An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study.
Saved in:
| Title: | An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study. |
|---|---|
| Authors: | Chen, Juan1,2,3 (AUTHOR), Lu, Shanhong1,2,3 (AUTHOR), Mao, Yitao4 (AUTHOR), Tan, Lei5 (AUTHOR), Li, Guo1,2,3 (AUTHOR), Gao, Yan1,2,3 (AUTHOR), Tan, Pingqing6 (AUTHOR), Huang, Donghai1,2,3,7 (AUTHOR), Zhang, Xin1,2,3,7 (AUTHOR), Qiu, Yuanzheng1,2,3,7 (AUTHOR) xyqyz@csu.edu.cn, Liu, Yong1,2,3,7 (AUTHOR) liuyongent@csu.edu.cn |
| Source: | European Radiology. Mar2022, Vol. 32 Issue 3, p1548-1557. 10p. |
| Subjects: | Hypopharyngeal cancer, Overall survival, Cohort analysis, Radiomics, Risk assessment, Nomography (Mathematics), Magnetic resonance imaging |
| Abstract: | Objective: To explore whether radiomics features extracted from pre-treatment magnetic resonance imaging (MRI) can predict the overall survival (OS) in patients with hypopharyngeal squamous cell carcinoma. Methods: A total of 190 patients with hypopharyngeal squamous cell carcinoma were eligibly enrolled from two institutions. Radiomics features were extracted from contrast-enhanced axial T1-weighted (CE-T1WI) sequence. The least absolute shrinkage selection operator (LASSO) algorithm was applied to establish a radiomics score correlated with OS. Multivariate logistic regression analysis was applied to determine the independent risk factors, which was combined with radiomics score to build the final radiomics nomogram. Results: A radiomics score with 6 CE-T1WI features for OS prediction was constructed and validated; its integration with specific clinicopathologic factors (N stage) showed a better prediction performance in the training, internal validation, and external validation cohorts (C-index 0.78, 0.75, and 0.75). Calibration curves determined a good agreement between the predicted and actual overall survival. Conclusions: The radiomics-clinical nomogram and radiomics score might be non-invasive and reliable methods for the risk stratification in patients with hypopharyngeal squamous cell carcinoma. Key Points: • An MRI-based radiomics model was constructed to evaluate of OS in patients with hypopharyngeal squamous cell carcinoma. • A radiomics-clinical nomogram that combined radiomics features and clinical characteristics was established. • Multi-cohort study validated the predictive performance of the radiomics-clinical nomogram to stratify patients with high risk in clinical practice. [ABSTRACT FROM AUTHOR] |
| 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 |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 155182495 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chen%2C+Juan%22">Chen, Juan</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Shanhong%22">Lu, Shanhong</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mao%2C+Yitao%22">Mao, Yitao</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tan%2C+Lei%22">Tan, Lei</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Guo%22">Li, Guo</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gao%2C+Yan%22">Gao, Yan</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tan%2C+Pingqing%22">Tan, Pingqing</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Donghai%22">Huang, Donghai</searchLink><relatesTo>1,2,3,7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xin%22">Zhang, Xin</searchLink><relatesTo>1,2,3,7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qiu%2C+Yuanzheng%22">Qiu, Yuanzheng</searchLink><relatesTo>1,2,3,7</relatesTo> (AUTHOR)<i> xyqyz@csu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Yong%22">Liu, Yong</searchLink><relatesTo>1,2,3,7</relatesTo> (AUTHOR)<i> liuyongent@csu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22European+Radiology%22">European Radiology</searchLink>. Mar2022, Vol. 32 Issue 3, p1548-1557. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Hypopharyngeal+cancer%22">Hypopharyngeal cancer</searchLink><br /><searchLink fieldCode="DE" term="%22Overall+survival%22">Overall survival</searchLink><br /><searchLink fieldCode="DE" term="%22Cohort+analysis%22">Cohort analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Radiomics%22">Radiomics</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Nomography+%28Mathematics%29%22">Nomography (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Objective: To explore whether radiomics features extracted from pre-treatment magnetic resonance imaging (MRI) can predict the overall survival (OS) in patients with hypopharyngeal squamous cell carcinoma. Methods: A total of 190 patients with hypopharyngeal squamous cell carcinoma were eligibly enrolled from two institutions. Radiomics features were extracted from contrast-enhanced axial T1-weighted (CE-T1WI) sequence. The least absolute shrinkage selection operator (LASSO) algorithm was applied to establish a radiomics score correlated with OS. Multivariate logistic regression analysis was applied to determine the independent risk factors, which was combined with radiomics score to build the final radiomics nomogram. Results: A radiomics score with 6 CE-T1WI features for OS prediction was constructed and validated; its integration with specific clinicopathologic factors (N stage) showed a better prediction performance in the training, internal validation, and external validation cohorts (C-index 0.78, 0.75, and 0.75). Calibration curves determined a good agreement between the predicted and actual overall survival. Conclusions: The radiomics-clinical nomogram and radiomics score might be non-invasive and reliable methods for the risk stratification in patients with hypopharyngeal squamous cell carcinoma. Key Points: • An MRI-based radiomics model was constructed to evaluate of OS in patients with hypopharyngeal squamous cell carcinoma. • A radiomics-clinical nomogram that combined radiomics features and clinical characteristics was established. • Multi-cohort study validated the predictive performance of the radiomics-clinical nomogram to stratify patients with high risk in clinical practice. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=155182495 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00330-021-08292-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 1548 Subjects: – SubjectFull: Hypopharyngeal cancer Type: general – SubjectFull: Overall survival Type: general – SubjectFull: Cohort analysis Type: general – SubjectFull: Radiomics Type: general – SubjectFull: Risk assessment Type: general – SubjectFull: Nomography (Mathematics) Type: general – SubjectFull: Magnetic resonance imaging Type: general Titles: – TitleFull: An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chen, Juan – PersonEntity: Name: NameFull: Lu, Shanhong – PersonEntity: Name: NameFull: Mao, Yitao – PersonEntity: Name: NameFull: Tan, Lei – PersonEntity: Name: NameFull: Li, Guo – PersonEntity: Name: NameFull: Gao, Yan – PersonEntity: Name: NameFull: Tan, Pingqing – PersonEntity: Name: NameFull: Huang, Donghai – PersonEntity: Name: NameFull: Zhang, Xin – PersonEntity: Name: NameFull: Qiu, Yuanzheng – PersonEntity: Name: NameFull: Liu, Yong IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 09387994 Numbering: – Type: volume Value: 32 – Type: issue Value: 3 Titles: – TitleFull: European Radiology Type: main |
| ResultId | 1 |
