Unlike neurologic conditions, such as brain tumors, dementia, and stroke, the neural mechanisms for all psychiatric disorders remain unclear. A large body of research obtained with structural and ...functional magnetic resonance imaging, positron emission tomography/single photon emission computed tomography, and optical imaging has demonstrated regional and illness-specific brain changes at the onset of psychiatric disorders and in individuals at risk for such disorders. Many studies have shown that psychiatric medications induce specific measurable changes in brain anatomy and function that are related to clinical outcomes. As a result, a new field of radiology, termed psychoradiology, seems primed to play a major clinical role in guiding diagnostic and treatment planning decisions in patients with psychiatric disorders. This article will present the state of the art in this area, as well as perspectives regarding preparations in the field of radiology for its evolution. Furthermore, this article will (a) give an overview of the imaging and analysis methods for psychoradiology; (b) review the most robust and important radiologic findings and their potential clinical value from studies of major psychiatric disorders, such as depression and schizophrenia; and (c) describe the main challenges and future directions in this field. An ongoing and iterative process of developing biologically based nomenclatures with which to delineate psychiatric disorders and translational research to predict and track response to different therapeutic drugs is laying the foundation for a shift in diagnostic practice in psychiatry from a psychologic symptom-based approach to an imaging-based approach over the next generation. This shift will require considerable innovations for the acquisition, analysis, and interpretation of brain images, all of which will undoubtedly require the active involvement of radiologists.
RSNA, 2016 Online supplemental material is available for this article.
Objective:Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. ...Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations.Method:A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected.Results:Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders.Conclusions:These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard.
IMPORTANCE: Questions of whether and how cortical thickness (CTh) alterations differ over the course of schizophrenia (SCZ) have yet to be resolved. OBJECTIVE: To characterize CTh alterations across ...illness stages in SCZ. DATA SOURCES: PubMed, Embase, Web of Science, and Science Direct were screened for CTh studies published before June 15, 2021. STUDY SELECTION: Original studies comparing whole-brain CTh alterations from healthy controls in individuals at clinical high-risk (CHR), first episode of psychosis (FEP), and long-term illness stages of SCZ were included. DATA EXTRACTION AND SYNTHESIS: This preregistered systematic review and meta-analysis followed PRISMA reporting guidelines. Separate and pooled meta-analyses were performed using seed-based d mapping. Meta-regression analyses were conducted. MAIN OUTCOMES AND MEASURES: Cortical thickness differences from healthy control individuals across illness stages. RESULTS: Ten studies comprising 859 individuals with CHR (mean SD age, 21.02 2.66 years; male, 573 66.7%), 12 studies including 671 individuals with FEP (mean SD age, 22.87 3.99 years; male, 439 65.4%), and 10 studies comprising 579 individuals with long-term SCZ (mean SD age, 41.58 6.95 years; male, 396 68.4%) were included. Compared with healthy control individuals, individuals with CHR showed cortical thinning in bilateral medial prefrontal cortex (z = −1.01; P < .001). Individuals with FEP showed cortical thinning in right lateral superior temporal cortex (z = −1.34; P < .001), right anterior cingulate cortex (z = −1.44; P < .001), and right insula (z = −1.14; P = .002). Individuals with long-term SCZ demonstrated CTh reductions in right insula (z = −3.25; P < .001), right inferior frontal cortex (z = −2.19; P < .001), and left (z = −2.37; P < .001) and right (z = −1.94; P = .002) temporal pole. There were no significant CTh differences between CHR and FEP. Individuals with long-term SCZ showed greater cortical thinning in right insula (z = −2.58; P < .001), right inferior frontal cortex (z = −2.32; P < .001), left lateral temporal cortex (z = −1.91; P = .002), and right temporal pole (z = −1.82; P = .002) than individuals with FEP. Combining all studies on SCZ, accelerated age-related CTh reductions were found in bilateral lateral middle temporal cortex and right pars orbitalis in inferior frontal cortex. CONCLUSIONS AND RELEVANCE: The absence of significant differences between FEP and CHR noted in this systematic review and meta-analysis suggests that the onset of psychosis was not associated with robust CTh reduction. The greater cortical thinning in long-term SCZ compared with FEP with accelerated age-related reduction in CTh suggests progressive neuroanatomic alterations following illness onset. Caution in interpretation is needed because heterogeneity in samples and antipsychotic treatment may confound these results.
Summary
Depression is the leading cause of disability around the world, but little is known about its pathology. Currently, the diagnosis of depression is made based on clinical manifestations, with ...little objective evidence. Magnetic resonance imaging (MRI) has been used to investigate the pathological changes in brain anatomy associated with this disorder. MRI can identify structural alterations in depressive patients in vivo, which could make considerable contributions to clinical diagnosis and treatment. Numerous studies that focused on gray and white matter have found significant brain region alterations in major depressive disorder patients, such as in the frontal lobe, hippocampus, temporal lobe, thalamus, striatum, and amygdala. The results are inconsistent and controversial because of the different demographic and clinical characteristics. However, some regions overlapped; thus, we think that there may be a “hub” in MDD and that an impairment in these regions contributes to disease severity. Brain connections contain both structural connections and functional connections, which reflect disease from a different view and support that MDD may be caused by the interaction of multiple brain regions. According to previous reports, significant circuits include the frontal‐subcortical circuit, the suicide circuit, and the reward circuit. As has been recognized, the pathophysiology of major depressive disorder is complex and changeable. The current review focuses on the significant alterations in the gray and white matter of patients with the depressive disorder to generate a better understanding of the circuits. Moreover, identifying the nuances of depressive disorder and finding a biomarker will make a significant contribution to the guidance of clinical diagnosis and treatment.
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BFBNIB, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Xanthine oxidase (XO) is distributed in mammals largely in the liver and small intestine, but also is highly active in milk where it generates hydrogen peroxide (H2O2). Adult human saliva is low in ...hypoxanthine and xanthine, the substrates of XO, and high in the lactoperoxidase substrate thiocyanate, but saliva of neonates has not been examined.
Median concentrations of hypoxanthine and xanthine in neonatal saliva (27 and 19 μM respectively) were ten-fold higher than in adult saliva (2.1 and 1.7 μM). Fresh breastmilk contained 27.3 ± 12.2 μM H2O2 but mixing baby saliva with breastmilk additionally generated >40 μM H2O2, sufficient to inhibit growth of the opportunistic pathogens Staphylococcus aureus and Salmonella spp. Oral peroxidase activity in neonatal saliva was variable but low (median 7 U/L, range 2-449) compared to adults (620 U/L, 48-1348), while peroxidase substrate thiocyanate in neonatal saliva was surprisingly high. Baby but not adult saliva also contained nucleosides and nucleobases that encouraged growth of the commensal bacteria Lactobacillus, but inhibited opportunistic pathogens; these nucleosides/bases may also promote growth of immature gut cells. Transition from neonatal to adult saliva pattern occurred during the weaning period. A survey of saliva from domesticated mammals revealed wide variation in nucleoside/base patterns.
During breast-feeding, baby saliva reacts with breastmilk to produce reactive oxygen species, while simultaneously providing growth-promoting nucleotide precursors. Milk thus plays more than a simply nutritional role in mammals, interacting with infant saliva to produce a potent combination of stimulatory and inhibitory metabolites that regulate early oral-and hence gut-microbiota. Consequently, milk-saliva mixing appears to represent unique biochemical synergism which boosts early innate immunity.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background Current definitions of psychotic illness lack biological validity, motivating alternative biomarker-driven disease entities. Building on experimental constructs—Biotypes—previously ...developed from cognitive and neurophysiologic measures (1), we contrast brain anatomy characteristics across Biotypes alongside conventional diagnoses, examining gray matter density (GMD) as an independent validator for the Biotypes. Methods Whole brain GMD measures were examined in probands, their relatives, and healthy subjects organized by Biotype, and then by DSM diagnosis (n=1,409), using Voxel-Based Morphometry with subsequent subject-level regional characterization and distribution analyses. Results Probands grouped by Biotype vs. healthy showed a step-wise pattern of GMD reductions: Biotype1, extensive and diffusely distributed GMD loss, with the largest effects in frontal, anterior/middle cingulate, temporal regions; Biotype2, intermediate and more localized reductions, with the largest effects in insula, fronto-temporal regions; Biotype3, small reductions localized to anterior limbic regions. Relatives showed regionally distinct GMD reductions vs. healthy, with primarily anterior (fronto-temporal) effects in Biotype1; posterior (temporo-parieto-cerebellar) in Biotype2; and normal GMD in Biotype3. Schizophrenia and schizoaffective probands vs. healthy showed overlapping GMD reductions, with the largest effects in fronto-temporal and parietal regions; psychotic bipolar probands had small reductions, primarily in frontal regions. GMD changes in relatives followed regional patterns observed in probands, albeit less extensive. Biotypes showed stronger between-group separation based on GMD than the conventional diagnoses, and were the strongest predictor of GMD change. Conclusions The GMD biomarkers depicted unique brain structure characteristics within Biotypes consistent with their cognitive and sensorimotor profiles, and provided stronger discrimination for biologically-driven Biotypes than symptom-based diagnoses.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
To characterize cognitive maturation through adolescence, processing speed, voluntary response suppression, and spatial working memory were measured in 8- to 30-year-old (N = 245) healthy ...participants using oculomotor tasks. Development progressed with a steep initial improvement in performance followed by stabilization in adolescence. Adult-level mature performance began at approximately 15, 14, and 19 years of age for processing speed, response inhibition, and working memory, respectively. Although processes developed independently, processing speed influenced the development of working memory whereas the development of response suppression and working memory were interdependent. These results indicate that processing speed, voluntary response suppression, and working memory mature through late childhood and into adolescence. How brain maturation specific to adolescence may support cognitive maturation is discussed.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NMLJ, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Purpose To identify cerebral radiomic features related to diagnosis and subtyping of attention deficit hyperactivity disorder (ADHD) and to build and evaluate classification models for ADHD diagnosis ...and subtyping on the basis of the identified features. Materials and Methods A consecutive cohort of 83 age- and sex-matched children with newly diagnosed and never-treated ADHD (mean age 10.83 years ± 2.30; range, 7-14 years; 71 boys, 40 with ADHD-inattentive ADHD-I and 43 with ADHD-combined ADHD-C, or inattentive and hyperactive) and 87 healthy control subjects (mean age, 11.21 years ± 2.51; range, 7-15 years; 72 boys) underwent anatomic and diffusion-tensor magnetic resonance (MR) imaging. Features representing the shape properties of gray matter and diffusion properties of white matter were extracted for each participant. The initial feature set was input into an all-relevant feature selection procedure within cross-validation loops to identify features with significant discriminative power for diagnosis and subtyping. Random forest classifiers were constructed and evaluated on the basis of identified features. Results No overall difference was found between children with ADHD and control subjects in total brain volume (1069830.00 mm
± 90743.36 vs 1079 213.00 mm
± 92742.25, respectively; P = .51) or total gray and white matter volume (611978.10 mm
± 51622.81 vs 616960.20 mm
± 51872.93, respectively; P = .53; 413532.00 mm
± 41 114.33 vs 418173.60 mm
± 42395.48, respectively; P = .47). The mean classification accuracy achieved with classifiers to discriminate patients with ADHD from control subjects was 73.7%. Alteration in cortical shape in the left temporal lobe, bilateral cuneus, and regions around the left central sulcus contributed significantly to group discrimination. The mean classification accuracy with classifiers to discriminate ADHD-I from ADHD-C was 80.1%, with significant discriminating features located in the default mode network and insular cortex. Conclusion The results of this study provide preliminary evidence that cerebral morphometric alterations can allow discrimination between patients with ADHD and control subjects and also between the most common ADHD subtypes. By identifying features relevant for diagnosis and subtyping, these findings may advance the understanding of neurodevelopmental alterations related to ADHD.
RSNA, 2017 Online supplemental material is available for this article.
: Adolescence marks the beginning of adult‐level cognitive control of behavior supported by the brain maturation processes of synaptic pruning and myelination. Cognitive development studies on ...adolescence indicate that this period is characterized by improvements in the performance of existing abilities including speed and capacity of information processing and the ability to have consistent cognitive control of behavior. Although adolescents can behave at adult levels in some ways, brain imaging studies indicate that the functional organization of brain systems that support higher‐cognitive processes are not fully mature. Synaptic pruning allows for more efficient local computations, enhancing the ability of discrete brain regions to support high‐level cognitive control of behavior including working memory. Myelination increases the speed of neuronal transmission supporting the collaboration of a widely distributed circuitry, integrating regions that support top‐down cognitive control of behavior. Functional brain imaging methods allow for the characterization of the relationship between cognitive development and brain maturation as we can map progressions in the establishment of distributed brain circuitry and its relation to enhanced cognitive control of behavior. We present a review on the maturation (as distinct from “development” in emphasizing the transition to maturity and stabilization) of response inhibition, brain structure, and brain function through adolescence. We also propose a model for brain‐behavior maturation that allows for the qualitative changes in cognitive processes that occur during adolescence.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
ObjectiveDeveloping categorical diagnoses that have biological meaning within the clinical phenotype of psychosis (schizophrenia, schizoaffective disorder, and bipolar I disorder with psychosis) is ...as important for developing targeted treatments as for nosological goals. The Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) was formed to examine a broad array of intermediate phenotypes across psychotic disorders and to test the hypothesis that intermediate phenotype characteristics are homogeneous within phenomenologically derived DSM-IV diagnoses.MethodThe consortium recruited 933 stable probands with schizophrenia, schizoaffective disorder, or psychotic bipolar I disorder, 1,055 of their first-degree relatives, and 459 healthy comparison subjects for clinical characterization and dense phenotyping. Clinical, psychosocial, and family characteristics were contrasted.ResultsAll proband groups showed lower psychosocial functioning than the relatives or comparison group. On average, schizophrenia probands showed more symptoms and lower psychosocial functioning than probands with psychotic bipolar disorder, but there was considerable overlap in clinical manifestations. The characteristics of schizoaffective disorder were more often similar to schizophrenia than to psychotic bipolar disorder. The rates of lifetime suicide attempts were high across all proband groups, with the highest reported frequencies in the schizoaffective and bipolar groups. Proband family lineages included both families with “pure” psychosis diagnoses and families with mixed schizophrenia-bipolar diagnoses.ConclusionsSymptoms, psychosocial functioning, and familial lineage overlap across the three DSM-IV psychosis diagnoses used in B-SNIP. The comingling of psychosis diagnoses within families suggests overlapping genetic determinants across psychoses. These data provide scant evidence for distinct phenotypic clustering around traditional phenomenological diagnoses.
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