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Updated: Aug 23, 2026
Evaluating the Role of Mitochondrial Function in Cancer-related Fatigue
Published on: May 17, 2018
Neurobiological Correlates of Cancer-Related Fatigue in Chemotherapy-Naïve Breast Cancer: A Retrospective
Ahmed Msherghi1, Franklin Wong2, Guofan Xu2
1From the Department of Neuroradiology (A.M., H.A.S.), Nuclear Medicine (F.W., G. X.), Imaging Physics (O.M.), Division of Diagnostic Imaging, Palliative (S.P.), Rehabilitation, and Integrative Medicine, Infectious Diseases (M.M.K.), Infection Control and Employee Health, Belfer Neurodegeneration Consortium (W.J.R.), Neuro-Oncology (V.K.P.), The University of Texas MD Anderson Cancer Center, Houston, Texas, USA; Markey Cancer Center at Lexington Clinic (M.A.), Oncology Department, University of Kentucky, Lexington, Kentucky; Department of Research (M.W., D.P.), UTHealth Houston Cizik School of Nursing, Houston, Texas, USA and Department of Radiology (M.W.), The University of Texas Medical Branch, Galveston, TX, USA. max.wintermark@gmail.com.
Background:
Cancer-related fatigue (CRF) is a prevalent and debilitating symptom in cancer patients, and its underlying pathophysiology remains poorly understood, particularly in patients who have not undergone chemotherapy. This study aimed to investigate the cerebral metabolic changes associated with CRF in chemotherapy-naïve breast cancer patients using high-resolution [18F]fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT).
Methods:
We retrospectively identified 20 consecutive adult patients with breast cancer who were diagnosed with CRF (ICD-10-CM R53.0) and had never received chemotherapy between January 2023 and August 2025. Patients underwent whole-body [18F]FDG-PET/CT imaging on a Biograph Vision Quadra scanner at baseline (up to 1 year before CRF diagnosis while having breast cancer) and at the time of CRF diagnosis, up to three months after the date of diagnosis. Brain image slices were extracted and preprocessed. Patients with brain metastases or other known causes of fatigue were excluded. The analysis used an Atlas-based region-of-interest analysis of bilateral regions, as well as separate right and left hemispheres, to compare the two scans and identify significant metabolic changes.
Results:
A significant increase in relative glucose metabolism was observed in the bilateral thalamus (T = -2.23, P = 0.05) and left thalamus (T = -2.59, P = 0.03). A significant decrease in relative metabolism was observed in the right anterior cingulate gyrus (T = 2.28, P = 0.05) following CRF diagnosis. A trend towards decreased metabolism in the retrosplenial cortex was also noted (1.40, P = 0.19; and 1.78, P = 0.11 for bilateral and right hemisphere, respectively). Additionally, the right Globus Pallidus (-1.53, P = 0.16) and right Amygdala (-1.62, P = 0.14) showed a trend toward increased metabolism following the diagnosis of CRF.
Conclusion:
This is the first study to investigate brain metabolic correlates of CRF in a chemotherapy-naïve breast cancer population using a high-sensitivity Brain [18F]FDG PET/CT. The observed hypermetabolism in the thalamus and other regions of the basal ganglia and limbic system suggests potential central neurobiological correlates of CRF, independent of chemotherapy effects. These findings provide a foundation for future research into imaging biomarkers for CRF and their application to the development of targeted therapeutic interventions.
