Literature DB >> 34969179

Structural abnormalities in paediatric moyamoya disease revealed by clinical magnetic resonance imaging, regionally distributed relative signal intensities and volumes.

Prahar Ijner1, Grace Tompkins2, Tadashi Shiohama3, Emi Takahashi4,5,6, Jacob Levman1.   

Abstract

Moyamoya disease (MMD) is a rare, progressive cerebrovascular disorder, with an unknown aetiology and pathogenesis. It is characterized by steno-occlusive changes at the terminal portion of the internal carotid artery (ICA), which is accompanied by variable development of the basal collaterals called moyamoya vessels. In this study, we investigate the potential for structural T1 magnetic resonance imaging (MRI) to help characterize MMD clinically, with the help of regionally distributed relative signal intensities (RRSIs) and volumes (RRVs). These RRSIs and RRVs provide the ability to characterize aspects of regional brain development and represent an extension to existing automated biomarker extraction technologies. This study included 269 MRI examinations from MMD patients and 993 MRI examinations from neurotypical controls, with regional biomarkers compared between groups with the area under the receiver operating characteristic curve (AUC). Results demonstrate abnormal presentation of RRSIs and RRVs in the insula (15- to 20-year old cohort, left AUC: 0.74, right AUC: 0.71) and the lateral orbitofrontal region (5- to 10-year old cohort, left AUC: 0.67; 15-20 year cohort, left AUC: 0.62, right AUC: 0.65). Results indicate that RRSIs and RRVs may help in characterizing brain development, assist in the assessment of the presentation of the brains of children with MMD and help overcome standardization challenges in multiprotocol clinical MRI. Further investigation of the potential for RRSIs and RRVs in clinical imaging is warranted and supported through the release of open-source software.
© 2021 International Society for Developmental Neuroscience.

Entities:  

Keywords:  biomarker extraction; magnetic resonance imaging; moyamoya

Mesh:

Year:  2022        PMID: 34969179      PMCID: PMC8983520          DOI: 10.1002/jdn.10167

Source DB:  PubMed          Journal:  Int J Dev Neurosci        ISSN: 0736-5748            Impact factor:   2.457


  38 in total

1.  Arterial spin-labeling MRI can identify the presence and intensity of collateral perfusion in patients with moyamoya disease.

Authors:  Greg Zaharchuk; Huy M Do; Michael P Marks; Jarrett Rosenberg; Michael E Moseley; Gary K Steinberg
Journal:  Stroke       Date:  2011-07-28       Impact factor: 7.914

2.  Diagnosis of moyamoya disease using 3-T MRI and MRA: value of cisternal moyamoya vessels.

Authors:  Takeshi Sawada; Akira Yamamoto; Yukio Miki; Ken-Ichiro Kikuta; Tomohisa Okada; Mitsunori Kanagaki; Seiko Kasahara; Susumu Miyamoto; Jun C Takahashi; Hidenao Fukuyama; Kaori Togashi
Journal:  Neuroradiology       Date:  2012-02-21       Impact factor: 2.804

3.  Pediatric moyamoya disease: An analysis of 410 consecutive cases.

Authors:  Seung-Ki Kim; Byung-Kyu Cho; Ji Hoon Phi; Ji Yeoun Lee; Jong Hee Chae; Ki Joong Kim; Yong-Seung Hwang; In-One Kim; Dong Soo Lee; Joongyub Lee; Kyu-Chang Wang
Journal:  Ann Neurol       Date:  2010-07       Impact factor: 10.422

4.  Inter-individual variation in blood pressure is associated with regional white matter integrity in generally healthy older adults.

Authors:  David H Salat; Victoria J Williams; Elizabeth C Leritz; David M Schnyer; James L Rudolph; Lewis A Lipsitz; Regina E McGlinchey; William P Milberg
Journal:  Neuroimage       Date:  2011-07-23       Impact factor: 6.556

5.  Moyamoya disease: diagnostic accuracy of MRI.

Authors:  I Yamada; S Suzuki; Y Matsushima
Journal:  Neuroradiology       Date:  1995-07       Impact factor: 2.804

6.  Posterior circulation in moyamoya disease: angiographic study.

Authors:  I Yamada; Y Himeno; S Suzuki; Y Matsushima
Journal:  Radiology       Date:  1995-10       Impact factor: 11.105

7.  Hemodynamic Impairment Measured by Positron-Emission Tomography Is Regionally Associated with Decreased Cortical Thickness in Moyamoya Phenomenon.

Authors:  J J Lee; J S Shimony; H Jafri; A R Zazulia; R G Dacey; G R Zipfel; C P Derdeyn
Journal:  AJNR Am J Neuroradiol       Date:  2018-10-25       Impact factor: 3.825

8.  High resolution MRI difference between moyamoya disease and intracranial atherosclerosis.

Authors:  Y J Kim; D H Lee; J Y Kwon; D W Kang; D C Suh; J S Kim; S U Kwon
Journal:  Eur J Neurol       Date:  2013-06-21       Impact factor: 6.089

9.  Reduced gray to white matter tissue intensity contrast in schizophrenia.

Authors:  Li Kong; Christina Herold; Bram Stieltjes; Marco Essig; Ulrich Seidl; Robert Christian Wolf; Torsten Wüstenberg; Marc Montgomery Lässer; Lena Anna Schmid; Knut Schnell; Dusan Hirjak; Philipp Arthur Thomann
Journal:  PLoS One       Date:  2012-05-15       Impact factor: 3.240

10.  Identification of RNF213 as a susceptibility gene for moyamoya disease and its possible role in vascular development.

Authors:  Wanyang Liu; Daisuke Morito; Seiji Takashima; Yohei Mineharu; Hatasu Kobayashi; Toshiaki Hitomi; Hirokuni Hashikata; Norio Matsuura; Satoru Yamazaki; Atsushi Toyoda; Ken-ichiro Kikuta; Yasushi Takagi; Kouji H Harada; Asao Fujiyama; Roman Herzig; Boris Krischek; Liping Zou; Jeong Eun Kim; Masafumi Kitakaze; Susumu Miyamoto; Kazuhiro Nagata; Nobuo Hashimoto; Akio Koizumi
Journal:  PLoS One       Date:  2011-07-20       Impact factor: 3.240

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