Global Sagittal Angle and T9-tilt seem to be the most clinically and functionally relevant global alignment parameters in patients with Adult Spinal Deformity

Introduction

Radiographic analysis is necessary for the assessment and the surgical planning in adults with spinal deformity (ASD). Restoration of global alignment is key to improving patient's quality of life. However, the large number of existing global alignment parameters can be confusing for surgeons.

Research question

To determine the most clinically and functionally relevant global alignment parameters in ASD.

Material and methods

ASD and controls underwent full body biplanar X-ray to calculate global alignment parameters: odontoid to hip axis angle (OD-HA), global sagittal angle (GSA), global tilt (GT), SVA, center of auditory meatus to hip axis (CAM-HA), SSA, T1-tilt and T9-tilt. All subjects filled HRQoL questionnaires: ODI, SF-36, VAS for pain and BDI (Beck's Depression Inventory). 3D gait analysis was performed to calculate kinematic and spatio-temporal parameters. A machine learning model predicted gait parameters and HRQoL scores from global alignment parameters.

Results

124 primary ASD and 47 controls were enrolled. T9 tilt predicted the most BDI (31%), hip flexion/extension during gait (36%), and double support time (39%). GSA predicted the most ODI (26%), thorax flexion/extension during gait (33%), and cadence (36%).

Discussion and conclusion

Among all global alignment parameters, GSA, evaluating both trunk shift and knee flexion, and T9 tilt, evaluating the shift of the center of mass, were the best predictors for most of HRQoL scores and gait kinematics. Therefore, we recommend using GSA and T9 tilt in clinical practice when evaluating ASD because they represent the most quality of life and functional kinematic of these patients.

Functional assessment using 3D movement analysis can better predict health-related quality of life outcomes in patients with adult spinal deformity: a machine learning approach

Introduction

Adult spinal deformity (ASD) is classically evaluated by health-related quality of life (HRQoL) questionnaires and static radiographic spino-pelvic and global alignment parameters. Recently, 3D movement analysis (3DMA) was used for functional assessment of ASD to objectively quantify patient's independence during daily life activities. The aim of this study was to determine the role of both static and functional assessments in the prediction of HRQoL outcomes using machine learning methods.

Methods

ASD patients and controls underwent full-body biplanar low-dose x-rays with 3D reconstruction of skeletal segment as well as 3DMA of gait and filled HRQoL questionnaires: SF-36 physical and mental components (PCS&MCS), Oswestry Disability Index (ODI), Beck's Depression Inventory (BDI), and visual analog scale (VAS) for pain. A random forest machine learning (ML) model was used to predict HRQoL outcomes based on three simulations: (1) radiographic, (2) kinematic, (3) both radiographic and kinematic parameters. Accuracy of prediction and RMSE of the model were evaluated using 10-fold cross validation in each simulation and compared between simulations. The model was also used to investigate the possibility of predicting HRQoL outcomes in ASD after treatment.

Results

In total, 173 primary ASD and 57 controls were enrolled; 30 ASD were followed-up after surgical or medical treatment. The first ML simulation had a median accuracy of 83.4%. The second simulation had a median accuracy of 84.7%. The third simulation had a median accuracy of 87%. Simulations 2 and 3 had comparable accuracies of prediction for all HRQoL outcomes and higher predictions compared to Simulation 1 (i.e., accuracy for PCS = 85 ± 5 vs. 88.4 ± 4 and 89.7% ± 4%, for MCS = 83.7 ± 8.3 vs. 86.3 ± 5.6 and 87.7% ± 6.8% for simulations 1, 2 and 3 resp., p < 0.05). Similar results were reported when the 3 simulations were tested on ASD after treatment.

Discussion

This study showed that kinematic parameters can better predict HRQoL outcomes than stand-alone classical radiographic parameters, not only for physical but also for mental scores. Moreover, 3DMA was shown to be a good predictive of HRQoL outcomes for ASD follow-up after medical or surgical treatment. Thus, the assessment of ASD patients should no longer rely on radiographs alone but on movement analysis as well.

Spinopelvic Adaptations in Standing and Sitting Positions in Patients With Adult Spinal Deformity

Purpose

To describe spinopelvic adaptations in the standing and sitting positions in patients with adult spinal deformity (ASD).

Methods

Ninety-five patients with ASD and 32 controls completed health-related quality of life (HRQOL) questionnaires: short form 36 (SF36), Oswestry Disability Index (ODI), and visual analog scale (VAS) for pain. They underwent biplanar radiography in both standing and sitting positions. Patients with ASD were divided into ASD-front (frontal deformity Cobb > 20°, n = 24), ASD-sag (sagittal vertical axis (SVA) > 50 mm, pelvic tilt (PT) > 25°, or pelvic incidence (PI)-lumbar lordosis (LL) > 10°, n = 40), and ASD-hyper thoracic kyphosis (TK >60°, n = 31) groups. Flexibility was defined as the difference (Δ) in radiographic parameters between the standing and sitting positions. The radiographic parameters were compared between the groups. Correlations between HRQOL scores were evaluated.

Results

All participants increased their SVA from standing to sitting (ΔSVA<0), except for patients with ASD-sag, who tended to decrease their SVA (78-62 mm) and maximize their pelvic retroversion (27-40° vs 10-34° in controls, p<0.001). They also showed reduced thoracic and lumbar flexibility (ΔLL = 3.4 vs 37.1°; ΔTK = −1.7 vs 9.4° in controls, p<0.001). ASD-hyperTK showed a decreased PT while sitting (28.9 vs 34.4° in controls, p<0.001); they tended to decrease their LL and TK but could not reach values for controls (ΔLL = 22.8 vs 37.1° and ΔTK = 5.2 vs 9.4°, p<0.001). The ASD-front had normal standing and sitting postures. ΔSVA and ΔLL were negatively correlated with the physical component scale (PCS of SF36) and ODI (r = −0.39 and r = −0.46, respectively).

Conclusion

Patients with ASD present with different spinopelvic postures and adaptations from standing to sitting positions, with those having sagittal malalignment most affected. In addition, changes in standing and sitting postures were related to HRQOL outcomes. Therefore, surgeons should consider patient sitting adaptations in surgical planning and spinal fusion. Future studies on ASD should evaluate whether physical therapy or spinal surgery can improve sitting posture and QOL, especially for those with high SVA or PT.