Estimation of biological heart age using cardiovascular magnetic resonance radiomics.
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ABSTRACT:
SUBMITTER: Raisi-Estabragh Z
PROVIDER: S-EPMC9329281 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPulmonary edema is a cardinal feature of heart failure but no quantitative tests are available in clinical practice. The goals of this study were to develop a simple cardiovascular magnetic resonance (CMR) approach for lung water quantification, to correlate CMR derived lung water with intra-cardiac pressures and to determine its prognostic significance.MethodsLung water density (LWD, %) was measured using a widely available single-shot fast spin-echo acquisition in two study cohorts. Validation Cohort: LWD was compared to left ventricular end-diastolic pressure or pulmonary capillary wedge pressure in 19 patients with heart failure undergoing cardiac catheterization. Prospective Cohort: LWD was measured in 256 subjects, including 121 with heart failure, 82 at-risk for heart failure and 53 healthy controls. Clinical outcomes were evaluated up to 1 year.ResultsWithin the validation cohort, CMR LWD correlated to invasively measured left-sided filling pressures (R = 0.8, p < 0.05). In the prospective cohort, mean LWD was 16.6 ± 2.1% in controls, 17.9 ± 3.0% in patients at-risk and 19.3 ± 5.4% in patients with heart failure, p < 0.001. In patients with or at-risk for heart failure, LWD > 20.8% (mean + 2 standard deviations of healthy controls) was an independent predictor of death, hospitalization or emergency department visit within 1 year, hazard ratio 2.4 (1.1-5.1, p = 0.03).ConclusionsIn patients with heart failure, increased CMR-derived lung water is associated with increased intra-cardiac filling pressures, and predicts 1 year outcomes. LWD could be incorporated in standard CMR scans.
| S-EPMC6739968 | biostudies-literature
Project description:Despite significant advances in heart failure diagnostics and therapy, the prognosis remains poor, with one in three dying within a year of hospital admission. This is at least in part due to the difficulties in risk stratification and personalisation of therapy. The use of left ventricular systolic function as the main arbiter for entrance into clinical trials for drugs and advanced therapy, such as implantable defibrillators, grossly simplifies the complex heterogeneous nature of the syndrome. Cardiovascular magnetic resonance offers a wealth of data to aid in diagnosis and prognostication. The advent of novel cardiovascular magnetic resonance mapping techniques allows us to glimpse some of the pathophysiological mechanisms underpinning heart failure. We review the growing prognostic evidence base using these techniques.
| S-EPMC5739890 | biostudies-literature
Project description:BackgroundRadial self-navigated (RSN) whole-heart coronary cardiovascular magnetic resonance angiography (CCMRA) is a free-breathing technique that estimates and corrects for respiratory motion. However, RSN has been limited to a 1D rigid correction which is often insufficient for patients with complex respiratory patterns. The goal of this work is therefore to improve the robustness and quality of 3D radial CCMRA by incorporating both 3D motion information and nonrigid intra-acquisition correction of the data into a framework called focused navigation (fNAV).MethodsWe applied fNAV to 500 data sets from a numerical simulation, 22 healthy subjects, and 549 cardiac patients. In each of these cohorts we compared fNAV to RSN and respiratory resolved extradimensional golden-angle radial sparse parallel (XD-GRASP) reconstructions of the same data. Reconstruction times for each method were recorded. Motion estimate accuracy was measured as the correlation between fNAV and ground truth for simulations, and fNAV and image registration for in vivo data. Percent vessel sharpness was measured in all simulated data sets and healthy subjects, and a subset of patients. Finally, subjective image quality analysis was performed by a blinded expert reviewer who chose the best image for each in vivo data set and scored on a Likert scale 0-4 in a subset of patients by two reviewers in consensus.ResultsThe reconstruction time for fNAV images was significantly higher than RSN (6.1 ± 2.1 min vs 1.4 ± 0.3, min, p < 0.025) but significantly lower than XD-GRASP (25.6 ± 7.1, min, p < 0.025). Overall, there is high correlation between the fNAV and reference displacement estimates across all data sets (0.73 ± 0.29). For simulated data, healthy subjects, and patients, fNAV lead to significantly sharper coronary arteries than all other reconstruction methods (p < 0.01). Finally, in a blinded evaluation by an expert reviewer fNAV was chosen as the best image in 444 out of 571 data sets (78%; p < 0.001) and consensus grades of fNAV images (2.6 ± 0.6) were significantly higher (p < 0.05) than uncorrected (1.7 ± 0.7), RSN (1.9 ± 0.6), and XD-GRASP (1.8 ± 0.8).ConclusionfNAV is a promising technique for improving the quality of RSN free-breathing 3D whole-heart CCMRA. This novel approach to respiratory self-navigation can derive 3D nonrigid motion estimations from an acquired 1D signal yielding statistically significant improvement in image sharpness relative to 1D translational correction as well as XD-GRASP reconstructions. Further study of the diagnostic impact of this technique is therefore warranted to evaluate its full clinical utility.
| S-EPMC8006382 | biostudies-literature
Project description:Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI [0.767-0.788]), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI [0.739-0.761]), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual's mortality risk. Values ranged between 20-years younger and 20-years older than individuals' chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population.
| S-EPMC10603148 | biostudies-literature
Project description:BackgroundThe orifice area of mitral bioprostheses provides important information regarding their hemodynamic performance. It is usually calculated by transthoracic echocardiography (TTE), however, accurate and reproducible determination may be challenging. Cardiovascular magnetic resonance (CMR) has been proven as an accurate alternative for assessing aortic bioprostheses. However, whether CMR can be similarly applied for bioprostheses in the mitral position, particularly in the presence of frequently coincident arrhythmias, is unclear. The aim of the study is to test the feasibility of CMR to evaluate the orifice area of mitral bioprostheses.MethodsCMR planimetry was performed in 18 consecutive patients with mitral bioprostheses (n = 13 Hancock(R), n = 4 Labcore(R), n = 1 Perimount(R); mean time since implantation 4.5 +/- 3.9 years) in an imaging plane perpendicular to the transprosthetic flow using steady-state free-precession cine imaging under breath-hold conditions on a 1.5T MR system. CMR results were compared with pressure half-time derived orifice areas obtained by TTE.ResultsSix subjects were in sinus rhythm, 11 in atrial fibrillation, and 1 exhibited frequent ventricular extrasystoles. CMR image quality was rated as good in 10, moderate in 6, and significantly impaired in 2 subjects. In one prosthetic type (Perimount(R)), strong stent artifacts occurred. Orifice areas by CMR (mean 2.1 +/- 0.3 cm2) and TTE (mean 2.1 +/- 0.3 cm2) correlated significantly (r = 0.94; p < 0.001). Bland-Altman analysis showed a 95% confidence interval from -0.16 to 0.28 cm2 (mean difference 0.06 +/- 0.11 cm2; range -0.1 to 0.3 cm2). Intra- and inter-observer variabilities of CMR planimetry were 4.5 +/- 2.9% and 7.9 +/- 5.2%.ConclusionsThe assessment of mitral bioprostheses using CMR is feasible even in those with arrhythmias, providing orifice areas with close agreement to echocardiography and low observer dependency. Larger samples with a greater variety of prosthetic types and more cases of prosthetic dysfunction are required to confirm these preliminary results.
| S-EPMC2898806 | biostudies-literature
Project description:Cardiovascular imaging is key for the assessment of patients with heart failure. Today, cardiovascular magnetic resonance imaging plays an established role in the assessment of patients with suspected and confirmed heart failure syndromes, in particular identifying aetiology. Its role in informing prognosis and guiding decisions around therapy are evolving. Key strengths include its accuracy; reproducibility; unrestricted field of view; lack of radiation; multiple abilities to characterise myocardial tissue, thrombus and scar; as well as unparalleled assessment of left and right ventricular volumes. T2* has an established role in the assessment and follow-up of iron overload cardiomyopathy and a role for T1 in specific therapies for cardiac amyloid and Anderson-Fabry disease is emerging.
| S-EPMC5490982 | biostudies-other
Project description:Cardiovascular magnetic resonance (CMR) has expanded its role in the diagnosis and management of congenital heart disease (CHD) and acquired heart disease in pediatric patients. Ongoing technological advancements in both data acquisition and data presentation have enabled CMR to be integrated into clinical practice with increasing understanding of the advantages and limitations of the technique by pediatric cardiologists and congenital heart surgeons. Importantly, the combination of exquisite 3D anatomy with physiological data enables CMR to provide a unique perspective for the management of many patients with CHD. Imaging small children with CHD is challenging, and in this article we will review the technical adjustments, imaging protocols and application of CMR in the pediatric population.
| S-EPMC3210092 | biostudies-literature
Project description:Biological brain age predicted using machine learning models based on high-resolution imaging data has been suggested as a potential biomarker for neurological and cerebrovascular diseases. In this work, we aimed to develop deep learning models to predict the biological brain age using structural magnetic resonance imaging and angiography datasets from a large database of 2074 adults (21-81 years). Since different imaging modalities can provide complementary information, combining them might allow to identify more complex aging patterns, with angiography data, for instance, showing vascular aging effects complementary to the atrophic brain tissue changes seen in T1-weighted MRI sequences. We used saliency maps to investigate the contribution of cortical, subcortical, and arterial structures to the prediction. Our results show that combining T1-weighted and angiography MR data led to a significantly improved brain age prediction accuracy, with a mean absolute error of 3.85 years comparing the predicted and chronological age. The most predictive brain regions included the lateral sulcus, the fourth ventricle, and the amygdala, while the brain arteries contributing the most to the prediction included the basilar artery, the middle cerebral artery M2 segments, and the left posterior cerebral artery. Our study proposes a framework for brain age prediction using multimodal imaging, which gives accurate predictions and allows identifying the most predictive regions for this task, which can serve as a surrogate for the brain regions that are most affected by aging.
| S-EPMC9057090 | biostudies-literature
Project description:BackgroundChronic type B aortic dissection (TBAD) is associated with poor long-term outcome, and accurate risk stratification tools remain lacking. Pressurization of the false lumen (FL) has been recognized as central in promoting aortic growth. Several surrogate imaging-based metrics have been proposed to assess FL hemodynamics; however, their relationship to enlarging aortic dimensions remains unclear. We investigated the association between aortic growth and three cardiovascular magnetic resonance (CMR)-derived metrics of FL pressurization: false lumen ejection fraction (FLEF), maximum systolic deceleration rate (MSDR), and FL relative pressure (FL ΔPmax).MethodsCMR/CMR angiography was performed in 12 patients with chronic dissection of the descending thoracoabdominal aorta, including contrast-enhanced CMR angiography and time-resolved three-dimensional phase-contrast CMR (4D Flow CMR). Aortic growth rate was calculated as the change in maximal aortic diameter between baseline and follow-up imaging studies over the time interval, with patients categorized as having either 'stable' (< 3 mm/year) or 'enlarging' (≥ 3 mm/year) growth. Three metrics relating to FL pressurization were defined as: (1) FLEF: the ratio between retrograde and antegrade flow at the TBAD entry tear, (2) MSDR: the absolute difference between maximum and minimum systolic acceleration in the proximal FL, and (3) FL ΔPmax: the difference in absolute pressure between aortic root and distal FL.ResultsFLEF was higher in enlarging TBAD (49.0 ± 17.9% vs. 10.0 ± 11.9%, p = 0.002), whereas FL ΔPmax was lower (32.2 ± 10.8 vs. 57.2 ± 12.5 mmHg/m, p = 0.017). MSDR and conventional anatomic variables did not differ significantly between groups. FLEF showed positive (r = 0.78, p = 0.003) correlation with aortic growth rate whereas FL ΔPmax showed negative correlation (r = - 0.64, p = 0.026). FLEF and FL ΔPmax remained as independent predictors of aortic growth rate after adjusting for baseline aortic diameter.ConclusionComparative analysis of three 4D flow CMR metrics of TBAD FL pressurization demonstrated that those that focusing on retrograde flow (FLEF) and relative pressure (FL ΔPmax) independently correlated with growth and differentiated patients with enlarging and stable descending aortic dissections. These results emphasize the highly variable nature of aortic hemodynamics in TBAD patients, and suggest that 4D Flow CMR derived metrics of FL pressurization may be useful to separate patients at highest and lowest risk for progressive aortic growth and complications.
| S-EPMC8117268 | biostudies-literature
Project description:This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert.
| S-EPMC4545395 | biostudies-literature