Your browser doesn't support javascript.
loading
Learning curve of lung dose optimization in intensity-modulated radiotherapy for locally advanced non-small cell lung cancer.
Igari, Mitsunobu; Abe, Takanori; Iino, Misaki; Saito, Satoshi; Aoshika, Tomomi; Ryuno, Yasuhiro; Ohta, Tomohiro; Hirai, Ryuta; Kumazaki, Yu; Noda, Shin-Ei; Kato, Shingo.
Afiliação
  • Igari M; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Abe T; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Iino M; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Saito S; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Aoshika T; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Ryuno Y; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Ohta T; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Hirai R; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Kumazaki Y; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Noda SE; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
  • Kato S; Department of Radiation Oncology, International Medical Center, Saitama Medical University, Saitama, Japan.
Thorac Cancer ; 14(26): 2642-2647, 2023 09.
Article em En | MEDLINE | ID: mdl-37466172
ABSTRACT

BACKGROUND:

Intensity-modulated radiotherapy (IMRT) has been increasingly used for patients with locally advanced non-small cell lung cancer (LA-NSCLC). However, there are some barriers to implementing IMRT for LA-NSCLC, including the complexity of treatment plan optimization. This study aimed to evaluate the learning curve of lung dose optimization in IMRT for LA-NSCLC and identify the factors that affect the degree of achievement of lung dose optimization.

METHODS:

We retrospectively evaluated 40 consecutive patients with LA-NSCLC who received concurrent chemoradiotherapy at our institution. These 40 patients were divided into two groups 20 initially treated patients (earlier group) and 20 subsequently treated patients (later group). Patient and tumor characteristics were compared between the two groups. The dose-volume parameter ratio between the actually delivered IMRT plan and the simulated three-dimensional conformal radiotherapy plan was also compared between the two groups to determine the learning curve of lung dose optimization.

RESULTS:

The dose-volume parameter ratio for lung volume to receive more than 5 Gy (lung V5) and mean lung dose (MLD) significantly decreased in later groups. The spread of the beam path and insufficient optimization of dose coverage of planning target volume (PTV) might cause poor control of lung V5, MLD.

CONCLUSIONS:

A learning curve for lung dose optimization was observed with the accumulation of experience. Appropriate techniques, such as restricting the beam path and ensuring dose coverage of PTV during the optimization process, are essential to control lung dose in IMRT for LA-NSCLC.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Radioterapia de Intensidade Modulada / Neoplasias Pulmonares Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Thorac Cancer Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Japão

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Radioterapia de Intensidade Modulada / Neoplasias Pulmonares Tipo de estudo: Observational_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Thorac Cancer Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Japão