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Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation

OBJECTIVE: To explore the application of the proposed intelligent image processing method in the diagnosis of aortic coarctation computed tomography angiography (CTA) and to clarify its value in the diagnosis of aortic coarctation based on the diagnosis results. METHODS: Fifty-three children with co...

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Autores principales: Yan, Taocui, Qin, Jinjie, Zhang, Yulin, Li, Qiuni, Han, Baoru, Jin, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996173/
https://www.ncbi.nlm.nih.gov/pubmed/36911025
http://dx.doi.org/10.3389/fped.2023.1131273
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author Yan, Taocui
Qin, Jinjie
Zhang, Yulin
Li, Qiuni
Han, Baoru
Jin, Xin
author_facet Yan, Taocui
Qin, Jinjie
Zhang, Yulin
Li, Qiuni
Han, Baoru
Jin, Xin
author_sort Yan, Taocui
collection PubMed
description OBJECTIVE: To explore the application of the proposed intelligent image processing method in the diagnosis of aortic coarctation computed tomography angiography (CTA) and to clarify its value in the diagnosis of aortic coarctation based on the diagnosis results. METHODS: Fifty-three children with coarctation of the aorta (CoA) and forty children without CoA were selected to constitute the study population. CTA was performed on all subjects. The minimum diameters of the ascending aorta, proximal arch, distal arch, isthmus, and descending aorta were measured using manual and intelligent methods, respectively. The Wilcoxon signed-rank test was used to analyze the differences between the two measurements. The surgical diagnosis results were used as the gold standard, and the diagnostic results obtained by the two measurement methods were compared with the gold standard to quantitatively evaluate the diagnostic results of CoA by the two measurement methods. The Kappa test was used to analyze the consistency of intelligence diagnosis results with the gold standard. RESULTS: Whether people have CoA or not, there was a significant difference (p < 0.05) in the measurements of the minimum diameter at most sites using the two methods. However, close final diagnoses were made using the intelligent method and the manual. Meanwhile, the intelligent measurement method obtained higher accuracy, specificity, and AUC (area under the curve) compared to manual measurement in diagnosing CoA based on Karl's classification (accuracy = 0.95, specificity = 0.9, and AUC = 0.94). Furthermore, the diagnostic results of the intelligence method applied to the three criteria agreed well with the gold standard (all kappa ≥ 0.8). The results of the comparative analysis showed that Karl's classification had the best diagnostic effect on CoA. CONCLUSION: The proposed intelligent method based on image processing can be successfully applied to assist in the diagnosis of CoA.
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spelling pubmed-99961732023-03-10 Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation Yan, Taocui Qin, Jinjie Zhang, Yulin Li, Qiuni Han, Baoru Jin, Xin Front Pediatr Pediatrics OBJECTIVE: To explore the application of the proposed intelligent image processing method in the diagnosis of aortic coarctation computed tomography angiography (CTA) and to clarify its value in the diagnosis of aortic coarctation based on the diagnosis results. METHODS: Fifty-three children with coarctation of the aorta (CoA) and forty children without CoA were selected to constitute the study population. CTA was performed on all subjects. The minimum diameters of the ascending aorta, proximal arch, distal arch, isthmus, and descending aorta were measured using manual and intelligent methods, respectively. The Wilcoxon signed-rank test was used to analyze the differences between the two measurements. The surgical diagnosis results were used as the gold standard, and the diagnostic results obtained by the two measurement methods were compared with the gold standard to quantitatively evaluate the diagnostic results of CoA by the two measurement methods. The Kappa test was used to analyze the consistency of intelligence diagnosis results with the gold standard. RESULTS: Whether people have CoA or not, there was a significant difference (p < 0.05) in the measurements of the minimum diameter at most sites using the two methods. However, close final diagnoses were made using the intelligent method and the manual. Meanwhile, the intelligent measurement method obtained higher accuracy, specificity, and AUC (area under the curve) compared to manual measurement in diagnosing CoA based on Karl's classification (accuracy = 0.95, specificity = 0.9, and AUC = 0.94). Furthermore, the diagnostic results of the intelligence method applied to the three criteria agreed well with the gold standard (all kappa ≥ 0.8). The results of the comparative analysis showed that Karl's classification had the best diagnostic effect on CoA. CONCLUSION: The proposed intelligent method based on image processing can be successfully applied to assist in the diagnosis of CoA. Frontiers Media S.A. 2023-02-23 /pmc/articles/PMC9996173/ /pubmed/36911025 http://dx.doi.org/10.3389/fped.2023.1131273 Text en © 2023 Yan, Qin, Zhang, Li, Han and Jin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pediatrics
Yan, Taocui
Qin, Jinjie
Zhang, Yulin
Li, Qiuni
Han, Baoru
Jin, Xin
Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
title Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
title_full Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
title_fullStr Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
title_full_unstemmed Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
title_short Research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
title_sort research and application of intelligent image processing technology in the auxiliary diagnosis of aortic coarctation
topic Pediatrics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996173/
https://www.ncbi.nlm.nih.gov/pubmed/36911025
http://dx.doi.org/10.3389/fped.2023.1131273
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