Patient Specific Material Mapping for Functional Outcome Prediction and Planning in Spinal Surgery

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Abstract

Background The research effort on spinal disorders and treatments has been increased during the last decades and a rapid progression in implant development has occurred. In spite of the effort, postoperative complications such as screw loosening, implant subsidence, pseudo-arthrosis still pose a relevant problem. Despite the diversity of these complications, changes of the mechanical loads acting on the anatomical structures after fusion surgery are considered to play an essential role.

Numerical simulations can help predict the stress (re-) distribution after a surgical intervention. Since, the load distribution is strongly dependent on individual factors such as anatomical and structural characteristics, the recent trend has been heading towards patient specific simulations. While patient specific geometries can be derived from radiological data by manual segmentation or with machine learning approaches, material mapping strategies are largely lacking. The lack of knowledge collides with the growing demand for patient specific simulations and leads to the goal of this dissertation:

Goal The objective of this doctoral thesis is to develop a material mapping strategy that allows individualized bone and soft tissue mapping for patient-specific computational models.

Biomechanical Fundamentals An array of experiments was performed to establish a biomechanical basis, which can serve as a fundament to build on for the development of a material mapping strategy. As a main project, a stepwise reduction study was conducted with spinal segments originating from human lumbar cadavers. The biomechanical relevance of each of the various passive spinal structure was characterized and associations with radiological data were synthesized.

It was found that spinal segments show a large inter-specific variability in stiffness, which mirrors in a large variability of range of motions of intervertebral discs and a large variability of load-displacement curves of spinal ligaments. However, this large interspecific variability stands in contrast to a very high consistency of the contribution patterns between the different anatomical structures. This consistency exists across different levels and throughout a very heterogeneous cohort. This “principle of contribution conservation” indicates that the characteristics of the passive structures are accurately matched to one another and that they are adapted to the specific range of motion of the spinal segment.

It was further found that in the degenerative situation, these contribution patterns are slightly altered due to structural degenerative changes. In the load cases in which the facet joints act as a major contributor, an increase in their contribution is observed, while some load is released from the intervertebral disc. Pretension, which exists in all structures is continuously reduced as the segment develops towards a more degenerative state.

As another sign of degeneration, spondylophytes develop. However, in contrast to the general opinion, spondylophytes (< grade 4) do not support the segment as a propping structure but increase stiffness at the spondylophyte-affected side during tensile loading. Only severe spondylophytes with osseous bridging (grade 4) show large contribution to the segmental stability. A clinical classification system based on the biomechanical data was introduced.

It was also found that shear wave elastography, which was developed for stiffness measurements, shows a decent effectiveness as an assessment tool for intervertebral disc stiffness. Data derived from the cadaveric study were used to derive a generic stiffness distribution function which allows bulk material mapping for numerical modelling.

A very intriguing finding, is a surprisingly high correlation between the intervertebral disc stiffness and the average HU-value acquired from clinical computed tomography (CT) of the intervertebral disc. While clinically established MRI based grading systems (e.g. Pfirrmann) barely show a correlation with the biomechanical properties of the intervertebral disc, the CT value is a good predictor for the mechanical condition of a specific intervertebral disc.

Soft tissue mapping On the basis of a the newly discovered correlation between the CT-intensity of the intervertebral disc and its biomechanical properties in combination with the high conformity of contribution patterns of the paraspinal structures, a novel approach for soft tissue mapping is proposed. Three features with the highest correlation (intervertebral disc area, intervertebral disc level and CT annulus intensity) were used to train a machine learning approach to predict the load deflection curves of the intervertebral disc. With the predicted range of motion during flexion-extension and the average contribution pattern, the load deflection curves of the other spinal soft-tissue structures are predicted. Besides an approach for the prediction of soft tissue parameters, a numerical material which is capable of rendering the spinal tissue realistically is another essential requirement. A tetrahedral-based, fiber reinforced, explicit Mooney Rivlin material for finite element modelling was developed and validated.

Bone tissue mapping Finite element analysis can serve as tool to preoperatively assess the performance of screw fixations in the bone. For this purpose, the individual bone density distribution must be well represented in the numerical material model of the spine. The great advantage of bone mapping in contrast to soft tissue mapping is that the apparent density on the CT has shown to be directly relate to the Young’s modulus of the bone. In order to achieve a bone mapping strategy which allows for the accurate simulation of a patient-specific screw-bone-interface, finite element pull-out simulations were performed and validated against cadaveric experiments.

Synthesis The current doctoral thesis presents a novel technique for material mapping (soft and bone tissue) in computational, spinal modelling. The required biomechanical fundamentals are established and an advanced insight in the biomechanical characteristics of the spine in the healthy and degenerated situation are elaborated within the frame of this work. The proposed material mapping strategy represents an essential milestone in person-specific computational modelling

Cited Works (32)

Year	Entry
1968	Tkaczuk H. Tensile properties of human lumbar longitudinal ligaments. Acta Orthop Scand. 1968;39(suppl 115):1-69.
1977	Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. March 1977;33(1):159-174.
1988	Urban JPG, McMullin JF. Swelling pressure of the lumbar intervertebral discs influence of age, spinal level, composition, and degeneration. Spine. February 1988;13(2):179-187.
1980	Adams MA, Stott JRR. The resistance to flexion of the lumbar intervertebral joint. Spine. May–June 1980;5(3):245-253.
1985	Chazal J, Tanguy A, Bourges M, Gaurel G, Escande G, Guillot M, Vanneuville G. Biomechanical properties of spinal ligaments and a histological study of the supraspinal ligament in traction. J Biomech. 1985;18(3):167-176.
1994	Goulet RW, Goldstein SA, Ciarelli MJ, Kuhn JL, Brown MB, Feldkamp LA. The relationship between the structural and orthogonal compressive properties of trabecular bone. J Biomech. April 1994;27(4):375-389.
2006	Gasser TC, Ogden RW, Holzapfel GA. Hyperelastic modelling of arterial layers with distributed collagen fibre orientations. J R Soc Interface. February 22, 2006;3(6):15-35.
1998	Keyak JH, Rossi SA, Jones KA, Skinner HB. Prediction of femoral fracture load using automated finite element modeling. J Biomech. February 1998;31(2):125-133.
1982	Panjabi MM, Goel VK, Takata K. Physiologic strains in the lumbar spinal ligaments: an in vitro biomechanical study. Spine. May 1982;7(3):192-203.
1967	Abrahams M. Mechanical behaviour of tendon in vitro: a preliminary report. Med Biol Eng. September 1967;5(5):433-443.
2003	Keyak JH, Falkinstein Y. Comparison of in situ and in vitro CT scan-based finite element model predictions of proximal femoral fracture load. Med Eng Phys. November 2003;25(9):781-787.
2001	Pfirrmann CWA, Metzdorf A, Zanetti M, Hodler J, Boos N. Magnetic resonance classification of lumbar intervertebral disc degeneration. Spine. September 1, 2001;26(17):1873-1878.
2001	Elliott DM, Setton LA. Anisotropic and inhomogeneous tensile behavior of the human anulus fibrosus: experimental measurement and material model predictions. J Biomech Eng. June 2001;123(3):256-263.
1994	Keller TS. Predicting the compressive mechanical behavior of bone. J Biomech. September 1994;27(9):1159-1168.
2005	Holzapfel GA, Schulze-Bauer CAJ, Feigl G, Regitnig P. Single lamellar mechanics of the human lumbar anulus fibrosus. Biomech Model Mechanobiol. March 2005;3(3):125-140.
1992	Pintar FA, Yoganandan N, Myers T, Elhagediab A, Sances A Jr. Biomechanical properties of human lumbar spine ligaments. J Biomech. November 1992;25(11):1351-1356.
1986	Pooni JS, Hukins DWL, Harris PF, Hilton RC, Davies KE. Comparison of the structure of human intervertebral discs in the cervical, thoracic and lumbar regions of the spine. Surg Radiol Anat. September 1986;8(3):175-182.
2002	Smit TH. The use of a quadruped as an in vivo model for the study of the spine: biomechanical considerations. Eur Spine J. April 2002;11(2):137-144.
1992	Oxland TR, Panjabi MM. The onset and progression of spinal injury: a demonstration of neutral zone sensitivity. J Biomech. October 1992;25(10):1165-1172.
1968	Nachemson AL, Evans JH. Some mechanical properties of the third human lumbar interlaminar ligament (ligamentum flavum). J Biomech. August 1968;1(3):211-220.
1987	Pearce RH, Grimmer BJ, Adams ME. Degeneration and the chemical composition of the human lumbar intervertebral disc. J Orthop Res. 1987;5(2):198-205.
1982	Tencer AF, Ahmed AM, Burke DL. Some static mechanical properties of the lumbar intervertebral joint, intact and injured. J Biomech Eng. August 1982;104(3):193-201.
2008	Helgason B, Taddei F, Pálsson H, Schileo E, Cristofolini L, Viceconti M, Brynjolfsson S. A modified method for assigning material properties to FE models of bones. Med Eng Phys. May 2008;30(4):444-453.
1996	Ebara S, Iatridis JC, Setton LA, Foster RJ, Mow VC, Weidenbaum M. Tensile properties of nondegenerate human lumbar anulus fibrosus. Spine. March 15, 1996;21(4):452-461.
1997	Fujita Y, Duncan NA, Lotz JC. Radial tensile properties of the lumbar annulus fibrosus are site and degeneration dependent. J Orthop Res. November 1997;15(6):814-819.
1976	Noyes FR, Grood ES. The strength of the anterior cruciate ligament in humans and Rhesus monkeys. J Bone Joint Surg. 1976;58A(8):1074-1082.
1990	Marchand F, Ahmed AM. Investigation of the laminate structure of lumbar disc anulus fibrosus. Spine. May 1990;15(5):402-410.
2003	Morgan EF, Bayraktar HH, Keaveny TM. Trabecular bone modulus–density relationships depend on anatomic site. J Biomech. July 2003;36(7):897-904.
1995	Rho JY, Hobatho MC, Ashman RB. Relations of mechanical properties to density and CT numbers in human bone. Med Eng Phys. July 1995;17(5):347-355.
1990	White AA III, Panjabi MM. Clinical Biomechanics of the Spine. 2nd ed. Philadelphia, PA: J.B. Lippincott Company; 1990.
1984	Dunlop RB, Adams MA, Hutton WC. Disc space narrowing and the lumbar facet joints. J Bone Joint Surg. 1984;66B(5):706-710.
1992	Neumann P, Keller TS, Ekström L, Perry L, Hansson TH, Spengler DM. Mechanical properties of the human lumbar anterior longitudinal ligament. J Biomech. 1992;25(10):1185-1194.

Cited By (1)

Year	Entry
2023	Minster P-H, Lafon Y, Beillas P. Implications of range of motion requirements for the laxity of ligaments in a lumbar finite element model. J Biomech. February 2023;148:111460.