A Novel and Reproducible Classification of Cervical Dumbbell Tumors to Inform Surgical Approach and Reconstruction Techniques.

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. MATERIALS AND 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±SD and were compared using an unpaired two-tailed Student t test. The χ 2 test or the Fisher exact test was used for categorical variables. Kendall's W test assessed three independent raters' inter-rater and intrarater reliabilities on 140 cervical dumbbell tumors. RESULTS: The inter-rater and intrarater consistency coefficient was 0.969 (χ 2 =404.3, P <0.001) and 0.984 (χ 2 =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. A recurrence was observed in 19 (6.4%) patients. CONCLUSION: The authors describe a novel classification system that is of practical use for planning the complete resection of cervical dumbbell tumors.

Stretchable graded multichannel self-powered respiratory sensor inspired by shark gill.

Respiratory sensing provides a simple, non-invasive, and efficient way for medical diagnosis and health monitoring, but it relies on sensors that are conformal, accurate, durable, and sustainable working. Here, a stretchable, multichannel respiratory sensor inspired by the structure of shark gill cleft is reported. The bionic shark gill structure can convert transverse elastic deformation into longitudinal elastic deformation during stretching. Combining the optimized bionic shark gill structure with the piezoelectric and the triboelectric effect, the bionic shark gill respiratory sensor (BSG-RS) can produce a graded electrical response to different tensile strains. Based on this feature, BSG-RS can simultaneously monitor the breathing rate and breathing depth of the human body accurately, and realize the effective recognition of the different human body's breathing state under the supporting software. With good stretchability, wearability, accuracy, and long-term stability (50,000 cycles), BSG-RS is expected to be applied as self-powered smart wearables for mobile medical diagnostic analysis in the future.