PEDIATRICS Vol. 118 No. 2 August 2006, pp. e442-e448 (doi:10.1542/peds.2006-0637)
ARTICLE |
Brain Developmental Abnormalities in Prader-Willi Syndrome Detected by Diffusion Tensor Imaging
a Center for Integrated Human Brain Science, Brain Research Institute
b Division of Pediatrics, Department of Homeostatic Regulation and Development, Graduate School of Medical and Dental Sciences, University of Niigata, Niigata, Japan
c Department of Neurology, University of California, Davis, California
 |
ABSTRACT |
|---|
 TOP ABSTRACT METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
OBJECTIVE. The purpose of this work was to detect brain developmental abnormalities in Prader-Willi syndrome by using diffusion tensor imaging based on a high-field MRI system.
METHODS. Eight patients with Prader-Willi syndrome and 8 age- and gender-matched normal control subjects were examined using a high-field (3.0 T) MRI system. Trace value and fractional anisotropy were assessed simultaneously in multiple representative brain regions: the deep gray matter (putamen, caudate head, and dorsomedial thalamus) and the white matter structures (frontal and parietal white matter, posterior limb of internal capsule, and corpus callosum).
RESULTS. In Prader-Willi syndrome patients, trace value was found to be significantly higher in the left frontal white matter and the left dorsomedial thalamus, whereas fractional anisotropy was significantly reduced in the posterior limb of the internal capsule bilaterally, the right frontal white matter, and the splenium of the corpus callosum. The observed diffusivity characteristics indicate developmental abnormalities in these areas, which are highly consistent with the clinical features of Prader-Willi syndrome.
CONCLUSIONS. The study provides the first objective evidence that Prader-Willi syndrome patients indeed have developmental abnormalities in specific areas of the brain, providing a new window toward understanding the pathophysiology of Prader-Willi syndrome.
Key Words: Prader-Willi syndrome • brain development • diffusion tensor imaging • trace • fractional anisotropy
Abbreviations: PWS—Prader-Willi syndrome • DTI—diffusion tensor imaging • Tr—trace value • FA—fractional anisotropy • ROI—region of interest • PLIC—posterior limb of internal capsule • CC—corpus callosum • 3DAC—three-dimensional anisotropy contrast
Prader-Willi syndrome (PWS) is a genetic disorder characterized by hypotonia, intellectual disabilities, obesity, hypogonadism, short stature, and behavioral disturbance. This syndrome, first described by Prader et al1 in 1956, occurs in 
1 in every 10000–25000 individuals, irrespective of races.1–3 Patients with PWS typically present with several neuroendocrinological abnormalities, such as growth hormone deficiency, hypogonadotropic hypogonadism, and hyperphagia, as the result of possible involvement of the hypothalamo-hypophyseal system.4–6 Moreover, they develop mild to moderate intellectual disabilities and characteristic maladaptive behaviors (ie, irritability, lying, skin picking, and obsessions) enhanced during developmental stages from childhood to adulthood.7–9 Although cytogenetic and molecular studies have revealed the cause of this syndrome as a failure of expression in paternally derived gene in the q11-13 region of chromosome 15,10,11 the relationship between genotype and phenotype has not been fully elucidated.
Although maturational delay is an essential part of PWS, thus far, no systematic analysis of brain development has been reported for PWS. Several studies have focused on functional abnormalities in specific neurologic domains associated with maturational delay in PWS by using a recent technique of physiologic analysis. Although an event-related potential study has associated abnormal deflation of P3 components with cognitive dysfunction in oddball task, a transcranial magnetic stimulation study has suggested hypoexcitability of the motor cortical areas as the altered corticospinal tract physiology.12,13 However, considering the clinical diversity of developmental abnormalities in neurologic and/or behavioral domains, as shown by the profiles of psychomotor development in PWS,14 it is desirable for the analysis of brain development to assess multiple areas of the brain simultaneously in a quantitative manner.
Diffusion tensor imaging (DTI) is a noninvasive imaging technique capable of providing quantitative indices of brain development.15,16 Quantitative indices provide in vivo information on trends in physiologic brain maturation17–19 and deviation as maturational delay.20,21 Although DTI provides 3 numerical values (eigenvalues) for quantitative analysis, in clinical settings 2 representative index values derived from 3 eigenvalues, namely trace value (Tr) and fractional anisotropy (FA), are frequently used. Although Tr gives the averaged value of diffusivity without directional consideration, FA provides information of directional deviation (anisotropism).15,16 Clinical DTI studies have so far revealed deviations of FA resulting from specific conditions such as disruption, degeneration, and disturbed connectivity in white matter (ie, perinatal brain injury, adrenoleukodystrophy, and schizophrenia, respectively).21–23 Moreover, analyses of the brain in patients with representative developmental disorders (ie, autism, fragile X syndrome, tuberous sclerosis, and chromosome 22q11.2 deletion syndrome) by using DTI have shown the disease-specific alterations in diffusivity characteristics indexed by Tr or FA indicative of brain developmental abnormalities.24–27 Accordingly, DTI would provide valuable information on brain developmental abnormalities in PWS, in which specific alteration of the brain development remains unknown.
In this study, we hypothesized that there would be regional brain abnormalities in PWS associated with specific developmental abnormalities in PWS. We used DTI based on a high-field (3.0 T) MRI system to detect brain developmental abnormalities in PWS.
|
METHODS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
Subjects
Eight patients with PWS, together with 8 randomly selected age- and gender-matched healthy control subjects, were recruited for the study. The characteristics of the participants are summarized in Table 1. Studies were performed according to the human research guidelines of the Internal Review Board of the University of Niigata.
|
All of the patients satisfied the commonly used clinical diagnostic criteria for PWS, and the diagnosis was confirmed by fluorescence in situ hybridization analysis, showing microdeletion of chromosome 15q11-13.28 The level of adaptive functioning on behavior was assessed using the Childhood Behavior Checklist (Japanese version).29 In addition, standardized psychological tests were administered to all of the patients by a clinical psychologist to assess global intellectual potential using intelligence quotient, calculated from values derived from the following batteries: Wechsler Intelligence Scale for Children-Third Edition or Wechsler Adult Intelligence Scale-Revised. Healthy subjects underwent a complete neurologic examination and interview (parents were interviewed in the case of early childhood) to ascertain that they had no developmental abnormalities and were free of any medication, illicit drugs, and alcohol.
MRI
A Signa LX 3.0-T (GE Medical System, Waukesha, WI) imaging system was used to perform all of the studies. Diffusion-weighted images were acquired with spin echo echo-planer imaging sequences using the following parameter settings: 4 axial slices; field of view: 200 x 200 mm; matrix: 128 x 128; slice thickness: 5.0 mm; interslice gaps: 2.5 mm; repetition time: 5 s; effective echo time: 82.7 ms; and number of excitations: 8. The b value was 500 s/mm2 per each axis with the 7 combinations of diffusion gradient vectors as follows: (0, 0, 0), (1, 0, 1) (–1, 0, 1), (0, 1, 1), (0, 1, –1), (1, 1, 0), and (–1, 1, 0), where (x, y, z) directions correspond with (readout, phase, slice). Parameters used for motion probing gradient were: amplitude, 2.19 g/cm; ramp time, 624 µs; 
= 37.2 ms; and 
= 33.4 ms. The total scanning time for acquisition of the entire diffusion imaging data set was 4 minutes and 40 seconds. In all of the imaging process, adequate preparations using audiovisual aids were provided for children and patients. No sedative procedure was performed.
Region of Interest
Multiple regions of interest (ROIs) were set up simultaneously in the following representative brain regions: the deep gray matter (putamen, caudate head, and dorsomedial thalamus) and the white matter structures (posterior limb of internal capsule [PLIC], frontal and parietal white matter, and genu and splenium of corpus callosum [CC]). All of the ROIs consisted of 3 x 3 pixels (4.7 mm x 4.7 mm) placed on the following slices: (1) the slice level of the splenium of the CC: putamen, caudate head, dorsomedial thalamus, PLIC, genu, and splenium of the CC; and (2) the slice level of the upper edge of lateral ventricles: frontal and parietal white matter.
For proper anatomic identification, ROI determination was performed based on three-dimensional anisotropy contrast (3DAC) images (Fig 1). 3DAC vector contrast imaging is known to provide exceptionally clear contrast among brain structures, especially between gray and white matter.30,31 3DAC images can be constructed by processing 3 principle images of 7 images, a series obtained for eigenvalue determination. This virtually eliminates any error for placement of ROIs as demonstrated by identical identification of ROIs by 3 independent investigators in blinded fashion.
|
Data Analysis
Representative index values, Tr and FA, commonly used under clinical setting, were derived from 3 eigenvalues (
1 > 2 > 3) by the following formula:
 |
 | (1) |
Statistical Analysis
A 2-way repeated-measures analysis of variance was conducted on Tr and FA independently, derived from all of the ROIs simultaneously. Disorder and region were set as the between- and the within-subjects variables, respectively. After the interaction effect between disorder and region was confirmed following the Huynh-Feldt correction in violating sphericity, tests of simple main effect on the factor of disorder were performed subsequently to contrast regional effects associated with disorder. Significant level was set at P < .05. All of the statistical analyses were performed by using technical statistical software (SPSS 12 and Sigma Plot 2000 for Windows version 6.0, SPSS Inc, Chicago, IL).
|
RESULTS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
Results are summarized in Table 2 and shown pictorially in Figs 2 and 3. Significant differences in diffusivity characteristics associated with disorder were observed in a region-dependent fashion. Although there was interaction between 2 factors (disorder and region; Tr: F10.038 = 1.925; P < .05; F12.527 = 1.883; P < .05) following the correction for sphericity (Huynh-Feldt's
; Tr: 0.772; FA: 0.964), tests of simple main effects subsequently showed discrete regional differences in each of the indices.
|
|
|
In PWS patients, Tr was found to be significantly higher in the left frontal white matter (F1132.459 = 14.613; P < .05) and the left dorsomedial thalamus (F1132.459 = 5.183; P < .05), whereas FA was significantly reduced in the PLIC bilaterally (left: F1162.322 = 6.525, P < .05; right: F1162.322 = 8.400, P < .05), the right frontal white matter (F1162.322 = 5.331; P < .05), and the splenium of the CC (F1162.322 = 5.195; P < .05). There were no regions presenting either lower Tr or higher FA in PWS, compared with normal controls.
|
DISCUSSION |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
In the current study, we demonstrated that there are regional abnormalities in brain development in PWS. Interestingly, the observed diffusivity characteristic alteration, which indicates developmental abnormalities in these areas, is consistent with the clinical features of PWS.
The fronto-thalamic regions, in which higher Tr were observed, have a close connection from the limbic system to the prefrontal and cingulate cortex.32 It has been suggested that abnormalities within these regions could result in psychiatric dysfunction, including personality change or bipolar disorder.33,34 Our findings may similarly indicate that abnormalities within these regions may be responsible for the clinically observed behavioral phenotype, including psychiatric manifestations in PWS.9
Motor dysfunction represents a main clinical feature of PWS and is considered to be primarily because of central nervous system abnormality, not muscular involvement.35 Previous DTI studies have shown that reduced FA reflects altered microstructure in PLIC and correlates with the level of motor disability in motor neuron disease.36,37 Reduced FA in PLIC observed bilaterally in this study may indeed reflect abnormalities responsible for "central hypotonia" in PWS.
Reduced FA in frontal white matter and posterior callosal connection indicate disintegrity in these regions, important for connecting cortices responsible for cognitive, visual, and spatial-perceptional function.38 CC is one of the crucial structures in developmental disorders, such as autism, in which structural difference has been reported.39,40 Its disruption results in the disturbance of executive functioning that requires effective interhemispheric information transfer, as a recent DTI study revealed in patients with alcoholism.41 Considering the psychological profiles as the superiority in spatial-perceptional organization and the inferiority in short-term memory on visual-perceptional contents, observed in patients with PWS,14 the difference in diffusivity characteristics within posterior callosal connection may indicate the brain developmental abnormality of interhemispheric connectivity in PWS.
Either higher Tr and/or reduced FA indicate deviation from regular development in each region. Although typical degenerative changes in the mature brain tend to produce Tr and FA abnormalities simultaneously, unique microstructural conditions during maturation can result in alteration in Tr or FA independently.42 Changes in eigenvalues during maturation are plausibly explained by the simultaneous occurrence of 2 independent phenomena, namely: (1) decline in unrestricted water content in extra-axonal space; and (2) increase in diffusivity within the axon. Extra-axonal free water has isotropic behavior as determined by DTI, and, hence, a decline in its relative volume results in a reduction of all eigenvalues to an identical degree. Increase in axonal diameter and/or axoplasmic flow affects anisotropic behavior of water within the axon and affects only the largest eigenvalue opposing the aforementioned reduction of the value. As a result, reduction in values will apparently retard the largest eigenvalue.43 Accordingly, higher Tr is likely to reflect a relative higher level in extracellular water contents because of the latent delay in the maturational process of matrix formation by glial cells,44,45 whereas reduced FA is likely to reflect maturational delay in axonal structure, including myelination.42,44,45 Nevertheless, it remains speculative, because no systematic analysis on brain pathology has been reported in PWS.
|
CONCLUSIONS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
This study provides the first objective evidence that PWS is accompanied by developmental abnormalities in specific areas of the brain. Success of the study owes highly to the ROI based approach that we adopted, which is readily performed under demanding clinical settings, such as the pediatric age group. The technique is sensitive for identifying individual differences in brain morphology, providing the ROI is properly set on functionally significant anatomic structures. 3DAC imaging,30,31 obtainable without the necessity of any additional imaging procedures, virtually guarantees highly accurate ROI settings. Nevertheless, it is prudent to cautiously interpret our presented data because of the rather small sample size studied.
|
ACKNOWLEDGMENTS |
|---|
The study was supported by grants from the Ministry of Education, Culture, Sports, Science, and Technology (Japan).
We thank Eiko Shouji for helpful advice in communicating with each patient who participated in the studies.
|
FOOTNOTES |
|---|
Accepted Apr 14, 2006.
Address correspondence to Tsutomu Nakada, MD, PhD, Center for Integrated Human Brain Science, Brain Research Institute, University of Niigata, Asahimachi 1-757, Niigata, 951-8585, Japan. E-mail: tnakada{at}bri.niigata-u.ac.jp
The authors have indicated they have no financial relationships relevant to this article to disclose.
This work was presented at the 2005 annual meeting of the Society for Neuroscience; November 12–16, 2005; Washington, DC.
|
REFERENCES |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
1. Prader A, Labhart A, Willi H. Ein Syndrom von Adipositas, Kleinwuchs, Kryptochismus und Oligophrenie nach Myatonieatigem Zustand im Neugeborenenalter. Schweiz Med Wschr. 1956;86 :1260 –1261
2. Akefeldt A, Gillberg C, Larsson C. Prader-Willi syndrome in a Swedish rural country: epidemiological aspects. Dev Med Child Neurol. 1991;33 :715 –721[Web of Science][Medline]
3. Whittington JE, Holland AJ, Webb T, Butler J, Clarke D, Boer H. Population prevalence and estimated birth incidence and mortality rate for people with Prader-Willi syndrome in 1 UK Health Region.
J Med Genet. 2001;38
:792
–798
4. Angulo M, Castro-Magana M, Mazur B, et al. Growth hormone secretion and effects or growth hormone therapy on growth velocity and weight gain in children with Prader-Willi syndrome. J Pediatr Endocrinol Metab. 1996;3 :393 –399
5. Bray GA et al. The Prader-Willi syndrome: a study of 40 patients and a review of the literature. Medicine (Baltimore). 1983;62 :59[Medline]
6. Swaab DF, Purba JS, Hofman MA. Alterations in the hypothalamic paraventricular nucleus and its oxytocin neurons (putative satiety cells) in Prader-Willi syndrome: a study of five cases. J Cli in Endocrinol Metab. 1995;80 :573 –579
7. Curfs LG. Psychological profile and behavioral characteristics in Prader-Willi syndrome. In: Cassidy SB, ed. Prader-Willi Syndrome and Other 15q Deletion Disorders. Berlin, Germany: Springer; 1991:430 –434
8. Dykens EM, Kasari C. Maladaptive behavior in children with Prader-Willi syndrome, Down syndrome and non-specific mental retardation. Am J Ment Retard. 1997;102 :228 –237[CrossRef][Web of Science][Medline]
9. Steinhausen HC, Eiholzer U, Hauffa BP, Malin Z. Behavioural and emotional disturbances in people with Prader-Willi Syndrome. J Intellect Disabil Res. 2004;48 :47 –52[CrossRef][Web of Science][Medline]
10. Ledbetter DH, Mascarello JT, Riccardi VM, Harper VD, Airhart SD, Strobel RJ. Deletions of chromosome 15 as a cause of the Prader-Willi syndrome. N Engl J Med. 1981;304 :325 –329[Web of Science][Medline]
11. Nicholls RD, Knoll JH, Butler MG, Karam S, Lalande M. Genetic imprinting suggested by maternal heterodisomy in non-deletion Prader-Willi syndrome. Nature. 1989;342 :281 –285[CrossRef][Medline]
12. Stauder JEA, Brinkman M, Curfs L. Multi-modal P3 deflation of event-related brain activity in Prader-Willi syndrome. Neurosci Lett. 2002;327 :99 –102[CrossRef][Web of Science][Medline]
13. Civarci C, Vincentini R, Grugni G, Cantello R. Corticospinal physiology in patients with Prader-Willi syndrome: a transcranial magnetic stimulation study.
Arch Neurol. 2004;61
:1585
–1589
14. Dykens EM, Hodapp RM, Walsh K, Nash LJ. Profiles, correlates and trajectories of intelligence in individuals with Prader-Willi syndrome. J Am Acad Child Adoles Psychiat. 1992;31 :1125 –1130
15. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B. 1996;111 :209 –219[CrossRef][Web of Science][Medline]
16. Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med. 1997;36 :893 –906[CrossRef][Web of Science]
17. Nomura Y, Sakuma H, Takeda K, Tagami T, Okuda Y, Nakagawa T. Diffusional anisotropy of the human brain assessed with diffusion-weighted MR: relation with normal brain development and aging. Am J Neuroradiol. 1994;15 :231 –238[Abstract]
18. Mukherjee P, Miller JH, Shimony JS, et al. Normal brain maturation during childhood: Developmental trends characterized with diffusion-tensor MR imaging.
Radiology. 2001;221
:349
–358
19. Schmithorst VJ, Wilke M, Dardzinski BJ, Holland SK. Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study.
Radiology. 2002;222
:212
–218
20. Hüppi PS, Maier SE, Peled S, et al. Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatr Res. 1998;44 :584 –590[Web of Science][Medline]
21. McKinstry RC, Miller JH, Snyder AZ, et al. A prospective, longitudinal diffusion tensor imaging study of brain injury in newborns.
Neurology. 2002;59
:824
–833
22. Ito R, Melhem ER, Mori S, Eichler FS, Raymond GV, Moser HW. Diffusion tensor brain MR imaging in X-linked cerebral adrenoleukodystrophy.
Neurology. 2001;56
:544
–547
23. Kitamura H, Matsuzawa H, Shioiri T, Someya T, Kwee IL, Nakada T. Diffusion tensor analysis in chronic schizophrenia A preliminary study on a high-field (3.0T) system. Eur Arch Psychiatry Clin Neurosci. 2005;255 :313 –318[CrossRef][Web of Science][Medline]
24. Barnea-Goraly N, Kwon H, et al. White matter structure inautism: preliminary evidence from diffusion tensor imaging. Biol Psychiatry. 2004;55 :323 –326[CrossRef][Web of Science][Medline]
25. Barnea-Goraly N, Eliez S, et al. White matter tract alterations in fragile X syndrome: preliminary evidence from diffusion tensor imaging. Am J Med Genet B Neuropsychiatr Genet. 2003;118 :81 –88[Medline]
26. Garaci FG, Floris R, Bozzao A, et al. Increased brain apparent diffusion coefficient in tuberous sclerosis.
Radiology. 2004;232
:461
–465
27. Simon TJ, Ding L, Bish JP, McDonald-McGinn DM, Zackai EH, Gee J. Volmetric, connective, and morphologic changes in the brains of children with chromosome 22q11.2 deletion syndrome: an integrative study. Neuroimage. 2005;25 :169 –180[CrossRef][Web of Science][Medline]
28. Holm VA, Cassidy SB, Butler MG, et al. Prader-Willi syndrome: consensus diagnostic criteria.
Pediatrics. 1993;91
:398
–402
29. Itani T, Kanbayashi Y, Nakata Y, et al. Standardization of the Japanese version of the Child Behavior Checklist/4–18. Jpn J Pediatr Psychiatr Neurol. 2001;41 :243 –252
30. Nakada T, Matsuzawa H. Three-dimensional anisotropy contrast magnetic resonance imaging of the rat nervous system: MR axonography. Neurosci Res. 1995;22 :389 –398[CrossRef][Web of Science][Medline]
31. Nakada T, Nakayama N, Fujii Y, Kwee IL. Clinical application of 3-dimensional anisotropy contrast magnetic resonance axonography: technical note. J Neurosurg. 1999;90 :791 –795[Web of Science][Medline]
32. Clark DL, Boutros NN. The Brain and Behavior: An Introduction to Behavioral Neuroanatomy. Malden, MA: Blackwell Science; 1999:119–129
33. Fukutake T, Akada K, Ito S, Okuda T, Ueki Y. Severe personality changes after unilateral left paramedian thalamic infarct. Eur Neurol. 2002;47 :156 –160[CrossRef][Web of Science][Medline]
34. Haznedar MM, Roversi F, Pallanti S, et al. Fronto-thalamo-striatal gray and white matter volumes and anisotropy of their connections in bipolar spectrum illnesses. Biol Psychiatry. 2005;57 :733 –742[CrossRef][Web of Science][Medline]
35. Argov Z, Gardner-Medwin D, Johnson MA, Mastaglia FL. Patterns of muscle fiber-type disproportion in hypotonic infants.
Arch Neurol. 1984;41
:53
–57
36. Graham JM, Papadakis N, Evans J, et al. Diffusion tensor imaging for the assessment of upper motor neuron integrity in ALS.
Neurology. 2004;63
:2111
–2119
37. Sach M, Winkler G, Glauche V, et al. Diffusion tensor MRI of early upper motor neuron involvement in amyotrophic lateral sclerosis.
Brain 2004;127
:340
–350.
38. Pandya D. Two Hemispheres-One Brain. New York, NY: Allan Liss; 1986
39. Piven J, Bailey AS, Randon BJ, Arndt S. An MRI study of the corpus callosum in autism. Am J Psychiatry. 1997;154 :1051 –1056[Abstract]
40. Chung MK, Dalton KM, Alexander AL, Davidson RJ. Less white matter concentration in autism: 2D voxel-based morphometry. Neuroimage. 2004;23 :242 –251[CrossRef][Web of Science][Medline]
41. Schulte T, Sullivan EV, Müller-Ochring EM, Adalsteinsson E, Pfefferbaum A. Corpus callosal microstructural integrity influences interhemispheric processing: a diffusion tensor imaging study.
Cereb Cortex 2005;15
:1384
–1392
42. Suzuki Y, Matsuzawa H, Nakada T. Feasibility study of single region lambda chart analysis for pyramidal tract physiology. J Neurol. 2003;250 :1185 –1189[CrossRef][Web of Science][Medline]
43. Suzuki Y, Matsuzawa H, Kwee IL, Nakada T. Absolute eigenvalue diffusion tensor analysis for human brain maturation. NMR Biomed. 2003;16 :257 –260[CrossRef][Web of Science][Medline]
44. Baratti C, Barnett AS, Pierpaoli C. Comparative MR imaging study of brain maturation in kittens with T1, T2, and the trace of the diffusion tensor.
Radiology. 1999;210
:133
–142
45. Tower DB, Bourke RS. Fluid conpartmentation and electrolytes of cat cerebral cortex in vitro. III. Ontogenetic and comparative aspects. J Neurochem. 1996;13 :1119 –1137
PEDIATRICS (ISSN 1098-4275). ©2006 by the American Academy of Pediatrics
CiteULike 
Connotea 
Del.icio.us 
Digg 
Facebook 
Reddit 
Technorati 
Twitter What's this?
This article has been cited by other articles:
|
|
 |
|
  K. Hasegawa and K. Yoshikawa Necdin Regulates p53 Acetylation via Sirtuin1 to Modulate DNA Damage Response in Cortical Neurons J. Neurosci., August 27, 2008; 28(35): 8772 - 8784. [Abstract] [Full Text] [PDF]
|
|
eLetters:
Read all eLetters
- Cerebellar abnormalities in PWS
- Luigi Titomanlio, et al.
- Pediatrics Online, 12 Oct 2006 [Full text]
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
