Advances in tissue state recognition in spinal surgery: a review
Hao Qu, Yu Zhao
Advances in tissue state recognition in spinal surgery: a review
Spinal disease is an important cause of cervical discomfort, low back pain, radiating pain in the limbs, and neurogenic intermittent claudication, and its incidence is increasing annually. From the etiological viewpoint, these symptoms are directly caused by the compression of the spinal cord, nerve roots, and blood vessels and are most effectively treated with surgery. Spinal surgeries are primarily performed using two different techniques: spinal canal decompression and internal fixation. In the past, tactile sensation was the primary method used by surgeons to understand the state of the tissue within the operating area. However, this method has several disadvantages because of its subjectivity. Therefore, it has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognition, improve the accuracy of safe area location, and avoid surgical injury to tissues. Aside from traditional imaging methods, surgical sensing techniques based on force, bioelectrical impedance, and other methods have been gradually developed and tested in the clinical setting. This article reviews the progress of different tissue state recognition methods in spinal surgery and summarizes their advantages and disadvantages.
spinal surgery / tissue state recognition / image / force sensing / bioelectrical impedance
Tab.1 Different methods for tissue state recognition |
Technology | Application | Advantages | Disadvantages |
---|---|---|---|
Imaging | C-arm, O-arm, AR, VR, MR, … | Provides accurate tissue location Improves the accuracy of operation | Fuzzy tissue type information Delays Cannot directly obtain physiologic information |
Force sensing | Surgical instruments with force sensors | Has strong specificity Has been applied to clinical practice | Different operative methods, speed, etc. affect the force signal Lack of research on force feedback to the operator |
Bioelectrical impedance | Health risk assessment system, pedicle probe and navigation system based on bioelectrical impedance technology | Reliable principle Simple operation Strong feasibility | Many factors can affect the accuracy of the numerical value Lacks a standard bioelectrical impedance database as a reference Suffers form deviations in data collection |
Physical feature perception | − | Shows specific changes according to different contact tissues | Limited relevant research |
AR, augmented reality; VR, virtual reality; MR, mixed reality. |
Fig.4 Distribution of frequency between 10 and 15 kHz after using the recursive FFT for different moments: (A) drilling the cortical born; (B) cancellous bone; (C) transition region from cortical born to cancellous bone; (D) transition region from cancellous bone to inner cortical born. Reprinted from Ref. [57] with permission. |
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