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Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy

Publication ,  Journal Article
Dong, Y; Zhang, J; Lam, S; Zhang, X; Liu, A; Teng, X; Han, X; Cao, J; Li, H; Lee, FK; Yip, CW; Au, K; Zhang, Y; Cai, J
Published in: Cancers
April 1, 2023

(1) Background: Acute oral mucositis is the most common side effect for nasopharyngeal carcinoma patients receiving radiotherapy. Improper or delayed intervention to severe AOM could degrade the quality of life or survival for NPC patients. An effective prediction method for severe AOM is needed for the individualized management of NPC patients in the era of personalized medicine. (2) Methods: A total of 242 biopsy-proven NPC patients were retrospectively recruited in this study. Radiomics features were extracted from contrast-enhanced CT (CECT), contrast-enhanced T1-weighted (cT1WI), and T2-weighted (T2WI) images in the primary tumor and tumor-related area. Dosiomics features were extracted from 2D or 3D dose-volume histograms (DVH). Multiple models were established with single and integrated data. The dataset was randomized into training and test sets at a ratio of 7:3 with 10-fold cross-validation. (3) Results: The best-performing model using Gaussian Naive Bayes (GNB) (mean validation AUC = 0.81 ± 0.10) was established with integrated radiomics and dosiomics data. The GNB radiomics and dosiomics models yielded mean validation AUC of 0.6 ± 0.20 and 0.69 ± 0.14, respectively. (4) Conclusions: Integrating radiomics and dosiomics data from the primary tumor area could generate the best-performing model for severe AOM prediction.

Duke Scholars

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Published In

Cancers

DOI

EISSN

2072-6694

Publication Date

April 1, 2023

Volume

15

Issue

7

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
 

Citation

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Dong, Y., Zhang, J., Lam, S., Zhang, X., Liu, A., Teng, X., … Cai, J. (2023). Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy. Cancers, 15(7). https://doi.org/10.3390/cancers15072032
Dong, Y., J. Zhang, S. Lam, X. Zhang, A. Liu, X. Teng, X. Han, et al. “Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy.” Cancers 15, no. 7 (April 1, 2023). https://doi.org/10.3390/cancers15072032.
Dong, Y., et al. “Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy.” Cancers, vol. 15, no. 7, Apr. 2023. Scopus, doi:10.3390/cancers15072032.
Dong Y, Zhang J, Lam S, Zhang X, Liu A, Teng X, Han X, Cao J, Li H, Lee FK, Yip CW, Au K, Zhang Y, Cai J. Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy. Cancers. 2023 Apr 1;15(7).

Published In

Cancers

DOI

EISSN

2072-6694

Publication Date

April 1, 2023

Volume

15

Issue

7

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis