Development and validation of a deep-learning model for scoring of radiographic finger joint destruction in rheumatoid arthritis
Identifieur interne : 000892 ( Main/Merge ); précédent : 000891; suivant : 000893Development and validation of a deep-learning model for scoring of radiographic finger joint destruction in rheumatoid arthritis
Auteurs : Toru Hirano ; Masayuki Nishide ; Naoki Nonaka ; Jun Seita ; Kosuke Ebina [Japon] ; Kazuhiro Sakurada ; Atsushi KumanogohSource :
- Rheumatology Advances in Practice [ 2514-1775 ] ; 2019.
Abstract
The purpose of this research was to develop a deep-learning model to assess radiographic finger joint destruction in RA.
The model comprises two steps: a joint-detection step and a joint-evaluation step. Among 216 radiographs of 108 patients with RA, 186 radiographs were assigned to the training/validation dataset and 30 to the test dataset. In the training/validation dataset, images of PIP joints, the IP joint of the thumb or MCP joints were manually clipped and scored for joint space narrowing (JSN) and bone erosion by clinicians, and then these images were augmented. As a result, 11 160 images were used to train and validate a deep convolutional neural network for joint evaluation. Three thousand seven hundred and twenty selected images were used to train machine learning for joint detection. These steps were combined as the assessment model for radiographic finger joint destruction. Performance of the model was examined using the test dataset, which was not included in the training/validation process, by comparing the scores assigned by the model and clinicians.
The model detected PIP joints, the IP joint of the thumb and MCP joints with a sensitivity of 95.3% and assigned scores for JSN and erosion. Accuracy (percentage of exact agreement) reached 49.3–65.4% for JSN and 70.6–74.1% for erosion. The correlation coefficient between scores by the model and clinicians per image was 0.72–0.88 for JSN and 0.54–0.75 for erosion.
Image processing with the trained convolutional neural network model is promising to assess radiographs in RA.
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DOI: 10.1093/rap/rkz047
PubMed: 31872173
PubMed Central: 6921374
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code="subfield">Osaka</wicri:noCountry></affiliation></author><author><name sortKey="Nonaka, Naoki" sort="Nonaka, Naoki" uniqKey="Nonaka N" first="Naoki" last="Nonaka">Naoki Nonaka</name><affiliation><nlm:aff id="rkz047-aff2"><institution>Medical Sciences Innovation Hub Program</institution>, RIKEN, Yokohama, Kanagawa</nlm:aff><wicri:noCountry code="subfield">Kanagawa</wicri:noCountry></affiliation></author><author><name sortKey="Seita, Jun" sort="Seita, Jun" uniqKey="Seita J" first="Jun" last="Seita">Jun Seita</name><affiliation><nlm:aff id="rkz047-aff2"><institution>Medical Sciences Innovation Hub Program</institution>, RIKEN, Yokohama, Kanagawa</nlm:aff><wicri:noCountry code="subfield">Kanagawa</wicri:noCountry></affiliation></author><author><name sortKey="Ebina, Kosuke" sort="Ebina, Kosuke" uniqKey="Ebina K" first="Kosuke" last="Ebina">Kosuke Ebina</name><affiliation wicri:level="1"><nlm:aff id="rkz047-aff3"><institution>Department of Musculoskeletal Regenerative Medicine, Graduate School of Medicine, Osaka University</institution>, Suita, Osaka,<country country="JP">Japan</country></nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Sakurada, Kazuhiro" sort="Sakurada, Kazuhiro" uniqKey="Sakurada K" first="Kazuhiro" last="Sakurada">Kazuhiro Sakurada</name><affiliation><nlm:aff id="rkz047-aff2"><institution>Medical Sciences Innovation Hub Program</institution>, RIKEN, Yokohama, Kanagawa</nlm:aff><wicri:noCountry code="subfield">Kanagawa</wicri:noCountry></affiliation></author><author><name sortKey="Kumanogoh, Atsushi" sort="Kumanogoh, Atsushi" uniqKey="Kumanogoh A" first="Atsushi" last="Kumanogoh">Atsushi Kumanogoh</name><affiliation><nlm:aff id="rkz047-aff1"><institution>Department of Respiratory Medicine and Clinical Immunology, Internal Medicine, Graduate School of Medicine</institution>, Osaka University, Suita, Osaka</nlm:aff><wicri:noCountry 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type="wicri:Area/Main/Merge">000892</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Development and validation of a deep-learning model for scoring of radiographic finger joint destruction in rheumatoid arthritis</title><author><name sortKey="Hirano, Toru" sort="Hirano, Toru" uniqKey="Hirano T" first="Toru" last="Hirano">Toru Hirano</name><affiliation><nlm:aff id="rkz047-aff1"><institution>Department of Respiratory Medicine and Clinical Immunology, Internal Medicine, Graduate School of Medicine</institution>, Osaka University, Suita, Osaka</nlm:aff><wicri:noCountry code="subfield">Osaka</wicri:noCountry></affiliation></author><author><name sortKey="Nishide, Masayuki" sort="Nishide, Masayuki" uniqKey="Nishide M" first="Masayuki" last="Nishide">Masayuki Nishide</name><affiliation><nlm:aff id="rkz047-aff1"><institution>Department of Respiratory Medicine and Clinical Immunology, Internal Medicine, Graduate School of Medicine</institution>, Osaka University, Suita, Osaka</nlm:aff><wicri:noCountry code="subfield">Osaka</wicri:noCountry></affiliation></author><author><name sortKey="Nonaka, Naoki" sort="Nonaka, Naoki" uniqKey="Nonaka N" first="Naoki" last="Nonaka">Naoki Nonaka</name><affiliation><nlm:aff id="rkz047-aff2"><institution>Medical Sciences Innovation Hub Program</institution>, RIKEN, Yokohama, Kanagawa</nlm:aff><wicri:noCountry code="subfield">Kanagawa</wicri:noCountry></affiliation></author><author><name sortKey="Seita, Jun" sort="Seita, Jun" uniqKey="Seita J" first="Jun" last="Seita">Jun Seita</name><affiliation><nlm:aff id="rkz047-aff2"><institution>Medical Sciences Innovation Hub Program</institution>, RIKEN, Yokohama, Kanagawa</nlm:aff><wicri:noCountry code="subfield">Kanagawa</wicri:noCountry></affiliation></author><author><name sortKey="Ebina, Kosuke" sort="Ebina, Kosuke" uniqKey="Ebina K" first="Kosuke" last="Ebina">Kosuke Ebina</name><affiliation wicri:level="1"><nlm:aff id="rkz047-aff3"><institution>Department of Musculoskeletal Regenerative Medicine, Graduate School of Medicine, Osaka University</institution>, Suita, Osaka,<country country="JP">Japan</country></nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Sakurada, Kazuhiro" sort="Sakurada, Kazuhiro" uniqKey="Sakurada K" first="Kazuhiro" last="Sakurada">Kazuhiro Sakurada</name><affiliation><nlm:aff id="rkz047-aff2"><institution>Medical Sciences Innovation Hub Program</institution>, RIKEN, Yokohama, Kanagawa</nlm:aff><wicri:noCountry code="subfield">Kanagawa</wicri:noCountry></affiliation></author><author><name sortKey="Kumanogoh, Atsushi" sort="Kumanogoh, Atsushi" uniqKey="Kumanogoh A" first="Atsushi" last="Kumanogoh">Atsushi Kumanogoh</name><affiliation><nlm:aff id="rkz047-aff1"><institution>Department of Respiratory Medicine and Clinical Immunology, Internal Medicine, Graduate School of Medicine</institution>, Osaka University, Suita, Osaka</nlm:aff><wicri:noCountry code="subfield">Osaka</wicri:noCountry></affiliation></author></analytic><series><title level="j">Rheumatology Advances in Practice</title><idno type="eISSN">2514-1775</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Abstract</title><sec id="s1"><title>Objective</title><p>The purpose of this research was to develop a deep-learning model to assess radiographic finger joint destruction in RA.</p></sec><sec id="s2"><title>Methods</title><p>The model comprises two steps: a joint-detection step and a joint-evaluation step. Among 216 radiographs of 108 patients with RA, 186 radiographs were assigned to the training/validation dataset and 30 to the test dataset. In the training/validation dataset, images of PIP joints, the IP joint of the thumb or MCP joints were manually clipped and scored for joint space narrowing (JSN) and bone erosion by clinicians, and then these images were augmented. As a result, 11 160 images were used to train and validate a deep convolutional neural network for joint evaluation. Three thousand seven hundred and twenty selected images were used to train machine learning for joint detection. These steps were combined as the assessment model for radiographic finger joint destruction. Performance of the model was examined using the test dataset, which was not included in the training/validation process, by comparing the scores assigned by the model and clinicians.</p></sec><sec id="s3"><title>Results</title><p>The model detected PIP joints, the IP joint of the thumb and MCP joints with a sensitivity of 95.3% and assigned scores for JSN and erosion. Accuracy (percentage of exact agreement) reached 49.3–65.4% for JSN and 70.6–74.1% for erosion. The correlation coefficient between scores by the model and clinicians per image was 0.72–0.88 for JSN and 0.54–0.75 for erosion.</p></sec><sec id="s4"><title>Conclusion</title><p>Image processing with the trained convolutional neural network model is promising to assess radiographs in RA.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Lecun, Y" uniqKey="Lecun Y">Y LeCun</name></author><author><name sortKey="Bengio, Y" uniqKey="Bengio Y">Y Bengio</name></author><author><name sortKey="Hinton, G" uniqKey="Hinton G">G. Hinton</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Webb, S" uniqKey="Webb S">S. Webb</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chartrand, G" uniqKey="Chartrand G">G Chartrand</name></author><author><name sortKey="Cheng, Pm" uniqKey="Cheng P">PM Cheng</name></author><author><name sortKey="Vorontsov, E" uniqKey="Vorontsov E">E Vorontsov</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gulshan, V" uniqKey="Gulshan V">V Gulshan</name></author><author><name sortKey="Peng, L" uniqKey="Peng L">L Peng</name></author><author><name sortKey="Coram, M" uniqKey="Coram M">M Coram</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Esteva, A" uniqKey="Esteva A">A Esteva</name></author><author><name sortKey="Kuprel, B" uniqKey="Kuprel B">B Kuprel</name></author><author><name sortKey="Novoa, Ra" uniqKey="Novoa R">RA Novoa</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fujisawa, Y" uniqKey="Fujisawa Y">Y Fujisawa</name></author><author><name sortKey="Otomo, Y" uniqKey="Otomo Y">Y Otomo</name></author><author><name sortKey="Ogata, Y" uniqKey="Ogata Y">Y Ogata</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Coudray, N" uniqKey="Coudray N">N Coudray</name></author><author><name sortKey="Ocampo, Ps" uniqKey="Ocampo P">PS Ocampo</name></author><author><name sortKey="Sakellaropoulos, T" uniqKey="Sakellaropoulos T">T Sakellaropoulos</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Walsh, Slf" uniqKey="Walsh S">SLF Walsh</name></author><author><name sortKey="Calandriello, L" uniqKey="Calandriello L">L Calandriello</name></author><author><name sortKey="Silva, M" uniqKey="Silva M">M Silva</name></author><author><name sortKey="Sverzellati, N" uniqKey="Sverzellati N">N. Sverzellati</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Smolen, Js" uniqKey="Smolen J">JS Smolen</name></author><author><name sortKey="Landewe, R" uniqKey="Landewe R">R Landewé</name></author><author><name sortKey="Bijlsma, J" uniqKey="Bijlsma J">J Bijlsma</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Steinbrocker, O" uniqKey="Steinbrocker O">O Steinbrocker</name></author><author><name sortKey="Traeger, Ch" uniqKey="Traeger C">CH Traeger</name></author><author><name sortKey="Batterman, Rc" uniqKey="Batterman R">RC. Batterman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kellgren, Jh" uniqKey="Kellgren J">JH Kellgren</name></author><author><name sortKey="Bier, F" uniqKey="Bier F">F. Bier</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sharp, Jt" uniqKey="Sharp J">JT Sharp</name></author><author><name sortKey="Lidsky, Md" uniqKey="Lidsky M">MD Lidsky</name></author><author><name sortKey="Collins, Lc" uniqKey="Collins L">LC Collins</name></author><author><name sortKey="Moreland, J" uniqKey="Moreland J">J. Moreland</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sharp, Jt" uniqKey="Sharp J">JT Sharp</name></author><author><name sortKey="Bluhm, Gb" uniqKey="Bluhm G">GB Bluhm</name></author><author><name sortKey="Brook, A" uniqKey="Brook A">A Brook</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Larsen, A" uniqKey="Larsen A">A Larsen</name></author><author><name sortKey="Dale, K" uniqKey="Dale K">K Dale</name></author><author><name sortKey="Eek, M" uniqKey="Eek M">M. Eek</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Genant, Hk" uniqKey="Genant H">HK. Genant</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Van Der Heijde, Dm" uniqKey="Van Der Heijde D">DM Van der Heijde</name></author><author><name sortKey="Van Riel, Pl" uniqKey="Van Riel P">PL Van Riel</name></author><author><name sortKey="Nuver Zwart, Ih" uniqKey="Nuver Zwart I">IH Nuver-Zwart</name></author><author><name sortKey="Gribnau, Fw" uniqKey="Gribnau F">FW Gribnau</name></author><author><name sortKey="Van De Putte, Lb" uniqKey="Van De Putte L">LB. Van de Putte</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Arnett, Fc" uniqKey="Arnett F">FC Arnett</name></author><author><name sortKey="Edworthy, Sm" uniqKey="Edworthy S">SM Edworthy</name></author><author><name sortKey="Bloch, Da" uniqKey="Bloch D">DA Bloch</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Aletaha, D" uniqKey="Aletaha D">D Aletaha</name></author><author><name sortKey="Neogi, T" uniqKey="Neogi T">T Neogi</name></author><author><name sortKey="Silman, Aj" uniqKey="Silman A">AJ Silman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Van Der Heijde, D" uniqKey="Van Der Heijde D">D. van der Heijde</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Viola, P" uniqKey="Viola P">P Viola</name></author><author><name sortKey="Jones, M" uniqKey="Jones M">M. Jones</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kingma, Dp" uniqKey="Kingma D">DP Kingma</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Loffe, S" uniqKey="Loffe S">S Loffe</name></author><author><name sortKey="Szegedy, C" uniqKey="Szegedy C">C. Szegedy</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Tokui, S" uniqKey="Tokui S">S Tokui</name></author><author><name sortKey="Oono, K" uniqKey="Oono K">K Oono</name></author><author><name sortKey="Hido, S" uniqKey="Hido S">S Hido</name></author><author><name sortKey="Clayton, J" uniqKey="Clayton J">J. Clayton</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Meyer, O" uniqKey="Meyer O">O Meyer</name></author><author><name sortKey="Labarre, C" uniqKey="Labarre C">C Labarre</name></author><author><name sortKey="Dougados, M" uniqKey="Dougados M">M Dougados</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Vencovsk, J" uniqKey="Vencovsk J">J Vencovský</name></author><author><name sortKey="Machacek, S" uniqKey="Machacek S">S Machácek</name></author><author><name sortKey="Sedova, L" uniqKey="Sedova L">L Sedová</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Koga, T" uniqKey="Koga T">T Koga</name></author><author><name sortKey="Okada, A" uniqKey="Okada A">A Okada</name></author><author><name sortKey="Fukuda, T" uniqKey="Fukuda T">T Fukuda</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Xue, Y" uniqKey="Xue Y">Y Xue</name></author><author><name sortKey="Zhang, R" uniqKey="Zhang R">R Zhang</name></author><author><name sortKey="Deng, Y" uniqKey="Deng Y">Y Deng</name></author><author><name sortKey="Chen, K" uniqKey="Chen K">K Chen</name></author><author><name sortKey="Jiang, T" uniqKey="Jiang T">T. Jiang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Spampinato, C" uniqKey="Spampinato C">C Spampinato</name></author><author><name sortKey="Palazzo, S" uniqKey="Palazzo S">S Palazzo</name></author><author><name sortKey="Giordano, D" uniqKey="Giordano D">D Giordano</name></author><author><name sortKey="Aldinucci, M" uniqKey="Aldinucci M">M Aldinucci</name></author><author><name sortKey="Leonardi, R" uniqKey="Leonardi R">R. Leonardi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Larson, Db" uniqKey="Larson D">DB Larson</name></author><author><name sortKey="Chen, Mc" uniqKey="Chen M">MC Chen</name></author><author><name sortKey="Lungren, Mp" uniqKey="Lungren M">MP Lungren</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lindsey, R" uniqKey="Lindsey R">R Lindsey</name></author><author><name sortKey="Daluiski, A" uniqKey="Daluiski A">A Daluiski</name></author><author><name sortKey="Chopra, S" uniqKey="Chopra S">S Chopra</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Liu, F" uniqKey="Liu F">F Liu</name></author><author><name sortKey="Zhou, Z" uniqKey="Zhou Z">Z Zhou</name></author><author><name sortKey="Samsonov, A" uniqKey="Samsonov A">A Samsonov</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Tack, A" uniqKey="Tack A">A Tack</name></author><author><name sortKey="Mukhopadhyay, A" uniqKey="Mukhopadhyay A">A Mukhopadhyay</name></author><author><name sortKey="Zachow, S" uniqKey="Zachow S">S. Zachow</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bien, N" uniqKey="Bien N">N Bien</name></author><author><name sortKey="Rajpurkar, P" uniqKey="Rajpurkar P">P Rajpurkar</name></author><author><name sortKey="Ball, Rl" uniqKey="Ball R">RL Ball</name></author></analytic></biblStruct></listBibl></div1></back></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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