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Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?
Jayaprakasam, Vetri Sudar; Gibbs, Peter; Gangai, Natalie; Bajwa, Raazi; Sosa, Ramon E; Yeh, Randy; Greally, Megan; Ku, Geoffrey Y; Gollub, Marc J; Paroder, Viktoriya.
Afiliação
  • Jayaprakasam VS; Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Gibbs P; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Gangai N; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Bajwa R; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Sosa RE; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Yeh R; Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Greally M; Mater Private Hospital, D07 WKW8 Dublin, Ireland.
  • Ku GY; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Gollub MJ; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
  • Paroder V; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Cancers (Basel) ; 14(12)2022 Jun 20.
Article em En | MEDLINE | ID: mdl-35740700
ABSTRACT
This study aimed to assess the usefulness of radiomics features of 18F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article