ABSTRACT. Objective. To investigate the effects of early experience on brain function and structure.Methods. A randomized clinical trial tested the neurodevelopmental effectiveness of the Newborn Individualized Developmental Care and Assessment Program (NIDCAP). Thirty preterm infants, 28 to 33 weeks' gestational age (GA) at birth and free of known developmental risk factors, participated in the trial. NIDCAP was initiated within 72 hours of intensive care unit admission and continued to the age of 2 weeks, corrected for prematurity. Control (14) and experimental (16) infants were assessed at 2 weeks' and 9 months' corrected age on health status, growth, and neurobehavior, and at 2 weeks' corrected age additionally on electroencephalogram spectral coherence, magnetic resonance diffusion tensor imaging, and measurements of transverse relaxation time.Results. The groups were medically and demographically comparable before as well as after the treatment. However, the experimental group showed significantly better neurobehavioral functioning, increased coherence between frontal and a broad spectrum of mainly occipital brain regions, and higher relative anisotropy in left internal capsule, with a trend for right internal capsule and frontal white matter. Transverse relaxation time showed no difference. Behavioral function was improved also at 9 months' corrected age. The relationship among the 3 neurodevelopmental domains was significant. The results indicated consistently better function and more mature fiber structure for experimental infants compared with their controls.Conclusions. This is the first in vivo evidence of enhanced brain function and structure due to the NIDCAP. The study demonstrates that quality of experience before term may influence brain development significantly. Pediatrics 2004;113:846 -857; preterm infants, NIDCAP, neurobehavior, spectral coherence, diffusion tensor imaging, transverse relaxation time, Bayley Scales of Infant Development, APIB.ABBREVIATIONS. NICU, newborn intensive care unit; NIDCAP, Newborn Individualized Developmental Care and Assessment Program; MRI, magnetic resonance imaging; EEG, electroencephalogram; APIB, Assessment of Preterm Infants' Behavior; Prechtl, Prechtl Neurologic Examination of the Fullterm Newborn Infant; Bayley II, Bayley Scales of Infant Development, Second Edition; MDI, mental developmental index; PDI, psychomotor developmental index; BRS, Behavior Rating Scale; T2*, transverse relaxation time; DTI, diffusion tensor imaging; ROI, region(s) of interest; E1, principal eigenvalue; E3, tertiary eigenvalue; RA, relative anisotropy; MANOVA, multivariate analysis of variance. T he preterm infant provides an opportunity to study the effects of early postnatal experience on brain development. Increasing evidence suggests that features of brain structure 1-4 and function [5][6][7][8] are different between medically healthy preterm infants and their term counterparts when assessed at a comparable age point. Although some differences are explained by the cumulative ...

The signal decay with increasing b‐factor at fixed echo time from brain tissue in vivo has been measured using a line scan Stejskal–Tanner spin echo diffusion approach in eight healthy adult volunteers. The use of a 175 ms echo time and maximum gradient strengths of 10 mT/m allowed 64 b‐factors to be sampled, ranging from 5 to 6000 s/mm2, a maximum some three times larger than that typically used for diffusion imaging. The signal decay with b‐factor over this extended range showed a decidedly non‐exponential behavior well‐suited to biexponential modeling. Statistical analyses of the fitted biexponential parameters from over 125 brain voxels (15 × 15 × 1 mm3 volume) per volunteer yielded a mean volume fraction of 0.74 which decayed with a typical apparent diffusion coefficient around 1.4 µm2/ms. The remaining fraction had an apparent diffusion coefficient of approximately 0.25 µm2/ms. Simple models which might explain the non‐exponential behavior, such as intra‐ and extracellular water compartmentation with slow exchange, appear inadequate for a complete description. For typical diffusion imaging with b‐factors below 2000 s/mm2, the standard model of monoexponential signal decay with b‐factor, apparent diffusion coefficient values around 0.7 µm2/ms, and a sensitivity to diffusion gradient direction may appear appropriate. Over a more extended but readily accessible b‐factor range, however, the complexity of brain signal decay with b‐factor increases, offering a greater parametrization of the water diffusion process for tissue characterization. Copyright © 1999 John Wiley & Sons, Ltd.

Diffusion tensor imaging (DTI) studies in schizophrenia demonstrate lower anisotropic diffusion within white matter due either to loss of coherence of white matter fiber tracts, to changes in the number and/or density of interconnecting fiber tracts, or to changes in myelination, although methodology as well as localization of such changes differ between studies. The aim of this study is to localize and to specify further DTI abnormalities in schizophrenia by combining DTI with magnetization transfer imaging (MTI), a technique sensitive to myelin and axonal alterations in order to increase specificity of DTI findings. 21 chronic schizophrenics and 26 controls were scanned using Line-Scan-Diffusion-Imaging and T1-weighted techniques with and without a saturation pulse (MT). Diffusion information was used to normalize co-registered maps of fractional anisotropy (FA) and magnetization transfer ratio (MTR) to a study-specific template, using the multi-channel daemon algorithm, designed specifically to deal with multi-directional tensor information. Diffusion anisotropy was decreased in schizophrenia in the following brain regions: the fornix, the corpus callosum, bilaterally in the cingulum bundle, bilaterally in the superior occipito-frontal fasciculus, bilaterally in the internal capsule, in the right inferior occipito-frontal fasciculus and the left arcuate fasciculus. MTR maps demonstrated changes in the corpus callosum, fornix, right internal capsule, and the superior occipito-frontal fasciculus bilaterally; however, no changes were noted in the anterior cingulum bundle, the left internal capsule, the arcuate fasciculus, or inferior occipito-frontal fasciculus. In addition, the right posterior cingulum bundle showed MTR but not FA changes in schizophrenia. These findings suggest that, while some of the diffusion abnormalities in schizophrenia are likely due to abnormal coherence, or organization of the fiber tracts, some of these abnormalities may, in fact, be attributed to or coincide with myelin/axonal disruption.

The development and optimization of spin-echo-based, single-slab, three-dimensional techniques for magnetic resonance imaging of the whole brain are described. T1-weighted and T2-weighted image sets with a volume resolution of 1 mm(3) and fluid-attenuated inversion-recovery image sets with a volume resolution of 3 mm(3) were obtained in acquisition times of less than 10 minutes per image set.

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A multichannel statistical classifier for detecting prostate cancer was developed and validated by combining information from three different magnetic resonance (MR) methodologies: T2-weighted, T2-mapping, and line scan diffusion imaging (LSDI). From these MR sequences, four different sets of image intensities were obtained: T2-weighted (T2W) from T2-weighted imaging, Apparent Diffusion Coefficient (ADC) from LSDI, and proton density (PD) and T2 (T2 Map) from T2-mapping imaging. Manually segmented tumor labels from a radiologist, which were validated by biopsy results, served as tumor "ground truth." Textural features were extracted from the images using co-occurrence matrix (CM) and discrete cosine transform (DCT). Anatomical location of voxels was described by a cylindrical coordinate system. A statistical jack-knife approach was used to evaluate our classifiers. Single-channel maximum likelihood (ML) classifiers were based on 1 of the 4 basic image intensities. Our multichannel classifiers: support vector machine (SVM) and Fisher linear discriminant (FLD), utilized five different sets of derived features. Each classifier generated a summary statistical map that indicated tumor likelihood in the peripheral zone (PZ) of the prostate gland. To assess classifier accuracy, the average areas under the receiver operator characteristic (ROC) curves over all subjects were compared. Our best FLD classifier achieved an average ROC area of 0.839(+/-0.064), and our best SVM classifier achieved an average ROC area of 0.761(+/-0.043). The T2W ML classifier, our best single-channel classifier, only achieved an average ROC area of 0.599(+/-0.146). Compared to the best single-channel ML classifier, our best multichannel FLD and SVM classifiers have statistically superior ROC performance (P=0.0003 and 0.0017, respectively) from pairwise two-sided t-test. By integrating the information from multiple images and capturing the textural and anatomical features in tumor areas, summary statistical maps can potentially aid in image-guided prostate biopsy and assist in guiding and controlling delivery of localized therapy under image guidance.

Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.

Magnetic resonance (MR) examinations of men with prostate cancer are most commonly performed for detecting, characterizing, and staging the extent of disease to best determine diagnostic or treatment strategies, which range from biopsy guidance to active surveillance to radical prostatectomy. Given both the exam's importance to individual treatment plans and the time constraints present for its operation at most institutions, it is essential to perform the study effectively and efficiently. This article reviews the most commonly employed modern techniques for prostate cancer MR examinations, exploring the relevant signal characteristics from the different methods discussed and relating them to intrinsic prostate tissue properties. Also, a review of recent articles using these methods to enhance clinical interpretation and assess clinical performance is provided.