Emma B Nadler, David E Lebel, Dorothy J Kim, Mark Camp, Jennifer A Dermott
{"title":"3D topographic acquisitions to predict spinal curvature in adolescent idiopathic scoliosis : a prospective validation study.","authors":"Emma B Nadler, David E Lebel, Dorothy J Kim, Mark Camp, Jennifer A Dermott","doi":"10.1302/2633-1462.74.BJO-2026-0029.R1","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>This study aims to determine the reliability, accuracy, and usability of a new health application that uses AI to estimate major coronal curve magnitude in patients with adolescent idiopathic scoliosis (AIS) from 3D surface topography (ST) captured on a smartphone video scan.</p><p><strong>Methods: </strong>This is a prospective validation study. AIS patients, aged ten to 18 years, with coronal curve magnitudes ≤ 45° were recruited at a tertiary care spine clinic. A single trained researcher performed scans twice, six months apart, during participants' routine clinical and radiological assessment. Participants were asked to complete a scan once a month between clinic visits, starting the day of recruitment. Agreement was calculated by comparing scan curve magnitude predictions to the reference standard: a three-foot standing spine radiograph measured by blinded spine clinicians. Inter-rater reliability was assessed by comparing in-clinic to home scan predictions. Measures of diagnostic accuracy to determine the app's ability to screen for coronal deformity > 25° and its ability to detect progression > 5° over a six-month period were determined. Successful compared with failed scans were recorded.</p><p><strong>Results: </strong>Among participants (n = 63), 59 patients (94%) had at least one successful in-clinic scan and 32 patients (51%) had at least one successful home scan. Agreement with the reference standard was moderate for in-clinic scans (intraclass correlation coefficient (ICC) 0.535) and poor for home scans (ICC 0.402). Inter-rater reliability between in-clinic and home scans was poor (ICC 0.168). The app had an accuracy of 70% when discriminating between curve magnitudes ± 25° and detecting curve progression > 5°. A larger proportion of scans failed at-home (30%) compared with in-clinic (16%).</p><p><strong>Conclusion: </strong>Conceptually, the app shows potential as an accessible screening tool for scoliosis. However, the accuracy and reliability suggest it is not yet a reasonable replacement for radiographs and in-person clinical evaluation.</p>","PeriodicalId":34103,"journal":{"name":"Bone & Joint Open","volume":"7 4","pages":"473-481"},"PeriodicalIF":3.1000,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13043243/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bone & Joint Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1302/2633-1462.74.BJO-2026-0029.R1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
引用次数: 0
Abstract
Aims: This study aims to determine the reliability, accuracy, and usability of a new health application that uses AI to estimate major coronal curve magnitude in patients with adolescent idiopathic scoliosis (AIS) from 3D surface topography (ST) captured on a smartphone video scan.
Methods: This is a prospective validation study. AIS patients, aged ten to 18 years, with coronal curve magnitudes ≤ 45° were recruited at a tertiary care spine clinic. A single trained researcher performed scans twice, six months apart, during participants' routine clinical and radiological assessment. Participants were asked to complete a scan once a month between clinic visits, starting the day of recruitment. Agreement was calculated by comparing scan curve magnitude predictions to the reference standard: a three-foot standing spine radiograph measured by blinded spine clinicians. Inter-rater reliability was assessed by comparing in-clinic to home scan predictions. Measures of diagnostic accuracy to determine the app's ability to screen for coronal deformity > 25° and its ability to detect progression > 5° over a six-month period were determined. Successful compared with failed scans were recorded.
Results: Among participants (n = 63), 59 patients (94%) had at least one successful in-clinic scan and 32 patients (51%) had at least one successful home scan. Agreement with the reference standard was moderate for in-clinic scans (intraclass correlation coefficient (ICC) 0.535) and poor for home scans (ICC 0.402). Inter-rater reliability between in-clinic and home scans was poor (ICC 0.168). The app had an accuracy of 70% when discriminating between curve magnitudes ± 25° and detecting curve progression > 5°. A larger proportion of scans failed at-home (30%) compared with in-clinic (16%).
Conclusion: Conceptually, the app shows potential as an accessible screening tool for scoliosis. However, the accuracy and reliability suggest it is not yet a reasonable replacement for radiographs and in-person clinical evaluation.