Histoplasty Modification of the Tumor Microenvironment in a Murine Preclinical Model of Breast Cancer.

PURPOSE: To develop a noninvasive therapeutic approach able to alter the biophysical organization and physiology of the extracellular matrix (ECM) in breast cancer. MATERIALS AND METHODS: In a 4T1 murine model of breast cancer, histoplasty treatment with a proprietary 700-kHz multielement therapy transducer using a coaxially aligned ultrasound (US) imaging probe was used to target the center of an ex vivo tumor and deliver subablative acoustic energy. Tumor collagen morphology was qualitatively evaluated before and after histoplasty with second harmonic generation. Separately, mice bearing bilateral 4T1 tumors (n = 4; total tumors = 8) were intravenously injected with liposomal doxorubicin. The right flank tumor was histoplasty-treated, and tumors were fluorescently imaged to detect doxorubicin uptake after histoplasty treatment. Next, 4T1 tumor-bearing mice were randomized into 2 treatment groups (sham vs histoplasty, n = 3 per group). Forty-eight hours after sham/histoplasty treatment, tumors were harvested and analyzed using flow cytometry. RESULTS: Histoplasty significantly increased (P = .002) liposomal doxorubicin diffusion into 4T1 tumors compared with untreated tumors (2.12- vs 1.66-fold increase over control). Flow cytometry on histoplasty-treated tumors (n = 3) demonstrated a significant increase in tumor macrophage frequency (42% of CD45 vs 33%; P = .022) and a significant decrease in myeloid-derived suppressive cell frequency (7.1% of CD45 vs 10.3%; P = .044). Histoplasty-treated tumors demonstrated increased CD8+ (5.1% of CD45 vs 3.1%; P = .117) and CD4+ (14.1% of CD45 vs 11.8%; P = .075) T-cell frequency. CONCLUSIONS: Histoplasty is a nonablative focused US approach to noninvasively modify the tumor ECM, increase chemotherapeutic uptake, and alter the tumor immune microenvironment.

Workflow interruptions in an era of instant messaging: A detailed analysis.

INTRODUCTION: The complex practice environment and responsibilities incumbent on diagnostic radiologists creates a workflow susceptible to disruption. While interruptions have been shown to contribute to medical errors in the healthcare delivery environment, the exact impact on highly subspecialized services such as diagnostic radiology is less certain. One potential source of workflow disruption is the use of a departmental instant messaging system (Webex), to facilitate communications between radiology faculty, residents, fellows, and technologists. A retrospective review was conducted to quantify the frequency of interruption experienced by our neuroradiology fellows. MATERIALS AND METHODS: Data logs were gathered comprising all instant messages sent and received within the designated group chats from July 5-December 31, 2021, during weekday shifts staffed by neuroradiology fellows. Interruptions per shift were calculated based on month, week, and day of the week. RESULTS: 14,424 messages were sent across 289 total shifts. The 6 fellows assigned to the main neuroradiology reading room sent 3258 messages and received 10,260 messages from technologists and other staff. There was an average of 50 interruptions per shift when examined by month (range 48-53), and 52 interruptions per shift when examined by day of the week (range 40-60). CONCLUSION: Neuroradiology fellows experience frequent interruptions from the departmental instant messaging system. These disruptions, when considered in conjunction with other non-interpretative tasks, may have negative implications for workflow efficiency, requiring iterative process improvements when incorporating new technology into the practice environment of diagnostic radiology.

Multimodal Neuroimaging of the Effect of Serotonergic Psychedelics on the Brain.

The neurobiological mechanisms underpinning psychiatric disorders such as treatment-resistant major depression, post-traumatic stress disorder, and substance use disorders, remain unknown. Psychedelic compounds, such as psilocybin, lysergic acid diethylamide, and N,N-dimethyltryptamine, have emerged as potential therapies for these disorders because of their hypothesized ability to induce neuroplastic effects and alter functional networks in the brain. Yet, the mechanisms underpinning the neurobiological treatment response remain obscure. Quantitative neuroimaging is uniquely positioned to provide insight into the neurobiological mechanisms of these emerging therapies and quantify the patient treatment response. This review aims to synthesize our current state-of-the-art understanding of the functional changes occurring in the brain following psilocybin, lysergic acid diethylamide, or N,N-dimethyltryptamine administration in human participants with fMRI and PET. We further aim to disseminate our understanding of psychedelic compounds as they relate to neuroimaging with the goal of improved diagnostics and treatment of neuropsychiatric illness.

Quantitative diffusion imaging and genotype-by-sex interactions in a rat model of Alexander disease.

PURPOSE: The clinical diagnosis and classification of Alexander disease (AxD) relies in part on qualitative neuroimaging biomarkers; however, these biomarkers fail to distinguish and discriminate different subtypes of AxD, especially in the presence of overlap in clinical symptoms. To address this gap in knowledge, we applied neurite orientation dispersion and density imaging (NODDI) to an innovative CRISPR-Cas9 rat genetic model of AxD to gain quantitative insights into the neural substrates and brain microstructural changes seen in AxD and to potentially identify novel quantitative NODDI biomarkers of AxD. METHODS: Multi-shell DWI of age- and sex-matched AxD and wild-type Sprague Dawley rats (n = 6 per sex per genotype) was performed and DTI and NODDI measures calculated. A 3 × 2 × 2 analysis of variance model was used to determine the effect of genotype, biological sex, and laterality on quantitative measures of DTI and NODDI across regions of interest implicated in AxD. RESULTS: There is a significant effect of genotype in the amygdala, hippocampus, neocortex, and thalamus in measures of both DTI and NODDI brain microstructure. A genotype by biological sex interaction was identified in DTI and NODDI measures in the corpus callosum, hippocampus, and neocortex. CONCLUSION: We present the first application of NODDI to the study of AxD using a rat genetic model of AxD. Our analysis identifies alterations in NODDI and DTI measures to large white matter tracts and subcortical gray nuclei. We further identified genotype by sex interactions, suggesting a possible role for biological sex in the neuropathogenesis of AxD.

Quantifying changes in local basal ganglia structural connectivity in the 6-hydroxydopamine model of Parkinson's Disease using correlational tractography.

In recent years, tractography based on diffusion magnetic resonance imaging (dMRI) has become a popular tool for studying microstructural changes resulting from brain diseases like Parkinson's Disease (PD). Quantitative anisotropy (QA) is a parameter that is used in deterministic fiber tracking as a measure of connection between brain regions. It remains unclear, however, if microstructural changes caused by lesioning the median forebrain bundle (MFB) to create a Parkinsonian rat model can be resolved using tractography based on ex-vivo diffusion MRI. This study aims to fill this gap and enable future mechanistic research on structural changes of the whole brain network rodent models of PD. Specifically, it evaluated the ability of correlational tractography to detect structural changes in the MFB of 6-hydroxydopamine (6-OHDA) lesioned rats. The findings reveal that correlational tractography can detect structural changes in lesioned MFB and differentiate between the 6-OHDA and control groups. Imaging results are supported by behavioral and histological evidence demonstrating that 6-OHDA lesioned rats were indeed Parkinsonian. The results suggest that QA and correlational tractography is appropriate to examine local structural changes in rodent models of neurodegenerative disease. More broadly, we expect that similar techniques may provide insight on how disease alters structure throughout the brain, and as a tool to optimize therapeutic interventions.

Diffusion radiomics for subtyping and clustering in autism spectrum disorder: A preclinical study.

Autism spectrum disorder (ASD) is a highly prevalent, heterogenous neurodevelopmental disorder. Neuroimaging methods such as functional, structural, and diffusion MRI have been used to identify candidate imaging biomarkers for ASD, but current findings remain non-specific and likely arise from the heterogeneity present in ASD. To account for this, efforts to subtype ASD have emerged as a potential strategy for both the study of ASD and advancement of tailored behavioral therapies and therapeutics. Towards these ends, to improve upon current neuroimaging methods, we propose combining biologically sensitive neurite orientation dispersion and density index (NODDI) diffusion MR imaging with radiomics image processing to create a new methodological approach that, we hypothesize, can sensitively and specifically capture neurobiology. We demonstrate this method can sensitively distinguish differences between four genetically distinct rat models of ASD (Fmr1, Pten, Nrxn1, Disc1). Further, we demonstrate diffusion radiomic analyses hold promise for subtyping in ASD as we show unsupervised clustering of NODDI radiomic data generates clusters specific to the underlying genetic differences between the animal models. Taken together, our findings suggest the unique application of radiomic analysis on NODDI diffusion MRI may have the capacity to sensitively and specifically disambiguate the neurobiological heterogeneity present in the ASD population.

Trimethylamine N-Oxide Reduces Neurite Density and Plaque Intensity in a Murine Model of Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is the most common aging-associated neurodegenerative disease; nevertheless, the etiology and progression of the disease is still incompletely understood. We have previously shown that the microbially-derived metabolite trimethylamine N-oxide (TMAO) is elevated in the cerebrospinal fluid (CSF) of individuals with cognitive impairment due to AD and positively correlates with increases in CSF biomarkers for tangle, plaque, and neuronal pathology. OBJECTIVE: We assessed the direct impact of TMAO on AD progression. METHODS: To do so, transgenic 5XFAD mice were supplemented with TMAO for 12 weeks. Neurite density was assessed through quantitative brain microstructure imaging with neurite orientation dispersion and density imaging magnetic resonance imaging (MRI). Label-free, quantitative proteomics was performed on cortex lysates from TMAO-treated and untreated animals. Amyloid-ß plaques, astrocytes, and microglia were assessed by fluorescent immunohistochemistry and synaptic protein expression was quantified via western blot. RESULTS: Oral TMAO administration resulted in significantly reduced neurite density in several regions of the brain. Amyloid-ß plaque mean intensity was reduced, while plaque count and size remained unaltered. Proteomics analysis revealed that TMAO treatment impacted the expression of 30 proteins (1.5-fold cut-off) in 5XFAD mice, including proteins known to influence neuronal health and amyloid-ß precursor protein processing. TMAO treatment did not alter astrocyte and microglial response nor cortical synaptic protein expression. CONCLUSION: These data suggest that elevated plasma TMAO impacts AD pathology via reductions in neurite density.

Increased expression of SLC25A1/CIC causes an autistic-like phenotype with altered neuron morphology.

N ε-lysine acetylation within the lumen of the endoplasmic reticulum is a recently characterized protein quality control system that positively selects properly folded glycoproteins in the early secretory pathway. Overexpression of the endoplasmic reticulum acetyl-CoA transporter AT-1 in mouse forebrain neurons results in increased dendritic branching, spine formation and an autistic-like phenotype that is attributed to altered glycoprotein flux through the secretory pathway. AT-1 overexpressing neurons maintain the cytosolic pool of acetyl-CoA by upregulation of SLC25A1, the mitochondrial citrate/malate antiporter and ATP citrate lyase, which converts cytosolic citrate into acetyl-CoA. All three genes have been associated with autism spectrum disorder, suggesting that aberrant cytosolic-to-endoplasmic reticulum flux of acetyl-CoA can be a mechanistic driver for the development of autism spectrum disorder. We therefore generated a SLC25A1 neuron transgenic mouse with overexpression specifically in the forebrain neurons. The mice displayed autistic-like behaviours with a jumping stereotypy. They exhibited increased steady-state levels of citrate and acetyl-CoA, disrupted white matter integrity with activated microglia and altered synaptic plasticity and morphology. Finally, quantitative proteomic and acetyl-proteomic analyses revealed differential adaptations in the hippocampus and cortex. Overall, our study reinforces the connection between aberrant cytosolic-to-endoplasmic reticulum acetyl-CoA flux and the development of an autistic-like phenotype.

SLC13A5/sodium-citrate co-transporter overexpression causes disrupted white matter integrity and an autistic-like phenotype.

Endoplasmic reticulum-based N ɛ-lysine acetylation serves as an important protein quality control system for the secretory pathway. Dysfunctional endoplasmic reticulum-based acetylation, as caused by overexpression of the acetyl coenzyme A transporter AT-1 in the mouse, results in altered glycoprotein flux through the secretory pathway and an autistic-like phenotype. AT-1 works in concert with SLC25A1, the citrate/malate antiporter in the mitochondria, SLC13A5, the plasma membrane sodium/citrate symporter and ATP citrate lyase, the cytosolic enzyme that converts citrate into acetyl coenzyme A. Here, we report that mice with neuron-specific overexpression of SLC13A5 exhibit autistic-like behaviours with a jumping stereotypy. The mice displayed disrupted white matter integrity and altered synaptic structure and function. Analysis of both the proteome and acetyl-proteome revealed unique adaptations in the hippocampus and cortex, highlighting a metabolic response that likely plays an important role in the SLC13A5 neuron transgenic phenotype. Overall, our results support a mechanistic link between aberrant intracellular citrate/acetyl coenzyme A flux and the development of an autistic-like phenotype.

Structural and functional neuroimaging of the effects of the gut microbiome.

Interactions between intestinal microbiota and the central nervous system profoundly influence brain structure and function. Over the past 15 years, intense research efforts have uncovered the significant association between gut microbial dysbiosis and neurologic, neurodegenerative, and psychiatric disorders; however, our understanding of the effect of gut microbiota on quantitative neuroimaging measures of brain microstructure and function remains limited. Many current gut microbiome studies specifically focus on discovering correlations between specific microbes and neurologic disease states that, while important, leave critical mechanistic questions unanswered. To address this significant gap in knowledge, quantitative structural and functional brain imaging has emerged as a vital bridge and as the next step in understanding how the gut microbiome influences the brain. In this review, we examine the current state-of-the-art, raise awareness of this important topic, and aim to highlight immense new opportunities-in both research and clinical imaging-for the imaging community in this emerging field of study. Our review also highlights the potential for preclinical imaging of germ-free and gnotobiotic models to significantly advance our understanding of the causal mechanisms by which the gut microbiome alters neural microstructure and function. KEY POINTS: • Alterations to the gut microbiome can significantly influence brain structure and function in health and disease. • Quantitative neuroimaging can help elucidate the effect of gut microbiota on the brain and with future translational advances, neuroimaging will be critical for both diagnostic assessment and therapeutic monitoring.

18F-SynVesT-1 PET/MR Imaging of the Effect of Gut Microbiota on Synaptic Density and Neurite Microstructure: A Preclinical Pilot Study.

The gut microbiome profoundly influences brain structure and function. The gut microbiome is hypothesized to play a key role in the etiopathogenesis of neuropsychiatric and neurodegenerative illness; however, the contribution of an intact gut microbiome to quantitative neuroimaging parameters of brain microstructure and function remains unknown. Herein, we report the broad and significant influence of a functional gut microbiome on commonly employed neuroimaging measures of diffusion tensor imaging (DTI), neurite orientation dispersion and density (NODDI) imaging, and SV2A 18F-SynVesT-1 synaptic density PET imaging when compared to germ-free animals. In this pilot study, we demonstrate that mice, in the presence of a functional gut microbiome, possess higher neurite density and orientation dispersion and decreased synaptic density when compared to age- and sex-matched germ-free mice. Our results reveal the region-specific structural influences and synaptic changes in the brain arising from the presence of intestinal microbiota. Further, our study highlights important considerations for the development of quantitative neuroimaging biomarkers for precision imaging in neurologic and psychiatric illness.

Clinical translational neuroimaging of the antioxidant effect of N-acetylcysteine on neural microstructure.

PURPOSE: Oxidative stress and downstream effectors have emerged as important pathological processes that drive psychiatric illness, suggesting that antioxidants may have a therapeutic role in psychiatric disease. However, no imaging biomarkers are currently available to track therapeutic response. The purpose of this study was to examine whether advanced DWI techniques are able to sensitively detect the potential therapeutic effects of the antioxidant N-acetylcysteine (NAC) in a Disc1 svΔ2 preclinical rat model of psychiatric illness. METHODS: Male and female Disc1 svΔ2 rats and age-matched, sex-matched Sprague-Dawley wild-type controls were treated with a saline vehicle or NAC before ex vivo MRI acquisition at P50. Imaging data were fit to DTI and neurite orientation dispersion and density imaging models and analyzed for region-specific changes in quantitative diffusion metrics. Brains were further processed for cellular quantification of microglial density and morphology. All experiments were repeated for Disc1 svΔ2 rats exposed to chronic early-life stress to test how gene-environment interactions might alter effectiveness of NAC therapy. RESULTS: The DTI and neurite orientation dispersion and density imaging analyses demonstrated amelioration of early-life, sex-specific neural microstructural deficits with concomitant differences in microglial morphology across multiple brain regions relevant to neuropsychiatric illness with NAC treatment, but only in male Disc1 svΔ2 rats. Addition of chronic early-life stress reduced the ability of NAC to restore microstructural deficits. CONCLUSION: These findings provide evidence for a treatment pathway targeting endogenous antioxidant capacity, and the clinical translational utility of neurite orientation dispersion and density imaging microstructural imaging to sensitively detect microstructural alterations resulting from antioxidant treatment.

Measuring interdisciplinarity of biomedical research, medical specialty performance, and implications for radiology: A retrospective review of 2.6 million citations.

PURPOSE: To assess and determine the overall interdisciplinarity and impact of radiology and imaging sciences research. METHODS: Utilizing the Thomson Reuters Web of Science, the top 15 journals rank-ordered by impact factor in each of 10 major medical subspecialties were identified. The 2012 impact factors for these journals were noted. All articles published in these journals between 2012 and 2014 were then used to produce an index list of publications. We next generated a list of all published articles in the ensuing 5-year period that cited any publication present on our index list. These data were then used to calculate an interdisciplinarity score (DIV*) for 146 unique scientific journals. The correlation between the impact factor and the DIV* score was calculated with Kendall's τ. RESULTS: The quantitative measure of research interdisciplinarity, DIV*, is significantly correlated with journal impact factor (τ = 0.201, p < 0.001). Research journals within radiology, nuclear medicine, and medical imaging ranked 5th among 10 clinical subspecialties by mean impact factor but ranked second-to-last in mean DIV*. CONCLUSION: The interdisciplinarity score DIV* is positively correlated with journal impact factor, demonstrating the greater impact and reach of interdisciplinary research. Further, we found radiology, nuclear medicine, and medical imaging research to have one of the lowest measures of DIV* among the 10 major clinical subspecialties. Our findings suggest and point to new opportunities and directions that can expand the breadth and impact of radiology research as well as new ways to increase our reach and audience in the clinical scientific literature.

Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage.

OBJECTIVE: To determine the institutional diagnostic accuracy of an artificial intelligence (AI) decision support systems (DSS), Aidoc, in diagnosing intracranial hemorrhage (ICH) on noncontrast head CTs and to assess the potential generalizability of an AI DSS. METHODS: This retrospective study included 3,605 consecutive, emergent, adult noncontrast head CT scans performed between July 1, 2019, and December 30, 2019, at our institution (51% female subjects, mean age of 61 ± 21 years). Each scan was evaluated for ICH by both a certificate of added qualification certified neuroradiologist and Aidoc. We determined the diagnostic accuracy of the AI model and performed a failure mode analysis with quantitative CT radiomic image characterization. RESULTS: Of the 3,605 scans, 349 cases of ICH (9.7% of studies) were identified. The neuroradiologist and Aidoc interpretations were concordant in 96.9% of cases and the overall sensitivity, specificity, positive predictive value, and negative predictive value were 92.3%, 97.7%, 81.3%, and 99.2%, respectively, with positive predictive values unexpectedly lower than in previously reported studies. Prior neurosurgery, type of ICH, and number of ICHs were significantly associated with decreased model performance. Quantitative image characterization with CT radiomics failed to reveal significant differences between concordant and discordant studies. DISCUSSION: This study revealed decreased diagnostic accuracy of an AI DSS at our institution. Despite extensive evaluation, we were unable to identify the source of this discrepancy, raising concerns about the generalizability of these tools with indeterminate failure modes. These results further highlight the need for standardized study design to allow for rigorous and reproducible site-to-site comparison of emerging deep learning technologies.

Mapping Sex-Specific Neurodevelopmental Alterations in Neurite Density and Morphology in a Rat Genetic Model of Psychiatric Illness.

Neurite orientation dispersion and density imaging (NODDI) is an emerging magnetic resonance (MR) diffusion-weighted imaging (DWI) technique that permits non-invasive quantitative assessment of neurite density and morphology. NODDI has improved our ability to image neuronal microstructure over conventional techniques such as diffusion tensor imaging (DTI) and is particularly suited for studies of the developing brain as it can measure and characterize the dynamic changes occurring in dendrite cytoarchitecture that are critical to early brain development. Neurodevelopmental alterations to the diffusion tensor have been reported in psychiatric illness, but it remains unknown whether advanced DWI techniques such as NODDI are able to sensitively and specifically detect neurodevelopmental changes in brain microstructure beyond those provided by DTI. We show, in an extension of our previous work with a Disc1 svΔ2 rat genetic model of psychiatric illness, the enhanced sensitivity and specificity of NODDI to identify neurodevelopmental and sex-specific changes in brain microstructure that are otherwise difficult to observe with DTI and further corroborate observed changes in brain microstructure to differences in sex-specific systems-level animal behavior. Together, these findings inform the potential application and clinical translational utility of NODDI in studies of brain microstructure in psychiatric illness throughout neurodevelopment and further, the ability of advanced DWI methods such as NODDI to examine the role of biological sex and its influence on brain microstructure in psychiatric illness.

Microglial Density Alters Measures of Axonal Integrity and Structural Connectivity.

Diffusion tensor imaging (DTI) has fundamentally transformed how we interrogate diseases and disorders of the brain in neuropsychiatric illness. DTI and recently developed multicompartment diffusion-weighted imaging (MC-DWI) techniques, such as NODDI (neurite orientation dispersion and density imaging), measure diffusion anisotropy presuming a static neuroglial environment; however, microglial morphology and density are highly dynamic in psychiatric illness, and how alterations in microglial density might influence intracellular measures of diffusion anisotropy in DTI and MC-DWI brain microstructure is unknown. To address this question, DTI and MC-DWI studies of murine brains depleted of microglia were performed, revealing significant alterations in axonal integrity and fiber tractography in DTI and in commonly used MC-DWI models. With accumulating evidence of the role of microglia in neuropsychiatric illness, our findings uncover the unexpected contribution of microglia to measures of axonal integrity and structural connectivity and provide unanticipated insights into the potential influence of microglia in diffusion imaging studies of neuropsychiatric disease.

Convergent brain microstructure across multiple genetic models of schizophrenia and autism spectrum disorder: A feasibility study.

Neuroimaging studies of psychiatric illness have revealed a broad spectrum of structural and functional perturbations that have been attributed in part to the complex genetic heterogeneity underpinning these disorders. These perturbations have been identified in both preclinical genetic models and in patients when compared to control populations, but recent work has also demonstrated strong evidence for genetic, molecular, and structural convergence of several psychiatric diseases. We explored potential similarities in neural microstructure in preclinical genetic models of ASD (Fmr1, Nrxn1, Pten) and schizophrenia (Disc1 svΔ2) and in age- and sex-matched control animals with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). Our findings demonstrate a convergence in brain microstructure across these four genetic models with both tract-based and region-of-interest based analyses, which continues to buttress an emerging understanding of converging neural microstructure in psychiatric disease.

Metabolic Changes in Synaptosomes in an Animal Model of Schizophrenia Revealed by 1H and 1H,13C NMR Spectroscopy.

Synaptosomes are isolated nerve terminals that contain synaptic components, including neurotransmitters, metabolites, adhesion/fusion proteins, and nerve terminal receptors. The essential role of synaptosomes in neurotransmission has stimulated keen interest in understanding both their proteomic and metabolic composition. Mass spectrometric (MS) quantification of synaptosomes has illuminated their proteomic composition, but the determination of the metabolic composition by MS has been met with limited success. In this study, we report a proof-of-concept application of one- and two-dimensional nuclear magnetic resonance (NMR) spectroscopy for analyzing the metabolic composition of synaptosomes. We utilize this approach to compare the metabolic composition synaptosomes from a wild-type rat with that from a newly generated genetic rat model (Disc1 svΔ2), which qualitatively recapitulates clinically observed early DISC1 truncations associated with schizophrenia. This study demonstrates the feasibility of using NMR spectroscopy to identify and quantify metabolites within synaptosomal fractions.

Cortical Microstructural Alterations in Mild Cognitive Impairment and Alzheimer's Disease Dementia.

In Alzheimer's disease (AD), neurodegenerative processes are ongoing for years prior to the time that cortical atrophy can be reliably detected using conventional neuroimaging techniques. Recent advances in diffusion-weighted imaging have provided new techniques to study neural microstructure, which may provide additional information regarding neurodegeneration. In this study, we used neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion model, in order to investigate cortical microstructure along the clinical continuum of mild cognitive impairment (MCI) and AD dementia. Using gray matter-based spatial statistics (GBSS), we demonstrated that neurite density index (NDI) was significantly lower throughout temporal and parietal cortical regions in MCI, while both NDI and orientation dispersion index (ODI) were lower throughout parietal, temporal, and frontal regions in AD dementia. In follow-up ROI analyses comparing microstructure and cortical thickness (derived from T1-weighted MRI) within the same brain regions, differences in NODDI metrics remained, even after controlling for cortical thickness. Moreover, for participants with MCI, gray matter NDI-but not cortical thickness-was lower in temporal, parietal, and posterior cingulate regions. Taken together, our results highlight the utility of NODDI metrics in detecting cortical microstructural degeneration that occurs prior to measurable macrostructural changes and overt clinical dementia.