Role of resting-state functional MRI in detecting brain functional changes following radiotherapy for head and neck cancer: a systematic review and meta-analysis.

PURPOSE: Increasing evidence implicates changes in brain function following radiotherapy for head and neck cancer as precursors for brain dysfunction. These changes may thus be used as biomarkers for early detection. This review aimed to determine the role of resting-state functional magnetic resonance imaging (rs-fMRI) in detecting brain functional changes. METHODS: A systematic search was performed in the PubMed, Scopus, and Web of Science (WoS) databases in June 2022. Patients with head and neck cancer treated with radiotherapy and periodic rs-fMRI assessments were included. A meta-analysis was performed to determine the potential of rs-fMRI for detecting brain changes. RESULTS: Ten studies with a total of 513 subjects (head and neck cancer patients, n = 437; healthy controls, n = 76) were included. A significance of rs-fMRI for detecting brain changes in the temporal and frontal lobes, cingulate cortex, and cuneus was demonstrated in most studies. These changes were reported to be associated with dose (6/10 studies) and latency (4/10 studies). A strong effect size (r = 0.71, p < 0.001) between rs-fMRI and brain changes was also reported, suggesting rs-fMRI's capability for monitoring brain alterations. CONCLUSION: Resting-state functional MRI is a promising tool for detecting brain functional changes following head and neck radiotherapy. These changes are correlated with latency and prescription dose.

Remote assessment of cognition and quality of life following radiotherapy for nasopharyngeal carcinoma: deep-learning-based predictive models and MRI correlates.

PURPOSE: Irradiation of the brain regions from nasopharyngeal carcinoma (NPC) radiotherapy (RT) is frequently unavoidable, which may result in radiation-induced cognitive deficit. Using deep learning (DL), the study aims to develop prediction models in predicting compromised cognition in patients following NPC RT using remote assessments and determine their relation to the quality of life (QoL) and MRI changes. METHODS: Seventy patients (20-76 aged) with MRI imaging (pre- and post-RT (6 months-1 year)) and complete cognitive assessments were recruited. Hippocampus, temporal lobes (TLs), and cerebellum were delineated and dosimetry parameters were extracted. Assessments were given post-RT via telephone (Telephone Interview Cognitive Status (TICS), Telephone Montreal Cognitive Assessment (T-MoCA), Telephone Mini Addenbrooke's Cognitive Examination (Tele-MACE), and QLQ-H&N 43). Regression and deep neural network (DNN) models were used to predict post-RT cognition using anatomical and treatment dose features. RESULTS: Remote cognitive assessments were inter-correlated (r > 0.9). TLs showed significance in pre- and post-RT volume differences and cognitive deficits, that are correlated with RT-associated volume atrophy and dose distribution. Good classification accuracy based on DNN area under receiver operating curve (AUROC) for cognitive prediction (T-MoCA AUROC = 0.878, TICS AUROC = 0.89, Tele-MACE AUROC = 0.919). CONCLUSION: DL-based prediction models assessed using remote assessments can assist in predicting cognitive deficit following NPC RT. Comparable results of remote assessments in assessing cognition suggest its possibility in replacing standard assessments. IMPLICATIONS FOR CANCER SURVIVORS: Application of prediction models in individual patient enables tailored interventions to be provided in managing cognitive changes following NPC RT.

Remote assessment of cognition and quality of life following radiotherapy for glioma: deep-learning-based predictive models and MRI correlates.

BACKGROUND: Glioma irradiation often unavoidably damages the brain volume and affects cognition. This study aims to evaluate the relationship of remote cognitive assessments in determining cognitive impairment of irradiated glioma patients in relation to the quality of life and MRI changes. METHODS: Thirty patients (16-76 aged) with two imaging (pre- and post-RT) and completed cognitive assessments were recruited. Cerebellum, right and left temporal lobes, corpus callosum, amygdala and spinal cord were delineated and their dosimetry parameters were collected. Cognitive assessments were given post-RT via telephone (Telephone Interview Cognitive Status (TICS), Telephone Montreal Cognitive Assessment (T-MoCA), Telephone Mini Addenbrooke's Cognitive Examination (Tele-MACE)). Regression models and deep neural network (DNN) were used to evaluate the relationship between brain volume, cognition and treatment dose in patients. RESULTS: Cognitive assessments were highly inter-correlated (r > 0.9) and impairment was shown between pre- and post-RT findings. Brain volume atrophy was shown post-RT, and cognitive impairments were correlated with radiotherapy-associated volume atrophy and dose-dependent in the left temporal lobe, corpus callosum, cerebellum and amygdala. DNN showed a good area under the curve for cognitive prediction; TICS (0.952), T-MoCA (0.909) and Tele-MACE (0.822). CONCLUSIONS: Cognition can be evaluated remotely in which radiotherapy-related brain injury is dose-dependent and volume-dependent. Prediction models can assist in the early identification of patients at risk for neurocognitive decline following RT for glioma, thus facilitating potential treatment interventions.

Diffusion tensor imaging indices as biomarkers for cognitive changes following paediatric radiotherapy: a systematic review and meta-analysis.

Diffusion tensor imaging (DTI) can detect subtle manifestations of white matter (WM) injury following paediatric radiotherapy, which may be a potential biomarker for cognitive changes. This study aimed to synthesise the relationships between DTI indices and cognitive changes following paediatric radiotherapy through systematic review and meta-analysis. PubMed and Scopus electronic databases were used to identify eligible studies. Quality assessment was performed using the National Institute of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Information on demographics, DTI changes, and associations to cognitive outcomes were extracted. Meta-analyses were performed on DTI changes in specific anatomical locations. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in the preparation of this report. Eighteen studies were included (median study size: 21; range 18-146). 17/18 studies showed significant cognitive decline following irradiation. Meta-analyses found significant cognitive changes within patient's group of acute lymphoblastic leukaemia (ALL; standard mean differences [SMD] = -0.075, P = 0.01) and brain tumours (BT; SMD = -1.037, P ≤ 0.001) compared to control/baseline. Both groups also had significantly lower fractional anisotropy (FA) scores in the corpus callosum (ALL: SMD = -0.979, P = 0.002; BT: SMD = -1.025, P < 0.001). Decreased FA was consistently associated with cognitive decline. Correlation on WMFA integrity to cognitive domains was statistically significant (Z = 9.86, P < 0.001) with a large effect size (r = 0.52). White matter tract integrity of the corpus callosum measured with FA has the potential to be a biomarker for radiotherapy-related cognitive decline. Inclusion of DTI in follow-up imaging should be encouraged.

Cognitive Decline following Radiotherapy of Head and Neck Cancer: Systematic Review and Meta-Analysis of MRI Correlates.

Radiotherapy for head and neck cancers exposes small parts of the brain to radiation, resulting in radiation-induced changes in cerebral tissue. In this review, we determine the correlation between cognitive deterioration in patients with head and neck cancer after radiotherapy and magnetic resonance imaging (MRI) changes. Systematic searches were performed in PubMed, Scopus, and Cochrane databases in February 2021. Studies of head and neck cancer patients treated with radiotherapy and periodical cognitive and MRI assessments were included. Meta-analysis was performed to analyse the correlation of Montreal Cognitive Assessment (MoCA) scores to MRI structural and functional changes. Seven studies with a total of 404 subjects (irradiated head and neck patients, n = 344; healthy control, n = 60) were included. Most studies showed the significance of MRI in detecting microstructural and functional changes in association with neurocognitive function. The changes were seen in various brain areas, predominantly the temporal region, which also shows dose dependency (6/7 studies). An effect size (r = 0.43, p < 0.001) was reported on the correlation of MoCA scores to MRI structural and functional changes with significant correlations shown among patients treated with head and neck radiotherapy. However, the effect size appears modest.

Is there an influence of dietary habits on breast density as seen on digital mammograms?

The purpose of this study was to evaluate the influence of dietary habit on breast density, which is an important risk factor for breast cancer. This cross-sectional study was performed on 64 Malaysian women of all races between the age of 35 to 70 years. All subjects underwent mammography and the breast density was analyzed from the images using BI-RADS by two independent radiologists. A validated food-frequency questionnaire was used to evaluate the nutrient intake. The data were analyzed using Chi-square test to evaluate the association of dietary habits to breast density. Based on the results, mutton, pork, vegetables, sweets, snacks, soy bean and eggs intake showed associations with increased breast density (p < 0.05) while grains, meat, beverages, oil and fruits, did not show any association (p > 0.05). As a conclusion, this study showed diet may make changes to the breast density as a risk factor for breast cancer.