In the comatose patient, urgent diagnosis can be a critical priority if appropriate interventions are going to be performed promptly. In many cases, imaging investigations will form a core component of this assessment. In others, where clinical criteria allow confident diagnosis, imaging may still be of significant benefit in providing confirmatory information and may also provide clinically useful prognostic data. In the critically ill comatose patient, confirmation of a diagnosis of brain death may be required. Although this diagnosis is based on clinical criteria, imaging has long been used to provide adjunct supportive information. In recent years, there has been an increased interest in the use of imaging to support a diagnosis of brain death as functional imaging modalities have improved. In this chapter, we will initially review the role of imaging in supporting diagnosis and prognostication in patients suffering from coma. We will discuss the optimal imaging strategies, specific disorders, and specific imaging findings which might help with differential diagnosis and prognostication. We will then discuss the role of imaging in supporting the diagnosis of brain death.

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First proton production rates from the d(d,p)t reaction in the Mega Amp Spherical Tokamak Upgrade (MAST-U) are measured. The data were taken during the MAST-U experimental campaign with an upgraded version of the proton detector (PD) previously used in MAST. The new detector array consists of three collimated silicon surface barrier detectors with a depletion depth of 300 μm and a collimated 120 μm thick diamond detector, mounted on the MAST-U reciprocating probe arm. This array measures the energies of unconfined energetic 3 MeV protons and 1 MeV tritons mainly produced by beam-thermal DD reactions during neutral beam injection heating. Diamond detectors have the potential to be uniquely suited to detect charged fusion products as they promise to be much more radiation resistant and much less sensitive to temperature variations compared to silicon-based detectors. Using silicon and diamond-based detectors simultaneously allowed us to directly compare the performance of these two detector types. PD particle rates measured during different plasma scenarios are presented and compared to neutron rates measured using the neutron camera upgrade and TRANSP predictions.

Background Nonauditory symptoms can be a prominent feature in patients with sporadic vestibular schwannoma (VS), but the cause of these symptoms is unknown. Inflammation is hypothesized to play a key role in the growth and symptomatic presentation of sporadic VS, and in this study, we investigated through translocator protein (TSPO) positron emission tomography (PET) whether inflammation occurred within the "normal appearing" brain of such patients and its association with tumor growth.Methods Dynamic PET datasets from 15 patients with sporadic VS (8 static and 7 growing) who had been previously imaged using the TSPO tracer [11C](R)-PK11195 were included. Parametric images of [11C](R)-PK11195 binding potential (BPND) and the distribution volume ratio (DVR) were derived and compared across VS growth groups within both contralateral and ipsilateral gray (GM) and white matter (WM) regions. Voxel-wise cluster analysis was additionally performed to identify anatomical regions of increased [11C](R)-PK11195 binding.Results Compared with static tumors, growing VS demonstrated significantly higher cortical (GM, 1.070 vs. 1.031, P = .03) and whole brain (GM & WM, 1.045 vs. 1.006, P = .03) [11C](R)-PK11195 DVR values. The voxel-wise analysis supported the region-based analysis and revealed clusters of high TSPO binding within the precentral, postcentral, and prefrontal cortex in patients with growing VS.Conclusions We present the first in vivo evidence of increased TSPO expression and inflammation within the brains of patients with growing sporadic VS. These results provide a potential mechanistic insight into the development of nonauditory symptoms in these patients and highlight the need for further studies interrogating the role of neuroinflammation in driving VS symptomatology.

Abstract Around 95% of low-grade gliomas undergo anaplastic de-differentiation into high-grade gliomas, a process only partially understood from in vivo clinical imaging. 11 patients with suspected transforming gliomas underwent a combined magnetic resonance imaging (MRI) and positron emission tomography (PET) protocol, incorporating post-contrast T1-weighted/FLAIR acquisition for tumour delineation and diffusion tensor imaging. The PET radiotracer [11C]-(R)-PK11195 assessed translocator protein 18kDa (TSPO) distribution, whose upregulation is associated with inflammation/glioma progression. [11C]-(R)-PK11195 binding potential (BPND) maps were generated using the simplified reference tissue model, with the grey-matter cerebellar time-activity curve serving as the reference tissue input function. KMeans clustering of mean diffusivity (MD) intensity values defined spatially distinct “habitats” of high/low MD voxels within the glioma microenvironment. BPND values within high/low MD clustering habitats were evaluated, across glioma grades and isocitrate dehydrogenase (IDH) mutational status. Across all grade 2 and 3 gliomas (n= 6), mean TSPO BPND values in low MD habitats (0.0383 ±0.102) were significantly greater than high MD habitats (-0.045 ±0.142) (p= 0.003). In grade 4 gliomas (n= 5), no significant difference was observed in mean BPND values between low (0.514 ±0.176) and high (0.465 ±0.296) MD habitats (p= 0.543). IDH mutant gliomas (n= 7) exhibited significantly higher mean BPND in low MD habitats (0.116 ±0.225), relative to high habitats (0.052 ±0.287) (p= 0.021). IDH wildtype gliomas (n= 4) showed no significant differences between BPND values in low (0.498 ±0.199) and high MD habitats (0.424 ±0.325) (p= 0.467). Our novel findings demonstrate spatial heterogeneity in TSPO expression within 2/3/IDH mutant gliomas, a characteristic absent from grade 4/IDH wildtype varieties. Regions of restricted diffusion with high TSPO signal in grade 2/3/IDH mutant tumours indicate the heterogenous distribution of active TSPO-expressing immune/neoplastic cell populations, contrasting the homogenous distribution in grade 4/IDH wildtype gliomas, highlighting differences between their inflammatory profile and pathological features.

Background: Tumour apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (MRI) is a putative pharmacodynamic/response biomarker but the relationship between drug-induced effects on the ADC and on the underlying pathology has not been adequately defined. Hypothesis: Changes in ADC during early chemotherapy reflect underlying histological markers of tumour response as measured by tumour regression grade (TRG). Methods: Twenty-six patients were enrolled in the study. Baseline, 14 days, and pre-surgery MRI were performed per study protocol. Surgical resection was performed in 23 of the enrolled patients; imaging-pathological correlation was obtained from 39 lesions from 21 patients. Results: There was no evidence of correlation between TRG and ADC changes at day 14 (study primary endpoint), and no significant correlation with other ADC metrics. In scans acquired one week prior to surgery, there was no significant correlation between ADC metrics and percentage of viable tumour, percentage necrosis, percentage fibrosis, or Ki67 index. Conclusions: Our hypothesis was not supported by the data. The lack of meaningful correlation between change in ADC and TRG is a robust finding which is not explained by variability or small sample size. Change in ADC is not a proxy for TRG in metastatic colorectal cancer.

Supplementary Figure S2. Number of histogram analyses of tumor imaging data between January 1990 and October 2014.

Schematic representation of MRI protocols

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Supplementary Table S1. TUMAPs contained in IMA950 and associated source antigens. Supplementary Table S2. Statistical analysis underlying the recruitment of 20 immune evaluable patients per cohort. Supplementary Table S3. Reasons for HLA-A*02 positive patients not entering the clinical trial. Supplementary Figure S1. Study schedule. Supplementary Figure S2. Exemplary gating strategy used for the primary multimer assay. Supplementary Figure S3. Exemplary immune responses in patients as determined by multimer assay after in vitro sensitization. Supplementary Figure S4. Apparent diffusion coefficient (ADC) in Cohort 1 at each of the four scan points.

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Summary mean DCE-MRI variables show a clear dependency between signal and noise variance, which can be shown to reduce the effectiveness of difference assessments. Appropriate transformation of these variables supports statistically efficient and robust comparisons. The capabilities of DCE-MRI based descriptions of hepatic colorectal tumour classification was assessed, with regard to their potential for use as imaging biomarkers. Four DCE-MRI parameters were extracted from 102 selected tumour regions. A multi-dimensional statistical distance metric was assessed for the challenging task of comparing intra- and inter- subject tumour differences. Statistical errors were estimated using bootstrap resampling. The potential for tumour classification was assessed via Monte Carlo simulation. Transformation of the variables and fusion into a single chi-squared statistic shows that inter subject variation in hepatic tumours is measurable and significantly greater than intra-subject variation at the group level. However, reliability analysis shows that, at current noise levels, individual tumour assessment is not possible. Appropriate data transforms for DCE-MRI derived parameters produce an improvement in statistical sensitivity compared to conventional approaches. Reliability analysis shows, that even with data transformation, DCI-MRI variables do not currently facilitate good tumour discrimination and a doubling of SNR is needed to support non-trivial levels of classification

Abstract AIMS To characterize spatial distributions of 18kDa translocator protein (TSPO) and amino acid uptake as measured through dynamic [11C] (R)-PK11195 and [11C]-methionine PET in high-grade glioma. METHOD Twelve patients with newly diagnosed high-grade glioma underwent dual PET studies. [11C] (R)-PK11195 binding potential (BPND) maps were generated using simplified reference tissue model with grey-matter cerebellar time- activity-curve as tissue input-function. [11C]-methionine uptake was calculated as tumour-to-background ratio (TBR). Volumes of interest (VOIs) were defined on T1W post-contrast MRI as contrast-enhancing (CE) tumour and a ‘peritumoural’ region 5mm from the CE edge. Voxel-wise comparison of the tracers used Pearson’s correlation coeffcient. VOIs were furthermore subdivided into higher/lower TSPO (BPND > 0.17) and higher/lower methionine (TBR > 1.7). RESULTS Within the CE, voxel-wise comparison showed a strong correlation (r > 0.7) in eight subjects, moderate correlation (r > 0.5) in three subjects and weak correlation (r < 0.5) in one subject. Volume (mm3) with high BPND/high TBR accounted for 62±29% whereas high BPND/low TBR accounted for 13±16%. Within the peritumoral area, there was a small reduction in the proportion of subjects in the strong correlation group (6/12) but the pro- portion of voxels with higher TSPO binding and lower methionine uptake was substantially greater (35±16%). CONCLUSIONS Within high-grade glioma, there is a strong overall correlation between TSPO expression and amino acid uptake. However, in the peritumoural region there are areas of elevated TSPO expression without increased methionine uptake which could represent an inflammatory component or a discrete neoplastic cell population that may not be adequately defined with standard imaging biomarkers.

CCR Translation for the Article from Quantifying Antivascular Effects of Monoclonal Antibodies to Vascular Endothelial Growth Factor: Insights from Imaging

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Accurate vascular input function (VIF) derivation is essential in brain dynamic contrast-enhanced (DCE) MRI. The optimum site for VIF estimation is, however, debated. This study sought to compare VIFs extracted from the internal carotid artery (ICA) and its branches with an arrival-corrected vascular output function (VOF) derived from the superior sagittal sinus (VOF SSS ). DCE-MRI datasets from sixty-six patients with different brain tumours were retrospectively analysed and plasma gadolinium-based contrast agent (GBCA) concentration-time curves used to extract VOF/VIFs from the SSS, the ICA, and the middle cerebral artery. Semi-quantitative parameters across each first-pass VOF/VIF were compared and the relationship between these parameters and GBCA dose was evaluated. Through a test–retest study in 12 patients, the repeatability of each semiquantitative VOF/VIF parameter was evaluated; and through comparison with histopathological data the accuracy of kinetic parameter estimates derived using each VOF/VIF and the extended Tofts model was also assessed. VOF SSS provided a superior surrogate global input function compared to arteries, with greater contrast-to-noise ( p < 0.001), higher peak ( p < 0.001, repeated-measures ANOVA), and a greater sensitivity to interindividual plasma GBCA concentration. The repeatability of VOF SSS derived semi-quantitative parameters was good to excellent (ICC = 0.717–0.888) outperforming arterial based approaches. In contrast to arterial VIFs, kinetic parameters obtained using a SSS derived VOF permitted detection of intertumoural differences in both microvessel surface area and cell density within resected tissue specimens. These results support the usage of an arrival-corrected VOF SSS as a surrogate vascular input function for kinetic parameter mapping in brain DCE-MRI.

Despite the disease's long history, little progress has been made toward a treatment for rabies. The prognosis for patient recovery remains dire. For any prospect of survival, patients require aggressive critical care, which physicians in rabies endemic areas may be reluctant or unable to provide given the cost, clinical expertise required, and uncertain outcome. Systematic clinical research into combination therapies is further hampered by sporadic occurrence of cases. In this Perspective, we examine the case for a One Medicine approach to accelerate development of an effective therapy for rabies through the veterinary care and investigational treatment of naturally infected dogs in appropriate circumstances. We review the pathogenesis of rabies virus in humans and dogs, including recent advances in our understanding of the molecular basis for the severe neurological dysfunction. We propose that four categories of disease process need to be managed in patients: viral propagation, neuronal degeneration, inflammation and systemic compromise. Compassionate critical care and investigational treatment of naturally infected dogs receiving supportive therapy that mimics the human clinical scenario could increase opportunities to study combination therapies that address these processes, and to identify biomarkers for prognosis and therapeutic response. We discuss the safety and ethics of this approach, and introduce the Canine Rabies Treatment Initiative, a non-profit organization with the mission to apply a One Medicine approach to the investigation of diagnostic, prognostic, and therapeutic options for rabies in naturally infected dogs, to accelerate transformation of rabies into a treatable disease for all patients.

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.