Identifying Thoracic Compensation and Predicting Reciprocal Thoracic Kyphosis and Proximal Junctional Kyphosis in Adult Spinal Deformity Surgery

Protopsaltis, Themistocles S.; Diebo, Bassel G.; Lafage, Renaud; Henry, Jensen K.; Smith, Justin S.; Sciubba, Daniel M.; Passias, Peter G.; Kim, Hee Jin; Hamilton, D. Kojo; Sorocéanu, Alexandra; Klineberg, Eric O.; Ames, Christopher P.; Shaffrey, Christopher I.; Bess, Shay; Hart, Robert A.; Schwab, Frank J.; Lafage, Virginie

doi:10.1097/brs.0000000000002843

Cited by 34 publications

(33 citation statements)

References 30 publications

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“…This can be used to estimate pre-operative compensation, predict reciprocal change, and potentially PJK as hypothesized by previous study 23 .…”

Section: Discussionmentioning

confidence: 96%

“…The UIV selected in the upper and lower thoracic spine has been shown to correlate with PJK 22 . Patients exhibiting preoperative thoracic compensation were more likely to develop proximal junctional kyphosis 23 . The data from this study may help modify the risk of PJK; evaluating deviation from "ideal thoracic shape" in patients with deformity and PJK, perhaps the risk of PJK can be modified.…”

Section: Discussionmentioning

confidence: 99%

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Understanding Thoracic Spine Morphology, Shape, and Proportionality

Lafage

Steinberger

Pesenti

et al. 2020

Spine

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“…This can be used to estimate pre-operative compensation, predict reciprocal change, and potentially PJK as hypothesized by previous study 23 .…”

Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 99%

Understanding Thoracic Spine Morphology, Shape, and Proportionality

Lafage

Steinberger

Pesenti

et al. 2020

Spine

Self Cite

View full text Add to dashboard Cite

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“…The ΔTK threshold was used to define reciprocal kyphosis which has also been used in prior literature. 23 …”

Section: Methodsmentioning

confidence: 99%

Can Machine Learning Accurately Predict Postoperative Compensation for the Uninstrumented Thoracic Spine and Pelvis After Fusion From the Lower Thoracic Spine to the Sacrum?

Lee

Sardar

Boddapati

et al. 2020

Global Spine Journal

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Study Design: Consecutively collected cases. Objective: To determine if a machine-learning (ML) program can accurately predict the postoperative thoracic kyphosis through the uninstrumented thoracic spine and pelvic compensation in patients who undergo fusion from the lower thoracic spine (T10 or T11) to the sacrum. Methods: From 2015 to 2019, a consecutive series of adult (≥18 years old) patients with adult spinal deformity underwent corrective spinal fusion from the lower thoracic spine (T10 or T11) to the sacrum. Deidentified data was processed by a ML system-based platform to predict the postoperative thoracic kyphosis (TK) and pelvic tilt (PT) for each patient. To validate the ML model, the postoperative TK (T4-T12, instrumented thoracic, and uninstrumented thoracic) and the pelvic tilt were compared against the predicted values. Results: A total of 20 adult patients with a minimum 6-month follow-up (mean: 22.4 ± 11.3 months) were included in this study. No significant differences were observed for TK (predicted 37.6° vs postoperative 38.3°, P = .847), uninstrumented TK (predicted 33.9° vs postoperative 29.8°, P = .188), and PT (predicted 23.4° vs postoperative 22.7°, P = .754). The predicted PT and the TK of the uninstrumented thoracic spine correlated well with postoperative values (uninstrumented TK: R 2 = 0.764, P < .001; PT: R 2 = 0.868, P < .001). The mean error with which kyphosis through the uninstrumented thoracic spine can be measured was 4.8° ± 4.0°. The mean error for predicting PT was 2.5° ± 1.7°. Conclusion: ML algorithms can accurately predict the spinopelvic compensation after spinal fusion from the lower thoracic spine to the sacrum. These findings suggest that surgeons may be able to leverage this technology to reduce the risk of proximal junctional kyphosis in this population.

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“…Previous efforts, in terms of identifying lumbopelvic and full body compensation, have resulted in improved surgical alignment goals built around obtaining superior patient outcomes. [5][6][7][8][9] As the cumulative data has grown, some authors have hypothesized that the development of PJK itself could be seen as a compensatory mechanism in the setting of overcorrection. 5,10 In terms of interplay between thoracolumbar alignment and cervical spine, a number of reciprocal adjacent level and regional changes in cervical alignment following deformity correction have been described.…”

Section: Introductionmentioning

confidence: 99%

Cervical, Thoracic, and Spinopelvic Compensation After Proximal Junctional Kyphosis (PJK): Does Location of PJK Matter?

Kim

Elysée

Shaffrey

et al. 2019

Global Spine Journal

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Study Design: Retrospective case series. Objective: Compensatory changes above a proximal junctional kyphosis (PJK) have not been defined. Understanding these mechanisms may help determine optimal level selection when performing revision for PJK. This study investigates how varying PJK location changes proximal spinal alignment. Methods: Patients were grouped by upper instrumented vertebrae (UIV): lower thoracic (LT; T8-L1) or upper thoracic (UT; T1-7). Alignment parameters were compared. Correlation analysis was performed between PJK magnitude and global/cervical alignment. Results: A total of 369 patients were included; mean age of 63 years, body mass index 28, and 81% female, LT (n = 193) versus UT (n = 176). The rate of radiographic PJK was 49%, higher in the LT group (55% vs 42%, P = .01). The UT group displayed significant differences in all cervical radiographic parameters ( P < .05) between PJK versus non-PJK patients, while the LT group displayed significant differences in T1S and C2-T3 sagittal vertical axis (SVA) (CTS). In comparing UT versus LT patients, UT had more posterior global alignment (smaller TPA [T1 pelvic angle], SVA, and larger PT [pelvic tilt]) and larger anterior cervical alignment (greater cSVA [cervical SVA], T1S-CL [T1 slope–cervical lordosis] mismatch, CTS) compared to LT. Correlation analysis of PJK magnitude and location demonstrated a correlation with increases in CL, T1S, and CTS in the UT group. In the LT group, PT increased with PJK angle ( r = 0.17) and no significant correlations were noted to SVA, cSVA, or T1S-CL. Conclusions: PJK location influences compensation mechanisms of the cervical and thoracic spine. LT PJK results in increased PT and CL with decreased CTS. UT PJK increases CL to counter increases in T1S with continued T1S-CL mismatch and elevated cSVA.

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Identifying Thoracic Compensation and Predicting Reciprocal Thoracic Kyphosis and Proximal Junctional Kyphosis in Adult Spinal Deformity Surgery

Abstract: 3.

Cited by 34 publications

References 30 publications

Understanding Thoracic Spine Morphology, Shape, and Proportionality

Understanding Thoracic Spine Morphology, Shape, and Proportionality

Can Machine Learning Accurately Predict Postoperative Compensation for the Uninstrumented Thoracic Spine and Pelvis After Fusion From the Lower Thoracic Spine to the Sacrum?

Cervical, Thoracic, and Spinopelvic Compensation After Proximal Junctional Kyphosis (PJK): Does Location of PJK Matter?

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