Magnetic resonance spectroscopic imaging and volumetric measurements of the brain in patients with postcancer fatigue: a randomized controlled trial

Neural Mechanisms Underlying Breast Cancer Related Fatigue: A Systematic Review of Neuroimaging Studies

Introduction: Fatigue and cognitive dysfunction commonly co-occur in breast cancer patients and survivors. However, the underlying neural mechanism is not clear. We performed a systematic review of studies that used neuroimaging methods to investigate structural and functional changes in the brain associated with fatigue in breast cancer patients and survivors.

Methods: We searched PubMed, Scopus, EmBase, and Cochrane CENTRAL from January 2009 to May 2021 for studies that reported brain neuroimaging findings in relationship to fatigue in breast cancer patients or survivors. Neuroimaging methods included magnetic resonance imaging (MRI), positron emission tomography (PET), and electroencephalogram (EEG). We summarized structural and functional neuroimaging changes associated with fatigue.

Results: Of the 176 articles retrieved, ten MRI studies reported neuroimaging findings in relationship to fatigue. Together these studies compared 385 breast cancer patients or survivors to 205 controls. Fatigue was associated with reduced white matter integrity and increased glutamate in the insula but changes in gray matter volume were not associated with fatigue score. Nine of the ten studies found significant associations between fatigue and functional changes in the frontoparietal cortex. In response to memory and planning tasks, fatigue was associated with increased activations in several regions of the frontoparietal cortex, however, overall performance on tasks was not reduced. Fatigue was also associated with extensive changes in the connectivity of brain networks that filter endogenous signals (salience network), internal attention (default mode network), and external attention (dorsal attention network). Subcortical regions associated with fatigue included insula (interoception), superior colliculus (sleep regulation), and thalamus (alertness). Functional brain changes before initiation of chemotherapy were a better predictor of post-treatment fatigue than chemotherapy itself.

Conclusions: Fatigue in breast cancer is associated with widespread functional changes of brain regions and networks that affect executive function including memory, planning, internal and external attention. Observed changes likely represent a compensatory mechanism through which breast cancer patients and survivors try to maintain adequate executive function. Breast cancer patients scheduled to undergo chemotherapy are at high risk for developing fatigue even before the start of treatment.

Interferon Gamma-Induced Protein (IP-10) as Potential Biomarker for Cancer-Related-Fatigue: Results from a 6-month Randomized Controlled Trial

We examined if serum concentrations Interferon gamma-induced protein (IP-10) is a potential clinical biomarker for cancer-related-fatigue (CRF). Fatigue scores and IP-10 concentrations were measured from curatively treated fatigued cancer patients randomized to either cognitive behavioral therapy (CBT, n = 26) or waiting-list (WL, n = 13). No correlation was found between baseline IP-10 level and fatigue severity and no significant differences in IP-10 serum levels were observed between fatigued and matched non-fatigued patients (n = 22). Relative changes in IP-10 concentrations from baseline to six-month follow-up were not significantly different between the CBT and WL conditions. In this study, IP-10 showed low potential as clinical CRF biomarker.

TRIAL REGISTRATION

This study is registered at ClinicalTrials.gov (NCT01096641).

Neural Indicators of Fatigue in Chronic Diseases: A Systematic Review of MRI Studies

While fatigue is prevalent in chronic diseases, the neural mechanisms underlying this symptom remain unknown. Magnetic resonance imaging (MRI) has the potential to enable us to characterize this symptom. The aim of this review was to gather and appraise the current literature on MRI studies of fatigue in chronic diseases. We systematically searched the following databases: MedLine, PsycInfo, Embase and Scopus (inception to April 2016). We selected studies according to a predefined inclusion and exclusion criteria. We assessed the quality of the studies and conducted descriptive statistical analyses. We identified 26 studies of varying design and quality. Structural and functional MRI, alongside diffusion tensor imaging (DTI) and functional connectivity (FC) studies, identified significant brain indicators of fatigue. The most common regions were the frontal lobe, parietal lobe, limbic system and basal ganglia. Longitudinal studies offered more precise and reliable analysis. Brain structures found to be related to fatigue were highly heterogeneous, not only between diseases, but also for different studies of the same disease. Given the different designs, methodologies and variable results, we conclude that there are currently no well-defined brain indicators of fatigue in chronic diseases.

Prefrontal Structure Varies as a Function of Pain Symptoms in Chronic Fatigue Syndrome

BACKGROUND

Chronic fatigue syndrome (CFS) is characterized by severe fatigue persisting for ≥6 months and leading to considerable impairment in daily functioning. Neuroimaging studies of patients with CFS have revealed alterations in prefrontal brain morphology. However, it remains to be determined whether these alterations are specific for fatigue or whether they relate to other common CFS symptoms (e.g., chronic pain, lower psychomotor speed, and reduced physical activity).

METHODS

We used magnetic resonance imaging to quantify gray matter volume (GMV) and the N-acetylaspartate and N-acetylaspartylglutamate/creatine ratio (NAA/Cr) in a group of 89 women with CFS. Building on previous reports, we tested whether GMV and NAA/Cr in the dorsolateral prefrontal cortex are associated with fatigue severity, pain, psychomotor speed, and physical activity, while controlling for depressive symptoms. We also considered GMV and NAA/Cr differences between patients with CFS and 26 sex-, age-, and education-matched healthy controls.

RESULTS

The presence of pain symptoms was the main predictor of both GMV and NAA/Cr in the left dorsolateral prefrontal cortex of patients with CFS. More pain was associated with reduced GMVs and NAA/Cr, over and above the effects of fatigue, depressive symptoms, physical activity, and psychomotor speed. In contrast to previous reports and despite a large representative sample, global GMV did not differ between the CFS and healthy control groups.

CONCLUSIONS

CFS, as diagnosed by Centers for Disease Control and Prevention criteria, is not a clinical entity reliably associated with reduced GMV. Individual variation in the presence of pain, rather than fatigue, is associated with neuronal alterations in the dorsolateral prefrontal cortex of patients with CFS.

Feasibility and reproducibility of neurochemical profile quantification in the human hippocampus at 3 T

Hippocampal dysfunction is known to be associated with several neurological and neuropsychiatric disorders such as Alzheimer's disease, epilepsy, schizophrenia and depression; therefore, there has been significant clinical interest in studying hippocampal neurochemistry. However, the hippocampus is a challenging region to study using (1) H MRS, hence the use of MRS for clinical research in this region has been limited. Our goal was therefore to investigate the feasibility of obtaining high-quality hippocampal spectra that allow reliable quantification of a neurochemical profile and to establish inter-session reproducibility of hippocampal MRS, including reproducibility of voxel placement, spectral quality and neurochemical concentrations. Ten healthy volunteers were scanned in two consecutive sessions using a standard clinical 3 T MR scanner. Neurochemical profiles were obtained with a short-echo (T(E) = 28 ms) semi-LASER localization sequence from a relatively small (~4 mL) voxel that covered about 62% of the hippocampal volume as calculated from segmentation of T1 -weighted images. Voxel composition was highly reproducible between sessions, with test-retest coefficients of variation (CVs) of 3.5% and 7.5% for gray and white matter volume fraction, respectively. Excellent signal-to-noise ratio (~54 based on the N-acetylaspartate (NAA) methyl peak in non-apodized spectra) and linewidths (~9 Hz for water) were achieved reproducibly in all subjects. The spectral quality allowed quantification of NAA, total choline, total creatine, myo-inositol and glutamate with high scan-rescan reproducibility (CV ≤ 6%) and quantification precision (Cramér-Rao lower bound, CRLB < 9%). Four other metabolites, including glutathione and glucose, were quantified with scan-rescan CV below 20%. Therefore, the highly optimized, short-echo semi-LASER sequence together with FASTMAP shimming substantially improved the reproducibility and number of quantifiable metabolites relative to prior reports. In addition, the between-session variation in metabolite concentrations, as well as CRLB, was lower than the between-subject variation of the concentrations for most metabolites, indicating that the method has the sensitivity to detect inter-individual differences in the healthy brain.