No Cover Image

Journal article 162 views

Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features

Benn Jessney, Xu Chen, Sophie Gu, Adam Brown, Daniel Obaid Orcid Logo, Charis Costopoulos, Martin Goddard, Nikunj Shah, Hector Garcia-Garcia, Yoshinobu Onuma, Patrick Serruys, Stephen P. Hoole, Michael Mahmoudi, Michael Roberts, Martin Bennett

Cardiovascular Revascularization Medicine

Swansea University Author: Daniel Obaid Orcid Logo

Full text not available from this repository: check for access using links below.

Check full text

DOI (Published version): 10.1016/j.carrev.2024.06.023

Abstract

BackgroundOptical coherence tomography (OCT) is used widely to guide stent placement, identify higher-risk plaques, and assess mechanisms of drug efficacy. However, a range of common artifacts can prevent accurate plaque classification and measurements, and limit usable frames in research studies. W...

Full description

Published in: Cardiovascular Revascularization Medicine
ISSN: 1553-8389
Published: Elsevier BV 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa67055
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2024-07-09T14:49:12Z
last_indexed 2024-07-09T14:49:12Z
id cronfa67055
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>67055</id><entry>2024-07-09</entry><title>Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features</title><swanseaauthors><author><sid>1cb4b49224d4f3f2b546ed0f39e13ea8</sid><ORCID>0000-0002-3891-1403</ORCID><firstname>Daniel</firstname><surname>Obaid</surname><name>Daniel Obaid</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2024-07-09</date><deptcode>MEDS</deptcode><abstract>BackgroundOptical coherence tomography (OCT) is used widely to guide stent placement, identify higher-risk plaques, and assess mechanisms of drug efficacy. However, a range of common artifacts can prevent accurate plaque classification and measurements, and limit usable frames in research studies. We determined whether pre-processing OCT images corrects artifacts and improves plaque classification.MethodsWe examined both ex-vivo and clinical trial OCT pullbacks for artifacts that prevented accurate tissue identification and/or plaque measurements. We developed Fourier transform-based software that reconstructed images free of common OCT artifacts, and compared corrected and uncorrected images.Results48 % of OCT frames contained image artifacts, with 62 % of artifacts over or within lesions, preventing accurate measurement in 12 % frames. Pre-processing corrected &gt;70 % of all artifacts, including thrombus, macrophage shadows, inadequate flushing, and gas bubbles. True tissue reconstruction was achieved in 63 % frames that would otherwise prevent accurate clinical measurements. Artifact correction was non-destructive and retained anatomical lumen and plaque parameters. Correction improved accuracy of plaque classification compared against histology and retained accurate assessment of higher-risk features. Correction also changed plaque classification and prevented artifact-related measurement errors in a clinical study, and reduced unmeasurable frames to &lt;5 % ex-vivo and ~1 % in-vivo.ConclusionsFourier transform-based pre-processing corrects a wide range of common OCT artifacts, improving identification of higher-risk features and plaque classification, and allowing more of the whole dataset to be used for clinical decision-making and in research. Pre-processing can augment OCT image analysis systems both for stent optimization and in natural history or drug studies.</abstract><type>Journal Article</type><journal>Cardiovascular Revascularization Medicine</journal><volume>0</volume><journalNumber/><paginationStart/><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1553-8389</issnPrint><issnElectronic/><keywords>Atherosclerosis; Fibroatheroma; Optical coherence tomography; Artifact</keywords><publishedDay>1</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-07-01</publishedDate><doi>10.1016/j.carrev.2024.06.023</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>This work was supported by British Heart Foundation Grants FS/19/66/34658, RG71070, RG84554, BHF Cambridge Centre for Research Excellence, EPSRC Cambridge Maths in Healthcare Centre Nr. EP/N014588/1, and Cambridge NIHR Biomedical Research Centre.</funders><projectreference/><lastEdited>2024-10-30T16:07:08.0404092</lastEdited><Created>2024-07-09T15:45:34.2312936</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Biomedical Science</level></path><authors><author><firstname>Benn</firstname><surname>Jessney</surname><order>1</order></author><author><firstname>Xu</firstname><surname>Chen</surname><order>2</order></author><author><firstname>Sophie</firstname><surname>Gu</surname><order>3</order></author><author><firstname>Adam</firstname><surname>Brown</surname><order>4</order></author><author><firstname>Daniel</firstname><surname>Obaid</surname><orcid>0000-0002-3891-1403</orcid><order>5</order></author><author><firstname>Charis</firstname><surname>Costopoulos</surname><order>6</order></author><author><firstname>Martin</firstname><surname>Goddard</surname><order>7</order></author><author><firstname>Nikunj</firstname><surname>Shah</surname><order>8</order></author><author><firstname>Hector</firstname><surname>Garcia-Garcia</surname><order>9</order></author><author><firstname>Yoshinobu</firstname><surname>Onuma</surname><order>10</order></author><author><firstname>Patrick</firstname><surname>Serruys</surname><order>11</order></author><author><firstname>Stephen P.</firstname><surname>Hoole</surname><order>12</order></author><author><firstname>Michael</firstname><surname>Mahmoudi</surname><order>13</order></author><author><firstname>Michael</firstname><surname>Roberts</surname><order>14</order></author><author><firstname>Martin</firstname><surname>Bennett</surname><order>15</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling v2 67055 2024-07-09 Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features 1cb4b49224d4f3f2b546ed0f39e13ea8 0000-0002-3891-1403 Daniel Obaid Daniel Obaid true false 2024-07-09 MEDS BackgroundOptical coherence tomography (OCT) is used widely to guide stent placement, identify higher-risk plaques, and assess mechanisms of drug efficacy. However, a range of common artifacts can prevent accurate plaque classification and measurements, and limit usable frames in research studies. We determined whether pre-processing OCT images corrects artifacts and improves plaque classification.MethodsWe examined both ex-vivo and clinical trial OCT pullbacks for artifacts that prevented accurate tissue identification and/or plaque measurements. We developed Fourier transform-based software that reconstructed images free of common OCT artifacts, and compared corrected and uncorrected images.Results48 % of OCT frames contained image artifacts, with 62 % of artifacts over or within lesions, preventing accurate measurement in 12 % frames. Pre-processing corrected >70 % of all artifacts, including thrombus, macrophage shadows, inadequate flushing, and gas bubbles. True tissue reconstruction was achieved in 63 % frames that would otherwise prevent accurate clinical measurements. Artifact correction was non-destructive and retained anatomical lumen and plaque parameters. Correction improved accuracy of plaque classification compared against histology and retained accurate assessment of higher-risk features. Correction also changed plaque classification and prevented artifact-related measurement errors in a clinical study, and reduced unmeasurable frames to <5 % ex-vivo and ~1 % in-vivo.ConclusionsFourier transform-based pre-processing corrects a wide range of common OCT artifacts, improving identification of higher-risk features and plaque classification, and allowing more of the whole dataset to be used for clinical decision-making and in research. Pre-processing can augment OCT image analysis systems both for stent optimization and in natural history or drug studies. Journal Article Cardiovascular Revascularization Medicine 0 Elsevier BV 1553-8389 Atherosclerosis; Fibroatheroma; Optical coherence tomography; Artifact 1 7 2024 2024-07-01 10.1016/j.carrev.2024.06.023 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee This work was supported by British Heart Foundation Grants FS/19/66/34658, RG71070, RG84554, BHF Cambridge Centre for Research Excellence, EPSRC Cambridge Maths in Healthcare Centre Nr. EP/N014588/1, and Cambridge NIHR Biomedical Research Centre. 2024-10-30T16:07:08.0404092 2024-07-09T15:45:34.2312936 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Biomedical Science Benn Jessney 1 Xu Chen 2 Sophie Gu 3 Adam Brown 4 Daniel Obaid 0000-0002-3891-1403 5 Charis Costopoulos 6 Martin Goddard 7 Nikunj Shah 8 Hector Garcia-Garcia 9 Yoshinobu Onuma 10 Patrick Serruys 11 Stephen P. Hoole 12 Michael Mahmoudi 13 Michael Roberts 14 Martin Bennett 15
title Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
spellingShingle Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
Daniel Obaid
title_short Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
title_full Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
title_fullStr Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
title_full_unstemmed Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
title_sort Correcting common OCT artifacts enhances plaque classification and identification of higher-risk plaque features
author_id_str_mv 1cb4b49224d4f3f2b546ed0f39e13ea8
author_id_fullname_str_mv 1cb4b49224d4f3f2b546ed0f39e13ea8_***_Daniel Obaid
author Daniel Obaid
author2 Benn Jessney
Xu Chen
Sophie Gu
Adam Brown
Daniel Obaid
Charis Costopoulos
Martin Goddard
Nikunj Shah
Hector Garcia-Garcia
Yoshinobu Onuma
Patrick Serruys
Stephen P. Hoole
Michael Mahmoudi
Michael Roberts
Martin Bennett
format Journal article
container_title Cardiovascular Revascularization Medicine
container_volume 0
publishDate 2024
institution Swansea University
issn 1553-8389
doi_str_mv 10.1016/j.carrev.2024.06.023
publisher Elsevier BV
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Biomedical Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Biomedical Science
document_store_str 0
active_str 0
description BackgroundOptical coherence tomography (OCT) is used widely to guide stent placement, identify higher-risk plaques, and assess mechanisms of drug efficacy. However, a range of common artifacts can prevent accurate plaque classification and measurements, and limit usable frames in research studies. We determined whether pre-processing OCT images corrects artifacts and improves plaque classification.MethodsWe examined both ex-vivo and clinical trial OCT pullbacks for artifacts that prevented accurate tissue identification and/or plaque measurements. We developed Fourier transform-based software that reconstructed images free of common OCT artifacts, and compared corrected and uncorrected images.Results48 % of OCT frames contained image artifacts, with 62 % of artifacts over or within lesions, preventing accurate measurement in 12 % frames. Pre-processing corrected >70 % of all artifacts, including thrombus, macrophage shadows, inadequate flushing, and gas bubbles. True tissue reconstruction was achieved in 63 % frames that would otherwise prevent accurate clinical measurements. Artifact correction was non-destructive and retained anatomical lumen and plaque parameters. Correction improved accuracy of plaque classification compared against histology and retained accurate assessment of higher-risk features. Correction also changed plaque classification and prevented artifact-related measurement errors in a clinical study, and reduced unmeasurable frames to <5 % ex-vivo and ~1 % in-vivo.ConclusionsFourier transform-based pre-processing corrects a wide range of common OCT artifacts, improving identification of higher-risk features and plaque classification, and allowing more of the whole dataset to be used for clinical decision-making and in research. Pre-processing can augment OCT image analysis systems both for stent optimization and in natural history or drug studies.
published_date 2024-07-01T16:07:06Z
_version_ 1814355694325858304
score 11.037319

Similar Items