RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista brasileira de medicina do esporte (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000500456 |
Resumo: | ABSTRACT Introduction: The integrity of articular cartilage determines the functional state of the joint. In recent years, the development of MRI sequences of various articular cartilage has become the focus of many research topics. Objective: The accuracy of diagnosis of knee cartilage injury caused by motion injury was studied retrospectively by meta-three-dimensional software. Methods: Forty-six knee joints of 45 patients with sports injuries, multi-sequence MRI was performed before surgery, including conventional knee MRI (SET1WI, FSEPD/T2WI), 3D SPGR, and 3D FIESTA sequences. Results: According to the operation results, the sensitivity, specificity, positive predictive value, and negative predictive value of 3D SPGR combined with conventional MRI sequence evaluation of cartilage damage are the highest, 73%, 98%, 95%, and 90%. Conclusions: 3D SPGR combined with conventional MRI sequences can improve accurate evaluation and diagnosis of cartilage disease over a reasonable scan time. Level of evidence II; Therapeutic studies - investigation of treatment results. |
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Revista brasileira de medicina do esporte (Online) |
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RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWAREWounds and injuriesKneeDiagnostic imagingABSTRACT Introduction: The integrity of articular cartilage determines the functional state of the joint. In recent years, the development of MRI sequences of various articular cartilage has become the focus of many research topics. Objective: The accuracy of diagnosis of knee cartilage injury caused by motion injury was studied retrospectively by meta-three-dimensional software. Methods: Forty-six knee joints of 45 patients with sports injuries, multi-sequence MRI was performed before surgery, including conventional knee MRI (SET1WI, FSEPD/T2WI), 3D SPGR, and 3D FIESTA sequences. Results: According to the operation results, the sensitivity, specificity, positive predictive value, and negative predictive value of 3D SPGR combined with conventional MRI sequence evaluation of cartilage damage are the highest, 73%, 98%, 95%, and 90%. Conclusions: 3D SPGR combined with conventional MRI sequences can improve accurate evaluation and diagnosis of cartilage disease over a reasonable scan time. Level of evidence II; Therapeutic studies - investigation of treatment results.Sociedade Brasileira de Medicina do Exercício e do Esporte2021-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000500456Revista Brasileira de Medicina do Esporte v.27 n.5 2021reponame:Revista brasileira de medicina do esporte (Online)instname:Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE)instacron:SBMEE10.1590/1517-8692202127042021_0099info:eu-repo/semantics/openAccessLiu,NaiLiu,Bichuaneng2021-11-24T00:00:00Zoai:scielo:S1517-86922021000500456Revistahttp://www.scielo.br/rbmeONGhttps://old.scielo.br/oai/scielo-oai.php||revista@medicinadoesporte.org.br1806-99401517-8692opendoar:2021-11-24T00:00Revista brasileira de medicina do esporte (Online) - Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE)false |
dc.title.none.fl_str_mv |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
title |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
spellingShingle |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE Liu,Nai Wounds and injuries Knee Diagnostic imaging |
title_short |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
title_full |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
title_fullStr |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
title_full_unstemmed |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
title_sort |
RESEARCH ON KNEE SPORTS INJURY CLASSIFICATION BASED ON MEDICAL IMAGES AND KWON3D SOFTWARE |
author |
Liu,Nai |
author_facet |
Liu,Nai Liu,Bichuan |
author_role |
author |
author2 |
Liu,Bichuan |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Liu,Nai Liu,Bichuan |
dc.subject.por.fl_str_mv |
Wounds and injuries Knee Diagnostic imaging |
topic |
Wounds and injuries Knee Diagnostic imaging |
description |
ABSTRACT Introduction: The integrity of articular cartilage determines the functional state of the joint. In recent years, the development of MRI sequences of various articular cartilage has become the focus of many research topics. Objective: The accuracy of diagnosis of knee cartilage injury caused by motion injury was studied retrospectively by meta-three-dimensional software. Methods: Forty-six knee joints of 45 patients with sports injuries, multi-sequence MRI was performed before surgery, including conventional knee MRI (SET1WI, FSEPD/T2WI), 3D SPGR, and 3D FIESTA sequences. Results: According to the operation results, the sensitivity, specificity, positive predictive value, and negative predictive value of 3D SPGR combined with conventional MRI sequence evaluation of cartilage damage are the highest, 73%, 98%, 95%, and 90%. Conclusions: 3D SPGR combined with conventional MRI sequences can improve accurate evaluation and diagnosis of cartilage disease over a reasonable scan time. Level of evidence II; Therapeutic studies - investigation of treatment results. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000500456 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000500456 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1517-8692202127042021_0099 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina do Exercício e do Esporte |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina do Exercício e do Esporte |
dc.source.none.fl_str_mv |
Revista Brasileira de Medicina do Esporte v.27 n.5 2021 reponame:Revista brasileira de medicina do esporte (Online) instname:Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE) instacron:SBMEE |
instname_str |
Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE) |
instacron_str |
SBMEE |
institution |
SBMEE |
reponame_str |
Revista brasileira de medicina do esporte (Online) |
collection |
Revista brasileira de medicina do esporte (Online) |
repository.name.fl_str_mv |
Revista brasileira de medicina do esporte (Online) - Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE) |
repository.mail.fl_str_mv |
||revista@medicinadoesporte.org.br |
_version_ |
1752122237689790464 |