Abstract
Objective: We designed, prototyped, and tested a system that measures the viscoelastic response of tissue using nondestructive mechanical probing, with the goal of aiding clinical providers during epidural needle placement. This system is meant to alert clinicians when an epidural needle is about to strike bone during insertion. Methods: During needle insertion, the system periodically mechanically stimulates and collects viscoelastic response information data from the tissue at the needle’s tip using an intra-needle probe. A machine-learning algorithm detects when the needle is close to bone using the series of observed stimulations. Results: Tests run on ex vivo pig spine show that the system can reliably determine if the needle is pointed at and within 3 mm of bone. Conclusion: Our technique can successfully differentiate materials at and in front of the needle’s tip. However, it does not provide the 5 mm of forewarning that we believe would be necessary for use in clinical epidural needle placement. The technique may be of use in other applications requiring tissue differentiation during needle placement or in the intended application with further technical advances. Clinical and Translational Impact Statement: This Early/Pre-Clinical Research evaluates the feasibility of a method for helping clinical providers receive feedback during epidural needle insertion—thereby reducing complication rates—without significant alterations from current workflow.
Highlights
Several medical procedures require primary physicians or clinicians to blindly insert needles into precise locations with little feedback, leading to high complication rates. One such procedure is epidural needle placement. This procedure is typically performed by anesthesiologists, who must precisely guide a needle between a patient’s vertebrae and into a 2–7 mm wide area known as the epidural space [1]
Improving the efficacy of epidural needle insertion could immediately improve healthcare outcomes, for women undergoing childbirth, people with chronic pain, and patients undergoing surgical procedures aided by epidural anesthesia, which is used in several types of orthopedic and gastrointestinal surgeries
The best high-bias-low-variance results (SVM, Subsequence Force FFTs, test/train) show that we can consistently detect when the needle is within 3.33 mm of bone based on an average error and mean absolute error (MAE) of 1.67 mm. These results indicate that, in general, our bone detection method works: it detects when the needle is near bone before the needle strikes the bone with only 20% the error of random guessing which, during a theoretical 40 mm needle insertion, would result in an average error of -15 mm, MAE of 15.68 mm, and root mean square error (RMSE) of 19.02 mm
Summary
Several medical procedures require primary physicians or clinicians to blindly insert needles into precise locations with little feedback, leading to high complication rates. One such procedure is epidural needle placement. This manuscript was submitted for review on January 8, 2022. Other medical procedures requiring precise needle placement may benefit from such improvements
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