The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection.

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

The diagnostic value of sST2 for myocardial fibrosis in idiopathic inflammatory myopathies in subclinical stage of cardiac involvement.

OBJECTIVE: Myocardial fibrosis occurs in the early subclinical stage of cardiac involvement in idiopathic inflammatory myopathies (IIMs). Soluble suppression of tumorigenicity 2 (sST2) is known to have an immunomodulatory impact during autoimmune disease development. The current study investigated the diagnostic value of sST2 for myocardial fibrosis during early stage of cardiac involvement in IIM. METHODS: A total of 44 IIM patients with normal heart function and 32 age- and gender-matched healthy controls (HCs) were enrolled. Serum sST2 levels were measured by ELISA and cardiac magnetic resonance (CMR) parameters for myocardial fibrosis [native T1, extracellular volume (ECV), late-gadolinium enhancement (LGE)] and oedema (T2 values) were analysed. RESULTS: IIM patients had significantly higher sST2 levels than HCs [67.5 ng/ml (s.d. 30.4)] vs 14.4 (5.5), P < 0.001] and levels correlated positively with diffuse myocardial fibrosis parameters, native T1 (r = 0.531, P = 0.000), ECV (r = 0.371, P = 0.013) and focal myocardial fibrosis index and LGE (r = 0.339, P = 0.024) by Spearman's correlation analysis. sST2 was an independent predictive factor for diffuse and focal myocardial fibrosis after adjustment for age, gender, BMI and ESR. Risk increased ≈15.4% for diffuse [odds ratio (OR) 1.154 (95% CI 1.021, 1.305), P = 0.022] and 3.8% for focal [OR 1.038 (95% CI 1.006, 1.072), P = 0.020] myocardial fibrosis per unit increase of sST2. Cut-off values for diagnosing diffuse and focal myocardial fibrosis were sST2 ≥51.3 ng/ml [area under the curve (AUC) = 0.942, sensitivity = 85.7%, specificity = 98.9%, P < 0.001] and 53.3 ng/ml (AUC = 0.753, sensitivity = 87.5%, specificity = 58.3%, P < 0.01), respectively. CONCLUSION: sST2 showed a marked elevation during the subclinical stage of cardiac involvement in IIM and has potential as a biomarker for predicting diffuse and focal myocardial fibrosis in IIM.

The impact of type 2 diabetes mellitus on the clinical profile, myocardial fibrosis, and prognosis in non-ischemic dilated cardiomyopathy: a prospective cohort study.

BACKGROUND: The impact of the coexistence of type 2 diabetes mellitus (T2DM) in patients with non-ischemic dilated cardiomyopathy (DCM) on clinical profiles, myocardial fibrosis, and outcomes remain incompletely understood. METHOD: A total of 1152 patients diagnosed with non-ischemic DCM were prospectively enrolled from June 2012 to October 2021 and categorized into T2DM and non-T2DM groups. Clinical characteristics, cardiac function, and myocardial fibrosis evaluated by CMR were compared between the two groups. The primary endpoint included both all-cause mortality and heart transplantation. Cause of mortality was classified into heart failure death, sudden cardiac death, and non-cardiac death. Cox regression analysis and Kaplan-Meier analysis were performed to identify the association between T2DM and clinical outcomes. Propensity score matching (PSM) cohort including 438 patients was analyzed to reduce the bias from confounding covariates. RESULTS: Among the 1152 included DCM patients, 155 (13%) patients had T2DM. Patients with T2DM were older (55 ± 12 vs. 47 ± 14 years, P < 0.001), had higher New York Heart Association (NYHA) functional class (P = 0.003), higher prevalence of hypertension (37% vs. 21%, P < 0.001), atrial fibrillation (31% vs. 16%, P < 0.001), lower left ventricular (LV) ejection fraction (EF) (23 ± 9% vs. 27 ± 12%, P < 0.001), higher late gadolinium enhancement (LGE) presence (55% vs. 45%, P = 0.02), and significantly elevated native T1 (1323 ± 81ms vs. 1305 ± 73ms, P = 0.01) and extracellular volume fraction (ECV) (32.7 ± 6.3% vs. 31.3 ± 5.9%, P = 0.01) values. After a median follow-up of 38 months (interquartile range: 20-57 months), 239 patients reached primary endpoint. Kaplan-Meier analysis showed that patients with T2DM had worse clinical outcomes compared with those without T2DM in the overall cohort (annual events rate: 10.2% vs. 5.7%, P < 0.001). T2DM was independently associated with an increased risk of primary endpoint in the overall (Hazard ratio [HR]: 1.61, 95% CI: 1.13-2.33, P = 0.01) and PSM (HR: 1.54, 95% CI: 1.05-2.24, P = 0.02) cohorts. Furthermore, T2DM was associated with a higher risk of heart failure death (P = 0.006) and non-cardiac death (P = 0.02), but not sudden cardiac death (P = 0.16). CONCLUSIONS: Patients with T2DM represented a more severe clinical profile and experienced more adverse outcomes compared to those without T2DM in a large DCM cohort. TRIAL REGISTRATION: Trial registration number: ChiCTR1800017058; URL: https://www. CLINICALTRIALS: gov .

Liver T1 Mapping Derived From Cardiac Magnetic Resonance Imaging: A Potential Prognostic Marker in Idiopathic Dilated Cardiomyopathy.

BACKGROUND: Hepatic alterations are common aftereffects of heart failure (HF) and ventricular dysfunction. The prognostic value of liver injury markers derived from cardiac MRI studies in nonischemic dilated cardiomyopathy (DCM) patients is unclear. PURPOSE: Evaluate the prognostic performance of liver injury markers derived from cardiac MRI studies in DCM patients. STUDY TYPE: Prospective. POPULATION: Three hundred fifty-six consecutive DCM patients diagnosed according to ESC guidelines (age 48.7 ± 14.2 years, males 72.6%). FIELD STRENGTH/SEQUENCE: Steady-state free precession, modified Look-Locker inversion recovery T1 mapping and phase sensitive inversion recovery late gadolinium enhancement (LGE) sequences at 3 T. ASSESSMENT: Clinical characteristics, conventional MRI parameters (ventricular volumes, function, mass), native myocardial and liver T1, liver extracellular volume (ECV), and myocardial LGE presence were assessed. Patients were followed up for a median duration of 48.3 months (interquartile range 42.0-69.9 months). Primary endpoints included HF death, sudden cardiac death, heart transplantation, and HF readmission; secondary endpoints included HF death, sudden cardiac death, and heart transplantation. Models were developed to predict endpoints and the incremental value of including liver parameters assessed. STATISTICAL TESTS: Optimal cut-off value was determined using receiver operating characteristic curve and Youden method. Survival analysis was performed using Kaplan-Meier and Cox proportional hazard. Discriminative power of models was compared using net reclassification improvement and integrated discriminatory index. P value <0.05 was considered statistically significant. RESULTS: 47.2% patients reached primary endpoints; 25.8% patients reached secondary endpoints. Patients with elevated liver ECV (cut-off 34.4%) had significantly higher risk reaching primary and secondary endpoints. Cox regression showed liver ECV was an independent prognostic predictor, and showed independent prognostic value for primary endpoints and long-term HF readmission compared to conventional clinical and cardiac MRI parameters. DATA CONCLUSIONS: Liver ECV is an independent prognostic predictor and may serve as an innovative approach for risk stratification for DCM. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Prognostic value of mid-term cardiovascular magnetic resonance follow-up in patients with non-ischemic dilated cardiomyopathy: a prospective cohort study.

BACKGROUND: The prognostic value of follow-up cardiovascular magnetic resonance (CMR) in dilated cardiomyopathy (DCM) patients is unclear. We aimed to investigate the prognostic value of cardiac function, structure, and tissue characteristics at mid-term CMR follow-up. METHODS: The study population was a prospectively enrolled cohort of DCM patients who underwent guideline-directed medical therapy with baseline and follow-up CMR, which included measurement of biventricular volume and ejection fraction, late gadolinium enhancement, native T1, native T2, and extracellular volume. During follow-up, major adverse cardiac events (MACE) were defined as a composite endpoint of cardiovascular death, heart transplantation, and heart-failure readmission. RESULTS: Among 235 DCM patients (median CMR interval: 15.3 months; interquartile range: 12.5-19.2 months), 54 (23.0%) experienced MACE during follow-up (median: 31.2 months; interquartile range: 20.8-50.0 months). In multivariable Cox regression, follow-up CMR models showed significantly superior predictive value than baseline CMR models. Stepwise multivariate Cox regression showed that follow-up left ventricular ejection fraction (LVEF; hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.91-0.96; p < 0.001) and native T1 (HR, 1.01; 95% CI, 1.00-1.01; p = 0.030) were independent predictors of MACE. Follow-up LVEF ≥ 40% or stable LVEF < 40% with T1 ≤ 1273 ms indicated low risk (annual event rate < 4%), while stable LVEF < 40% and T1 > 1273 ms or LVEF < 40% with deterioration indicated high risk (annual event rate > 15%). CONCLUSIONS: Follow-up CMR provided better risk stratification than baseline CMR. Improvements in the LVEF and T1 mapping are associated with a lower risk of MACE.

Triage in major incidents: development and external validation of novel machine learning-derived primary and secondary triage tools.

BACKGROUND: Major incidents (MIs) are an important cause of death and disability. Triage tools are crucial to identifying priority 1 (P1) patients-those needing time-critical, life-saving interventions. Existing expert opinion-derived tools have limited evidence supporting their use. This study employs machine learning (ML) to develop and validate models for novel primary and secondary triage tools. METHODS: Adults (16+ years) from the UK Trauma Audit and Research Network (TARN) registry (January 2008-December 2017) served as surrogates for MI victims, with P1 patients identified using predefined criteria. The TARN database was split chronologically into model training and testing (70:30) datasets. Input variables included physiological parameters, age, mechanism and anatomical location of injury. Random forest, extreme gradient boosted tree, logistic regression and decision tree models were trained to predict P1 status, and compared with existing tools (Battlefield Casualty Drills (BCD) Triage Sieve, CareFlight, Modified Physiological Triage Tool, MPTT-24, MSTART, National Ambulance Resilience Unit Triage Sieve and RAMP). Primary and secondary candidate models were selected; the latter was externally validated on patients from the UK military's Joint Theatre Trauma Registry (JTTR). RESULTS: Models were internally tested in 57 979 TARN patients. The best existing tool was the BCD Triage Sieve (sensitivity 68.2%, area under the receiver operating curve (AUC) 0.688). Inability to breathe spontaneously, presence of chest injury and mental status were most predictive of P1 status. A decision tree model including these three variables exhibited the best test characteristics (sensitivity 73.0%, AUC 0.782), forming the candidate primary tool. The proposed secondary tool (sensitivity 77.9%, AUC 0.817), applicable via a portable device, includes a fourth variable (injury mechanism). This performed favourably on external validation (sensitivity of 97.6%, AUC 0.778) in 5956 JTTR patients. CONCLUSION: Novel triage tools developed using ML outperform existing tools in a nationally representative trauma population. The proposed primary tool requires external validation prior to consideration for practical use. The secondary tool demonstrates good external validity and may be used to support decision-making by healthcare workers responding to MIs.

Cardiac MRI to Predict Sudden Cardiac Death Risk in Dilated Cardiomyopathy.

Background Sudden cardiac death (SCD) is one of the leading causes of death in individuals with nonischemic dilated cardiomyopathy (DCM). However, the risk stratification of SCD events remains challenging in clinical practice. Purpose To determine whether myocardial tissue characterization with cardiac MRI could be used to predict SCD events and to explore a SCD stratification algorithm in nonischemic DCM. Materials and Methods In this prospective single-center study, adults with nonischemic DCM who underwent cardiac MRI between June 2012 and August 2020 were enrolled. SCD-related events included SCD, appropriate implantable cardioverter-defibrillator shock, and resuscitation after cardiac arrest. Competing risk regression analysis and Kaplan-Meier analysis were performed to identify the association of myocardial tissue characterization with outcomes. Results Among the 858 participants (mean age, 48 years; age range, 18-83 years; 603 men), 70 (8%) participants experienced SCD-related events during a median follow-up of 33.0 months. In multivariable competing risk analysis, late gadolinium enhancement (LGE) (hazard ratio [HR], 1.87; 95% CI: 1.07, 3.27; P = .03), native T1 (per 10-msec increase: HR, 1.07; 95% CI: 1.04, 1.11; P < .001), and extracellular volume fraction (per 3% increase: HR, 1.26; 95% CI: 1.11, 1.44; P < .001) were independent predictors of SCD-related events after adjustment of systolic blood pressure, atrial fibrillation, and left ventricular ejection fraction. An SCD risk stratification category was developed with a combination of native T1 and LGE. Participants with a native T1 value 4 or more SDs above the mean (1382 msec) had the highest annual SCD-related events rate of 9.3%, and participants with a native T1 value 2 SDs below the mean (1292 msec) and negative LGE had the lowest rate of 0.6%. This category showed good prediction ability (C statistic = 0.74) and could be used to discriminate SCD risk and competing heart failure risk. Conclusion Myocardial tissue characteristics derived from cardiac MRI were independent predictors of sudden cardiac death (SCD)-related events in individuals with nonischemic dilated cardiomyopathy and could be used to stratify participants according to different SCD risk categories. Clinical trial registration no. ChiCTR1800017058 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sakuma in this issue.

CACONET: a novel classification framework for microbial correlation networks.

MOTIVATION: Existing microbiome-based disease prediction relies on the ability of machine learning methods to differentiate disease from healthy subjects based on the observed taxa abundance across samples. Despite numerous microbes have been implicated as potential biomarkers, challenges remain due to not only the statistical nature of microbiome data but also the lack of understanding of microbial interactions which can be indicative of the disease. RESULTS: We propose CACONET (classification of Compositional-Aware COrrelation NETworks), a computational framework that learns to classify microbial correlation networks and extracts potential signature interactions, taking as input taxa relative abundance across samples and their health status. By using Bayesian compositional-aware correlation inference, a collection of posterior correlation networks can be drawn and used for graph-level classification, thus incorporating uncertainty in the estimates. CACONET then employs a deep learning approach for graph classification, achieving excellent performance metrics by exploiting the correlation structure. We test the framework on both simulated data and a large real-world dataset pertaining to microbiome samples of colorectal cancer (CRC) and healthy subjects, and identify potential network substructure characteristic of CRC microbiota. CACONET is customizable and can be adapted to further improve its utility. AVAILABILITY AND IMPLEMENTATION: CACONET is available at https://github.com/yuanwxu/corr-net-classify. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Predictive Value of Myocardial Native T1 Mapping Radiomics in Dilated Cardiomyopathy: A Study in a Chinese Population.

BACKGROUND: Investigation of the factors influencing dilated cardiomyopathy (DCM) prognosis is important as it could facilitate risk stratification and guide clinical decision-making. PURPOSE: To assess the prognostic value of magnetic resonance imaging (MRI) radiomics analysis of native T1 mapping in DCM. STUDY TYPE: Prospective. SUBJECTS: Three hundred and thirty consecutive patients with non-ischemic DCM (mean age 48.42 ± 14.20 years, 247 males). FIELD STRENGTH/SEQUENCE: Balanced steady-state free precession and modified Look-Locker inversion recovery T1 mapping sequences at 3 T. ASSESSMENT: Clinical characteristics, conventional MRI parameters (ventricular volumes, function, and mass), native myocardial T1, and radiomics features extracted from native T1 mapping were obtained. The study endpoint was defined as all-cause mortality or heart transplantation. Models were developed based on 1) clinical data; 2) radiomics data based on T1 mapping; 3) clinical and conventional MRI data; 4) clinical, conventional MRI, and native T1 data; and 5) clinical, conventional MRI, and radiomics T1 mapping data. Each prediction model was trained according to follow-up results with AdaBoost, random forest, and logistic regression classifiers. STATISTICAL TESTS: The predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1 score by 5-fold cross-validation. RESULTS: During a median follow-up of 53.5 months (interquartile range, 41.6-69.5 months), 77 patients with DCM experienced all-cause mortality or heart transplantation. The random forest model based on radiomics combined with clinical and conventional MRI parameters achieved the best performance, with AUC and F1 score of 0.95 and 0.89, respectively. DATA CONCLUSION: A machine-learning framework based on radiomics analysis of T1 mapping prognosis prediction in DCM. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Pulmonary Transit Time Derived from First-Pass Perfusion Cardiac MR Imaging: A Potential New Marker for Cardiac Involvement and Prognosis in Light-Chain Amyloidosis.

BACKGROUND: First-pass perfusion cardiac MR imaging could reflect pulmonary hemodynamics. However, the clinical value of pulmonary transit time (PTT) derived from first-pass perfusion MRI in light-chain (AL) amyloidosis requires further evaluation. PURPOSE: To assess the clinical and prognostic value of PTT in patients with AL amyloidosis. STUDY TYPE: Prospective observational study. POPULATION: 226 biopsy-proven systemic AL amyloidosis patients (age 58.62 ± 10.10 years, 135 males) and 43 healthy controls (age 42 ± 16.2 years, 20 males). FIELD STRENGTH/SEQUENCE: SSFP cine and phase sensitive inversion recovery late gadolinium enhancement (LGE) sequences, and multislice first-pass myocardial perfusion imaging with a saturation recovery turbo fast low-angle shot (SR-TurboFLASH) pulse sequence at 3.0T. ASSESSMENT: PTT was measured as the time interval between the peaks of right and left ventricular cavity arterial input function curves on first-pass perfusion MR images. STATISTICAL TESTS: Independent-sample t test, Mann-Whitney U test, Chi-square test, Fisher's exact test, analysis of variance, or Kruskal-Wallis test, as appropriate; univariable and multivariable Cox proportional hazards models and Kaplan-Meier curves, area under receiver operating characteristic curve were used to determine statistical significance. RESULTS: PTT could differentiate AL amyloidosis patients with (N = 188) and without (N = 38) cardiac involvement (area under the curve [AUC] = 0.839). During a median follow-up of 35 months, 160 patients (70.8%) demonstrated all-cause mortality. After adjustments for clinical (Hazard ratio [HR] 1.061, confidence interval [CI]: 1.021-1.102), biochemical (HR 1.055, CI: 1.014-1.097), cardiac MRI-derived (HR 1.077, CI: 1.034-1.123), and therapeutic (HR 1.063, CI: 1.024-1.103) factors, PTT predicted mortality independently in patients with AL amyloidosis. Finally, PTT could identify worse outcomes in patients demonstrating New York Heart Association class III, Mayo 2004 stage III, and transmural LGE pattern. DATA CONCLUSION: PTT may serve as a new imaging predictor of cardiac involvement and prognosis in AL amyloidosis. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Multiparametric mapping by cardiovascular magnetic resonance imaging in cardiac tumors.

BACKGROUND: There is a paucity of quantitative measurements of cardiac tumors and myocardium using parametric mapping techniques. This study aims to explore quantitative characteristics and diagnostic performance of native T1, T2, and extracellular volume (ECV) values of cardiac tumors and left ventricular (LV) myocardium. METHODS: Patients with suspected cardiac tumors who underwent cardiovascular magnetic resonance (CMR) between November 2013 and March 2021 were prospectively enrolled. The diagnoses of primary benign or malignant tumors were based on pathologic findings if available, comprehensive medical history evaluations, imaging, and long-term follow-up data. Patients with pseudo-tumors, cardiac metastasis, primary cardiac diseases, and prior radiotherapy or chemotherapy were excluded. Multiparametric mapping values were measured on both cardiac tumors and the LV myocardium. Statistical analyses were performed using independent-samples t-test, receiver operating characteristic, and Bland-Altman analyses. RESULTS: A total of 80 patients diagnosed with benign (n = 54), or primary malignant cardiac tumors (n = 26), and 50 age and sex-matched healthy volunteers were included. Intergroup differences in the T1 and T2 values of cardiac tumors were not significant, however, patients with primary malignant cardiac tumors showed significantly higher mean myocardial T1 values (1360 ± 61.4 ms) compared with patients with benign tumors (1259.7 ± 46.2 ms), and normal controls (1206 ± 44.0 ms, all P < 0.05) at 3 T. Patients with primary malignant cardiac tumors also showed significantly higher mean ECV (34.6 ± 5.2%) compared with patients with benign (30.0 ± 2.5%) tumors, and normal controls (27.3 ± 3.0%, all P < 0.05). For the differentiation between primary malignant and benign cardiac tumors, the mean myocardial native T1 value showed the highest efficacy (AUC: 0.919, cutoff value: 1300 ms) compared with mean ECV (AUC: 0.817) and T2 (AUC: 0.619) values. CONCLUSION: Native T1 and T2 of cardiac tumors showed high heterogeneity, while myocardial native T1 values in primary malignant cardiac tumors were elevated compared to patients with benign cardiac tumors, which may serve as a new imaging marker for primary malignant cardiac tumors.

Left Atrial Function Predicts Outcome in Dilated Cardiomyopathy: Fast Long-Axis Strain Analysis Derived from MRI.

Background There is increasing recognition that left atrial (LA) function is prognostically important in cardiovascular disease. LA strain is a sensitive parameter to describe complex LA phasic function. However, the prognostic value of LA strain in participants with idiopathic dilated cardiomyopathy (DCM) remains unclear. Purpose To evaluate the prognostic value of LA strain derived from cardiac MRI in study participants with idiopathic DCM. Materials and Methods Participants with idiopathic DCM who underwent cardiac MRI between June 2012 and November 2018 were prospectively enrolled. The fast long-axis strain MRI method was performed to assess LA strain. The primary end point was all-cause mortality and heart transplant, and the secondary end point was a combination of primary end point, heart failure readmission, and aborted sudden cardiac death. Cox regression analyses and Kaplan-Meier survival analysis were performed to identify the association between variables and outcomes. Results There were 497 participants (mean age, 47 years ± 14 [standard deviation]; 357 men) evaluated. During a median follow-up of 36 months (interquartile range, 26-54 months), 113 participants reached primary end points and 203 participants reached secondary end points. LA reservoir, conduit and booster strain, and strain rate were lower in participants with primary end points (P < .001). In multivariable Cox regression analysis, LA reservoir strain and conduit strain were independent predictors for primary end point (hazard ratio [HR] per 1% increase, 0.95 [95% CI: 0.91, 0.99; P = .008] and 0.92 [95% CI: 0.87, 0.98; P = .010], respectively) and secondary end points (HR per 1% increase, 0.95 [95% CI: 0.93, 0.97; P < .001] and 0.93 [95% CI: 0.89, 0.97; P < .001], respectively). In addition, LA reservoir strain and conduit strain added incremental prognostic value to clinical risk factors and late gadolinium enhancement presence (all, P < .05). Conclusion Left atrial reservoir and conduit strain, derived from cardiac MRI by using the fast long-axis method, were independent predictors of adverse clinical outcomes in idiopathic dilated cardiomyopathy. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Ambale-Venkatesh in this issue.

Optimized data-independent acquisition approach for proteomic analysis at single-cell level.

BACKGROUND: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

Prognostic value of right atrial strain derived from cardiovascular magnetic resonance in non-ischemic dilated cardiomyopathy.

BACKGROUND: The value of right atrial (RA) function in cardiovascular diseases is currently limited. This study was to explore the prognostic value of RA strain derived from fast long axis method by cardiovascular magnetic resonance (CMR) in patients with non-ischemic dilated cardiomyopathy (DCM). METHODS: We prospectively enrolled patients with DCM who underwent CMR from June 2012 to March 2019 and 120 age- and sex-matched healthy subjects. Fast long-axis strain method was performed to assess the RA phasic function including RA reservoir strain, conduit strain, and booster strain. The predefined primary endpoint was all-cause mortality. The composite heart failure (HF) endpoint included HF death, HF readmission, and heart transplantation. Cox regression analysis and Kaplan-Meier survival curve were performed to describe the association between RA strain and outcomes. RESULTS: A total of 624 patients (444 men, mean 48 years) were studied. After a median follow-up of 32.5 months, 116 patients (18.6%) experienced all-cause mortality and 205 patients (32.9%) reached composite HF endpoint. RA function was impaired in DCM patients compared with healthy subjects (all P < 0.001). After adjustment for covariates, RA reservoir strain [hazard ratio (HR) (per 5% decrease) 1.19, 95% confidence interval (CI) 1.03-1.37, P = 0.022] and conduit strain [HR (per 5% decrease) 1.37, 95% CI 1.03-1.84, P = 0.033] were independent predictors of all-cause mortality. Moreover, RA strain added incremental prognostic value for the prediction of adverse cardiac events over baseline clinical and CMR predictors (all P < 0.05). CONCLUSION: RA strain by fast long-axis analysis is independently associated with adverse clinical outcomes in patients with DCM. TRIAL REGISTRATION: Trial registration number: ChiCTR1800017058; Date of registration: 2018-07-10 (Retrospective registration); URL: https://www. CLINICALTRIALS: gov.

Cardiovascular magnetic resonance characterization of rheumatic mitral stenosis: findings from three worldwide endemic zones.

BACKGROUND: Cardiac remodeling in rheumatic mitral stenosis (MS) is complex and incompletely understood. The objective of this study was to evaluate cardiac structural and functional changes in a cohort of patients with rheumatic MS using cardiovascular magnetic resonance (CMR). METHODS: This retrospective study included 40 patients with rheumatic MS, consisting of 19 patients from India, 15 patients from China, and 6 patients from Mexico (median (interquartile range (IQR)) age: 45 years (34-55); 75% women). Twenty patients were included in the control group. CMR variables pertaining to morphology and function were collected. Late gadolinium enhancement (LGE) sequences were acquired for tissue characterization. Statistical analyses were performed using the Kruskal-Wallis test and the chi-square test. RESULTS: Compared to the control group, patients with MS had lower left ventricular (LV) ejection fraction (51% (42%-55%) vs 60% (57%-65%), p < 0.001), lower right ventricular (RV) ejection fraction (44% (40%-52%) vs 64% (59%-67%), p < 0.001), higher RV end-diastolic volume (72 (58-87) mL/m2 vs 59 (49-69) mL/m2, p = 0.003), larger left atrial volume (87 (67-108) mL/m2 vs 29 (22-34) mL/m2, p < 0.001), and right atrial areas (20 (16-23) cm2 vs 13 (12-16) cm2, p < 0.001). LGE was prevalent in patients with rheumatic MS (82%), and was commonly located at the RV insertion sites. Furthermore, the patient cohorts from India, China, and Mexico were heterogeneous in terms of baseline characteristics and cardiac remodeling. CONCLUSION: Our findings demonstrated that biventricular dysfunction, right and left atrial remodeling, and LGE at the RV insertion sites are underappreciated in contemporary rheumatic MS. Further studies are needed to elucidate the prognostic implications of these findings.

Fractal Analysis: Prognostic Value of Left Ventricular Trabecular Complexity Cardiovascular MRI in Participants with Hypertrophic Cardiomyopathy.

Background The prognostic value of myocardial trabecular complexity in patients with hypertrophic cardiomyopathy (HCM) is unknown. Purpose To explore the prognostic value of myocardial trabecular complexity using fractal analysis in participants with HCM. Materials and Methods The authors prospectively enrolled participants with HCM who underwent 3.0-T cardiovascular MRI from August 2011 to October 2017. The authors also enrolled 100 age- and sex-matched healthy participants to form a comparison group. Trabeculae were quantified with fractal analysis of cine slices to estimate the fractal dimension (FD). Participants with HCM were divided into normal and high FD groups according to the upper limit of normal reference value from the healthy group. The primary end point was defined as all-cause mortality and aborted sudden cardiac death. The secondary end point was the composite of the primary end point and readmission to the hospital owing to heart failure. Internal validation was performed using the bootstrapping method. Results A total of 378 participants with HCM (median age, 50 years; age range, 40-61 years; 207 men) and 100 healthy participants (median age, 46 years; age range, 36-59 years; 55 women) were included in this study. During the median follow-up of 33 months ± 18 (standard deviation), the increased maximal apical FD (≥1.325) had a higher risk of the primary and secondary end points than those with a normal FD (<1.325) (P = .01 and P = .04, respectively). Furthermore, Cox analysis revealed that left ventricular maximal apical FD (hazard ratio range, 1.001-1.008; all P < .05) provided significant prognostic value to predict the primary and secondary end points after adjustment for the European Society of Cardiology predictors and late gadolinium enhancement. Internal validation showed that left ventricular maximal apical FD retained a good performance in predicting the primary end points with an area under the curve of 0.70 ± 0.03. Conclusion Left ventricular apical fractal dimension, which reflects myocardial trabecular complexity, was an independent predictor of the primary and secondary end points in patients with hypertrophic cardiomyopathy. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Captur and Moon in this issue.

Prognostic value of myocardial extracellular volume fraction evaluation based on cardiac magnetic resonance T1 mapping with T1 long and short in hypertrophic cardiomyopathy.

OBJECTIVE: To investigate the prognostic significance of T1 mapping using T1 long and short in hypertrophic cardiomyopathy (HCM) patients. METHODS: A total of 263 consecutive patients with HCM referred for cardiovascular magnetic resonance (CMR) imaging were enrolled in this study. The imaging protocol consisted of cine, late gadolinium enhancement (LGE), and T1 mapping with T1 long and short. All patients were followed up prospectively. Outcome events were divided into the primary and secondary endpoint events. Primary endpoint events included cardiac death, heart transplant, aborted sudden death, and cardiopulmonary resuscitation after syncope. The secondary endpoint event was defined as unplanned rehospitalization for heart failure. RESULT: The average follow-up duration was 28.3 ± 12.1 (range: 1-78) months. In all, 17 patients (7.0%) experienced a primary endpoint including 13 cardiovascular deaths, three aborted sudden deaths, and one resuscitation after syncope, and 34 patients experienced a secondary endpoint. Patients with primary endpoints showed a trend towards more extensive LGE (p < 0.001), significantly higher ECV (p < 0.001), and native T1 (p = 0.028) than those without events. In multivariate Cox regression analysis, ECV was independently associated with primary and secondary endpoints (p < 0.001 and p = 0.047, respectively). For every 3% increase, ECV portended a 1.374-fold increase risk of a primary endpoint occurring (p < 0.001). In the Kaplan-Meier survival analysis, the incidence of primary and secondary endpoint events was significantly higher in HCM with increased ECV (p < 0.001 and p = 0.009, respectively). CONCLUSION: In patients with HCM, ECV is a strong imaging marker for predicting adverse outcome. KEY POINTS: • ECV is a potent imaging index which has a strong correlation with LVEF and LVEDVI and can evaluate myocardial tissue structure and function. • ECV and LGE can provide a prognostic value in patients with hypertrophic cardiomyopathy. • ECV has stronger predictive effectiveness than LGE; even in the subgroup with LGE, ECV shows independent predictive significance for adverse events.

Phenotyping of myocardial involvement by cardiac magnetic resonance in idiopathic inflammatory myopathies.

OBJECTIVES: Cardiac dysfunction is commonly noted in patients with idiopathic inflammatory myopathies (IIMs). This study aimed to investigate the characteristics of cardiac dysfunction using cardiac magnetic resonance (CMR) in polymyositis (PM), dermatomyositis (DM) and necrotising myositis (NM). METHODS: Fifty-one patients with IIMs and 20 matched healthy controls (HCs) were assessed using CMR examination. The clinical data, cardiac serum markers and autoimmune antibodies were determined for all patients. Cardiac involvement was identified by myocardial native T1, extracellular volume (ECV), late gadolinium enhancement (LGE) and left ventricular ejection fraction (LVEF). RESULTS: Different subtypes of IIMs showed different patterns of LGE and varying degrees of myocardial damage. The PM subgroup showed higher native T1 (p = 0.010) and ECV (p = 0.000) than the HCs. The prevalence of LGE was comparable between the PM and DM subgroups (40.0% vs. 31.6%, p = 0.741); however, it was higher in the PM subgroup than in the NM subgroup (40% vs. 0.0%, p = 0.014). Patients with positive LGE in the PM subgroup showed a higher proportion of positive LGE (p = 0.018) and lower LVEF (p = 0.024) than those with positive LGE in the DM subgroup. In multivariate analysis, the presence of LGE could be predicted by increased NT-proBNP (p = 0.036, OR = 1.001) and anti-MDA-5 antibody positivity (p = 0.011, OR = 12.4). The risk factors associated with native T1 were NT-proBNP (p = 0.016, ß = 0.353) and body mass index (BMI) (p = 0.024, ß = - 0.331). CONCLUSIONS: Distinct cardiac involvements in different subtypes of IIMs were identified using CMR. Elevated NT-proBNP and a low BMI were the risk factors associated with LGE and elevated native T1. KEY POINTS: • The characteristics of cardiac involvement in different subtypes of IIMs could be identified with cardiac magnetic resonance. • The NT-proBNP levels could reflect focal and diffuse myocardial damage in patients with IIMs.

Prognostic value of fast semi-automated left atrial long-axis strain analysis in hypertrophic cardiomyopathy.

BACKGROUND: The prognostic value of left atrial (LA) size and function in hypertrophic cardiomyopathy (HCM) is well recognized, but LA function is difficult to routinely analyze. Fast LA long-axis strain (LA-LAS) analysis is a novel technique to assess LA function on cine cardiovascular magnetic resonance (CMR). We aimed to assess the association between fast LA-LAS and adverse clinical outcomes in patients with HCM. METHODS: 359 HCM patients and 100 healthy controls underwent routine CMR imaging. Fast LA-LAS was analyzed by automatically tracking the length between the midpoint of posterior LA wall and the left atrioventricular junction based on standard 2- and 4-chamber balanced steady-state free precession cine-CMR. Three strain parameters including reservoir strain (εs), conduit strain (εe), and active strain (εa) were assessed. The endpoint was set as composite adverse events including cardiovascular death, resuscitated cardiac arrest, sudden cardiac death aborted by appropriate implantable cardioverter-defibrillator discharge, and hospital admission related to heart failure. RESULTS: During an average follow-up of 40.9 months, 59 patients (19.7%) reached endpoints. LA strains were correlated with LA diameter, LA volume index (LAVI) and LA empty fraction (LAEF) (all p < 0.05). In the stepwise multivariate Cox regression analysis, εs and εe (hazard ratio, 0.94 and 0.89; p = 0.019 and 0.006, respectively) emerged as independent predictors of the composite adverse events. Fast LA εs and LA εe are stronger prognostic factors than LA size, LAVI and the presence of left ventricular late gadolinium enhancement. CONCLUSIONS: Fast LA reservoir and conduit strains are independently associated with adverse outcomes in HCM.

Comparative analysis of major incident triage tools in children: a UK population-based analysis.

INTRODUCTION: Triage is a key principle in the effective management of major incidents. There is currently a paucity of evidence to guide the triage of children. The aim of this study was to perform a comparative analysis of nine adult and paediatric triage tools, including the novel 'Sheffield Paediatric Triage Tool' (SPTT), assessing their ability in identifying patients needing life-saving interventions (LSIs). METHODS: A 10-year (2008-2017) retrospective database review of the Trauma Audit Research Network (TARN) Database for paediatric patients (<16 years) was performed. Primary outcome was identification of patients receiving one or more LSIs from a previously defined list. Secondary outcomes included mortality and prediction of Injury Severity Score (ISS) >15. Primary analysis was conducted on patients with complete prehospital physiological data with planned secondary analyses using first recorded data. Performance characteristics were evaluated using sensitivity, specificity, undertriage and overtriage. RESULTS: 15 133 patients met TARN inclusion criteria. 4962 (32.8%) had complete prehospital physiological data and 8255 (54.5%) had complete first recorded physiological data. The majority of patients were male (69.5%), with a median age of 11.9 years. The overwhelming majority of patients (95.4%) sustained blunt trauma, yielding a median ISS of 9 and overall, 875 patients (17.6%) received at least one LSI. The SPTT demonstrated the greatest sensitivity of all triage tools at identifying need for LSI (92.2%) but was associated with the highest rate of overtriage (75.0%). Both the Paediatric Triage Tape (sensitivity 34.1%) and JumpSTART (sensitivity 45.0%) performed less well at identifying LSI. By contrast, the adult Modified Physiological Triage Tool-24 (MPTT-24) triage tool had the second highest sensitivity (80.8%) with tolerable rates of overtriage (70.2%). CONCLUSION: The SPTT and MPTT-24 outperform existing paediatric triage tools at identifying those patients requiring LSIs. This may necessitate a change in recommended practice. Further work is needed to determine the optimum method of paediatric major incident triage, but consideration should be given to simplifying major incident triage by the use of one generic tool (the MPTT-24) for adults and children.