Noninvasive Risk Stratification Research Articles

Non-Invasive Risk Stratification in NAFLD/NASH Patients for Screening EGD.

Non-Invasive Risk Stratification in NAFLD/NASH Patients for Screening EGD.

Noninvasive Risk Stratification for Nonalcoholic Fatty Liver Disease Among Living Liver Donor Candidates: A Proposed Algorithm.

To reduce waitlist mortality, living donor liver transplantation (LDLT) has increased over the past decade in the United States, but not at a rate sufficient to completely mitigate organ shortage. As a result, there are ongoing efforts to expand the living liver donor pool. Simultaneously, the prevalence of nonalcoholic fatty liver disease (NAFLD) in the general population has increased, which has significant implications on the pool of potential living liver donors. As such, a clinical assessment algorithm that exhaustively evaluates for NAFLD and fibrosis is critical to the safe expansion of LDLT. An ideal algorithm would employ safe and noninvasive methods, relying on liver biopsy only when necessary. While exclusion of NAFLD and fibrosis by noninvasive means is widely studied within the general population, there are no well-accepted guidelines for evaluation of living donors using these modalities. Here we review the current literature regarding noninvasive NALFD and fibrosis evaluation and propose a potential algorithm to apply these modalities for the selection of living liver donors.

Ambulatory electrocardiographic markers predict serious cardiac events in patients with chronic kidney disease: The Japanese Noninvasive Electrocardiographic Risk Stratification of Sudden Cardiac Death in Chronic Kidney Disease (JANIES-CKD) study.

BackgroundNoninvasive electrocardiographic markers (NIEMs) are promising arrhythmic risk stratification tools for assessing the risk of sudden cardiac death. However, little is known about their utility in patients with chronic kidney disease (CKD) and organic heart disease. This study aimed to determine whether NIEMs can predict cardiac events in patients with CKD and structural heart disease (CKD‐SHD).MethodsWe prospectively analyzed 183 CKD‐SHD patients (median age, 69 years [interquartile range, 61−77 years]) who underwent 24‐h ambulatory electrocardiographic monitoring and assessed the worst values for ambulatory‐based late potentials (w‐LPs), heart rate turbulence, and nonsustained ventricular tachycardia (NSVT). The primary endpoint was the occurrence of documented lethal ventricular tachyarrhythmias (ventricular fibrillation or sustained ventricular tachycardia) or cardiac death. The secondary endpoint was admission for cardiovascular causes.ResultsThirteen patients reached the primary endpoint during a follow‐up period of 24 ± 11 months. Cox univariate regression analysis showed that existence of w‐LPs (hazard ratio [HR] = 6.04, 95% confidence interval [CI]: 1.4−22.3, p = .007) and NSVT [HR = 8.72, 95% CI: 2.8−26.5: p < .001] was significantly associated with the primary endpoint. Kaplan–Meier analysis demonstrated that the combination of w‐LPs and NSVT resulted in a lower event‐free survival rate than did other NIEMs (p < .0001). No NIEM was useful in predicting the secondary endpoint, although the left ventricular mass index was correlated with the secondary endpoint.ConclusionThe combination of w‐LPs and NSVT was a significant risk factor for lethal ventricular tachyarrhythmias and cardiac death in CKD‐SHD patients.

Shock Index in COVID Era

AbstractThe health care burden and risks to health care workers imposed by novel coronavirus disease 2019 (COVID-19) mandated the need for a simple, noninvasive, objective, and parsimonious risk stratification system predicting the level of care, need for definitive airway, and titration of the ongoing patient care. Shock index (SI = heart rate/systolic blood pressure) has been evaluated in emergency triage, sepsis, and trauma settings including different age group of patients. The ever accumulating girth of evidences demonstrated a superior predictive value of SI over other hemodynamic parameters. Inclusion of respiratory and/or neurological parameters and adjustment of the cutoffs appropriate to patient age increase the predictability in the trauma and sepsis scenario. Being reproducible, dynamic, and simple, SI can be a valuable patient risk stratification tool in this ongoing era of COVID-19 pandemic.

Assessment of P- to delta-wave interval and its relationship with accessory pathway properties in patients with pre-excitation.

The first clinical manifestation of the Wolff-Parkinson-White syndrome in previously asymptomatic individuals may be sudden cardiac death. The options for non-invasive risk stratification are limited in the current era beyond ambulatory rhythm monitoring and an exercise stress test. In our study, we sought to investigate whether there was a relationship between the shortest measured P- to delta-wave time interval (PDI) on the conduction properties of surface electrocardiogram and accessory pathways expressed as antegrade effective refractory period (APERP). Demographic data, symptom status, electrocardiograms (ECG) and intra-cardiac recordings of invasive electrophysiology testing of 103 patients who underwent accessory pathway ablation procedures were collected. Exclusion criteria were: (1) intermittently occurring pre-excitation, which was detected in previous ECGs, (2) delta-wave resolution on treadmill test, (3) presence of multiple accessory pathways, and (4) accessory pathway locations other than the septum. The PDI was measured as the time interval from the beginning of the P wave to the earliest upstroke or downstroke of the delta wave on V1 and V2 derivations of the surface ECG, and the shortest measurement was recorded. Patients were grouped into two groups: group I, if APERP was < 240 ms and group II if APERP was ≥ 240 ms. PDI was significantly shorter in group II. By correlation analysis, a positive and moderate correlation between PDI and APERP (r = 0.598, p < 0.001) and PDI and age (r = 0.800, p < 0.001) was found, and a negative and moderate correlation between PDI and inducible AF (r = -492, p < 0.001). The best cut-off value for PDI to predict APERP ≥ 240 was 90.5 ms with a sensitivity of 80% and a specificity of 83%. Our results demonstrate that there was a strong correlation between the P- to delta-wave interval and universally accepted risk factors, such as low age, low APERP and atrial fibrillation inducibility. Further studies with larger patient groups and follow-up data are needed to appraise its predictive value.

Noninvasive risk stratification of intraductal papillary mucinous neoplasia with malignant potential by serum apolipoprotein-A2-isoforms.

Intraductal papillary mucinous neoplasms (IPMNs) are premalignant lesions of pancreatic cancer. An accurate serum biomarker, which allows earlier identification of asymptomatic individuals with high-risk for developing cancer, is of urgent need. Apolipoprotein A2-isoforms (apoA2-i) have previously been identified as biomarkers in pancreatic cancer. This study investigates a potential clinical application of the serum apoA2-i for risk stratification of IPMN and associated cancer. The concentrations of apoA2-i were retrospectively determined in 523 patient sera specimen, composed of 305 IPMNs with preinvasive lesions with different grades of dysplasia and invasive cancer, 140 pancreatic ductal adenocarcinoma, 78 with other cystic lesions and healthy controls cohorts, using an apoA2-i enzyme-linked immunosorbent assay kit. The diagnostic performance of serum apoA2-i was assessed and compared to routine clinical marker CA 19-9. ApoA2-i levels were significantly reduced in all IPMN samples regardless of stage compared to healthy controls. Receiver operating characteristic curve analysis of IPMNs with high-grade dysplasia and IPMN with associated carcinoma revealed the area under curve (AUC) of 0.91 and >0.94, respectively. The respective sensitivities were 70% and 83% with a specificity of 95%, and significantly higher than the gold standard biomarker CA 19-9. AUC values of apoA2-i for detecting IPMN-associated carcinoma of colloid and ductal subtypes were 0.990 and 0.885, respectively. ApoA2-i has the potential to early detect the risk of malignancy of patients with IPMN. The serological apoA2-i test in combination with imaging modalities could help improve the diagnosis of IPMN malignancy. Further validation in larger and independent international cohort studies is needed.

Abstract 12636: ECG-Based Risk Stratification of Long-Term Mortality in Suspected Acute Coronary Syndrome

Introduction: Non-invasive risk stratification can play a significant role in the initial triage of patients with suspected acute coronary syndrome. Numerous ECG features have been previously linked with mortality in both the general and cardiac populations. We sought to build an ECG-based model that can predict time-to-death in high-risk chest pain patients transported by Emergency Medical Services. Methods: This was a prospective observational cohort study of patients evaluated for suspected acute coronary syndrome. The study recruited consecutive patients evaluated at the emergency department of three UPMC-affiliated tertiary care hospitals. We included consecutive patients in whom a prehospital echocardiogram was performed during indexed encounter. Baseline ECGs were preprocessed using manufacturer specific algorithms. We evaluated 554 temporal-spatial features of the 12-lead ECG in multivariate proportional hazards Cox regression model for predicting all-cause death during long term follow up. Death was ascertained using phenotyping UPMC electronic hospital records and through the CDC National Death Index database. Model fit was evaluated using C-statistic and AIC. We set alpha at 0.01 for two-tailed hypothesis testing. Results: Our sample included 2311 patients (aged 59 ± 16.6, 47% females, 41% Black). Over a median follow up period of 1868 days (IQR = 688; [Q1, Q3] = [1511, 2199]), there was 622 (26.9%) adjudicated deaths. During univariate analysis, 288 features were significantly associated with time-to-death. In the final multivariate model (c-statistic = 0.79, AIC = 9066.05), controlling for demographic and clinical data, 15 ECG features remained predictive of the study outcome, with Selvester score being the strongest predictor (Hazard Ratio = 1.09, 95% CI = 1.03 - 1.16). Other clinically important ECG features included horizontal-plane QRS axis, QRS-T angle, QTc interval, QTpeak, T peak-end, S wave morphology the inferior leads, QRS morphology in lead aVR, and T wave morphology in the anterior leads. Conclusions: The presenting 12-lead ECG can serve as a powerful risk stratification tool of long-term mortality in patients with chest pain. Selvester score can serve as a plausible and easy to use clinical decision tool.

Profiling of Circulating Tumor DNA for Noninvasive Disease Detection, Risk Stratification, and MRD Monitoring in Patients with CNS Lymphoma

Abstract Introduction: Clinical outcomes for patients with central nervous system lymphoma (CNSL) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure remains challenging with existing methods. In addition, diagnosis of CNSL requires invasive neurosurgical biopsies that carry procedural risks and often cannot be performed in frail or elderly patients. Circulating tumor DNA (ctDNA) has shown great potential as a noninvasive biomarker in systemic lymphomas. Yet, previous studies revealed low ctDNA detection rates in blood plasma of CNSL patients. In this study, we utilized ultrasensitive targeted high-throughput sequencing technologies to explore the role of ctDNA for disease classification, MRD detection, and early prediction of clinical outcomes in patients with CNSL. Methods: We applied Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) and Phased Variant Enrichment and Detection Sequencing (PhasED-Seq, Kurtz et al, Nat Biotech 2021) to 85 tumor biopsies, 131 plasma samples, and 62 CSF specimens from 92 CNSL patients and 44 patients with other brain cancers or inflammatory cerebral diseases, targeting 794 distinct genetic regions. Concentrations of ctDNA were correlated with radiological measures of tumor burden and tested for associations with clinical outcomes at distinct clinical time points. We further developed a novel classifier to noninvasively distinguish CNS lymphomas from other CNS tumors based on their mutational landscapes in plasma and CSF, using supervised training of a machine learning approach from tumor whole genome sequencing data and own genotyping analyses, followed by its independent validation. Results: We identified genetic aberrations in 100% of CNSL tumor biopsies (n=63), with a median of 262 mutations per patient. Pretreatment plasma ctDNA was detectable in 78% of plasma samples and in 100% of CSF specimens (Fig. 1a), with ctDNA concentrations ranging from 0.0004 - 5.94% allele frequency (AF, median: 0.01%) in plasma and 0.0049 - 50.47% AF (median: 0.62%) in CSF (Fig. 1b). Compared to ctDNA concentrations in patients with systemic diffuse large B-cell lymphoma (DLBCL, data from Kurtz et al., J Clin Oncol, 2018), plasma ctDNA levels in CNSL were in median more than 200-fold lower (Fig. 1b). We observed a significant correlation of ctDNA concentrations with total radiographic tumor volumes (TRTV) measured by MRI (Fig. 1c,d), but no association with clinical risk scores (i.e., MSKCC score) or concurrent steroid treatment. Assessment of ctDNA at pretreatment time points predicted progression-free survival (PFS) and overall survival (OS), both as continuous and binary variable (Fig. 1e,f). Notably, patients could be stratified into risk groups with particularly favorable or poor prognoses by combining ctDNA and TRTV as pretreatment biomarkers (Fig. 1g). Furthermore, ctDNA positivity during curative-intent induction therapy was significantly associated with clinical outcomes, both PFS and OS (Fig. 1h). Finally, we applied our novel machine learning classifier to 207 specimens from an independent validation cohort of CNSL and Non-CNSL patients. We observed high specificity (100%) and positive predictive value (100%) for noninvasive diagnosis of CNSL, with a sensitivity of 57% for CSF and 21% for plasma, suggesting that a significant subset of CNSL patients might be able to forego invasive surgical biopsies. Conclusions: We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings suggest that ctDNA accurately mirrors tumor burden and serves as a valuable clinical biomarker for risk stratification, outcome prediction, and surgery-free lymphoma classification in CNSL. We foresee an important potential future role of ctDNA as a decision-making tool to guide treatment in patients with CNSL. Figure 1 Figure 1. Disclosures Esfahani: Foresight Diagnostics: Current holder of stock options in a privately-held company. Kurtz: Genentech: Consultancy; Roche: Consultancy; Foresight Diagnostics: Consultancy, Current holder of stock options in a privately-held company. Schorb: Riemser Pharma GmbH: Honoraria, Research Funding; Roche: Research Funding; AbbVie: Research Funding. Diehn: BioNTech: Consultancy; RefleXion: Consultancy; Roche: Consultancy; AstraZeneca: Consultancy; Foresight Diagnostics: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; CiberMed: Current holder of stock options in a privately-held company, Patents &amp; Royalties; Illumina: Research Funding; Varian Medical Systems: Research Funding. Alizadeh: Foresight Diagnostics: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Gilead: Consultancy; Roche: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Janssen Oncology: Honoraria; CAPP Medical: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Forty Seven: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Cibermed: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Bristol Myers Squibb: Research Funding.

Inclusion of echocardiographic measure of right ventricular function in the non-invasive French pulmonary arterial hypertension risk stratification method

Abstract Background Although preserved right ventricular (RV) function is consistently associated with better survival in pulmonary arterial hypertension (PAH), the French risk assessment method has not yet considered echocardiographic criteria of RV function. Purpose In the present study, we tested the value of tricuspid annular plane systolic excursion (TAPSE) measured by echocardiography for non-invasive PAH risk assessment. Methods We retrospectively studied a cohort of 306 incident PAH patients treated in two French expert centers who underwent follow-up TAPSE measurement from echocardiographic apical 4-chamber view in addition to previously validated invasive and non-invasive risk stratification variables. The primary composite outcome was 3-year lung transplantation free survival after follow-up assessment. Results At re-evaluation, 66% of patients were in NYHA functional class I-II and mean pulmonary arterial pressure, cardiac index, N-Terminal pro brain natriuretic peptide (NTproBNP), and 6-minute walk distance (6MWD) were 40±16 mmHg, 3.5±1.1 L/min/m2, 270 [interquartile range (IQR) 896] ng/L and 401 (IQR 213) meters, respectively. The primary outcome occurred in 58 (19%) patients. In multivariable Cox regression analysis, NYHA functional class I-II (p=0.02), NTproBNP &amp;lt;300 ng/L or BNP &amp;lt;50 ng/L (p=0.02), 6MWD &amp;gt;440m (p=0.049) and TAPSE≥17 mm (p=0.02) were associated with lung transplantation free survival. TAPSE provided similar information over 6MWD when both were used alternatively to stratify PAH patients at low risk (log-rank&amp;lt;0.001); Harrell's c-index 0.73. Conclusion Three dichotomized low-risk criteria (TAPSE, 6MWD and NTproBNP or BNP plasma levels) allow non-invasive risk assessment in PAH. Funding Acknowledgement Type of funding sources: None. 3-years transplant-free survival

Non-invasive alloimmune risk stratification of long-term liver transplant recipients

Management of long-term immunosuppression following liver transplantation (LT) remains empirical. Surveillance liver biopsies in combination with transcriptional profiling could overcome this challenge by identifying recipients with active alloimmune-mediated liver damage despite normal liver tests, but this approach lacks applicability. Our aim was to investigate the utility of non-invasive tools for the stratification of stable long-term survivors of LT, according to their immunological risk and need for immunosuppression. We conducted a cross-sectional multicentre study of 190 adult LT recipients assessed to determine their eligibility to participate in an immunosuppression withdrawal trial. Patients had stable liver allograft function and had been transplanted for non-autoimmune non-replicative viral liver disease >3 years before inclusion. We performed histological, immunogenetic and serological studies and measured the intrahepatic transcript levels of an 11-gene classifier highly specific for T cell-mediated rejection (TCMR). In this cohort, 35.8% of patients harboured clinically silent fibro-inflammatory liver lesions (13.7% had mild damage and 22.1% had moderate-to-severe damage). The severity of liver allograft damage was positively associated with TCMR-related transcripts, class II donor-specific antibodies (DSAs), ALT, AST, and liver stiffness measurement (LSM), and negatively correlated with serum creatinine and tacrolimus trough levels. Liver biopsies were stratified according to their TCMR transcript levels using a cut-off derived from biopsies with clinically significant TCMR. Two multivariable prediction models, integrating ALT+LSM or ALT+class II DSAs, had a high discriminative capacity for classifying patients with or without alloimmune damage. The latter model performed well in an independent cohort of 156 liver biopsies obtained from paediatric liver recipients with similar inclusion/exclusion criteria. ALT, class II DSAs and LSM are valuable tools to non-invasively identify stable LT recipients without significant underlying alloimmunity who could benefit from minimisation of immunosuppression. A large proportion of liver transplant patients with normal liver tests have inflammatory liver lesions, which in 17% of cases are molecularly indistinguishable from those seen at the time of rejection. ALT, class II donor-specific antibodies and liver stiffness are useful in identifying patients with this form of subclinical rejection. We propose these markers as a useful tool to help clinicians determine if the immunosuppression administered is adequate.

Radiomic Score as a Potential Imaging Biomarker for Predicting Survival in Patients With Cervical Cancer.

ObjectivesAccurate prediction of prognosis will help adjust or optimize the treatment of cervical cancer and benefit the patients. We aimed to investigate the incremental value of radiomics when added to the FIGO stage in predicting overall survival (OS) in patients with cervical cancer.MethodsThis retrospective study included 106 patients with cervical cancer (FIGO stage IB1–IVa) between October 2017 and May 2019. Patients were randomly divided into a training cohort (n = 74) and validation cohort (n = 32). All patients underwent contrast-enhanced computed tomography (CT) prior to treatment. The ITK-SNAP software was used to delineate the region of interest on pre-treatment standard-of-care CT scans. We extracted 792 two-dimensional radiomic features by the Analysis Kit (AK) software. Pearson correlation coefficient analysis and Relief were used to detect the most discriminatory features. The radiomic signature (i.e., Radscore) was constructed via Adaboost with Leave-one-out cross-validation. Prognostic models were built by Cox regression model using Akaike information criterion (AIC) as the stopping rule. A nomogram was established to individually predict the OS of patients. Patients were then stratified into high- and low-risk groups according to the Youden index. Kaplan–Meier curves were used to compare the survival difference between the high- and low-risk groups.ResultsSix textural features were identified, including one gray-level co-occurrence matrix feature and five gray-level run-length matrix features. Only the FIGO stage and Radscore were independent risk factors associated with OS (p < 0.05). The C-index of the FIGO stage in the training and validation cohorts was 0.703 (95% CI: 0.572–0.834) and 0.700 (95% CI: 0.526–0.874), respectively. Correspondingly, the C-index of Radscore was 0.794 (95% CI: 0.707–0.880) and 0.754 (95% CI: 0.623–0.885). The incorporation of the FIGO stage and Radscore achieved better performance, with a C-index of 0.830 (95% CI: 0.738–0.922) and 0.772 (95% CI: 0.615–0.929), respectively. The nomogram based on the FIGO stage and Radscore could individually predict the OS probability with good discrimination and calibration. The high-risk patients had shorter OS compared with the low-risk patients (p < 0.05).ConclusionRadiomics has the potential for noninvasive risk stratification and may improve the prediction of OS in patients with cervical cancer when added to the FIGO stage.

Urinary Proteomics Identifying Novel Biomarkers for the Diagnosis and Phenotyping of Carotid Artery Stenosis.

Background: Carotid artery stenosis (CAS) is caused by the formation of atherosclerotic plaques inside the arterial wall and accounts for 20–30% of all strokes. The development of an early, noninvasive diagnostic method and the identification of high-risk patients for ischemic stroke is essential to the management of CAS in clinical practice.Methods: We used the data-independent acquisition (DIA) technique to conduct a urinary proteomic study in patients with CAS and healthy controls. We identified the potential diagnosis and risk stratification biomarkers of CAS. And Ingenuity pathway analysis was used for functional annotation of differentially expressed proteins (DEPs). Furthermore, receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic values of DEPs.Results: A total of 194 DEPs were identified between CAS patients and healthy controls by DIA quantification. The bioinformatics analysis showed that these DEPs were correlated with the pathogenesis of CAS. We further identified 32 DEPs in symptomatic CAS compared to asymptomatic CAS, and biological function analysis revealed that these proteins are mainly related to immune/inflammatory pathways. Finally, a biomarker panel of six proteins (ACP2, PLD3, HLA-C, GGH, CALML3, and IL2RB) exhibited potential diagnostic value in CAS and good discriminative power for differentiating symptomatic and asymptomatic CAS with high sensitivity and specificity.Conclusions: Our study identified novel potential urinary biomarkers for noninvasive early screening and risk stratification of CAS.

Automatic segmentation of uterine endometrial cancer on multi-sequence MRI using a convolutional neural network

Endometrial cancer (EC) is the most common gynecological tumor in developed countries, and preoperative risk stratification is essential for personalized medicine. There have been several radiomics studies for noninvasive risk stratification of EC using MRI. Although tumor segmentation is usually necessary for these studies, manual segmentation is not only labor-intensive but may also be subjective. Therefore, our study aimed to perform the automatic segmentation of EC on MRI with a convolutional neural network. The effect of the input image sequence and batch size on the segmentation performance was also investigated. Of 200 patients with EC, 180 patients were used for training the modified U-net model; 20 patients for testing the segmentation performance and the robustness of automatically extracted radiomics features. Using multi-sequence images and larger batch size was effective for improving segmentation accuracy. The mean Dice similarity coefficient, sensitivity, and positive predictive value of our model for the test set were 0.806, 0.816, and 0.834, respectively. The robustness of automatically extracted first-order and shape-based features was high (median ICC = 0.86 and 0.96, respectively). Other high-order features presented moderate-high robustness (median ICC = 0.57–0.93). Our model could automatically segment EC on MRI and extract radiomics features with high reliability.

The impact of genetic risk on liver fibrosis in non-alcoholic fatty liver disease as assessed by magnetic resonance elastography.

Variants in multiple genetic loci modify the risk of non-alcoholic fatty liver disease (NAFLD) and cirrhosis but there are limited data on the quantitative impact of variant copies on liver fibrosis. To investigate the effect of PNPLA3, TM6SF2, MBOAT7, GCKR and HSD17B13 genotype on liver fibrosis assessed by magnetic resonance elastography (MRE), a reproducible, accurate, continuous biomarker of liver fibrosis. This is a cross-sectional analysis derived from a well-characterised cohort at risk for NAFLD who underwent genotyping and MRE assessment. Liver stiffness (LS) was estimated using MRE and advanced fibrosis was defined as liver stiffness ≥3.63kilopascals (kPa). Univariable and multivariable linear and logistic regression analysis, were used to assess the association between genotype and MRE. Two hundred sixty-four patients (63% women) with a mean age 53 (±17)years, and 31% Hispanic ethnicity with genotyping and MRE were included. The odds of advanced fibrosis were 3.1 (95% CI: 1.1-8.9, P=0.04) for CG and 6.5 (95% CI: 2.2-18.9, P<0.01) for GG compared to CC PNPLA3 genotype. Each PNPLA3 risk variant copy was associated with 0.40kPa (95% CI: 0.19-0.61, P<0.01) increase in LS on MRE in analysis adjusted for age, sex and BMI and there was significant genotype-age interaction (P<0.01). Conversely, the protective TA allele in HSD17B13 was associated with a -0.41kPa (95% CI: -0.76 to -0.05, P=0.03) decrease in liver stiffness on MRE multivariable analysis. Knowledge of PNPLA3 and HSD17B13 genotype may assist in the non-invasive risk stratification of NAFLD with closer monitoring recommended for those with high genetic risk.

Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging.

Simple SummaryPancreatic ductal adenocarcinoma (PDAC) remains a devastating disease. However, variations in tumor biology influence individual patient outcomes greatly. We previously showed a strong association between magnetic resonance imaging-based tumor cell estimates and patient survival. In this study we aimed to transfer this finding to more broadly applied computed tomography (CT) imaging for non-invasive risk stratification. We correlated in vivo CT imaging with histopathological analyses and could show a strong association between regional Hounsfield Units (HU) and tumor cellularity. In conclusion, our study suggests CT-based tumor cell estimates as a widely applicable way of non-invasive tumor cellularity characterization in PDAC.Background: PDAC remains a tumor entity with poor prognosis and a 5-year survival rate below 10%. Recent research has revealed invasive biomarkers, such as distinct molecular subtypes, predictive for therapy response and patient survival. Non-invasive prediction of individual patient outcome however remains an unresolved task. Methods: Discrete cellularity regions of PDAC resection specimen (n = 43) were analyzed by routine histopathological work up. Regional tumor cellularity and CT-derived Hounsfield Units (HU, n = 66) as well as iodine concentrations were regionally matched. One-way ANOVA and pairwise t-tests were performed to assess the relationship between different cellularity level in conventional, virtual monoenergetic 40 keV (monoE 40 keV) and iodine map reconstructions. Results: A statistically significant negative correlation between regional tumor cellularity in histopathology and CT-derived HU from corresponding image regions was identified. Radiological differentiation was best possible in monoE 40 keV CT images. However, HU values differed significantly in conventional reconstructions as well, indicating the possibility of a broad clinical application of this finding. Conclusion: In this study we establish a novel method for CT-based prediction of tumor cellularity for in-vivo tumor characterization in PDAC patients.

Proteomic Analyses of Fibroblast- and Serum-Derived Exosomes Identify QSOX1 as a Marker for Non-invasive Detection of Colorectal Cancer.

Simple SummaryEarly diagnosis of colorectal cancer (CRC) is crucial to improve patient outcomes. The tumour microenvironment immediately adapts to malignant transformations, including the activation of fibroblasts in the connective tissue nearby. In this study, we investigated fibroblast activity-related protein secretion via extracellular vesicles (EVs). QSOX1, a protein identified to be significantly reduced in activated fibroblasts and derived EVs, was also found to be significantly reduced in circulating blood plasma EVs of CRC patients as compared to control patients. Hence, blood plasma EV-associated QSOX1 represents a promising platform for diagnostic CRC screening.The treatment of colorectal cancer (CRC) has improved during the last decades, but methods for crucial early diagnosis are yet to be developed. The influence of the tumour microenvironment on liquid biopsies for early cancer diagnostics are gaining growing interest, especially with emphasis on exosomes (EXO), a subgroup of extracellular vesicles (EVs). In this study, we established paired cancer-associated (CAFs) and normal fibroblasts (NF) from 13 CRC patients and investigated activation status-related protein abundance in derived EXOs. Immunohistochemical staining of matched patient tissue was performed and an independent test cohort of CRC patient plasma-derived EXOs was assessed by ELISA. A total of 11 differentially abundant EV proteins were identified between NFs and CAFs. In plasma EXOs, the CAF-EXO enriched protein EDIL3 was elevated, while the NF-EXO enriched protein QSOX1 was diminished compared to whole plasma. Both markers were significantly reduced in patient-matched CRC tissue compared to healthy colon tissue. In an independent test cohort, a significantly reduced protein abundance of QSOX1 was observed in plasma EXOs from CRC patients compared to controls and diagnostic ROC curve analysis revealed an AUC of 0.904. In conclusion, EXO-associated QSOX1 is a promising novel marker for early diagnosis and non-invasive risk stratification in CRC.

Long-term prognostic value of whole-heart coronary magnetic resonance angiography

BackgroundCoronary magnetic resonance angiography (CMRA) allows non-ionizing visualization of luminal narrowing in coronary artery disease (CAD). Although a prior study showed the usefulness of CMRA for risk stratification in short-term follow-up, the long-term prognostic value of CMRA remains unclear. The purpose of this study was to evaluate the long-term prognostic value of CMRA.MethodsA total of 506 patients without history of myocardial infarction or prior coronary artery revascularization underwent free-breathing whole-heart CMRA between 2009 and 2015. Images were acquired using a 1.5 T or 3 T scanner and visually evaluated as the consensus decisions of two observers. Obstructive CAD on CMRA was defined as luminal narrowing of ≥ 50% in at least one coronary artery. Major adverse cardiac events (MACE) comprised cardiac death, nonfatal myocardial infarction, and unstable angina.ResultsObstructive CAD on CMRA was observed in 214 patients (42%). During follow-up (median, 5.6 years), 31 MACE occurred. Kaplan–Meier curve analysis revealed a significant difference in event-free survival between patients with and without obstructive CAD for MACE (log-rank, p = 0.003) and cardiac death (p = 0.012). Annualized event rates for MACE in patients with no obstructive CAD, 1-vessel disease, 2-vessel disease, and left-main or 3-vessel disease were 0.6%, 1.5%, 2.3%, and 3.6%, respectively (log-rank, p = 0.003). Cox proportional hazard regression analysis showed that, among obstructive CAD on CMRA and clinical risk factors (age, sex, hypertension, diabetes, dyslipidemia, smoking, and family history of CAD), obstructive CAD and diabetes were significant predictors of MACE (hazard ratios, 2.9 [p = 0.005] and 2.2 [p = 0.034], respectively). In multivariate analysis, obstructive CAD remained an independent predictor (adjusted hazard ratio, 2.6 [p = 0.010]) after adjusting for diabetes. Addition of obstructive CAD to clinical risk factors significantly increased the global chi-square result from 8.3 to 13.8 (p = 0.022).ConclusionsIn long-term follow-up, free breathing whole heart CMRA allows non-invasive risk stratification for MACE and cardiac death and provides incremental prognostic value over conventional risk factors in patients without a history of myocardial infarction or prior coronary artery revascularization. The presence and severity of obstructive CAD detected by CMRA were associated with worse prognosis. Importantly, patients without obstructive CAD on CMRA displayed favorable prognosis.

Computed Tomography Coronary Angiography in Rural Referral Hospitals, A Single Centre Experience

Computed Tomography Coronary Angiography (CT-CA) is an established technology in non-invasive cardiac risk stratification [ [1] Hoffmann U. Truong Q. Schoenfeld D. Chou E. Woodard P. Nagurney J. et al. Coronary CT angiography versus standard evaluation in acute chest pain. N Engl J Med. 2012; 367: 299-308 Crossref PubMed Scopus (604) Google Scholar , [2] SCOT-HEART investigatorsCT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label, parallel-group, multicentre trial. Lancet. 2015; 385: 2383-2391 Abstract Full Text Full Text PDF PubMed Scopus (627) Google Scholar ]. Here, we describe the process of establishing the service in a single regional centre in North-Western New South Wales over the period of 9 months, during the COVID-19 pandemic.

De Novo Donor Specific Antibody and Long-Term Outcome After Liver Transplantation: A Systematic Review and Meta-Analysis.

BackgroundThe impact of de novo anti-HLA donor-specific alloantibodies (DSA) which develop after long-term liver transplantation (LT) remains controversial and unclear. The aim of this study was to investigate the role of de novo DSAs on the outcome in LT.MethodsWe did a systematic review and meta-analysis of observational studies published until Dec 31, 2019, that reported de novo DSA outcome data (≥1 year of follow-up) after liver transplant. A literature search in the MEDLINE/PubMed, EMBASE, Cochrane Library, Scopus and Web of Science Core Collection databases was performed.ResultsOf 5,325 studies identified, 15 fulfilled our inclusion criteria. The studies which reported 2016 liver transplant recipients with de novo DSAs showed an increased complication risk, i.e. graft loss and chronic rejection (OR 3.61; 95% CI 1.94–6.71, P < 0.001; I2 58.19%), and allograft rejection alone (OR 6.43; 95% CI: 3.17–13.04; P < 0.001; I2 49.77%); they were compared to patients without de novo DSAs. The association between de novo DSAs and overall outcome failure was consistent across all subgroups and sensitivity analysis.ConclusionsOur study suggested that de novo DSAs had a significant deleterious impact on the liver transplant risk of rejection. The routine detection of de novo DSAs may be beneficial as noninvasive biomarker-guided risk stratification.

Reducing Unnecessary Noninvasive Testing for Inpatients With Unstable Angina: The RUNIT Protocol

BackgroundRoutine inpatient transthoracic echocardiography (TTE) for patients with unstable angina is common, but it anecdotally adds little value to clinical care. A practice audit at our academic hospital demonstrated that 61.5% of patients with troponin-negative chest pain (TNCP) had normal left ventriculography (LVG) during coronary angiography and normal TTE on the same admission (duplicate testing). MethodsWe developed the Reducing Non-Invasive Testing (RUNIT) protocol, a clinical algorithm applied by clinical nurses to patient with TNCP. We performed a prospective assessment of rate of duplicate testing before and after intervention. If patients met certain simple clinical criteria, their TTE was cancelled (RUNIT positive). Patients then proceeded to have either coronary angiography with LVG or noninvasive risk stratification. We aimed to reduce duplicate testing by 25% over a 1-year period. Balancing measures included pathology on ordered TTEs, 30-day readmission, length of stay, and number of LVG. ResultsAmong 254 patients admitted with TNCP over 12 months, we reduced duplicate testing from 61.5% (before intervention) to 34% (P = 0.001). There was no clinical difference in 30-day readmission (0.9% vs 0.7%), and length of stay was significantly shorter in RUNIT positive (3.48 vs 4.16 days, P = 0.02). The majority of duplicate TTEs did not reveal any management-informing pathology. RUNIT-positive patients underwent more LVG than RUNIT-negative patients (78.3% vs 62.8%, P = 0.008). ConclusionWe achieved a sustained reduction in reflexive TTE ordering in patients with TNCP, and we discuss the potential of nursing-led interventions to address other areas of low value care in cardiology.