Combination of FDG PET/CT Radiomics and Clinical Parameters for Outcome Prediction in Patients with Hodgkin’s Lymphoma

Author:

Ortega Claudia1,Eshet Yael2,Prica Anca3,Anconina Reut4,Johnson Sarah1,Constantini Danny5,Keshavarzi Sareh6,Kulanthaivelu Roshini1ORCID,Metser Ur1ORCID,Veit-Haibach Patrick1

Affiliation:

1. Joint Department of Medical Imaging, University Health Network-Mount Sinai Hospital, Women’s College Hospital, University Medical Imaging Toronto, University of Toronto, Toronto, ON M5T 1W7, Canada

2. Department of Diagnostic Imaging, Chaim Sheba Medical Center, Ramat Gan 5210000, Israel

3. Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C4, Canada

4. Department of Medical Imaging, Belilinson Hospital, Rabin Medical Center, Tel Aviv University, Petah Tikva 4941492, Israel

5. Department of Diagnostic Imaging, William Osler Health System, 2100 Bovaird Avenue East, Brampton, ON L6R 3J7, Canada

6. Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada

Abstract

Purpose: The aim of the study is to evaluate the prognostic value of a joint evaluation of PET and CT radiomics combined with standard clinical parameters in patients with HL. Methods: Overall, 88 patients (42 female and 46 male) with a median age of 43.3 (range 21–85 years) were included. Textural analysis of the PET/CT images was performed using freely available software (LIFE X). 65 radiomic features (RF) were evaluated. Univariate and multivariate models were used to determine the value of clinical characteristics and FDG PET/CT radiomics in outcome prediction. In addition, a binary logistic regression model was used to determine potential predictors for radiotherapy treatment and odds ratios (OR), with 95% confidence intervals (CI) reported. Features relevant to survival outcomes were assessed using Cox proportional hazards to calculate hazard ratios with 95% CI. Results: albumin (p = 0.034) + ALP (p = 0.028) + CT radiomic feature GLRLM GLNU mean (p = 0.012) (Area under the curve (AUC): 95% CI (86.9; 100.0)—Brier score: 3.9, 95% CI (0.1; 7.8) remained significant independent predictors for PFS outcome. PET-SHAPE Sphericity (p = 0.033); CT grey-level zone length matrix with high gray-level zone emphasis (GLZLM SZHGE mean (p = 0.028)); PARAMS XSpatial Resampling (p = 0.0091) as well as hemoglobin results (p = 0.016) remained as independent factors in the final model for a binary outcome as predictors of the need for radiotherapy (AUC = 0.79). Conclusion: We evaluated the value of baseline clinical parameters as well as combined PET and CT radiomics in HL patients for survival and the prediction of the need for radiotherapy treatment. We found that different combinations of all three factors/features were independently predictive of the here evaluated endpoints.

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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