Spine deformity · 2025
Automated measurement of spinopelvic alignment parameters using a spine planning software: a validation study.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Almahozi Ahmad, Früh Anton, Sargut Tarik Alp, Rosenstock Tizian, Jelgersma Claudius, Roethe Anna L, Tkatschenko Dimitri, Truckenmueller Peter, Alsolivany Joan, Ferdowssian Kiarash, Hecht Nils, Vajkoczy Peter, Wessels Lars
Аннотация
BACKGROUND: Accurate assessment of spinopelvic alignment is essential for managing adult spinal deformities. This study validates the Brainlab Elements Spine Planning software for automated measurement of spinopelvic parameters, comparing it with manual methods.
METHODS: Spinopelvic parameters were measured manually and with the software in 21 patients with degenerative spinal disease, including instrumented and non-instrumented spines. Accuracy, intraobserver, and interobserver reliability were evaluated using Bland-Altman plots and intraclass correlation coefficients (ICCs). Measurement times were also compared.
RESULTS: The software showed high reliability (ICC = 1), while manual measurements ranged from fair to excellent reliability (ICC 0.44-0.99). Bland-Altman plots indicated strong agreement between automated and manual measurements, though variability was noted for certain parameters. Automated measurements were significantly faster, averaging 62 s versus 227 s in manual measurements (p < 0.001), though 76.2% of cases had at least one parameter that could not be measured automatically, most frequently the sagittal vertical axis (SVA) and several coronal parameters.
CONCLUSION: The Brainlab Elements software provides accurate, reproducible, and time-efficient spinopelvic measurements for parameters it successfully captures. However, frequent failures in assessing SVA and coronal plane parameters automatically suggest that further refinement of the software is necessary.
METHODS: Spinopelvic parameters were measured manually and with the software in 21 patients with degenerative spinal disease, including instrumented and non-instrumented spines. Accuracy, intraobserver, and interobserver reliability were evaluated using Bland-Altman plots and intraclass correlation coefficients (ICCs). Measurement times were also compared.
RESULTS: The software showed high reliability (ICC = 1), while manual measurements ranged from fair to excellent reliability (ICC 0.44-0.99). Bland-Altman plots indicated strong agreement between automated and manual measurements, though variability was noted for certain parameters. Automated measurements were significantly faster, averaging 62 s versus 227 s in manual measurements (p < 0.001), though 76.2% of cases had at least one parameter that could not be measured automatically, most frequently the sagittal vertical axis (SVA) and several coronal parameters.
CONCLUSION: The Brainlab Elements software provides accurate, reproducible, and time-efficient spinopelvic measurements for parameters it successfully captures. However, frequent failures in assessing SVA and coronal plane parameters automatically suggest that further refinement of the software is necessary.