Neuroimaging alterations and relapse in early-stage psychosis.

BACKGROUND: Recent reports have indicated that symptom exacerbation after a period of improvement, referred to as relapse, in early-stage psychosis could result in brain changes and poor disease outcomes. We hypothesized that substantial neuroimaging alterations may exist among patients who experience relapse in early-stage psychosis. METHODS: We studied patients with psychosis within 2 years after the first psychotic event and healthy controls. We divided patients into 2 groups, namely those who did not experience relapse between disease onset and the magnetic resonance imaging (MRI) scan (no-relapse group) and those who did experience relapse between these 2 timings (relapse group). We analyzed 3003 functional connectivity estimates between 78 regions of interest (ROIs) derived from resting-state functional MRI data by adjusting for demographic and clinical confounding factors. RESULTS: We studied 85 patients, incuding 54 in the relapse group and 31 in the no-relapse group, along with 94 healthy controls. We observed significant differences in 47 functional connectivity estimates between the relapse and control groups after multiple comparison corrections, whereas no differences were found between the no-relapse and control groups. Most of these pathological signatures (64%) involved the thalamus. The Jonckheere-Terpstra test indicated that all 47 functional connectivity changes had a significant cross-group progression from controls to patients in the no-relapse group to patients in the relapse group. LIMITATIONS: Longitudinal studies are needed to further validate the involvement and pathological importance of the thalamus in relapse. CONCLUSION: We observed pathological differences in neuronal connectivity associated with relapse in early-stage psychosis, which are more specifically associated with the thalamus. Our study implies the importance of considering neurobiological mechanisms associated with relapse in the trajectory of psychotic disorders.

Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors.

Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheimer's disease outcomes. In this study, we propose an ℓ1 -type regularization for predictors that follow a hierarchical tree structure. Considering a tree as a directed acyclic graph, we interpret the model parameters from a path analysis perspective. Under this concept, the proposed penalty regulates the total effect of each predictor on the outcome. With regularity conditions, it is shown that under the proposed regularization, the estimator of the model coefficient is consistent in ℓ2 -norm and the model selection is also consistent. When applied to a brain sMRI dataset acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the proposed approach identifies brain regions where atrophy in these regions demonstrates the declination in memory. With regularization on the total effects, the findings suggest that the impact of atrophy on memory deficits is localized from small brain regions, but at various levels of brain segmentation. Data used in preparation of this paper were obtained from the ADNI database.

Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup.

Multi-institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure-based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI-rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure-based analysis showed widespread DTI abnormalities in FEP and rs-fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof-of-concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub-groups.

Visualising the topography of the acoustic radiation in clinical diffusion tensor imaging scans.

PURPOSE: It has long been thought that the acoustic radiation (AR) white matter fibre tract from the medial geniculate body of the thalamus to the Heschl's gyrus cannot be reconstructed via single-fibre analysis of clinical diffusion tensor imaging (DTI) scans. A recently developed single-fibre probabilistic method suggests otherwise. The method uses dynamic programming (DP) to compute the most probable paths between two regions of interest. This study aims to observe the ability of single-fibre probabilistic analysis via DP to visualise the AR in clinical DTI scans from legacy pilot cohorts of subjects with normal hearing (NH) and profound hearing loss (HL). METHODS: Single-fibre probabilistic analysis via DP was applied to reconstruct 3D models of the AR in the two cohorts. DTI and T1 data at 1.5 T for subjects with NH (n = 11) and HL (n = 5), as well as 3 T for NH (n = 1) and HL (n = 1), were used. RESULTS: The topographical features of AR previously observed in post-mortem and multi-fibre analyses can be visualised in DTI scans of 16 subjects and 2 atlases with a success rate of 100%. Relative to MNI coordinates, there was no significant difference in the varifold distances between the topography of the tracts in the 1.5 T cohort. CONCLUSION: The AR can be visualised in clinical 1.5 T and 3 T DTI scans using single-fibre probabilistic analysis via DP, hence, the potential for DP to visualise the AR in medical and pre-surgical applications in pathologies such as vestibular schwannoma, multiple sclerosis, thalamic tumours and stroke as well as hearing loss.

White Matter Hyperintensities Contribute to Language Deficits in Primary Progressive Aphasia.

OBJECTIVE: To determine the contribution of white matter hyperintensities (WMH) to language deficits while accounting for cortical atrophy in individuals with primary progressive aphasia (PPA). METHOD: Forty-three individuals with PPA completed neuropsychological assessments of nonverbal semantics, naming, and sentence repetition plus T2-weighted and fluid-attenuated inversion recovery scans. Using three visual scales, we rated WMH and cerebral ventricle size for both scan types. We used Spearman correlations to evaluate associations between the scales and scans. To test whether visual ratings-particularly of WMH-are associated with language, we compared a base model (including gray matter component scores obtained via principal component analysis, age, and days between assessment and MRI as independent variables) with full models (ie, the base model plus visual ratings) for each language variable. RESULTS: Visual ratings were significantly associated within and between scans and were significantly correlated with age but not with other vascular risk factors. Only the T2 scan ratings were associated with language abilities. Specifically, controlling for other variables, poorer naming was significantly related to larger ventricles (P = 0.033) and greater global (P = 0.033) and periventricular (P = 0.049) WMH. High global WMH (P = 0.034) were also correlated with worse sentence repetition skills. CONCLUSION: Visual ratings of global brain health were associated with language deficits in PPA independent of cortical atrophy and age. While WMH are not unique to PPA, measuring WMH in conjunction with cortical atrophy may elucidate more accurate brain structure-behavior relationships in PPA than cortical atrophy measures alone.

An Efficient Bedside Measure Yields Prognostic Implications for Language Recovery in Acute Stroke Patients.

BACKGROUND: It is estimated that ∼30% of stroke survivors have aphasia, a language disorder resulting from damage to left-hemisphere language networks. In acute care settings, efficient identification of aphasia is critical, but there is a paucity of efficient bedside assessments. OBJECTIVE: To determine whether objective measures on a picture description task administered within 48 hours post stroke (a) predict language recovery, (b) estimate left-hemisphere lesion volume and location, and (c) correlate with other bedside language assessments. METHOD: Behavioral data were scored at acute and chronic time points. Neuroimaging data were used to determine associations between the picture description task, other language assessments, and lesion volume and location. RESULTS: Acute content units, age, and total lesion volume predicted communication recovery; F3,18 = 3.98, P = 0.024; r = 0.40. Significant correlations were found between the picture description task and lesion volume and location. Picture description outcomes were also associated with other clinical language assessments. DISCUSSION: This picture description task quickly predicted the language performance (communication recovery and outcome) for patients who suffered a left-hemisphere stroke. Picture description task measures correlated with damage in the left hemisphere and with other, more time-consuming and cumbersome language assessments that are typically administered acutely at bedside. CONCLUSION: The predictive value of this picture description task and correlations with existing language assessments substantiate the clinical importance of a reliable yet rapid bedside measure for acute stroke patients that can be administered by a variety of health care professionals.

Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility.

Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ±â€¯0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ±â€¯0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ±â€¯0.08 to manual labels and 0.89 ±â€¯0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

ASL-MRICloud: An online tool for the processing of ASL MRI data.

Arterial spin labeling (ASL) MRI is increasingly used in research and clinical settings. The purpose of this work is to develop a cloud-based tool for ASL data processing, referred to as ASL-MRICloud, which may be useful to the MRI community. In contrast to existing ASL toolboxes, which are based on software installation on the user's local computer, ASL-MRICloud uses a web browser for data upload and results download, and the computation is performed on the remote server. As such, this tool is independent of the user's operating system, software version, and CPU speed. The ASL-MRICloud tool was implemented to be compatible with data acquired by scanners from all major MRI manufacturers, is capable of processing several common forms of ASL, including pseudo-continuous ASL and pulsed ASL, and can process single-delay and multi-delay ASL data. The outputs of ASL-MRICloud include absolute and relative values of cerebral blood flow, arterial transit time, voxel-wise masks indicating regions with potential hyper-perfusion and hypo-perfusion, and an image quality index. The ASL tool is also integrated with a T1 -based brain segmentation and normalization tool in MRICloud to allow generation of parametric maps in standard brain space as well as region-of-interest values. The tool was tested on a large data set containing 309 ASL scans as well as on publicly available ASL data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

Evidence for a subcortical origin of mirror movements after stroke: a longitudinal study.

Following a stroke, mirror movements are unintended movements that appear in the non-paretic hand when the paretic hand voluntarily moves. Mirror movements have previously been linked to overactivation of sensorimotor areas in the non-lesioned hemisphere. In this study, we hypothesized that mirror movements might instead have a subcortical origin, and are the by-product of subcortical motor pathways upregulating their contributions to the paretic hand. To test this idea, we first characterized the time course of mirroring in 53 first-time stroke patients, and compared it to the time course of activities in sensorimotor areas of the lesioned and non-lesioned hemispheres (measured using functional MRI). Mirroring in the non-paretic hand was exaggerated early after stroke (Week 2), but progressively diminished over the year with a time course that parallelled individuation deficits in the paretic hand. We found no evidence of cortical overactivation that could explain the time course changes in behaviour, contrary to the cortical model of mirroring. Consistent with a subcortical origin of mirroring, we predicted that subcortical contributions should broadly recruit fingers in the non-paretic hand, reflecting the limited capacity of subcortical pathways in providing individuated finger control. We therefore characterized finger recruitment patterns in the non-paretic hand during mirroring. During mirroring, non-paretic fingers were broadly recruited, with mirrored forces in homologous fingers being only slightly larger (1.76 times) than those in non-homologous fingers. Throughout recovery, the pattern of finger recruitment during mirroring for patients looked like a scaled version of the corresponding control mirroring pattern, suggesting that the system that is responsible for mirroring in controls is upregulated after stroke. Together, our results suggest that post-stroke mirror movements in the non-paretic hand, like enslaved movements in the paretic hand, are caused by the upregulation of a bilaterally organized subcortical system.

Separable systems for recovery of finger strength and control after stroke.

Impaired hand function after stroke is a major cause of long-term disability. We developed a novel paradigm that quantifies two critical aspects of hand function, strength, and independent control of fingers (individuation), and also removes any obligatory dependence between them. Hand recovery was tracked in 54 patients with hemiparesis over the first year after stroke. Most recovery of strength and individuation occurred within the first 3 mo. A novel time-invariant recovery function was identified: recovery of strength and individuation were tightly correlated up to a strength level of ~60% of estimated premorbid strength; beyond this threshold, strength improvement was not accompanied by further improvement in individuation. Any additional improvement in individuation was attributable instead to a second process that superimposed on the recovery function. We conclude that two separate systems are responsible for poststroke hand recovery: one contributes almost all of strength and some individuation; the other contributes additional individuation.NEW & NOTEWORTHY We tracked recovery of the hand over a 1-yr period after stroke in a large cohort of patients, using a novel paradigm that enabled independent measurement of finger strength and control. Most recovery of strength and control occurs in the first 3 mo after stroke. We found that two separable systems are responsible for motor recovery of hand: one contributes strength and some dexterity, whereas a second contributes additional dexterity.

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc.

Structural signature of classical versus late-onset friedreich's ataxia by Multimodality brain MRI.

INTRODUCTION: Friedreich's ataxia (FRDA) is the most common autosomal-recessive ataxia worldwide. It is characterized by early onset, sensory abnormalities, and slowly progressive ataxia. However, some individuals manifest the disease after the age of 25 years and are classified as late-onset FRDA (LOFA). Therefore, we propose a transversal multimodal MRI-based study to investigate which anatomical substrates are involved in classical (cFRDA) and LOFA. METHODS: We enrolled 36 patients (13 with LOFA) and 29 healthy controls. All subjects underwent magnetic resonance imaging in a 3 T device; three-dimensional high-resolution T1-weighted images and diffusion tensor images were used to assess gray and white matter, respectively. We used T1 multiatlas approach to assess deep gray matter and cortical thickness measures to evaluate cerebral cortex and DTI multiatlas approach to assess white matter. All analyses were corrected for multiple comparisons. RESULTS: Group comparison showed that both groups presented gray matter atrophy mostly in the motor cortex. Regarding white matter, we found abnormalities in the cerebellar peduncles, pyramidal tracts, midbrain, pons, and medulla oblongata for both groups, but the microstructural abnormalities in the cFRDA group were more widespread. In addition, we found that the corticospinal tract presented more severe microstructural damage in the LOFA group. Finally, the midbrain volume of the cFRDA, but not of the LOFA group, correlated with disease duration (R = -0.552, P = 0.012) and severity (R = -0.783, P < 0.001). CONCLUSION: The cFRDA and LOFA groups have similar, but not identical neuroimaging damage pattern. These structural differences might help to explain the phenotypic variability observed in FRDA. Hum Brain Mapp 38:4157-4168, 2017. © 2017 Wiley Periodicals, Inc.

Critical role of the right uncinate fasciculus in emotional empathy.

OBJECTIVE: Common neurological diseases or injuries that can affect the right hemisphere, including stroke, traumatic brain injury, and frontotemporal dementia, disrupt emotional empathy-the ability to share in and make inferences about how other people feel. This impairment negatively impacts social interactions and relationships. Accumulating evidence indicates that emotional empathy depends on coordinated functions of orbitofrontal cortex, anterior insula, anterior cingulate, temporal pole, and amygdala, but few studies have investigated effects of lesions to white matter tracts that connect these structures. We tested the hypothesis that percentage damage to specific white matter tracts connecting these gray matter structures predicts error rate in an emotional empathy task after acute right hemisphere ischemic stroke. METHODS: We used multivariate linear regression with percentage damage to 8 white matter tracts, age, and education as independent variables and error rate on emotional empathy as the dependent variable to test a predictive model of emotional empathy in 30 patients with acute ischemic right hemisphere stroke. RESULTS: Percentage damage to 8 white matter tracts along with age and education predicted the error rate in emotional empathy, but only percentage damage to the uncinate fasciculus was independently associated with error rate. Participants with right uncinate fasciculus lesions were significantly more impaired than right hemisphere stroke patients without uncinate fasciculus lesions in the emotional empathy task. INTERPRETATION: The right uncinate fasciculus plays an important role in the emotional empathy network. Patients with lesions in this network should be evaluated for empathy, so that deficits can be addressed.

White matter tracts critical for recognition of sarcasm.

Failure to recognize sarcasm can lead to important miscommunications. Few previous studies have identified brain lesions associated with impaired recognition of sarcasm. We tested the hypothesis that percent damage to specific white matter tracts, age, and education together predict accuracy in sarcasm recognition. Using multivariable linear regression, with age, education, and percent damage to each of eight white matter tracts as independent variables, and percent accuracy on sarcasm recognition as the dependent variable, we developed a model for predicting sarcasm recognition. Percent damage to the sagittal stratum had the greatest weight and was the only independent predictor of sarcasm recognition.

Evaluation of group-specific, whole-brain atlas generation using Volume-based Template Estimation (VTE): application to normal and Alzheimer's populations.

MRI-based human brain atlases, which serve as a common coordinate system for image analysis, play an increasingly important role in our understanding of brain anatomy, image registration, and segmentation. Study-specific brain atlases are often obtained from one of the subjects in a study or by averaging the images of all participants after linear or non-linear registration. The latter approach has the advantage of providing an unbiased anatomical representation of the study population. But, the image contrast is influenced by both inherent MR contrasts and residual anatomical variability after the registration; in addition, the topology of the brain structures cannot reliably be preserved. In this study, we demonstrated a population-based template-creation approach, which is based on Bayesian template estimation on a diffeomorphic random orbit model. This approach attempts to define a population-representative template without the cross-subject intensity averaging; thus, the topology of the brain structures is preserved. It has been tested for segmented brain structures, such as the hippocampus, but its validity on whole-brain MR images has not been examined. This paper validates and evaluates this atlas generation approach, i.e., Volume-based Template Estimation (VTE). Using datasets from normal subjects and Alzheimer's patients, quantitative measurements of sub-cortical structural volumes, metric distance, displacement vector, and Jacobian were examined to validate the group-averaged shape features of the VTE. In addition to the volume-based quantitative analysis, the preserved brain topology of the VTE allows surface-based analysis within the same atlas framework. This property was demonstrated by analyzing the registration accuracy of the pre- and post-central gyri. The proposed method achieved registration accuracy within 1mm for these population-preserved cortical structures in an elderly population.

Tools for multiple granularity analysis of brain MRI data for individualized image analysis.

Voxel-based analysis is widely used for quantitative analysis of brain MRI. While this type of analysis provides the highest granularity level of spatial information (i.e., each voxel), the sheer number of voxels and noisy information from each voxel often lead to low sensitivity for detection of abnormalities. To ameliorate this issue, granularity reduction is commonly performed by applying isotropic spatial filtering. This study proposes a systematic reduction of the spatial information using ontology-based hierarchical structural relationships. The 254 brain structures were first defined in multiple (n=29) geriatric atlases. The multiple atlases were then applied to T1-weighted MR images of each subject's data for automated brain parcellation and five levels of ontological relationships were established, which further reduced the spatial dimension to as few as 11 structures. At each ontology level, the amount of atrophy was evaluated, providing a unique view of low-granularity analysis. This reduction of spatial information allowed us to investigate the anatomical features of each patient, demonstrated in an Alzheimer's disease group.

Atlas-based neuroinformatics via MRI: harnessing information from past clinical cases and quantitative image analysis for patient care.

With the ever-increasing amount of anatomical information radiologists have to evaluate for routine diagnoses, computational support that facilitates more efficient education and clinical decision making is highly desired. Despite the rapid progress of image analysis technologies for magnetic resonance imaging of the human brain, these methods have not been widely adopted for clinical diagnoses. To bring computational support into the clinical arena, we need to understand the decision-making process employed by well-trained clinicians and develop tools to simulate that process. In this review, we discuss the potential of atlas-based clinical neuroinformatics, which consists of annotated databases of anatomical measurements grouped according to their morphometric phenotypes and coupled with the clinical informatics upon which their diagnostic groupings are based. As these are indexed via parametric representations, we can use image retrieval tools to search for phenotypes along with their clinical metadata. The review covers the current technology, preliminary data, and future directions of this field.

Mary has a little chair: Eliciting noun-modifier phrases in individuals with acute post-stroke aphasia.

Background: Aphasia assessment primarily examines an individual's syntax, nouns, and verbs. However, modifiers, such as adjectives and number words, and bound morphemes can be the subject of considerable difficulty for individuals with aphasia. The Morphosyntactic Generation (MorGen) targets nouns, modifiers, and bound inflectional morphemes in two-word phrases among people with aphasia. Aims: The purpose of this work is to provide the first report of the MorGen in hyperacute-acute aphasia. In doing so, we aim to (1) examine the MorGen's concurrent validity with common assessments of aphasia; (2) describe performance in modifiers by people with acute aphasia; and (3) associate MorGen performance with extent of lesioned vascular territories in acute stroke. Methods & Procedures: 62 adult English speakers within the first 14 days of left hemisphere ischemic stroke and 61 healthy control participants completed the MorGen. In addition to receiving the MorGen, participants with stroke received the Western Aphasia Battery (WAB), Boston Naming Test, and Hopkins Action Naming Assessment. Clinical MRIs were analyzed for the extent of lesion in the vascular territory of the left anterior, medial, and posterior cerebral artery, as well as the left posterior choroidal and thalamoperforator arteries. Outcomes & Results: Aim 1: Performance on the MorGen demonstrated consistently high, significant correlations with that on the WAB, Boston Naming Test, and Hopkins Action Naming Assessment. Aim 2: Individuals who had a stroke but were within functional limits (WFL) on the WAB performed significantly worse than healthy controls on the MorGen, driven by differences in adjective performance. When controlling for aphasia severity, those with fluent aphasia performed significantly better in their production of nouns, plurals, number, size, and color than those who had non-fluent aphasia, but both groups were similarly inclined to omit genitive marking. Aim 3: Lesions in the territory of the temporal branch of the posterior cerebral artery were associated with poorer performance in nouns, size, and color. Lesions in the territory of the anterior cerebral artery were associated with poorer performance in numbers. Conclusions: This work highlights the value of the MorGen as a tool for post-stroke language evaluation that complements the skills captured in more widely-used assessments such as the WAB and BNT.