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ESR Bridges: imaging and treatment of extranodal spread in head and neck cancer—a multidisciplinary view.

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Title: ESR Bridges: imaging and treatment of extranodal spread in head and neck cancer—a multidisciplinary view.
Authors: Becker, Minerva1 (AUTHOR) Minerva.Becker@hug.ch, van den Brekel, Michiel M. W.2 (AUTHOR), Maroldi, Roberto3 (AUTHOR)
Source: European Radiology. Feb2025, Vol. 35 Issue 2, p640-642. 3p.
Subjects: Biometry, Magnetic resonance imaging, Machine learning, Cross-sectional imaging, Prognosis, Neck dissection
Abstract: The article discusses the challenges in diagnosing and treating extranodal spread in head and neck cancer, particularly focusing on the impact of extranodal extension (ENE) on prognosis and treatment decisions. It highlights the importance of distinguishing between clinical, histopathological, and imaging-based diagnosis of ENE, as well as the need for multidisciplinary collaboration in patient care. The article also emphasizes the limitations of current imaging techniques in detecting microscopic ENE and suggests the potential role of artificial intelligence in improving ENE detection. The authors call for further research to standardize diagnostic criteria, refine imaging techniques, and enhance treatment outcomes for patients with head and neck cancer. [Extracted from the article]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="AR" term="%22Becker%2C+Minerva%22">Becker, Minerva</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> Minerva.Becker@hug.ch</i><br /><searchLink fieldCode="AR" term="%22van+den+Brekel%2C+Michiel+M%2E+W%2E%22">van den Brekel, Michiel M. W.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Maroldi%2C+Roberto%22">Maroldi, Roberto</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Radiology%22">European Radiology</searchLink>. Feb2025, Vol. 35 Issue 2, p640-642. 3p.
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  Data: <searchLink fieldCode="DE" term="%22Biometry%22">Biometry</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+imaging%22">Cross-sectional imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Prognosis%22">Prognosis</searchLink><br /><searchLink fieldCode="DE" term="%22Neck+dissection%22">Neck dissection</searchLink>
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  Data: The article discusses the challenges in diagnosing and treating extranodal spread in head and neck cancer, particularly focusing on the impact of extranodal extension (ENE) on prognosis and treatment decisions. It highlights the importance of distinguishing between clinical, histopathological, and imaging-based diagnosis of ENE, as well as the need for multidisciplinary collaboration in patient care. The article also emphasizes the limitations of current imaging techniques in detecting microscopic ENE and suggests the potential role of artificial intelligence in improving ENE detection. The authors call for further research to standardize diagnostic criteria, refine imaging techniques, and enhance treatment outcomes for patients with head and neck cancer. [Extracted from the article]
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  Data: <i>Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00330-024-10989-w
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        Text: English
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        Type: general
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        Type: general
      – SubjectFull: Machine learning
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      – SubjectFull: Cross-sectional imaging
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      – SubjectFull: Prognosis
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      – SubjectFull: Neck dissection
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      – TitleFull: ESR Bridges: imaging and treatment of extranodal spread in head and neck cancer—a multidisciplinary view.
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              Text: Feb2025
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              Y: 2025
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