RESUMO
Robotic systems for surgery of the inner ear must enable highly precise movement in relation to the patient. To allow for a suitable collaboration between surgeon and robot, these systems should not interrupt the surgical workflow and integrate well in existing processes. As the surgical microscope is a standard tool, present in almost every microsurgical intervention and due to it being in close proximity to the situs, it is predestined to be extended by assistive robotic systems. For instance, a microscope-mounted laser for ablation. As both, patient and microscope are subject to movements during surgery, a well-integrated robotic system must be able to comply with these movements. To solve the problem of on-line registration of an assistance system to the situs, the standard of care often utilizes marker-based technologies, which require markers being rigidly attached to the patient. This not only requires time for preparation but also increases invasiveness of the procedure and the line of sight of the tracking system may not be obstructed. This work aims at utilizing the existing imaging system for detection of relative movements between the surgical microscope and the patient. The resulting data allows for maintaining registration. Hereby, no artificial markers or landmarks are considered but an approach for feature-based tracking with respect to the surgical environment in otology is presented. The images for tracking are obtained by a two-dimensional RGB stream of a surgical microscope. Due to the bony structure of the surgical site, the recorded cochleostomy scene moves nearly rigidly. The goal of the tracking algorithm is to estimate motion only from the given image stream. After preprocessing, features are detected in two subsequent images and their affine transformation is computed by a random sample consensus (RANSAC) algorithm. The proposed method can provide movement feedback with up to 93.2 µm precision without the need for any additional hardware in the operating room or attachment of fiducials to the situs. In long term tracking, an accumulative error occurs.
RESUMO
INTRODUCTION: Head and neck mucosal melanoma (HNMM) is a rare tumor with a poor outcome. The objective of this study was to assess outcome and prognostic factors for a cohort of patients treated in a head and neck cancer center. In addition, a case series on sentinel lymph node biopsy (SLNB) was included to evaluate it as a method for staging the node-negative neck. METHODS: A retrospective study design was chosen, and 50 patients who were treated from 1973 to 2015 in our institution for primary HNMM were included. The Kaplan-Meier method was used to estimate survival rates. Uni- and multivariate analyses were used to study the influence of possible risk factors on the patients' outcome. These risk factors included patient demographics, tumor characteristics, and treatment modalities. RESULTS: All patients were treated surgically and 50% received adjuvant treatment. The median disease specific survival (DSS) was 38 months, with a 5-year survival rate of 44%. Positive surgical margin (p = 0.004) and distant failure (p = 0.005) were associated with a worse DSS. The median disease-free survival (DFS) was 27 months, with a 5-year disease-free rate of 12%. Only tumor depth >5 mm (p = 0.002) was associated with a worse DFS. Five clinically node-negative patients received SLNB and only the two SLN-positive individuals suffered from distant failure. Radiotherapy, chemotherapy, and AJCC/UICC stage had no influence on any outcome measure. CONCLUSIONS: Positive surgical margin and distant failure are the only independent prognostic factors for DSS. Tumor depth can predict distant failure. SLNB may be a valuable staging tool for the node-negative neck.