Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium

Abstract Background Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deployin...

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Autores principales:	Constantin Anastasopoulos, Shan Yang, Maurice Pradella, Tugba Akinci D’Antonoli, Sven Knecht, Joshy Cyriac, Marco Reisert, Elias Kellner, Rita Achermann, Philip Haaf, Bram Stieltjes, Alexander W. Sauter, Jens Bremerich, Gregor Sommer, Ahmed Abdulkadir
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Magnetic resonance imaging Heart atria Artificial intelligence Workflow Atrial fibrillation Biplane area-length method Diseases of the circulatory (Cardiovascular) system RC666-701
Acceso en línea:	https://doaj.org/article/2c7dad674455468f9cb132fffb8fde99
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spelling	oai:doaj.org-article:2c7dad674455468f9cb132fffb8fde992021-11-14T12:12:48ZAtri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium10.1186/s12968-021-00791-81532-429Xhttps://doaj.org/article/2c7dad674455468f9cb132fffb8fde992021-11-01T00:00:00Zhttps://doi.org/10.1186/s12968-021-00791-8https://doaj.org/toc/1532-429XAbstract Background Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deploying a fully automatic black-box, we propose to incorporate the automated LA volumetry into a human-centric interactive image-analysis process. Methods and results Atri-U, an automated data analysis pipeline for long-axis cardiac cine images, computes the atrial volume by: (i) detecting the end-systolic frame, (ii) outlining the endocardial borders of the LA, (iii) localizing the mitral annular hinge points and constructing the longitudinal atrial diameters, equivalent to the usual workup done by clinicians. In every step human interaction is possible, such that the results provided by the algorithm can be accepted, corrected, or re-done from scratch. Atri-U was trained and evaluated retrospectively on a sample of 300 patients and then applied to a consecutive clinical sample of 150 patients with various heart conditions. The agreement of the indexed LA volume between Atri-U and two experts was similar to the inter-rater agreement between clinicians (average overestimation of 0.8 mL/m2 with upper and lower limits of agreement of − 7.5 and 5.8 mL/m2, respectively). An expert cardiologist blinded to the origin of the annotations rated the outputs produced by Atri-U as acceptable in 97% of cases for step (i), 94% for step (ii) and 95% for step (iii), which was slightly lower than the acceptance rate of the outputs produced by a human expert radiologist in the same cases (92%, 100% and 100%, respectively). The assistance of Atri-U lead to an expected reduction in reading time of 66%—from 105 to 34 s, in our in-house clinical setting. Conclusions Our proposal enables automated calculation of the maximum LA volume approaching human accuracy and precision. The optional user interaction is possible at each processing step. As such, the assisted process sped up the routine CMR workflow by providing accurate, precise, and validated measurement results.Constantin AnastasopoulosShan YangMaurice PradellaTugba Akinci D’AntonoliSven KnechtJoshy CyriacMarco ReisertElias KellnerRita AchermannPhilip HaafBram StieltjesAlexander W. SauterJens BremerichGregor SommerAhmed AbdulkadirBMCarticleMagnetic resonance imagingHeart atriaArtificial intelligenceWorkflowAtrial fibrillationBiplane area-length methodDiseases of the circulatory (Cardiovascular) systemRC666-701ENJournal of Cardiovascular Magnetic Resonance, Vol 23, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Magnetic resonance imaging Heart atria Artificial intelligence Workflow Atrial fibrillation Biplane area-length method Diseases of the circulatory (Cardiovascular) system RC666-701
spellingShingle	Magnetic resonance imaging Heart atria Artificial intelligence Workflow Atrial fibrillation Biplane area-length method Diseases of the circulatory (Cardiovascular) system RC666-701 Constantin Anastasopoulos Shan Yang Maurice Pradella Tugba Akinci D’Antonoli Sven Knecht Joshy Cyriac Marco Reisert Elias Kellner Rita Achermann Philip Haaf Bram Stieltjes Alexander W. Sauter Jens Bremerich Gregor Sommer Ahmed Abdulkadir Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
description	Abstract Background Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deploying a fully automatic black-box, we propose to incorporate the automated LA volumetry into a human-centric interactive image-analysis process. Methods and results Atri-U, an automated data analysis pipeline for long-axis cardiac cine images, computes the atrial volume by: (i) detecting the end-systolic frame, (ii) outlining the endocardial borders of the LA, (iii) localizing the mitral annular hinge points and constructing the longitudinal atrial diameters, equivalent to the usual workup done by clinicians. In every step human interaction is possible, such that the results provided by the algorithm can be accepted, corrected, or re-done from scratch. Atri-U was trained and evaluated retrospectively on a sample of 300 patients and then applied to a consecutive clinical sample of 150 patients with various heart conditions. The agreement of the indexed LA volume between Atri-U and two experts was similar to the inter-rater agreement between clinicians (average overestimation of 0.8 mL/m2 with upper and lower limits of agreement of − 7.5 and 5.8 mL/m2, respectively). An expert cardiologist blinded to the origin of the annotations rated the outputs produced by Atri-U as acceptable in 97% of cases for step (i), 94% for step (ii) and 95% for step (iii), which was slightly lower than the acceptance rate of the outputs produced by a human expert radiologist in the same cases (92%, 100% and 100%, respectively). The assistance of Atri-U lead to an expected reduction in reading time of 66%—from 105 to 34 s, in our in-house clinical setting. Conclusions Our proposal enables automated calculation of the maximum LA volume approaching human accuracy and precision. The optional user interaction is possible at each processing step. As such, the assisted process sped up the routine CMR workflow by providing accurate, precise, and validated measurement results.
format	article
author	Constantin Anastasopoulos Shan Yang Maurice Pradella Tugba Akinci D’Antonoli Sven Knecht Joshy Cyriac Marco Reisert Elias Kellner Rita Achermann Philip Haaf Bram Stieltjes Alexander W. Sauter Jens Bremerich Gregor Sommer Ahmed Abdulkadir
author_facet	Constantin Anastasopoulos Shan Yang Maurice Pradella Tugba Akinci D’Antonoli Sven Knecht Joshy Cyriac Marco Reisert Elias Kellner Rita Achermann Philip Haaf Bram Stieltjes Alexander W. Sauter Jens Bremerich Gregor Sommer Ahmed Abdulkadir
author_sort	Constantin Anastasopoulos
title	Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
title_short	Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
title_full	Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
title_fullStr	Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
title_full_unstemmed	Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
title_sort	atri-u: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
publisher	BMC
publishDate	2021
url	https://doaj.org/article/2c7dad674455468f9cb132fffb8fde99
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Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium

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