Magnetic resonance velocity imaging derived pressure differential using control volume analysis

• Main Authors: Cohen Benjamin, Voorhees Abram, Wei Timothy
• Format: Article
• Language: English
• Published: BMC 2011-03-01
• Series: Fluids and Barriers of the CNS
• Online Access: http://www.fluidsbarrierscns.com/content/8/1/16

<p>Abstract</p> <p>Background</p> <p>Diagnosis and treatment of hydrocephalus is hindered by a lack of systemic understanding of the interrelationships between pressures and flow of cerebrospinal fluid in the brain. Control volume analysis provides a fluid physics approach to quantify and relate pressure and flow information. The objective of this study was to use control volume analysis and magnetic resonance velocity imaging to non-invasively estimate pressure differentials <it>in vitro</it>.</p> <p>Method</p> <p>A flow phantom was constructed and water was the experimental fluid. The phantom was connected to a high-resolution differential pressure sensor and a computer controlled pump producing sinusoidal flow. Magnetic resonance velocity measurements were taken and subsequently analyzed to derive pressure differential waveforms using momentum conservation principles. Independent sensor measurements were obtained for comparison.</p> <p>Results</p> <p>Using magnetic resonance data the momentum balance in the phantom was computed. The measured differential pressure force had amplitude of 14.4 <it>dynes </it>(pressure gradient amplitude 0.30 <it>Pa/cm</it>). A 12.5% normalized root mean square deviation between derived and directly measured pressure differential was obtained. These experiments demonstrate one example of the potential utility of control volume analysis and the concepts involved in its application.</p> <p>Conclusions</p> <p>This study validates a non-invasive measurement technique for relating velocity measurements to pressure differential. These methods may be applied to clinical measurements to estimate pressure differentials <it>in vivo </it>which could not be obtained with current clinical sensors.</p>