Prediction of local recurrence in tenosynovial giant cell tumor of the knee: Based on preoperative MRI evaluation into disease subtypes and severity
Tenosynovial giant cell tumors (TSGCTs) of the knee differ in their clinical outcome according to disease subtypes and severity. The aim of this study was to determine the predictive MRI features related to local recurrence in TSGCT of the knee regarding disease subtypes and severity. This retrospec...
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| description | Tenosynovial giant cell tumors (TSGCTs) of the knee differ in their clinical outcome according to disease subtypes and severity. The aim of this study was to determine the predictive MRI features related to local recurrence in TSGCT of the knee regarding disease subtypes and severity.
This retrospective study included 20 patients with pathology-proven TSGCT of the knee who underwent preoperative MRI and surgery from Jan. 2007 to Jan. 2022. The anatomical point of the lesion was determined with a knee mapping. And then MRI features related to disease subtype including nodularity (single vs. multinodular); margin (circumscribed vs. infiltrative); peripheral hypointenseity (present vs. absent); internal hypointensity reflecting hemosiderin deposition (speckled vs. granular) were assessed. Third, MRI features related to disease severity including involvement of bone, cartilage, and tendon were evaluated. MRI features for predicting local recurrence of TSGCT were tested using chi-square test and logistic regression analysis.
Ten patients with diffuse-type TSGCT (D-TSGCT) and 10 patients with localized-type TSGCT (L-TSGCT) were included. There were six cases of local recurrence and all of them were D-TSGCT and none for L-TSGCT with statistical difference (P = 0.015). D-TSGCT that was direct risk factor for local recurrence showed more multinodular (80.0% vs. 10.0%; P = 0.007), infiltrative margin (90.0% vs. 10.0%; P = 0.002), and absent peripheral hypointensity (100.0% vs. 20.0%; P = 0.001) than L-TSGCT. Multivariate analysis showed infiltrative margin (odds ratio [OR], 81.0; P = 0.003) was independent MRI factor for D-TSGCT. Disease severity for risk of local recurrence included cartilage (66.7% vs. 7.1%; P = 0.024) and tendon (100.0% vs. 28.6%; P = 0.015) involvement compared to no local recurrence. Multivariate analysis showed tendon involvement (OR, 12.5; P = 0.042) was predictive MRI parameter for local recurrence. By combining tumor margin and tendon involvement, local recurrence was predicted sensitively on preoperative MRI (sensitivity, 100%; specificity, 50%; accuracy, 65%).
D-TSGCTs was associated with local recurrence and showed multinodularity infiltrative margin, and absent peripheral hypointensity. Disease severity including cartilage and tendon involvement was associated with local recurrence. Preoperative MRI evaluation by combining disease subtypes and severity can predict local recurrence sensitively. |
| doi_str_mv | 10.1371/journal.pone.0287028 |
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This retrospective study included 20 patients with pathology-proven TSGCT of the knee who underwent preoperative MRI and surgery from Jan. 2007 to Jan. 2022. The anatomical point of the lesion was determined with a knee mapping. And then MRI features related to disease subtype including nodularity (single vs. multinodular); margin (circumscribed vs. infiltrative); peripheral hypointenseity (present vs. absent); internal hypointensity reflecting hemosiderin deposition (speckled vs. granular) were assessed. Third, MRI features related to disease severity including involvement of bone, cartilage, and tendon were evaluated. MRI features for predicting local recurrence of TSGCT were tested using chi-square test and logistic regression analysis.
Ten patients with diffuse-type TSGCT (D-TSGCT) and 10 patients with localized-type TSGCT (L-TSGCT) were included. There were six cases of local recurrence and all of them were D-TSGCT and none for L-TSGCT with statistical difference (P = 0.015). D-TSGCT that was direct risk factor for local recurrence showed more multinodular (80.0% vs. 10.0%; P = 0.007), infiltrative margin (90.0% vs. 10.0%; P = 0.002), and absent peripheral hypointensity (100.0% vs. 20.0%; P = 0.001) than L-TSGCT. Multivariate analysis showed infiltrative margin (odds ratio [OR], 81.0; P = 0.003) was independent MRI factor for D-TSGCT. Disease severity for risk of local recurrence included cartilage (66.7% vs. 7.1%; P = 0.024) and tendon (100.0% vs. 28.6%; P = 0.015) involvement compared to no local recurrence. Multivariate analysis showed tendon involvement (OR, 12.5; P = 0.042) was predictive MRI parameter for local recurrence. By combining tumor margin and tendon involvement, local recurrence was predicted sensitively on preoperative MRI (sensitivity, 100%; specificity, 50%; accuracy, 65%).
D-TSGCTs was associated with local recurrence and showed multinodularity infiltrative margin, and absent peripheral hypointensity. Disease severity including cartilage and tendon involvement was associated with local recurrence. Preoperative MRI evaluation by combining disease subtypes and severity can predict local recurrence sensitively.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0287028</identifier><identifier>PMID: 37315053</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Age ; Analysis ; Biology and Life Sciences ; Care and treatment ; Cartilage ; Chi-square test ; Diagnosis ; Diseases ; Giant Cell Tumor of Tendon Sheath ; Health risks ; Humans ; Injuries ; Knee ; Knee Joint - diagnostic imaging ; Knee Joint - surgery ; Magnetic Resonance Imaging ; Medical research ; Medicine and Health Sciences ; Medicine, Experimental ; Morphology ; Multivariate analysis ; Patients ; Radiation therapy ; Regression analysis ; Relapse ; Research and Analysis Methods ; Retrospective Studies ; Risk factors ; Software ; Statistical analysis ; Surgery ; Tendons ; Tendons - diagnostic imaging ; Tenosynovitis ; Tumors</subject><ispartof>PloS one, 2023-06, Vol.18 (6), p.e0287028-e0287028</ispartof><rights>Copyright: © 2023 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Kim et al 2023 Kim et al</rights><rights>2023 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c693t-6b1ee6d8fbed244537036f3bb11f08fe7a5fab1c0e1dbf2a40045835b7920ff73</citedby><cites>FETCH-LOGICAL-c693t-6b1ee6d8fbed244537036f3bb11f08fe7a5fab1c0e1dbf2a40045835b7920ff73</cites><orcidid>0000-0002-6296-5559</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266632/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266632/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37315053$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Jun-Ho</creatorcontrib><creatorcontrib>Lee, Seul Ki</creatorcontrib><creatorcontrib>Kim, Jee-Young</creatorcontrib><title>Prediction of local recurrence in tenosynovial giant cell tumor of the knee: Based on preoperative MRI evaluation into disease subtypes and severity</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Tenosynovial giant cell tumors (TSGCTs) of the knee differ in their clinical outcome according to disease subtypes and severity. The aim of this study was to determine the predictive MRI features related to local recurrence in TSGCT of the knee regarding disease subtypes and severity.
This retrospective study included 20 patients with pathology-proven TSGCT of the knee who underwent preoperative MRI and surgery from Jan. 2007 to Jan. 2022. The anatomical point of the lesion was determined with a knee mapping. And then MRI features related to disease subtype including nodularity (single vs. multinodular); margin (circumscribed vs. infiltrative); peripheral hypointenseity (present vs. absent); internal hypointensity reflecting hemosiderin deposition (speckled vs. granular) were assessed. Third, MRI features related to disease severity including involvement of bone, cartilage, and tendon were evaluated. MRI features for predicting local recurrence of TSGCT were tested using chi-square test and logistic regression analysis.
Ten patients with diffuse-type TSGCT (D-TSGCT) and 10 patients with localized-type TSGCT (L-TSGCT) were included. There were six cases of local recurrence and all of them were D-TSGCT and none for L-TSGCT with statistical difference (P = 0.015). D-TSGCT that was direct risk factor for local recurrence showed more multinodular (80.0% vs. 10.0%; P = 0.007), infiltrative margin (90.0% vs. 10.0%; P = 0.002), and absent peripheral hypointensity (100.0% vs. 20.0%; P = 0.001) than L-TSGCT. Multivariate analysis showed infiltrative margin (odds ratio [OR], 81.0; P = 0.003) was independent MRI factor for D-TSGCT. Disease severity for risk of local recurrence included cartilage (66.7% vs. 7.1%; P = 0.024) and tendon (100.0% vs. 28.6%; P = 0.015) involvement compared to no local recurrence. Multivariate analysis showed tendon involvement (OR, 12.5; P = 0.042) was predictive MRI parameter for local recurrence. By combining tumor margin and tendon involvement, local recurrence was predicted sensitively on preoperative MRI (sensitivity, 100%; specificity, 50%; accuracy, 65%).
D-TSGCTs was associated with local recurrence and showed multinodularity infiltrative margin, and absent peripheral hypointensity. Disease severity including cartilage and tendon involvement was associated with local recurrence. Preoperative MRI evaluation by combining disease subtypes and severity can predict local recurrence sensitively.</description><subject>Age</subject><subject>Analysis</subject><subject>Biology and Life Sciences</subject><subject>Care and treatment</subject><subject>Cartilage</subject><subject>Chi-square test</subject><subject>Diagnosis</subject><subject>Diseases</subject><subject>Giant Cell Tumor of Tendon Sheath</subject><subject>Health risks</subject><subject>Humans</subject><subject>Injuries</subject><subject>Knee</subject><subject>Knee Joint - diagnostic imaging</subject><subject>Knee Joint - surgery</subject><subject>Magnetic Resonance Imaging</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Medicine, Experimental</subject><subject>Morphology</subject><subject>Multivariate analysis</subject><subject>Patients</subject><subject>Radiation therapy</subject><subject>Regression analysis</subject><subject>Relapse</subject><subject>Research and Analysis Methods</subject><subject>Retrospective Studies</subject><subject>Risk factors</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Tendons</subject><subject>Tendons - 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diagnostic imaging</topic><topic>Knee Joint - surgery</topic><topic>Magnetic Resonance Imaging</topic><topic>Medical research</topic><topic>Medicine and Health Sciences</topic><topic>Medicine, Experimental</topic><topic>Morphology</topic><topic>Multivariate analysis</topic><topic>Patients</topic><topic>Radiation therapy</topic><topic>Regression analysis</topic><topic>Relapse</topic><topic>Research and Analysis Methods</topic><topic>Retrospective Studies</topic><topic>Risk factors</topic><topic>Software</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Tendons</topic><topic>Tendons - diagnostic imaging</topic><topic>Tenosynovitis</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Jun-Ho</creatorcontrib><creatorcontrib>Lee, Seul Ki</creatorcontrib><creatorcontrib>Kim, Jee-Young</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Jun-Ho</au><au>Lee, Seul Ki</au><au>Kim, Jee-Young</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of local recurrence in tenosynovial giant cell tumor of the knee: Based on preoperative MRI evaluation into disease subtypes and severity</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2023-06-14</date><risdate>2023</risdate><volume>18</volume><issue>6</issue><spage>e0287028</spage><epage>e0287028</epage><pages>e0287028-e0287028</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Tenosynovial giant cell tumors (TSGCTs) of the knee differ in their clinical outcome according to disease subtypes and severity. The aim of this study was to determine the predictive MRI features related to local recurrence in TSGCT of the knee regarding disease subtypes and severity.
This retrospective study included 20 patients with pathology-proven TSGCT of the knee who underwent preoperative MRI and surgery from Jan. 2007 to Jan. 2022. The anatomical point of the lesion was determined with a knee mapping. And then MRI features related to disease subtype including nodularity (single vs. multinodular); margin (circumscribed vs. infiltrative); peripheral hypointenseity (present vs. absent); internal hypointensity reflecting hemosiderin deposition (speckled vs. granular) were assessed. Third, MRI features related to disease severity including involvement of bone, cartilage, and tendon were evaluated. MRI features for predicting local recurrence of TSGCT were tested using chi-square test and logistic regression analysis.
Ten patients with diffuse-type TSGCT (D-TSGCT) and 10 patients with localized-type TSGCT (L-TSGCT) were included. There were six cases of local recurrence and all of them were D-TSGCT and none for L-TSGCT with statistical difference (P = 0.015). D-TSGCT that was direct risk factor for local recurrence showed more multinodular (80.0% vs. 10.0%; P = 0.007), infiltrative margin (90.0% vs. 10.0%; P = 0.002), and absent peripheral hypointensity (100.0% vs. 20.0%; P = 0.001) than L-TSGCT. Multivariate analysis showed infiltrative margin (odds ratio [OR], 81.0; P = 0.003) was independent MRI factor for D-TSGCT. Disease severity for risk of local recurrence included cartilage (66.7% vs. 7.1%; P = 0.024) and tendon (100.0% vs. 28.6%; P = 0.015) involvement compared to no local recurrence. Multivariate analysis showed tendon involvement (OR, 12.5; P = 0.042) was predictive MRI parameter for local recurrence. By combining tumor margin and tendon involvement, local recurrence was predicted sensitively on preoperative MRI (sensitivity, 100%; specificity, 50%; accuracy, 65%).
D-TSGCTs was associated with local recurrence and showed multinodularity infiltrative margin, and absent peripheral hypointensity. Disease severity including cartilage and tendon involvement was associated with local recurrence. Preoperative MRI evaluation by combining disease subtypes and severity can predict local recurrence sensitively.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>37315053</pmid><doi>10.1371/journal.pone.0287028</doi><tpages>e0287028</tpages><orcidid>https://orcid.org/0000-0002-6296-5559</orcidid><oa>free_for_read</oa></addata></record> |
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| recordid | cdi_plos_journals_2825791585 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Age Analysis Biology and Life Sciences Care and treatment Cartilage Chi-square test Diagnosis Diseases Giant Cell Tumor of Tendon Sheath Health risks Humans Injuries Knee Knee Joint - diagnostic imaging Knee Joint - surgery Magnetic Resonance Imaging Medical research Medicine and Health Sciences Medicine, Experimental Morphology Multivariate analysis Patients Radiation therapy Regression analysis Relapse Research and Analysis Methods Retrospective Studies Risk factors Software Statistical analysis Surgery Tendons Tendons - diagnostic imaging Tenosynovitis Tumors |
| title | Prediction of local recurrence in tenosynovial giant cell tumor of the knee: Based on preoperative MRI evaluation into disease subtypes and severity |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-12T19%3A01%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prediction%20of%20local%20recurrence%20in%20tenosynovial%20giant%20cell%20tumor%20of%20the%20knee:%20Based%20on%20preoperative%20MRI%20evaluation%20into%20disease%20subtypes%20and%20severity&rft.jtitle=PloS%20one&rft.au=Kim,%20Jun-Ho&rft.date=2023-06-14&rft.volume=18&rft.issue=6&rft.spage=e0287028&rft.epage=e0287028&rft.pages=e0287028-e0287028&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0287028&rft_dat=%3Cgale_plos_%3EA752983064%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2825791585&rft_id=info:pmid/37315053&rft_galeid=A752983064&rft_doaj_id=oai_doaj_org_article_f0b4dd1c8fb14480b93e8cb6be12cc11&rfr_iscdi=true |