Abstract
Mobile technology has recently been introduced for blood pressure measurements or glucose level controls. In surgical disciplines the use of smartphone applications is mostly restricted as training tools or knowledge resources. Simple surgical procedures which are performed often in certain disciplines may be performed with limited accuracy since routine and overwork of medical staff lead to less awareness to possible mistakes. In these cases simple and effective means are necessary to achieve better patient safety.
In this context, a surgical instrument for ventricular catheter placement in neurosurgical patients was designed which is assisted by measurements undertaken in a smartphone software application specifically visualizing the use of this instrument and achieving better accuracy for catheter positioning. On theoretical ground, the angulation of the catheter trajectory towards the surface of the skull in a coronal reconstructed CT or MR image is determined as the simplified but the most relevant individual parameter for correct ventricular catheter placement. Transfer of a CT/MRI image onto the smartphone can be performed via mail as anonymous file. Using this image, the trajectory measurement can be performed individually in a few steps by calibration of the image size, definition of the frontal entry point, and virtual placement of the instrument on the surface of the skull. Then the angulation can be adjusted and measured to place the catheter’s trajectory towards the ipsilateral ventricle and the catheter length is determined. The parameters are now given by the app and visualized on the image in order to be applied to the surgical site of the patient.
The tool represents a widely available and cost-effective solution as navigation technique which is simple to apply in order to achieve better accuracy in ventricular catheter placement for higher safety in a large cohort of neurosurgical patients.
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Thomale, UW. (2015). Intracranial Ventricular Catheter Placement with a Smartphone Assisted Instrument. In: Rasooly, A., Herold, K. (eds) Mobile Health Technologies. Methods in Molecular Biology, vol 1256. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2172-0_27
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DOI: https://doi.org/10.1007/978-1-4939-2172-0_27
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Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-2171-3
Online ISBN: 978-1-4939-2172-0
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