The growth factors chosen exhibited an anabolic effect on the meniscus tissue explants, encouraging matrix production and deposition. The addition of static mechanical compression produced comparable relative inhibition of matrix production for each growth factor, suggesting that static compression and growth factors may modulate meniscal fibrochondrocyte biosynthesis via distinct pathways.

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Background:Monitoring for acute allograft rejection improves outcomes after cardiac transplantation. Endomyocardial biopsy is the gold standard test defining rejection, but carries risk and has limitations. Cardiac magnetic resonance T2 mapping may be able to predict rejection in adults, but has not been studied in children. Our aim was to evaluate T2 mapping in identifying paediatric cardiac transplant patients with acute rejection.Methods:Eleven paediatric transplant patients presenting 18 times were prospectively enrolled for non-contrast cardiac magnetic resonance at 1.5 T followed by endomyocardial biopsy. Imaging included volumetry, flow, and T2 mapping. Regions of interest were manually selected on the T2 maps using the middle-third technique in the left ventricular septal and lateral wall in a short-axis and four-chamber slice. Mean and maximum T2 values were compared with Student’s t-tests analysis.Results:Five cases of acute rejection were identified in three patients, including two cases of grade 2R on biopsy and three cases of negative biopsy treated for clinical symptoms attributed to rejection (new arrhythmia, decreased exercise capacity). A monotonic trend between increasing T2 values and higher biopsy grades was observed: grade 0R T2 53.4 ± 3 ms, grade 1R T2 54.5 ms ± 3 ms, grade 2R T2 61.3 ± 1 ms. The five rejection cases had significantly higher mean T2 values compared to cases without rejection (58.3 ± 4 ms versus 53 ± 2 ms, p = 0.001).Conclusions:Cardiac magnetic resonance with quantitative T2 mapping may offer a non-invasive method for screening paediatric cardiac transplant patients for acute allograft rejection. More data are needed to understand the relationship between T2 and rejection in children.

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Precision Cardiology is a targeted strategy for cardiovascular disease prevention and treatment that accounts for individual variability. Computational heart modeling is one of the novel approaches that have been developed under the umbrella of Precision Cardiology. Personalized computational modeling of patient hearts has made strides in the development of models that incorporate the individual geometry and structure of the heart as well as other patient‐specific information. Of these developments, one of the potentially most impactful is the research aimed at noninvasively predicting the targets of ablation of lethal arrhythmia, ventricular tachycardia (VT), using patient‐specific models. The approach has been successfully applied to patients with ischemic cardiomyopathy in proof‐of‐concept studies. The goal of this paper is to review the strategies for computational VT ablation guidance in ischemic cardiomyopathy patients, from model developments to the intricacies of the actual clinical application. To provide context in describing the road these computational modeling applications have undertaken, we first review the state of the art in VT ablation in the clinic, emphasizing the benefits that personalized computational prediction of ablation targets could bring to the clinical electrophysiology practice. This article is characterized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Translational, Genomic, and Systems Medicine > Translational Medicine

Background Cardiovascular magnetic resonance (CMR) is emerging as an important tool for cardiac allograft assessment. Native T1 mapping may add value in identifying rejection and in assessing graft dysfunction and myocardial fibrosis burden. We hypothesized that CMR native T1 values and features of textural analysis of T1 maps would identify acute rejection, and in a secondary analysis, correlate with markers of graft dysfunction, and with fibrosis percentage from endomyocardial biopsy (EMB). Methods Fifty cases with simultaneous EMB, right heart catheterization, and 1.5 T CMR with breath-held T1 mapping via modified Look-Locker inversion recovery (MOLLI) in 8 short-axis slices and subsequent quantification of mean and peak native T1 values, were performed on 24 pediatric subjects. A single mid-ventricular slice was used for image texture analysis using nine gray-level co-occurrence matrix features. Digital quantification of Masson trichrome stained EMB samples established degree of fibrosis. Markers of graft dysfunction, including serum brain natriuretic peptide levels and hemodynamic measurements from echocardiography, catheterization, and CMR were collated. Subjects were divided into three groups based on degree of rejection: acute rejection requiring new therapy, mild rejection requiring increased ongoing therapy, and no rejection with no change in treatment. Statistical analysis included student’s t-test and linear regression. Results Peak and mean T1 values were significantly associated with acute rejection, with a monotonic trend observed with increased grade of rejection. Texture analysis demonstrated greater spatial heterogeneity in T1 values, as demonstrated by energy, entropy, and variance, in cases requiring treatment. Interestingly, 2 subjects who required increased therapy despite low grade EMB results had abnormal peak T1 values. Peak T1 values also correlated with increased BNP, right-sided filling pressures, and capillary wedge pressures. There was no difference in histopathological fibrosis percentage among the 3 groups; histopathological fibrosis did not correlate with T1 values or markers of graft dysfunction. Conclusion In pediatric heart transplant patients, native T1 values identify acute rejection requiring treatment and may identify graft dysfunction. CMR shows promise as an important tool for evaluation of cardiac grafts in children, with T1 imaging outperforming biopsy findings in the assessment of rejection.