Author:
Yang Minglei,Zhong Nanzhe,Lou Yan,Jiang Dongjie,Liu Yujie,Dai Zeyu,Wan Wei,Jiao Jian,Yang Xinghai,Xiao Jianru
Abstract
Study Design.
A retrospective case series.
Objective.
This study developed a novel classification system based on imaging and anatomy to select optimal surgical approaches and reconstruction strategies to achieve total resection of cervical dumbbell tumors and restore spinal stability.
Summary of Background Data.
Total resection is necessary to decrease the recurrence rate of cervical dumbbell tumors. Previous cervical dumbbell tumor classifications are insufficient for determining surgical strategies, therefore, a practical classification is needed.
Methods.
This study included 295 consecutive patients with cervical dumbbell tumors who underwent total surgical resection. A novel classification of cervical dumbbell tumors was developed based on magnetic resonance imaging and computed tomography. Continuous variables were expressed as mean±standard deviation (SD) and were compared using an unpaired two-tailed Student’s t‑test. The χ2 test or Fisher’s exact test was used for categorical variables. Kendall’s W test assessed three independent raters’ inter- and intra-rater reliabilities on 140 cervical dumbbell tumors.
Results.
The inter-rater and intra-rater consistency coefficient was 0.969 (χ2=404.3, P<0.001) and 0.984 (χ2=273.7, P<0.001). All patients with type I and II tumors underwent single-posterior surgeries to achieve total resection. Of the patients in this study, 86.1%, 25.9%, 75.9%, and 76.9% underwent posterior surgeries for types IIIa, IIIb, IVa, and V tumors, respectively. All patients with type IVb tumors underwent a combined anterior and posterior approach. Posterior internal fixation was used for all patients in posterior surgery. Anterior reconstruction was applied for patients with type IVb tumors (20/20, 100%) and some with Type V tumors (3/13, 23.1%). The mean follow-up duration was 93.6±2.6 months. Recurrence was observed in 19 (6.4%) patients.
Conclusion.
We describe a novel classification system that is of practical use for planning the complete resection of cervical dumbbell tumors.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
1 articles.
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