Custom implant design for large cranial defects

Marreiros, Filipe Miguel Maria; Heuzé, Yann; Verius, Michael; Unterhofer, Claudia; Freysinger, Wolfgang; Recheis, Wolfgang

doi:10.1007/s11548-016-1454-8

Cited by 30 publications

(15 citation statements)

References 29 publications

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“…Combining non-invasive 3D head shape scanning with nonparametric statistical shape modelling and PLS regression, it was found that craniotomy dimensions and positions of springs on average had significant effects on head shapes achieved at the time of spring removal. While previous studies have used SSM to predict the shape of missing anatomical bony parts [ 27 , 34 ] or choose best suited bone segments to plan patient-specific mandibular reconstructions [ 28 ], to the best of our knowledge, this is the first prospective study establishing direct population-based associations between craniofacial surgical choices and long-term head shape outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, computer-assisted analysis of 3D medical image data has been employed to improve the head shape description [ 9 – 12 ] and to aid in the diagnosis of craniosynostosis [ 13 – 19 ] as well as in the evaluation of surgical outcomes [ 20 – 23 ]. With the aim of facilitating cranio-maxillofacial surgery, statistical shape modelling (SSM) has been used in virtual surgery planning [ 24 – 28 ] as well as in the design of pre-fabricated templates [ 29 – 31 ], surgical guides [ 32 , 33 ] and cranial implants [ 34 , 35 ] to achieve desired patient-specific post-operative outcomes on-table. However, some craniofacial procedures rely on gradual post-operative skull remodelling instead of acute changes and thus seek to obtain desired shapes not immediately on the operative table, but months later.…”

Section: Introductionmentioning

confidence: 99%

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Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty

et al. 2017

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PurposeSpring-assisted cranioplasty is performed to correct the long and narrow head shape of children with sagittal synostosis. Such corrective surgery involves osteotomies and the placement of spring-like distractors, which gradually expand to widen the skull until removal about 4 months later. Due to its dynamic nature, associations between surgical parameters and post-operative 3D head shape features are difficult to comprehend. The current study aimed at applying population-based statistical shape modelling to gain insight into how the choice of surgical parameters such as craniotomy size and spring positioning affects post-surgical head shape.MethodsTwenty consecutive patients with sagittal synostosis who underwent spring-assisted cranioplasty at Great Ormond Street Hospital for Children (London, UK) were prospectively recruited. Using a nonparametric statistical modelling technique based on mathematical currents, a 3D head shape template was computed from surface head scans of sagittal patients after spring removal. Partial least squares (PLS) regression was employed to quantify and visualise trends of localised head shape changes associated with the surgical parameters recorded during spring insertion: anterior–posterior and lateral craniotomy dimensions, anterior spring position and distance between anterior and posterior springs.ResultsBivariate correlations between surgical parameters and corresponding PLS shape vectors demonstrated that anterior–posterior (Pearson’s ) and lateral craniotomy dimensions (Spearman’s ), as well as the position of the anterior spring () and the distance between both springs () on average had significant effects on head shapes at the time of spring removal. Such effects were visualised on 3D models.ConclusionsPopulation-based analysis of 3D post-operative medical images via computational statistical modelling tools allowed for detection of novel associations between surgical parameters and head shape features achieved following spring-assisted cranioplasty. The techniques described here could be extended to other cranio-maxillofacial procedures in order to assess post-operative outcomes and ultimately facilitate surgical decision making.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty

et al. 2017

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“…The pediatric craniofacial population provides distinct challenges in the design of custom made implants mainly due to congenital deformities with varying degrees of bilateral dysmorphism [21,22], thus precluding the ability to plan reconstructions based on the healthy hemi-face [23]. Moreover, the defect can be caused by a trauma [24] or a tumor's resection [16] that requires a sequence of surgical procedures. Finally, surgical correction must allow for, and anticipate, further growth and development, often with the knowledge that dysmorphic relapse may occur [25].…”

Section: Background and Aims Of The Workmentioning

confidence: 99%

Surgery of complex craniofacial defects: A single-step AM-based methodology

Volpe

Furferi

Governi

et al. 2018

Computer Methods and Programs in Biomedicine

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Background and objectiveThe purpose of the present paper is to pave the road to the systematic optimization of complex craniofacial surgical intervention and to validate a design methodology for the virtual surgery and the fabrication of cranium vault custom plates. Recent advances in the field of medical imaging, image processing and additive manufacturing (AM) have led to new insights in several medical applications. The engineered combination of medical actions and 3D processing steps, foster the optimization of the intervention in terms of operative time and number of sessions needed. Complex craniofacial surgical intervention, such as for instance severe hypertelorism accompanied by skull holes, traditionally requires a first surgery to correctly "resize" the patient cranium and a second surgical session to implant a customized 3D printed prosthesis. Between the two surgical interventions, medical imaging needs to be carried out to aid the design the skull plate. Instead, this paper proposes a CAD/AM-based one-in-all design methodology allowing the surgeons to perform, in a single surgical intervention, both skull correction and implantation. MethodsA strategy envisaging a virtual/mock surgery on a CAD/AM model of the patient cranium so as to plan the surgery and to design the final shape of the cranium plaque is proposed. The procedure relies on patient imaging, 3D geometry reconstruction of the defective skull, virtual planning and mock surgery to determine the hypothetical anatomic 3D model and, finally, to skull plate design and 3D printing. ResultsThe methodology has been tested on a complex case study. Results demonstrate the feasibility of the proposed approach and a consistent reduction of time and overall cost of the surgery, not to mention the huge benefits on the patient that is subjected to a single surgical operation. ConclusionsDespite a number of AM-based methodologies have been proposed for designing cranial implants or to correct orbital hypertelorism, to the best of the authors' knowledge, the present work is the first to simultaneously treat osteotomy and titanium cranium plaque.

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“…Moreover, since every cranium is characterized by a certain degree of asymmetry, mirror imaging can lead to large deviations of affected regions during alignment of the affected and unaffected side (Quinto‐Sánchez et al, 2015 ). Alternatively, deformation‐based geometric morphometrics (GM) show a high potential for the generation of patient‐specific implants, since available morphological information of the reconstructed cranium is incorporated into the final implant (Marreiros et al, 2016 ; Mitteroecker & Gunz, 2009 ; Senck et al, 2013 ). Using thin‐plate splines (TPS), a mapping function warps the landmark configuration (template) from a complete reference specimen onto a target specimen showing cranial defects (Bookstein, 1989 ).…”

Section: Introductionmentioning

confidence: 99%

Thickness accuracy of virtually designed patient‐specific implants for large neurocranial defects

et al. 2021

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The combination of computer‐aided design (CAD) techniques based on computed tomography (CT) data to generate patient‐specific implants is in use for decades. However, persisting disadvantages are complicated design procedures and rigid reconstruction protocols, for example, for tailored implants mimicking the patient‐specific thickness distribution of missing cranial bone. In this study we used two different approaches, CAD‐ versus thin‐plate spline (TPS)‐based implants, to reconstruct extensive unilateral and bilateral cranial defects in three clinical cases. We used CT data of three complete human crania that were virtually damaged according to the missing regions in the clinical cases. In total, we carried out 132 virtual reconstructions and quantified accuracy from the original to the generated implant and deviations in the resulting implant thickness as root‐mean‐square error (RMSE). Reconstructions using TPS showed an RMSE of 0.08–0.18 mm in relation to geometric accuracy. CAD‐based implants showed an RMSE of 0.50–1.25 mm. RMSE in relation to implant thickness was between 0.63 and 0.70 mm (TPS) while values for CAD‐based implants were significantly higher (0.63–1.67 mm). While both approaches provide implants showing a high accuracy, the TPS‐based approach additionally provides implants that accurately reproduce the patient‐specific thickness distribution of the affected cranial region.

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Custom implant design for large cranial defects

Abstract: In conclusion, the results show that our CAD tool can generate patient-specific implants with high accuracy.

Cited by 30 publications

References 29 publications

Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty

Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty

Surgery of complex craniofacial defects: A single-step AM-based methodology

Thickness accuracy of virtually designed patient‐specific implants for large neurocranial defects

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