Dean Chou

Study Design.: Retrospective analysis of a multicenter complex adult spinal deformity (ASD) cohort. Objectives.: Develop a simplified, weighted, and modifiable ASD Frailty Index (o-ASD-FI) that incorporates modifiable health components. Background.: Though newer frailty indices have emerged, none specifically addresses complex ASD while incorporating modifiable health factors. Methods.: Miller’s ASD-FI variables were evaluated via Pearson bivariate correlation and multiple stepwise regression. Ten frailty and three modifiable health factors (depression, diabetes, and osteoporosis) were identified and regressed against mortality, extended length of stay (LOS > 8 d), revisions, and major complications. Coefficients were weighted using Johnson’s method to create the o-ASD-FI (range: 0 – 18). Frailty categories were defined as: not frail (P P P P <0.01. Conclusions.: The newly developed simplified, weighted, and optimizable ASD Frailty Index (o-ASD-FI) incorporates modifiable health components, providing a robust assessment of physiological status and potentially superior risk stratification compared with existing tools for both primary and revision complex spinal deformity surgery. Level of Evidence: III

Objective: This study aims to evaluate the clinical and radiological outcomes of posterior reduction and fusion strategies, with or without interfacet joints distraction and cage implantation, based on reducibility, in the surgical management of atlantoaxial dislocation (AAD).Methods: Patients who underwent posterior reduction and fusion surgery for AAD in our institution were included. They were categorized into 2 groups based on reducibility. Japanese Orthopaedic Association (JOA), visual analogue scale (VAS), and patient-reported satisfaction scores were collected. The atlantodental interval, distance of the tip of the odontoid to Chamberlain’s line (DOCL), clivus-axial angle (CXA) and mean obliquity of the atlantoaxial articular facet (OAAF) were measured on computed tomography (CT) images. Fusion was evaluated using CT and dynamic x-rays.Results: A total of 90 patients (45 males and 45 females) were included. Among them, 54 patients in the reducible group underwent direct posterior reduction and fusion, and 36 patients in the irreducible group were treated with additional interfacet joint distraction and cage implantation. All patients showed significant improvements in JOA and VAS scores postoperatively. In the irreducible group, the preoperative CXA was smaller, whereas the OAAF was greater. Receiver operating characteristic curve analysis identified optimal cutoff value of OAAF in predicting reducibility was 32.4° (sensitivity: 86.1%, specificity: 81.5%). Postoperative changes in DOCL and CXA were more pronounced in irreducible group. The fusion rates were comparable in the 2 groups (92.6% vs. 94.4%, p=0.730).Conclusion: The reducibility-based posterior reduction fusion strategy achieves satisfactory clinical and radiological outcomes in the surgical management of AAD. For reducible cases, direct reduction under continuous intraoperative skull traction is preferred to minimize surgical trauma. In contrast, interfacet joints distraction and cage implantation are essential for irreducible cases. Preoperative OAAF may act as a potential predictor of reducibility.

Objectives To evaluate a deep learning model for automated and interpretable classification of central canal stenosis, neural foraminal stenosis, and facet arthropathy from lumbar spine MRI. Methods T2-weighted axial MRI studies of the lumbar spine acquired between 2008 and 2019 were retrospectively selected (n = 200) and graded for central canal stenosis, neural foraminal stenosis, and facet arthropathy. Studies were partitioned into patient-level train (n = 150), validation (n = 20), and test (n = 30) splits. V-Net models were first trained to segment the dural sac and the intervertebral disk, and localize facet and foramen using geometric rules. Subsequently, Big Transfer (BiT) models were trained for downstream classification tasks. An interpretable model for central canal stenosis was also trained using a decision tree classifier. Evaluation metrics included linearly weighted Cohen’s kappa score for multi-grade classification and area under the receiver operator characteristic curve (AUROC) for binarized classification. Results Segmentation of the dural sac and intervertebral disk achieved Dice scores of 0.93 and 0.94. Localization of foramen and facet achieved intersection over union of 0.72 and 0.83. Multi-class grading of central canal stenosis achieved a kappa score of 0.54. The interpretable decision tree classifier had a kappa score of 0.80. Pairwise agreement between readers (R1, R2), (R1, R3), and (R2, R3) was 0.86, 0.80, and 0.74. Binary classification of neural foraminal stenosis and facet arthropathy achieved AUROCs of 0.92 and 0.93. Conclusion Deep learning systems can be performant as well as interpretable for automated evaluation of lumbar spine MRI including classification of central canal stenosis, neural foraminal stenosis, and facet arthropathy. Key Points • Interpretable deep-learning systems can be developed for the evaluation of clinical lumbar spine MRI. Multi-grade classification of central canal stenosis with a kappa of 0.80 was comparable to inter-reader agreement scores (0.74, 0.80, 0.86). Binary classification of neural foraminal stenosis and facet arthropathy achieved favorable and accurate AUROCs of 0.92 and 0.93, respectively. • While existing deep-learning systems are opaque, leading to clinical deployment challenges, the proposed system is accurate as well as interpretable, providing valuable information to a radiologist in clinical practice.

Extradural malignant primary spinal tumors are rare and outcome data, especially for younger patients, is limited. In a worldwide (11 centers) study (Predictors of Mortality and Morbidity in the Surgical Management of Primary Tumors of the Spine study; ClinicalTrials.gov Identifier NCT01643174) by the AO Spine Knowledge Forum Tumor, patients surgically treated for primary tumors of the spine between 1992 and 2012, were retrospectively analyzed from a prospective database of their medical history. Medical history, tumor characteristics, diagnostics, treatments, cross-sectional survival, and local recurrences were analyzed. Sixty-eight cases (32 f; 36 m), at an average age of 18.6 ± 4.7 years at the time of diagnosis, were identified (median follow-up 2.9 years). The most common entities were Ewing’s sarcoma (42.6%). Of the patients, 28% had undergone previous spine tumor surgery in another center (84% with intralesional margins). Resection was considered “Enneking appropriate” (EA) in 47.8% of the cases. Of the patients, 77.9% underwent chemotherapy and 50% radiotherapy. A local recurrence occurred in 36.4%. Over a third of patients died within a 10-year follow-up period. Kaplan-Meier-analysis demonstrated statistically significant overall survival (p = 0.007) and local recurrence rates (p = 0.042) for tumors treated with EA surgery versus Enneking inappropriate surgery. Aggressive resection of extradural primary malignant spinal tumors combined with adjuvant therapy reveals low local recurrence rates and better outcomes overall in younger patients.

Extradural primary spinal tumors were retrospectively analyzed from a prospective database of 1495 cases. All subjects with benign primary tumors under the age of 25 years, who were enrolled between 1990 and 2012 (Median FU was 2.4 years), were identified. Patient- and case-related characteristics were collected and statistically analyzed. Results: 161 patients (66f;95m; age 17.0 ± 4.7 years at time of diagnosis) were identified. The most common tumors were osteoblastomas n = 53 (32.9%), osteoid osteomas n = 45 (28.0%), and aneurysmal bone cysts n = 32 (19.9%). The tumor grade, according to the Enneking Classification S1/S2/S3, was 14/73/74 (8.7/45.3/46.0%), respectively. Tumor-related pain was present in 156 (96.9%) patients. Diagnosis was achieved by biopsies in 2/3 of the cases. Spinal fixation was used in >50% of the cases. Resection was Enneking appropriate in n = 100 (62.1%) of cases. Local recurrence occurred in 21 (13.1%) patients. Two patients died within a 10-year follow-up period. Conclusion: This is one of the largest international multicenter cohorts of young patients surgically treated for benign spinal tumors. The heterogenic young patient cohort presented at a mid-term follow-up without a correlation between the grade of aggressiveness in resection and local recurrence rates. Further prospective data are required to identify prognostic factors that determine oncological and functional outcomes for young patients suffering from these rare tumors.

BACKGROUND AND PURPOSE: Quantitative metrics of the dural sac such as the cross-sectional area are commonly used to evaluate central canal stenosis. The aim of this study was to analyze 2 new metrics to measure spinal stenosis on the basis of the ratio between the dural sac and disc cross-sectional areas (DDRCA) and the dural sac and disc anterior-posterior diameters (DDRDIA) and compare them with established quantitative metrics of the dural sac. MATERIALS AND METHODS: T2-weighted axial MR images (n = 260 patients) were retrospectively evaluated, graded for central canal stenosis as normal (no stenosis), mild, moderate, or severe from L1/L2 through L5/S1 with 1 grade per spinal level and annotated to measure the DDRCA and DDRDIA. Thresholds were obtained using a decision tree classifier on a subset of patients (n = 130) and evaluated on the remaining patients (n = 130) for accuracy and consistency across demographics, anatomic variation, and clinical outcomes. RESULTS: DDRCA and DDRDIA had areas under the receiver operating characteristic curve of 98.6 (97.4–99.3) and 98.0 (96.7–98.9) compared with dural sac cross-sectional area at 96.5 (95.0–97.7) for binary classification. DDRDIA and DDRCA had κ scores of 0.75 (0.71–0.79) and 0.80 (0.75–0.83) compared with dural sac cross-sectional area at 0.62 (0.57–0.66) for multigrade classification. No significant differences (P > .1) in the area under the receiver operating characteristic curve were observed for the DDRDIA across variations in the body mass index. The DDRDIA also had the highest area under the receiver operating characteristic curve among symptomatic patients (visual analog scale ≥ 7) or patients who underwent surgery. CONCLUSIONS: Ratio-based metrics (DDRDIA and DDRCA) are accurate and robust to anatomic and demographic variability compared with quantitative metrics of the dural sac and better correlated with symptomatology and surgical outcomes.