Clinical classification of scoliosis patients using machine learning and markerless 3D surface trunk data

Rothstock, Stephan; Weiss, Hans‐Rudolf; Krueger, Daniel; Paul, Lothar

doi:10.1007/s11517-020-02258-x

Cited by 19 publications

(22 citation statements)

References 37 publications

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“…Efforts must be done in the future to automatize the methodology presented as much as possible and successfully transfer it from virtual morphology labs to hospitals. In this line, machine learning is showing greater results in clinical decisions made for patients with scoliosis [14,31]. Applying all this knowledge to GMM remains to be done in the study of this condition.…”

Section: Discussionmentioning

confidence: 99%

Investigating Human Torso Asymmetries: An Observational Longitudinal Study of Fluctuating and Directional Asymmetry in the Scoliotic Torso

et al. 2021

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The presence of directional and fluctuating asymmetry in adolescent idiopathic scoliosis has not been deeply studied. We aimed to test the presence of both in a scoliosis group and a control group. 24 patients with adolescent idiopathic scoliosis and 24 control subjects were subjected to geometric morphometrics analyses to address our main hypotheses and to make qualitative visualizations of the 3D shape changes in patients with scoliosis. Our results support the hypothesis that both asymmetric traits are present in the scoliosis and control groups, but to a greater degree in patients. A qualitative visualization tool that allows us to measure the impact that directional and fluctuating asymmetry have on the 3D shape of our patients has been developed. Adolescent idiopathic scoliosis is the result of developmental instabilities during growth and the visualization of the 3D shape changes in response to both asymmetric variables has shown different morphological behaviors. Measuring these variables is important, as they can prevent the localization and deformation that is expected to occur during the course of scoliosis in every individual patient and therefore acts as a key clinical finding that may be used in the prognosis of the condition.

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Section: Discussionmentioning

confidence: 99%

Investigating Human Torso Asymmetries: An Observational Longitudinal Study of Fluctuating and Directional Asymmetry in the Scoliotic Torso

et al. 2021

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Section: Resultsmentioning

confidence: 99%

“…77 Also, a semi-automatic method had been built to classify scoliosis severity and treatment group with 3D markerless surface topography scans. 78 And approaches were proposed to predict curve shape variation, curve types and progression in AIS. [79][80][81] Recently scholars built models to automatically provide measurements of implants, placement trajectories, pedicle screw planning and surgical navigation.…”

Section: Image Processing and Diagnosismentioning

confidence: 99%

Current Applications of Machine Learning in Spine: From Clinical View

Ren

Xie

et al. 2021

Global Spine Journal

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Study Design: Narrative review. Objectives: This review aims to present current applications of machine learning (ML) in spine domain to clinicians. Methods: We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2020 using terms (spine, spinal, lumbar, cervical, thoracic, machine learning) to examine ML in spine. Then exclude research of other domain, case report, review or meta-analysis, and which without available abstract or full text. Results: Total 1738 articles were retrieved from database, and 292 studies were finally included. Key findings of current applications were compiled and summarized in this review. Main clinical applications of those techniques including image processing, diagnosis, decision supporting, operative assistance, rehabilitation, surgery outcomes, complications, hospitalization and cost. Conclusions: ML had achieved excellent performance and hold immense potential in spine. ML could help clinical staff to improve medical level, enhance work efficiency, and reduce adverse events. However more randomized controlled trials and improvement of interpretability are essential to clinicians accepting models’ assistance in real work.

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“…While in the 3C patterns the thoracic curve is structural and dominant, in the 4C patterns it is the structural lumbar curve which takes the lead. The ALSclassification provides a further subclassification of 3C and 4C patterns according to the length of the major curve and of the existing nonstructural counter curves (Chik 2020;Rothstock et al 2020;Weiss 2010).…”

Section: Discussionmentioning

confidence: 99%

Impact of Gensingen brace treatment on Lenke 5 curvatures and chronic low back pain in late adolescent and adult scoliosis patients

Widjaja

Varani

2022

South African Journal of Physiotherapy

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Background: Lenke 5C (lumbar and or thoracolumbar) curve patterns lead to loss of lumbar lordosis which is associated with low back pain in later adulthood. We undertook our study to investigate if brace treatment may have an effect on low back pain and on improving the cosmetic appearance in late adolescents and adults.Objectives: To estimate if conservative treatment may have an effect on pain in single lumbar curvatures in late adolescent and adult patients with Adolescent Idiopathic Scoliosis (AIS) using a Gensingen Brace by Weiss (GBW).Method: We investigated AIS patients with Lenke 5C pattern who wore a GBW prospectively. The inclusion criteria of our study were age over 15 years, Cobb angle greater than 20° before treatment and Risser 4 or 5. A verbal pain rating scale was used (no pain, mild pain, moderate pain, severe pain, very severe pain).Results: A total of 26 patients met the inclusion criteria. The average age was 17.7 years and the average Cobb angle was 41.5°. Nineteen patients (73.1%) experienced mild or moderate chronic low back pain before treatment and seven patients (26.9%) were asymptomatic but seeking treatment for cosmetic reasons. At follow-up, a 23% correction of the curve was achieved. All previously symptomatic patients reported that they no longer experienced low back pain after having worn the brace regularly.Conclusion: High correction bracing seems to have a positive effect on the curve and on chronic low back pain in patients with a scoliosis and a Lenke 5C curve pattern.Clinical implications: High correction, pattern specific bracing with a GBW may be applied aiming at reducing structural curves and chronic low back pain in late adolescent and adult patients with AIS and with a single lumbar curvature.

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Clinical classification of scoliosis patients using machine learning and markerless 3D surface trunk data

Cited by 19 publications

References 37 publications

Investigating Human Torso Asymmetries: An Observational Longitudinal Study of Fluctuating and Directional Asymmetry in the Scoliotic Torso

Investigating Human Torso Asymmetries: An Observational Longitudinal Study of Fluctuating and Directional Asymmetry in the Scoliotic Torso

Current Applications of Machine Learning in Spine: From Clinical View

Impact of Gensingen brace treatment on Lenke 5 curvatures and chronic low back pain in late adolescent and adult scoliosis patients

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