Examining iron-related off-target binding effects of 18F-AV1451 PET in the cortex of Aß+ individuals.

The presence of neurofibrillary tangles containing hyper-phosphorylated tau is a characteristic of Alzheimer's disease (AD) pathology. The positron emission tomography (PET) radioligand sensitive to tau neurofibrillary tangles (18F-AV1451) also binds with iron. This off-target binding effect may be enhanced in older adults on the AD spectrum, particularly those with amyloid-positive biomarkers. Here, we examined group differences in 18F-AV1451 PET after controlling for iron-sensitive measures from magnetic resonance imaging (MRI) and its relationships to tissue microstructure and cognition in 40 amyloid beta positive (Aß+) individuals, 20 amyloid beta negative (Aß-) with MCI and 31 Aß- control participants. After controlling for iron, increased 18F-AV1451 PET uptake was found in the temporal lobe and hippocampus of Aß+ participants compared to Aß- MCI and control participants. Within the Aß+ group, significant correlations were seen between 18F-AV1451 PET uptake and tissue microstructure and these correlations remained significant after controlling for iron. These findings indicate that off-target binding of iron to the 18F-AV1451 ligand may not affect its sensitivity to Aß status or cognition in early-stage AD.

In vivo detection of lateral-ventral tier nigral degeneration in Parkinson's disease.

The objective of this study was to measure neuromelanin-sensitive MRI contrast changes in the lateral-ventral tier of substantia nigra pars compacta in Parkinson's disease (PD). Histopathological studies of PD have demonstrated both massive loss of melanized dopamine neurons and iron accumulation in the substantia nigra pars compacta. Neurodegeneration is most profound in the lateral-ventral tier of this structure. We have previously shown in both healthy controls and individuals with PD that neuromelanin-sensitive MRI and iron-sensitive MRI contrast regions in substantia nigra overlap. This overlap region is located in the lateral-ventral tier. Exploiting this area of contrast overlap for region of interest selection, we developed a semi-automated image processing approach to characterize the lateral-ventral tier in MRI data. Here we apply this approach to measure magnetization transfer contrast, which corresponds to local neuromelanin density, in both the lateral-ventral tier and the entire pars compacta in 22 PD patients and 19 controls. Significant contrast reductions were seen in PD in both the entire pars compacta (P = 0.009) and in its lateral-ventral tier (P = 0.0002); in PD contrast was significantly lower in the lateral-ventral tier than in the entire pars compacta (P = 0.0008). These findings are the first in vivo evidence of the selective vulnerability of this nigral subregion in PD, and this approach may be developed for high impact biomarker applications. Hum Brain Mapp 38:2627-2634, 2017. © 2017 Wiley Periodicals, Inc.

Parkinson's disease-related increase of T2*-weighted hypointensity in substantia nigra pars compacta.

BACKGROUND: In PD, at the time of diagnosis, approximately 50% of melanized dopaminergic neurons in SNpc have died, yet ongoing neuronal death and neuromelanin release with associated neuroinflammation and microglial activation continue, as does local iron accumulation. Previous studies investigating nigral iron accumulation used T2 / T2*-weighted contrasts to define the regions of interest in the SN. Given that T2 / T2*-weighted contrasts lack sensitivity to neuromelanin and thereby SNpc, neuromelanin-sensitive MRI provides better delineation of SNpc and allows the examination of increased iron deposition in SNpc more specifically and accurately. OBJECTIVES: To examine regions of the SNpc, defined by neuromelanin-sensitive MRI, exhibiting iron deposition in PD. METHODS: T1 -weighted and susceptibility weighted imaging data were obtained in a cohort of 82 subjects (54 controls and 28 PD patients). The PD patients were clinically diagnosed with an average UPDRS-III score of 37.9 ± 12.5 in the off medication state. Susceptibility weighted imaging data were analyzed using SNpc regions of interest defined by neuromelanin-sensitive MRI. RESULTS: Compared to control subjects, significantly more hypointense signal was observed in the SNpc defined by neuromelanin-sensitive MRI in the PD patients. In the PD group, the lateral ventral region of SNpc exhibited the greatest increase of hypointensity. This increase in the lateral ventral region of SNpc robustly differentiated PD patients from controls. CONCLUSION: T2*-weighted hypointense signal in the SNpc defined by neuromelanin-sensitive MRI is significantly increased in PD. It is most likely a measure sensitive to PD-related iron deposition and may serve as a robust biomarker of PD. © 2016 International Parkinson and Movement Disorder Society.

Improved Neuroimaging Atlas of the Dentate Nucleus.

The dentate nucleus (DN) of the cerebellum is the major output nucleus of the cerebellum and is rich in iron. Quantitative susceptibility mapping (QSM) provides better iron-sensitive MRI contrast to delineate the boundary of the DN than either T2-weighted images or susceptibility-weighted images. Prior DN atlases used T2-weighted or susceptibility-weighted images to create DN atlases. Here, we employ QSM images to develop an improved dentate nucleus atlas for use in imaging studies. The DN was segmented in QSM images from 38 healthy volunteers. The resulting DN masks were transformed to a common space and averaged to generate the DN atlas. The center of mass of the left and right sides of the QSM-based DN atlas in the Montreal Neurological Institute space was -13.8, -55.8, and -36.4 mm, and 13.8, -55.7, and -36.4 mm, respectively. The maximal probability and mean probability of the DN atlas with the individually segmented DNs in this cohort were 100 and 39.3%, respectively, in contrast to the maximum probability of approximately 75% and the mean probability of 23.4 to 33.7% with earlier DN atlases. Using QSM, which provides superior iron-sensitive MRI contrast for delineating iron-rich structures, an improved atlas for the dentate nucleus has been generated. The atlas can be applied to investigate the role of the DN in both normal cortico-cerebellar physiology and the variety of disease states in which it is implicated.

Age-related increases in basal ganglia glutamate are associated with TNF, reduced motivation and decreased psychomotor speed during IFN-alpha treatment: Preliminary findings.

Inflammation-induced alterations in central nervous system (CNS) metabolism have focused on glutamate. At excessive concentrations, glutamate is toxic to glia and neurons, and inflammatory cytokines have been shown to influence glutamate turnover by blocking glutamate reuptake and increasing glutamate release. Increased glutamate has also been found in depression, a disorder associated with increased inflammation. Data by our group have shown increased glutamate as measured by magnetic resonance spectroscopy (MRS) in basal ganglia and dorsal anterior cingulate cortex of patients administered the inflammatory cytokine interferon (IFN)-alpha. Given data that increasing age is associated with an exaggerated CNS inflammatory response, we examined whether older age (>55years) would be associated with a greater IFN-alpha-induced increase in CNS glutamate. Using a longitudinal design, 31 patients with hepatitis C virus (HCV) underwent MRS, blood sampling for inflammatory markers, and behavioral assessments before (Visit 1) and after 4weeks (Visit 2) of either IFN-alpha (n=17) or no treatment (n=14). Older patients treated with IFN-alpha exhibited a significantly greater increase in glutamate from Visit 1 to Visit 2 as reflected by the glutamate/creatine ratio (Glu/Cr) in left basal ganglia compared to older controls and younger IFN-alpha-treated and untreated subjects. In addition, increased Glu/Cr in older but not younger IFN-alpha-treated and untreated patients was associated with increased tumor necrosis factor, reduced motivation as measured by the Multidimensional Fatigue Inventory and increased choice movement time on the Cambridge Neuropsychological Test Automated Battery. Taken together, these preliminary data support the notion that older age may interact with inflammation to exaggerate the effects of inflammatory stimuli on CNS glutamate and behavior.

A bacterial gene, mms6, as a new reporter gene for magnetic resonance imaging of mammalian cells.

Magnetic resonance imaging (MRI) allows for noninvasive, deep tissue imaging with high spatial resolution, making it an attractive modality for in vivo cellular imaging. Since reporter genes can generate magnetic resonance (MR) contrast based on molecular activity, they offer a potentially powerful tool for cellular imaging. The mms6 gene was originally identified in magnetotactic bacteria (MTB), which is known to play a key role in magnetic crystal formation. The purpose of the present work was to investigate the possibility of using mms6 as an MR reporter gene. We established a transgenic mammalian cell line that stably expresses mms6. In vitro experiments show that mms6-expressing cells form clusters of nanoparticles within and outside membrane-enclosed structures and produce changes in MR contrast, most likely by increasing iron uptake of intracellular iron. Additionally, in vivo MRI experiments demonstrate that mms6-expressing tumors can be distinguished from parental tumors not expressing mms6, even in the absence of exogenous iron supplementation. Our results demonstrate that mms6 can function as an MR reporter gene with the potential to monitor gene expression and to visualize the proliferation, migration, and metastasis of tumor cells expressing it.

Use of high-resolution volumetric MR spectroscopic imaging in assessing treatment response of glioblastoma to an HDAC inhibitor.

OBJECTIVE: Improved predictive imaging would enable personalization and adjustment of treatment, which are critical for patients with glioblastomain whom therapy is likely to fail. This article describes the use of MR spectroscopic imaging (MRSI) to predict early clinical and behavioral response to a therapy and an effort to develop high-resolution, volumetric MRSI to improve its clinical application. CONCLUSION: MRSI may enable quantitative analysis of brain tumor response, offering a precise tool for monitoring of patients in clinical trials.

Locus coeruleus contrast and diffusivity metrics differentially relate to age and memory performance.

Neurocognitive aging researchers are increasingly focused on the locus coeruleus, a neuromodulatory brainstem structure that degrades with age. With this rapid growth, the field will benefit from consensus regarding which magnetic resonance imaging (MRI) metrics of locus coeruleus structure are most sensitive to age and cognition. To address this need, the current study acquired magnetization transfer- and diffusion-weighted MRI images in younger and older adults who also completed a free recall memory task. Results revealed significantly larger differences between younger and older adults for maximum than average magnetization transfer-weighted contrast (MTC), axial than mean or radial single-tensor diffusivity (DTI), and free than restricted multi-compartment diffusion (NODDI) metrics in the locus coeruleus; with maximum MTC being the best predictor of age group. Age effects for all imaging modalities interacted with sex, with larger age group differences in males than females for MTC and NODDI metrics. Age group differences also varied across locus coeruleus subdivision for DTI and NODDI metrics, and across locus coeruleus hemispheres for MTC. Within older adults, however, there were no significant effects of age on MTC or DTI metrics, only an interaction between age and sex for free diffusion. Finally, independent of age and sex, higher restricted diffusion in the locus coeruleus was significantly related to better (lower) recall variability, but not mean recall. Whereas MTC has been widely used in the literature, our comparison between the average and maximum MTC metrics, inclusion of DTI and NODDI metrics, and breakdowns by locus coeruleus subdivision and hemisphere make important and novel contributions to our understanding of the aging of locus coeruleus structure.

Nigral volume loss in prodromal, early, and moderate Parkinson's disease.

The loss of melanized neurons in the substantia nigra pars compacta (SNc) is a hallmark pathology in Parkinson's disease (PD). Melanized neurons in SNc can be visualized in vivo using magnetization transfer (MT) effects. Nigral volume was extracted in data acquired with a MT-prepared gradient echo sequence in 33 controls, 83 non-manifest carriers (42 LRRK2 and 41 GBA nonmanifest carriers), 65 prodromal hyposmic participants, 105 de novo PD patients and 26 48-month PD patients from the Parkinson's Progressive Markers Initiative. No difference in nigral volume was seen between controls and LRRK2 and GBA non-manifest carriers (F=0.076; P=0.927). A significant main effect in group was observed between controls, prodromal hyposmic participants, and overt PD patients (F=5.192; P=0.002). Longer disease duration significantly correlated with lower nigral volume (r=-0.252; P=0.010). This study shows that nigral depigmentation can be robustly detected in prodromal hyposmic participants and overt PD patients.

In vivo detection of substantia nigra and locus coeruleus volume loss in Parkinson's disease using neuromelanin-sensitive MRI: Replication in two cohorts.

Patients with Parkinson's disease undergo a loss of melanized neurons in substantia nigra pars compacta and locus coeruleus. Very few studies have assessed substantia nigra pars compacta and locus coeruleus pathology in Parkinson's disease simultaneously with magnetic resonance imaging (MRI). Neuromelanin-sensitive MRI measures of substantia nigra pars compacta and locus coeruleus volume based on explicit magnetization transfer contrast have been shown to have high scan-rescan reproducibility in controls, but no study has replicated detection of Parkinson's disease-associated volume loss in substantia nigra pars compacta and locus coeruleus in multiple cohorts with the same methodology. Two separate cohorts of Parkinson's disease patients and controls were recruited from the Emory Movement Disorders Clinic and scanned on two different MRI scanners. In cohort 1, imaging data from 19 controls and 22 Parkinson's disease patients were acquired with a Siemens Trio 3 Tesla scanner using a 2D gradient echo sequence with magnetization transfer preparation pulse. Cohort 2 consisted of 33 controls and 39 Parkinson's disease patients who were scanned on a Siemens Prisma 3 Tesla scanner with a similar imaging protocol. Locus coeruleus and substantia nigra pars compacta volumes were segmented in both cohorts. Substantia nigra pars compacta volume (Cohort 1: p = 0.0148; Cohort 2: p = 0.0011) and locus coeruleus volume (Cohort 1: p = 0.0412; Cohort 2: p = 0.0056) were significantly reduced in the Parkinson's disease group as compared to controls in both cohorts. This imaging approach robustly detects Parkinson's disease effects on these structures, indicating that it is a promising marker for neurodegenerative neuromelanin loss.

A Novel Hidden Markov Approach to Studying Dynamic Functional Connectivity States in Human Neuroimaging.

Introduction: Hidden Markov models (HMMs) are a popular choice to extract and examine recurring patterns of activity or functional connectivity in neuroimaging data, both in terms of spatial patterns and their temporal progression. Although many diverse HMMs have been applied to neuroimaging data, most have defined states based on activity levels (intensity-based [IB] states) rather than patterns of functional connectivity between brain areas (connectivity-based states), which is problematic if we want to understand connectivity dynamics: IB states are unlikely to provide comprehensive information about dynamic connectivity patterns. Methods: We addressed this problem by introducing a new HMM that defines states based on full functional connectivity (FFC) profiles among brain regions. We empirically explored the behavior of this new model in comparison to existing approaches based on IB or summed functional connectivity states using the Human Connectome Project unrelated 100 functional magnetic resonance imaging "resting-state" dataset. Results: Our FFC model discovered connectivity states with more distinguishable (i.e., unique and separable from each other) patterns than previous approaches, and recovered simulated connectivity-based states more faithfully than the other models tested. Discussion: Thus, if our goal is to extract and interpret connectivity states in neuroimaging data, our new model outperforms previous methods, which miss crucial information about the evolution of functional connectivity in the brain. Impact statement Hidden Markov models (HMMs) can be used to investigate brain states noninvasively. Previous models "recover" connectivity from intensity-based hidden states, or from connectivity "summed" across nodes. In this study, we introduce a novel connectivity-based HMM and show how it can reveal true connectivity hidden states under minimal assumptions.

Locus coeruleus integrity predicts ease of attaining and maintaining neural states of high attentiveness.

The locus coeruleus (LC), a small subcortical structure in the brainstem, is the brain's principal source of norepinephrine. It plays a primary role in regulating stress, the sleep-wake cycle, and attention, and its degradation is associated with aging and neurodegenerative diseases associated with cognitive deficits (e.g., Parkinson's, Alzheimer's). Yet precisely how norepinephrine drives brain networks to support healthy cognitive function remains poorly understood - partly because LC's small size makes it difficult to study noninvasively in humans. Here, we characterized LC's influence on brain dynamics using a hidden Markov model fitted to functional neuroimaging data from healthy young adults across four attention-related brain networks and LC. We modulated LC activity using a behavioral paradigm and measured individual differences in LC magnetization transfer contrast. The model revealed five hidden states, including a stable state dominated by salience-network activity that occurred when subjects actively engaged with the task. LC magnetization transfer contrast correlated with this state's stability across experimental manipulations and with subjects' propensity to enter into and remain in this state. These results provide new insight into LC's role in driving spatiotemporal neural patterns associated with attention, and demonstrate that variation in LC integrity can explain individual differences in these patterns even in healthy young adults.

Generalized RAICAR: discover homogeneous subject (sub)groups by reproducibility of their intrinsic connectivity networks.

Existing spatial independent component analysis (ICA) methods for multi-subject fMRI datasets have mainly focused on detecting common components across subjects, under the assumption that all the subjects in a group share the same (identical) components. However, as a data-driven approach, ICA could potentially serve as an exploratory tool at multi-subject level, and help us uncover inter-subject differences in patterns of connectivity (e.g., find subtypes in patient populations). In this work, we propose a methodology named gRAICAR that exploits the data-driven nature of ICA to allow discovery of sub-groupings of subjects based on reproducibility of their ICA components. This technique allows us not only to find highly reproducible common components across subjects but also to explore (without a priori subject groupings) components that could classify all subjects into sub-groups. gRAICAR generalizes the reproducibility framework previously developed for single subjects (Ranking and averaging independent component analysis by reproducibility-RAICAR-Yang et al., Hum Brain Mapp, 2008) to multiple-subject analysis. For each group-level component, gRAICAR generates its reproducibility matrix and further computes two metrics, inter-subject consistency and intra-subject reliability, to characterize inter-subject variability and reflect contributions from individual subjects. Nonparametric tests are employed to examine the significance of both the inter-subject consistency and the separation of subject groups reflected in the component. Our validations based on simulated and experimental resting-state fMRI datasets demonstrated the advantage of gRAICAR in extracting features reflecting potential subject groupings. It may facilitate discovery of the underlying brain functional networks with substantial potential to inform our understandings of development, neurodegenerative conditions, and psychiatric disorders.

A whole brain fMRI atlas generated via spatially constrained spectral clustering.

Connectivity analyses and computational modeling of human brain function from fMRI data frequently require the specification of regions of interests (ROIs). Several analyses have relied on atlases derived from anatomical or cyto-architectonic boundaries to specify these ROIs, yet the suitability of atlases for resting state functional connectivity (FC) studies has yet to be established. This article introduces a data-driven method for generating an ROI atlas by parcellating whole brain resting-state fMRI data into spatially coherent regions of homogeneous FC. Several clustering statistics are used to compare methodological trade-offs as well as determine an adequate number of clusters. Additionally, we evaluate the suitability of the parcellation atlas against four ROI atlases (Talairach and Tournoux, Harvard-Oxford, Eickoff-Zilles, and Automatic Anatomical Labeling) and a random parcellation approach. The evaluated anatomical atlases exhibit poor ROI homogeneity and do not accurately reproduce FC patterns present at the voxel scale. In general, the proposed functional and random parcellations perform equivalently for most of the metrics evaluated. ROI size and hence the number of ROIs in a parcellation had the greatest impact on their suitability for FC analysis. With 200 or fewer ROIs, the resulting parcellations consist of ROIs with anatomic homology, and thus offer increased interpretability. Parcellation results containing higher numbers of ROIs (600 or 1,000) most accurately represent FC patterns present at the voxel scale and are preferable when interpretability can be sacrificed for accuracy. The resulting atlases and clustering software have been made publicly available at: http://www.nitrc.org/projects/cluster_roi/.

View angle tilting echo planar imaging for distortion correction.

Geometric distortion caused by field inhomogeneity along the phase-encode direction is one of the most prominent artifacts due to a relatively low effective bandwidth along that direction in magnetic resonance echo planar imaging. This work describes a method for correcting in-plane image distortion along the phase-encode direction using a view angle tilting imaging technique in spin-echo echo planar imaging. Spin-echo echo planar imaging with view angle tilting uses the addition of gradient blips along the slice-select direction, concurrently applied with the phase-encode gradient blips, producing an additional phase. This phase effectively offsets an unwanted phase accumulation caused by field inhomogeneity, resulting in the removal of image distortion along the phase-encode direction. The proposed method is simple and straightforward both in implementation and application with no scan time penalty. Therefore, it is readily applicable on commercial scanners without having any customized postprocessing. The efficacy of the spin-echo echo planar imaging with view angle tilting technique in the correction of image distortion is demonstrated in phantom and in vivo brain imaging.

Adiabatic pulse preparation for imaging iron oxide nanoparticles.

Superparamagnetic iron oxide nanoparticles produce changes in the surrounding microscopic magnetic field. A method for generating contrast based on the application of an adiabatic preparation pulse and the failure of the adiabatic condition surrounding the nanoparticles is introduced in this article. Images were obtained in the presence and absence of an adiabatic preparation pulse and the difference was obtained. With the use of an adiabatic full passage pulse, the contrast in the difference image depends linearly on iron concentration up to 1 mM. The use of an adiabatic zero passage pulse resulted in higher sensitivity to nanoparticles compared to the adiabatic full passage, while maintaining linear concentration dependence to 0.1 mM. This technique was shown to be insensitive to magnetization transfer and B(0) inhomogeneity. With its linearity with iron concentration and insensitivity to changes in the main magnetic field, the new method is well suited for quantitative iron oxide nanoparticle imaging.

Direct detection of a single evoked action potential with MRS in Lumbricus terrestris.

Functional MRI (fMRI) measures neural activity indirectly by detecting the signal change associated with the hemodynamic response following brain activation. In order to alleviate the temporal and spatial specificity problems associated with fMRI, a number of attempts have been made to detect neural magnetic fields (NMFs) with MRI directly, but have thus far provided conflicting results. In this study, we used MR to detect axonal NMFs in the median giant fiber of the earthworm, Lumbricus terrestris, by examining the free induction decay (FID) with a sampling interval of 0.32 ms. The earthworm nerve cords were isolated from the vasculature and stimulated at the threshold of action potential generation. FIDs were acquired shortly after the stimulation, and simultaneous field potential recordings identified the presence or absence of single evoked action potentials. FIDs acquired when the stimulus did not evoke an action potential were summed as background. The phase of the background-subtracted FID exhibited a systematic change, with a peak phase difference of (-1.2 ± 0.3) × 10(-5) radians occurring at a time corresponding to the timing of the action potential. In addition, we calculated the possible changes in the FID magnitude and phase caused by a simulated action potential using a volume conductor model. The measured phase difference matched the theoretical prediction well in both amplitude and temporal characteristics. This study provides the first evidence for the direct detection of a magnetic field from an evoked action potential using MR.

Early prediction of response to Vorinostat in an orthotopic rat glioma model.

Glioblastoma is the most common primary brain tumor and is uniformly fatal despite aggressive surgical and adjuvant therapy. As survival is short, it is critical to determine the value of therapy early on in treatment. Improved early predictive assessment would allow neuro-oncologists to personalize and adjust or change treatment sooner to maximize the use of efficacious therapy. During carcinogenesis, tumor suppressor genes can be silenced by aberrant histone deacetylation. This epigenetic modification has become an important target for tumor therapy. Suberoylanilide hydroxamic acid (SAHA, Vorinostat, Zolinza) is an orally active, potent inhibitor of histone deacetylase (HDAC) activity. A major shortcoming of the use of HDAC inhibitors in the treatment of patients with brain tumors is the lack of reliable biomarkers to predict and determine response. Histological evaluation may reflect tumor viability following treatment, but is an invasive procedure and impractical for glioblastoma. Another problem is that response to SAHA therapy is associated with tumor redifferentiation and cytostasis rather than tumor size reduction, thus limiting the use of traditional imaging methods. A noninvasive method to assess drug delivery and efficacy is needed. Here, we investigated whether changes in (1)H MRS metabolites could render reliable biomarkers for an early response to SAHA treatment in an orthotopic animal model for glioma. Untreated tumors exhibited significantly elevated alanine and lactate levels and reduced inositol, N-acetylaspartate and creatine levels, typical changes reported in glioblastoma relative to normal brain tissues. The (1)H MRS-detectable metabolites of SAHA-treated tumors were restored to those of normal-like brain tissues. In addition, reduced inositol and N-acetylaspartate were found to be potential biomarkers for mood alteration and depression, which may also be alleviated with SAHA treatment. Our study suggests that (1)H MRS can provide reliable metabolic biomarkers at the earliest stage of SAHA treatment to predict the therapeutic response.

Nigral volumetric and microstructural measures in individuals with scans without evidence of dopaminergic deficit.

Introduction: Striatal dopamine transporter (DAT) imaging using 123I-ioflupane single photon positron emitted computed tomography (SPECT) (DaTScan, GE) identifies 5-20% of newly diagnosed Parkinson's disease (PD) subjects enrolling in clinical studies to have scans without evidence of dopaminergic deficit (SWEDD). These individuals meet diagnostic criteria for PD, but do not clinically progress as expected, and they are not believed to have neurodegenerative Parkinsonism. Inclusion of SWEDD participants in PD biomarker studies or therapeutic trials may therefore cause them to fail. DaTScan can identify SWEDD individuals, but it is expensive and not widely available; an alternative imaging approach is needed. Here, we evaluate the use of neuromelanin-sensitive, iron-sensitive, and diffusion contrasts in substantia nigra pars compacta (SNpc) to differentiate SWEDD from PD individuals. Methods: Neuromelanin-sensitive, iron-sensitive, and diffusion imaging data for SWEDD, PD, and control subjects were downloaded from the Parkinson's progression markers initiative (PPMI) database. SNpc volume, SNpc iron (R 2), and SNpc free water (FW) were measured for each participant. Results: Significantly smaller SNpc volume was seen in PD as compared to SWEDD (P < 10-3) and control (P < 10-3) subjects. SNpc FW was elevated in the PD group relative to controls (P = 0.017). No group difference was observed in SNpc R 2. Conclusion: In conclusion, nigral volume and FW in the SWEDD group were similar to that of controls, while a reduction in nigral volume and increased FW were observed in the PD group relative to SWEDD and control participants. These results suggest that these MRI measures should be explored as a cost-effective alternative to DaTScan for evaluation of the nigrostriatal system.

Subtyping Autism Spectrum Disorder Via Joint Modeling of Clinical and Connectomic Profiles.

Background: Autism spectrum disorder (ASD) is a highly heterogeneous developmental disorder with diverse clinical manifestations. Neuroimaging studies have explored functional connectivity (FC) of ASD through resting-state functional magnetic resonance imaging studies; however, the findings have remained inconsistent, thus reflecting the possibility of multiple subtypes. Identification of the relationship between clinical symptoms and FC measures may help clarify the inconsistencies in earlier findings and advance our understanding of ASD subtypes. Methods: Canonical correlation analysis was performed on 210 ASD subjects from the Autism Brain Imaging Data Exchange to identify significant linear combinations of resting-state connectomic and clinical profiles of ASD. Then, hierarchical clustering defined ASD subtypes based on distinct brain-behavior relationships. Finally, a support vector machine (SVM) classifier was used to verify that subtypes comprised subjects with distinct clinical and connectivity features. Results: Three ASD subtypes were identified. Subtype 1 exhibited increased intra-network FC, increased Intelligence Quotient (IQ) scores, and restricted and repetitive behaviors. Subtype 2 was characterized by decreased whole-brain FC and more severe Autism Diagnostic Interview-Revised and Social Responsiveness Scale symptoms. Subtype 3 demonstrated mixed FC, low IQ scores, as well as social motivation and verbal deficits. To verify subtype assignment, a multi-class SVM using connectomic and clinical profiles yielded an average accuracy of 71.3% and 65.2% respectively for subtype classification, which is significantly higher than chance (33.3%). Conclusion: The present study demonstrates that combining connectomic and behavioral measures is a powerful approach for disease subtyping and suggests that there are ASD subtypes with distinct connectomic and clinical profiles.