Development and validation of AI-based automatic measurement of coronal Cobb angles in degenerative scoliosis using sagittal lumbar MRI

被引:4
作者
van der Graaf, Jasper W. [1 ,2 ]
van Hooff, Miranda L. [2 ,3 ]
van Ginneken, Bram [1 ]
Huisman, Merel [4 ]
Rutten, Matthieu [1 ,5 ]
Lamers, Dominique [2 ]
Lessmann, Nikolas [1 ]
de Kleuver, Marinus [2 ]
机构
[1] Radboud Univ Nijmegen, Med Ctr, Diagnost Image Anal Grp, NL-6500 HB Nijmegen, Netherlands
[2] Radboud Univ Nijmegen, Med Ctr, Dept Orthoped, Nijmegen, Netherlands
[3] Sint Maartenskliniek, Dept Res, Nijmegen, Netherlands
[4] Radboud Univ Nijmegen, Med Ctr, Dept Med Imaging, Nijmegen, Netherlands
[5] Jeroen Bosch Hosp, Dept Radiol, Shertogenbosch, Netherlands
关键词
Spine; Scoliosis; Magnetic resonance imaging; Cobb angle; Deep learning; IDIOPATHIC SCOLIOSIS; ADULT;
D O I
10.1007/s00330-024-10616-8
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectivesSeverity of degenerative scoliosis (DS) is assessed by measuring the Cobb angle on anteroposterior radiographs. However, MRI images are often available to study the degenerative spine. This retrospective study aims to develop and evaluate the reliability of a novel automatic method that measures coronal Cobb angles on lumbar MRI in DS patients.Materials and methodsVertebrae and intervertebral discs were automatically segmented using a 3D AI algorithm, trained on 447 lumbar MRI series. The segmentations were used to calculate all possible angles between the vertebral endplates, with the largest being the Cobb angle. The results were validated with 50 high-resolution sagittal lumbar MRI scans of DS patients, in which three experienced readers measured the Cobb angle. Reliability was determined using the intraclass correlation coefficient (ICC).ResultsThe ICCs between the readers ranged from 0.90 (95% CI 0.83-0.94) to 0.93 (95% CI 0.88-0.96). The ICC between the maximum angle found by the algorithm and the average manually measured Cobb angles was 0.83 (95% CI 0.71-0.90). In 9 out of the 50 cases (18%), all readers agreed on both vertebral levels for Cobb angle measurement. When using the algorithm to extract the angles at the vertebral levels chosen by the readers, the ICCs ranged from 0.92 (95% CI 0.87-0.96) to 0.97 (95% CI 0.94-0.98).ConclusionThe Cobb angle can be accurately measured on MRI using the newly developed algorithm in patients with DS. The readers failed to consistently choose the same vertebral level for Cobb angle measurement, whereas the automatic approach ensures the maximum angle is consistently measured.Clinical relevance statementOur AI-based algorithm offers reliable Cobb angle measurement on routine MRI for degenerative scoliosis patients, potentially reducing the reliance on conventional radiographs, ensuring consistent assessments, and therefore improving patient care.Key Points center dot While often available, MRI images are rarely utilized to determine the severity of degenerative scoliosis.center dot The presented MRI Cobb angle algorithm is more reliable than humans in patients with degenerative scoliosis.center dot Radiographic imaging for Cobb angle measurements is mitigated when lumbar MRI images are available.Key Points center dot While often available, MRI images are rarely utilized to determine the severity of degenerative scoliosis.center dot The presented MRI Cobb angle algorithm is more reliable than humans in patients with degenerative scoliosis.center dot Radiographic imaging for Cobb angle measurements is mitigated when lumbar MRI images are available.Key Points center dot While often available, MRI images are rarely utilized to determine the severity of degenerative scoliosis.center dot The presented MRI Cobb angle algorithm is more reliable than humans in patients with degenerative scoliosis.center dot Radiographic imaging for Cobb angle measurements is mitigated when lumbar MRI images are available.
引用
收藏
页码:5748 / 5757
页数:10
相关论文
共 33 条
[1]   Principal component analysis [J].
Abdi, Herve ;
Williams, Lynne J. .
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2010, 2 (04) :433-459
[2]   The adult scoliosis [J].
Aebi, M .
EUROPEAN SPINE JOURNAL, 2005, 14 (10) :925-948
[3]  
Alharbi RH, 2020, 2020 3 INT C COMPUTE, P1
[4]  
Allegri Massimo, 2016, F1000Res, V5
[5]   A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation [J].
Alukaev, Danis ;
Kiselev, Semen ;
Mustafaev, Tamerlan ;
Ainur, Ahatov ;
Ibragimov, Bulat ;
Vrtovec, Tomaz .
EUROPEAN SPINE JOURNAL, 2022, 31 (08) :2115-2124
[6]   Adult degenerative scoliosis: A review [J].
Birknes, John K. ;
White, Andrew P. ;
Albert, Todd J. ;
Shaffrey, Christopher I. ;
Harrop, James S. .
NEUROSURGERY, 2008, 63 (03) :A94-A103
[7]  
Cicek Ozgun, 2016, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016. 19th International Conference. Proceedings: LNCS 9901, P424, DOI 10.1007/978-3-319-46723-8_49
[8]  
Cobb J, 1948, Instr Course Lect AAOS, V5, P261
[9]   Adult spinal deformity [J].
Diebo, Bassel G. ;
Shah, Neil, V ;
Boachie-Adjei, Oheneba ;
Zhu, Feng ;
Rothenfluh, Dominique A. ;
Paulino, Carl B. ;
Schwab, Frank J. ;
Lafage, Virgirlie .
LANCET, 2019, 394 (10193) :160-172
[10]   The Aging of the Global Population: The Changing Epidemiology of Disease and Spinal Disorders INTRODUCTION [J].
Fehlings, Michael G. ;
Tetreault, Lindsay ;
Nater, Anick ;
Choma, Ted ;
Harrop, James ;
Mroz, Tom ;
Santaguida, Carlo ;
Smith, Justin S. .
NEUROSURGERY, 2015, 77 :S1-S5