Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleBrain

Changes in Integrity of Normal-Appearing White Matter in Patients with Moyamoya Disease: A Diffusion Tensor Imaging Study

H. Jeong, J. Kim, H.S. Choi, E.S. Kim, D.-S. Kim, K.-W. Shim and S.-K. Lee
American Journal of Neuroradiology November 2011, 32 (10) 1893-1898; DOI: https://doi.org/10.3174/ajnr.A2683
H. Jeong
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J. Kim
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
H.S. Choi
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
E.S. Kim
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
D.-S. Kim
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
K.-W. Shim
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S.-K. Lee
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

Abstract

BACKGROUND AND PURPOSE: DTI is widely used for the evaluation of white matter integrity in various neurologic diseases. The purpose of this study was to investigate changes in white matter integrity by using DTI in NAWM of patients with MMD and to evaluate the correlation between diffusion and perfusion characteristics through an interhemispheric comparison.

MATERIALS AND METHODS: We retrospectively reviewed 20 primary MMD patients with asymmetric disease stage and 20 age-matched healthy controls. FACS and ADCCS values of bilateral centrum semiovale were measured by using region of interest analysis. Mean FACS and ADCCS were compared between patient and control groups by unpaired t test. Interhemispheric differences in FACS and ADCCS were assessed and compared between the H-TTPdelayed and the H-TTPshorter by using paired t test. AIs also were assessed to verify interhemispheric differences.

RESULTS: The patient group showed a significantly lower mean FACS and a higher mean ADCCS value than the control group. In the patient group, the H-TTPdelayed had a significantly lower FACS and higher ADCCS value than the H-TTPshorter. Both AIFA and AIADC were significantly higher in the patient compared with the control group.

CONCLUSIONS: DTI can describe subtle changes in white matter integrity in NAWM of patients with primary MMD that are not detected by conventional MR imaging. In addition, diffusion characteristics are well correlated with perfusion characteristics. We believe that DTI is a useful ancillary tool to evaluate patients with MMD.

Abbreviations

ADCCS
apparent diffusion coefficient in centrum semiovale
AI
asymmetric index
FACS
fractional anisotropy in centrum semiovale
H-TTPdelayed
hemisphere with more delayed time-to-peak
H-TTPshorter
contralateral hemisphere of H-TTPdelayed
MMD
Moyamoya disease
NAWM
normal-appearing white matter
PWI
perfusion-weighted MR imaging
rCBV
relative cerebral blood volume

MMD is a chronic steno-occlusive disease of the internal carotid arteries that mainly affects children. Various imaging techniques have been applied to evaluate the hemodynamic status, tissue integrity, and prognosis of MMD.1–3

The recent development of DTI has allowed visualization of fiber orientation and microstructural integrity in white matter and is considered to be a very useful tool for evaluating white matter in various central nervous system diseases.4–7 DTI has been accepted as a tool with sufficient sensitivity to detect brain pathologies hidden in NAWM.8–11 For example, DTI can reveal microstructural damage of NAWM in patients with chronic cerebral arterial occlusive disease.11,12

In patients with MMD, progressive vascular stenosis causes chronic cerebral hypoperfusion in the territory of the internal carotid arteries, but partial adaptation occurs through collateral blood flow from the posterior circulation, the ethmoidal vessel, and other basal vessels.13 MMD with partially adapted chronic hypoperfusion follows a dynamic disease process. Patients with MMD may experience serial ischemic attacks, and some patients eventually experience cerebral infarct. We hypothesized that NAWM in MMD patients without cerebral infarct may be affected by chronic hypoperfusion, and DTI could reveal cumulative microstructural damage that is not visualized by conventional MR imaging.

Perfusion MR imaging has been found to be effective in the evaluation of cerebral hemodynamics in MMD.3,14–16 TTP images are simple to use for the assessment of collateral status, development of neovascularization after encephaloduroarteriosyangiosis, and general perfusion status. In addition, the ischemic hemisphere usually shows an increased rCBV due to compensatory vasodilation and delayed TTP due to proximal vessel stenosis.17 In MMD without infarction, an interhemispheric difference in TTP may be present due to different stages of proximal vessel stenosis. We hypothesized that the hemisphere with more delayed TTP (H-TTPdelayed) may be vulnerable to hypoperfusion, so NAWM in the H-TTPdelayed may demonstrate a higher level of cumulative microstructural damage than NAWM in the contralateral hemisphere.

Thus, the purpose of this study was to investigate changes in white matter integrity by using DTI in NAWM of patients with MMD and to evaluate the correlation between diffusion and perfusion characteristics by an interhemispheric comparison.

Materials and Methods

Patients and Control Subjects

The institutional review board approved this retrospective study and waived the requirement for informed consent from patients or legal guardians. We retrospectively reviewed brain MR images and clinical data of 103 childhood MMD patients from August 2006 to August 2009 at the Severance Hospital of the Yonsei University Health System of Korea. Of these patients, 20 (15 girls and 5 boys; mean age, 9.55 years; range, 5–15 years) who satisfied the following criteria were included in the patient group: 1) patients who were diagnosed with primary childhood MMD on MR imaging and MRA according to the diagnostic criteria and guidelines for MMD proposed by the Research Committee on Spontaneous Occlusion of the Circle of Willis18; 2) patients who simultaneously underwent FLAIR imaging, MRA, PWI imaging, and DTI; 3) patients who had no clinical history of therapeutic intervention, such as pharmacotherapy (vasodilator or anticoagulant) or surgery (bypass or indirect revascularization procedure) before undergoing MR imaging; 4) patients who had no overt cerebral infarct on conventional MR imaging; and 5) patients who showed definitive asymmetric involvement upon visual analysis of MRA and TTP maps. Thirty-seven patients satisfied criteria 1–4, and 20 among them satisfied criteria 5 and were therefore included in the final patient group.

Because healthy childhood volunteers were not available due to the sedation procedure, “closest-to-normal” control diffusion data were obtained from 20 age-matched children (7 girls and 13 boys; mean age, 9.75 years; age range, 5–15 years) who had no vascular pathology on either radiologic or clinical evaluation. The control subjects had the following indications for MR imaging: central nervous system symptoms (headache, 12 patients; seizure, 2 patients) or psychiatric problems (schizophrenia, 2 patients; social phobia, 2 patients; adjustment disorder, 1 patient; conversion disorder, 1 patient). Conventional MR imaging and DTI were simultaneously performed on controls during the same period as for patient subjects.

Data Acquisition

All examinations were performed by 3T MR imaging (Achieva; Philips Medical Systems, Best, the Netherlands) by using an 8-channel sensitivity-encoding head coil. DTI, PWI, MRA, FLAIR, T2-weighted, and gradient-echo T2*-weighted images were obtained in patients with MMD. T1-weighted, T2-weighted, and postcontrast T1-weighted images and DTI were obtained in the control group.

DTI was performed by using single-shot spin-echo-EPI. The axial images were obtained parallel to the anterior/posterior commissure line. The parameters for DTI were as follows: TR/TE/flip angle = 6000 ms/100 ms/90°, FOV = 22 cm, acquisition matrix = 128 × 128, section thickness/intersection gap = 5 mm/2 mm, and NEX = 4. Diffusion sensitizing gradient encoding was applied in 6 directions (x, y, z, xy, yz, and zx) with b at 1000 seconds/mm2, and 1 image was acquired without by using a diffusion gradient (with b at 0). Isotropic ADC, trace, and FA maps were immediately generated on the console by research software (Packman Tools; Philips Medical Systems). The 6 elements of the diffusion tensor were estimated in each voxel assuming a mono-exponential relationship between signal intensity and the b-matrix. Using multivariate regression, the eigenvectors and eigenvalues of the diffusion tensor were determined. To minimize the eddy current–related artifact, we implemented zero and first-order eddy current compensations into the MR imaging system and monitored and calibrated the eddy current level.

PWI was carried out by using multishot gradient-echo principles of echo shifting with a train of observations technique by using the following parameters: TR/TE/flip angle = 2000/60/90°, matrix = 128 × 128, FOV = 24 cm, and section thickness/intersection gap = 5 mm/2 mm. All 60 phase images were obtained before, during, and after the administration of contrast agent (0.1 mmol of gadopentetate dimeglumine [Magnevist; Schering, Berlin, Germany] per kilogram of body weight at a rate of 2 mL/s) through an MR imaging–compatible power injector (Spectris; Medrad, Indianola, Pennsylvania) in those patients older than 5 years or by manual injection in those patients 5 years and younger. This injection was followed by a 15-mL bolus of saline administered at the same injection rate. Perfusion maps of TTP and CBV were generated after eliminating the effect of contrast agent recirculation by γ-variate curve fitting.19,20

MRA was obtained with the 3D time-of-flight technique with a 3D spoiled gradient recalled-echo sequence by using the following parameters: TR/TE/flip angle = 24/3.45/20°, matrix = 512 × 208, FOV = 20 cm, section thickness = 0.8 mm, and effective voxel size = 0.39 × 0.96 × 0.8 mm.

Conventional T1-weighted (TR/TE/flip angle, 2000 ms/10 ms/90°), FLAIR (TR/TE/TI, 11,000 ms/125 ms/2800 ms), T2-weighted (TR/TE, 3000 ms/80 ms), and gradient-echo T2*-weighted (TR/TE/flip angle, 576 ms/15 ms/18°) images were obtained by using the respective parameters.

Data Analysis

In each MMD patient, the H-TTPdelayed and the greater degree of proximal vessel stenosis was determined by the consensus of 2 radiologists (H.J. with 3 years of experience in MR imaging interpretation and S.-K.L. with 13 years of experience) by visual analysis of the TTP map and by using the MRA scoring system proposed by Houkin et al.21 The rCBV patterns in the areas with more delayed TTP also were visually evaluated.

ADC and FA values were measured in the bilateral centrum semiovale of both patient and control groups. The software program NeuRoi (Dr C. Tench, Department of Clinical Neurology, University of Nottingham, United Kingdom), was used for semiautomatic measurement. This program is available at www.nottingham.ac.uk/scs/divisions/clinicalneurology/index.aspx. The ROIs in the centrum semiovale were drawn manually in a 60-mm3 round shape. To avoid contamination from adjacent CSF and gray matter, the ROIs were drawn on the EPI scan of the b = 0 step (T2-weighted, but not diffusion-weighted) at the level of the centrum semiovale, and then automatically overlaid onto the coregistered FA and ADC images (Fig 1). To ensure consistency and consensus, 1 investigator (H.J.) drew the ROIs and 1 board-certified neuroradiologist (S.-K.L.) subsequently confirmed them.

Fig 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig 1.

ROI method for ADCCS and FACS measurement. Round ROIs (60 mm3) were drawn on the EPI scan of the b = 0 step at the level of the centrum semiovale, followed by automatic overlaying onto the coregistered FA and ADC images.

Statistical Analysis

We compared the FA and ADC values between the patient and control groups by using the independent samples t test. We then compared the diffusion characteristics of H-TTPdelayed and the H-TTPshorter in the patient group by using the paired samples t test.

Because diffusion characteristics in the normal brain are somewhat asymmetrical,22 AIs also were used to verify the significance of the difference between H-TTPdelayed and H-TTPshorter. The mathematic equations providing AI for FA values in the centrum semiovale were as follows: Embedded Image Embedded Image where FA-H-TTPshorter is the FA value in the H-TTPshorter (FA-H-TTPshorter), FA-H-TTPdelayed is the FA value in the H-TTPdelayed (FA-H-TTPdelayed), FARt is the FA value in the right hemisphere, and FALt is the FA value in the left hemisphere.

The same pattern of mathematic equations also was applied to the ADC values. The independent samples t test was used to compare AI between patient and control groups.

A probability of <5% was considered statistically significant. All statistical analyses were performed by using MedCalc 7.4.0.0 software (MedCalc, Mariakerke, Belgium).

Results

The clinical information and findings pertaining to the hemisphere with TTPdelayed and greater degree of proximal vessel stenosis among the bilateral hemispheres, and the rCBV pattern are summarized in Table 1. Fourteen of the 20 MMD patients presented with recurrent TIA. In patients with recurrent TIA, H-TTPdelayed was highly concordant with the symptomatic hemisphere (95%). The detailed FA and ADC values in each group are summarized in Table 2.

View this table:
  • View inline
  • View popup
Table 1:

Clinical information and findings for TTP status, degree of supraclinoid ICA or MCA stenosis, and rCBV pattern

View this table:
  • View inline
  • View popup
Table 2:

Measured diffusion characteristics in patient and control groups

The patient group showed a significantly lower mean FACS value and a higher mean ADCCS value compared with the control group (Table 3). The results of the interhemispheric comparison are summarized in Table 4. In the patient group, H-TTPdelayed showed a significantly lower FACS value and a higher ADCCS value compared with H-TTPshorter (Fig 2). There were no significant differences in the mean FA and ADC values between the right and left centrum semiovales in the control group. Both AIFA and AIADC were significantly higher in the patient group compared with the control group.

View this table:
  • View inline
  • View popup
Table 3:

Comparison of diffusion characteristics between patient and control groups

View this table:
  • View inline
  • View popup
Table 4:

Interhemispheric comparison of diffusion characteristics

Fig 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig 2.

Primary MMD in a 6-year-old girl. A–C, MRA images showed asymmetric MRA cores and stages between both hemispheres (Rt., stage III; Lt., stage II). TTP (D) and CBV (E) maps demonstrated asymmetric hemodynamic status, in which the Rt. hemisphere showed more delayed TTP and increased CBV. Diffusion-weighted image (b = 1000; F) and a FLAIR image (G) did not show any abnormalities. H, ADC map, right side ADCCS (836.3 mm2/s) was higher than left side ADCCS (779.8 mm2/s). I, FA map, right side FACS (0.438 × 10−3) was lower than left side FACS (0.487 × 10−3).

Discussion

We demonstrated that DTI could detect the cumulative microstructural damage that was not detected on conventional MR imaging in the NAWM with chronic hypoperfusion in primary childhood MMD without overt infarction. In addition, we revealed that the NAWM of the hemisphere with more delayed perfusion in each MMD patient had more microstructural damage.

The 2 most commonly determined diffusion properties are the FA, reflecting the degree to which the diffusion tensor deviates from isotropy, and the ADC, reflecting the orientation-averaged apparent diffusivity.7 The FA value may be low when white matter integrity is disrupted. Several studies revealed that the FA value is an indicator of tissue damage in the white matter despite the absence of definite abnormalities on conventional T2 or FLAIR images.11,12,23 The net diffusion of water molecules measured in a particular tissue is referred to as ADC.5 In chronic hypoperfusion, ischemic injury to white matter is associated with axonal destruction and glial proliferation.24 These microstructural changes are associated with an increase in the ADC, probably reflecting increased water diffusivity due to axonal loss.25 However, ADC changes are not confined to ischemic lesions and may occur in NAWM.11,26–28 Thus, we investigated changes in integrity of NAWM with MMD, by using measurements of both FA and ADC.

Our results showed that NAWM of MMD patients without infarction had a significantly lower mean FACS value and a higher mean ADCCS value compared with controls. There have been a few previous DTI studies for MMD. Using whole brain histogram analysis, Mori et al29 revealed that MMD with infarction had significantly lower FA and mean diffusivity than controls. Moreover, they reported that MMD without infarction showed the same tendency, though the differences were not statistically significant. The discrepancy in statistical significance between our study and that of Mori et al29 can be explained by differences in data analysis. The whole brain histogram is an accurate and robust method for overall measurements, but it cannot reveal results in a specific site. We therefore assume that in our study the localized regional analysis for centrum semiovale revealed significant differences in diffusion characteristics, suggesting microstructural damage in the NAWM of patients with MMD without infarction. Recently, Conklin et al30 revealed that regions of steal phenomenon are spatially correlated with elevated ADC in NAWM of patients with MMD, suggesting that even if there is no overt infarction in MMD, microstructural damage of NAWM can develop from low-grade ischemia. Our finding of increased ADC in NAWM of patients with MMD without infarction is consistent with the findings of Conklin et al.30 We found a significantly lower mean FACS value and a higher mean ADCCS value in patients with MMD, probably reflecting cumulative white matter damage from chronic hypoperfusion and recurrent ischemic attacks.

Next, we analyzed the interhemispheric DTI difference in patients with MMD who showed asymmetric TTP status. MMD was defined as bilateral disease, but MMD is known to have a rather asymmetric perfusion appearance, especially in children. MMD also can show a somewhat asymmetric disease status in chronic progressive disease. This asymmetric disease status in MMD can be detected on MRA and PWI. In MMD, the hypoperfused hemisphere usually shows increased rCBV due to compensatory vasodilation, and delayed TTP represents proximal occlusion or stenosis and collateral flow. Our results showed that the hemisphere with a more delayed TTP and a higher MRA score had a significantly lower FACS value and a higher ADCCS value than the more perfused contralateral hemisphere. This result may reflect that NAWM of H-TTPdelayed is more vulnerable to hypoperfusion than the more perfused contralateral hemisphere and that NAWM in H-TTPdelayed may demonstrate more cumulative microstructural damage than NAWM in the contralateral hemisphere.

We note that our study has some limitations. First, the retrospective data analysis resulted in a reduced number of enrolled patients with a high degree of homogeneity in terms of disease and age. Second, for ethical reasons, ideal healthy control subjects were not recruited and structurally normal children's brains were used for comparison. However, we speculate that our results would not have been too different if this study had been performed with ideal controls. Third, DTI in this study was performed with only 6 different diffusion gradients. It has been reported that at least 20 diffusion gradients are necessary for a robust estimation of diffusion characteristics.31 The small number of diffusion gradients in our study could thus be a limitation. Fourth, the lack of absolute quantification in perfusion MR imaging is another limitation. Thus, future investigation by using quantitative analysis of PWI and DTI with at least 20 diffusion gradients is needed.

Conclusions

DTI can detect subtle changes in white matter integrity in chronic hypoperfused brains of patients with primary childhood MMD that are not detected by conventional MR imaging. In addition, diffusion and perfusion characteristics are well correlated. Our findings suggest that DTI can be used as an ancillary tool to evaluate disease severity of patients with primary childhood MMD.

References

  1. 1.↵
    1. Suzuki J,
    2. Takaku A
    . Cerebrovascular “Moyamoya” disease. Disease showing abnormal net-like vessels in base of brain. Arch Neurol 1969;20:288–99
    CrossRefPubMed
  2. 2.↵
    1. Yamada I,
    2. Himeno Y,
    3. Nagaoka T,
    4. et al
    . Moyamoya disease: evaluation with diffusion-weighted and perfusion echo-planar MR imaging. Radiology 1999;212:340–47
    PubMed
  3. 3.↵
    1. Calamante F,
    2. Ganesan V,
    3. Kirkham FJ,
    4. et al
    . MR perfusion imaging in Moyamoya syndrome: potential implications for clinical evaluation of occlusive cerebrovascular disease. Stroke 2001;32:2810–16
    Abstract/FREE Full Text
  4. 4.↵
    1. Le Bihan D
    . Diffusion, perfusion and functional magnetic resonance imaging. J Mal Vasc 1995;20:203–14
    PubMed
  5. 5.↵
    1. Le Bihan D,
    2. Breton E,
    3. Lallemand D,
    4. et al
    . MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986;161:401–07
    CrossRefPubMed
  6. 6.↵
    1. Chenevert TL,
    2. Brunberg JA,
    3. Pipe JG
    . Anisotropic diffusion in human white matter: demonstration with MR techniques in vivo. Radiology 1990;177:401–05
    PubMed
  7. 7.↵
    1. Basser PJ,
    2. Pierpaoli C
    . Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 1996;111:209–19
    CrossRefPubMed
  8. 8.↵
    1. Buchsbaum MS,
    2. Tang CY,
    3. Peled S,
    4. et al
    . MRI white matter diffusion anisotropy and PET metabolic rate in schizophrenia. Neuroreport 1998;9:425–30
    CrossRefPubMed
  9. 9.↵
    1. Werring DJ,
    2. Clark CA,
    3. Barker GJ,
    4. et al
    . Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis. Neurology 1999;52:1626–32
    Abstract/FREE Full Text
  10. 10.↵
    1. Chabriat H,
    2. Pappata S,
    3. Poupon C,
    4. et al
    . Clinical severity in CADASIL related to ultrastructural damage in white matter: in vivo study with diffusion tensor MRI. Stroke 1999;30:2637–43
    Abstract/FREE Full Text
  11. 11.↵
    1. O'Sullivan M,
    2. Summers PE,
    3. Jones DK,
    4. et al
    . Normal-appearing white matter in ischemic leukoaraiosis: a diffusion tensor MRI study. Neurology 2001;57:2307–10
    Abstract/FREE Full Text
  12. 12.↵
    1. Shiraishi A,
    2. Hasegawa Y,
    3. Okada S,
    4. et al
    . Highly diffusion-sensitized tensor imaging of unilateral cerebral arterial occlusive disease. AJNR Am J Neuroradiol 2005;26:1498–504
    Abstract/FREE Full Text
  13. 13.↵
    1. Miyamoto S,
    2. Kikuchi H,
    3. Karasawa J,
    4. et al
    . Study of the posterior circulation in Moyamoya disease. Clinical and neuroradiological evaluation. J Neurosurg 1984;61:1032–37
    PubMed
  14. 14.↵
    1. Kim SK,
    2. Wang KC,
    3. Oh CW,
    4. et al
    . Evaluation of cerebral hemodynamics with perfusion MRI in childhood Moyamoya disease. Pediatr Neurosurg 2003;38:68–75
    CrossRefPubMed
  15. 15.↵
    1. Tanaka Y,
    2. Nariai T,
    3. Nagaoka T,
    4. et al
    . Quantitative evaluation of cerebral hemodynamics in patients with Moyamoya disease by dynamic susceptibility contrast magnetic resonance imaging—comparison with positron emission tomography. J Cereb Blood Flow Metab 2006;26:291–300
    CrossRefPubMed
  16. 16.↵
    1. Yun TJ,
    2. Cheon JE,
    3. Na DG,
    4. et al
    . Childhood Moyamoya disease: quantitative evaluation of perfusion MR imaging—correlation with clinical outcome after revascularization surgery. Radiology 2009;251:216–23
    CrossRefPubMed
  17. 17.↵
    1. Lee SK,
    2. Kim DI,
    3. Jeong EK,
    4. et al
    . Postoperative evaluation of Moyamoya disease with perfusion-weighted MR imaging: initial experience. AJNR Am J Neuroradiol 2003;24:741–47
    Abstract/FREE Full Text
  18. 18.↵
    1. Fukui M
    . Guidelines for the diagnosis and treatment of spontaneous occlusion of the circle of Willis (‘Moyamoya' disease). Research Committee on Spontaneous Occlusion of the Circle of Willis (Moyamoya Disease) of the Ministry of Health and Welfare, Japan. Clin Neurol Neurosurg 1997;99 Suppl 2:S238–40
    PubMed
  19. 19.↵
    1. Ostergaard L,
    2. Weisskoff RM,
    3. Chesler DA,
    4. et al
    . High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: mathematical approach and statistical analysis. Magn Reson Med 1996;36:715–25
    CrossRefPubMed
  20. 20.↵
    1. Ostergaard L,
    2. Sorensen AG,
    3. Kwong KK,
    4. et al
    . High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: experimental comparison and preliminary results. Magn Reson Med 1996;36:726–36
    CrossRefPubMed
  21. 21.↵
    1. Houkin K,
    2. Nakayama N,
    3. Kuroda S,
    4. et al
    . Novel magnetic resonance angiography stage grading for Moyamoya disease. Cerebrovasc Dis 2005;20:347–54
    CrossRefPubMed
  22. 22.↵
    1. Cao Y,
    2. Whalen S,
    3. Huang J,
    4. et al
    . Asymmetry of subinsular anisotropy by in vivo diffusion tensor imaging. Hum Brain Mapp 2003;20:82–90
    CrossRefPubMed
  23. 23.↵
    1. Guo AC,
    2. MacFall JR,
    3. Provenzale JM
    . Multiple sclerosis: diffusion tensor MR imaging for evaluation of normal-appearing white matter. Radiology 2002;222:729–36
    PubMed
  24. 24.↵
    1. Pantoni L,
    2. Garcia JH
    . Pathogenesis of leukoaraiosis: a review. Stroke 1997;28:652–59
    Abstract/FREE Full Text
  25. 25.↵
    1. Helenius J,
    2. Soinne L,
    3. Salonen O,
    4. et al
    . Leukoaraiosis, ischemic stroke, and normal white matter on diffusion-weighted MRI. Stroke 2002;33:45–50
    Abstract/FREE Full Text
  26. 26.↵
    1. Soinne L,
    2. Helenius J,
    3. Saimanen E,
    4. et al
    . Brain diffusion changes in carotid occlusive disease treated with endarterectomy. Neurology 2003;61:1061–65
    Abstract/FREE Full Text
  27. 27.↵
    1. O'Sullivan M,
    2. Morris RG,
    3. Huckstep B,
    4. et al
    . Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis. J Neurol Neurosurg Psychiatry 2004;75:441–47
    Abstract/FREE Full Text
  28. 28.↵
    1. Engelter ST,
    2. Provenzale JM,
    3. Petrella JR,
    4. et al
    . The effect of aging on the apparent diffusion coefficient of normal-appearing white matter. AJR Am J Roentgenol 2000;175:425–30
    PubMed
  29. 29.↵
    1. Mori N,
    2. Miki Y,
    3. Fushimi Y,
    4. et al
    . Cerebral infarction associated with Moyamoya disease: histogram-based quantitative analysis of diffusion tensor imaging—a preliminary study. Magn Reson Imaging 2008;26:835–40
    CrossRefPubMed
  30. 30.↵
    1. Conklin J,
    2. Fierstra J,
    3. Crawley AP,
    4. et al
    . Impaired cerebrovascular reactivity with steal phenomenon is associated with increased diffusion in white matter of patients with Moyamoya disease. Stroke 2010;41:1610–16
    Abstract/FREE Full Text
  31. 31.↵
    1. Jones DK
    . The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn Reson Med 2004;51:807–15
    CrossRefPubMed
  • Received February 28, 2011.
  • Accepted after revision March 10, 2011.
  • © 2011 by American Journal of Neuroradiology
View Abstract
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 32 (10)
American Journal of Neuroradiology
Vol. 32, Issue 10
1 Nov 2011
  • Table of Contents
  • Index by author
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Changes in Integrity of Normal-Appearing White Matter in Patients with Moyamoya Disease: A Diffusion Tensor Imaging Study
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
H. Jeong, J. Kim, H.S. Choi, E.S. Kim, D.-S. Kim, K.-W. Shim, S.-K. Lee
Changes in Integrity of Normal-Appearing White Matter in Patients with Moyamoya Disease: A Diffusion Tensor Imaging Study
American Journal of Neuroradiology Nov 2011, 32 (10) 1893-1898; DOI: 10.3174/ajnr.A2683

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Changes in Integrity of Normal-Appearing White Matter in Patients with Moyamoya Disease: A Diffusion Tensor Imaging Study
H. Jeong, J. Kim, H.S. Choi, E.S. Kim, D.-S. Kim, K.-W. Shim, S.-K. Lee
American Journal of Neuroradiology Nov 2011, 32 (10) 1893-1898; DOI: 10.3174/ajnr.A2683
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • Abbreviations
    • Materials and Methods
    • Results
    • Discussion
    • Conclusions
    • References
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • MR Diffusional Kurtosis Imaging-Based Assessment of Brain Microstructural Changes in Patients with Moyamoya Disease before and after Revascularization
  • Chronic Ischemia Alters Brain Microstructural Integrity and Cognitive Performance in Adult Moyamoya Disease
  • Crossref (17)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • Chronic Ischemia Alters Brain Microstructural Integrity and Cognitive Performance in Adult Moyamoya Disease
    Ken Kazumata, Khin Khin Tha, Hisashi Narita, Ichiro Kusumi, Hideo Shichinohe, Masaki Ito, Naoki Nakayama, Kiyohiro Houkin
    Stroke 2015 46 2
  • Reversibility of White Matter Hyperintensity by Revascularization Surgery in Moyamoya Disease
    Katsuya Komatsu, Takeshi Mikami, Shouhei Noshiro, Kei Miyata, Masahiko Wanibuchi, Nobuhiro Mikuni
    Journal of Stroke and Cerebrovascular Diseases 2016 25 6
  • Cognitive reserve moderates the relationship between neuropsychological performance and white matter fiber bundle length in healthy older adults
    Laurie M. Baker, David H. Laidlaw, Ryan Cabeen, Erbil Akbudak, Thomas E. Conturo, Stephen Correia, David F. Tate, Jodi M. Heaps-Woodruff, Matthew R. Brier, Jacob Bolzenius, Lauren E. Salminen, Elizabeth M. Lane, Amanda R. McMichael, Robert H. Paul
    Brain Imaging and Behavior 2017 11 3
  • Executive Function and Diffusion in Frontal White Matter of Adults with Moyamoya Disease
    Akira Nakamizo, Yuichiro Kikkawa, Akio Hiwatashi, Toshio Matsushima, Tomio Sasaki
    Journal of Stroke and Cerebrovascular Diseases 2014 23 3
  • Application of DTI and fMRI in moyamoya disease
    Xiaokuan Hao, Ziqi Liu, Shihao He, Yanru Wang, Yuanli Zhao, Rong Wang
    Frontiers in Neurology 2022 13
  • Pathophysiological consideration of medullary streaks on FLAIR imaging in pediatric moyamoya disease
    Hime Suzuki, Takeshi Mikami, Tomoyoshi Kuribara, Kazuhisa Yoshifuji, Katsuya Komatsu, Yukinori Akiyama, Hirofumi Ohnishi, Kiyohiro Houkin, Nobuhiro Mikuni
    Journal of Neurosurgery: Pediatrics 2017 19 5
  • Neuroimaging in Moyamoya angiopathy: Updated review
    E. Filimonova, K. Ovsiannikov, J. Rzaev
    Clinical Neurology and Neurosurgery 2022 222
  • Early Diffusion Magnetic Resonance Imaging Changes in Normal-Appearing Brain in Pediatric Moyamoya Disease
    Jennifer L Quon, Lily H Kim, Sarah J MacEachern, Maryam Maleki, Gary K Steinberg, Venkatesh Madhugiri, Michael S B Edwards, Gerald A Grant, Kristen W Yeom, Nils D Forkert
    Neurosurgery 2020 86 4
  • MR Diffusional Kurtosis Imaging–Based Assessment of Brain Microstructural Changes in Patients with Moyamoya Disease before and after Revascularization
    P.-G. Qiao, X. Cheng, G.-J. Li, P. Song, C. Han, Z.-H. Yang
    American Journal of Neuroradiology 2020 41 2
  • Apparent Diffusion Coefficient and Transient Neurological Deficit after Revascularization Surgery in Moyamoya Disease
    Yoshio Araki, Yasushi Takagi, Yasutaka Fushimi, Yoshiki Arakawa, Takeshi Funaki, Takayuki Kikuchi, Jun C. Takahashi, Kaori Togashi, Susumu Miyamoto
    Journal of Stroke and Cerebrovascular Diseases 2015 24 9

More in this TOC Section

  • Statin Therapy Does Not Affect the Radiographic and Clinical Profile of Patients with TIA and Minor Stroke
  • Usefulness of Quantitative Susceptibility Mapping for the Diagnosis of Parkinson Disease
  • White Matter Alterations in the Brains of Patients with Active, Remitted, and Cured Cushing Syndrome: A DTI Study
Show more BRAIN

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner
  • Book Reviews

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire