Topological Organization of Metabolic Brain Networks in Pre-Chemotherapy Cancer with Depression: A Resting-State PET Study

Detecting microstructural alterations of cerebral white matter associated with breast cancer and chemotherapy revealed by generalized q-sampling MRI

Objective

Previous studies have discussed the impact of chemotherapy on the brain microstructure. There is no evidence of the impact regarding cancer-related psychiatric comorbidity on cancer survivors. We aimed to evaluate the impact of both chemotherapy and mental health problem on brain microstructural alterations and consequent cognitive dysfunction in breast cancer survivors.

Methods

In this cross-sectional study conducted in a tertiary center, data from 125 female breast cancer survivors who had not received chemotherapy (BB = 65; 49.86 ± 8.23 years) and had received chemotherapy (BA = 60; 49.82 ± 7.89 years) as well as from 71 age-matched healthy controls (47.18 ± 8.08 years) was collected. Chemotherapeutic agents used were docetaxel and epirubicin. We used neuropsychological testing and questionnaire to evaluate psychiatric comorbidity, cognitive dysfunction as well as generalized sampling imaging (GQI) and graph theoretical analysis (GTA) to detect microstructural alterations in the brain.

Findings

Cross-comparison between groups revealed that neurotoxicity caused by chemotherapy and cancer-related psychiatric comorbidity may affect the corpus callosum and middle frontal gyrus. In addition, GQI indices were correlated with the testing scores of cognitive function, quality of life, anxiety, and depression. Furthermore, weaker connections between brain regions and lower segregated ability were found in the post-treatment group.

Conclusion

This study suggests that chemotherapy and cancer-related mental health problem both play an important role in the development of white matter alterations and cognitive dysfunction.

Brain glucose metabolism on [18F]-FDG PET/CT: a dynamic biomarker predicting depression and anxiety in cancer patients

Objectives

To explore the correlation between the incidence rates of depression and anxiety and cerebral glucose metabolism in cancer patients.

Methods

The experiment subjects consisted of patients with lung cancer, head and neck tumor, stomach cancer, intestinal cancer, breast cancer and healthy individuals. A total of 240 tumor patients and 39 healthy individuals were included. All subjects were evaluated by the Hamilton depression scale (HAMD) and Manifest anxiety scale (MAS), and were examined by whole body Positron Emission Tomography/Computed Tomography (PET/CT) with 18F-fluorodeoxyglucose (FDG). Demographic, baseline clinical characteristics, brain glucose metabolic changes, emotional disorder scores and their relations were statistically analyzed.

Results

The incidence rates of depression and anxiety in patients with lung cancer were higher than those in patients with other tumors, and Standard uptake values (SUVs) and metabolic volume in bilateral frontal lobe, bilateral temporal lobe, bilateral caudate nucleus, bilateral hippocampus, left cingulate gyrus were lower than those in patients with other tumors. We also found that poor pathological differentiation, and advanced TNM stage independently associated with depression and anxiety risk. SUVs in the bilateral frontal lobe, bilateral temporal lobe, bilateral caudate nucleus, bilateral hippocampus, left cingulate gyrus were negatively correlated with HAMD and MAS scores.

Conclusion

This study revealed the correlation between brain glucose metabolism and emotional disorders in cancer patients. The changes in brain glucose metabolism were expected to play a major role in emotional disorders in cancer patients as psychobiological markers. These findings indicated that functional imaging can be applied for psychological assessment of cancer patients as an innovative method.

Construction of an individualized brain metabolic network in patients with advanced non-small cell lung cancer by the Kullback-Leibler divergence-based similarity method: A study based on 18F-fluorodeoxyglucose positron emission tomography

Background

Lung cancer has one of the highest mortality rates of all cancers, and non-small cell lung cancer (NSCLC) accounts for the vast majority (about 85%) of lung cancers. Psychological and cognitive abnormalities are common in cancer patients, and cancer information can affect brain function and structure through various pathways. To observe abnormal brain function in NSCLC patients, the main purpose of this study was to construct an individualized metabolic brain network of patients with advanced NSCLC using the Kullback-Leibler divergence-based similarity (KLS) method.

Methods

This study included 78 patients with pathologically proven advanced NSCLC and 60 healthy individuals, brain 18F-FDG PET images of these individuals were collected and all patients with advanced NSCLC were followed up (>1 year) to confirm their overall survival. FDG-PET images were subjected to individual KLS metabolic network construction and Graph theoretical analysis. According to the analysis results, a predictive model was constructed by machine learning to predict the overall survival of NSLCL patients, and the correlation with the real survival was calculated.

Results

Significant differences in the degree and betweenness distributions of brain network nodes between the NSCLC and control groups (p<0.05) were found. Compared to the normal group, patients with advanced NSCLC showed abnormal brain network connections and nodes in the temporal lobe, frontal lobe, and limbic system. The prediction model constructed using the abnormal brain network as a feature predicted the overall survival time and the actual survival time fitting with statistical significance (r=0.42, p=0.012).

Conclusions

An individualized brain metabolic network of patients with NSCLC was constructed using the KLS method, thereby providing more clinical information to guide further clinical treatment.

Cerebral Blood Flow and its Connectivity Deficits in Patients With Lung Cancer After Chemotherapy

Purpose: This study was performed to investigate the regional cerebral blood flow (CBF) and CBF connectivity in the chemotherapy-induced cognitive impairment of patients with lung cancer by using arterial spin labeling.

Methods: Pseudocontinuous arterial spin labeling perfusion magnetic resonance imaging and neuropsychological tests were performed for 21 patients with non-small cell lung cancer who had received chemotherapy CT (+) and 25 non-small cell lung cancer patients who need chemotherapy but did not yet received CT (-). The CT (+) group previously received platinum-based therapy for 3 months to 6 months (the time from their first chemotherapy to the MRI scan). Group comparisons were performed in the regional normalized CBF and CBF connectivity, and the relationship between the regional normalized CBF and cognitive impairment were detected.

Results: The CT (+) group exhibited higher CBF in the left insula, right caudate, right superior occipital gyrus, left superior temporal gyrus (STG), and right middle frontal gyrus (MFG). MoCA scores as well as the memory scores were negatively correlated with the increased CBF in the right MFG (r = −0.492, p = 0.023; r = −0.497, p = 0.022). Alterations in the CBF connectivity were detected only in the CT (+) group between the following: right MFG and the right precentral gyrus; the right caudate and the right lingual gyrus; right caudate and right precuneus; left STG and the bilateral MFG; and the left STG and the right middle cingulum.

Conclusion: These findings indicated that chemotherapy is associated with abnormalities in the CBF and connectivity alterations, which may contribute to the cognitive impairment in patients with lung cancer.

Resting-state brain metabolic fingerprinting clusters (biomarkers) and predictive models for major depression in multiple myeloma patients

Background

Major depression is a common comorbidity in cancer patients. Oncology clinics lack practical, objective tools for simultaneous evaluation of cancer and major depression. Fludeoxyglucose F-18 positron emission tomography–computed tomography (FDG PET/CT) is universally applied in modern medicine.

Methods

We used a retrospective analysis of whole-body FDG PET/CT images to identify brain regional metabolic patterns of major depression in multiple myeloma patients. The study included 134 multiple myeloma (MM) patients, 38 with major depression (group 1) and 96 without major depression (group 2).

Results

In the current study, Statistic Parameter Mapping (SPM) demonstrated that the major depression patient group (n = 38) had significant regional metabolic differences (clusters of continuous voxels) as compared to the non-major depression group (n = 96) with the criteria of height threshold T = 4.38 and extent threshold > 100 voxels. The five significant hypo- and three hyper-metabolic clusters from the computed T contrast maps were localized on the glass-brain view, consistent with published brain metabolic changes in major depression patients. Subsequently, using these clusters as features for classification learner, the fine tree and medium tree algorithms from 25 classification algorithms best fitted our data (accuracy 0.85%; AUC 0.88; sensitivity 79%; and specificity 88%).

Conclusion

This study demonstrated that whole-body FDG PET/CT scans could provide added value for screening for major depression in cancer patients in addition to staging and evaluating response to chemoradiation therapies.

Connectome analysis of brain functional network alterations in breast cancer survivors with and without chemotherapy

Purpose

Treatment modalities for breast cancer, the leading cause of cancer-related deaths in women worldwide, include surgery, radiotherapy, adjuvant chemotherapy, targeted therapy, and hormonal therapy. The advancement in medical technology has facilitated substantial reduction in breast cancer mortality. However, patients may experience cognitive impairment after chemotherapy. This phenomenon called chemotherapy-induced cognitive impairment (i.e., “chemobrain”) is common among breast cancer survivors. However, cognitive function deficits may exist before chemotherapy initiation. This study examined the functional network alterations in breast survivors by using resting-state functional magnetic resonance imaging (fMRI).

Methods

We recruited 172 female participants and separated them into three groups: C+ (57 breast cancer survivors who had finished 3–12-month-long chemotherapy), C- (45 breast cancer survivors who had not undergone chemotherapy), and HC (70 participants with no breast cancer history). We analyzed mean fractional amplitudes of low-frequency fluctuation and graph theoretical topologies from resting-state fMRI and applied network-based analysis to portray functional changes among the three groups.

Results

Among the three groups, the C- group demonstrated hyperactivity in the prefrontal cortex, bilateral middle temporal gyrus, right inferior temporal gyrus and right angular gyrus. Only the left caudate demonstrated significantly more hypoactivity in the C- group than in the C+ group. Graph theoretical analysis demonstrated that the brains of the C+ group became inclined toward regular networks and the brains of the C- group became inclined toward random networks.

Conclusion

Subtle alterations were noted in the brain activity and networks of our cancer survivors. Moreover, functional network disruptions occurred regardless of chemotherapeutic agent administration.

Emotional distress, brain functioning, and biobehavioral processes in cancer patients: a neuroimaging review and future directions

Despite emerging evidence that distress and adversity can contribute to negative health outcomes in cancer, little is known about the brain networks, regions, or circuits that can contribute to individual differences in affect/distress states and health outcomes in treated cancer patients. To understand the state-of-the-science in this regard, we reviewed neuroimaging studies with cancer patients that examined the associations between negative affect (distress) and changes in the metabolism or structure of brain regions. Cancer patients showed changes in function and/or structure of key brain regions such as the prefrontal cortex, thalamus, amygdala, hippocampus, cingulate cortex (mainly subgenual area), hypothalamus, basal ganglia (striatum and caudate), and insula, which are associated with greater anxiety, depression, posttraumatic stress disorder (PTSD) symptoms, and distress. These results provide insights for understanding the effects of these psychological and emotional factors on peripheral stress-related biobehavioral pathways known to contribute to cancer progression and long-term health outcomes. This line of work provides leads for understanding the brain-mediated mechanisms that may explain the health effects of psychosocial interventions in cancer patients and survivors. A multilevel and integrated model for distress management intervention effects on psychological adaptation, biobehavioral processes, cancer pathogenesis, and clinical outcomes is proposed for future research.

A population stereotaxic positron emission tomography brain template for the macaque and its application to ischemic model

PURPOSE

Positron emission tomography (PET) is a non-invasive imaging tool for the evaluation of brain function and neuronal activity in normal and diseased conditions with high sensitivity. The macaque monkey serves as a valuable model system in the field of translational medicine, for its phylogenetic proximity to man. To translation of non-human primate neuro-PET studies, an effective and objective data analysis platform for neuro-PET studies is needed.

MATERIALS AND METHODS

A set of stereotaxic templates of macaque brain, namely the Institute of High Energy Physics & Jinan University Macaque Template (HJT), was constructed by iteratively registration and averaging, based on 30 healthy rhesus monkeys. A brain atlas image was created in HJT space by combining sub-anatomical regions and defining new 88 bilateral functional regions, in which a unique integer was assigned for each sub-anatomical region.

RESULTS

The HJT comprised a structural MRI T1 weighted image (T1WI) template image, a functional FDG-PET template image, intracranial tissue segmentations accompanied with a digital macaque brain atlas image. It is compatible with various commercially available software tools, such as SPM and PMOD. Data analysis was performed on a stroke model compared with a group of healthy controls to demonstrate the usage of HJT.

CONCLUSION

We have constructed a stereotaxic template set of macaque brain named HJT, which standardizes macaque neuroimaging data analysis, supports novel radiotracer development and facilitates translational neuro-disorders research.

The negative correlation between energy consumption and communication efficiency in motor network

OBJECTIVE

Motor network plays an important role in people's daily lives. However, until now, the energy consumption mechanism of motor network remains unclear. In this study, we aimed to investigate the energy consumption of motor network.

MATERIALS AND METHODS

Fluorine-18-fluorodeoxyglucose PET ([F]FDG PET) data of 81 healthy male Sprague-Dawley rats were included in this study. Metabolic motor network was constructed on the basis of group independent component analysis. Properties of motor network such as degree and nodal efficiency were investigated using graph theory-based analysis. Furthermore, the relationships between [F]FDG standardized uptake value ratio and these properties of each node were investigated.

RESULTS

A motor network comprising of the following 11 regions were found: left primary motor cortex, right primary motor cortex, left secondary motor cortex, right secondary motor cortex, left primary somatosensory cortex, right primary somatosensory cortex, left secondary somatosensory cortex, right secondary somatosensory cortex, left insular cortex, right insular cortex, and left orbital cortex. Graph theory-based analysis indicated that right primary somatosensory cortex and left secondary somatosensory cortex were the hubs of motor network, and the nodal efficiency and nodal degree share the same order. Further investigation found a significantly negative correlation between nodal efficiency and [F]FDG standardized uptake value ratios.

CONCLUSION

This study investigated the energy consumption of motor network and found a relationship between energy consumption and communication efficiency. These results may provide insights into the understanding of energy consumption mechanism underlying motor network.Video abstract: http://links.lww.com/NMC/A142.

Meningioma and psychiatric symptoms: An individual patient data analysis

Meningioma is a slow-growing benign tumor arising from meninges and is usually asymptomatic. Though neuropsychiatric symptoms are common in patients with brain tumors, they often can be the only manifestation in cases of meningioma. Meningiomas might present with mood symptoms, psychosis, memory disturbances, personality changes, anxiety, or anorexia nervosa. The diagnosis of meningioma could be delayed where only psychiatric symptoms are seen. A comprehensive review of the literature and individual patient data analysis was conducted, which included all case reports, and case series on meningioma and psychiatric symptoms till September 2018 with the search terms "meningioma" and "psychiatric symptoms/ depression/ bipolar disorder/mania/ psychosis/ obsessive-compulsive disorder". Search engines used included PubMed, MEDLINE, PsycINFO, Cochrane database and Google Scholar. Studies reported varied psychiatric symptoms in cases with meningioma of differing tumor site, size and lateralization. Factors which led to a neuroimaging work-up included the occurrence of sudden new or atypical psychiatric symptoms, a lack of response to typical line of treatment and the presence of neurological signs or symptoms such as headache, seizures, diplopia, urinary incontinence etc. This review emphasizes on the need of neurological examination and neuroimaging in the patients presenting to psychiatry especially with atypical symptoms.

Gender-disease interaction on brain cerebral metabolism in cancer patients with depressive symptoms

BACKGROUND

Cancer patients are accompanied with high morbidity of depression, and gender effects are known to inhabit in the depressive episodes. This study aimed to explore the gender effects in cancer patients, and the relationship between gender-cancer factors and the depression symptoms.

METHODS

The 18F-FDG PET scans of 49 cancer patients and 48 normal controls were included. We used voxel-wise analysis to explore the effects of cancer factor and gender factor in cerebral glucose metabolism. Beck Depression Inventory was utilized to quantify the depression symptoms in cancer patients.

RESULTS

Our results showed significant cancer main effects primarily in superior frontal gyrus and parietal gyrus; and significant gender main effects primarily in cerebellum posterior lobe, inferior temporal gyrus. Significant gender-by-cancer interaction effects were also observed, which primarily located in superior frontal gyrus. We showed the metabolic intensities of the 5 aforementioned clusters were related to the mental stress of depressive emotion.

CONCLUSIONS

Our results suggested that males and females have different psychological endurance when facing cancer diagnosis or preventing depression. Furthermore, the cerebral abnormal metabolism might serve as a depressive indicator for cancer patients. The present findings provided supporting evidence for abnormal cerebral glucose metabolism affected by gender factor in cancer patients with mental stress of depressive emotion, and these brain regions should be concerned in clinic.

Neonatal brain resting-state functional connectivity imaging modalities

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Depression comorbidity in epileptic rats is related to brain glucose hypometabolism and hypersynchronicity in the metabolic network architecture

OBJECTIVE

Temporal lobe epilepsy (TLE) is one of the most common types of epilepsy syndromes in the world. Depression is an important comorbidity of epilepsy, which has been reported in patients with TLE and in different experimental models of epilepsy. However, there is no established consensus on which brain regions are associated with the manifestation of depression in epilepsy. Here, we investigated the alterations in cerebral glucose metabolism and the metabolic network in the pilocarpine-induced rat model of epilepsy and correlated it with depressive behavior during the chronic phase of epilepsy.

METHODS

Fluorodeoxyglucose (¹⁸ F-FDG) was used to investigate the cerebral metabolism, and a cross-correlation matrix was used to examine the metabolic network in chronically epileptic rats using micro-positron emission tomography (microPET) imaging. An experimental model of epilepsy was induced by pilocarpine injection (320 mg/kg, ip). Forced swim test (FST), sucrose preference test (SPT), and eating-related depression test (ERDT) were used to evaluate depression-like behavior.

RESULTS

Our results show an association between epilepsy and depression comorbidity based on changes in both cerebral glucose metabolism and the functional metabolic network. In addition, we have identified a significant correlation between brain glucose hypometabolism and depressive-like behavior in chronically epileptic rats. Furthermore, we found that the epileptic depressed group presents a hypersynchronous brain metabolic network in relation to the epileptic nondepressed group.

SIGNIFICANCE

This study revealed relevant alterations in glucose metabolism and the metabolic network among the brain regions of interest for both epilepsy and depression pathologies. Thus it seems that depression in epileptic animals is associated with a more diffuse hypometabolism and altered metabolic network architecture and plays an important role in chronic epilepsy.