Planning of skull reconstruction based on a statistical shape model combined with geometric morphometrics

Fuessinger, Marc Anton; Schwarz, Steffen; Cornelius, Carl‐Peter; Metzger, Marc Christian; Ellis, Edward; Probst, Florian; Semper-Hogg, Wiebke; Gass, Mathieu; Schlager, Stefan

doi:10.1007/s11548-017-1674-6

Cited by 59 publications

(40 citation statements)

References 39 publications

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“…For example, it is extensively used for organ segmentation, [36][37][38] to extract morphological bio-markers of (diseased) organs, [39][40][41] or for numerous orthopedic applications. [42][43][44][45][46][47] Although few, several studies-mainly in the field of orthopedics-attempted to relate SSM parameterized anatomical shape variation with Finite Element Analysis (FEA). These studies used SSM and FEA to: investigate the relationship between patellofemoral shape and function 48 ; force-displacement behavior of proximal femurs 49 ; to investigate cervical spine loading, 50 or for real-time prediction of joint-mechanics.…”

Section: Discussionmentioning

confidence: 99%

“…The large number of publications in various bio‐medical fields proves that statistical shape modeling is a versatile and widely accepted technique to capture anatomic variation in the population. For example, it is extensively used for organ segmentation, 36‐38 to extract morphological bio‐markers of (diseased) organs, 39‐41 or for numerous orthopedic applications 42‐47 . Although few, several studies—mainly in the field of orthopedics—attempted to relate SSM parameterized anatomical shape variation with Finite Element Analysis (FEA).…”

Section: Discussionmentioning

confidence: 99%

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Combining statistical shape modeling, CFD, and meta‐modeling to approximate the patient‐specific pressure‐drop across the aortic valve in real‐time

Hoeijmakers

Waechter-Stehle

Weese

et al. 2020

Numer Methods Biomed Eng

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Background: Advances in medical imaging, segmentation techniques, and high performance computing have stimulated the use of complex, patient-specific, three-dimensional Computational Fluid Dynamics (CFD) simulations. Patient-specific, CFD-compatible geometries of the aortic valve are readily obtained. CFD can then be used to obtain the patient-specific pressure-flow relationship of the aortic valve. However, such CFD simulations are computationally expensive, and real-time alternatives are desired. Aim: The aim of this work is to evaluate the performance of a meta-model with respect to high-fidelity, three-dimensional CFD simulations of the aortic valve. Methods: Principal component analysis was used to build a statistical shape model (SSM) from a population of 74 iso-topological meshes of the aortic valve. Synthetic meshes were created with the SSM, and steady-state CFD simulations at flow-rates between 50 and 650 mL/s were performed to build a metamodel. The meta-model related the statistical shape variance, and flow-rate to the pressure-drop. Results: Even though the first three shape modes account for only 46% of shape variance, the features relevant for the pressure-drop seem to be captured. The three-mode shape-model approximates the pressure-drop with an average error of 8.8% to 10.6% for aortic valves with a geometric orifice area below 150 mm 2. The proposed methodology was least accurate for aortic valve areas above 150 mm 2. Further reduction to a meta-model introduces an additional 3% error.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Combining statistical shape modeling, CFD, and meta‐modeling to approximate the patient‐specific pressure‐drop across the aortic valve in real‐time

Hoeijmakers

Waechter-Stehle

Weese

et al. 2020

Numer Methods Biomed Eng

View full text Add to dashboard Cite

show abstract

“…Recently, there were several studies using different methods for this situation, including statistical methods, deep learning and so on. For example, Fuessinger MA et al 24 proposed a computer‐based approach to rebuild cranial vault model by employing a statistical shape model (SSM), which combined with the geometric morphometry. They created the SSM based on 131 CT scans of health human, to capture the shape variability of the cranial vault.…”

Section: Discussionmentioning

confidence: 99%

Computer‐aided porous implant design for cranio‐maxillofacial defect restoration

Wang

Shi

Sun

et al. 2020

Robotics Computer Surgery

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The porous structure of the implant contributes significantly to prosthetic osseointegration in cranio-maxillofacial defect repair surgeries. This study establishes a system called EasyImplant that can easily and efficiently design customized craniomaxillofacial implant with porous structure. Healthy side of the skull model is used to obtain the initial implant model on defective side by mirroring method. According to

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“…The precision of the SSMbased virtual reconstruction, for the midface and the neurocranium, has already been demonstrated. (5,13,14) Future research has to focus on the clinical feasibility of the shown technique. The SSM will be used by the surgeon to plan the fracture reduction preoperatively.…”

Section: Discussionmentioning

confidence: 99%

“…(12) As one opportunity, we show the advantages of a statistical shape model (SSM) in preoperative virtual planning for repairing arti cial unilateral midface and neurocranium defects. (13,14) Arti cial bilateral defects of the midface could also be reconstructed satisfactorily. 5The purpose of this study is to demonstrate the application of the SSM for measuring the quality of the postoperative result in the reconstruction of bilateral midface fractures.…”

Section: Introductionmentioning

confidence: 99%

The Statistical shape model as a quality assurance measure in the treatment of complex midface fractures: A Case control study

Fuessinger

Steffen

Gass

et al. 2020

Preprint

Self Cite

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BackgroundComplex bilateral midface fractures necessitate a surgically challenging procedure to preserve or restore the occlusion and the sensitive eye area. In this case control study, we aim to show the potential of a statistical shape model (SSM) for measuring the quality of the midface reconstruction, compared to the estimated preoperative situation.MethodsAn individualized SSM was postoperatively registered on 19 reconstructed complex bilateral midface fractures. Using this SSM, the distances from the simulated preoperative situation to the postoperative positions of the fracture segments were calculated. The fracture lines for Le Fort II, Le Fort III, and NOE fractures were chosen as reference points for the distance measurements.ResultsThe SSM could be registered on all 19 complex bilateral midface fractures. All analyzed fractures show a dorsal impaction (negative values) of the midface. Le Fort II fractures show deviation values of − 0.98 ± 4.6 mm, Le Fort III fractures show values of − 3.68 ± 3.6 mm, NOE type 2 fractures show values of − 0.25 ± 4.6 mm, and NOE type 1 fractures show values of − 0.25 ± 4.6 mm.ConclusionThe SSM can be used to measure the quality of the achieved reduction of complex bilateral midface fractures based on the estimated preoperative situation.Trial registrationDRKS00009719

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Planning of skull reconstruction based on a statistical shape model combined with geometric morphometrics

Abstract: The presented computer-based approach using SSM is a precise and simple tool in the field of computer-assisted surgery. It helps to reconstruct large-size defects of the skull considering the natural asymmetry of the cranium and is not limited to unilateral defects.

Cited by 59 publications

References 39 publications

Combining statistical shape modeling, CFD, and meta‐modeling to approximate the patient‐specific pressure‐drop across the aortic valve in real‐time

Combining statistical shape modeling, CFD, and meta‐modeling to approximate the patient‐specific pressure‐drop across the aortic valve in real‐time

Computer‐aided porous implant design for cranio‐maxillofacial defect restoration

The Statistical shape model as a quality assurance measure in the treatment of complex midface fractures: A Case control study

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