{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:15:08Z","timestamp":1789992908554,"version":"4.0.1"},"reference-count":27,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>Cerebrospinal fluid (CSF) shunts are the primary treatment for patients suffering from hydrocephalus. While proven effective in symptom relief, these shunt systems are plagued by high failure rates and often require repeated revision surgeries to replace malfunctioning components. One of the leading causes of CSF shunt failure is obstruction of the ventricular catheter by aggregations of cells, proteins, blood clots, or fronds of choroid plexus that occlude the catheter\u2019s small inlet holes or even the full internal catheter lumen. Such obstructions can disrupt CSF diversion out of the ventricular system or impede it entirely. Previous studies have suggested that altering the catheter\u2019s fluid dynamics may help to reduce the likelihood of complete ventricular catheter failure caused by obstruction. However, systematic correlation between a ventricular catheter\u2019s design parameters and its performance, specifically its likelihood to become occluded, still remains unknown. Therefore, an automated, open-source computational fluid dynamics (CFD) simulation framework was developed for use in the medical community to determine optimized ventricular catheter designs and to rapidly explore parameter influence for a given flow objective.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>The computational framework was developed by coupling a 3D CFD solver and an iterative optimization algorithm and was implemented in a high-performance computing environment. The capabilities of the framework were demonstrated by computing an optimized ventricular catheter design that provides uniform flow rates through the catheter\u2019s inlet holes, a common design objective in the literature. The baseline computational model was validated using 3D nuclear imaging to provide flow velocities at the inlet holes and through the catheter.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The optimized catheter design achieved through use of the automated simulation framework improved significantly on previous attempts to reach a uniform inlet flow rate distribution using the standard catheter hole configuration as a baseline. While the standard ventricular catheter design featuring uniform inlet hole diameters and hole spacing has a standard deviation of 14.27% for the inlet flow rates, the optimized design has a standard deviation of 0.30%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>This customizable framework, paired with high-performance computing, provides a rapid method of design testing to solve complex flow problems. While a relatively simplified ventricular catheter model was used to demonstrate the framework, the computational approach is applicable to any baseline catheter model, and it is easily adapted to optimize catheters for the unique needs of different patients as well as for other fluid-based medical devices.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3171\/2017.5.jns161882","type":"journal-article","created":{"date-parts":[[2017,11,10]],"date-time":"2017-11-10T09:59:22Z","timestamp":1510307962000},"page":"1067-1077","source":"Crossref","is-referenced-by-count":13,"title":["A computational fluid dynamics simulation framework for ventricular catheter design optimization"],"prefix":"10.3171","volume":"129","author":[{"given":"Sofy H.","family":"Weisenberg","sequence":"first","affiliation":[{"name":"Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephanie C.","family":"TerMaath","sequence":"additional","affiliation":[{"name":"Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlotte N.","family":"Barbier","sequence":"additional","affiliation":[{"name":"Instrument and Source Division, Spallation Neutron Source, and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Judith C.","family":"Hill","sequence":"additional","affiliation":[{"name":"Scientific Computing Group, National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A.","family":"Killeffer","sequence":"additional","affiliation":[{"name":"Division of Neurosurgery, Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, Tennessee"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1754","reference":[{"key":"b1","series-title":"Pediatr Neurosurg","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1159\/000319365","article-title":"Long-term outcome after treatment of hydrocephalus in children","volume":"46","author":"Appelgren T","year":"2010","unstructured":"Appelgren T, Zetterstrand S, Elfversson J, Nilsson D: Long-term outcome after treatment of hydrocephalus in children. 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