Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review
<h3>Purpose</h3><p dir="ltr">The purpose of this scoping review is to analyze the application of artificial intelligence (AI) in ultrasound (US) imaging for diagnosing carpal tunnel syndrome (CTS), with an aim to explore the potential of AI in enhancing diagnostic accurac...
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2025
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| _version_ | 1864513537119879168 |
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| author | Yosra Magdi Mekki (21673721) |
| author2 | Hye Chang Rhim (9135305) Daniel Daneshvar (20621151) Antonios N. Pouliopoulos (22457659) Catherine Curtin (6307904) Elisabet Hagert (13528690) |
| author2_role | author author author author author |
| author_facet | Yosra Magdi Mekki (21673721) Hye Chang Rhim (9135305) Daniel Daneshvar (20621151) Antonios N. Pouliopoulos (22457659) Catherine Curtin (6307904) Elisabet Hagert (13528690) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yosra Magdi Mekki (21673721) Hye Chang Rhim (9135305) Daniel Daneshvar (20621151) Antonios N. Pouliopoulos (22457659) Catherine Curtin (6307904) Elisabet Hagert (13528690) |
| dc.date.none.fl_str_mv | 2025-03-18T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1007/s00264-025-06497-1 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Applications_of_artificial_intelligence_in_ultrasound_imaging_for_carpal-tunnel_syndrome_diagnosis_a_scoping_review/30393184 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Clinical sciences Neurosciences Health sciences Health services and systems Sports science and exercise Carpal tunnel syndrome (CTS) US imaging Artificial intelligence (AI) Scoping review |
| dc.title.none.fl_str_mv | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <h3>Purpose</h3><p dir="ltr">The purpose of this scoping review is to analyze the application of artificial intelligence (AI) in ultrasound (US) imaging for diagnosing carpal tunnel syndrome (CTS), with an aim to explore the potential of AI in enhancing diagnostic accuracy, efficiency, and patient outcomes by automating tasks, providing objective measurements, and facilitating earlier detection of CTS.</p><h3>Methods</h3><p dir="ltr">We systematically searched multiple electronic databases, including Embase, PubMed, IEEE Xplore, and Scopus, to identify relevant studies published up to January 1, 2025. Studies were included if they focused on the application of AI in US imaging for CTS diagnosis. Editorials, expert opinions, conference papers, dataset publications, and studies that did not have a clear clinical application of the AI algorithm were excluded.</p><h3>Results</h3><p dir="ltr">345 articles were identified, following abstract and full-text review by two independent reviewers, 18 manuscripts were included. Of these, thirteen studies were experimental studies, three were comparative studies, and one was a feasibility study. All eighteen studies shared the common objective of improving CTS diagnosis and/or initial assessment using AI, with shared aims ranging from median nerve segmentation (<i>n</i> = 12) to automated diagnosis (<i>n</i> = 9) and severity classification (<i>n</i> = 2). The majority of studies utilized deep learning approaches, particularly CNNs (<i>n</i> = 15), and some focused on radiomics features (<i>n</i> = 5) and traditional machine learning techniques.</p><h3>Conclusion</h3><p dir="ltr">The integration of AI in US imaging for CTS diagnosis holds significant promise for transforming clinical practice. AI has the potential to improve diagnostic accuracy, streamline the diagnostic process, reduce variability, and ultimately lead to better patient outcomes. Further research is needed to address challenges related to dataset limitations, variability in US imaging, and ethical considerations.</p><h2>Other Information</h2><p dir="ltr">Published in: International Orthopaedics<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s00264-025-06497-1" target="_blank">https://dx.doi.org/10.1007/s00264-025-06497-1</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_9680c457c965cc7e26c8bdd753896e54 |
| identifier_str_mv | 10.1007/s00264-025-06497-1 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30393184 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping reviewYosra Magdi Mekki (21673721)Hye Chang Rhim (9135305)Daniel Daneshvar (20621151)Antonios N. Pouliopoulos (22457659)Catherine Curtin (6307904)Elisabet Hagert (13528690)Biomedical and clinical sciencesClinical sciencesNeurosciencesHealth sciencesHealth services and systemsSports science and exerciseCarpal tunnel syndrome (CTS)US imagingArtificial intelligence (AI)Scoping review<h3>Purpose</h3><p dir="ltr">The purpose of this scoping review is to analyze the application of artificial intelligence (AI) in ultrasound (US) imaging for diagnosing carpal tunnel syndrome (CTS), with an aim to explore the potential of AI in enhancing diagnostic accuracy, efficiency, and patient outcomes by automating tasks, providing objective measurements, and facilitating earlier detection of CTS.</p><h3>Methods</h3><p dir="ltr">We systematically searched multiple electronic databases, including Embase, PubMed, IEEE Xplore, and Scopus, to identify relevant studies published up to January 1, 2025. Studies were included if they focused on the application of AI in US imaging for CTS diagnosis. Editorials, expert opinions, conference papers, dataset publications, and studies that did not have a clear clinical application of the AI algorithm were excluded.</p><h3>Results</h3><p dir="ltr">345 articles were identified, following abstract and full-text review by two independent reviewers, 18 manuscripts were included. Of these, thirteen studies were experimental studies, three were comparative studies, and one was a feasibility study. All eighteen studies shared the common objective of improving CTS diagnosis and/or initial assessment using AI, with shared aims ranging from median nerve segmentation (<i>n</i> = 12) to automated diagnosis (<i>n</i> = 9) and severity classification (<i>n</i> = 2). The majority of studies utilized deep learning approaches, particularly CNNs (<i>n</i> = 15), and some focused on radiomics features (<i>n</i> = 5) and traditional machine learning techniques.</p><h3>Conclusion</h3><p dir="ltr">The integration of AI in US imaging for CTS diagnosis holds significant promise for transforming clinical practice. AI has the potential to improve diagnostic accuracy, streamline the diagnostic process, reduce variability, and ultimately lead to better patient outcomes. Further research is needed to address challenges related to dataset limitations, variability in US imaging, and ethical considerations.</p><h2>Other Information</h2><p dir="ltr">Published in: International Orthopaedics<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s00264-025-06497-1" target="_blank">https://dx.doi.org/10.1007/s00264-025-06497-1</a></p>2025-03-18T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s00264-025-06497-1https://figshare.com/articles/journal_contribution/Applications_of_artificial_intelligence_in_ultrasound_imaging_for_carpal-tunnel_syndrome_diagnosis_a_scoping_review/30393184CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/303931842025-03-18T09:00:00Z |
| spellingShingle | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review Yosra Magdi Mekki (21673721) Biomedical and clinical sciences Clinical sciences Neurosciences Health sciences Health services and systems Sports science and exercise Carpal tunnel syndrome (CTS) US imaging Artificial intelligence (AI) Scoping review |
| status_str | publishedVersion |
| title | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| title_full | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| title_fullStr | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| title_full_unstemmed | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| title_short | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| title_sort | Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review |
| topic | Biomedical and clinical sciences Clinical sciences Neurosciences Health sciences Health services and systems Sports science and exercise Carpal tunnel syndrome (CTS) US imaging Artificial intelligence (AI) Scoping review |