Significant Discrimination Research Articles

Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma

ObjectiveTo evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall survival (OS) in patients with early stage hepatocellular carcinoma (HCC) receiving surgical resection. MethodsAll 283 eligible patients were included retrospectively between January 2008 and December 2015, and assigned into the training cohort (n = 198) and the testing cohort (n = 85). We extracted radiomics features via handcrafted radiomics analysis manually and DL analysis of pretrained convolutional neural networks via transfer learning automatically. Support vector machine was adopted as the classifier. A clinical-radiological model for MVI status integrated significant clinical features and the radiological signature generated from the radiological model with the optimal area under the receiver operating characteristics curve (AUC) in the testing cohort. Otherwise, DL-based prognostic models were constructed in prediction of recurrence and mortality via Cox proportional hazard analysis. ResultsThe clinical-radiological model for MVI represented an AUC of 0.909, accuracy of 96.47%, sensitivity of 90.91%, specificity of 97.30%, positive predictive value of 83.33%, and negative predictive value of 98.63% in the testing cohort. The clinical-radiological models for identification of RFS and OS outperformed prediction performance of the clinical model or the DL signature alone. The DL-based integrated model for prognostication showed great predictive value with significant classification and discrimination abilities after validation. ConclusionsThe integrated DL-based radiomics models achieved accurate preoperative prediction of MVI status, and might facilitate predicting tumor recurrence and mortality in order to optimize clinical decisions for patients with early stage HCC.

Abstract 12915: Machine Learning Models Show That Age, Functional Status, and TNF-α Accurately Predicts Multimorbidity in Acute Coronary Syndrome

Introduction: Increasing prevalence of multimorbidity (>2 conditions) put individuals, especially older adults, at increased risk for acute coronary syndrome (ACS). Machine learning techniques provide an opportunity to identify clinical factors associated with multimorbidity that may aid in identifying subgroups of multimorbid patients that are at higher risk for ACS. Our primary objective was to use machine learning techniques to identify factors associated multimorbidity in individuals presenting to the emergency department (ED) for potential ACS. Hypothesis: Markers of chronologic and physiologic aging are associated with multimorbidity and vary by functional status and inflammatory profiles. Methods: This was a secondary analysis of data collected from a large multi-site study aimed at characterizing sex differences in symptoms suggestive of ACS in the ED. Variables of interests were measured with the Charlson Comorbidity Index, the Duke Activity Status Index, and serum cytokines (TNF-α, IL-6, and IL-18). A logistic regression model was applied to a sample of 414 patients utilizing a 70/30 test/train split to determine if biomarkers, functional status, sex, and age were associated with multimorbidity. Results: Patients were predominantly male (62.5%), white (73.0%), and had a mean age of 58.9 years. The accuracy of the model in predicting multimorbidity was 86.8% in the training set (n=290). In validation testing, accuracy was 73.0% (n=124). Functional status (OR .960, 95% CI .94-.206, p<0.000), age (OR 1.10, 95% CI 1.04-1.10, p<0.000), and TNF- α (OR 2.21, 95% CI 1.17-4.45, p<0.000), were associated with multimorbidity. The overall model was significant with a χ 2 (286, N=71.1) = 6, p>0.05. A responder operator curve was run on the individual variables and age, functional status, and TNF- α and showed significant discrimination levels (c-statistic 0.74, 0.73, and 0.65, respectively). Conclusions: Multimorbidity increases the risk for ACS. TNF-α, functional status, and age improved models of ACS risk stratification in a heterogeneous sample of multimorbid patients. Machine learning methodologies exhibit utility in identifying potential clinical markers of multimorbidity.

Hiring discrimination on the basis of skin colour? A correspondence test in Switzerland

ABSTRACT With the rise of the Black Lives Matter movement in 2020, the situation of Black people in many Western countries has come under closer scrutiny and ethnic discrimination has been brought to the forefront. Little is known about hiring discrimination against Blacks in many European countries. In a correspondence test in the Swiss labour market, we sent fictitious paired applications by candidates of Swiss (ostensibly White) and Cameroonian descent (ostensibly Black) in response to 354 adverts for sales assistants and electricians. We report significant discrimination against Black job seekers, who must send around 30 per cent more applications than White candidates in order to be invited to a job interview. The level of discrimination is substantively equivalent to results for applicants with a Kosovo-Albanian name that were included in previous correspondence tests in Switzerland. This suggests that in the Swiss case there is on average no additional penalty for skin colour. Explorations, however, reveal significant differences in discrimination rates between urban and rural settings, opening new avenues for understanding why ethnic and racial discrimination vary across geographical contexts.

Prognostic value of depressed cardiac index after STEMI: a phase-contrast magnetic resonance study.

An invasively measured cardiac index (CI) of ≤2.2 L/min/m2 is one of the strongest prognostic indicators after ST-elevation myocardial infarction (STEMI), however, knowledge is mainly based on invasive evaluations performed in the pre-stent era. Velocity-encoded phase-contrast cardiac magnetic resonance (PC-CMR) allows non-invasive determination of CI. In this prospective study, CMR was performed in 406 stable and contemporarily revascularized patients a median of 3 days after STEMI. Forward stroke volume was assessed at the level of the ascending aorta by PC-CMR. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) were determined by cine CMR. Major adverse cardiac events (MACE) were defined as the composite of death, myocardial infarction, or hospitalization for heart failure. Median CI was 2.52 L/min/m2 and 27% of patients had ≤2.2 L/min/m2. Median LVEF was 53% and median GLS was -12.2%. During a median follow-up of 14.2 [95% confidence interval (95% CI) 13.6-14.7] months, 41 patients (10.1%) experienced a MACE. A depressed CI was significantly associated with MACE after adjustment for LVEF, GLS, Thrombolysis in Myocardial Infarction (TIMI) risk score, and infarct size [hazard ratio = 3.15 (95% CI 1.53-6.47); P = 0.002] and led to significant discrimination improvement [net reclassification improvement 0.61 (95% CI 0.25-0.97); P < 0.001]. A CI of 2.2 L/min/m2 or less as measured by PC-CMR was present in 27% of clinically stable patients after STEMI and strongly and independently predicted medium-term MACE. The prognostic value of a depressed CI was superior and incremental to LVEF, GLS, TIMI risk score, and infarct size.

Working With Environmental Noise and Noise-Cancelation: A Workload Assessment With EEG and Subjective Measures.

As working and learning environments become open and flexible, people are also potentially surrounded by ambient noise, which causes an increase in mental workload. The present study uses electroencephalogram (EEG) and subjective measures to investigate if noise-canceling technologies can fade out external distractions and free up mental resources. Therefore, participants had to solve spoken arithmetic tasks that were read out via headphones in three sound environments: a quiet environment (no noise), a noisy environment (noise), and a noisy environment but with active noise-canceling headphones (noise-canceling). Our results of brain activity partially confirm an assumed lower mental load in no noise and noise-canceling compared to noise test condition. The mean P300 activation at Cz resulted in a significant differentiation between the no noise and the other two test conditions. Subjective data indicate an improved situation for the participants when using the noise-canceling technology compared to normal headphones but shows no significant discrimination. The present results provide a foundation for further investigations into the relationship between noise-canceling technology and mental workload. Additionally, we give recommendations for an adaptation of the test design for future studies.

Working With Environmental Noise and Noise-Cancelation: A Workload Assessment With EEG and Subjective Measures.

As working and learning environments become open and flexible, people are also potentially surrounded by ambient noise, which causes an increase in mental workload. The present study uses electroencephalogram (EEG) and subjective measures to investigate if noise-canceling technologies can fade out external distractions and free up mental resources. Therefore, participants had to solve spoken arithmetic tasks that were read out via headphones in three sound environments: a quiet environment (no noise), a noisy environment (noise), and a noisy environment but with active noise-canceling headphones (noise-canceling). Our results of brain activity partially confirm an assumed lower mental load in no noise and noise-canceling compared to noise test condition. The mean P300 activation at Cz resulted in a significant differentiation between the no noise and the other two test conditions. Subjective data indicate an improved situation for the participants when using the noise-canceling technology compared to “normal” headphones but shows no significant discrimination. The present results provide a foundation for further investigations into the relationship between noise-canceling technology and mental workload. Additionally, we give recommendations for an adaptation of the test design for future studies.

Alterations in Glycerolipid and Fatty Acid Metabolic Pathways in Alzheimer's Disease Identified by Urinary Metabolic Profiling: A Pilot Study.

An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) is needed. Evidence suggests that metabolic dysfunction underlies the pathophysiology of AD. While urine is a non-invasively collectable biofluid and a good source for metabolomics analysis, it is not yet widely used for this purpose. This small-scale pilot study aimed to examine whether the metabolic profile of urine from AD patients reflects the metabolic dysfunction reported to underlie AD pathology, and to identify metabolites that could distinguish AD patients from cognitively healthy controls. Spot urine of 18 AD patients (AD group) and 18 age- and sex-matched, cognitively normal controls (control group) were analyzed by mass spectrometry (MS). Capillary electrophoresis time-of-flight MS and liquid chromatography–Fourier transform MS were used to cover a larger range of molecules with ionic as well as lipid characteristics. A total of 304 ionic molecules and 81 lipid compounds of 12 lipid classes were identified. Of these, 26 molecules showed significantly different relative concentrations between the AD and control groups (Wilcoxon's rank-sum test). Moreover, orthogonal partial least-squares discriminant analysis revealed significant discrimination between the two groups. Pathway searches using the KEGG database, and pathway enrichment and topology analysis using Metaboanalyst software, suggested alterations in molecules relevant to pathways of glycerolipid and glycerophospholipid metabolism, thermogenesis, and caffeine metabolism in AD patients. Further studies of urinary metabolites will contribute to the early detection of AD and understanding of its pathogenesis.

The Combined Measurement of Pelvic Organ Mobility and Hiatus Area Improves the Sensitivity of Transperineal Ultrasound When Detecting Pelvic Organ Prolapse.

Objective: To evaluate whether the combined measurement of pelvic organ mobility and levator hiatus area improves the sensitivity of transperineal ultrasound (the index test) for diagnosing pelvic organ prolapse (POP).Methods: We retrospectively recruited women who had been examined in a tertiary gynecological center for symptoms of lower urinary tract incontinence and/or POP between January 2017 and June 2018. We excluded patients who had undergone hysterectomy previously or those who had received corrective surgery. All subjects underwent a standardized interview, POP quantification (POP-Q) examination (a reference standard for patients and controls), and ultrasound measurements of the levator hiatus area at rest (rHA), on contraction (cHA), and on Valsalva (vHA). We also determined the mobility of the bladder neck (BNM), cervix (CM), and rectum ampulla (RAM). Receiver operating characteristic (ROC) curve analyses were performed to determine cut-off values for diagnosis. Diagnostic performance was assessed by sensitivity, specificity, and area under curve (AUC).Results: A total of 343 women were eligible for analysis, including 247 POP patients (stage 2–3 by POP-Q) and 96 controls. Compared with controls, POP cases had significantly higher values for rHA, vHA, cHA, BNM, CM, and RAM. Each parameter was identified as a significant discriminator for POP and controls, as determined by ROC curve analysis, although the cut-off value varied slightly between different parameters. The combination of rHA, vHA, and cHA (with any HA that was ≥ the cut-off) improved the sensitivity from 64–89 to 89–93%. The combination of pelvic organ mobility with rHA, vHA, and cHA, further increased the sensitivity from 89–93 to 95–97%.Conclusion: The combination of levator hiatus area and pelvic organ mobility improved the sensitivity of transperineal ultrasound in the diagnosis of POP, whether used as a frontline test to assist POP-Q grading or to monitor the effect of pelvic floor exercise programs.

Valid and Reliable Assessment of Upper Respiratory Tract Specimen Collection Skills during the COVID-19 Pandemic.

Proper specimen collection is the most important step to ensure accurate testing for the coronavirus disease 2019 (COVID-19) and other infectious diseases. Assessment of healthcare workers’ upper respiratory tract specimen collection skills is needed to ensure samples of high-quality clinical specimens for COVID-19 testing. This study explored the validity evidence for a theoretical MCQ-test and checklists developed for nasopharyngeal (NPS) and oropharyngeal (OPS) specimen collection skills assessment. We found good inter-item reliability (Cronbach’s alpha = 0.76) for the items of the MCQ-test and high inter-rater reliability using the checklist for the assessment of OPS and NPS skills on 0.86 and 0.87, respectively. The MCQ scores were significantly different between experts (mean 98%) and novices (mean 66%), p < 0.001, and a pass/fail score of 91% was established. We found a significant discrimination between checklist scores of experts (mean 95% score for OPS and 89% for NPS) and novices (mean 50% score for OPS and 36% for NPS), p < 0.001, and a pass/fail score was established of 76% for OPS and 61% for NPS. Further, the results also demonstrated that a group of non-healthcare educated workers can perform upper respiratory tract specimen collection comparably to experts after a short and focused simulation-based training session. This study, therefore, provides validity evidence for the use of a theoretical and practical test for upper respiratory specimens’ collection skills that can be used for competency-based training of the workers in the COVID-19 test centers.

Radiomic Analysis of Primary GTV and CTV for Prediction of Extranodal Extension Using Diagnostic CT Images in Patients With Oropharyngeal Squamous Cell Carcinoma

<h3>Purpose/Objective(s)</h3> Prediction of extranodal extension (ENE) status of the involved lymph nodes has been shown to be an important factor in the prognosis and treatment of patients with Oropharyngeal Squamous Cell Carcinomas (OPSCC). Official diagnosis of ENE occurs pathologically at the time of surgery, and typically necessitates aggressive adjuvant treatment with radiation and concurrent chemotherapy. Due to higher toxicity with trimodality therapy, definitive chemoradiation can be a preferred treatment option up front instead of surgery if there is high clinical suspicion of ENE. This study investigates the potential value of radiomic features extracted from pre-treatment primary gross tumor volume (GTV) and clinical target volume (CTV) on diagnostic contrast enhanced Computed Tomography (CE-CT) images for prediction of ENE in patients with OPSCC. <h3>Materials/Methods</h3> For this study we identified 26 patients with pathologically confirmed OPSCC who went on to receive surgery and neck nodal dissection. Out of this group 13 were p16 positive, 13 were p16 negative, 7 were pathologic ENE positive, and 19 pathologic ENE negative. We contoured the primary tumor GTV on their pre-surgery CE-CT and added a 1 cm to create the CTV for radiomic analysis. For each patient, two sets of IBSI (Image Biomarker Standardization Initiative) validated radiomic features (N = 192 features from 11 different feature categories) were extracted from primary GTV and CTV on the diagnostic CE-CT images. Levene and Kolmogorov-Smirnov's (KS, <i>P</i> < 0.05) tests with confidence level of 95% along with absolute biserial correlation (|BSC|) with a threshold of > 0.2 were used to statistically reveal significant associations between ENE status and radiomics features. The Belsley collinearity diagnostics test was applied on the discriminant radiomic features for removing highly correlated features. Eight different Generalized-Linear Models (GLMs) were trained and tested using each individual feature along with two combined feature sets (combined discriminant features extracted from GTV and CTV). Balanced Accuracy Score (BAS), Positive predictive and negative predictive values (<b>PPV</b> and <b>NPV</b>, respectively) were used to evaluate the performance of the classifiers. <h3>Results</h3> Four GTV-based radiomic features and two CTV-based radiomic features (both from textural feature categories) were found to be statistically significant discriminators between the two ENE cohorts. Performances for prediction of the ENE for the two classifiers trained with the combined feature sets were: GTV-based GLM: BAS/PPV/NPV = 0.765/0.724/0.805 and CTV-based GLM: 0.875/0.928/0.822. Results imply that the CTV-based features have greater predictive value compared to GTV-based features for characterization of ENE. <h3>Conclusion</h3> This pilot study, albeit subject to confirmation in a larger patient population, suggests potential for the use of radiomics-based signatures extracted from the primary tumor for prediction of ENE in patients with OPSCC.

Superiority of Radiomics Information Compared to Clinical Factors in Characterization of Human Papilloma Virus (HPV) Status in Patients With Oropharyngeal Squamous Cell Carcinomas

To investigate the potential predictive value of patient clinical factors versus radiomic features extracted from CT images for characterization of Human Papilloma Virus (HPV) status for patients with oropharyngeal squamous cell carcinoma (OPSCC).One hundred twenty-eight OPSCC patients with known HPV-status (60-HPV+ and 68-HPV-, confirmed by immunohistochemistry-P16-protein testing) were retrospectively studied. Radiomic features (11 feature-categories) were extracted in 3D from contrast-enhanced (CE)-CT images of gross-tumor-volumes using 'in-house' software (ROdiomX) developed and validated following the image-biomarker-standardization-initiative (IBSI) guidelines. Six categories of clinical factors were investigated: Age-at-Diagnosis, Gender, Total-Charlson comorbidity score, Alcohol-Use, Smoking-History, and T-Stage, according to AJCC 7th-edition. An Elastic Net technique combined with a Generalized-Linear-Model (Lasso-GLM) were applied to perform L1 and L2 regularizations in the radiomic and clinical feature spaces to identify and rank the optimal feature subsets with most representative information for prediction of HPV. Elastic-Net GLM classifiers based on clinical factors only, radiomics only, and combined clinical and radiomics (ensemble/integrated) were constructed using random-permutation-sampling. Tests of significance (One-way ANOVA), average Area-Under-Receiver-Operating-Characteristic (AUC), and Positive and Negative Predictive values (PPV and NPV) were computed to estimate the generalization-error and prediction performance of the classifiers.Five clinical factors, including T-stage, smoking status, and age; and 21 radiomic features, including tumor morphology, textural information, and intensity contrast were found to be statistically significant discriminators between HPV positive and negative cohorts. Performances for prediction of HPV status for the 3 classifiers were: Radiomics Elastic-Net-GLM: AUC/PPV/NPV = 0.799/0.775/0.802; Clinical Elastic-Net-GLM: 0.673/0.738/0.679, and Integrated/Ensemble Elastic-Net-GLM: 0.912/0.884/0.860. Results imply that the radiomics-based classifier significantly outperforms that using clinical factors only, and that the combination of both radiomics and clinical factors yields even higher predictive performance.Albeit subject to confirmation in a larger cohort, this pilot study presents encouraging results in support of the role of radiomic features towards characterization of HPV in patients with OPSCC.

The Caregiver Contribution to Heart Failure Self-care Instrument: Further Psychometric Testing in a European Sample.

The 20-item Caregiver Contribution to Heart Failure Self-care (CACHS) was developed and tested in a series of preliminary studies providing evidence for the validity of this instrument in Canada. The purpose of this study was to assess the initial psychometric testing of a translated version of the 20-item CACHS in a European sample using classical test theory and item response theory (IRT) methods. This study is a preplanned subanalysis of data from a multisite, descriptive study of caregivers (n = 277; mean age, 52.7 years; 70.4% female) of Italian patients with heart failure. The CACHS-Italian version demonstrated adequate validity and reliability using classical test theory methods. Using IRT methods, test information function was unimodal with more item information in the negative versus positive regions of the latent trait. Most items displayed moderate to high discrimination with acceptable levels of difficulty. Differential item functioning, which determines whether caregivers from different groups with equal amounts of the latent trait have different expected item responses, differed based on caregivers' biological sex as did the IRT discrimination "α" and difficulty "β" parameters. Overall, the CACHS-Italian version demonstrated similar psychometric properties and excellent reliability as demonstrated in the Canadian sample. However, unlike the original Canadian English version, the CACHS-Italian version showed significant nonuniform differential item functioning, discrimination, and difficulty based on caregivers' biological sex. Ongoing examination of the CACHS-Italian version, particularly in men, is needed as is further linguistic validation using the Canadian CACHS-English version in non-North American English-speaking countries.

Listening to Transgender Patients and Their Providers in Non-Metropolitan Spaces: Needs, Gaps, and Patient-Provider Discrepancies.

Trans and gender non-conforming (TGNC) patients need better care; providers need TGNC focused medical trainings. TGNC health conferences can help, yet these events occur mostly in urban centers. Meanwhile, patients in non-metropolitan areas often face significant discrimination and notably poor access to TGNC care. This study explores the ongoing needs of TGNC patients and their providers following a one-day TGNC health conference in a small town in the American Midwest. Exploratory semi-structured interviews were used to gather in-depth information from TGNC conference attendees (N = 25). Theme analysis methods were used to identify areas of need for future trainings. Providers reported that they needed more exposure to TGNC patients, judgement-free opportunities to learn the basics about TGNC care, and ongoing trainings integrated into their medical school and ongoing education credits. Patients needed better access to care, more informed providers, and safer clinics. They cited lack of specialty care (e.g., mental health, surgery) as particularly problematic in a non-metropolitan setting. TGNC patients, and their providers in non-metropolitan areas, urgently need support. Patients lack specialized care and often possess greater knowledge than their health care teams; providers, in these areas, lack opportunities to work with patients and stay up to date on treatments.

Comparison of the Amyloid Load in the Brains of Two Transgenic Alzheimer's Disease Mouse Models Quantified by Florbetaben Positron Emission Tomography.

Alzheimer’s disease (AD) is characterized by formation of amyloid plaques and neurofibrillary tangles in the brain, which can be mimicked by transgenic mouse models. Here, we report on the characterization of amyloid load in the brains of two transgenic amyloidosis models using positron emission tomography (PET) with florbetaben (FBB), an 18F-labeled amyloid PET tracer routinely used in AD patients. Young, middle-aged, and old homozygous APP/PS1 mice (ARTE10), old hemizygous APPswe/PS1ΔE9, and old wild-type control mice were subjected to FBB PET using a small animal PET/computed tomography scanner. After PET, brains were excised, and ex vivo autoradiography was performed. Plaque pathology was verified on brain sections with histological methods. Amyloid plaque load increased progressively with age in the cortex and hippocampus of ARTE10 mice, which could be detected with both in vivo FBB PET and ex vivo autoradiography. FBB retention showed significant differences to wild-type controls already at 9 months of age by both in vivo and ex vivo analyses. An excellent correlation between data derived from PET and autoradiography could be obtained (rPearson = 0.947, p < 0.0001). Although amyloid load detected by FBB in the brains of old APPswe/PS1ΔE9 mice was as low as values obtained with young ARTE10 mice, statistically significant discrimination to wild-type animals was reached (p < 0.01). In comparison to amyloid burden quantified by histological analysis, FBB retention correlated best with total plaque load and number of congophilic plaques in the brains of both mouse models. In conclusion, the homozygous ARTE10 mouse model showed superior properties over APPswe/PS1ΔE9 mice for FBB small animal amyloid PET imaging. The absolute amount of congophilic dense-cored plaques seems to be the decisive factor for feasibility of amyloidosis models for amyloid PET analysis.

Alcohol and tobacco influencing prevalence of hypertension among 15–54 years old Indian men: An application of discriminant analysis using National Family Health Survey (NFHS), 2015–16

BackgroundHypertension has been described as an “iceberg disease” as those who suffer are usually unaware and hence usually seek healthcare services at a very late stage. It is estimated that more than two million Indians are suffering from hypertensive heart diseases that contributed to above 0.13 million deaths in 2016. ObjectivesThe present study aims to know the prevalence of Hypertension in India and its variation by socioeconomic backgrounds, and to find out risk factors discriminating hypertension with special emphasis on tobacco and alcohol consumption among men aged 15–54 years in India. MethodsIn this study, NFHS (2015–16) data were analyzed by applying binary logistic regression and discriminant analysis in the attempt to find significant predictors and discriminants of interest. ResultsThe prevalence of hypertension was 16.5% in the study population. The results suggested that the consumption of alcohol and tobacco are significant discriminant characteristics associated with hypertension irrespective of the socioeconomic background characteristics of the respondents. Hypertension is a chronic disease and is itself a causative factor for several other diseases like renal impairment, other cardiovascular diseases, and stroke. ConclusionsThe findings are expected to have direct implications on public health interventions and policy formulation to reduce diseases caused by tobacco and alcohol, particularly hypertension among men in the potential economically productive age group in India and similar settings.

Evaluation of MicroRNA-122 as A Non-invasive Diagnostic Biomarker For Non-Alcoholic Fatty Liver Disease and NASH related Cirrhosis

Abstract Background Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease worldwide. NAFLD is considered to represent the hepatic manifestation of metabolic syndrome. NAFLD was traditionally considered as a relatively benign liver disease. However, some patients with NAFLD progress to liver fibrosis, cirrhosis and hepatocellular carcinoma 8-13. Therefore, the precise diagnosis and staging of NAFLD patients is clinically important. Liver biopsy is the gold standard for the evaluation of NAFLD patients in terms of staging. However, liver biopsy is an invasive technique, and the identification of noninvasive biomarkers is required. Objective To assess the value of MicroRNA-122 as a non-invasive biomarker for diagnosis of NAFLD and NASH related Cirrhosis. Patients and Methods In the present study, we assess the value of MicroRNA-122 as a noninvasive biomarker for diagnosis of NAFLD and NASH related Cirrhosis. Gastroenterology and Hepatology outpatient clinic at: Ain Shams University Hospitals, Shebin El-Kom Teaching Hospital, Kafr Elsheikh University Hospitals. Clinical Pathology department at Faculty of Medicine, Ain Shams University. Results Patients with NASH had higher NAFLD score than patients with NAFLD than normal control. Patients with NASH had significantly higher frequency of upregulated miRNA-22. Patients with NASH had higher miRNA 122 expression than normal controls and patients with NAFLD. Likewise, patients with NAFLD had higher miRNA 122 expression than normal controls. The miRNA 122 was a significant discriminator of NAFLD and NASH with a sensitivity of 75% and specificity of 82% for NAFLD and a sensitivity of 91% and specificity of 86% for the NASH. Conclusion miRNA-122 is a sensitive and specific biomarker in the early detection of NAFLD and NASH as they are linked to the lipid metabolism reducing the need for liver biopsy. NAFLD fibrosis score had high sensitivity in differentiating the NAFLD groups from the control group and in differentiating the steatosis group from the NASH group. Serum levels of miRNA-122 were positively correlated with BMI, ALT and AST.

Evaluation of MicroRNA-122 as A Non-invasive Diagnostic Biomarker For Non-Alcoholic Fatty Liver Disease and NASH related Cirrhosis

Abstract Background Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease worldwide. NAFLD is considered to represent the hepatic manifestation of metabolic syndrome. NAFLD was traditionally considered as a relatively benign liver disease. However, some patients with NAFLD progress to liver fibrosis, cirrhosis and hepatocellular carcinoma 8-13. Therefore, the precise diagnosis and staging of NAFLD patients is clinically important. Liver biopsy is the gold standard for the evaluation of NAFLD patients in terms of staging. However, liver biopsy is an invasive technique, and the identification of noninvasive biomarkers is required. Objective To assess the value of MicroRNA-122 as a non-invasive biomarker for diagnosis of NAFLD and NASH related Cirrhosis. Patients and Methods In the present study, we assess the value of MicroRNA-122 as a noninvasive biomarker for diagnosis of NAFLD and NASH related Cirrhosis. Gastroenterology and Hepatology outpatient clinic at: Ain Shams University Hospitals, Shebin El-Kom Teaching Hospital, Kafr Elsheikh University Hospitals. Clinical Pathology department at Faculty of Medicine, Ain Shams University. Results Patients with NASH had higher NAFLD score than patients with NAFLD than normal control. Patients with NASH had significantly higher frequency of upregulated miRNA-22. Patients with NASH had higher miRNA 122 expression than normal controls and patients with NAFLD. Likewise, patients with NAFLD had higher miRNA 122 expression than normal controls. The miRNA 122 was a significant discriminator of NAFLD and NASH with a sensitivity of 75% and specificity of 82% for NAFLD and a sensitivity of 91% and specificity of 86% for the NASH. Conclusion miRNA-122 is a sensitive and specific biomarker in the early detection of NAFLD and NASH as they are linked to the lipid metabolism reducing the need for liver biopsy. NAFLD fibrosis score had high sensitivity in differentiating the NAFLD groups from the control group and in differentiating the steatosis group from the NASH group. Serum levels of miRNA-122 were positively correlated with BMI, ALT and AST.

Shear Wave Elastography in Assessment of Liver Fibrosis

Abstract Background Liver fibrosis is major medical issues in patients with chronic hepatitis C (CHC). It may lead to cirrhosis, hepatocellular carcinoma (HCC) and liver-related death. Therefore, assessing the degree of fibrosis in patients with chronic liver diseases, especially before the advanced stage, is clinically important to allow early care and prevent fatal liver disease. Objective The plan was to do shear-wave Elastography after fibroscan (TE) in order to assess the stiffness of the liver, detect the changes occurred in hepatitis C patients and measure diagnostic accuracy of 2D- SWE by using TE as reference standard. Methods A cross-section study included 30 persons with positive hepatitis C. They were referred to Radiology department at National Hepatology and tropical medicine research institute. Results Our study included (30) patients who have hepatitis C positive, their ages ranged from (18) years old to (60) years old with mean SD of 52.97 ± 9.43. They were 17 females (56.7%) and 13 males (43.3%). Different liver fibrosis stages were observed by 2D-SWE as following: (FO) 4 patients (13.3%), (Fl) 4 patients (13.3%), (F2) 9 patients (30.0%), (F3) 10 patients (33.3%), (F4) 3 patients (10.0%). While TE (fibroscan) shows (FO) 6 (20.0%), (Fl) 3 patients (10.0%), (F2) 7 patients (23.3%), (F3) 8 patients (26.7%) (F4) 6 patients (20.0%). Our study showed that the relation between TE (fibroscan) and SWE finding had positive correlation of most patients with liver fibrosis with (p-value 0.006 and r-value 0.487). Because the impoltant of significant fibrosis for initiate antiviral protocol therapy, 30 patients classified into FO—FI (non-significant liver fibrosis) versus F2—F4 (significant liver fibrosis). Our study show significant discrimination was found between no/mild fibrosis (FO-FI) and significant fibrosis (F2-F4), shows the sensitivity of SWE in detection of significant fibrosis results is 95.2% and the specificity is 77.8%, PPV 90.91 %, NPV 87.5% and the accuracy 90.0% with cutoff value &amp;gt;5.7kPa. Conclusion SD-SWE is accurate in prediction significant fibrosis (2F2), Thus is expected to overcome the limitation of TE as a reliable method to assess fibrosis induce by hepatitis.

Performance of the REACH, PARIS, BleeMACS, and PRECISE-DAPT scores for predicting 1-year bleeding events in patients undergoing coronary drug-eluting stent implantation

This study aimed to evaluate the predictive performance of the REACH, PARIS, BleeMACS, and PRECISE-DAPT scores in Chinese patients undergoing coronary drug-eluting stent (DES) implantation. A total of 1911 patients undergoing coronary DES implantation were consecutively recruited and followed up for 1 year. The primary endpoints were BARC type 3 or 5 bleeding and BARC type 2,3, or 5 bleeding. The BleeMACS score and the PRECISE-DAPT score were significantly associated with 1-year incidence of BARC type 3 or 5 bleeding, but not BARC type 2, 3, or 5 bleeding. The discrimination of the PRECISE-DAPT score was moderate for BARC type 3 or 5 bleeding (c-statistic = 0.633), while those of the REACH (c-statistic = 0.533), PARIS (c-statistic = 0.553), and BleeMACS scores (c-statistic = 0.613) were relatively low. However, the analysis of c-statistic, NRI, and IDI detected no significant discrimination improvement of the PRECISE-DAPT score for BARC type 3 or 5 bleeding compared to the other three scores. The calibrations of the PRECISE-DAPT and BleeMACS scores were modest (Hosmer-Lemeshow test p > .05). Decision curve analysis indicated net benefit of the PRECISE-DAPT score in bleeding risk evaluation. In conclusion, the PRECISE-DAPT score performed moderately in predicting BARC type 3 or 5 bleeding, while the discriminative capacities of the REACH, PARIS, BleeMACS scores were relatively low in patients undergoing DES implantation. But no significant discrimination improvement of the PRECISE-DAPT score compared to the other scores could be detected. Further studies are required to develop standardized bleeding risk scores for this population.

Technical note: On the development of an outcome-driven frequency filter for improving radiomics-based modeling of human papillomavirus (HPV) in patients with oropharyngeal squamous cell carcinoma.

To implement an outcome-driven frequency filter for improving radiomics-based modeling of human papillomavirus (HPV) for patients with oropharyngeal squamous cell carcinoma (OPSCC). One hundred twenty-eight OPSCC patients with known HPV status (60-HPV+ and 68-HPV-, confirmed by immunohistochemistry-P16 protein testing) were retrospectively studied. A 3D Discrete Fourier Transform was applied on contrast-enhanced computed tomography (CE-CT) images of patient gross tumor volumes (GTVs) to transform intensity distributions to the frequency domain and estimate frequency power spectrums of HPV- and HPV+ patient cohorts. Statistical analyses were performed to rank frequency bands contributing toward the prediction of HPV status. An outcome-driven frequency filter was designed accordingly and applied to GTV frequency information. A 3D inverse discrete Fourier transform was applied to reconstruct HPV-related frequency-filtered images. Radiomics features (11 feature-categories) were extracted from pre- and post-frequency filtered images using our previously published "ROdiomiX" software. Least-absolute-shrinkage-and-selection-operation (Lasso) combined with a generalized linear model (Lasso-GLM) was developed to identify and rank feature subsets with the optimal information for prediction of HPV+/-. Radiomics-based Lasso-GLM classifiers (pre- and post-frequency filtered) were constructed and validated using random permutation sampling and nested cross-validation (CV) techniques. Average area under the receiver operating characteristic (AUC), and positive and negative predictive values (PPV and NPV) were computed to estimate generalization error and prediction performance. Among 192 radiomic features, 15 features were found to be statistically significant discriminators between HPV+/- cohorts on post-frequency filtered CE-CT images. Fourteen such radiomic features were observed on pre-frequency filtered datasets. Discriminant features included tumor morphology and intensity contrast. Performances for prediction of HPV for the pre- and post-frequency filtered Lasso-GLM classifiers were as follows: AUC/PPV/NPV=0.789/0.755/0.805 and 0.850/0.808/0.877, respectively. Nested CV performances for prediction of HPV for the pre- and post-frequency filtered Lasso-GLM classifiers were as follows: AUC/PPV/NPV=0.814/0.725/0.877 and 0.890/0.820/0.911, respectively. Albeit subject to confirmation in a larger cohort, this pilot study presents encouraging results on the importance of frequency analysis prior to radiomic feature extraction toward enhancement of model performance for characterizing HPV in patients with OPSCC.