|SYMPOSIUM: ADOLESCENT IDIOPATHIC SCOLIOSIS
|Year : 2020 | Volume
| Issue : 2 | Page : 143-150
Classification systems in adolescent idiopathic scoliosis revisited: Is a three-dimensional classification needed?
Krishnankutty Venugopal Menon
Department of Orthopaedics, Bharati Vidyapeeth Medical College, Pune, Maharashtra, India
|Date of Submission||21-Oct-2019|
|Date of Decision||02-Dec-2019|
|Date of Acceptance||24-Apr-2020|
|Date of Web Publication||13-Jul-2020|
Krishnankutty Venugopal Menon
Department of Orthopaedics, Bharati Vidyapeeth Medical College, Pune, Maharashtra.
Source of Support: None, Conflict of Interest: None
Classification systems for adolescent idiopathic scoliosis (AIS) have been in existence since the Schulthess system of 1905. Despite the numerous schema that have evolved over the last 115 years, little has changed from the original system based on the location of the coronal plane apex of the curves. Attempts at adding the sagittal plane, axial plane and shoulder balance to the system has generally yielded unscientific schemas or unwieldy numbers of variables within the scheme. The fundamental flaw with all these classifications is that they are based on two-dimensional imaging. The introduction of 3-D imaging like EOS and surface topography studies allow us an entirely novel perception of the spinal orientation in space. Thus the 3-D classifications that have emerged does not necessarily mean adding on Cartesian co-ordinates to the existing systems, but a far more comprehensive, yet simplistic view of the spinal deformity. Evidently, we are far from fully establishing all the variables and potentials of such schemas. Current modalities of 3-D imaging and evaluation are largely in the research domain and have not yet reached the clinical practice stage. The clinical utility of such 3-D classifications is also conjectural at present. But it is eminently possible that in the foreseeable future scoliosis classifications would cease to appear and be applied as they are today.
Keywords: 3D classification, adolescent idiopathic scoliosis, scoliosis, scoliosis classification, spinal deformity
|How to cite this article:|
Menon KV. Classification systems in adolescent idiopathic scoliosis revisited: Is a three-dimensional classification needed?. Indian Spine J 2020;3:143-50
|How to cite this URL:|
Menon KV. Classification systems in adolescent idiopathic scoliosis revisited: Is a three-dimensional classification needed?. Indian Spine J [serial online] 2020 [cited 2021 Nov 29];3:143-50. Available from: https://www.isjonline.com/text.asp?2020/3/2/143/289660
Science is the systematic classification of experience.
George Henry Lewes
……….. and all classification is the root of prejudice.
| Historical Introduction|| |
There have been numerous classifications for adolescent idiopathic scoliosis (AIS) over the years. Yet surprisingly little new information has been added in each successive generation. Schulthessin 1905 is credited with the first classification of AIS. It is quite remarkable that he described five curve types based on the location of the deformity: thoracic, lumbar, thoracolumbar, cervicothoracic, and combined. Fifty years later, James in 1954 expanded the classification to nine types, again based on the same criteria. In 1948 John Cobb is recorded to have described the criteria for major and minor (structural and nonstructural) curves in his classification schema. Meanwhile, in 1950 Ponseti and Friedman reinvented the Schulthess’s schema based on the location of the curve apex. Almost 20 years later, Harrington published his classification with similar characteristics but added curve magnitude and assigned instrumentation strategies for each curve pattern. In 1973 Goldstein and Waugh described the terminology and classification of scoliosis––it was the same as the others who came before and after them! The King–Moe system published in 1983 has been the mainstay of deformity surgeons globally for over two decades and is still used in many centers. Although Winter and Lonstein (as quoted by Dickson and Harms) and Coonrad et al. have attempted to further elaborate AIS classifications, none have influenced surgical decision-making significantly. The Lenke’s classification of 2001 is considered the current benchmark for AIS. In addition to the six basic curve patterns based on curve location, it takes into account the sagittal plane deformity as well as the coronal plane translation of the lumbar apex. The Peking Union Medical College (PUMC) classification that was published by the Chinese group of authors in 2005 is a much simpler scheme, although less popular at this time. It addresses the coronal plane primarily but also looks at the axial plane (apical vertebral rotation) and to a lesser extent the sagittal plane. In 2011 Se Il Suk of South Korea published his classification system, once again based on two-dimensional (2D) imaging by X-rays, but emphasizing the neutrally rotated vertebrae as end points and segmental rotational correction as the primary maneuver for deformity correction. Each of these classifications has been shown to have good inter- and intraobserver reliability in the hands of their originators but less so when independently assessed.,,,
A few points are obvious at a glance from the above narrative. First, all the classification systems that have emerged in the last 100 years are based on two plane images (radiographs). Moreover, they all look primarily at the coronal plane deformity and that too the location of the apex. The original plan of thoracic, lumbar, and thoracolumbar has changed little since the first description of Schulthess. Obviously addition of the sagittal plane modifier and lumbar apical translation as in the Lenke scheme would appear to enhance the value of the system but several important variables such as axial plane rotation, trunk shift, and shoulder levels have still been omitted. Needless to say, the incorporation of these parameters would make the classification structure large and unwieldy. For example, the 42 Lenke subtypes if graded for axial plane rotation of the apical vertebra as mild, moderate, and severe would yield 126 subtypes!!! Recently, Elsebaie et al. have published a study where the shoulder balance is taken into account as well; yet this system remarkably simplifies the classification into six subtypes only. Less frequently discussed by surgeons are the schemes that look at the clinical deformity rather than X-rays such as the Trunk Appearance Perception Scale (TAPS) and Walter-Reed Visual Assessment Scale (WRVS), which both look at the cosmetic disfigurement produced by the scoliosis subjectively and objectively. The TAPS was published by Bago et al. and the WRVS by Sanders et al. Sanders et al. also brought out the SPQ (Spinal Appearance Questionnaire). In addition, the SOSORT group has popularized several classifications such as the Rigo–Cheneau, Lehnert–Schroth, which, though primarily meant for brace design, fabrication, and rehabilitation, essentially look at the spinal deformity and trunk alignment in terms of spatial orientation of the trunk around the central axis, much unlike the radiological schemes discussed above.,,,,,, Each curve of the spine along with the trunkal element attached is treated as a wedge that is displaced about the three Cartesian coordinates [Figure 1]. Much alike to the surgical classifications that depend on the Center Sacral Vertical Line (CSVL) and the C7 plumb line, the bracing schemas are based on the offset of the Transitional Point (the neutral vertebra between adjacent curves) from the CSVL [Figure 2].
|Figure 1: The Schroth concept of the displacement of body segments about the Cartesian co-ordinates|
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|Figure 2: The Rigo-Weiss classification system. The 4 basic curve patterns are based on the relationship of the transitional point to the CSVL, and the T1 and T4 vertebrae tilts|
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It seems intriguing that spinal deformity has one classification system for bracing, another one for surgical planning and yet another for cosmetic appraisal, though the terms of reference appears same for all of them. Does this not imply that we are not really classifying the disease itself and thereafter assigning treatment but tend to be stratifying the treatment plan according to a pre-determined policy engraved in our minds? (say, for example, Cobb angle of a given curve). The question then is whether the radiological–surgical classifications can stand alone in future. Do we need to integrate them with cosmetic, clinical, patient reported schemas and also incorporate nonsurgical treatment such as bracing? What might be the impact of newer 3D imaging on these classifications? How would clinical photography and surface imaging add value to the information accrued? Would such a comprehensive classification be functionally useful in determining treatment strategy for a given patient? Would newer technologies such as digital archiving and CBIR (content-based image retrieval), fuzzy logic-based algorithms, machine learning and artificial intelligence change the way we evaluate and assign therapy for AIS?
| Three-dimensional Classifications|| |
What do we understand by 3D evaluation and 3D classification of the deformed spine? Why do we need it? Scoliosis is acknowledged to be a 3D deformity of the spine and yet studies thus far have been based on 2D imaging obtained by X-rays. The deformity is rarely if ever analyzed by the Cartesian coordinates to determine the actual spatial orientation of the deformed spine. At a superficial glance, it would appear that adding one more dimension to the existing systems (e.g., adding the transverse plane measure to the Lenke system) would be adequate. Implying a 2D image as obtained by a pair of X-rays is resolved into the X-, Y-, and Z-axes. The whole cohort of scoliosis patients is then regrouped according to the additional information thus obtained. But the other approach, that many French and French–Canadian surgeons have been working on, is the use of computerized image acquisition tools to acquire the actual spatial orientation of the spine in three dimensions, particularly the “top–down view” (Da Vinci view). The measurements made are then related to identifying the barycenter (axis of gravity) and the relationship of the various curves to this axis. Typically, the plane of maximum deformity and the degree of displacement from the center are measured [Figure 3]. This concept is akin to the deformity correction planning by the Taylor Spatial frame software (Smith + Nephew Inc, Andover, MA, USA). Although these proposed measures do give us a precise concept of the orientation and balance of the spine, trunk, pelvis, and chest wall, it does not tell us how to treat a given case, for example, selection of fusion levels, implant density, or correction maneuvers, at least for the time being.
|Figure 3: Schematic representation of the top view of the deformed spine and the plane of maximum curve (PMC) of each cure (adapted from Donzelli S et al.). MT = Main thoracic, TL/L = Thorocolumbar/lumbar, PT = Proximal thoracic|
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The current systems in vogue
The concept of a 3D classification of the spinal deformity is not new. Poncet et al. described their geometric torsion concept in 2001. Many years before, in 1994, Ian Stokes introduced the 3D terminology to the Scoliosis Research Society (SRS). The Cotrel–Dubousset instrumentation that appeared in 1984 was perhaps one of the forerunners of the concept of axial plane deformation in AIS and its correction by segmental holds on the spine. The essential issue in early literature appears to be the exact modus of acquiring the axial plane images. Typically, axial plane data are derived from top view images, computer reconstructed images, stereo radiography, surface analysis, and finite-element modeling. Poncet et al. used anteroposterior (AP) and lateral X-rays and generated a digitized model of the spine based on pedicle rotation. They described three possible patterns of geometric torsion in all AIS cases but did not offer any treatment suggestions for each based on their schema. Duong et al. and Sangole et al. used cluster analysis to describe the various curve patterns as visualized from the axial plane. The PMC (plane of maximal curvature) is a key term they use to describe the direction of the curvature along the axial plane. Thong et al. described two basic curve patterns: one with thoracic hypokyphosis larger than lumbar and the other with the reverse pattern. Negrini et al. used an optoelectronic system (AUSCAN) in 149 cases for image acquisition; they described the global position of the spine in three domains: direction, shift, and phase, each describing the deviation of the axis, the position of the barycenter, and the spatial relation of one curve to the next, respectively [Figure 4]. Kadoury and Labelle also used computer-reconstructed models in the Lenke 1 curve-type patients and their classification describes four subtypes to this curve pattern: normal kyphosis, hyper lordosis, and high Cobb angles; hypo kyphosis, normal lordosis, and high rotation of PMC; hypokyphosis with hyper lordosis; and hyperkyphosis with severe vertebral rotation. The emphasis was on determining the direction of deformity of each of the curves or “PMC” as termed by these authors. Aubin et al. from the Montreal polytechnique described the variability in spinal instrumentation possible in various scoliosis clusters based on the 3D reconstructed models. Donzelli et al. performed a systematic review of 3D classifications of spinal deformities till date and their study highlights numerous issues with the knowledge thus far. None of these appear to correlate with our existing 2D classification systems; moreover, they do not have any therapeutic orientation. The value of these schema thus far is largely research oriented. Jean Dubousset, in a recent keynote address, brought out several remarkable insights into the axial plane in spinal deformity. Besides describing the cephalic vertebra and the pelvic vertebra in 1972 and emphasizing the role of balance as the relationship between these and the gravity axis on standing, Dubousset et al. at the ENSAM institute in Paris developed the EOS (End of Scan) system (EOS Imaging SA, Paris, France) that allows low-radiation 3D skeletal images in the standing position. Graf et al. first described the 3D deformation in scoliosis in 1978 and proposed the importance of the “top view” of the spine. Modern EOS systems permit such top view evaluation of spinal deformity and assigns barycentrometric evaluation of the spine. Dubousset goes on to predict that in future the measurement of Cobb angle will be obsolete and replaced by such barycentric measures. The projected advantage of the EOS based 3D system (besides the lesser dosage of radiation) is that even bracing strategies and thoracic cage deformations can be studied using the device. Pasha et al. have recently published their technique of recreating the vertebral centroid orientation in space with the MATLAB software (Mathworks Inc, Natick, MA, USA) to produce an orthogonal view of the spine to give five basic curve clusters in a series of 103 scoliosis patients. In summary, though the potential of this study domain appears immense, as of now the evaluation of the third dimension of spinal deformity and the development of a classification to include that measure has limited clinical applicability.
|Figure 4: The axial plane of the deformed spine (adapted from Negrini S et al.)|
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| Discussion|| |
For a moment consider what the very purpose of a classification in AIS is. It should describe all possible variations of the deformity (clearly distinguish apples from oranges), allow accurate documentation, permit archival and retrieval of case records, enhance ease of communication between professionals, help assign therapeutic strategies, and improve outcome prognostication of therapy. Arlet has elegantly summarized what the ideal classification schema should achieve––cover all curve patterns, be easily memorized, be easily reproduced and reliable, be therapy oriented, be outcome related, and posses scope for future expansion. Obviously we are far from achieving these objectives. Dickson and Harms have lamented that “new classifications seem irresistible.” They go on to suggest that perhaps the paradigm has shifted from understanding the biology and the mechanics of spinal deformation to creating cook book recipes for each of the curve types. The original SRS classification, the authors quote, consists of single, double, and triple curves with three subgroups in the first two based on the location of the curves. This is adequate in planning nearly all curve types successfully according to him.
Let us also try and understand what the limitations of the current classification systems of AIS are [Table 1]. First, the ambiguity in choosing an appropriate schema that avoids regional, linguistic, training, and other biases. There is evidently little inter-operability between the various systems that might have a beneficial additive effect. This means that the same curve (in the same patient) might be assigned different treatments depending on which classification one chooses to apply!!! Although the authors and their protégés have shown good results, actual inter- and intraobserver variability of most schemes are dubious. Robitaille et al. and Aubin et al. have published two interesting studies in the European Spine Journal in 2007 highlighting the extreme variability in treatment options when the very popular Lenke system was used. Some of the newer schema such as the PUMC and the Lenke are often difficult to memorize due to the numerous sub and sub–sub types. This is besides what are often described as “outliers” or “rule breakers.” Future parameters such as axial plane deformation, trunk shift, and rib cage deformity have not been added to the existing schemes, nor is there scope to do so without making an already cumbersome system unwieldy. One of the major criticisms of the Lenke classification is the very sagittal plane measurement it adds to traditional schemas––it’s claimed advantage over others. Given that the sagittal plane measures are taken on a standard lateral standing X-ray and that they hardly reflect the true sagittal plane of the spine due to the vertebral rotation (as opposed to du Peloux et al.’s plan d’election views), the true value of this information is doubted. In addition, visibility of the strategic D2, D5, and D10 vertebrae on standing lateral roentgenograms is often poor and measurements are at best imaginary. The latter authors are also critical of the fact that normal values for thoracic kyphosis in adolescents are not known due to the evolving nature of the spine at maturation. So, the cutoff value of 20° may have little meaning according to them. Dickson and Harms also describe the junctional kyphosis seen on the sagittal plane X-rays as spurious due to the rotated lordosis of the individual curves with the neutrally rotated junctional vertebrae appearing so on the lateral X-ray. Moreover, the Lenke classification system is based on the need for posterior corrections alone, whereas many curves can be adequately and often better addressed anteriorly (specifically Lenke 1, 5, and 6).
The PUMC system has been shown by Qiu and Li (the original authors) in 2008 to have similar excellent and good results as Lenke in the domains of inter- and intraobserver reliability with fewer errors in selection of fusion levels and easier to memorize. Their study was based on a database of 427 cases of AIS, which makes it numerically quite sound. Unfortunately, the schema has not enjoyed the widespread patronage it deserved. The scheme considers apical vertebral rotation as well as the sagittal plane at D12-L1 in planning the treatment. It has 13 subtypes and is therefore easier than the Lenke system to remember. Zhuang et al. published the modified version that includes shoulder balance correction by addressing the proximal thoracic curve appropriately. Zhang et al. have published a computerized version of the schema with a higher degree of precision. The Suk’s system has the putative advantage that it considers axial plane rotation of the deformed spinal segment. Typically, fusion extends from neutral to neutral vertebrae. Yet the schema is deficient in many ways––it does not include all potential curve patterns, it is meant only for posterior correction with 100% screw density, and it uses segmental vertebral rotation as the sole correction maneuver.
One remarkable feature about AIS is that most features that we currently use to describe the deformity are morphological variables measured on X-rays such as Cobb angle, vertebral rotation, and trunk shift. Even clinical photographic features are amenable to digital measurement. This essentially renders nonmanual data collection and archival relatively easier. The authors had proposed the CBIR strategy for scoliosis X-rays some years ago. The same strategy might also be applicable for planning surgery. The concept is attractive in that it eliminates classification systems altogether. Based on the image attributes and the available cases in the database, a treatment is assigned to a given case. The statistical variability from the standard is also given at the same time enhancing the predictability of the outcomes of surgery (or indeed bracing).
The future of AIS classifications is interesting to conceptualize. Computerized documentation of medical information has been in practice for the last three decades and has come to stay. Digital archiving and retrieval of radiographic as well as clinical images is the order of the day and scoliosis images are no exception. The addition of artificial intelligence and robotic technologies would enhance the potential of the available resources infinitely. Fuzzy logic-based algorithms for selection of appropriate treatment strategies would appear to be the future rather than classification-based programs. The author has studied the concept of CBIR and found that morphological variables in scoliosis can be accurately picked up and archived without a classification based category assignment. In future, we may be able to identify curves based on just pictorial features and in finger printing or retina scanning. Clearly 3D imaging modalities, especially with low-dose radiation such as EOS, will hold the future but till it becomes affordable to much of the developing world where most of the population is concentrated, computerized reconstruction would have to do. One thing is almost certain: scoliosis classifications as we see it today are likely to be obsolete in the near future.
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| References|| |
Schulthess W. Die pathologie und therapie der Rückgratsverkrümmungen. In: Chirurgie HBO, editor. Volume 1. Jena, Joachimsthal, Germany; 1906. p. 1905-7.
James JIP. Idiopathic scoliosis. The prognosis, diagnosis and operative indications related to curve patterns and age of onset. J Bone Joint Surg 1954;36-B:36-49.
Ovadia D. Classification of adolescent idiopathic scoliosis (AIS). J Child Orthop 2013;7:25-8.
Ponseti IV, Friedman B. Prognosis in idiopathic scoliosis. J Bone Joint Surg Am 1950;32A:381-95.
Harrington PR. Technical details in relation to the successful use of instrumentation in scoliosis. Orthop Clin North Am 1972;3: 49-67.
Goldstein LA, Waugh TR. Classification and terminology of scoliosis. Clin Orthop Relat Res1973:10-22.
King HA, Moe JH, Bradford DS, Winter RB. The selection of fusion levels in thoracic idiopathic scoliosis. J Bone Joint Surg Am 1983;65:1302-13.
Dickson R, Harms J, editors. Modern management of spinal deformities. Stuttgart, Germany: Thieme; 2018.
Coonrad RW, Murrell GA, Motley G, Lytle E, Hey LA. A logical coronal pattern classification of 2,000 consecutive idiopathic scoliosis cases based on the Scoliosis Research Society-defined apical vertebra. Spine (Phila Pa 1976) 1998;23:1380-91.
Lenke LG, Betz RR, Harms J, Bridwell KH, Clements DH, Lowe TG, et al
. Adolescent idiopathic scoliosis: A new classification to determine extent of spinal arthrodesis. J Bone Joint Surg Am 2001;83:1169-81.
Qiu G, Zhang J, Wang Y, Xu H, Zhang J, Weng X, et al
. A new operative classification of idiopathic scoliosis: A Peking union medical college method. Spine (Phila Pa 1976) 2005;30:1419-26.
Suk SI. Pedicle screw instrumentation for adolescent idiopathic scoliosis: The insertion technique, the fusion levels and direct vertebral rotation. Clin Orthop Surg 2011;3:89-100.
Cummings RJ, Loveless EA, Campbell J, Samelson S, Mazur JM, et al
. Interobserver reliability and intraobserver reproducibility of the system of king. For the classification of adolescent idiopathic scoliosis. J Bone Joint Surg Am 1998;80:1107-11.
Richards BS, Sucato DJ, Konigsberg DE, Ouellet JA. Comparison of reliability between the Lenke and King classification systems for adolescent idiopathic scoliosis using radiographs that were not premeasured. Spine (Phila Pa 1976) 2003;28:1148-56; discussion 1156-7.
Qiu GX, Li QY, Wang YP, Zhang JG, Yu B, Wang T, et al
. Comparison of reliability between the Lenke and King classification systems for adolescent idiopathic scoliosis using radiographs that were not premeasured. Spine2003;28:1148-56; discussion 1156-7.
Sheng WB, Zheng XF, Guo HL, Zhan YL, Mai ED, Jin GL, et al
. [Intraobserver and interobserver reliability of the King, Lenke, and PUMC classification systems for idiopathic scoliosis]. Zhonghua Yi Xue Za Zhi 2009;89:1047-52.
Elsebaie HB, Dannawi Z, Altaf F, Zaidan A, Al-Mukhtar M, Shaw MJ, et al
. Erratum to: Clinically orientated classification incorporating shoulder balance for the surgical treatment of adolescent idiopathic scoliosis. Eur Spine J 2016;25:969.
Bago J, Sanchez-Raya J, Perez-Grueso FJ, Climent JM. The Trunk Appearance Perception Scale (taps): A new tool to evaluate subjective impression of trunk deformity in patients with idiopathic scoliosis. Scoliosis 2010;5:6.
Sanders JO, Polly DW Jr, Cats-Baril W, Jones J, Lenke LG, O’Brien MF, et al
; AIS Section of the Spinal Deformity Study Group. Analysis of patient and parent assessment of deformity in idiopathic scoliosis using the Walter Reed Visual Assessment Scale. Spine (Phila Pa 1976) 2003;28:2158-63.
Sanders JO, Harrast JJ, Kuklo TR, Polly DW, Bridwell KH, Diab M, et al
; Spinal Deformity Study Group. The Spinal Appearance Questionnaire: Results of reliability, validity, and responsiveness testing in patients with idiopathic scoliosis. Spine (Phila Pa 1976) 2007;32:2719-22.
Rigo M. Abstracts. International conference on conservative management of spinal deformities Barcelona 23–24 January 2004. Pediatr Rehabil 2004;7:51-64.
Corset-Chêneau CJ. Manuel d’orthopédie des scolioses suivant la technique originale. Paris, France: Édition Frison-Roche; 1994.
Rigo M. Intra-observer reliability of a new classification correlating with brace treatment. Pediatr Rehabil 2004;7:63.
Rigo M, Weiss HR. The Chêneau concept of bracing–biomechanical aspects. Stud Health Technol Inform 2008;135:303-19.
Rigo M, Jelačić M. Brace technology thematic series: The 3D Rigo Chêneau-type brace [J]. Scoliosis Spinal Disord 2017;12:1-49.
Lehnert-Schroth Ch. Dreidimensionalle Skoliosebehandlung. 6 Auflage. Stuttgart, Germany: Urban and Scharzer; 2000.
Weiss HR. The method of Katharina Schroth: History, principles and current development. Scoliosis 2011;6:17.
Dubousset J. Recorded webinar available at: www.ssftv.org [Last accessed on 30 Apr 2020]. Seattle, WA: Seattle Science Foundation; 2020.
Poncet P, Dansereau J, Labelle H. Geometric torsion in idiopathic scoliosis: Three-dimensional analysis and proposal for a new classification. Spine (Phila Pa 1976) 2001;26:2235-43.
Stokes IA. Three-dimensional terminology of spinal deformity: A report presented to the Scoliosis Research Society by the Scoliosis Research Society Working Group on 3D terminology of spinal deformity. Spine 1994;19:236-48.
Cotrel Y, Dubousset J, Guillaumat M. New universal instrumentation in spinal surgery. Clin Orthop Relat Res 1988;227:10-23.
Duong L, Cheriet F, Labelle H. Three-dimensional classification of spinal deformities using fuzzy clustering. Spine (Phila Pa 1976) 2006;31:923-30.
Sangole AP, Aubin CE, Labelle H, Stokes IA, Lenke LG, Jackson R, et al
. Three-dimensional classification of thoracic scoliotic curves. Spine (Phila Pa 1976) 2009;34:91-9.
Thong W, Parent S, Wu J, Aubin CE, Labelle H, Kadoury S. Three-dimensional morphology study of surgical adolescent idiopathic scoliosis patient from encoded geometric models. Eur Spine J 2016;25:3104-13.
Negrini S, Atanasio S, Fusco C, Zaina F, Negrini A. 3DEMO classification of scoliosis: A useful understanding of the 3(rd) dimension of the deformity. Stud Health Technol Inform 2008;135:139-53.
Kadoury S, Labelle H. Classification of three-dimensional thoracic deformities in adolescent idiopathic scoliosis from a multivariate analysis. Eur Spine J 2012;21:40-9.
Aubin CE, Labelle H, Ciolofan OC. Variability of spinal instrumentation configurations in adolescent idiopathic scoliosis. Eur Spine J 2007;16:57-64.
Donzelli S, Poma S, Balzarini L, Borboni A, Respizzi S, Villafane JH, et al
. State of the art of current 3D scoliosis classifications: A systematic review from a clinical perspective. J Neuroeng Rehabil 2015;12:91.
Dubousset J, Charpak G, Skalli W, Kalifa G, Lazennec JY. EOS stereo-radiography system: Whole-body simultaneous anteroposterior and lateral radiographs with very low radiation dose. Rev Chir Orthop Reparatrice Appar Mot 2007;93:141-3.
Graf H, Hecquet J, Dubousset J. [3Dimensional approach to spinal deformities. Application to the study of the prognosis of pediatric scoliosis]. Rev Chir Orthop Reparatrice Appar Mot 1983;69: 407-16.
Pasha S, Hassanzadeh P, Ecker M, Ho V. A hierarchical classification of adolescent idiopathic scoliosis: Identifying the distinguishing features in 3D spinal deformities. PLoS One 2019;14: e0213406.
Arlet V. Deformity severity measures: scoliosis. In: Chapman JR, Dettori JR, Norvell DC, editors. Spine Classifications and Severity Measures. New York: Thieme; 2009. p. 63-97.
Robitaille M, Aubin CE, Labelle H. Intra and interobserver variability of preoperative planning for surgical instrumentation in adolescent idiopathic scoliosis. Eur Spine J 2007;16:1604-14.
du Peloux J, Fauchet R, Faucon B, Stagnara P. Le plan d’election pour l’examen radiologique des cypho-scolioses. Rev Chir Orthop Repar Appar Mot 1965;51:517-24.
Zhuang Q, Qiu G, Li Q, Zhang J, Shen J, Wang Y, et al
. Modified PUMC classification for adolescent idiopathic scoliosis. Spine J 2019;19:1518-28.
Zhang J, Li H, Zhang Y. Application of computer-aided approaches to the PUMC classification of scoliosis. Biomed Eng Lett 2017:7;245.
Dinesh K, Vathiath P, Tessamma T, Menon KV. Content based image retrieval of spine radiographs with scoliosis. J Spinal Disord Tech 2009;22:284-9.
Phan P, Mezghani N, Nault ML, Aubin CE, Parent S, de Guise J, et al
. A decision tree can increase accuracy when assessing curve types according to Lenke classification of adolescent idiopathic scoliosis. Spine (Phila Pa 1976) 2010;35:1054-9.
Menon KV, Dinesh Kumar VP, Tessamma T. Experiments with a novel content based image retrieval software: Can we eliminate classification systems in adolescent idiopathic scoliosis. Global Spine J 2014;4:13-20.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]