: Return 1889

Notes

Contact for queries: Alistair.Young@kcl.ac.uk or s.e.petersen@qmul.ac.uk

This returned dataset contains CMR data on the first ~5000 participants who attended the imaging enhancement visit.

This category contains derived data from cardiovascular magnetic resonance (CMR) short-axis tagged images acquired in the basal, mid and apical levels of the left ventricle. Myocardial strain measurements were calculated via semi-automated analyses using CIMTag2D software (CIMTag2D v.8.1.5, Auckland MRI Research Group, New Zealand). Manual adjustments of the tagging grid were made in the end-diastolic (first frame), end-systolic (manually defined at the mid slice), early diastolic phase (rapid filling phase) and also in the last frame.

Returned data contains:

1) Image derived phenotypes:

End-systolic circumferential strain (apex)
End-systolic circumferential strain (base)
End-systolic circumferential strain (mid)
End-systolic torsion
End-systolic torsion rate

2) Quality control scores of CMR tagging images and analysis

Application 2964

Description of cardiovascular phenotype in the UK Biobank population based on cardiovascular magnetic resonance and carotid ultrasound

Imaging of the heart and blood vessels is performed in a large subset of the UK Biobank cohort. Many measures defining the state of the heart and blood vessels can be derived from the images acquired. These measures are influenced by various health conditions and modifiable and non-modifiable factors, such as age, gender and ethnicity. The aim of this proposal is to describe the measures of the heart and blood vessel in the UK Biobank population and investigate how much modifiable and non-modifiable factors influence them. All new data will be made available for future research. Knowing the reference ranges for common imaging measures of the heart and circulation and how they are influenced by factors, such as age, gender, ethnicity, risk factors for heart attacks and strokes, is key for improving making diagnoses and predicting health outcomes. Descriptive statistics will be performed for all image derived phenotypes (IDPs) from the cardiovascular magnetic resonance (CMR) and carotid ultrasound images. We will perform subgroup analysis for important clinical factors, such as age, gender, cardiovascular risk, chronic conditions (e.g. Diabetes). We will apply descriptive statistics to a subpopulation considered `healthy without cardiovascular disease or presence of modifiable risk factors`. Univariate and multivariate regression analysis will be used to assess relationships between IDPs and relevant co-variates. We will also assess intra- and inter-observer variability for IDP measurement when repeat analysis is available. Initial 5000 subjects from the imaging enhancement study.

Lead investigator:	Professor Steffen Petersen
Lead institution:	Queen Mary University of London

17 related Returns

Return ID	App ID	Description	Archive Date
2158	2964	3-D Consistent and Robust Segmentation of Cardiac Images by Deep Learning With Spatial Propagation	7 Apr 2020
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2103	2964	Automated Quality-Controlled Cardiovascular Magnetic Resonance Pericardial Fat Quantification Using a Convolutional Neural Network in the UK Biobank	10 Nov 2022
1866	2964	Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data	15 Jan 2020
1971	2964	Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data	6 Feb 2020
3245	2964	Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data	18 Mar 2021
1864	2964	Cardiac radiomics data returned by application 2964	15 Jan 2020
1883	2964	Fully-automated left ventricular mass and volume MRI analysis in the UK Biobank population cohort: evaluation of initial results	16 Jan 2020
2855	2964	Genome-wide association study identifes loci for arterial stifness index in 127,121 UK Biobank participants	24 Nov 2020
3561	2964	Independent left ventricular morphometric atlases show consistent relationships with cardiovascular risk factors: a UK biobank study	21 Jun 2021
3628	2964	Physical activity and left ventricular trabeculation in the UK Biobank community-based cohort study	7 Jul 2021
1363	2964	Reference ranges for cardiac structure and function using cardiovascular magnetic resonance (CMR) in Caucasians from the UK Biobank population cohort	13 Jun 2018
3635	2964	Reference ranges for cardiac structure and function using cardiovascular magnetic resonance (CMR) in Caucasians from the UK Biobank population cohort	9 Jul 2021
2536	2964	Right ventricular shape and function: cardiovascular magnetic resonance reference	23 Oct 2020
2842	2964	Right ventricular shape and function: cardiovascular magnetic resonance reference morphology and biventricular risk factor morphometrics in UK Biobank	23 Nov 2020
2541	2964	The impact of cardiovascular risk factors on cardiac structure and function: Insights from the UK Biobank imaging enhancement study	26 Oct 2020
2364	2964	The impact of menopausal hormone therapy (MHT) on cardiac structure and function	25 Aug 2020

1 Publication

Pub ID	Title	Author(s)	Year	Journal
1890	Fully Automated Myocardial Strain Estimation from Cardiovascular MRI-tagged Images Using a Deep Learning Framework in the UK Biobank	Edward Ferdian (+11)	2020	Radiology Cardiothoracic Imaging

Application:	2964, Description of cardiovascular phenotype in the UK Biobank population based on cardiovascular magnetic resonance and carotid ultrasound
Title:	Fully Automated Myocardial Strain Estimation from Cardiovascular MRI-tagged Images Using a Deep Learning Framework in the UK Biobank
Size:	136985 B
Archived:	17 Jan 2020
Stability:	Complete
Personal:	Contains individual-level data