Your browser doesn't support javascript.
loading
Development and validation of an [18F]FDG-PET/CT radiomic model for predicting progression-free survival for patients with stage II - III thoracic esophageal squamous cell carcinoma who are treated with definitive chemoradiotherapy.
Takahashi, Noriyoshi; Tanaka, Shohei; Umezawa, Rei; Takanami, Kentaro; Takeda, Kazuya; Yamamoto, Takaya; Suzuki, Yu; Katsuta, Yoshiyuki; Kadoya, Noriyuki; Jingu, Keiichi.
  • Takahashi N; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Tanaka S; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Umezawa R; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Takanami K; Department of Radiology, Tohoku University Graduate School of Medicine.
  • Takeda K; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Yamamoto T; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Suzuki Y; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Katsuta Y; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Kadoya N; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
  • Jingu K; Department of Radiation Oncology, Tohoku University Graduate School of Medicine.
Acta Oncol ; 62(2): 159-165, 2023 Feb.
Article en En | MEDLINE | ID: mdl-36794365
ABSTRACT

BACKGROUND:

Radiomics is a method for extracting a large amount of information from images and used to predict treatment outcomes, side effects and diagnosis. In this study, we developed and validated a radiomic model of [18F]FDG-PET/CT for predicting progression-free survival (PFS) of definitive chemoradiotherapy (dCRT) for patients with esophageal cancer. MATERIAL AND

METHODS:

Patients with stage II - III esophageal cancer who underwent [18F]FDG-PET/CT within 45 days before dCRT between 2005 and 2017 were included. Patients were randomly assigned to a training set (85 patients) and a validation set (45 patients). Radiomic parameters inside the area of standard uptake value ≥ 3 were calculated. The open-source software 3D slicer and Pyradiomics were used for segmentation and calculating radiomic parameters, respectively. Eight hundred sixty radiomic parameters and general information were investigated.In the training set, a radiomic model for PFS was made from the LASSO Cox regression model and Rad-score was calculated. In the validation set, the model was applied to Kaplan-Meier curves. The median value of Rad-score in the training set was used as a cutoff value in the validation set. JMP was used for statistical analysis. RStudio was used for the LASSO Cox regression model. p < 0.05 was defined as significant.

RESULTS:

The median follow-up periods were 21.9 months for all patients and 63.4 months for survivors. The 5-year PFS rate was 24.0%. In the training set, the LASSO Cox regression model selects 6 parameters and made a model. The low Rad-score group had significantly better PFS than that the high Rad-score group (p = 0.019). In the validation set, the low Rad-score group had significantly better PFS than that the high Rad-score group (p = 0.040).

CONCLUSIONS:

The [18F]FDG-PET/CT radiomic model could predict PFS for patients with esophageal cancer who received dCRT.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Esofágicas / Carcinoma de Células Escamosas de Esófago Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Esofágicas / Carcinoma de Células Escamosas de Esófago Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article