Citations

BACKGROUND: Dilated cardiomyopathy (DCM) is a major cause of heart failure and carries a high mortality rate. Myocardial recovery in DCM-related heart failure patients is highly variable, with some patients having little or no response to standard drug therapy. A genome-wide association study may agnostically identify biomarkers and provide novel insight into the biology of myocardial recovery in DCM. METHODS: A genome-wide association study for change in left ventricular ejection fraction was performed in 686 White subjects with recent-onset DCM who received standard pharmacotherapy. Genome-wide association study signals were subsequently functionally validated and studied in relevant cellular models to understand molecular mechanisms that may have contributed to the change in left ventricular ejection fraction. RESULTS: The genome-wide association study identified a highly suggestive locus that mapped to the 5′-flanking region of the CDCP1 (CUB [complement C1r/C1s, Uegf, and Bmp1] domain containing protein 1) gene (rs6773435; P =7.12×10 −7 ). The variant allele was associated with improved cardiac function and decreased CDCP1 transcription. CDCP1 expression was significantly upregulated in human cardiac fibroblasts (HCFs) in response to the PDGF (platelet-derived growth factor) signaling, and knockdown of CDCP1 significantly repressed HCF proliferation and decreased AKT (protein kinase B) phosphorylation. Transcriptomic profiling after CDCP1 knockdown in HCFs supported the conclusion that CDCP1 regulates HCF proliferation and mitosis. In addition, CDCP1 knockdown in HCFs resulted in significantly decreased expression of soluble ST2 (suppression of tumorigenicity-2), a prognostic biomarker for heart failure and inductor of cardiac fibrosis. CONCLUSIONS: CDCP1 may play an important role in myocardial recovery in recent-onset DCM and mediates its effect primarily by attenuating cardiac fibrosis.

AbstractBackgroundInaccurate manual organ delineation is one of the high‐risk failure modes in radiation treatment. Numerous automated contour quality assurance (QA) systems have been developed to assess contour acceptability; however, manual inspection of flagged cases is a time‐consuming and challenging process, and can lead to users overlooking the exact error location.PurposeOur aim is to develop and validate a contour QA system that can effectively detect and visualize subregional contour errors, both qualitatively and quantitatively.Methods/MaterialsA novel contour subregion error detection (CSED) system was developed using subregional surface distance discrepancies between manual and deep learning auto‐segmentation (DLAS) contours. A validation study was conducted using a head and neck public dataset containing 339 cases and evaluated according to knowledge‐based pass criteria derived from a clinical training dataset of 60 cases. A blind qualitative evaluation was conducted, comparing the results from the CSED system with manual labels. Subsequently, the CSED‐flagged cases were re‐examined by a radiation oncologist.ResultsThe CSED system could visualize the diverse types of subregional contour errors qualitatively and quantitatively. In the validation dataset, the CSED system resulted in true positive rates (TPR) of 0.814, 0.800, and 0.771; false positive rates (FPR) of 0.310, 0.267, and 0.298; and accuracies of 0.735, 0.759, and 0.730, for brainstem and left and right parotid contours, respectively. The CSED‐assisted manual review caught 13 brainstem, 19 left parotid, and 21 right parotid contour errors missed by conventional human review. The TPR/FPR/accuracy of the CSED‐assisted manual review improved to 0.836/0.253/0.784, 0.831/0.171/0.830, and 0.808/0.193/0.807 for each structure, respectively. Further, the time savings achieved through CSED‐assisted review improved by 75%, with the time for review taking 24.81 ± 12.84, 26.75 ± 10.41, and 28.71 ± 13.72 s for each structure, respectively.ConclusionsThe CSED system enables qualitative and quantitative detection, localization, and visualization of manual segmentation subregional errors utilizing DLAS contours as references. The use of this system has been shown to help reduce the risk of high‐risk failure modes resulting from inaccurate organ segmentation.

BACKGROUND: Common genetic variants are associated with risk for hypertrophic cardiomyopathy and dilated cardiomyopathy and with left ventricular (LV) traits. Whether these variants are associated with myocardial fibrosis, an important pathophysiological mediator of cardiomyopathy, is unknown. METHODS: Multi-Ethnic Study of Atherosclerosis participants with T1-mapping cardiac magnetic resonance imaging in-whom extracellular volume was assessed, and genotyping information was available were included (N=1255). Log extracellular volume (%) was regressed on 50 candidate single nucleotide polymorphisms (previously identified to be associated with hypertrophic cardiomyopathy, dilated cardiomyopathy, and LV traits) adjusting for age, sex, diabetes, blood pressure, and principal components of ancestry. Ancestry-specific results were pooled by fixed-effect meta-analyses. Gene knockdown experiments were performed in human cardiac fibroblasts. RESULTS: The SMARCB1 rs2186370 intronic variant (minor allele frequency: 0.18 in White and 0.50 in Black participants), previously identified as a risk variant for dilated cardiomyopathy and hypertrophic cardiomyopathy, was significantly associated with increased extracellular volume ( P= 0.0002) after adjusting for confounding clinical variables. The SMARCB1 rs2070458 locus previously associated with increased LV wall thickness and mass was similarly significantly associated with increased extracellular volume ( P= 0.0002). The direction of effect was similar in all 4 ancestry groups, but the effect was strongest in Black participants. The variants are strong expression quantitative loci in human LV tissue and associated with genotype-dependent decreased expression of SMARCB1 ( P= 7.3×10 -22 ). SMARCB1 knockdown in human cardiac fibroblasts resulted in increased TGF (transforming growth factor)-β1–mediated α-smooth muscle actin and collagen expression. CONCLUSIONS: Common genetic variation in SMARCB1 previously associated with risk for cardiomyopathies and increased LV wall thickness is associated with increased cardiac magnetic resonance imaging–based myocardial fibrosis and increased TGF-β1 mediated myocardial fibrosis in vitro. Whether these findings suggest a pathophysiologic link between myocardial fibrosis and cardiomyopathy risk remains to be proven.

Introduction: Genome-wide association studies have identified common genetic variants associated with hypertrophic (HCM) and dilated cardiomyopathy (DCM) and left ventricular (LV) characteristics. However, the association of these variants with myocardial fibrosis (MF), an important pathophysiological mediator of cardiomyopathy, is unknown. Hypothesis: We used the Multi-Ethnic Study of Atherosclerosis (MESA), to evaluate the association of these loci with interstitial MF measured by cardiac MRI (CMR). Methods: Unrelated MESA participants with T1-mapping CMR and no history of MI or heart failure were included (n=1,235). We used the extracellular volume (ECV) fraction as a well-established surrogate of interstitial MF. Genotyping was performed by Affymetrix Human SNP array 6.0, and imputation was performed using the TOPMED reference panel. Log ECV(%) was regressed on 50 candidate SNPs, in each ethnicity/race group, adjusting for age, sex, and population stratification principal component. The race-specific results were pooled by fixed-effect meta-analyses using METASOFT. Results: The SMARCB1 rs2186370 intronic variant, previously identified as a risk variant for DCM and HCM, was associated with ECV (p=0.0004). The rs2186370 A allele (frequency: 0.18 in Whites, and 0.50 in African Americans) was associated with a 1.6% increase in ECV. The rs2070458 A allele (another SMARCB1 intronic variant), in complete linkage disequilibrium with rs2186370, was known previously to be associated with increased LV wall thickness, mass, and concentricity. The direction of effect was similar in all four ancestry groups, but the effect was strongest in African Americans. These variants are strong expression quantitative loci (eQTLs) in human LV tissue and are associated with genotype-dependent expression of SMARCB1 ( p =7.3х10 -22 ) and MMP11 ( p =2.5х10 -24 ). Conclusions: In conclusion, variants in two linked SMARCB1 loci previously associated with HCM, DCM and LV traits, are associated with CMR-based interstitial MF. These loci are eQTL not only for SMARCB1 but also for MMP11 an important mediator of MF . These findings underscore the important link between MF and CM, and potentially provide novel mechanistic targets in understanding the development of CM.

Introduction: It has been previously demonstrated that cardiomyopathy predisposing common genetic variation in SMARCB1 is associated with interstitial myocardial fibrosis (MF) as determined by cardiac MRI (CMR) linking the development of cardiomyopathy with MF. SMARCB1 is known to be a tumor suppressor, but it’s role in the pathophysiology of MF and fibroblast physiology has not been functionally validated. Hypothesis: SMARCB1 plays an important role in regulating human cardiac fibroblast (HCF) differentiation/activation and collagen deposition, which are the critical steps in the development of MF. Methods: Cultured HCFs were treated with TGF-β1 (10ng/ml) for 48hrs to transdifferentiate into myofibroblasts, which are characterized by increased expression of α-smooth muscle actin (α-SMA, ACTA2) and collagen I (COL1A1). HCFs were transfected by siRNA using Lipofectamine™ RNAiMAX Transfection Reagent to knock-down (KD) the expression of SMARCB1 . Total RNA and protein were extracted from cell lysate followed by qPCR and Western blot (WB) to quantify the expression level of SMARCB1, ACTA2 and COL1A1. Triplicate experiments were performed using biologically independent samples. For statistical analysis, a paired two-tail t-test was used. Results: HCFs treatment with TGF-β1, resulted in a significant decrease in expression of SMARCB1 (p=0.031) with accompanying significant increase in expression of ACTA2 (p=0.025) and COL1A1 (p=0.0015) as compared to control by qPCR and WB. SMARCB1 KD resulted in a further significant increase in expression of ACTA2 (p=0.018) and COL1A1 (p=0.028) as compared to non-target siRNA control group at both the transcript and protein level. Conclusion: We demonstrate for the first time that a gene associated with the development of cardiomyopathy SMARCB1 mediates TGF-β1 induced cardiac fibrosis. These findings suggest SMARCB1 as a potential therapeutic target to attenuate MF in cardiomyopathy.

AbstractBackgroundDeep learning auto‐segmentation (DLAS) models have been adopted in the clinic; however, they suffer from performance deterioration owing to the clinical practice variability. Some commercial DLAS software provide an incremental retraining function that enables users to train a custom model using their institutional data to account for clinical practice variability.PurposeThis study was performed to evaluate and implement the commercial DLAS software with the incremental retraining function for definitive treatment of patients with prostate cancer in a multi‐user environment.MethodsCT‐based target organs and organs‐at‐risk (OAR) delineation of 215 prostate cancer patients were utilized. The performance of three commercial DLAS software built‐in models was validated with 20 patients. A retrained custom model was developed using 100 patients and evaluated on the remaining data (n = 115). Dice similarity coefficient (DSC), Hausdorff distance (HD), mean surface distance (MSD), and surface DSC (SDSC) were utilized for quantitative evaluation. A multi‐rater qualitative evaluation was blindly performed with a five‐level scale. Visual inspection was performed in consensus and non‐consensus unacceptable cases to identify the failure modes.ResultsThree commercial DLAS vendor built‐in models achieved sub‐optimal performance in 20 patients. The retrained custom model had a mean DSC of 0.82 for prostate, 0.48 for seminal vesicles (SV), and 0.92 for rectum, respectively. This represents a significant improvement over the built‐in model with DSC of 0.73, 0.37, and 0.81 for the corresponding structures. Compared to the acceptance rate of 96.5% and consensus unacceptable rate (i.e., both reviewers rated as unacceptable) of 3.5% achieved by manual contours, the custom model achieved a 91.3% acceptance rate and 8.7% consensus unacceptable rate. The failure modes of retrained custom model were attributed to the following: cystogram (n = 2), hip prosthesis (n = 2), low dose rate brachytherapy seeds (n = 2), air in endorectal balloon(n = 1), non‐iodinated spacer (n = 2), and giant bladder(n = 1).ConclusionThe commercial DLAS software with the incremental retraining function was validated and clinically adopted for prostate patients in a multi‐user environment. AI‐based auto‐delineation of the prostate and OARs is shown to achieve improved physician acceptance, overall clinical utility, and accuracy.

Radiation-induced brain injury (RIBI) is a debilitating sequela after radiotherapy to treat head and neck cancer, and 20 to 30% of patients with RIBI fail to respond to or have contraindications to the first-line treatments of bevacizumab and corticosteroids. Here, we reported a Simon’s minmax two-stage, single-arm, phase 2 clinical trial (NCT03208413) to assess the efficacy of thalidomide in patients with RIBI who were unresponsive to or had contraindications to bevacizumab and corticosteroid therapies. The trial met its primary endpoint, with 27 of 58 patients enrolled showing ≥25% reduction in the volume of cerebral edema on fluid-attenuated inversion recovery–magnetic resonance imaging (FLAIR-MRI) after treatment (overall response rate, 46.6%; 95% CI, 33.3 to 60.1%). Twenty-five (43.1%) patients demonstrated a clinical improvement based on the Late Effects Normal Tissues–Subjective, Objective, Management, Analytic (LENT/SOMA) scale, and 36 (62.1%) experienced cognitive improvement based on the Montreal Cognitive Assessment (MoCA) scores. In a mouse model of RIBI, thalidomide restored the blood-brain barrier and cerebral perfusion, which were attributed to the functional rescue of pericytes secondary to elevation of platelet-derived growth factor receptor β (PDGFRβ) expression by thalidomide. Our data thus demonstrate the therapeutic potential of thalidomide for the treatment of radiation-induced cerebral vasculature impairment.