Estimation of biological heart age using cardiovascular magnetic resonance radiomics.
Estimation of biological heart age using cardiovascular magnetic resonance radiomics.
We developed a novel interpretable biological heart age estimation model using cardiovascular magnetic resonance radiomics measures of ventricular shape and myocardial character. We included 29,996 UK Biobank participants without cardiovascular disease. Images were segmented using an automated analysis pipeline. We extracted 254 radiomics features from the left ventricle, right ventricle, and myocardium of each study. We then used Bayesian ridge regression with tenfold cross-validation to develop a heart age estimation model using the radiomics features as the model input and chronological age as the model output. We examined associations of radiomics features with heart age in men and women, observing sex-differential patterns. We subtracted actual age from model estimated heart age to calculate a “heart age delta”, which we considered as a measure of heart aging. We performed a phenome-wide association study of 701 exposures with heart age delta. The strongest correlates of heart aging were measures of obesity, adverse serum lipid markers, hypertension, diabetes, heart rate, income, multimorbidity, musculoskeletal health, and respiratory health. This technique provides a new method for phenotypic assessment relating to cardiovascular aging; further studies are required to assess whether it provides incremental risk information over current approaches.
Raisi-Estabragh, Zahra
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Salih, Ahmed
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Gkontra, Polyxeni
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Atehortua, Angelica
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Radeva, Petia
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Boscolo-Galazzo, Ilaria
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Menegaz, Gloria
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Harvey, Nicholas
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Lekadir, Karim
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Petersen, Steffen E.
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December 2022
Raisi-Estabragh, Zahra
43c85c5e-4574-476b-80d6-8fb1cdb3df0a
Salih, Ahmed
c9783bc9-e223-4d3a-b0ec-34120337061c
Gkontra, Polyxeni
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Atehortua, Angelica
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Radeva, Petia
98a53fff-5ef1-4d8a-8cd4-3836a14b920a
Boscolo-Galazzo, Ilaria
83d40e19-3d2f-497d-89e4-c05c10dae07f
Menegaz, Gloria
d0707f26-30d4-4d8a-9eb5-140eda67af2e
Harvey, Nicholas
ce487fb4-d360-4aac-9d17-9466d6cba145
Lekadir, Karim
b8de558a-869c-4574-b0d3-005dc52c3106
Petersen, Steffen E.
04f2ce88-790d-48dc-baac-cbe0946dd928
Raisi-Estabragh, Zahra, Salih, Ahmed, Gkontra, Polyxeni, Atehortua, Angelica, Radeva, Petia, Boscolo-Galazzo, Ilaria, Menegaz, Gloria, Harvey, Nicholas, Lekadir, Karim and Petersen, Steffen E.
(2022)
Estimation of biological heart age using cardiovascular magnetic resonance radiomics.
Scientific Reports, 12 (1), [12805].
(doi:10.1038/s41598-022-16639-9).
Abstract
We developed a novel interpretable biological heart age estimation model using cardiovascular magnetic resonance radiomics measures of ventricular shape and myocardial character. We included 29,996 UK Biobank participants without cardiovascular disease. Images were segmented using an automated analysis pipeline. We extracted 254 radiomics features from the left ventricle, right ventricle, and myocardium of each study. We then used Bayesian ridge regression with tenfold cross-validation to develop a heart age estimation model using the radiomics features as the model input and chronological age as the model output. We examined associations of radiomics features with heart age in men and women, observing sex-differential patterns. We subtracted actual age from model estimated heart age to calculate a “heart age delta”, which we considered as a measure of heart aging. We performed a phenome-wide association study of 701 exposures with heart age delta. The strongest correlates of heart aging were measures of obesity, adverse serum lipid markers, hypertension, diabetes, heart rate, income, multimorbidity, musculoskeletal health, and respiratory health. This technique provides a new method for phenotypic assessment relating to cardiovascular aging; further studies are required to assess whether it provides incremental risk information over current approaches.
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Accepted/In Press date: 13 July 2022
Published date: December 2022
Additional Information:
Funding Information:
ZR-E recognizes the National Institute for Health Research (NIHR) Integrated Academic Training programme which supports her Academic Clinical Lectureship post and was also supported by British Heart Foundation Clinical Research Training Fellowship No. FS/17/81/33318. SEP acknowledge the BHF for funding the manual image analysis underpinning creation of a cardiovascular magnetic resonance imaging reference standard for the UK Biobank imaging in 5000 scans ( http://www.bhf.org.uk ; PG/14/89/31194). SEP, PG, and KL have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825903 (euCanSHare project). SEP also acknowledges support from the “SmartHeart” EPSRC programme grant ( http://www.nihr.ac.uk ; EP/P001009/1). SEP acknowledges support from the National Institute for Health Research (NIHR) Biomedical Research Centre at Barts. KL received funding from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-099898-B-I00. NCH acknowledges support from the UK Medical Research Council (MC_UU_12011/1), NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton. This work was supported by Health Data Research UK, an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities. This study was conducted using the UK Biobank resource under access application 2964. AS is supported by INVITE program co-financed by the European Union within the Horizon 2020 Programme and by the Regione del Veneto.
Publisher Copyright:
© 2022, The Author(s).
Identifiers
Local EPrints ID: 468986
URI: http://eprints.soton.ac.uk/id/eprint/468986
ISSN: 2045-2322
PURE UUID: f52c48e8-fb90-4b14-a55d-1beb0f605a57
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Date deposited: 02 Sep 2022 19:03
Last modified: 10 Apr 2024 01:40
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Contributors
Author:
Zahra Raisi-Estabragh
Author:
Ahmed Salih
Author:
Polyxeni Gkontra
Author:
Angelica Atehortua
Author:
Petia Radeva
Author:
Ilaria Boscolo-Galazzo
Author:
Gloria Menegaz
Author:
Karim Lekadir
Author:
Steffen E. Petersen
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