Literature DB >> 12684979

[Analysis of dot-like hemosiderin spots using brain dock system].

Yoshifumi Horita1, Toshio Imaizumi, Jun Niwa, Junpei Yoshikawa, Kei Miyata, Takeshi Makabe, Ryo Moriyama, Kiyofumi Kurokawa, Masashi Mikami, Manami Nakamura.   

Abstract

BACKGROUND AND
PURPOSE: Dot-like low intensity spots (a dot-like hemosiderin spot: dotHS) on T2*-weighted MR images (T2*WI), which is regarded as a sensitive method for hemosiderin detection, have been histologically diagnosed as old microbleeds associated with microangiopathies. The clinical significance of the dotHS, however, is still under debate. Therefore, we investigated the factors associated with dotHS.
METHODS: We investigated 209 healthy volunteers in our hospital (sex: 106 males, 103 females; age: 38 to 78 years old, mean age: 56.4 +/- 8.3 years old) using "Brain Dock", a formalized screening system for asymptomatic brain diseases. The Odds ratio (OR) was estimated from multiple logistic regression analyses using the dotHS and variables.
RESULTS: T2*WI demonstrated dotHS in 7.7% of volunteers, and the mean number of dotHS was 0.16 +/- 0.78. The hemosiderin was preferentially deposited in the basal ganglia and thalamus. Age > or = 65 years old (OR: 5.9; 95% confidence interval [CI]: 1.4-25.9; p = 0.02), hypertension (OR: 7.0; 95% CI: 1.4-34.7; p = 0.02), and headache (OR: 5.8; 95% CI: 1.4-24.6; p = 0.02) were all found to be independently associated with dotHS.
CONCLUSIONS: The dotHS was significantly associated with several factors, including age, hypertension and headache.

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Year:  2003        PMID: 12684979

Source DB:  PubMed          Journal:  No Shinkei Geka        ISSN: 0301-2603


  5 in total

Review 1.  Distribution of cerebral microbleeds in the East and West: Individual participant meta-analysis.

Authors:  Yusuke Yakushiji; Duncan Wilson; Gareth Ambler; Andreas Charidimou; Alexa Beiser; Mark A van Buchem; Charles DeCarli; Ding Ding; Villi Gudnason; Hideo Hara; Toshio Imaizumi; Katsuhiko Kohara; Hyung-Min Kwon; Lenore J Launer; Vincent Mok; Thanh Phan; Sarah R Preis; José Rafael Romero; Sudha Seshadri; Velandai Srikanth; Yuki Takashima; Yoshito Tsushima; Zhaolu Wang; Philip A Wolf; Yunyun Xiong; Shuhei Yamaguchi; David J Werring
Journal:  Neurology       Date:  2019-02-01       Impact factor: 9.910

2.  Cerebral microbleeds in a multiethnic elderly community: demographic and clinical correlates.

Authors:  Anne F Wiegman; Irene B Meier; Nicole Schupf; Jennifer J Manly; Vanessa A Guzman; Atul Narkhede; Yaakov Stern; Sergi Martinez-Ramirez; Anand Viswanathan; José A Luchsinger; Steven M Greenberg; Richard Mayeux; Adam M Brickman
Journal:  J Neurol Sci       Date:  2014-07-18       Impact factor: 3.181

Review 3.  Cerebral microbleeds: a guide to detection and interpretation.

Authors:  Steven M Greenberg; Meike W Vernooij; Charlotte Cordonnier; Anand Viswanathan; Rustam Al-Shahi Salman; Steven Warach; Lenore J Launer; Mark A Van Buchem; Monique Mb Breteler
Journal:  Lancet Neurol       Date:  2009-02       Impact factor: 44.182

4.  Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning.

Authors:  Vaanathi Sundaresan; Christoph Arthofer; Giovanna Zamboni; Robert A Dineen; Peter M Rothwell; Stamatios N Sotiropoulos; Dorothee P Auer; Daniel J Tozer; Hugh S Markus; Karla L Miller; Iulius Dragonu; Nikola Sprigg; Fidel Alfaro-Almagro; Mark Jenkinson; Ludovica Griffanti
Journal:  Front Neuroinform       Date:  2022-01-20       Impact factor: 4.081

5.  Incidental Intracranial Findings and Their Clinical Impact; The HUNT MRI Study in a General Population of 1006 Participants between 50-66 Years.

Authors:  Asta Kristine Håberg; Tommy Arild Hammer; Kjell Arne Kvistad; Jana Rydland; Tomm B Müller; Live Eikenes; Mari Gårseth; Lars Jacob Stovner
Journal:  PLoS One       Date:  2016-03-07       Impact factor: 3.240

  5 in total

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