# Automatic Needle Route Proposal in Preoperative Neck CT for Injection Laryngoplasty
## 1 Introduction  
Vocal fold paresis is a prevalent condition that causes a glottal gap leading to problems ranging from voice discomfort to breathing difficulty and other respiratory issues [1]. Transcutaneous injection laryngoplasty (TIL) is an office-based vocal fold augmentation method for treating vocal fold paresis [2]. In this method, augmentation material is usually injected through the cricothyroid membrane into the affected vocal fold to reduce the glottal gap [3]. One of the major challenges of this procedure is to determine the optimal site and route of the injecting needle [4]. This is because laryngeal anatomy varies across patients and the needle tip is not visible during the procedure under endoscopic guidance. Generally, neck CT scans are shown to be helpful for preoperative planning in injection laryngoplasty by providing a superior perception of the laryngeal anatomy [5]. However, identifying the optimal needle route in the 2D view of CT slices is time-consuming and requires a substantial amount of prior experience. Thus, an automatic method for identifying the optimal needle route in preoperative CT can be useful for preprocedural planning. In addition, training residents in performing TIL is difficult due to the nature of this procedure being typically carried out in an office setting. Hence, having neck CT volumes with automated needle trajectory annotations can prove to be beneficial in this regard as well.  
Existing works related to the optimal needle route for TIL are strictly limited to manual annotation approaches. [PERSON] et al. [3] presented a comparative study on needle routes based on neck CT volumes of different patients, where the needle routes were manually annotated. [PERSON] et al. [4] and [PERSON] et al. [6] suggested 3D printing of the larynx to improve the perception of the injection route before the TIL procedure. A comprehensive medical guide for determining the injection route was presented by [PERSON] et al. [2]. In our earlier work [7], we trained a reinforcement learning (RL) agent to automatically localizethe right and left vocal folds in neck CT. To the best of our knowledge, no previous work has attempted to computationally identify the needle route in neck CT scans.  
In this communication, we propose an automatic method to compute the optimal needle trajectory for TIL. Utilizing the vocal fold locations detected by the RL agent in our previous work [7], we determine the optimal needle route by scanning through all possible linear trajectories from the neck skin to the vocal folds. By carefully investigating the medical routine of TIL, we identify the critical regions and constraints that should be considered while defining the search space. To segment such regions consistently across different patients, we propose a reformulation of the geodesic distance-based segmentation [8]. Finally, we define an appropriate cost function to find the optimal route from the trajectory search space. Furthermore, we experimentally evaluate the proposed method on 136 subjects, where the resultant needle routes are evaluated by an expert laryngologist. Our contribution can be summarized into the following points:  
* We propose the first automatic method to compute the optimal needle route in neck CT for TIL based on critical structure segmentation and minimal cost route search.
* We perform a comprehensive evaluation on neck CT scans of 136 patients, which is carried out by an expert laryngologist.  
We organize the rest of the paper as follows. In Section 2, we describe the proposed method in detail. We present and discuss the experimental evaluation of our method in Section 3. Finally, we present our concluding remarks in Section 4.