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. Author manuscript; available in PMC: 2022 Mar 4.
Published in final edited form as: Proc Des Med Devices Conf. 2020 Jul 27;2020:V001T06A006. doi: 10.1115/dmd2020-9042

Minimizing cotton ball retention in neurological procedures

Raphael Bechtold 1,1, Benjamin Garlow 2, Renee Liu 3, Arushi Tandon 4, Alexandra Szewc 5, William Zhu 6, Olivia Musmanno 7, Noah Gorelick 8, Ian Suk 9, Judy Huang 10, Henry Brem 11, Amir Manbachi 12, George Coles 13
PMCID: PMC8895243  NIHMSID: NIHMS1779204  PMID: 35253016

Abstract

Neurosurgical operations are long and intensive medical procedures, during which the surgeon must constantly have an unobscured view of the brain in order to be able to properly operate, and thus must use a variety of tools to clear obstructions (like blood and fluid) from the operating area. Currently, cotton balls are the most versatile and effective option to accomplish this as they absorb fluids, are soft enough to safely manipulate the brain, act as a barrier between other tools and the brain, and function as a spacer to keep anatomies of the brain open and visible during the operation. While cotton balls allow neurosurgeons to effectively improve visibility of the operating area, they may also be accidentally left in the brain upon completion of the surgery. This can lead to a wide range of post-operative risks including dangerous immune responses, additional medical care or surgical operations, and even death. This project seeks to develop a unique medical device that utilizes ultrasound technology in order to minimize cotton retention after neurosurgical procedures in order to reduce undesired post-operative risks, and maximize visibility.

Keywords: Cotton balls, Ultrasound, Textiloma, Visibility

INTRODUCTION

Approximately 22.6 million people around the world are affected by a neurological injury or disorder every year, and 13.8 million of those patients need a surgical operation3. This constitutes 13.8 million opportunities annually for cotton balls to be used during surgery and potentially left behind post-operatively. Therefore, maintaining unobstructed visibility throughout surgery while simultaneously prioritizing surgical patient well-being is critical. Surgical cotton left unintentionally can cause seizures, epilepsy, memory loss, and headaches which may end up being permanent1,2. Retained cotton can also induce potentially life-threatening immunologic responses, impair post-operative imaging, lead to a misdiagnosis, and will always require an additional correctional surgery1,3,4. Retained cotton may not present symptoms for months or years postoperatively while the body undergoes an immune response to the aseptic fibrous tissue and a gossypiboma (a foreign object, that is left behind during an operation that radiologically mimics recurrent tumor or abscess) forms around the cotton ball. There have been 50 recorded cases of gossypiboma since 19731. Moreover, the accidental retention of cotton balls will require additional medical care or surgical operations for patients as well as additional medical expenses and costly lawsuits against the hospital, with the estimated annual cost of retained surgical items being $2.4 million for healthcare systems, as well as 70% of the objects left behind being absorbents2,5. However, there is currently no existing means to reliably detect cotton balls prior to surgical closure. Thus, there is a need for an intraoperative ultrasound device that can effectively detect cotton balls specifically designed for neurosurgical procedures.

1.1. ULTRASOUND TECHNOLOGY FEASIBILITY

Preliminary experiments have been performed using an ultrasound device to detect cotton within a pig brain (fig. 1). First, the pig brain was scanned for a control image (fig. 2a). A ~3cm diameter cotton ball was then wedged into a sulcus on the surface of the pig brain and the probe was used to capture an image (fig. 2b). This was repeated with cotton underneath the brain and similar results were found (fig. 2c). These results are very promising as they show a distinct dark spot where there was cotton. This experiment shows that cotton and brain matter respond to different acoustic frequencies and appear as differentiable materials to an ultrasound device.

Figure 1:

Figure 1:

Pig brain used for ultrasound testing

Figure 2:

Figure 2:

Ultrasound scans of pig brain (2.a), pig brain with cotton the surface (2.b), pig brain with cotton 2cm deep (2.c)

An effective medical device to detect retained cotton would be a custom ultrasound transducer probe head with a 180 degree field of view that is able to rotate 360 degrees so as to detect foreign bodies (fig. 3)—namely cotton balls of 3mm diameter or greater—up to 8 cm deep within the brain. The device would be capable of quantifying the contrast between the cotton and the blood-brain background by automatically detecting cotton through the novel ultrasound probe and an integrated AI software technology. For the purposes of image analytics, the contrast between the cotton and its blood and brain environment may be operationally defined as:

CNR=IcIBIB

where CNR represents the contrast to noise ratio, Ic is the intensity of the ultrasound scan produced by cotton and Ib is the intensity of the ultrasound scan produced by the blood/brain background. Through this contrast definition, a spectral analysis of the data, and a machine learning segmentation algorithm, the AI integrated device will be able to automatically detect cotton in the brain—minimizing cotton retention, and significantly improving patient outcomes.

Figure 3:

Figure 3:

Shows potential design for the foreign body detection device.

ACKNOWLEDGEMENTS

We would like to thank Dr. Amir Manbachi, George Coles, Dr. Judy Huang, Dr. Henry Brem, and Noah Gorelick for their continued support and insight on this project.

Contributor Information

Raphael Bechtold, Johns Hopkins University, Baltimore, Maryland, United States.

Benjamin Garlow, Johns Hopkins University, Baltimore, Maryland, United States.

Renee Liu, Johns Hopkins University, Baltimore, Maryland, United States.

Arushi Tandon, Johns Hopkins University, Baltimore, Maryland, United States.

Alexandra Szewc, Johns Hopkins University, Baltimore, Maryland, United States.

William Zhu, Johns Hopkins University, Baltimore, Maryland, United States.

Olivia Musmanno, Johns Hopkins University, Baltimore, Maryland, United States.

Noah Gorelick, Johns Hopkins Medical Institution, Baltimore, Maryland, United States.

Ian Suk, Johns Hopkins Medical Institution, Baltimore, Maryland, United States.

Dr. Judy Huang, Johns Hopkins Medical Institution, Baltimore, Maryland, United States

Dr. Henry Brem, Johns Hopkins Medical Institution, Baltimore, Maryland, United States

Dr. Amir Manbachi, Johns Hopkins Medical Institution, Baltimore, Maryland, United States

George Coles, Applied Physics Laboratory, Laurel, Maryland, United States.

REFERENCES

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