BACKGROUND: The purpose of this study was to investigate whether white matter microstructure is altered in patients suffering from systemic lupus erythematosus (SLE), and if so, whether such alterations differed between patients with and without neuropsychiatric symptoms.
METHODS: Structural MRI and diffusion tensor imaging (DTI) were performed in 64 female SLE patients (mean age 36.9 years, range 18.2-52.2 years) and 21 healthy controls (mean age 36.7 years, range 23.3-51.2 years) in conjunction with clinical examination, laboratory tests, cognitive evaluation, and self-assessment questionnaires. The patients were subgrouped according to the American College of Rheumatology Neuropsychiatric Systemic Lupus Erythematosus case definitions into non-neuropsychiatric SLE (nonNPSLE) and neuropsychiatric SLE (NPSLE).
RESULTS: Comparisons between the SLE group and healthy controls showed that the mean fractional anisotropy (FA) was significantly reduced in the right rostral cingulum (p = 0.038), the mid-sagittal corpus callosum (CC) (p = 0.050), and the forceps minor of the CC (p = 0.015). The mean diffusivity (MD) was significantly increased in the left hippocampal cingulum (p = 0.017). No significant differences in MD or FA values were identified between NPSLE and nonNPSLE patients. Disease duration among all SLE patients correlated significantly with reduced FA in the CC (p < 0.05). No correlations were found between DTI parameters and white matter hyperintensities, SLE Disease Activity Index-2000, Systemic Lupus International Collaborating Clinical/ACR Organ Damage Index, or Montgomery Asberg Depression Rate Score Self-report.
CONCLUSIONS: We found alterations of white matter microstructure in SLE patients that were related to disease duration and fatigue. Our results indicate that cerebral involvement in SLE is not isolated to the NPSLE subgroup.
A single-nucleotide polymorphism (rs35705950) in the mucin 5B () gene promoter is associated with pulmonary fibrosis and interstitial features on chest CT but may also have beneficial effects. In non-Hispanic whites in the COPDGene cohort with interstitial features (n=454), the promoter polymorphism was associated with a 61% lower odds of a prospectively reported acute respiratory disease event (P=0.001), a longer time-to-first event (HR=0.57; P=0.006) and 40% fewer events (P=0.016). The promoter polymorphism may have a beneficial effect on the risk of acute respiratory disease events in smokers with interstitial CT features.
BACKGROUND: Previous investigations in adult smokers from the COPDGene Study have shown that early-life respiratory disease is associated with reduced lung function, COPD, and airway thickening. Using 5-year follow-up data, we assessed disease progression in subjects who had experienced early-life respiratory disease. We hypothesized that there are alternative pathways to reaching reduced FEVand that subjects who had childhood pneumonia, childhood asthma, or asthma-COPD overlap (ACO) would have less lung function decline than subjects without these conditions. METHODS: Subjects returning for 5-year follow-up were assessed. Childhood pneumonia was defined by self-reported pneumonia at < 16 years. Childhood asthma was defined as self-reported asthma diagnosed by a health professional at < 16 years. ACO was defined as subjects with COPD who self-reported asthma diagnosed by a health-professional at ≤ 40 years. Smokers with and those without these early-life respiratory diseases were compared on measures of disease progression. RESULTS: Follow-up data from 4,915 subjects were examined, including 407 subjects who had childhood pneumonia, 323 subjects who had childhood asthma, and 242 subjects with ACO. History of childhood asthma or ACO was associated with an increased exacerbation frequency (childhood asthma, P < .001; ACO, P = .006) and odds of severe exacerbations (childhood asthma, OR, 1.41; ACO, OR, 1.42). History of childhood pneumonia was associated with increased exacerbations in subjects with COPD (absolute difference [β], 0.17; P = .04). None of these early-life respiratory diseases were associated with an increased rate of lung function decline or progression on CT scans. CONCLUSIONS: Subjects who had early-life asthma are at increased risk of developing COPD and of having more active disease with more frequent and severe respiratory exacerbations without an increased rate of lung function decline over a 5-year period. TRIAL REGISTRY: ClinicalTrials.gov; No. NCT00608764; https://clinicaltrials.gov.
Characterization of anisotropy via diffusion MRI reveals fiber crossings in a substantial portion of voxels within the white-matter (WM) regions of the human brain. A considerable number of such voxels could exhibit asymmetric features such as bends and junctions. However, widely employed reconstruction methods yield symmetric Orientation Distribution Functions (ODFs) even when the underlying geometry is asymmetric. In this paper, we employ inter-voxel directional filtering approaches through a cone model to reveal more information regarding the cytoarchitectural organization within the voxel. The cone model facilitates a sharpening of the ODFs in some directions while suppressing peaks in other directions, thus yielding an Asymmetric ODF (AODF) field. We also show that a scalar measure of AODF asymmetry can be employed to obtain new contrast within the human brain. The feasibility of the technique is demonstrated on in vivo data obtained from the MGH-USC Human Connectome Project (HCP) and Parkinson's Progression Markers Initiative (PPMI) Project database. Characterizing asymmetry in neural tissue cytoarchitecture could be important for localizing and quantitatively assessing specific neuronal pathways.
Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions in an appropriately chosen basis, where the coefficients are determined using some variation of least-squares. However, such approaches lack any notion of uncertainty, which could be valuable in e.g. group analyses. In this work, we use a probabilistic interpretation of linear least-squares methods to recast popular dMRI models as Bayesian ones. This makes it possible to quantify the uncertainty of any derived quantity. In particular, for quantities that are affine functions of the coefficients, the posterior distribution can be expressed in closed-form. We simulated measurements from single- and double-tensor models where the correct values of several quantities are known, to validate that the theoretically derived quantiles agree with those observed empirically. We included results from residual bootstrap for comparison and found good agreement. The validation employed several different models: Diffusion Tensor Imaging (DTI), Mean Apparent Propagator MRI (MAP-MRI) and Constrained Spherical Deconvolution (CSD). We also used in vivo data to visualize maps of quantitative features and corresponding uncertainties, and to show how our approach can be used in a group analysis to downweight subjects with high uncertainty. In summary, we convert successful linear models for dMRI signal estimation to probabilistic models, capable of accurate uncertainty quantification.
The rate of water exchange across cell membranes is a parameter of biological interest and can be measured by diffusion magnetic resonance imaging (dMRI). In this work, we investigate a stochastic model for the diffusion-and-exchange of water molecules. This model provides a general solution for the temporal evolution of dMRI signal using any type of gradient waveform, thereby generalizing the signal expressions for the Kärger model. Moreover, we also derive a general nth order cumulant expansion of the dMRI signal accounting for water exchange, which has not been explored in earlier studies. Based on this analytical expression, we compute the cumulant expansion for dMRI signals for the special case of single diffusion encoding (SDE) and double diffusion encoding (DDE) sequences. Our results provide a theoretical guideline on optimizing experimental parameters for SDE and DDE sequences, respectively. Moreover, we show that DDE signals are more sensitive to water exchange at short-time scale but provide less attenuation at long-time scale than SDE signals. Our theoretical analysis is also validated using Monte Carlo simulations on synthetic structures.
BACKGROUND: Exposure to ambient air pollution has been associated with lower lung function in adults, but few studies have investigated associations with radiographic lung and airway measures.
METHODS: We ascertained lung volume, mass, density, visual emphysema, airway size, and airway wall area by computed tomography (CT) among 2,545 nonsmoking Framingham CT substudy participants. We examined associations of home distance to major road and PM2.5 (2008 average from a spatiotemporal model using satellite data) with these outcomes using linear and logistic regression models adjusted for age, sex, height, weight, census tract median household value and population density, education, pack-years of smoking, household tobacco exposure, cohort, and date. We tested for differential susceptibility by sex, smoking status (former vs. never), and cohort.
RESULTS: The mean participant age was 60.1 years (standard deviation 11.9 years). Median PM2.5 level was 9.7 µg/m (interquartile range, 1.6). Living <100 m from a major road was associated with a 108 ml (95% CI = 8, 207) higher lung volume compared with ≥400 m away. There was also a log-linear association between proximity to road and higher lung volume. There were no convincing associations of proximity to major road or PM2.5 with the other pulmonary CT measures. In subgroup analyses, road proximity was associated with lower lung density among men and higher odds of emphysema among former smokers.
CONCLUSIONS: Living near a major road was associated with higher average lung volume, but otherwise, we found no association between ambient pollution and radiographic measures of emphysema or airway disease.
INTRODUCTION: Diffusion tensor imaging detects early tissue alterations in Alzheimer's disease and cerebral small vessel disease (SVD). However, the origin of diffusion alterations in SVD is largely unknown.
METHODS: To gain further insight, we applied free water (FW) imaging to patients with genetically defined SVD (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy [CADASIL], n = 57), sporadic SVD (n = 444), and healthy controls (n = 28). We modeled freely diffusing water in the extracellular space (FW) and measures reflecting fiber structure (tissue compartment). We tested associations between these measures and clinical status (processing speed and disability).
RESULTS: Diffusion alterations in SVD were mostly driven by increased FW and less by tissue compartment alterations. Among imaging markers, FW showed the strongest association with clinical status (R up to 34%, P < .0001). Findings were consistent across patients with CADASIL and sporadic SVD.
DISCUSSION: Diffusion alterations and clinical status in SVD are largely determined by extracellular fluid increase rather than alterations of white matter fiber organization.
Despite their widespread use in non-invasive studies of porous materials, conventional MRI methods yield ambiguous results for microscopically heterogeneous materials such as brain tissue. While the forward link between microstructure and MRI observables is well understood, the inverse problem of separating the signal contributions from different microscopic pores is notoriously difficult. Here, we introduce an experimental protocol where heterogeneity is resolved by establishing 6D correlations between the individual values of isotropic diffusivity, diffusion anisotropy, orientation of the diffusion tensor, and relaxation rates of distinct populations. Such procedure renders the acquired signal highly specific to the sample's microstructure, and allows characterization of the underlying pore space without prior assumptions on the number and nature of distinct microscopic environments. The experimental feasibility of the suggested method is demonstrated on a sample designed to mimic the properties of nerve tissue. If matched to the constraints of whole body scanners, this protocol could allow for the unconstrained determination of the different types of tissue that compose the living human brain.
RATIONALE: There are limited data on factors in young adulthood that predict future lung disease. OBJECTIVE: To determine the relationship between respiratory symptoms, loss of lung health, and incident respiratory disease in a population-based study of young adults. METHODS: Prospective data from 2749 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study who completed respiratory symptom questionnaires at baseline and 2 years later and repeated spirometry measurements over 30 years. MEASUREMENTS AND MAIN RESULTS: Cough or phlegm, episodes of bronchitis, wheeze, shortness of breath, and chest illnesses at both baseline and year 2 were the main predictor variables in models assessing decline in forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) from year 5 to year 30, incident obstructive and restrictive lung physiology, and visual emphysema on thoracic CT. After adjustment for covariates including body mass index (BMI), asthma, and smoking, report of any symptom was associated with -2.71 mL/year excess decline in FEV1 (p<0.001) and -2.18 in FVC (P<0.001) as well as greater odds of incident (pre-bronchodilator) obstructive (odds ratio (OR) 1.63, 95% CI 1.24, 2.14) and restrictive (OR 1.40, 95% CI 1.09, 1.80) physiology. Cough-related symptoms (OR 1.56, 95% CI 1.13, 2.16) were associated with greater odds of future emphysema. CONCLUSIONS: Persistent respiratory symptoms in young adults are associated with accelerated decline in lung function, incident obstructive and restrictive physiology, and greater odds of future radiographic emphysema.
BACKGROUND AND PURPOSE: Free water in the posterior substantia nigra obtained from a bi-tensor diffusion MR imaging model has been shown to significantly increase over 1- and 4-year periods in patients with early-stage idiopathic Parkinson disease compared with healthy controls, which suggests that posterior substantia nigra free water may be an idiopathic Parkinson disease progression biomarker. Due to the known temporal posterior-to-anterior substantia nigra degeneration in idiopathic Parkinson disease, we assessed longitudinal changes in free water in both the posterior and anterior substantia nigra in patients with later-stage idiopathic Parkinson disease and age-matched healthy controls for comparison. MATERIALS AND METHODS: Nineteen subjects with idiopathic Parkinson disease and 19 age-matched healthy control subjects were assessed on the same 3T MR imaging scanner at baseline and after approximately 3 years. RESULTS: Baseline mean idiopathic Parkinson disease duration was 7.1 years. Both anterior and posterior substantia nigra free water showed significant intergroup differences at baseline (< .001 and= .014, respectively, idiopathic Parkinson disease versus healthy controls); however, only anterior substantia nigra free water showed significant longitudinal group × time interaction increases (= .021, idiopathic Parkinson disease versus healthy controls). There were no significant longitudinal group × time interaction differences found for conventional diffusion tensor imaging or free water-corrected DTI assessments in either the anterior or posterior substantia nigra. CONCLUSIONS: Results from this study provide further evidence supporting substantia nigra free water as a promising disease-progression biomarker in idiopathic Parkinson disease that may help to identify disease-modifying therapies if used in future clinical trials. Our novel finding of longitudinal increases in anterior but not posterior substantia nigra free water is potentially a result of the much longer disease duration of our cohort compared with previously studied cohorts and the known posterior-to-anterior substantia nigra degeneration that occurs over time in idiopathic Parkinson disease.
This work presents a suprathreshold fiber cluster (STFC) method that leverages the whole brain fiber geometry to enhance statistical group difference analyses. The proposed method consists of 1) a well-established study-specific data-driven tractography parcellation to obtain white matter tract parcels and 2) a newly proposed nonparametric, permutation-test-based STFC method to identify significant differences between study populations. The basic idea of our method is that a white matter parcel's neighborhood (nearby parcels with similar white matter anatomy) can support the parcel's statistical significance when correcting for multiple comparisons. We propose an adaptive parcel neighborhood strategy to allow suprathreshold fiber cluster formation that is robust to anatomically varying inter-parcel distances. The method is demonstrated by application to a multi-shell diffusion MRI dataset from 59 individuals, including 30 attention deficit hyperactivity disorder patients and 29 healthy controls. Evaluations are conducted using both synthetic and in-vivo data. The results indicate that the STFC method gives greater sensitivity in finding group differences in white matter tract parcels compared to several traditional multiple comparison correction methods.
Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases.
Purpose To assess the diagnostic test accuracy and sources of heterogeneity for the discriminative potential of diffusion kurtosis imaging (DKI) to differentiate low-grade glioma (LGG) (World Health Organization [WHO] grade II) from high-grade glioma (HGG) (WHO grade III or IV). Materials and Methods The Cochrane Library, Embase, Medline, and the Web of Science Core Collection were systematically searched by two librarians. Retrieved hits were screened for inclusion and were evaluated with the revised tool for quality assessment for diagnostic accuracy studies (commonly known as QUADAS-2) by two researchers. Statistical analysis comprised a random-effects model with associated heterogeneity analysis for mean differences in mean kurtosis (MK) in patients with LGG or HGG. A bivariate restricted maximum likelihood estimation method was used to describe the summary receiver operating characteristics curve and bivariate meta-regression. Results Ten studies involving 430 patients were included. The mean difference in MK between LGG and HGG was 0.17 (95% confidence interval [CI]: 0.11, 0.22) with a z score equal to 5.86 (P < .001). The statistical heterogeneity was explained by glioma subtype, echo time, and the proportion of recurrent glioma versus primary glioma. The pooled area under the curve was 0.94 for discrimination of HGG from LGG, with 0.85 (95% CI: 0.74, 0.92) sensitivity and 0.92 (95% CI: 0.81, 0.96) specificity. Heterogeneity was driven by neuropathologic subtype and DKI technique. Conclusion MK shows high diagnostic accuracy in the discrimination of LGG from HGG.RSNA, 2017 Online supplemental material is available for this article.
BACKGROUND AND PURPOSE: Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients' white matter tracts, but these maps suffer from echo-planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image-registration-based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data.
METHODS: Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts.
RESULTS: Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2-weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres.
CONCLUSIONS: Quantitative results of mean tract distortions on the order of 1-2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings.
OBJECTIVES: Bipolar disorder (BP) is a debilitating psychiatric disease that is not well understood. Previous diffusion magnetic resonance imaging (dMRI) studies of BP patients found prominent microstructural white matter (WM) abnormalities of reduced fractional anisotropy (FA). Because FA is a nonspecific measure, relating these abnormalities to a specific pathology is difficult. Here, dMRI specificity was increased by free water (FW) imaging, which allows identification of changes in extracellular space (FW) from neuronal tissue (fractional anisotropy of tissue [FA-t]). Previous studies identified increased FW in early schizophrenia (SZ) stages which was replaced by widespread decreased FA-t in chronic stages. This is the first analysis utilizing this method to compare BP patients and controls.
METHODS: 3 Tesla diffusion weighted imaging (3T DWI) data were acquired for 17 chronic BP and 28 healthy control (HC) participants at Oxford University. Tract-based spatial statistics was utilized to generate a WM skeleton. FW imaging deconstructed the diffusion signal into extracellular FW and tissue FA-t maps. These maps were projected onto the skeleton and FA, FA-t, and FW were compared between groups.
RESULTS: We found significantly lower FA in BP patients when compared to HC in areas that overlapped with extensive FW increases. There were no FA-t differences.
CONCLUSIONS: Our study suggests that chronic BP shows similar WM changes to early SZ, suggesting that extracellular FW increases could be a transient indication of recent psychotic episodes. Since FW increase in SZ has been suggested to be related to neuroinflammation, we theorize that neuroinflammation might be a shared pathology between chronic BP and early SZ.
INTRODUCTION: Previous studies have reported abnormalities in the ventral posterior cingulate cortex (vPCC) and middle temporal gyrus (MTG) in schizophrenia patients. However, it remains unclear whether the white matter tracts connecting these structures are impaired in schizophrenia. Our study investigated the integrity of these white matter tracts (vPCC-MTG tract) and their asymmetry (left versus right side) in patients with recent onset schizophrenia.
METHOD: Forty-seven patients and 24 age-and sex-matched healthy controls were enrolled in this study. We extracted left and right vPCC-MTG tract on each side from T1W and diffusion MRI (dMRI) at 3T. We then calculated the asymmetry index of diffusion measures of vPCC-MTG tracts as well as volume and thickness of vPCC and MTG using the formula: 2×(right-left)/(right+left). We compared asymmetry indices between patients and controls and evaluated their correlations with the severity of psychiatric symptoms and cognition in patients using the Positive and Negative Syndrome Scale (PANSS), video-based social cognition scale (VISC) and the Wechsler Adult Intelligence Scale (WAIS-III).
RESULTS: Asymmetry of fractional anisotropy (FA) and radial diffusivity (RD) in the vPCC-MTG tract, while present in healthy controls, was not evident in schizophrenia patients. Also, we observed that patients, not healthy controls, had a significant FA decrease and RD increase in the left vPCC-MTG tract. There was no significant association between the asymmetry indices of dMRI measures and IQ, VISC, or PANSS scores in schizophrenia.
CONCLUSION: Disruption of asymmetry of the vPCC-MTG tract in schizophrenia may contribute to the pathophysiology of schizophrenia.
We examined whether abnormal volumes of several brain regions as well as their mutual associations that have been observed in patients with schizophrenia, are also present in individuals at clinical high-risk (CHR) for developing psychosis. 3T magnetic resonance imaging was acquired in 19 CHR and 20 age- and handedness-matched controls. Volumes were measured for the body and temporal horns of the lateral ventricles, hippocampus and amygdala as well as total brain, cortical gray matter, white matter, and subcortical gray matter volumes. Relationships between volumes as well as correlations between volumes and cognitive and clinical measures were explored. Ratios of lateral ventricular volume to total brain volume and temporal horn volume to total brain volume were calculated. Volumetric abnormalities were lateralized to the left hemisphere. Volumes of the left temporal horn, and marginally, of the body of the left lateral ventricle were larger, while left amygdala but not hippocampal volume was significantly smaller in CHR participants compared to controls. Total brain volume was also significantly smaller and the ratio of the temporal horn/total brain volume was significantly higher in CHR than in controls. White matter volume correlated positively with higher verbal fluency score while temporal horn volume correlated positively with a greater number of perseverative errors. Together with the finding of larger temporal horns and smaller amygdala volumes in the left hemisphere, these results indicate that the ratio of temporal horns volume to brain volume is abnormal in CHR compared to controls. These abnormalities present in CHR individuals may constitute the biological basis for at least some of the CHR syndrome.
Thalamic atrophy has been associated with exposure to repetitive head impacts (RHI) in professional fighters. The aim of this study is to investigate whether or not age at first exposure (AFE) to RHI is associated with thalamic volume in symptomatic former National Football League (NFL) players at risk for chronic traumatic encephalopathy (CTE). Eighty-six symptomatic former NFL players (mean age = 54.9 ± 7.9 years) were included. T1-weighted data were acquired on a 3T magnetic resonance imager, and thalamic volumes were derived using FreeSurfer. Mood and behavior, psychomotor speed, and visual and verbal memory were assessed. The association between thalamic volume and AFE to playing football and to number of years playing was calculated. Decreased thalamic volume was associated with more years of play (left: p = 0.03; right: p = 0.03). Younger AFE was associated with decreased right thalamic volume (p = 0.014). This association remained significant after adjusting for total years of play. Decreased left thalamic volume was associated with worse visual memory (p = 0.014), whereas increased right thalamic volume was associated with fewer mood and behavior symptoms (p = 0.003). In our sample of symptomatic former NFL players at risk for CTE, total years of play and AFE were associated with decreased thalamic volume. The effect of AFE on right thalamic volume was almost twice as strong as the effect of total years of play. Our findings confirm previous reports of an association between thalamic volume and exposure to RHI. They suggest further that younger AFE may result in smaller thalamic volume later in life.
Neuroimaging studies demonstrate gray matter (GM) macrostructural abnormalities in patients with schizophrenia (SCZ). While ex-vivo and genetic studies suggest cellular pathology associated with abnormal neurodevelopmental processes in SCZ, few in-vivo measures have been proposed to target microstructural GM organization. Here, we use diffusion heterogeneity- to study GM microstructure in SCZ. Structural and diffusion magnetic resonance imaging (MRI) were acquired on a 3 Tesla scanner in 46 patients with SCZ and 37 matched healthy controls (HC). After correction for free water, diffusion heterogeneity as well as commonly used diffusion measures FA and MD and volume were calculated for the four cortical lobes on each hemisphere, and compared between groups. Patients with early course SCZ exhibited higher diffusion heterogeneity in the GM of the frontal lobes compared to controls. Diffusion heterogeneity of the frontal lobe showed excellent discrimination between patients and HC, while none of the commonly used diffusion measures such as FA or MD did. Higher diffusion heterogeneity in the frontal lobes in early SCZ may be due to abnormal brain maturation (migration, pruning) before and during adolescence and early adulthood. Further studies are needed to investigate the role of heterogeneity as potential biomarker for SCZ risk.