Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans
<p><strong>BACKGROUND:</strong> Scoliosis is spinal curvature that may progress to require surgical stabilisation. Risk factors for progression are little understood due to lack of population-based research, since radiographs cannot be performed on entire populations due to high le...
| 主要な著者: | , , , , , |
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| フォーマット: | Journal article |
| 言語: | English |
| 出版事項: |
Elsevier
2023
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| _version_ | 1826312794094436352 |
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| author | Jamaludin, A Fairbank, J Harding, I Kadir, T Zisserman, A Clark, EM |
| author_facet | Jamaludin, A Fairbank, J Harding, I Kadir, T Zisserman, A Clark, EM |
| author_sort | Jamaludin, A |
| collection | OXFORD |
| description | <p><strong>BACKGROUND:</strong> Scoliosis is spinal curvature that may progress to require surgical stabilisation. Risk factors for progression are little understood due to lack of population-based research, since radiographs cannot be performed on entire populations due to high levels of radiation. To help address this, we have previously developed and validated a method for quantification of spinal curvature from total body dual energy X-ray absorptiometry (DXA) scans. The purpose of this study was to automate this quantification of spinal curve size from DXA scans using machine learning techniques.</p>
<p><strong>METHODS:</strong> To develop the automation of curve size, we utilised manually annotated scans from 7298 participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) at age 9 and 5122 at age 15. To validate the automation we assessed (1) agreement between manual vs automation using the Bland-Altman limits of agreement, (2) reliability by calculating the coefficient of variation, and (3) clinical validity by running the automation on 4969 non-annotated scans at age 18 to assess the associations with physical activity, body composition, adipocyte function and backpain compared to previous literature.</p>
<p><strong>RESULTS:</strong> The mean difference between manual vs automated readings was less than one degree, and 90.4 % of manual vs automated readings fell within 10°. The coefficient of variation was 25.4 %. Clinical validation showed the expected relationships between curve size and physical activity, adipocyte function, height and weight.</p>
<p><strong>CONCLUSION:</strong> We have developed a reasonably accurate and valid automated method for quantifying spinal curvature from DXA scans for research purposes.</p> |
| first_indexed | 2024-03-07T07:44:21Z |
| format | Journal article |
| id | oxford-uuid:b427dffc-0536-46a3-95ae-0c2adc1c6638 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-04-23T08:26:13Z |
| publishDate | 2023 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:b427dffc-0536-46a3-95ae-0c2adc1c66382024-04-18T09:47:05ZAutomated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scansJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:b427dffc-0536-46a3-95ae-0c2adc1c6638EnglishSymplectic ElementsElsevier2023Jamaludin, AFairbank, JHarding, IKadir, TZisserman, AClark, EM<p><strong>BACKGROUND:</strong> Scoliosis is spinal curvature that may progress to require surgical stabilisation. Risk factors for progression are little understood due to lack of population-based research, since radiographs cannot be performed on entire populations due to high levels of radiation. To help address this, we have previously developed and validated a method for quantification of spinal curvature from total body dual energy X-ray absorptiometry (DXA) scans. The purpose of this study was to automate this quantification of spinal curve size from DXA scans using machine learning techniques.</p> <p><strong>METHODS:</strong> To develop the automation of curve size, we utilised manually annotated scans from 7298 participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) at age 9 and 5122 at age 15. To validate the automation we assessed (1) agreement between manual vs automation using the Bland-Altman limits of agreement, (2) reliability by calculating the coefficient of variation, and (3) clinical validity by running the automation on 4969 non-annotated scans at age 18 to assess the associations with physical activity, body composition, adipocyte function and backpain compared to previous literature.</p> <p><strong>RESULTS:</strong> The mean difference between manual vs automated readings was less than one degree, and 90.4 % of manual vs automated readings fell within 10°. The coefficient of variation was 25.4 %. Clinical validation showed the expected relationships between curve size and physical activity, adipocyte function, height and weight.</p> <p><strong>CONCLUSION:</strong> We have developed a reasonably accurate and valid automated method for quantifying spinal curvature from DXA scans for research purposes.</p> |
| spellingShingle | Jamaludin, A Fairbank, J Harding, I Kadir, T Zisserman, A Clark, EM Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans |
| title | Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans |
| title_full | Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans |
| title_fullStr | Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans |
| title_full_unstemmed | Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans |
| title_short | Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans |
| title_sort | automated measurement of size of spinal curve in population based cohorts validation of a method based on total body dual energy x ray absorptiometry scans |
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