A Patient Selection Approach Based on NTCP Models and DVH Parameters for Definitive Proton Therapy in Locally Advanced Sinonasal Cancer Patients.
Cancers (Basel)
; 14(11)2022 May 28.
Article
em En
| MEDLINE
| ID: mdl-35681661
ABSTRACT
(1) Background:
In this work, we aim to provide selection criteria based on normal tissue complication probability (NTCP) models and additional explanatory dose-volume histogram parameters suitable for identifying locally advanced sinonasal cancer patients with orbital invasion benefitting from proton therapy. (2)Methods:
Twenty-two patients were enrolled, and two advanced radiation techniques were compared intensity modulated proton therapy (IMPT) and photon volumetric modulated arc therapy (VMAT). Plans were optimized with a simultaneous integrated boost modality 70 and 56 Gy(RBE) in 35 fractions were prescribed to the high risk/low risk CTV. Several endpoints were investigated, classified for their severity and used as discriminating paradigms. In particular, when NTCP models were already available, a first selection criterion based on the delta-NTCP was adopted. Additionally, an overall analysis in terms of DVH parameters was performed. Furthermore, a second selection criterion based on a weighted sum of the ΔNTCP and ΔDVH was adopted. (3)Results:
Four patients out of 22 (18.2%) were suitable for IMPT due to ΔNTCP > 3% for at least one severe toxicity, 4 (18.2%) due to ΔNTCP > 20% for at least three concurrent intermediate toxicities and 16 (72.7%) due to the mixed sum of ΔNTCP and ΔDVH criterion. Since, for some cases, both criteria were contemporary fulfilled, globally 17/22 patients (77.3%) would benefit from IMPT. (4)Conclusions:
For this rare clinical scenario, the use of a strategy including DVH parameters and NTCPs when comparing VMAT and IMPT is feasible. We showed that patients affected by sinonasal cancer could profit from IMPT compared to VMAT in terms of optical and central nervous system organs at risk sparing.
Texto completo:
1
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article