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Column, Line-of-Sight, Margins, Ring: A Framework for Planning En Bloc Spondylectomies
Karan Joseph1, Samuel Vogl1, Alexander T Yahanda1
1Department of Neurological Surgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.
Operative Neurosurgery (Hagerstown, Md.)
|February 10, 2026
Summary
The novel CLiMR framework simplifies planning for en bloc spondylectomies, crucial for spinal tumor control. This system correlates with surgical complexity, hospital stay, and outcomes.
Area of Science:
- Spine surgery
- Surgical oncology
- Orthopedic oncology
Background:
- En bloc spondylectomies are vital for malignant spinal tumor resection.
- Existing classification systems for these complex procedures are often impractical.
- A need exists for a standardized, user-friendly system for planning and classification.
Purpose of the Study:
- To introduce and evaluate the CLiMR (Column, Line-of-Sight, Margins, Ring) framework.
- To simplify and standardize the planning and classification of en bloc spondylectomies.
- To assess the correlation between the CLiMR framework and surgical outcomes.
Main Methods:
- Retrospective review of en bloc spinal tumor resections (October 2019-December 2024).
- Application of the CLiMR framework assessing four components: Column, Line-of-Sight, Margins, and Ring.
- Correlation of CLiMR scores with operative details, hospital stay, case duration, blood loss, and patient outcomes.
Main Results:
- The CLiMR framework demonstrated variability in scores across different surgical components.
- Higher CLiMR scores correlated significantly with longer hospital stays (R=0.64, P=.0012) and case durations (R=0.61, P=.0023).
- Increased CLiMR scores trended towards higher rates of local recurrence, positive margins, and complications.
Conclusions:
- The CLiMR framework offers a novel, practical method for planning and communicating en bloc spondylectomies.
- This system aids in standardizing assessment and surgical decision-making for complex spinal tumor resections.
- The CLiMR framework shows feasibility and provides a foundation for future validation studies.
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