Guo Shangyu,Wang Dahui.Combining artificial intelligence for diagnosing adolescent idiopathic scoliosis[J].Journal of Clinical Pediatric Surgery,,():89-92.[doi:10.3760/cma.j.cn101785-202211044-018]
Combining artificial intelligence for diagnosing adolescent idiopathic scoliosis
- Keywords:
- Adolescent Idiopathic Scoliosis; Artificial Intelligence; School Scoliosis Screening; Early Diagnosis; Non-Radiation; Review
- Abstract:
- As the most common type of scoliosis,adolescent idiopathic scoliosis (AIS) occurs predominantly in adolescents.Lateral spinal curvature >10° is the most common type of scoliosis.An early diagnosis and a timely intervention are essential for reducing complications and optimizing outcomes.Although mass screening for AIS has remained controversial at schools,it is also widely implemented.Currently a routine tool for evaluating scoliosis is using a scoliometer for Adam test.First proposed in 1948,manual radiographic measurement of Cobb angle has remained a gold standard.However,this diagnostic modality is radioactive and it relies heavily on the professional capability of an examiner.Thus it is quite imperative to seek early screening and diagnostic modalities with high sensitivity,high specificity,non-radiation and high efficiency.In recent years,with a rapid development of artificial intelligence (AI),it has also accelerated the progress of medical imaging and diagnostics.This review focused upon three-dimensional spinal imaging based upon ultrasound,scoliosis detection system based upon three-dimensional camera or sensor,combination of two-dimensional digital camera and AI and posture analysis system based upon computer vision for applying artificial intelligence to AIS screening.It was intended to offer new rationales for clinical scientific researches and development directions.
References:
[1] Cheng JC,Castelein RM,Chu WC,et al.Adolescent idiopathic scoliosis[J].Nat Rev Dis Primers,2015,1:15030.DOI:10.1038/nrdp.2015.30.
[2] Hresko MT.Clinical practice.Idiopathic scoliosis in adolescents[J].N Engl J Med,2013,368(9):834-841.DOI:10.1056/NEJMcp1209063.
[3] Sharma S,Londono D,Eckalbar WL,et al.A PAX1 enhancer locus is associated with susceptibility to idiopathic scoliosis in females[J].Nat Commun,2015,6:6452.DOI:10.1038/ncomms7452.
[4] Grivas TB,Vasiliadis ES,Mihas C,et al.Trunk asymmetry in juveniles[J].Scoliosis,2008,3:13.DOI:10.1186/1748-7161-3-13.
[5] Kotwicki T,Kinel E,Stryla W,et al.Discrepancy in clinical versus radiological parameters describing deformity due to brace treatment for moderate idiopathic scoliosis[J].Scoliosis,2007,2:18.DOI:10.1186/1748-7161-2-18.
[6] Cobb JLCJRCJ.Outlines for the study of scoliosis[J].J Bone Joint Surg Am,1948,5:261-275.
[7] Hines T,Roland S,Nguyen D,et al.School scoliosis screenings:family experiences and potential anxiety after orthopaedic referral[J].Spine (Phila Pa 1976),2015,40(21):E1135-E1143.DOI:10.1097/BRS.0000000000001040.
[8] Fong DYT,Lee CF,Cheung KMC,et al.A meta-analysis of the clinical effectiveness of school scoliosis screening[J].Spine (Phila Pa 1976),2010,35(10):1061-1071.DOI:10.1097/BRS.0b013e3181bcc835.
[9] Luan FJ,Zhang J,Mak KC,et al.Low radiation X-rays:benefiting people globally by reducing cancer risks[J].Int J Med Sci,2021,18(1):73-80.DOI:10.7150/ijms.48050.
[10] Vrtovec T,Pernus F,Likar B.A review of methods for quantitative evaluation of spinal curvature[J].Eur Spine J,2009,18(5):593-607.DOI:10.1007/s00586-009-0913-0.
[11] Doody MM,Lonstein JE,Stovall M,et al.Breast cancer mortality after diagnostic radiography:findings from the U.S.Scoliosis Cohort Study[J].Spine (Phila Pa 1976),2000,25(16):2052-2063.DOI:10.1097/00007632-200008150-00009.
[12] Knott P,Mardjetko S,Nance D,et al.Electromagnetic topographical technique of curve evaluation for adolescent idiopathic scoliosis[J].Spine (Phila Pa 1976),2006,31(24):E911-E915.DOI:10.1097/01.brs.0000245924.82359.ab.
[13] 李芹,刘文英.人工智能在小儿外科领域的应用及展望[J].中华小儿外科杂志,2021,42(1):76-81.DOI:10.3760/cma.j.cn421158-20190813-00496. Li Q,Liu WY.Applications and future prospects of artificial intelligence in pediatric surgery[J].Chin J Pediatr Surg,2021,42(1):76-81.DOI:10.3760/cma.j.cn421158-20190813-00496.
[14] Horng MH,Kuok CP,Fu MJ,et al.Cobb angle measurement of spine from X-ray images using convolutional neural network[J].Comput Math Methods Med,2019,2019:6357171.DOI:10.1155/2019/6357171.
[15] Wang LS,Xu QH,Leung S,et al.Accurate automated Cobb angles estimation using multi-view extrapolation net[J].Med Image Anal,2019,58:101542.DOI:10.1016/j.media.2019.101542.
[16] Wu HB,Bailey C,Rasoulinejad P,et al.Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net[J].Med Image Anal,2018,48:1-11.DOI:10.1016/j.media.2018.05.005.
[17] Fenster A,Downey DB,Cardinal HN.Three-dimensional ultrasound imaging[J].Phys Med Biol,2001,46(5):R67-R99.DOI:10.1088/0031-9155/46/5/201.
[18] Nelson TR,Pretorius DH.Three-dimensional ultrasound imaging[J].Ultrasound Med Biol,1998,24(9):1243-1270.DOI:10.1016/s0301-5629(98)00043-x.
[19] Lou E,Nguyen D,Hill D,et al.Validation of a novel handheld 3D ultrasound system for imaging scoliosis-phantom study[J].Stud Health Technol Inform,2021,280:100-105.DOI:10.3233/SHTI210444.
[20] Hisaund A,Pietton R,Vialle R,et al.Feasibility of rib kinematics and intercostal-space biomechanical characterization by ultrasound in adolescent idiopathic scoliosis[J].Ultrasound Med Biol,2021,47(7):1957-1963.DOI:10.1016/j.ultrasmedbio.2021.03.017.
[21] F?lsch C,Schl?gel S,Lakemeier S,et al.Test-retest reliability of 3D ultrasound measurements of the thoracic spine[J].PM R,2012,4(5):335-341.DOI:10.1016/j.pmrj.2012.01.009.
[22] Takács M,Orlovits Z,Jáger B,et al.Comparison of spinal curvature parameters as determined by the ZEBRIS spine examination method and the Cobb method in children with scoliosis[J].PLoS One,2018,13(7):e0200245.DOI:10.1371/journal.pone.0200245.
[23] Jiang WW,Chen XT,Yu CH.A real-time freehand 3D ultrasound imaging method for scoliosis assessment[J].J Appl Clin Med Phys,2022,23(8):e13709.DOI:10.1002/acm2.13709.
[24] Lv P,Chen JY,Dong LJ,et al.Evaluation of scoliosis with a commercially available ultrasound system[J].J Ultrasound Med,2020,39(1):29-36.DOI:10.1002/jum.15068.
[25] Sudo H,Kokabu T,Abe Y,et al.Automated noninvasive detection of idiopathic scoliosis in children and adolescents:a principle validation study[J].Sci Rep,2018,8(1):17714.DOI:10.1038/s41598-018-36360-w.
[26] Kokabu T,Kawakami N,Uno K,et al.Three-dimensional depth sensor imaging to identify adolescent idiopathic scoliosis:a prospective multicenter cohort study[J].Sci Rep,2019,9(1):9678.DOI:10.1038/s41598-019-46246-0.
[27] Sapkas G,Papagelopoulos PJ,Kateros K,et al.Prediction of Cobb angle in idiopathic adolescent scoliosis[J].Clin Orthop Relat Res,2003,411:32-39.DOI:10.1097/01.blo.0000068360.47147.30.
[28] Roy S,Grünwald ATD,Alves-Pinto A,et al.A noninvasive 3D body scanner and software tool towards analysis of scoliosis[J].Biomed Res Int,2019,2019:4715720.DOI:10.1155/2019/4715720.
[29] Yang JL,Zhang K,Fan HW,et al.Development and validation of deep learning algorithms for scoliosis screening using back images[J].Commun Biol,2019,2:390.DOI:10.1038/s42003-019-0635-8.
[30] Daruwalla JS,Balasubramaniam P.Moiré topography in scoliosis.Its accuracy in detecting the site and size of the curve[J].J Bone Joint Surg Br,1985,67(2):211-213.DOI:10.1302/0301-620X.67B2.3980527.
[31] Chowanska J,Kotwicki T,Rosadzinski K,et al.School screening for scoliosis:can surface topography replace examination with scoliometer?[J].Scoliosis,2012,7(1):9.DOI:10.1186/1748-7161-7-9.
[32] Kuroki H,Nagai T,Chosa E,et al.School scoliosis screening by Moiré topography-overview for 33 years in Miyazaki Japan[J].J Orthop Sci,2018,23(4):609-613.DOI:10.1016/j.jos.2018.03.005.
[33] Watanabe K,Aoki Y,Matsumoto M.An application of artificial intelligence to diagnostic imaging of spine disease:estimating spinal alignment from moiré images[J].Neurospine,2019,16(4):697-702.DOI:10.14245/ns.1938426.213.
[34] Akazawa T,Torii Y,Ueno J,et al.Mobile application for scoliosis screening using a standard 2D digital camera[J].Cureus,2021,13(3):e13944.DOI:10.7759/cureus.13944.
[35] Kim KH,Sohn MJ,Park CG.Conformity assessment of a computer vision-based posture analysis system for the screening of postural deformation[J].BMC Musculoskelet Disord,2022,23(1):799.DOI:10.1186/s12891-022-05742-7.
Memo
收稿日期:2022-11-21。
基金项目:科学技术部高技术研究发展中心科技创新2030——"新一代人工智能"重大项目(2021ZD0113405)
通讯作者:王达辉,Email:wangdahui@fudan.edu.cn