ArticlePhysics in medicine and biology2017
Spinal pedicle screw planning using deformable atlas registration.
Article in Physics in medicine and biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A comprehensive framework for planning pedicle screw trajectory using ANTs template-based registration approach.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Agreement Between Automated Pedicle Screw Planning and Surgeon-Selected Implant Dimensions in Thoracic and Lumbar Spine Surgery: A Three-Year Single-Center Study.Journal of clinical medicine · 2026Article
- Automated multi-objective pedicle screw planning.Journal of spine surgery (Hong Kong) · 2026Article
- Feasibility of automatic screw planning via transformer-based shape completion from RGB-D imaging.Scientific reports · 2025Article
- Development and Validation of Deep Learning Preoperative Planning Software for Automatic Lumbosacral Screw Selection Using Computed Tomography.Bioengineering (Basel, Switzerland) · 2024Article
- Automatic Planning Tools for Lumbar Pedicle Screws: Comparison and Validation of Planning Accuracy for Self-Derived Deep-Learning-Based and Commercial Atlas-Based Approaches.Journal of clinical medicine · 2023Article
- Bone density optimized pedicle screw insertion.Frontiers in bioengineering and biotechnology · 2023Article
- The accuracy and effectiveness of automatic pedicle screw trajectory planning based on computer tomography values: an in vitro osteoporosis model study.BMC musculoskeletal disorders · 2022Article
- A level-wise spine registration framework to account for large pose changes.International journal of computer assisted radiology and surgery · 2021Article
- Automated Pipeline to Generate Anatomically Accurate Patient-Specific Biomechanical Models of Healthy and Pathological FSUs.Frontiers in bioengineering and biotechnology · 2021Article
- Article
- SpineCloud: image analytics for predictive modeling of spine surgery outcomes.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- Automatic pedicle screw planning using atlas-based registration of anatomy and reference trajectories.Physics in medicine and biology · 2019Article
- Atlas-based automatic planning and 3D-2D fluoroscopic guidance in pelvic trauma surgery.Physics in medicine and biology · 2019Article
- Robotic drill guide positioning using known-component 3D-2D image registration.Journal of medical imaging (Bellingham, Wash.) · 2018Article
- Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration.Physics in medicine and biology · 2017Article
- Toward Perception-based Anticipation of Cortical Breach During K-wire Fixation of the Pelvis.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Spinal screw placement is a challenging task due to small bone corridors and high risk of neurological or vascular complications, benefiting from precision guidance/navigation and quality assurance (QA). Implicit to both guidance and QA is the definition of a surgical plan-i.e. the desired trajectories and device selection for target vertebrae-conventionally requiring time-consuming manual annotations by a skilled surgeon. We propose automation of such planning by deriving the pedicle trajectory and device selection from a patient's preoperative CT or MRI. An atlas of vertebrae surfaces was created to provide the underlying basis for automatic planning-in this work, comprising 40 exemplary vertebrae at three levels of the spine (T7, T8, and L3). The atlas was enriched with ideal trajectory annotations for 60 pedicles in total. To define trajectories for a given patient, sparse deformation fields from the atlas surfaces to the input (CT or MR image) are applied on the annotated trajectories. Mean value coordinates are used to interpolate dense deformation fields. The pose of a straight trajectory is optimized by image-based registration to an accumulated volume of the deformed annotations. For evaluation, input deformation fields were created using coherent point drift (CPD) to perform a leave-one-out analysis over the atlas surfaces. CPD registration demonstrated surface error of 0.89 ± 0.10 mm (median ± interquartile range) for T7/T8 and 1.29 ± 0.15 mm for L3. At the pedicle center, registered trajectories deviated from the expert reference by 0.56 ± 0.63 mm (T7/T8) and 1.12 ± 0.67 mm (L3). The predicted maximum screw diameter differed by 0.45 ± 0.62 mm (T7/T8), and 1.26 ± 1.19 mm (L3). The automated planning method avoided screw collisions in all cases and demonstrated close agreement overall with expert reference plans, offering a potentially valuable tool in support of surgical guidance and QA.
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