CT radiomics nomogram for prediction of the Ki-67 index in head and neck squamous cell carcinoma.
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| Title: | CT radiomics nomogram for prediction of the Ki-67 index in head and neck squamous cell carcinoma. |
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| Authors: | Zheng, Ying-mei1, Chen, Jing2, Zhang, Min3, Wu, Zeng-jie4, Tang, Guo-Zhang5, Zhang, Yue4, Dong, Cheng4 chengdong@qdu.edu.cn |
| Source: | European Radiology. Mar2023, Vol. 33 Issue 3, p2160-2170. 11p. 1 Color Photograph, 1 Diagram, 4 Charts, 4 Graphs. |
| Subjects: | Radiomics, Squamous cell carcinoma, Head & neck cancer, Antigens, Protein expression |
| Abstract: | Objectives: To construct and validate a contrast-enhanced computed tomography (CECT)–based radiomics nomogram to predict Ki-67 expression level in head and neck squamous cell carcinoma (HNSCC). Methods: A total of 217 patients with HNSCC who underwent CECT scans and immunohistochemical examination of their Ki-67 index were enrolled in this study. The patients were divided into a training set (n = 140; Ki-67: ≥ 50% [n = 72] and < 50% [n = 68]) and an external test set (n = 77; Ki-67: ≥ 50% [n = 38] and < 50% [n = 39]). The least absolute shrinkage and selection operator method was used to select key features for a CECT-image-based radiomics signature and a radiomics score (Rad-score) was calculated. A clinical model was established using clinical data and CT findings. The independent clinical factors and Rad-score were then combined to construct a radiomics nomogram. The performance characteristics of the Rad-score, clinical model, and nomogram were assessed using ROCs and decision curve analysis. Results: Twenty features were finally selected to construct the Rad-score. The radiomics nomogram incorporating the Rad-score, low histological grade, and lymphatic spread showed higher predictive value for the Ki-67 index (≥ 50% vs. < 50%) than the clinical model on both the training (AUC, 0.919 vs. 0.648, p < 0.001) and test (AUC, 0.832 vs. 0.685, p = 0.030) sets. Decision curve analysis demonstrated that the radiomics nomogram was more clinically useful than the clinical model. Conclusions: A CECT-based radiomics nomogram was constructed to predict the expression of Ki-67 in HNSCC. This model showed favorable predictive efficacy and might be useful for prognostic evaluation and clinical decision-making in patients with HNSCC. Key Points: • Accurate pre-treatment prediction of Ki-67 index in HNSCC is crucial. • A CECT-based radiomics nomogram showed favorable predictive efficacy in estimation of Ki-67 expression status in HNSCC patients. [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.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 161963585 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: CT radiomics nomogram for prediction of the Ki-67 index in head and neck squamous cell carcinoma. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zheng%2C+Ying-mei%22">Zheng, Ying-mei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Jing%22">Chen, Jing</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Min%22">Zhang, Min</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Wu%2C+Zeng-jie%22">Wu, Zeng-jie</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Tang%2C+Guo-Zhang%22">Tang, Guo-Zhang</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Yue%22">Zhang, Yue</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Dong%2C+Cheng%22">Dong, Cheng</searchLink><relatesTo>4</relatesTo><i> chengdong@qdu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22European+Radiology%22">European Radiology</searchLink>. Mar2023, Vol. 33 Issue 3, p2160-2170. 11p. 1 Color Photograph, 1 Diagram, 4 Charts, 4 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Radiomics%22">Radiomics</searchLink><br /><searchLink fieldCode="DE" term="%22Squamous+cell+carcinoma%22">Squamous cell carcinoma</searchLink><br /><searchLink fieldCode="DE" term="%22Head+%26+neck+cancer%22">Head & neck cancer</searchLink><br /><searchLink fieldCode="DE" term="%22Antigens%22">Antigens</searchLink><br /><searchLink fieldCode="DE" term="%22Protein+expression%22">Protein expression</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Objectives: To construct and validate a contrast-enhanced computed tomography (CECT)–based radiomics nomogram to predict Ki-67 expression level in head and neck squamous cell carcinoma (HNSCC). Methods: A total of 217 patients with HNSCC who underwent CECT scans and immunohistochemical examination of their Ki-67 index were enrolled in this study. The patients were divided into a training set (n = 140; Ki-67: ≥ 50% [n = 72] and < 50% [n = 68]) and an external test set (n = 77; Ki-67: ≥ 50% [n = 38] and < 50% [n = 39]). The least absolute shrinkage and selection operator method was used to select key features for a CECT-image-based radiomics signature and a radiomics score (Rad-score) was calculated. A clinical model was established using clinical data and CT findings. The independent clinical factors and Rad-score were then combined to construct a radiomics nomogram. The performance characteristics of the Rad-score, clinical model, and nomogram were assessed using ROCs and decision curve analysis. Results: Twenty features were finally selected to construct the Rad-score. The radiomics nomogram incorporating the Rad-score, low histological grade, and lymphatic spread showed higher predictive value for the Ki-67 index (≥ 50% vs. < 50%) than the clinical model on both the training (AUC, 0.919 vs. 0.648, p < 0.001) and test (AUC, 0.832 vs. 0.685, p = 0.030) sets. Decision curve analysis demonstrated that the radiomics nomogram was more clinically useful than the clinical model. Conclusions: A CECT-based radiomics nomogram was constructed to predict the expression of Ki-67 in HNSCC. This model showed favorable predictive efficacy and might be useful for prognostic evaluation and clinical decision-making in patients with HNSCC. Key Points: • Accurate pre-treatment prediction of Ki-67 index in HNSCC is crucial. • A CECT-based radiomics nomogram showed favorable predictive efficacy in estimation of Ki-67 expression status in HNSCC patients. [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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00330-022-09168-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 2160 Subjects: – SubjectFull: Radiomics Type: general – SubjectFull: Squamous cell carcinoma Type: general – SubjectFull: Head & neck cancer Type: general – SubjectFull: Antigens Type: general – SubjectFull: Protein expression Type: general Titles: – TitleFull: CT radiomics nomogram for prediction of the Ki-67 index in head and neck squamous cell carcinoma. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zheng, Ying-mei – PersonEntity: Name: NameFull: Chen, Jing – PersonEntity: Name: NameFull: Zhang, Min – PersonEntity: Name: NameFull: Wu, Zeng-jie – PersonEntity: Name: NameFull: Tang, Guo-Zhang – PersonEntity: Name: NameFull: Zhang, Yue – PersonEntity: Name: NameFull: Dong, Cheng IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 09387994 Numbering: – Type: volume Value: 33 – Type: issue Value: 3 Titles: – TitleFull: European Radiology Type: main |
| ResultId | 1 |
