Neurotransmitter receptor densities are associated with changes in regional Cerebral blood flow during clinical ongoing pain

MR-guided Focused Ultrasound Thalamotomy for Chronic Pain

MR-guided focused ultrasound (FUS) represents a promising alternative for patients with chronic neuropathic who have failed medical management and other treatment options. Early single-center experience with chronic neuropathic pain and trigeminal neuralgia has demonstrated favorable long-term outcomes. Excellent safety profile with low risk of motor and sensory complications and so far anecdotal permanent neurologic deficits make FUS a powerful tool to treat patients who are otherwise hopeless. Neuromodulation may be the most influential factor driving outcomes and studies devised to detect neuroplasticity will be critical to guide such therapies.

Improving neuropathic pain treatment - by rigorous stratification from bench to bedside

Chronic pain is a constantly recurring and persistent illness, presenting a formidable healthcare challenge for patients and physicians alike. Current first-line analgesics offer only low-modest efficacy when averaged across populations, further contributing to this debilitating disease burden. Moreover, many recent trials for novel analgesics have not met primary efficacy endpoints, which is particularly striking considering the pharmacological advances have provided a range of highly relevant new drug targets. Heterogeneity within chronic pain cohorts is increasingly understood to play a critical role in these failures of treatment and drug discovery, with some patients deriving substantial benefits from a given intervention while it has little-to-no effect on others. As such, current treatment failures may not result from a true lack of efficacy, but rather a failure to target individuals whose pain is driven by mechanisms which it therapeutically modulates. This necessitates a move towards phenotypical stratification of patients to delineate responders and non-responders in a mechanistically driven manner. In this article, we outline a bench-to-bedside roadmap for this transition to mechanistically informed personalised pain medicine. We emphasise how the successful identification of novel analgesics is dependent on rigorous experimental design as well as the validity of models and translatability of outcome measures between the animal model and patients. Subsequently, we discuss general and specific aspects of human trial design to address heterogeneity in patient populations to increase the chance of identifying effective analgesics. Finally, we show how stratification approaches can be brought into clinical routine to the benefit of patients.

Radiomic features of the hippocampal based on magnetic resonance imaging in the menopausal mouse model linked to neuronal damage and cognitive deficits

Estrogen deficiency in the early postmenopausal phase is associated with an increased long-term risk of cognitive decline or dementia. Non-invasive characterization of the pathological features of the pathological hallmarks in the brain associated with postmenopausal women (PMW) could enhance patient management and the development of therapeutic strategies. Radiomics is a means to quantify the radiographic phenotype of a diseased tissue via the high-throughput extraction and mining of quantitative features from images acquired from modalities such as CT and magnetic resonance imaging (MRI). This study set out to explore the correlation between radiomics features based on MRI and pathological features of the hippocampus and cognitive function in the PMW mouse model. Ovariectomized (OVX) mice were used as PWM models. MRI scans were performed two months after surgery. The brain's hippocampal region was manually annotated, and the radiomic features were extracted with PyRadiomics. Chemiluminescence was used to evaluate the peripheral blood estrogen level of mice, and the Morris water maze test was used to evaluate the cognitive ability of mice. Nissl staining and immunofluorescence were used to quantify neuronal damage and COX1 expression in brain sections of mice. The OVX mice exhibited marked cognitive decline, brain neuronal damage, and increased expression of mitochondrial complex IV subunit COX1, which are pathological phenomena commonly observed in the brains of AD patients, and these phenotypes were significantly correlated with radiomics features (p < 0.05, |r|>0.5), including Original_firstorder_Interquartile Range, Original_glcm_Difference Average, Original_glcm_Difference Average and Wavelet-LHH_glszm_Small Area Emphasis. Meanwhile, the above radiomics features were significantly different between the sham-operated and OVX groups (p < 0.01) and were associated with decreased serum estrogen levels (p < 0.05, |r|>0.5). This initial study indicates that the above radiomics features may have a role in the assessment of the pathology of brain damage caused by estrogen deficiency using routinely acquired structural MR images.

From neurotransmitters to networks: Transcending organisational hierarchies with molecular-informed functional imaging

The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain's function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research - spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses - to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.