Morphometric change in intervertebral foramen after percutaneous endoscopic lumbar foraminotomy: an in vivo radiographic study based on three-dimensional foramen reconstruction.

PURPOSE: This study aimed to perform in vivo three-dimensional (3D) quantitative measurements of morphometric changes in the foramen in patients with lumbar foraminal stenosis (LFS) undergoing percutaneous endoscopic lumbar foraminotomy (PELF) and investigate the relationship between anatomical changes in the foramen and clinical outcomes. METHODS: We retrospectively reviewed consecutive patients with LFS treated with PELF between January 2016 and September 2020 at our centre. Clinical outcomes were evaluated. Foraminal volume (FV) and foraminal minimal area (FMA) were calculated using a novel vertebral and foramen segmentation method. A comparison of the anatomical parameters of the foramen were conducted between the satisfied and unsatisfied groups divided based on the modified MacNab criteria. RESULTS: A total of 26 eligible patients with a mean follow-up of 3.6 years were enrolled. A significant increase was found in overall FV (71.5%) from 1.436 ± 0.396 to 2.464 ± 0.719 cm3 (P < 0.001) and FMA (109.5%) from 0.849 ± 0.207 to 1.780 ± 0.524 cm2. All clinical outcomes were significantly improved (P < 0.001) after PELF. No significant difference was found in changes in neither FV nor FMA between the two groups. CONCLUSION: Clinical results and foraminal dimensions improved significantly after PELF, indicating that PELF was a prominent technique suitable for LFS because of the direct decompression at impingement structures. No relationship was found between morphometric changes and clinical outcomes, revealing that full-scale endoscopic decompression is necessary and adequate for LFS, and unsatisfactory outcomes are less likely to result from decompression procedure.

A CT Image-Based Virtual Sensing Method to Estimate Bone Drilling Force for Surgical Robots.

OBJECTIVE: Current surgical robots face challenges to understand preoperative images like human surgeons, which hindering robots from making full use of preoperative information to operate stably and efficiently. We offer a method to estimate drilling force information based on preoperative images to provide a priori force information for surgical robots performing bone drilling tasks. METHODS: A visual sensing computing framework is proposed to help robots calculate drill-tissue contact area 3D image information in a one-dimensional signal format. Under this computing framework, a computed tomography (CT) image-weighted bone drilling mechanical model is built, which further considers both targets bone shape and material properties to predict the thrust force, torque, and radial force of a drilling process based on preoperative CT images. RESULTS: The built model can respond to multiple bone drilling process factors, such as personalized surgery plans, varying tissue densities, uneven drilling surfaces, different drilling speeds, feed rates, and drill bit geometries. The best trust force prediction error on bovine bones is 1.13 ± 0.95 N, and the best normalized average prediction error on porcine bones is 0.07 ± 0.08. Experiments in spinal pedicle screw placement surgery also show potential application abilities. CONCLUSION: Our method predicts the bone drilling force well based on preoperative images, providing robots with more efficient preoperative information. SIGNIFICANCE: This work offers a new perspective to study the interaction relationship between robot surgical instruments and tissues with the assistance of preoperative images.

A convenient and stable vertebrae instance segmentation method for transforaminal endoscopic surgery planning.

PURPOSE: Transforaminal endoscopic surgery (TES) is effective for treatment of intervertebral disc-related diseases. To avoid injury to the critical structures, preoperative planning is required to find a safe working channel. Therefore, accurate patient-specific vertebral segmentation is important. The purpose of this work is to develop a convenient, stable and feasible lumbar vertebrae segmentation method for TES planning. METHODS: Based on the chain structure of the spine, an interactive dual-output vertebrae instance segmentation network was designed to segment the specific vertebrae in CT images. First, an initialization locator module was set up to provide an initial locating box. Then the dual-output network was designed to segment two adjacent vertebrae inside the locating box. Finally, iteration was performed until all the expected vertebrae were segmented. RESULTS: Verification on reconstructed public dataset showed that the vertebral segmentation Dice coefficient was 96.8 ± 1.2% and average surface distance (ASD) was 0.25 ± 0.10 mm. For intervertebral foramen (IVF) region, the Dice coefficient was 96.1 ± 1.5% and ASD was 0.29 ± 0.10 mm. For IVF forming region, the Dice coefficient was 93.4 ± 3.1% and ASD was 0.28 ± 0.13 mm. The evaluation on private dataset showed that more than 90% of the segmentation were suitable for TES planning. For IVF region, the Dice coefficient was 94.4 ± 1.8% and ASD was 0.71 ± 0.49 mm. CONCLUSION: This work provides a convenient, stable and feasible segmentation method for lumbar vertebrae, IVF region, and IVF forming region. The segmentation can meet the requirement for TES planning.