Assessment Of Diagnostic Performance Research Articles

Assessment of diagnostic performance and complication rate in percutaneous lung biopsy based on target nodule size.

Assessment of diagnostic performance and complication rate in percutaneous lung biopsy based on target nodule size.

Gathering Validity Evidence for a Simulation-Based Test of Otoscopy Skills.

Otoscopy is a key clinical examination used by multiple healthcare providers but training and testing of otoscopy skills remain largely uninvestigated. Simulator-based assessment of otoscopy skills exists, but evidence on its validity is scarce. In this study, we explored automated assessment and performance metrics of an otoscopy simulator through collection of validity evidence according to Messick's framework. Novices and experienced otoscopists completed a test program on the Earsi otoscopy simulator. Automated assessment of diagnostic ability and performance were compared with manual ratings of technical skills. Reliability of assessment was evaluated using Generalizability theory. Linear mixed models and correlation analysis were used to compare automated and manual assessments. Finally, we used the contrasting groups method to define a pass/fail level for the automated score. A total of 12 novices and 12 experienced otoscopists completed the study. We found an overall G-coefficient of .69 for automated assessment. The experienced otoscopists achieved a significantly higher mean automated score than the novices (59.9% (95% CI [57.3%-62.6%]) vs. 44.6% (95% CI [41.9%-47.2%]), P < .001). For the manual assessment of technical skills, there was no significant difference, nor did the automated score correlate with the manually rated score (Pearson's r = .20, P = .601). We established a pass/fail standard for the simulator's automated score of 49.3%. We explored validity evidence supporting an otoscopy simulator's automated score, demonstrating that this score mainly reflects cognitive skills. Manual assessment therefore still seems necessary at this point and external video-recording is necessary for valid assessment. To improve the reliability, the test course should include more cases to achieve a higher G-coefficient and a higher pass/fail standard should be used.

B-101 Assessing the Performance of Cerebrospinal Fluid Kappa Immunoglobulin Free Light Chain as a Diagnostic Marker for Multiple Sclerosis Using Automated Chart Review

Abstract Background Multiple sclerosis (MS) is an immune-mediated central nervous system (CNS) demyelinating disease which is diagnosed based on CNS lesions' spatial and temporal dissemination. The 2017 revised McDonald Criteria include cerebrospinal fluid (CSF) specific oligoclonal bands (OCBs) to indicate dissemination in time, but their assessment is labor-intensive and requires a paired serum sample. Kappa immunoglobulin free light chain in CSF (KCSF) has emerged as a more sensitive but less specific MS biomarker, measured from a single CSF sample. Our institution's MS testing panel uses KCSF initially to rule out MS, with reflex to OCB for positive confirmation if KCSF is borderline positive (≥0.06 mg/dL). However, manual correlation of laboratory and clinical data hinders the direct comparison of the diagnostic performance between these markers. Herein we report a retrospective assessment of KCSF and OCB diagnostic performance using automated chart review. Methods Between January 1st, 2021 and December 31st, 2022, there were 1,237 patients with simultaneously measured OCB and KCSF. CSF-specific OCBs were measured by separating CSF and serum proteins using an agarose isoelectric focusing gel with a pH gradient from 3-10 (Sebia). After transfer to nitrocellulose paper, antisera were applied to visualize IgG specific bands and quantify CSF-specific OCBs. KCSF was quantitated using nephelometry by applying free light chain antisera (Binding Site) to CSF samples using a Siemens BNII analyzer. An automated chart review process utilizing keyword matching was implemented to identify patients with MS. An initial filter phase required presence of the term “multiple sclerosis”, while a second required the presence of any of the following terms: “primary progressive,” “secondary progressive,” “relapsing remitting,” “progressive relapsing,” or “tumefactive” to identify patients with diagnosed MS. The automated method’s performance was then compared to a manual chart review of 200 randomly selected patients. Subsequently, the automated process was used to determine the MS diagnosis status of all 1,237 patients. Results Of the 200 manually reviewed patients, 44 MS diagnoses were found. The automated process correctly identified 41 of these with a resulting sensitivity and specificity of 93.18% and 95.51%, respectively. Applied to the entire cohort, the automated review identified 275 MS diagnoses. For the entire cohort, the area under the curve (AUC) for the receiver operating characteristic (ROC) curves for OCB and KCSF were 0.824 (95% confidence interval: 0.794, 0.854) and 0.808 (0.777, 0.839) respectively. Our institution’s diagnostic cutoff of ≥2 for OCB yielded a sensitivity and specificity of 74.2% (68.3%, 79.1%) and 84.9% (73.8%, 89.5%), respectively. The best combination for sensitivity and specificity for KCSF with the Youden index yielded a cutoff ≥0.0654 mg/dL (sensitivity of 79.6% [73.1%, 84.0%] and specificity of 72.4% [62.8%, 76.8%]), which is similar to previous publications. This supports the use of automated chart review and suggests the KCSF cutoff has been stable over time. Conclusions KCSF exhibits comparable MS diagnostic performance to OCB yet only requires one CSF sample and can be measured rapidly. When validated, mining unstructured data allows for test performance characterization in large patient cohorts without the need for manual chart review.

Intermanufacturer assessment of diagnostic performance of angiogenic ratio vs glycosylated fibronectin in women with suspected pre-eclampsia.

To compare the diagnostic performance of different manufacturers' immunoassays for the soluble fms-like tyrosine kinase-1 (sFlt-1)-to-placental growth factor (PlGF) ratio with that of a point-of-care test for glycosylated fibronectin (GlyFn) in women with suspected pre-eclampsia (PE). This was a prospective, single-center, double-blinded, non-interventional study of East Asian women with a singleton pregnancy who presented with hypertension with or without clinical features of PE after 20 weeks' gestation between January 2020 and March 2022. Maternal serum samples were collected at the time of presentation, and subsequent management followed the departmental protocol, based on gestational age, severity of hypertension, fetal condition and presence of severe PE features. Women diagnosed with PE at presentation were excluded. PE was diagnosed according to the 2018 International Society for the Study of Hypertension in Pregnancy classification. Levels of sFlt-1 and PlGF were measured using the Cobas e411 (Roche Diagnostics), BRAHMS KRYPTOR (ThermoFisher Scientific) and iMAGIN 1800 (Ningbo-Aucheer) platforms. GlyFn levels were measured using the Lumella™ GlyFn PoC test (Diabetomics). The predictive performance of each test to rule out PE within 7 days and rule in PE within 28 days from the date of presentation was assessed. Based on the PROGNOSIS study, a sFlt-1/PlGF ratio of ≤ 38 on the Roche platform was used to predict the absence of PE within 7 days. The sFlt-1/PlGF ratio was classified as high or low using platform-specific thresholds equivalent to a Roche sFlt-1/PlGF ratio of 38, which were derived using Passing-Bablok regression. GlyFn was categorized as high or low using two reported clinical management thresholds (263 μg/mL and 510 μg/mL). Overall, 236 women with suspected PE were included, of whom 70 (29.7%) were diagnosed with PE; 36 (51.4%) and 70 (100%) developed PE within 7 days and 28 days, respectively. Eighty-eight (37.3%) women had a sFlt-1/PlGF ratio of > 38 on the Roche platform, 79 (33.5%) women had a sFlt-1/PlGF ratio of > 55 on the KRYPTOR platform and 96 (40.7%) women had a sFlt-1/PlGF ratio of > 40 on the iMAGIN 1800 platform. Furthermore, 62 (26.3%) and four (1.7%) women had a GlyFn level of > 263 μg/mL and > 510 μg/mL, respectively. The negative predictive value (NPV) of the sFlt-1/PlGF ratio measured on the Roche, KRYPTOR and iMAGIN 1800 platforms to rule out PE within 7 days after presentation was 83.3%, 82.0% and 82.9%, respectively, while that for GlyFn > 263 μg/mL and > 510 μg/mL was 82.6% and 70.4%, respectively. The corresponding positive predictive values (PPV) to rule in PE within 28 days after presentation were 50.5%, 52.3% and 46.7%, respectively, for the sFlt-1/PlGF ratio, and 35.4% and 50.0%, respectively, for GlyFn > 263 μg/mL and > 510 μg/mL. The predictive performance of different manufacturers' assays for the sFlt-1/PlGF ratio to rule in and rule out PE were similar once standardized to a common threshold. Our findings suggest that the sFlt-1/PlGF ratio and GlyFn using a cut-off of 263 μg/mL can both be utilized to rule out PE within 7 days after assessment, with a moderate NPV. The PPV for ruling in PE within 28 days remains poor. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Patterns of Lipid Abnormalities in Obesity: A Comparative Analysis in Normoglycemic and Prediabetic Obese Individuals.

Background: Obesity is a growing global health concern, often accompanied by dyslipidemia, contributing to cardiovascular risk. Understanding the patterns of dyslipidemia in different glycemic states is crucial for targeted interventions. This study compares dyslipidemia patterns in normoglycemic and prediabetic obesity to improve clinical management strategies. Methods: The study analyzed the complete lipid profiles of 138 subjects, comparing the medians, prevalence, diagnostic performance, and risk assessment of each lipid parameter across 54 non-obese (NO), 44 normoglycemic obese (NG-OB), and 40 pre-diabetic obese (PreDM-OB) groups. Results: Elevated total cholesterol (TC) and low-density lipoprotein (LDL) were the most prevalent forms of dyslipidemia observed in obesity (45.35% and 43.53%, respectively). Stratification by glycemic status revealed that triglyceride (TG) levels were elevated in both the NG-OB and PreDM-OB groups, with a more marked increase in the latter group (73.07 mg/dL vs. 97.87 mg/dL vs. 121.8 mg/dL, respectively). Elevated LDL showed better diagnostic performance and higher odds ratios (OR) in the NG-OB group (AUC = 0.660, p = 0.006; OR = 2.78, p = 0.022). Conversely, low high-density lipoprotein (HDL) was more common and exhibited significant diagnostic performance, with higher OR values in the PreDM-OB group (AUC = 0.687, p = 0.002; OR = 3.69, p = 0.018). Importantly, all lipid ratios were elevated in obesity, with TC/HDL showing the highest predictive ability for prediabetes (AUC = 0.7491, p < 0.001). Conclusions: These findings revealed unique and common lipid abnormalities in normoglycemic and prediabetic obesity. Future research should explore the effects of targeted lipid management on obesity-associated complications.

Comparative evaluation of CT and MRI in the preoperative staging of colon cancer

The aim of this study is to compare the diagnostic performance of magnetic resonance imaging (MRI) against computed tomography (CT) in various aspects of local staging in colon cancer patients. This study was a prospective single arm diagnostic accuracy study. All consecutive adult patients with confirmed colon cancer that met the current criteria for surgical resection were considered as eligible. Diagnostic performance assessment included T (T1/T2 vs T3/T4 and < T3ab vs > T3cd) and N (N positive) staging, serosa and retroperitoneal surgical margin (RSM) involvement and extramural vascular invasion (EMVI). Imaging was based on a 3 Tesla MRI system and the evaluation of all sequences (T1, T2 and diffusion-weighted imaging-DWI series) by two independent readers. CT scan was performed in a 128 row multidetector (MD) CT scanner (slice thickness: 1 mm) with intravenous contrast. Pathology report was considered as the gold standard for local staging. Sensitivity (SE), specificity (SP), and area under the curve (AUC) were calculated for both observers. MRI displayed a higher diagnostic performance over CT in terms of T1/T2 vs T3/T4 (SE: 100% vs 83.9%, SP: 96.6% vs 81%, AUC: 0.825 vs 0.983, p < 0.001), N positive (p < 0.001) and EMVI (p = 0.023) assessment. An excellent performance of MRI was noted in the T3ab vs T3cd (CT AUCReader1: 0.636, AUCReader2: 0.55 vs MRI AUCReader1: 0.829 AUCReader2 0.846, p = 0.01) and RSM invasion diagnosis. In contrast to these, MRI did not perform well in the identification of serosa invasion. MRI had a higher diagnostic yield than CT in several local staging parameters.

Comparison of veterinarians and a deep learning tool in the diagnosis of equine ophthalmic diseases.

The aim was to compare ophthalmic diagnoses made by veterinarians to a deep learning (artificial intelligence) software tool which was developed to aid in the diagnosis of equine ophthalmic diseases. As equine ophthalmology is a very specialised field in equine medicine, the tool may be able to help in diagnosing equine ophthalmic emergencies such as uveitis. In silico tool development and assessment of diagnostic performance. A deep learning tool which was developed and trained for classification of equine ophthalmic diseases was tested with 40 photographs displaying various equine ophthalmic diseases. The same data set was shown to different groups of veterinarians (equine, small animal, mixed practice, other) using an opinion poll to compare the results and evaluate the performance of the programme. Convolutional Neural Networks (CNN) were trained on 2346 photographs of equine eyes, which were augmented to 9384 images. Two hundred and sixty-one separate unmodified images were used to evaluate the trained network. The trained deep learning tool was used on 40 photographs of equine eyes (10 healthy, 12 uveitis, 18 other diseases). An opinion poll was used to evaluate the diagnostic performance of 148 veterinarians in comparison to the software tool. The probability for the correct answer was 93% for the AI programme. Equine veterinarians answered correctly in 76%, whereas other veterinarians reached 67% probability for the correct diagnosis. Diagnosis was solely based on images of equine eyes without the possibility to evaluate the inner eye. The deep learning tool proved to be at least equivalent to veterinarians in assessing ophthalmic diseases in photographs. We therefore conclude that the software tool may be useful in detecting potential emergency cases. In this context, blindness in horses may be prevented as the horse can receive accurate treatment or can be sent to an equine hospital. Furthermore, the tool gives less experienced veterinarians the opportunity to differentiate between uveitis and other ocular anterior segment disease and to support them in their decision-making regarding treatment.

Narrative Review and Diagnostic Performance Assessment of Paired Blood Cultures in Children with Cancer and Febrile Neutropenia: An Analysis of Four Studies

Children receiving cancer treatment face a heightened risk of bloodstream infections, posing challenges in care. Accurate diagnosis is crucial, and paired blood cultures (BC) from central venous catheter (CVC) and peripheral vein (PV) are a promising diagnostic approach. This review assesses the diagnostic accuracy and clinical utility of pediatric paired BC in children with cancer. A PubMed search (2003-2023) yielded 1042 titles; four articles meeting inclusion criteria were included. Studies on diagnostic accuracy or clinical utility of pediatric paired BC in ages 0-18 were reviewed by two independent assessors. Data extraction covered study characteristics, demographics, and diagnostic parameters. Observing 825 positive paired BC with a 23.5% false-positive rate, PV exclusively detected bacteremia in 22.7%, while CVC culture exclusively detected it in 54.7%. Both methods detected bacteremia in 54.0%. Variable sensitivity, specificity, PPV, and NPV across studies necessitate nuanced interpretation. PV showed higher sensitivity, while CVC exhibited higher specificity. Method choice should align with clinical context, urgency, and potential consequences. False positives, particularly with CVC, underscore the need for cautious clinical decision-making. Personalized approaches balancing clinical and diagnostic considerations are essential. Collecting paired samples aids in avoiding false positives, reducing unnecessary interventions, but may involve causing pain.

Flexed elbow, abducted shoulder, forearm supinated (FABS) reconstruction from three-dimensional elbow MRI: diagnostic performance assessment in biceps head anatomy and pathology

To determine inter-reader analysis and diagnostic performance on digitally reconstructed virtual flexed, abducted, supinated (FABS) imaging from three-dimensional (3D) isotropic elbow magnetic resonance imaging (MRI). Six musculoskeletal radiologists independently evaluated elbow MRI images with virtual FABS reconstructions, blinded to clinical findings and final diagnoses. Each radiologist recorded a binary result as to whether the tendon was intact and if both heads were visible, along with a categorical value to the type of tear and extent of retraction in centimetres where applicable. Kappa and interclass correlation (ICC) were reported with 95% confidence intervals. Areas under the receiver operating curve (AUC) were reported. FABS reconstructions were obtained successfully in all 48 cases. With respect to tendon intactness, visibility of both heads, and type of tear, the Kappa values were 0.66 (0.53-0.78), 0.24 (0.12-0.37), and 0.55 (0.43-0.66), respectively. For the extent of retraction, the ICC was 0.85 (0.79-0.91) when including the tendons with and without retraction and 0.78 (0.61-0.91) when only including tendons with retraction. For tear versus no tear, AUC values were 0.82 (0.74-0.89) to 0.96 (0.91-1.01). Digital reconstruction of FABS positioning is feasible and allows good assessment of individual tendon head tears and retraction with high diagnostic performance.

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance.

The aim of this study was to evaluate the impact of ultra-high-resolution acquisition and deep learning reconstruction (DLR) on the image quality and diagnostic performance of T2-weighted periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) imaging of the rectum. This prospective study included 34 patients who underwent magnetic resonance imaging (MRI) for initial staging or restaging of rectal tumors. The following 4 types of oblique axial PROPELLER images perpendicular to the tumor were obtained: a standard 3-mm slice thickness with conventional reconstruction (3-CR) and DLR (3-DLR), and 1.2-mm slice thickness with CR (1.2-CR) and DLR (1.2-DLR). Three radiologists independently evaluated the image quality and tumor extent by using a 5-point scoring system. Diagnostic accuracy was evaluated in 22 patients with rectal cancer who underwent surgery after MRI without additional neoadjuvant therapy (median interval between MRI and surgery, 22 days). The signal-to-noise ratio and tissue contrast were measured on the 4 types of PROPELLER imaging. 1.2-DLR imaging showed the best sharpness, overall image quality, and rectal and lesion conspicuity for all readers ( P < 0.01). Of the assigned scores for tumor extent, extramural venous invasion (EMVI) scores showed moderate agreement across the 4 types of PROPELLER sequences in all readers (intraclass correlation coefficient, 0.60-0.71). Compared with 3-CR imaging, the number of cases with MRI-detected extramural tumor spread was significantly higher with 1.2-DLR imaging (19.0 ± 2.9 vs 23.3 ± 0.9, P = 0.03), and the number of cases with MRI-detected EMVI was significantly increased with 1.2-CR, 3-DLR, and 1.2-DLR imaging (8.0 ± 0.0 vs 9.7 ± 0.5, 11.0 ± 2.2, and 12.3 ± 1.7, respectively; P = 0.02). For the diagnosis of histopathologic extramural tumor spread, 3-CR and 1.2-CR had significantly higher specificity than 3-DLR and 1.2-DLR imaging (0.75 and 0.78 vs 0.64 and 0.58, respectively; P = 0.02), and only 1.2-CR had significantly higher accuracy than 3-CR imaging (0.83 vs 0.79, P = 0.01). The accuracy of MRI-detected EMVI with reference to pathological EMVI was significantly lower for 3-CR and 3-DLR compared with 1.2-CR (0.77 and 0.74 vs 0.85, respectively; P < 0.01), and was not significantly different between 1.2-CR and 1.2-DLR (0.85 vs 0.80). Using any pathological venous invasion as the reference standard, the accuracy of MRI-detected EMVI was significantly the highest with 1.2-DLR, followed by 1.2-CR, 3-CR, and 3-DLR (0.71 vs 0.67 vs 0.59 vs 0.56, respectively; P < 0.01). The signal-to-noise ratio was significantly highest with 3-DLR imaging ( P < 0.05). There were no significant differences in tumor-to-muscle contrast between the 4 types of PROPELLER imaging. Ultra-high-resolution PROPELLER T2-weighted imaging of the rectum combined with DLR improved image quality, increased the number of cases with MRI-detected extramural tumor spread and EMVI, but did not improve diagnostic accuracy with respect to pathology in rectal cancer, possibly because of false-positive MRI findings or false-negative pathologic findings.

Assessment of the ITER divertor bolometer diagnostic performance

The ITER bolometer diagnostic will provide measurements of the total radiation emitted from the plasma, a part of the overall energy balance. It will consist of some 550 lines of sight (LOS) of bolometer detector, bundled in multiple individual cameras, which will be located in the gaps between blanket modules on the vacuum vessel wall, in five divertor cassettes, in two upper port plugs and in one equatorial port plug (Meister et al., 2017). The LOS are optimised as much as possible with design constraints to capture the details of different plasma regions in which the intensity and local distribution of radiation will vary over a large range. This is especially true in the divertor, where up to 70 % of the total thermal exhaust power from the core will have to be radiated during burning plasma operation. This radiation will be tightly concentrated meaning that not only will tomographic reconstruction of the distribution be challenging, but the bolometer cameras themselves need to be properly designed to handle the resulting heat fluxes. This paper first presents an assessment of the photonic heat fluxes falling on bolometers in the divertor region during high performance operation (where the heat fluxes will be highest). These heat fluxes are computed using ray-tracing from radiation distributions obtained with the SOLPS (plasma boundary region) and JINTRAC (plasma core region) codes and will serve as essential input to the thermal design studies of bolometers. The same SOLPS and JINTRAC simulations are used as models for the second focus of the paper which examines how closely the radiation distribution obtained from tomographic inversion of synthetic signals from the bolometer LOS matches the model input. Some effort has also been devoted to a study of how the reconstructions are affected by loss of individual LOS.

Assessment of diagnostic performance of risk factors affecting extraprostatic extension: Role of zonal level of prostate cancer.

Extraprostatic extension (EPE) serves as a crucial marker of prostate cancer aggressiveness and independently predicts the likelihood of biochemical recurrence (BCR), exhibiting a strong correlation with the histologic severity of EPE. Therefore, this study aimed to investigate the probability of EPE along the zonal level of the prostate by measuring tumor contact length (TCL) using multiparametric magnetic resonance imaging (mpMRI). Records of 308 patients who had undergone radical prostatectomy (RP) were identified. Tumor levels in the prostate were categorized as apex, mid-gland, and base, after which the correlation between TCL measured using MRI and microscopic EPE on pathologic specimens was evaluated. Univariable and multivariable logistic regression analyses were performed to assess the association among tumor origin, index tumor diameter, and TCL measured using MRI and microscopic EPE in RP specimens. Among the 214 patients included, 45 apical cancers (21%), 87 mid-gland cancers (41%), and 82 base cancers (38%) were observed. Pathological reports revealed that 18 (40.0%) apex, 31 (35.6%) mid-gland, and 50 (61.0%) base tumors were pT3a. Multivariable analysis demonstrated that the zonal level of the tumor, especially the base level, was an independent predictive factor for EPE (P < 0.001), and the AUC value of the base tumor was 0.858. Prostate cancers arising from the base were more likely to exhibit EPE than those arising from the mid-gland and apex of the prostate gland. Therefore, identifying the origin of the zonal level of prostate cancer may help guide treatment decisions and predict clinical prognosis.

Dickkopf-1 (DKK1): A Diagnostic Marker for Hepatocellular Carcinoma (HCC) on Top of Chronic Hepatitis C Virus Related Diseases

Abstract Background Hepatocellular carcinoma (HCC) is a common form of cancer in the world and is the third leading cause of cancer-related death. More than 80% of its incidence is found in developing countries; rates are more than twice as high in men compared with women. HCC is the most common form among primary liver cancers occurring worldwide, about 70–85% of liver tumors. Aim of the Work This study was aimed to evaluate the clinical significance of serum Dickkopf-1 (DKK1) as a diagnostic and prognostic marker in hepatocellular carcinoma. Patients and Methods This was a prospective study that was conducted on 60 patients and 30 healty control subjects recruited from Al Sahel Teaching Hospital. Results Regarding the demographic data, there was no statistically significant difference found between 3 groups regarding age and sex. Tumor Size was &amp;lt; 2 cm in 10.0% of HCC patients, 2 – 3 cm in 56.7% of them &amp; &amp;gt; 5 cm in 33.3% of HCC patients. While number of tumors was Single in 33.3% of HCC patients, 2 – 3 in 30.0% &amp; Multiple masses in 36.7% of patients. PV thrombosis was reported in 30% of patients. Incidence of child score c in our study was significantly higher in HCC Group when compared with Liver Cirrhosis group. According to this study, there was Non statistically significant correlation Between DKKA1 (pg/ml) &amp; each of Age, HB, WBCs, Platelets, ALT, AST, Creat, Urea, Albumin, INR, Bilirubin and AFP in both all patients &amp; Liver Cirrhosis groups. While for HCC group, there was Non statistically significant correlation Between DKKA1(pg/ml), Age, HB, Platelets, ALT, Creat, Urea, Albumin, INR, Bilirubin and AFP, but there was statically significant Positive correlation Between DKKA1(pg/ml), WBCs and AST. Serum DKK1 was significantly higher in HCC group comparing with liver cirrhosis group and control group. According to our study, ROC curve showed that the best cut off point of DKKA1 to detect Liver Cirrhosis group was &amp;gt; 264.9 pg/ml with sensitivity of 56.67%, specificity of 86.67%, PPV of 81.0%, NPV of 66.7%. Another ROC curve showed that the best cut off point of DKKA1 to detect HCC group was found &amp;gt; 453 with sensitivity of 83.33%, specificity of 93.33%, PPV of 92.6%, NPV of 84.8%. Assessment of diagnostic performance of serum DKK1 when used in discriminating Group (HCC) from Group (Liver Cirrhosis), revealed a better diagnostic performance of DKK1) as the best ROC cut-off for DKK1 was &amp;gt; 1674.8 ng/mL, this had a diagnostic sensitivity of 50%, specificity 96.67%, positive predictive value 93.7%, negative predictive value 65.9%. Conclusion In conclusion, our study suggests that DKK-1 may be a key regulator in HCC progression, a promising potential therapeutic target for HCC. We also demonstrated that serum DDK-1 could be a useful marker for diagnosing HCC.

Pooling of six respiratory samples for the detection of SARS-CoV-2: A validation and cost study in a cohort in Lima, Peru

BackgroundThe continuous evolution of the SARS-CoV-2 pandemic has led to a high demand for diagnostic testing and major shortages in testing materials, especially in low- and middle-income countries. As an alternative to testing individual samples, pooling of respiratory samples has been suggested. Previous studies have assessed performance of pooling, mainly using nasopharyngeal samples for the detection of SARS-CoV-2, but few studies have examined the performance of pooling the more practical nasal swabs or saliva samples. ObjectiveTo evaluate the sensitivity, specificity, and potential cost reduction of pooling of nasal swab (NS) and saliva (SL) samples for detection of SARS-CoV-2 in a community-based cohort study in Lima, Peru. Study designA prospective cohort study was conducted in a community setting in San Juan de Lurigancho, Lima-Peru. NS and SL samples were collected from 132 participants twice-a-week for a 2-month period. Pools of 2 to 12 samples of the same type, from participants of the same household, were tested by RT-PCR. After pooled testing, all individual samples from positive pools and all individual samples from randomly chosen negative pools were evaluated. For assessment of diagnostic performance, pool testing results were compared with results from individual testing, which served as reference, and concordance in pooled and individual test detections was evaluated. Laboratory costs for both types of samples and testing were compared. ResultsA total of 2008 NS and 2002 SL samples were collected from 132 study participants. We tested 329 NS and 333 SL pools. The mean pool size for NS and SL pools was 6.22 (SD = 0.92) and 6.39 (SD = 1.71), respectively. Using individual testing as reference, NS pooling of 6 had a sensitivity and specificity of 94% and 100%, respectively, with kappa of 0.97 (CI 95%: 0.93–1.00). The corresponding values for SL pooling of 6 were 83%, 100%, and 0.90 (CI 95%: 0.83–0.97). Compared with individual testing, pooling resulted in a cost reduction of 74.8% for NS and 72.4% for SL samples. ConclusionsPooling easy-to-collect respiratory samples, especially NS, demonstrated very high diagnostic performance for detection of SARS-CoV-2 with substantial cost savings. This approach could be considered in large population screening programs, especially in LMIC.

Assessment of Diagnostic Performance of Dermatologists Cooperating With a Convolutional Neural Network in a Prospective Clinical Study

Studies suggest that convolutional neural networks (CNNs) perform equally to trained dermatologists in skin lesion classification tasks. Despite the approval of the first neural networks for clinical use, prospective studies demonstrating benefits of human with machine cooperation are lacking. To assess whether dermatologists benefit from cooperation with a market-approved CNN in classifying melanocytic lesions. In this prospective diagnostic 2-center study, dermatologists performed skin cancer screenings using naked-eye examination and dermoscopy. Dermatologists graded suspect melanocytic lesions by the probability of malignancy (range 0-1, threshold for malignancy ≥0.5) and indicated management decisions (no action, follow-up, excision). Next, dermoscopic images of suspect lesions were assessed by a market-approved CNN, Moleanalyzer Pro (FotoFinder Systems). The CNN malignancy scores (range 0-1, threshold for malignancy ≥0.5) were transferred to dermatologists with the request to re-evaluate lesions and revise initial decisions in consideration of CNN results. Reference diagnoses were based on histopathologic examination in 125 (54.8%) lesions or, in the case of nonexcised lesions, on clinical follow-up data and expert consensus. Data were collected from October 2020 to October 2021. Primary outcome measures were diagnostic sensitivity and specificity of dermatologists alone and dermatologists cooperating with the CNN. Accuracy and receiver operator characteristic area under the curve (ROC AUC) were considered as additional measures. A total of 22 dermatologists detected 228 suspect melanocytic lesions (190 nevi, 38 melanomas) in 188 patients (mean [range] age, 53.4 [19-91] years; 97 [51.6%] male patients). Diagnostic sensitivity and specificity significantly improved when dermatologists additionally integrated CNN results into decision-making (mean sensitivity from 84.2% [95% CI, 69.6%-92.6%] to 100.0% [95% CI, 90.8%-100.0%]; P = .03; mean specificity from 72.1% [95% CI, 65.3%-78.0%] to 83.7% [95% CI, 77.8%-88.3%]; P < .001; mean accuracy from 74.1% [95% CI, 68.1%-79.4%] to 86.4% [95% CI, 81.3%-90.3%]; P < .001; and mean ROC AUC from 0.895 [95% CI, 0.836-0.954] to 0.968 [95% CI, 0.948-0.988]; P = .005). In addition, the CNN alone achieved a comparable sensitivity, higher specificity, and higher diagnostic accuracy compared with dermatologists alone in classifying melanocytic lesions. Moreover, unnecessary excisions of benign nevi were reduced by 19.2%, from 104 (54.7%) of 190 benign nevi to 84 nevi when dermatologists cooperated with the CNN (P < .001). Most lesions were examined by dermatologists with 2 to 5 years (96, 42.1%) or less than 2 years of experience (78, 34.2%); others (54, 23.7%) were evaluated by dermatologists with more than 5 years of experience. Dermatologists with less dermoscopy experience cooperating with the CNN had the most diagnostic improvement compared with more experienced dermatologists. In this prospective diagnostic study, these findings suggest that dermatologists may improve their performance when they cooperate with the market-approved CNN and that a broader application of this human with machine approach could be beneficial for dermatologists and patients.

Establishment of reference intervals for plasma metanephrines in seated position measured by LC-MS/MS and assessment of diagnostic performance in pheochromocytoma/paraganglioma.

The use of supine reference intervals instead of the corresponding seated reference intervals for seated plasma-free metanephrines (MNs) in pheochromocytoma /paraganglioma (PPGL) screening has been controversial in recent years. Each clinical laboratory should choose the optimal sampling posture and diagnostic strategy according to local conditions. The reference population consisted of 736 cases aged 14 to 92 years old and the validation population consisted of 1068 patients aged 8 to 87 years old. Seated MNs were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and the reference intervals and diagnostic cut-off values were established and the diagnostic performance compared with reference intervals established in a supine position. There was no correlation between seated plasma MNs and age (P>0.05) and there were differences in MNs among the various disease groups (P<0.05). MNs were different in gender (P<0.0001). The upper reference limit (URL) established in this study had the same sensitivity (100%) and better specificity (94.6% vs 83.5%) compared with the published age-adjusted supine reference intervals. The proportion of suspected patients with MNs within the URL-2×URL range was lower using seated reference intervals compared to supine intervals (5.3% vs 15.7%). Using the corresponding seated reference intervals for seated plasma MNs can reduce the unnecessary re-examinations of suspected patients with slightly elevated MNs. The cut-off value established by seated plasma MNs has good diagnostic performance in PPGL. Use of seated sampling is an acceptable practice and is more convenient and economical than supine sampling.

Reliability and Diagnostic Accuracy of Radiography for the Diagnosis of Calcium Pyrophosphate Deposition: Performance of the Novel Definitions Developed by an International Multidisciplinary Working Group.

To assess the reliability and diagnostic accuracy of new radiographic imaging definitions developed by an international multidisciplinary working group for identification of calcium pyrophosphate deposition (CPPD). Patients with knee osteoarthritis scheduled for knee replacement were enrolled. Two radiologists and 2 rheumatologists twice assessed radiographic images for presence or absence of CPPD in menisci, hyaline cartilage, tendons, joint capsule, or synovial membrane, using the new definitions. In case of disagreement, a consensus decision was made and considered for the assessment of diagnostic performance. Histologic examination of postsurgical specimens under compensated polarized light microscopy was the reference standard. Prevalence-adjusted bias-adjusted kappa values were used to assess reliability, and diagnostic performance statistics were calculated. Sixty-seven patients were enrolled for the reliability study. The interobserver reliability was substantial in most of the assessed structures when considering all 4 readers (κ range 0.59-0.90), substantial to almost perfect among radiologists (κ range 0.70-0.91), and moderate to almost perfect among rheumatologists (κ range 0.46-0.88). The intraobserver reliability was substantial to almost perfect for all the observers (κ range 0.70-1). Fifty-one patients were included in the accuracy study. Radiography demonstrated an overall specificity of 92% for CPPD, but sensitivity remained low for all sites and for the overall diagnosis (54%). The new radiographic definitions of CPPD are highly specific against the gold standard of histologic diagnosis. When the described radiographic findings are present, these definitions allow for a definitive diagnosis of CPPD, rather than other calcium-containing crystal depositions; however, a negative radiographic finding does not exclude the diagnosis.

Initial Characterization of Focal Bone Lesions with Conventional Radiographs or Computed Tomography: Diagnostic Performance and Interobserver Agreement Assessment.

Objectives: To ascertain the role of CT and conventional radiographs for the initial characterization of focal bone lesions.Methods: Images from 184 patients with confirmed bone tumors included in an ethics committee-approved study were retrospectively evaluated. The reference for benign-malignant distribution was based on histological analysis and long-term follow-up. Radiographs and CT features were analyzed by 2 independent musculoskeletal radiologists blinded to the final diagnosis. Lesion margins, periosteal reaction, cortical lysis, endosteal scalloping, presence of pathologic fracture, and lesion mineralization were evaluated. Results: The benign-malignant distribution in the study population was 68.5-31.5% (126 benign and 58 malignant). In the lesions that could be seen in both radiographs and CT, the performance of these methods for the benign-malignant differentiation was similar (accuracy varying from 72.8% to 76.5%). The interobserver agreement for the overall evaluation of lesion aggressiveness was considerably increased on CT compared to radiographs (Kappa of .63 vs .22). With conventional radiographs, 18 (9.7%) and 20 (10.8%) of the lesions evaluated were not seen respectively by readers 1 and 2. Among these unseen lesions, 50%-61.1% were located in the axial skeleton. Compared to radiographs, the number of lesions with cortical lysis and endosteal scalloping was 26-34% higher with CT. Conclusion: Although radiographs remain the primary imaging tool for lesions in the peripheral skeleton, CT should be performed for axial lesions. CT imaging can assess the extent of perilesional bone lysis more precisely than radiographs with a better evaluation of lesion fracture risk.

A Standardized Approach for MRI-PDFF is Necessary in the Assessment of Diagnostic Performances of the Ultrasound-Based Hepatic Fat Quantification Tools.

The recently developed ultrasound-based hepatic fat quantification tools have the potential to be implemented in daily practice with wide acceptance due to inherited advantages of ultrasound technology. Researchers intensively focused on this topic and the accumulated evidences that support clinical usefulness of these tools. However, differences in the researcher-dependent factors of the utilized MRI-PDFF technique, the recommended reference standard, may hinder the better understanding of the diagnostic performances of these tools. Therefore, a standardized approach for MRI-PDFF technique, which is established with international consensus may be considered as important.

Performance of Machine Learning and Texture Analysis for Predicting Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer with 3T MRI.

Background: To evaluate the diagnostic performance of a Machine Learning (ML) algorithm based on Texture Analysis (TA) parameters in the prediction of Pathological Complete Response (pCR) to Neoadjuvant Chemoradiotherapy (nChRT) in Locally Advanced Rectal Cancer (LARC) patients. Methods: LARC patients were prospectively enrolled to undergo pre- and post-nChRT 3T MRI for initial loco-regional staging. TA was performed on axial T2-Weighted Images (T2-WI) to extract specific parameters, including skewness, kurtosis, entropy, and mean of positive pixels. For the assessment of TA parameter diagnostic performance, all patients underwent complete surgical resection, which served as a reference standard. ROC curve analysis was carried out to determine the discriminatory accuracy of each quantitative TA parameter to predict pCR. A ML-based decisional tree was implemented combining all TA parameters in order to improve diagnostic accuracy. Results: Forty patients were considered for final study population. Entropy, kurtosis and MPP showed statistically significant differences before and after nChRT in patients with pCR; in particular, when patients with Pathological Partial Response (pPR) and/or Pathological Non-Response (pNR) were considered, entropy and skewness showed significant differences before and after nChRT (all p < 0.05). In terms of absolute value changes, pre- and post-nChRT entropy, and kurtosis showed significant differences (0.31 ± 0.35, in pCR, −0.02 ± 1.28 in pPR/pNR, (p = 0.04); 1.87 ± 2.19, in pCR, −0.06 ± 3.78 in pPR/pNR (p = 0.0005); 107.91 ± 274.40, in pCR, −28.33 ± 202.91 in pPR/pNR, (p = 0.004), respectively). According to ROC curve analysis, pre-treatment kurtosis with an optimal cut-off value of ≤3.29 was defined as the best discriminative parameter, resulting in a sensitivity and specificity in predicting pCR of 81.5% and 61.5%, respectively. Conclusions: TA parameters extracted from T2-WI MRI images could play a key role as imaging biomarkers in the prediction of response to nChRT in LARC patients. ML algorithms can be used to efficiently combine all TA parameters in order to improve diagnostic accuracy.