Pierre Lovinfosse1, Marc Polus2, Daniel Van Daele2, Philippe Martinive3, Frédéric Daenen4, Mathieu Hatt5, Dimitris Visvikis5, Benjamin Koopmansch6, Frédéric Lambert6, Carla Coimbra7, Laurence Seidel8, Adelin Albert8, Philippe Delvenne9, Roland Hustinx10. 1. Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics CHU, University of Liège, B35 Domaine Universitaire du Sart-Tilman, 4000, Liege, Belgium. pierre.lovinfosse@chu.ulg.ac.be. 2. Department of Gastro-enterology, Centre Hospitalier Universitaire de Liège, Liège, Belgium. 3. Division of Radiation Oncology, Department of Medical Physics, CHU and University of Liège, Liège, Belgium. 4. Department of Nuclear Medicine, Centre Hospitalier Régional de la Citadelle, Liège, Belgium. 5. LaTIM, INSERM UMR 1101, Brest, France. 6. Center for Human Genetic, Molecular Haemato-Oncology Unit, UniLab Liège, Centre Hospitalier Universitaire de Liège, Liège, Belgium. 7. Department of Abdominal Surgery and Transplantation, Centre Hospitalier Universitaire de Liège, Liège, Belgium. 8. Department of Biostatistics and Medico-economic Information, Centre Hospitalier Universitaire de Liège, Liège, Belgium. 9. Department of Pathology, Centre Hospitalier Universitaire de Liège, Liège, Belgium. 10. Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics CHU, University of Liège, B35 Domaine Universitaire du Sart-Tilman, 4000, Liege, Belgium.
Abstract
PURPOSE: The aim of this study was to investigate the prognostic value of baseline 18F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). METHODS: Eighty-six patients with LARC underwent 18F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT). RESULTS: The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrastNGTDM) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4). CONCLUSION: Textural analysis of baseline 18F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume-based parameters. The utility of such features, especially coarseness, should be confirmed by larger clinical studies before considering their potential integration into decisional algorithms aimed at personalized medicine.
PURPOSE: The aim of this study was to investigate the prognostic value of baseline 18F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). METHODS: Eighty-six patients with LARC underwent 18F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT). RESULTS: The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrastNGTDM) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4). CONCLUSION: Textural analysis of baseline 18F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume-based parameters. The utility of such features, especially coarseness, should be confirmed by larger clinical studies before considering their potential integration into decisional algorithms aimed at personalized medicine.
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