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Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19

BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image a...

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Autores principales: Kotanidis, Christos P, Xie, Cheng, Alexander, Donna, Rodrigues, Jonathan C L, Burnham, Katie, Mentzer, Alexander, O’Connor, Daniel, Knight, Julian, Siddique, Muhammad, Lockstone, Helen, Thomas, Sheena, Kotronias, Rafail, Oikonomou, Evangelos K, Badi, Ileana, Lyasheva, Maria, Shirodaria, Cheerag, Lumley, Sheila F, Constantinides, Bede, Sanderson, Nicholas, Rodger, Gillian, Chau, Kevin K, Lodge, Archie, Tsakok, Maria, Gleeson, Fergus, Adlam, David, Rao, Praveen, Indrajeet, Das, Deshpande, Aparna, Bajaj, Amrita, Hudson, Benjamin J, Srivastava, Vivek, Farid, Shakil, Krasopoulos, George, Sayeed, Rana, Ho, Ling-Pei, Neubauer, Stefan, Newby, David E, Channon, Keith M, Deanfield, John, Antoniades, Charalambos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417284/
https://www.ncbi.nlm.nih.gov/pubmed/36038496
http://dx.doi.org/10.1016/S2589-7500(22)00132-7
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author Kotanidis, Christos P
Xie, Cheng
Alexander, Donna
Rodrigues, Jonathan C L
Burnham, Katie
Mentzer, Alexander
O’Connor, Daniel
Knight, Julian
Siddique, Muhammad
Lockstone, Helen
Thomas, Sheena
Kotronias, Rafail
Oikonomou, Evangelos K
Badi, Ileana
Lyasheva, Maria
Shirodaria, Cheerag
Lumley, Sheila F
Constantinides, Bede
Sanderson, Nicholas
Rodger, Gillian
Chau, Kevin K
Lodge, Archie
Tsakok, Maria
Gleeson, Fergus
Adlam, David
Rao, Praveen
Indrajeet, Das
Deshpande, Aparna
Bajaj, Amrita
Hudson, Benjamin J
Srivastava, Vivek
Farid, Shakil
Krasopoulos, George
Sayeed, Rana
Ho, Ling-Pei
Neubauer, Stefan
Newby, David E
Channon, Keith M
Deanfield, John
Antoniades, Charalambos
author_facet Kotanidis, Christos P
Xie, Cheng
Alexander, Donna
Rodrigues, Jonathan C L
Burnham, Katie
Mentzer, Alexander
O’Connor, Daniel
Knight, Julian
Siddique, Muhammad
Lockstone, Helen
Thomas, Sheena
Kotronias, Rafail
Oikonomou, Evangelos K
Badi, Ileana
Lyasheva, Maria
Shirodaria, Cheerag
Lumley, Sheila F
Constantinides, Bede
Sanderson, Nicholas
Rodger, Gillian
Chau, Kevin K
Lodge, Archie
Tsakok, Maria
Gleeson, Fergus
Adlam, David
Rao, Praveen
Indrajeet, Das
Deshpande, Aparna
Bajaj, Amrita
Hudson, Benjamin J
Srivastava, Vivek
Farid, Shakil
Krasopoulos, George
Sayeed, Rana
Ho, Ling-Pei
Neubauer, Stefan
Newby, David E
Channon, Keith M
Deanfield, John
Antoniades, Charalambos
author_sort Kotanidis, Christos P
collection PubMed
description BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19. METHODS: For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes. FINDINGS: Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43–6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17–3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49–7·33], p=0·0033; and 2·58 [1·10–6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16–31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69–7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. INTERPRETATION: Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy. FUNDING: Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.
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spelling pubmed-94172842022-08-30 Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19 Kotanidis, Christos P Xie, Cheng Alexander, Donna Rodrigues, Jonathan C L Burnham, Katie Mentzer, Alexander O’Connor, Daniel Knight, Julian Siddique, Muhammad Lockstone, Helen Thomas, Sheena Kotronias, Rafail Oikonomou, Evangelos K Badi, Ileana Lyasheva, Maria Shirodaria, Cheerag Lumley, Sheila F Constantinides, Bede Sanderson, Nicholas Rodger, Gillian Chau, Kevin K Lodge, Archie Tsakok, Maria Gleeson, Fergus Adlam, David Rao, Praveen Indrajeet, Das Deshpande, Aparna Bajaj, Amrita Hudson, Benjamin J Srivastava, Vivek Farid, Shakil Krasopoulos, George Sayeed, Rana Ho, Ling-Pei Neubauer, Stefan Newby, David E Channon, Keith M Deanfield, John Antoniades, Charalambos Lancet Digit Health Articles BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19. METHODS: For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes. FINDINGS: Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43–6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17–3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49–7·33], p=0·0033; and 2·58 [1·10–6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16–31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69–7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. INTERPRETATION: Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy. FUNDING: Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation. The Author(s). Published by Elsevier Ltd. 2022-10 2022-08-26 /pmc/articles/PMC9417284/ /pubmed/36038496 http://dx.doi.org/10.1016/S2589-7500(22)00132-7 Text en © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Articles
Kotanidis, Christos P
Xie, Cheng
Alexander, Donna
Rodrigues, Jonathan C L
Burnham, Katie
Mentzer, Alexander
O’Connor, Daniel
Knight, Julian
Siddique, Muhammad
Lockstone, Helen
Thomas, Sheena
Kotronias, Rafail
Oikonomou, Evangelos K
Badi, Ileana
Lyasheva, Maria
Shirodaria, Cheerag
Lumley, Sheila F
Constantinides, Bede
Sanderson, Nicholas
Rodger, Gillian
Chau, Kevin K
Lodge, Archie
Tsakok, Maria
Gleeson, Fergus
Adlam, David
Rao, Praveen
Indrajeet, Das
Deshpande, Aparna
Bajaj, Amrita
Hudson, Benjamin J
Srivastava, Vivek
Farid, Shakil
Krasopoulos, George
Sayeed, Rana
Ho, Ling-Pei
Neubauer, Stefan
Newby, David E
Channon, Keith M
Deanfield, John
Antoniades, Charalambos
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
title Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
title_full Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
title_fullStr Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
title_full_unstemmed Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
title_short Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
title_sort constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine ct angiograms: a prospective outcomes validation study in covid-19
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417284/
https://www.ncbi.nlm.nih.gov/pubmed/36038496
http://dx.doi.org/10.1016/S2589-7500(22)00132-7
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