Centres of Excellence in Neurodegeneration.

fects to the development of indicator fractionation and clearance methods such as autoradiography, hydrogen clearance, and positron emission tomography (PET), the clinical and experimental need for a ready means of CBF assessment has been complemented by the efforts to de velop such quantification techniques (Bell, 1984). Nev ertheless, the ultimate goal of a totally noninvasive method that enables the mapping of CBF with high tem poral and spatial resolution over the wide range of rel evant blood flows has not been attained.The advantage of using a magnetic resonance imaging (MRI) based perfusion imaging method is that, in addi tion to its noninvasiveness, the option of using other nuclear magnetic resonance techniques (e.g., diffusion weighted imaging, metabolite spectroscopy, tissue relax ometry) is available. This allows the combined longitu dinal assessment of tissue perfusion, morphologic fea tures, metabolism, and function, thus providing a more complete understanding of the developing pathophysi ologic mechanism. The sensitivity of nuclear magnetic resonance to the movement of spins in flowing liquids was noted at an early stage (Singer, 1959) and has led to the important radiologic technique of magnetic reso nance (MR) angiography (Potchen et al., 1993). Efforts to image perfusion, on the other hand, have been dogged by the relatively low volume and velocity of moving spins in capillary beds. The pioneering work of Le Bihan et al. (1986) and Turner (1988), who used the dephasing of randomly perfusing water protons (intravoxel incoher ent motion) in magnetic field gradients as an index of 702 F. CALAMANTE ET AL.tissue perfusion, was thwarted by the inadequacy of the hardware available to provide sufficient image dynamic range for useful quantification of perfusion. In the suc ceeding years, two distinct MRI techniques have arisen, each with well-supported claims to provide a quantitative assessment of CBF. These methods differ with regard to their respective use of an exogenous and endogenous MRI-visible tracer. The first of the techniques, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI), is not entirely noninvasive, requiring injec tion of a contrast agent toxic in high dosages, whereas the second, arterial spin labeling (ASL), uses radiofre quency (RF) pulses to magnetically label moving spins in flowing blood. PERFUSION IMAGING USING MR CONTRAST AGENTSThe use of exogenous MR contrast agents for the study of cerebral perfusion has long been recognized (Villringer et aI., 1988; Rosen et aI., 1990). These con trast agents also provide information about different physiologic parameters related to CBF, cerebral blood volume (CBV) and the mean transit time (MTT) ... through a volume of tissue. This technique, usually re ferred to as DSC-MRI, involves the injection of a bolus of contrast agent (typically 0. 1 to 0.3 mmol/kg body weight) and the rapid measurement of the MRI signal loss caused by spin dephasing (i.e., decrease in T2 and T 2 *) during its fast passage through the tissue (V...

Tumors display a greater reliance on glycolysis for energy production than normal tissues. We have developed a non-invasive method for imaging glucose uptake in vivo, which is based on magnetic resonance imaging, and allows the uptake of non-labeled glucose to be measured via the chemical exchange of protons between hydroxyl groups and water. This method differs from existing molecular imaging methods, as it permits detection of the delivery and uptake of a metabolically active compound at physiological quantities. We show that our technique, named glucose chemical exchange saturation transfer (glucoCEST), is sensitive to tumor glucose accumulation in colorectal tumor models, and can distinguish tumor types with differing metabolic characteristics and pathophysiology. The results of this study suggest that glucoCEST has potential as a useful and cost-effective method for characterizing disease and assessing response to therapy in the clinic.

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique—Subtype and Stage Inference (SuStaIn)—able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer’s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10−4) or temporal stage (p = 3.96 × 10−5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

No abstract

Frontotemporal dementia (FTD) is a highly heritable condition with multiple genetic causes. In this study, similarities and differences of gray matter (GM) atrophy patterns were assessed among 3 common forms of genetic FTD (mutations in C9orf72, GRN, and MAPT). Participants from the Genetic FTD Initiative (GENFI) cohort with a suitable volumetric T1 magnetic resonance imaging scan were included (319): 144 nonmutation carriers, 128 presymptomatic mutation carriers, and 47 clinically affected mutation carriers. Cross-sectional differences in GM volume between noncarriers and carriers were analyzed using voxel-based morphometry. In the affected carriers, each genetic mutation group exhibited unique areas of atrophy but also a shared network involving the insula, orbitofrontal lobe, and anterior cingulate. Presymptomatic GM atrophy was observed particularly in the thalamus and cerebellum in the C9orf72 group, the anterior and medial temporal lobes in MAPT, and the posterior frontal and parietal lobes as well as striatum in GRN. Across all presymptomatic carriers, there were significant decreases in the anterior insula. These results suggest that although there are important differences in atrophy patterns for each group (which can be seen presymptomatically), there are also similarities (a fronto-insula-anterior cingulate network) that help explain the clinical commonalities of the disease.

Objectives This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. Methods An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. Results Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. Discussion This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding.

The habenula is a small, evolutionarily conserved brain structure that plays a central role in aversive processing and is hypothesised to be hyperactive in depression, contributing to the generation of symptoms such as anhedonia. However, habenula responses during aversive processing have yet to be reported in individuals with major depressive disorder (MDD). Unmedicated and currently depressed MDD patients (N=25, aged 18–52 years) and healthy volunteers (N=25, aged 19–52 years) completed a passive (Pavlovian) conditioning task with appetitive (monetary gain) and aversive (monetary loss and electric shock) outcomes during high-resolution functional magnetic resonance imaging; data were analysed using computational modelling. Arterial spin labelling was used to index resting-state perfusion and high-resolution anatomical images were used to assess habenula volume. In healthy volunteers, habenula activation increased as conditioned stimuli (CSs) became more strongly associated with electric shocks. This pattern was significantly different in MDD subjects, for whom habenula activation decreased significantly with increasing association between CSs and electric shocks. Individual differences in habenula volume were negatively associated with symptoms of anhedonia across both groups. MDD subjects exhibited abnormal negative task-related (phasic) habenula responses during primary aversive conditioning. The direction of this effect is opposite to that predicted by contemporary theoretical accounts of depression based on findings in animal models. We speculate that the negative habenula responses we observed may result in the loss of the capacity to actively avoid negative cues in MDD, which could lead to excessive negative focus.