[Intraoperative navigation system in endoscopic sinus surgery]

Trustworthy and Intelligent COVID-19 Diagnostic IoMT Through XR and Deep-Learning-Based Clinic Data Access

This article presents a novel extended reality (XR) and deep-learning-based Internet-of-Medical-Things (IoMT) solution for the COVID-19 telemedicine diagnostic, which systematically combines virtual reality/augmented reality (AR) remote surgical plan/rehearse hardware, customized 5G cloud computing and deep learning algorithms to provide real-time COVID-19 treatment scheme clues. Compared to existing perception therapy techniques, our new technique can significantly improve performance and security. The system collected 25 clinic data from the 347 positive and 2270 negative COVID-19 patients in the Red Zone by 5G transmission. After that, a novel auxiliary classifier generative adversarial network-based intelligent prediction algorithm is conducted to train the new COVID-19 prediction model. Furthermore, The Copycat network is employed for the model stealing and attack for the IoMT to improve the security performance. To simplify the user interface and achieve an excellent user experience, we combined the Red Zone's guiding images with the Green Zone's view through the AR navigate clue by using 5G. The XR surgical plan/rehearse framework is designed, including all COVID-19 surgical requisite details that were developed with a real-time response guaranteed. The accuracy, recall, F1-score, and area under the ROC curve (AUC) area of our new IoMT were 0.92, 0.98, 0.95, and 0.98, respectively, which outperforms the existing perception techniques with significantly higher accuracy performance. The model stealing also has excellent performance, with the AUC area of 0.90 in Copycat slightly lower than the original model. This study suggests a new framework in the COVID-19 diagnostic integration and opens the new research about the integration of XR and deep learning for IoMT implementation.

The Application of Three-Dimensional Technology Combined With Image Navigation in Nasal Skull Base Surgery

Three-dimensional (3D) technology including 3D reconstruction and 3D printing technology, has been widely used in clinical treatment, especially in surgical planning, and image navigation technology, which can make surgical procedures more accurate, now is also increasingly favored by surgeons. But the combination of those 2 technologies was rarely reported. Thus, this study will preliminarily investigate the feasibility and the effect of the combination of 2 technologies in endonasal skull base surgery. Eight patients were involved in this study (from October 2016 to July 2017 at The Affiliated Hospital of Qingdao University), 5 cases of nasal skull base tumors and 3 cases of foreign body perforation. All operations were done under the assistance of 3D technology and image guidance system. Surgical discussion with patient, preoperative planning and clinical teaching were investigated between 2D images and 3D models by voting. For all cases, 3D reconstruction model and 3D printed model were deemed to be more helpful than CT/MRI images in surgical discussion with the patient; surgical simulation on 3D model in preoperative planning was largely deemed to be helpful and very helpful; and in clinical teaching, 3D models combined with image guidance system were deemed to be more helpful in understanding the disease than using 2D images. Besides, all patients recovered well after surgery, no recurrence and complications were found in the follow-up. The combination of 3D technology and electromagnetic image guidance system could improve surgical efficiency and the quality of clinical teaching.

Robotic Transnasal Endoscopic Skull Base Surgery: Systematic Review of the Literature and Report of a Novel Prototype for a Hybrid System (Brescia Endoscope Assistant Robotic Holder)

BACKGROUND

Although robotics has already been applied to several surgical fields, available systems are not designed for endoscopic skull base surgery (ESBS). New conception prototypes have been recently described for ESBS. The aim of this study was to provide a systematic literature review of robotics for ESBS and describe a novel prototype developed at the University of Brescia.

METHODS

PubMed and Scopus databases were searched using a combination of terms, including Robotics OR Robot and Surgery OR Otolaryngology OR Skull Base OR Holder. The retrieved papers were analyzed, recording the following features: interface, tools under robotic control, force feedback, safety systems, setup time, and operative time. A novel hybrid robotic system has been developed and tested in a preclinical setting at the University of Brescia, using an industrial manipulator and readily available off-the-shelf components.

RESULTS

A total of 11 robotic prototypes for ESBS were identified. Almost all prototypes present a difficult emergency management as one of the main limits. The Brescia Endoscope Assistant Robotic holder has proven the feasibility of an intuitive robotic movement, using the surgeon's head position: a 6 degree of freedom sensor was used and 2 light sources were added to glasses that were therefore recognized by a commercially available sensor.

CONCLUSIONS

Robotic system prototypes designed for ESBS and reported in the literature still present significant technical limitations. Hybrid robot assistance has a huge potential and might soon be feasible in ESBS.