Chapter title |
Increasing the Contrast-to-Noise Ratio of MRI Signals for Regional Assessment of Dynamic Cerebral Autoregulation
|
---|---|
Chapter number | 32 |
Book title |
Intracranial Pressure & Neuromonitoring XVI
|
Published in |
Acta neurochirurgica Supplement, January 2018
|
DOI | 10.1007/978-3-319-65798-1_32 |
Pubmed ID | |
Book ISBNs |
978-3-31-965797-4, 978-3-31-965798-1
|
Authors |
José L. Jara, Nazia P. Saeed, Ronney B. Panerai, Thompson G. Robinson |
Abstract |
To devise an appropriate measure of the quality of a magnetic resonance imaging (MRI) signal for the assessment of dynamic cerebral autoregulation, and propose simple strategies to improve its quality. Magnetic resonance images of 11 healthy subjects were scanned during a transient decrease in arterial blood pressure (BP). Mean signals were extracted from non-overlapping brain regions for each image. An ad-hoc contrast-to-noise ratio (CNR) was used to evaluate the quality of these regional signals. Global mean signals were obtained by averaging the set of regional signals resulting after applying a Hampel filter and discarding a proportion of the lower quality component signals. Significant improvements in CNR values of global mean signals were obtained, whilst maintaining significant correlation with the original ones. A Hampel filter with a small moving window and a low rejection threshold combined with a selection of the 50% component signals seems a recommendable option. This work has demonstrated the possibility of improving the quality of MRI signals acquired during transient drops in BP. This approach needs validation at a voxel level, which could help to consolidate MRI as a technological alternative to the standard techniques for the study of cerebral autoregulation. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 9 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 2 | 22% |
Student > Postgraduate | 2 | 22% |
Researcher | 1 | 11% |
Librarian | 1 | 11% |
Unknown | 3 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Nursing and Health Professions | 2 | 22% |
Neuroscience | 2 | 22% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 11% |
Medicine and Dentistry | 1 | 11% |
Unknown | 3 | 33% |