Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Coluna/Columna |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1808-18512015000100018 |
Resumo: | OBJECTIVE: Early detection of degenerative changes in lumbar intervertebral disc by magnetic resonance imaging in a semiautomatic classifier for prevention of degenerative disease. METHOD: MRIs were selected with a diagnosis of degenerative disc disease or back pain from January to May 2014, with a sample of 23 patients and a total of 170 disks evaluated by sagittal T2 MRI image, first evaluated by a specialist physician in training and them were introduced into the software, being the results compared. RESULTS: One hundred and fifteen discs were evaluated by a programmed semiautomatic classifier to identify MODIC changes and hernia, which produced results "normal or MODIC" and "normal or abnormal", respectively. With a total of 230 readings, of which 141 were correct, 84 were reading errors and 10 readings were undiagnosed, the semiautomatic classifier is a useful tool for early diagnosis or established disease and is easy to apply because of the speed and ease of use; however, at this early stage of development, software is inferior to clinical observations and the results were from around 65% to 60% certainty for MODIC rating and 61% to 58% for disc herniation, compared with clinical evaluations. CONCLUSION: The comparative results between the two doctors were 94 consistent results and only 21 errors, which represents 81% certainty. |
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Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonanceIntervertebral discHerniaLow back painMagnetic resonance imaging OBJECTIVE: Early detection of degenerative changes in lumbar intervertebral disc by magnetic resonance imaging in a semiautomatic classifier for prevention of degenerative disease. METHOD: MRIs were selected with a diagnosis of degenerative disc disease or back pain from January to May 2014, with a sample of 23 patients and a total of 170 disks evaluated by sagittal T2 MRI image, first evaluated by a specialist physician in training and them were introduced into the software, being the results compared. RESULTS: One hundred and fifteen discs were evaluated by a programmed semiautomatic classifier to identify MODIC changes and hernia, which produced results "normal or MODIC" and "normal or abnormal", respectively. With a total of 230 readings, of which 141 were correct, 84 were reading errors and 10 readings were undiagnosed, the semiautomatic classifier is a useful tool for early diagnosis or established disease and is easy to apply because of the speed and ease of use; however, at this early stage of development, software is inferior to clinical observations and the results were from around 65% to 60% certainty for MODIC rating and 61% to 58% for disc herniation, compared with clinical evaluations. CONCLUSION: The comparative results between the two doctors were 94 consistent results and only 21 errors, which represents 81% certainty. Sociedade Brasileira de Coluna2015-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1808-18512015000100018Coluna/Columna v.14 n.1 2015reponame:Coluna/Columnainstname:Sociedade Brasileira de Coluna (SBCO)instacron:SBCO10.1590/S1808-1851201514010R121info:eu-repo/semantics/openAccessVivas,Eduardo López ArceOliva,Francisco Javier CisnerosAguilar,Rita Quetziquel FuentesGonzález,Alejandro GarcíaCruz,José GonzálezÁvila,José María Jiménezeng2015-08-03T00:00:00Zoai:scielo:S1808-18512015000100018Revistahttps://www.revistacoluna.org/ONGhttps://old.scielo.br/oai/scielo-oai.phpcoluna.columna@uol.com.br||revistacoluna@uol.com.br2177-014X1808-1851opendoar:2015-08-03T00:00Coluna/Columna - Sociedade Brasileira de Coluna (SBCO)false |
dc.title.none.fl_str_mv |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
title |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
spellingShingle |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance Vivas,Eduardo López Arce Intervertebral disc Hernia Low back pain Magnetic resonance imaging |
title_short |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
title_full |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
title_fullStr |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
title_full_unstemmed |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
title_sort |
Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance |
author |
Vivas,Eduardo López Arce |
author_facet |
Vivas,Eduardo López Arce Oliva,Francisco Javier Cisneros Aguilar,Rita Quetziquel Fuentes González,Alejandro García Cruz,José González Ávila,José María Jiménez |
author_role |
author |
author2 |
Oliva,Francisco Javier Cisneros Aguilar,Rita Quetziquel Fuentes González,Alejandro García Cruz,José González Ávila,José María Jiménez |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Vivas,Eduardo López Arce Oliva,Francisco Javier Cisneros Aguilar,Rita Quetziquel Fuentes González,Alejandro García Cruz,José González Ávila,José María Jiménez |
dc.subject.por.fl_str_mv |
Intervertebral disc Hernia Low back pain Magnetic resonance imaging |
topic |
Intervertebral disc Hernia Low back pain Magnetic resonance imaging |
description |
OBJECTIVE: Early detection of degenerative changes in lumbar intervertebral disc by magnetic resonance imaging in a semiautomatic classifier for prevention of degenerative disease. METHOD: MRIs were selected with a diagnosis of degenerative disc disease or back pain from January to May 2014, with a sample of 23 patients and a total of 170 disks evaluated by sagittal T2 MRI image, first evaluated by a specialist physician in training and them were introduced into the software, being the results compared. RESULTS: One hundred and fifteen discs were evaluated by a programmed semiautomatic classifier to identify MODIC changes and hernia, which produced results "normal or MODIC" and "normal or abnormal", respectively. With a total of 230 readings, of which 141 were correct, 84 were reading errors and 10 readings were undiagnosed, the semiautomatic classifier is a useful tool for early diagnosis or established disease and is easy to apply because of the speed and ease of use; however, at this early stage of development, software is inferior to clinical observations and the results were from around 65% to 60% certainty for MODIC rating and 61% to 58% for disc herniation, compared with clinical evaluations. CONCLUSION: The comparative results between the two doctors were 94 consistent results and only 21 errors, which represents 81% certainty. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-03-01 |
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=S1808-18512015000100018 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1808-18512015000100018 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1808-1851201514010R121 |
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 Coluna |
publisher.none.fl_str_mv |
Sociedade Brasileira de Coluna |
dc.source.none.fl_str_mv |
Coluna/Columna v.14 n.1 2015 reponame:Coluna/Columna instname:Sociedade Brasileira de Coluna (SBCO) instacron:SBCO |
instname_str |
Sociedade Brasileira de Coluna (SBCO) |
instacron_str |
SBCO |
institution |
SBCO |
reponame_str |
Coluna/Columna |
collection |
Coluna/Columna |
repository.name.fl_str_mv |
Coluna/Columna - Sociedade Brasileira de Coluna (SBCO) |
repository.mail.fl_str_mv |
coluna.columna@uol.com.br||revistacoluna@uol.com.br |
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1752126614760587264 |