Ronald Pierson

Long-term Antipsychotic Treatment and Brain Volumes: A Longitudinal Study of First-Episode Schizophrenia

CONTEXT Progressive brain volume changes in schizophrenia are thought to be due principally to the disease. However, recent animal studies indicate that antipsychotics, the mainstay of treatment for schizophrenia patients, may also contribute to brain tissue volume decrement. Because antipsychotics are prescribed for long periods for schizophrenia patients and have increasingly widespread use in other psychiatric disorders, it is imperative to determine their long-term effects on the human brain. OBJECTIVE To evaluate relative contributions of 4 potential predictors (illness duration, antipsychotic treatment, illness severity, and substance abuse) of brain volume change. DESIGN Predictors of brain volume changes were assessed prospectively based on multiple informants. SETTING Data from the Iowa Longitudinal Study. PATIENTS Two hundred eleven patients with schizophrenia who underwent repeated neuroimaging beginning soon after illness onset, yielding a total of 674 high-resolution magnetic resonance scans. On average, each patient had 3 scans (≥2 and as many as 5) over 7.2 years (up to 14 years). MAIN OUTCOME MEASURE Brain volumes. RESULTS During longitudinal follow-up, antipsychotic treatment reflected national prescribing practices in 1991 through 2009. Longer follow-up correlated with smaller brain tissue volumes and larger cerebrospinal fluid volumes. Greater intensity of antipsychotic treatment was associated with indicators of generalized and specific brain tissue reduction after controlling for effects of the other 3 predictors. More antipsychotic treatment was associated with smaller gray matter volumes. Progressive decrement in white matter volume was most evident among patients who received more antipsychotic treatment. Illness severity had relatively modest correlations with tissue volume reduction, and alcohol/illicit drug misuse had no significant associations when effects of the other variables were adjusted. CONCLUSIONS Viewed together with data from animal studies, our study suggests that antipsychotics have a subtle but measurable influence on brain tissue loss over time, suggesting the importance of careful risk-benefit review of dosage and duration of treatment as well as their off-label use.

The role of the cerebellum in schizophrenia.

For many years the cerebellum has been considered to serve as a coordinator of motor function. Likewise, for many years schizophrenia has been considered to be a disease that primarily affects the cerebrum. This review summarizes recent evidence that both these views must be revised in the light of emerging evidence about cerebellar function and the mechanisms of schizophrenia. Evidence indicating that the cerebellum plays a role in higher cortical functions is summarized. Evidence indicating that cerebellar abnormalities occur in schizophrenia is also reviewed. These suggest interesting directions for future research.

Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study.

In addition to its well-established role in balance, coordination, and other motor skills, the cerebellum is increasingly recognized as a prominent contributor to a wide array of cognitive and emotional functions. Many of these capacities undergo dramatic changes during childhood and adolescence. However, accurate characterization of co-occurring anatomical changes has been hindered by lack of longitudinal data and methodologic challenges in quantifying subdivisions of the cerebellum. In this study we apply an innovative image analysis technique to quantify total cerebellar volume and 11 subdivisions (i.e. anterior, superior posterior, and inferior posterior lobes, corpus medullare, and three vermal regions) from anatomic brain MRI scans from 25 healthy females and 25 healthy males aged 5-24 years, each of whom was scanned at least three times at approximately 2-year intervals. Total cerebellum volume followed an inverted U shaped developmental trajectory peaking at age 11.8 years in females and 15.6 years in males. Cerebellar volume was 10% to 13% larger in males depending on the age of comparison and the sexual dimorphism remained significant after covarying for total brain volume. Subdivisions of the cerebellum had distinctive developmental trajectories with more phylogenetically recent regions maturing particularly late. The cerebellums unique protracted developmental trajectories, sexual dimorphism, preferential vulnerability to environmental influences, and frequent implication in childhood onset disorders such as autism and ADHD make it a prime target for pediatric neuroimaging investigations.

Progressive Brain Change in Schizophrenia: A Prospective Longitudinal Study of First-Episode Schizophrenia

BACKGROUND Schizophrenia has a characteristic onset during adolescence or young adulthood but also tends to persist throughout life. Structural magnetic resonance studies indicate that brain abnormalities are present at onset, but longitudinal studies to assess neuroprogression have been limited by small samples and short or infrequent follow-up intervals. METHODS The Iowa Longitudinal Study is a prospective study of 542 first-episode patients who have been followed up to 18 years. In this report, we focus on those patients (n = 202) and control subjects (n = 125) for whom we have adequate structural magnetic resonance data (n = 952 scans) to provide a relatively definitive determination of whether progressive brain change occurs over a time interval of up to 15 years after intake. RESULTS A repeated-measures analysis showed significant age-by-group interaction main effects that represent a significant decrease in multiple gray matter regions (total cerebral, frontal, thalamus), multiple white matter regions (total cerebral, frontal, temporal, parietal), and a corresponding increase in cerebrospinal fluid (lateral ventricles and frontal, temporal, and parietal sulci). These changes were most severe during the early years after onset. They occur at severe levels only in a subset of patients. They are correlated with cognitive impairment but only weakly with other clinical measures. CONCLUSIONS Progressive brain change occurs in schizophrenia, affects both gray matter and white matter, is most severe during the early stages of the illness, and occurs only in a subset of patients. Measuring severity of progressive brain change offers a promising new avenue for phenotype definition in genetic studies of schizophrenia.

Striatal and white matter predictors of estimated diagnosis for Huntington disease.

Previous MRI studies with participants prior to manifest Huntington disease have been conducted in small single-site samples. The current study reports data from a systematic multi-national study during the prodromal period of Huntington disease and examines whether various brain structures make unique predictions about the proximity to manifest disease. MRI scans were acquired from 657 participants enrolled at 1 of 32 PREDICT-HD research sites. Only prodromal Huntington disease participants (those not meeting motor criteria for diagnosis) were included and subgrouped by estimated diagnosis proximity (Near, Mid, and Far) based upon a formula incorporating age and CAG-repeat length. Results show volumes of all three subgroups differed significantly from Controls for total brain tissue, cerebral spinal fluid, white matter, cortical gray matter, thalamus, caudate, and putamen. Total striatal volume demonstrated the largest differences between Controls and all three prodromal subgroups. Cerebral white matter offered additional independent power in the prediction of estimated proximity to diagnosis. In conclusion, this large cross-sectional study shows that changes in brain volume are detectable years to decades prior to estimated motor diagnosis of Huntington disease. This suggests that a clinical trial of a putative neuroprotective agent could begin as much as 15 years prior to estimated motor diagnosis in a cohort of persons at risk for but not meeting clinical motor diagnostic criteria for Huntington disease, and that neuroimaging (striatal and white matter volumes) may be among the best predictors of diagnosis proximity.

Longitudinal change in regional brain volumes in prodromal Huntington disease

Objective As therapeutics are being developed to target the underlying neuropathology of Huntington disease, interest is increasing in methodologies for conducting clinical trials in the prodromal phase. This study was designed to examine the potential utility of structural MRI measures as outcome measures for such trials. Methods Data are presented from 211 prodromal individuals and 60 controls, scanned both at baseline and at the 2-year follow-up. Prodromal participants were divided into groups based on proximity to estimated onset of diagnosable clinical disease: far (>15 years from estimated onset), mid (9–15 years) and near (<9 years). Volumetric measurements of caudate, putamen, total striatum, globus pallidus, thalamus, total grey and white matter and cerebrospinal fluid were performed. Results All prodromal groups showed a faster rate of atrophy than controls in striatum, total brain and cerebral white matter (especially in the frontal lobe). Neither prodromal participants nor controls showed any significant longitudinal change in cortex (either total cortical grey or within individual lobes). When normal age-related atrophy (ie, change observed in the control group) was taken into account, there was more statistically significant disease-related atrophy in white matter than in striatum. Conclusion Measures of volume change in striatum and white-matter volume, particularly in the frontal lobe, may serve as excellent outcome measures for future clinical trials in prodromal Huntington disease. Clinical trials using white matter or striatal volume change as an outcome measure will be most efficient if the sample is restricted to individuals who are within 15 years of estimated onset of diagnosable disease.

Registration and Machine Learning Based Automated Segmentation of Subcortical and Cerebellar Brain Structures

The large amount of imaging data collected in several ongoing multi-center studies requires automated methods to delineate brain structures of interest. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures. Here we present several automated segmentation methods using multidimensional registration. A direct comparison between template, probability, artificial neural network (ANN) and support vector machine (SVM)-based automated segmentation methods is presented. Three metrics for each segmentation method are reported in the delineation of subcortical and cerebellar brain regions. Results show that the machine learning methods outperform the template and probability-based methods. Utilization of these automated segmentation methods may be as reliable as manual raters and require no rater intervention.

Smaller intracranial volume in prodromal Huntington's disease: evidence for abnormal neurodevelopment

Huntingtons disease is an autosomal dominant brain disease. Although conceptualized as a neurodegenerative disease of the striatum, a growing number of studies challenge this classic concept of Huntingtons disease aetiology. Intracranial volume is the tissue and fluid within the calvarium and is a representation of the maximal brain growth obtained during development. The current study reports intracranial volume obtained from an magnetic resonance imaging brain scan in a sample of subjects (n = 707) who have undergone presymptomatic gene testing. Participants who are gene-expanded but not yet manifesting the disease (prodromal Huntingtons disease) are compared with subjects who are non-gene expanded. The prodromal males had significantly smaller intracranial volume measures with a mean volume that was 4% lower compared with controls. Although the prodromal females had smaller intracranial volume measures compared with their controls, this was not significant. The current findings suggest that mutant huntingtin can cause abnormal development, which may contribute to the pathogenesis of Huntingtons disease.

Striatal Volume Contributes to the Prediction of Onset of Huntington Disease in Incident Cases

BACKGROUND Previous neuroimaging research indicates that brain atrophy in Huntington disease (HD) begins many years before movement abnormalities become severe enough to warrant diagnosis. Most clinical trials being planned for individuals in the prediagnostic stage of HD propose to use delay of disease onset as the primary outcome measure. Although formulas have been developed based on age and CAG repeat length, to predict when HD motor onset will occur, it would be useful to have additional measures that can improve the accuracy of prediction of disease onset. METHODS The current study examined magnetic resonance imaging (MRI) measures of striatum and white matter volume in 85 individuals prospectively followed from pre-HD stage through diagnosable motor onset (incident cases) and 85 individuals individually matched with incident cases on CAG repeat length, sex, and age, who were not diagnosed with HD during the course of the study. RESULTS Volumes of striatum and white matter were significantly smaller in individuals who would be diagnosed 1 to 4 years following the initial MRI scan, compared with those who would remain in the pre-HD stage. Putamen volume was the measure that best distinguished between the two groups. CONCLUSIONS Results suggest that MRI volumetric measures may be helpful in selecting individuals for future clinical trials in pre-HD where HD motor onset is the primary outcome measure. In planning for multisite clinical trials in pre-HD, investigators may also want to consider using more objective measures, such as MRI volumes, in addition to onset of diagnosable movement disorder, as major outcome measures.

Manual and Semiautomated Measurement of Cerebellar Subregions on MR Images

Previous structural and functional imaging studies suggest that the corticocerebellar-thalamic-cortical circuit is dysfunctional in schizophrenia. Accurate identification and volumetric measurement of cerebellar subregions are essential to the assessment of the cerebellums role in healthy and disease states. Manual parcellation of the cerebellum on MR images was performed with the use of guide traces. Guide traces identified relevant fissures and borders in several planes, and their intersections with the primary tracing plane were used to maintain consistency and accuracy during the parcellation. The cerebellum was parcellated into right and left anterior lobes, superior posterior lobes, inferior posterior lobes, and corpus medullare. A systematic review of the final traces ensured their accuracy. An artificial neural network was trained using a novel landmark-warped method to help account for wide variability in structure size and location. Overlaps of the manually traced lobes (intersection/union) ranged from 0.78 to 0.85 and intraclass correlations (r2) ranged from 0.82 to 0.94. In a comparison of the semiautomated method with the manual method overlaps ranged from 0.83 to 0.88 and intraclass correlations ranged from 0.92 to 0.97. For two raters using the semiautomated method overlaps ranged from 0.83 to 0.88 and intraclass correlations ranged from 0.97 to 0.99. The semiautomated method was built on the groundwork of the manual method to produce more reliable results in a fraction of the time, making valid measurements possible on a large number of subjects.