Spinal sagittal alignment goals based on statistical modelling and musculoskeletal simulations. (26th March 2020)
- Record Type:
- Journal Article
- Title:
- Spinal sagittal alignment goals based on statistical modelling and musculoskeletal simulations. (26th March 2020)
- Main Title:
- Spinal sagittal alignment goals based on statistical modelling and musculoskeletal simulations
- Authors:
- Caprara, Sebastiano
Moschini, Greta
Snedeker, Jess G.
Farshad, Mazda
Senteler, Marco - Abstract:
- Abstract: The definition of target alignment for spinal fusion surgery follows anatomical criteria and strongly relies on surgical experience. However, the optimal patient-specific alignment often remains unknown. Statistical models could provide information about physiological alignments, and musculoskeletal models are powerful tools to investigate biomechanics. We aimed to statistically predict alignments and hypothesized they would be biomechanically favorable. A statistical model was trained with 60 annotated radiographs to predict physiological sagittal alignment based on position of femoral heads and sacrum. Predicted alignments for 11 back pain patients were clinically evaluated in terms of balance and compared to Original alignments. The normative ranges for spinal balance parameters were obtained from Surgimap™. Musculoskeletal loads were furthermore simulated in upright standing and 30° forward flexion, using alignment-specific musculoskeletal models. For the majority of Predicted alignments (n = 9) at least two of three investigated balance parameters were within the normative range, as opposed to the minority of the Original alignments (n = 4). Predicted alignments resulted in significantly lowered overall muscle activity and compressive loads (all levels, both postures). Shear force magnitudes in upright standing decreased significantly at levels L1L2 (−68 N) and L2L3 (−69 N) and clearly yet not significantly at L3L4 (−39 N) and L4L5 (−152 N). Shear loads atAbstract: The definition of target alignment for spinal fusion surgery follows anatomical criteria and strongly relies on surgical experience. However, the optimal patient-specific alignment often remains unknown. Statistical models could provide information about physiological alignments, and musculoskeletal models are powerful tools to investigate biomechanics. We aimed to statistically predict alignments and hypothesized they would be biomechanically favorable. A statistical model was trained with 60 annotated radiographs to predict physiological sagittal alignment based on position of femoral heads and sacrum. Predicted alignments for 11 back pain patients were clinically evaluated in terms of balance and compared to Original alignments. The normative ranges for spinal balance parameters were obtained from Surgimap™. Musculoskeletal loads were furthermore simulated in upright standing and 30° forward flexion, using alignment-specific musculoskeletal models. For the majority of Predicted alignments (n = 9) at least two of three investigated balance parameters were within the normative range, as opposed to the minority of the Original alignments (n = 4). Predicted alignments resulted in significantly lowered overall muscle activity and compressive loads (all levels, both postures). Shear force magnitudes in upright standing decreased significantly at levels L1L2 (−68 N) and L2L3 (−69 N) and clearly yet not significantly at L3L4 (−39 N) and L4L5 (−152 N). Shear loads at level L5S1 remained the same. In flexed postures identical trends were observed. The statistical model was able to predict spinal alignments that led to both improved balance and reduced musculoskeletal loads. Further studies are needed to investigate clinical validity of such models. … (more)
- Is Part Of:
- Journal of biomechanics. Volume 102(2020)
- Journal:
- Journal of biomechanics
- Issue:
- Volume 102(2020)
- Issue Display:
- Volume 102, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 102
- Issue:
- 2020
- Issue Sort Value:
- 2020-0102-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-03-26
- Subjects:
- Statistical shape modelling -- Musculoskeletal modelling -- Sagittal alignment -- Intervertebral lumbar forces
Animal mechanics -- Periodicals
Biomechanics -- Periodicals
Biomechanics -- Periodicals
Mécanique animale -- Périodiques
Biomécanique -- Périodiques
Electronic journals
571.4305 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00219290 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/00219290 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/00219290 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jbiomech.2020.109621 ↗
- Languages:
- English
- ISSNs:
- 0021-9290
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4953.600000
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