Decision Trees Predicting Tumor Shrinkage for Head and Neck Cancer: Implications for Adaptive Radiotherapy

Technology in Cancer Research & Treatment
Murat SurucuBahman Emami

Abstract

To develop decision trees predicting for tumor volume reduction in patients with head and neck (H&N) cancer using pretreatment clinical and pathological parameters. Forty-eight patients treated with definitive concurrent chemoradiotherapy for squamous cell carcinoma of the nasopharynx, oropharynx, oral cavity, or hypopharynx were retrospectively analyzed. These patients were rescanned at a median dose of 37.8 Gy and replanned to account for anatomical changes. The percentages of gross tumor volume (GTV) change from initial to rescan computed tomography (CT; %GTVΔ) were calculated. Two decision trees were generated to correlate %GTVΔ in primary and nodal volumes with 14 characteristics including age, gender, Karnofsky performance status (KPS), site, human papilloma virus (HPV) status, tumor grade, primary tumor growth pattern (endophytic/exophytic), tumor/nodal/group stages, chemotherapy regimen, and primary, nodal, and total GTV volumes in the initial CT scan. The C4.5 Decision Tree induction algorithm was implemented. The median %GTVΔ for primary, nodal, and total GTVs was 26.8%, 43.0%, and 31.2%, respectively. Type of chemotherapy, age, primary tumor growth pattern, site, KPS, and HPV status were the most predictive parameter...Continue Reading

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Citations

May 6, 2016·Medical Physics·Minsun Kim, Mark H Phillips
Aug 10, 2016·Technology in Cancer Research & Treatment·Murat SurucuBahman Emami
Oct 6, 2018·Acta Oncologica·J CastelliR de Crevoisier
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Dec 12, 2018·BMC Cancer·Yu-Chang HuWen-Shan Liu
Feb 2, 2021·Journal of Applied Clinical Medical Physics·Jung-In KimHong-Gyun Wu
Jul 16, 2021·Biomedical Physics & Engineering Express·Vasiliki IliadouGeorge K Matsopoulos

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Methods Mentioned

BETA
biopsy

Software Mentioned

Eclipse
Weka
XIO

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