Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline <sup>18</sup>F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?
Ricarda Hinzpeter,
Seyed Ali Mirshahvalad,
Roshini Kulanthaivelu,
Andres Kohan,
Claudia Ortega,
Ur Metser,
Amy Liu,
Adam Farag,
Elena Elimova,
Rebecca K. S. Wong,
Jonathan Yeung,
Raymond Woo-Jun Jang,
Patrick Veit-Haibach
Affiliations
Ricarda Hinzpeter
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Seyed Ali Mirshahvalad
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Roshini Kulanthaivelu
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Andres Kohan
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Claudia Ortega
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Ur Metser
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Amy Liu
Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 1X6, Canada
Adam Farag
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
Elena Elimova
Department of Medical Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada
Rebecca K. S. Wong
Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada
Jonathan Yeung
Division of Thoracic Surgery, Department of Surgery, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada
Raymond Woo-Jun Jang
Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2C4, Canada
Patrick Veit-Haibach
University Medical Imaging Toronto, Toronto Joint Department Medical Imaging, University Health Network, Sinai Health System, Women’s College Hospital, University of Toronto, Toronto, ON M5G 2N2, Canada
We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients.
