|Title: Boundary prediction during epidural punctures based on OCT relative motion analysis|
|Written by: S. Latus and P. Breitfeld and M. Neidhardt and W. Reip and C. Zöllner and A. Schlaefer|
|in: EUR J ANAESTH 6 2020|
|Volume: 2020 Number: Volume 37 | e-Supplement 58 | June 2020|
|Publisher: Lippincott Williams and Wilkins|
Abstract: 1 Background and Goal of StudyUntil today, physicians mainly use their haptic impression for the correct po-sitioning of the needle during epidural punctures. ?Blind? techniques such asLoss-of-Resistance (LOR) and saline drop methods [1, 2] help to identify theepidural space, but the error rate is highly dependent on the physician?s exper-tise. The challenge of a direct needle insertion through different tissues into theepidural space with reliable identification of the same and without bone contactrequires a lot of experience from the performer. A penetration into the spinalcolumn space has to be absolutely avoided . Different imaging modalities suchas ultrasound (US)  are used to assist needle navigation task in a few anesthe-sia cases. However, an external tracking of the needle path is limited due to theanatomy around the spinal cord. Hence, optical fibers are integrated in epiduralneedles to enable high-resolution optical coherence tomography (OCT) imagingof the punctured tissue . Deep learning approaches based on morphologicalinformation of OCT intensity data facilitate an online identification of tissuestructures along the needle trajectory . Furthermore, the fiber bragg gratings(FBG) are integrated to measure the forces during punctures . In this study,we propose a novel method to determine both the morphological and mechanicproperties of tissues during epidural punctures. In addition to the intensity theOCT phase data is used to differentiate between tissue structures and identifyruptures and deformations in front of the needle tip in order to detect relevanttissue structures and boundaries.2 Material and MethodsWe perform ex-vivo epidural punctures in a pig cadaver model using an adaptedepidural Tuohy-needle with an integrated forward facing OCT fiber (Fig. 1).During manual punctures we capture ground-truth information of the needlepose and interacting forces at the needle shaft using an optical tracking system(fusion track 500, Atracsys) and a force-torque (FT) sensor (SRI, Sunrise In-struments), respectively. In addition, the physician feeds his haptic impression2S. Latus and P. Breitfeld(e.g. harder or softer resistance in tissues and the sensing of slight click by pen-etrating the ligamentum flavum) and expectation of the boundary interactionsback. We allocate one dimensional OCT depth scans (A-scans) throughout theFig. 1.Setup for OCT deformation analysis during ex-vivo epidural punctures. Theepidural needle is attached to a force torque (FT) sensor with associated trackingmarker. An optical fiber is integrated in the Tuohy-needle enabling a forward facingA-scan acquisitions (bottom right, red dashed line). A physician navigates the OCTneedle towards the epidural space, meanwhile OCT, FT, and tracking data is capturedsynchronously. During epidural puncture the needle needs to be navigated through skin(orange), supraspinous ligament, fat/muscle tissue, and ligamentum flavum (brown)preventing a rupture of the Dura (blue) or a collision with bone structures (gray).punctures applying a spectral domain OCT system (Telesto, Thorlabs) with aconstant A-scan frequency of 91 kHz.Using both the acquired OCT intensity and phase data, we are able to mag-nify the tissue properties in front of the needle towards the haptic feedbacksensed by the FT sensor and physician. We analyze the tissue interactions infront of the needle by means of the relative motion derived from the OCT phasedifferences . An increase of the determined relative motion can be relatedto deformations and following ruptures at tissue boundaries, whereas negativevalues are associated to negative needle motion w.r.t. the tissue. We use thehaptic impression of the physician as ground-truth information for the detectedboundary interactions.Title Suppressed Due to Excessive Length33 Results and DiscussionExemplary, OCT intensity data is shown with overlayed relative motion (greenand red) and measured force in needle direction (blue line) for one epiduralpuncture (Fig. 2). In case of boundary deformations and following ruptures therelative motion increases rapidly (time points B, C, and E). Especially, duringthe puncture of the ligamentum flavum (E to F) multiple ruptures are detecteduntil a LOR is measured with the FT sensor. Between C and D several smallruptures appear due to sinews and muscle structures. In contrast, the highlightedtime points without tissue boundary ruptures (A and D) do not show an increaseof the estimated relative motion. After the bone contact (D) the needle is pulledbackwards and an obvious negative relative motion (red) follows.Fig. 2.OCT intensity and relative motion estimations related to the externally mea-sured forces for an exemplary epidural puncture. The relative motion is depicted ingreen and red for positive and negative values, respectively. The time points (A-F)are related to different needle-tissue interactions: A) Re-orientation of needle, B) firstrupture at skin, C) second rupture at supraspinous ligament, D) bone contact and fol-lowing needle re-orientation, E) start of ruptures at ligamentum flavum, and F) LORafter ligamentum flavum.4 ConclusionWe propose a forward facing OCT needle design to enable the evaluation of both,OCT speckle due to different tissue structures and the relative motion in orderto determine relevant deformations and ruptures at tissue boundaries. Hence,we are able to sense and thereby magnify the tissue mechanics during and priorboundary punctures without additional sensors such as FBGs.