Brain MRI in Autism Spectrum Disorder: Narrative Review and Recent Advances.

Autism spectrum disorder (ASD) is neuropsychiatric continuum of disorders characterized by persistent deficits in social communication and restricted repetitive patterns of behavior which impede optimal functioning. Early detection and intervention in ASD children can mitigate the deficits in social interaction and result in a better outcome. Various non-invasive imaging methods and molecular techniques have been developed for the early identification of ASD characteristics. There is no general consensus on specific neuroimaging features of autism; however, quantitative magnetic resonance techniques have provided valuable structural and functional information in understanding the neuropathophysiology of ASD and how the autistic brain changes during childhood, adolescence, and adulthood. In this review of decades of ASD neuroimaging research, we identify the structural, functional, and molecular imaging clues that most accurately point to the diagnosis of ASD vs. typically developing children. These studies highlight the 1) exaggerated synaptic pruning, 2) anomalous gyrification, 3) interhemispheric under- and overconnectivity, and 4) excitatory glutamate and inhibitory GABA imbalance theories of ASD. The application of these various theories to the analysis of a patient with ASD is mitigated often by superimposed comorbid neuropsychological disorders, evolving brain maturation processes, and pharmacologic and behavioral interventions that may affect the structure and function of the brain. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

Neuroimaging in Attention-Deficit/Hyperactivity Disorder: Recent Advances.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition that leads to impaired attention and impulsive behaviors diagnosed in, but not limited to, children. ADHD can cause symptoms throughout life. This article summarizes the structural (conventional, volumetric, and diffusion tensor imaging) and functional (task-based functional MRI [fMRI], resting-state fMRI, PET, and MR spectroscopy) brain findings in patients with ADHD. Consensus is lacking regarding altered anatomic or functional imaging findings of the brain in children with ADHD, likely because of the heterogeneity of the disorder. Most anatomic studies report abnormalities in the frontal lobes, basal ganglia, and corpus callosum; decreased surface area in the left ventral frontal and right prefrontal cortex; thinner medial temporal lobes; and smaller caudate nuclei. Using fMRI, researchers have focused on the prefrontal and temporal regions, reflecting perception-action mapping alterations. Artificial intelligence models evaluating brain anatomy have highlighted changes in cortical thickness and the shape of the inferior frontal cortex, bilateral sensorimotor cortex, left temporal lobe, and insula. Early intervention and/or normal brain maturation can alter imaging patterns and convert functional imaging studies to a normal pattern. Although imaging findings provide insight into the neuropathophysiology of the disease, no definitive structural or functional pattern defines the disorder from a neuroradiologic perspective.

Factors Determining Scientific Paper Productivity by Neuroradiology Fellows.

RATIONALE AND OBJECTIVES: We sought to determine (1) whether United States Medical Licensing Examination (USMLE) scores predict academic productivity in neuroradiology fellows as measured by publications and citations, and (2) what factors predict such productivity. MATERIALS AND METHODS: We reviewed the USMLE scores, gender, medical school location attended, publication record before and during fellowship, fellowship evaluation ratings and subsequent practice site (private vs academic) of neuroradiology fellows from 2004 to 2014 to determine relationships with publications and citations after fellowship. Spearman's correlation and Poisson regression analyses were performed to assess the association between these factors and quantity of publications and citations per year after fellowship. RESULTS: USMLE scores and fellowship evaluation scores correlated inversely with radiology publications and citations. There were strong correlations between publication records before or during fellowship and after fellowship. Fellows from international medical schools, with PhD degrees, and those fellows proceeding to academic practice had more publications before or during and after neuroradiology fellowship. CONCLUSIONS: The best predictors of whether a graduating neuroradiology fellow will publish and have high citation rates is prior publication record, a PhD degree, and staying in academics. USMLE scores and evaluations during the fellowship were inversely correlated with publication measures of academic productivity.

United States Medical Licensing Examination Step 1 and 2 Scores Predict Neuroradiology Fellowship Success.

PURPOSE: Many neuroradiology programs use United States Medical Licensing Examination (USMLE) scores to assess fellowship candidates. The authors hypothesized that because they are taken several years before fellowship, USMLE scores would correlate poorly with success in fellowship training as measured by faculty evaluations. METHODS: USMLE scores from 10 years of neuroradiology fellows (n = 73) were compared with their cumulative mean E*Value scores from their fellowship years and their best-to-worst rankings within their fellowship years. If available, subspecialty certification scores were also factored as an outcome. Linear correlation and regression analyses were performed adjusting for gender, medical school site, and practice setting after fellowship. RESULTS: USMLE Step 1, 2, and 3 scores were available for 69, 64, and 56 fellows, respectively. Fellowship E*Value scores and rankings showed statistically significant (P < .05) correlations with all USMLE scores, but most strongly for Step 1 scores and E*Value grade (r = 0.443) and rank (r = 0.370). The mean USMLE Step 1 score of the top-ranked fellows (234.5) was significantly higher than that of the bottom-ranked fellows (217.7). The correlations of E*Value score and rank with USMLE Step 1 and 2 scores remained after adjusting for gender and American versus foreign medical school, but the medical school site attended also was an independent predictor of fellowship evaluations. Subspecialty certification scores did not show correlations but were underpowered (n = 28). CONCLUSIONS: USMLE Step 1 and 2 scores correlated significantly with success in neuroradiology fellowship, measured by faculty assessments of the six core competencies. Using the scores as a means of assessing candidates for positions is justified.