Intraoperative tissue classification methods in orthopedic and neurological surgeries: A systematic review

Accurate tissue differentiation during orthopedic and neurological surgeries is critical, given that such surgeries involve operations on or in the vicinity of vital neurovascular structures and erroneous surgical maneuvers can lead to surgical complications. By now, the number of emerging technologies tackling the problem of intraoperative tissue classification methods is increasing. Therefore, this systematic review paper intends to give a general overview of existing technologies. The review was done based on the PRISMA principle and two databases: PubMed and IEEE Xplore. The screening process resulted in 60 full-text papers. The general characteristics of the methodology from extracted papers included data processing pipeline, machine learning methods if applicable, types of tissues that can be identified with them, phantom used to conduct the experiment, and evaluation results. This paper can be useful in identifying the problems in the current status of the state-of-the-art intraoperative tissue classification methods and designing new enhanced techniques

Automatic breach detection during spine pedicle drilling based on vibroacoustic sensing

Pedicle drilling is a complex and critical spinal surgery task. Detecting breach or penetration of the surgical tool to the cortical wall during pilot-hole drilling is essential to avoid damage to vital anatomical structures adjacent to the pedicle, such as the spinal cord, blood vessels, and nerves. Currently, the guidance of pedicle drilling is done using image-guided methods that are radiation intensive and limited to the preoperative information. This work proposes a new radiation-free breach detection algorithm leveraging a non-visual sensor setup in combination with deep learning approach. Multiple vibroacoustic sensors, such as a contact microphone, a free-field microphone, a tri-axial accelerometer, a uni-axial accelerometer, and an optical tracking system were integrated into the setup. Data were collected on four cadaveric human spines, ranging from L5 to T10. An experienced spine surgeon drilled the pedicles relying on optical navigation. A new automatic labeling method based on the tracking data was introduced. Labeled data was subsequently fed to the network in mel-spectrograms, classifying the data into breach and non-breach. Different sensor types, sensor positioning, and their combinations were evaluated. The best results in breach recall for individual sensors could be achieved using contact microphones attached to the dorsal skin (85.8\%) and uni-axial accelerometers clamped to the spinous process of the drilled vertebra (81.0\%). The best-performing data fusion model combined the latter two sensors with a breach recall of 98\%. The proposed method shows the great potential of non-visual sensor fusion for avoiding screw misplacement and accidental bone breaches during pedicle drilling and could be extended to further surgical applications

Influence of Artificial Soft Tissue on Intra-Operative Vibration Analysis Method for Primary Fixation Monitoring in Cementless Total Hip Arthroplasty

In cementless Total Hip Arthroplasty (THA), achieving high primary implant fixation is crucial for the long-term survivorship of the femoral stem. While orthopedic surgeons traditionally assess fixation based on their subjective judgement, novel vibration-analysis fixation-monitoring techniques show promising potential in providing the surgeon with objective and quantifiable fixation measurements. This study presents a dynamic response measurement protocol for implant endpoint insertion and evaluates this protocol in the presence of artificial soft tissue. After the artificial femur was prepared in accordance with the THA protocol, the implant was inserted and progressively hammered into the cavity. The Pearson Correlation Coefficient (PCC) and Frequency Response Assurance Criterion (FRAC) corresponding to each insertion hammer hit were derived from the Frequency Response Functions (FRF) corresponding to each insertion step. The protocol was repeated with the artificial femur submerged in artificial soft tissue to imitate the influence of anatomical soft tissue. The FRAC appeared overall more sensitive than the PCC. In the presence of the artificial soft tissue the technique yielded higher PCC and FRAC values earlier in the insertion process. The measurements with artificial soft tissue produced FRFs with fewer peaks, lower resonance frequencies, and overall higher damping factors. The soft tissue appears to limit the fixation-change detection capabilities of the system and a promising potential remedy to this limitation is suggested

Motivating arm-hand use for stroke patients by serious games

\u3cp\u3eWe present a novel technology to support playful rehabilitation of arm-hand performance for stroke survivors. The system combines tangible tabletop interaction with wearable technology, to encourage stroke patients to train their arm-hand skills in a task-oriented manner, while a jacket supporting tilt-sensing and vibrotactile feedback guides patients regarding the correct execution of exercises and specifically to avoid compensatory movements. We present the iterative client centered development of this technology and its on going development.\u3c/p\u3