Literature DB >> 33484752

Normal tissue complication probability (NTCP) models for predicting temporal lobe injury after intensity-modulated radiotherapy in nasopharyngeal carcinoma: A large registry-based retrospective study from China.

Dan-Wan Wen1, Li Lin1, Yan-Ping Mao1, Chun-Yan Chen1, Fo-Ping Chen1, Chen-Fei Wu1, Xiao-Dan Huang1, Zhi-Xuan Li1, Si-Si Xu1, Jia Kou1, Xing-Li Yang1, Jun Ma1, Ying Sun1, Guan-Qun Zhou2.   

Abstract

PURPOSE: To develop predictive models with dosimetric and clinical variables for temporal lobe injury (TLI) in nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).
MATERIALS AND METHODS: Data of 8194 NPC patients who received IMRT-based treatment were retrospectively reviewed. TLI was diagnosed by magnetic resonance imaging. Dosimetric factors were selected by penalized regression and machine learning, with area under the receiver operating curve (AUC) calculated. Cox proportional hazards models containing the most predictive dosimetric factor with/without clinical variables were performed. A nomogram was generated as a visualization of Cox regression for predicting TLI-free survival.
RESULTS: During median follow-up of 66.8 months (interquartile range [IQR] 54.2-82.2 months), 12.1% of patients (989/8194) developed TLI. Median latency from IMRT to TLI was 36 months (IQR 28-47 months). D0.5cc (dose delivered to 0.5-cm3 temporal-lobe volume) was the most predictive dosimetric factor (AUC: 0.799). Tolerance dose for 5% and 50% probabilities to develop TLI in 5 years were 65.06 Gy (95% confidence interval [CI]: 64.19-65.92) and 89.75 Gy (95% CI: 87.39-92.11), respectively. A nomogram comprising age, T stage, and D0.5cc significantly outperformed the model with only D0.5cc in predicting TLI (C-index: 0.78 vs. 0.737 in train set; 0.775 vs. 0.73 in test set; both P < 0.001). The nomogram-defined high-risk group had worse 5-year TLI-free survival.
CONCLUSIONS: D0.5cc of 65.06 Gy was the tolerance dose of the temporal lobe. Reducing D0.5cc decreased risk of TLI, especially in older patients with advanced T stage. The nomogram could predict TLI precisely and allow individualized follow-up management.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Intensity-modulated radiotherapy; Machine learning; Nasopharyngeal carcinoma; Nomogram; Normal tissue complication probability; Temporal lobe injury

Mesh:

Year:  2021        PMID: 33484752     DOI: 10.1016/j.radonc.2021.01.008

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  2 in total

Review 1.  Application of Artificial Intelligence for Nasopharyngeal Carcinoma Management - A Systematic Review.

Authors:  Wai Tong Ng; Barton But; Horace C W Choi; Remco de Bree; Anne W M Lee; Victor H F Lee; Fernando López; Antti A Mäkitie; Juan P Rodrigo; Nabil F Saba; Raymond K Y Tsang; Alfio Ferlito
Journal:  Cancer Manag Res       Date:  2022-01-26       Impact factor: 3.989

Review 2.  Cognitive Decline following Radiotherapy of Head and Neck Cancer: Systematic Review and Meta-Analysis of MRI Correlates.

Authors:  Noor Shatirah Voon; Hanani Abdul Manan; Noorazrul Yahya
Journal:  Cancers (Basel)       Date:  2021-12-08       Impact factor: 6.639

  2 in total

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