating current echocardiographic screening criteria using hand-held machines and establishing training of non-physicians to conduct screening in low-resource settings.