International Journal of Oral & Maxillofacial Surgery
Volume 39, Issue 7 , Pages 666-672, July 2010

Orbital form analysis: problems with design and positioning of precontoured orbital implants:

A serial study using post-processed clinical CT data in unaffected orbits

  • L. Kamer

      Affiliations

    • AO Research Institute Davos, Davos Platz, Switzerland
    • Corresponding Author InformationAddress: Lukas Kamer, AO Research Institute Davos, Clavadelerstrasse 8, 7270 Davos Platz, Switzerland. Tel.: +41 81 414 24 61; fax: +41 81 414 22 85.
    • ,
  • H. Noser

      Affiliations

    • AO Research Institute Davos, Davos Platz, Switzerland
    • ,
  • A. Schramm

      Affiliations

    • Department of Oral and Maxillofacial Surgery, Plastic and Esthetic Facial Surgery, Military Hospital Ulm, Academic Hospital, University of Ulm, Germany
    • ,
  • B. Hammer

      Affiliations

    • cfc hirslanden Cranio Facial Center, Hirslanden Medical Center, Aarau, Switzerland

Accepted 16 March 2010. published online 26 April 2010.

Article Outline

Abstract 

Inter-individual size and shape (form) variation for the orbital floor and medial wall was assessed and compared with its posterior partition. Reconstruction of the posterior partition is known to be a surgical challenge in complex orbital defect repair when using standard manual implant contouring and positioning techniques. The size variation of both regions was assessed, alone and combined, in statistical form analysis using three-dimensional computer models of left and mirrored right orbits, obtained from 70 clinical computed tomography (CT) scans of adult European Caucasians with unaffected orbits. Major shape and size variability for both regions was observed, but to a larger extent for the entire orbital floor and medial wall, with males having significantly larger regions but with no differing shape patterns. Statistical modeling was used to identify characteristic shape patterns in given orbits. The size, shape and positioning of precontoured implants are decisive criteria for the adequate repair of complex orbital defects. The results indicate that optimal form conditions for prefabricated implants exist in a restricted area corresponding to the transition of the posterior orbital floor and medial wall.

Key words: orbital fracture, precontoured implant, computed tomography, three-dimensional bone models, statistical form analysis

 

The mainstay of a severe injured orbit repair is restitution of the preinjury bone anatomy in order to re-establish orbital form and function 6. Dislocation of orbital wall fragments leads to orbital widening, resulting in an enlarged orbital volume, it also induces displacement and dysfunction of orbital soft tissue structures 13, 3. Traditional surgical techniques for restoring orbital wall defects involve freehand contouring and positioning of grafts which are technically difficult and prone to error.

In the present study, the authors evaluate the inter-individual variability of the orbital floor/medial wall region (FMW) and its posterior partition (pFMW), in order to establish a scientific anatomical basis and to define optimal conditions for preshaped orbital implants for complex orbital fracture repair (Fig. 1). This includes the use of clinical computed tomography (CT) data from unaffected adult orbits, the creation of three-dimensional (3D) computer models, size measurements and 3D statistical modeling and analysis techniques, the latter comprising techniques of anatomical homologous point determination and evaluation. Statistical modeling identified characteristic shape patterns in given orbits.

  • View full-size image.
  • Fig. 1. 

    3D CT computer model of a left orbit comprising the two evaluated regions (FMW, blue; pFMW, red). Homology in different datasets was obtained (i) by manual determination of anatomical landmarks at the corners of the FMW (yellow), (ii) by calculating interpolated equidistant anatomical-mathematical boundary pathway landmarks (blue) and (iii) by computation of identical located and numbered mesh points (i.e. mathematical landmarks, (black)).

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Material and methods 

Consecutive CT scans from 70 adult European Caucasians (35 females and 35 males), aged 20–88 years (mean±SD 53±19.4 years; 53.4±17.8 for females, and 52.7±21 for males) were retrospectively assessed using routine CT head protocols from patients undergoing diagnostic procedures for pathologies near, but not directly involving, the orbits (e.g. for paranasal sinus problems). Exclusion criteria included the presence of uni- or bilateral radiological signs of orbital pathology.

CT data were obtained on a standard multi-slice CT scanner (SOMATOM Sensation 10, Siemens AG, Erlangen, Germany) and comprised continuous 0.4–0.8mm high resolution (512×512 matrix) axial slices in a bone window setting. After acquiring the patients’ meta-data (i.e. age, gender and ethnicity) all image data were stored in DICOM-format (Digital Imaging and Communications in Medicine), anonymized and transferred via compact disc to an off-line desktop computer and processed with Amira, a commercial software package for image visualization and data analysis (Visage Imaging GmbH, Berlin, Germany).

In Amira, semi-automated segmentation tools were used, associating DICOM threshold values of grey scales to bone. Very thin bony orbital structures led to the creation of partial volume averaging and required additional manual segmentation. 3D triangulated surfaces of the bony orbit were created and all image data of the right orbits were mirrored, resulting in 140 left sided orbits (i.e. 70 mirrored right and 70 left orbits).

The surface area of FMW and pFMW was determined using the Amira's SurfaceAreaGet module. Related descriptive statistics, tests for normality, the independent sample t-test for testing gender related variability and the paired t-test for laterality evaluation were carried out using SPSS 14.0 (Statistic Package for the Social Sciences, SPSS Inc., Chicago, USA). A p-value <0.05 was considered significant.

In order to perform statistical form modeling in FMW and pFMW, homologous boundary and surface points had to be determined. For this, a statistical model analysis procedure was developed based on manual anatomical landmark tracing, computing anatomical–mathematical boundary landmarks and mathematically defined surface landmarks (Fig. 1). Evaluation was carried out with special regard for anatomical regions lacking anatomical criteria as observed in the pFMW 11. In standard shape analysis, scaled region evaluation is performed, thus eliminating size as a factor, but in the present study, unscaled statistical modeling was carried out, allowing analysis of both the shape and size; this is termed statistical form analysis. Homology computing was finalized by creating corresponding mesh surfaces with an identical triangulation structure (1385 mesh points for FMW and 541 for pFMW).

The datasets with homologous landmarks were aligned using an unscaled generalized Procrustes Fit1 and analyzed using Principal Component Analysis (PCA), a state of the art method for statistical modeling and analysis 2, 18. PCA was performed with MATLAB (The MatWorks GmbH, Bern, Switzerland) and results were expressed as PCA scatterplots, charts and simplified 3D visualizations. The size variability in the PCAs was characterized using the Frobenius Norm and MATLAB's standard correlation test.

The scatterplots were also used to identify characteristic shape patterns of the FMW region, visualized in given orbits using Amira's curvature module.

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Results 

FMW and pFMW surface area measurements showed normal distribution (Kolmogorov–Smirnov and Lilliefors significance level p≥0.2). The area of the mean FMW in women and men was roughly four times larger than the corresponding mean pFMW (Table 1). For both regions a significant gender dependent surface size variation was observed with males having significantly larger values (independent samples t-test (the null hypothesis of a t-test for equality of means could clearly be rejected with a p-value=0.000 for FMW and for pFMW)). In the laterality evaluation of corresponding left and right orbits, the null hypothesis of the paired t-test could not be rejected for both regions, indicating no significant side difference (paired t-test p=0.726 for FMW and 0.983 for pFMW). No significant correlations between age and both areas could be observed (Pearson correlation≤|0.071|).

Table 1. Data for FMW and pFMW surface area measurements (cm2).
FMWpFMW
WomenMenWomenMen
Min10.722112.05412.89903.4189
Max14.329415.23284.88265.0048
Mean12.53097913.5917203.8541544.187711
SD0.95896980.81735610.38304140.3342664

A statistical form model for both FMW and pFMW regions was evaluated. The results were compared with the corresponding mean shapes and visualized (Fig. 2) with colour maps showing the degree of form variation and by vectors indicating the amount and direction of maximum values analyzed for all corresponding homologous mesh points.

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  • Fig. 2. 

    Lateral (1st row) and frontal view (2nd row) of average models of 140 unscaled FMW (left) and pFMW (right), showing maximum deviation (red and yellow) at the boundaries of the orbital floor/medial wall region for FMW and at the anterior lateral orbital floor for pFMW (mm). pFMW is visualized in a larger scale than FMW.

High deviation of the FMW region (≥3mm) was observed at the periphery and centrally at the transition from the anterior to the posterior orbital floor. Good form match (≤2mm deviation) was obtained at the posterior medial orbital wall and the anterior orbital floor. The pFMW showed increased form variation at the anterior and posterior margins (i.e. anteriorly towards the lacrimal fossa and posteriorly below the optic foramen). In contrast to the orbital FMW region, maximum deviations (≥5mm) were limited to the area corresponding to the infraorbital sulcus. 3D rendered standard deviations are shown in Fig. 3.

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  • Fig. 3. 

    Lateral view of average model of the FMW (left) and its posterior partition (pFMW) (right) with standard deviations of homologous points shown as colour maps (mm); pFMW is visualized in a larger scale than FMW.

Identification and categorization of patterns of form similarities were performed with the statistical models created by applying PCA. As expected, most significant variability was obtained in the first principal component (1st PC) (Fig. 4). It showed a significant correlation between size and shape values at a p-level of ≤0.05 in both regions, indicating that most relevant form variation was due to size and not to shape variation. Other significant correlations between these parameters were observed in the 3rd PC and 4th PC for FMW and the 2nd PC and 3rd PC for pFMW. The remaining PCs showed variation patterns due to shape variation and were not correlated to size. Gender specific patterns of shape variation could not be observed in the PCA. The cumulative percentage of contribution of each PC is shown in Fig. 5. The first five PCs cover about 60% FMW and more than 70% pFMW overall form variability. In Fig. 6 the fit of each individual FMW and pFMW was quantified and visualized by computing and plotting normalized average distances from the corresponding average values of FMW and pFMW. The overall average distance between mean form and its samples was 1.28mm (±0.3 SD) for FMW and 0.86 (±0.26 SD) for pFMW.

  • View full-size image.
  • Fig. 4. 

    FMW (left) and pFMW (right) scatterplots of form coordinates for females (blue dots) and males (red dots). The 1st PC (1st row) shows high correlation between size values (Frobenius norm) and form coordinates in FMW, indicating that most relevant form variation was due to size variation. 2nd row: in most other PCs shape variation was the predominant variation factor, as shown for 2nd PC.

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  • Fig. 5. 

    Cumulative percentage of total form variance of the first 15 PCs showing the contribution of each PC to the overall form variation. The 1st PC comprised most significant variation for both regions (FMW (left) and pFMW (right)).

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  • Fig. 6. 

    Mean distance deviations (mm) of all 140 FMW calculated from the corresponding FMW mean form (left); corresponding scatterplot with better fit values for pFMW (right); females (blue dots), males (red dots).

PCA analysis revealed characteristic floor and medial wall shape patterns and given orbits could be selected where such patterns existed (Fig. 7). In some orbits, floor and medial wall are separated by a sharp bend while in others the transition is virtually flat. In most orbits an intermediate shaped transition became evident. The second shape pattern was observed in the orbital floor where significant differences in shape (i.e. large lazy-s-shape variability) and antero-posterior inclination could be observed.

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  • Fig. 7. 

    Curvature graded CT reconstruction showing characteristic orbital/floor medial wall patterns in given orbits. 1st row: frontal views with different inter-individual shape patterns in the transition area between the orbital floor and medial wall: with a sharp bend (left), intermediate (middle) and virtually flat transition area (right). 2nd row: lateral views of sagittal cuts reveals typical orbital floor form patterns, considered to be a function orbital floor length, different shapes (i.e. different lazy-s-shapes) and medial wall related degree of floor inclination.

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Discussion 

Within the orbit, the posterior orbital floor and medial wall are critical areas for fracture-induced globe displacement, where dislocation of relatively small bone fragments leads to significant globe retrusion, and where standard fracture repair remains a surgical challenge even for experienced surgeons. In complex orbital defects this region is typically involved and it is important to restore its anatomy accurately with primary surgery to achieve preinjury orbital form and function.

The goal of this study was to perform CT based orbital size and form analysis of the FMW and pFMW to assess inter-individual variations. This information can then be used to establish a scientific anatomical basis and to define optimal conditions for preshaped orbital implants for complex orbital fracture repair.

Homologous image data were created from 3D computer models to carry out 3D statistical FMW and pFMW modeling and analysis. Different concepts deal with the difficulty and reliability of creating landmark correspondence in different datasets (i.e. the definition of homologous points) and performing 3D statistical shape analysis 1, 4, 5, 9, 17, 18. This study is based on the definition of the smallest anatomical definable area (SADA)11 and includes homologous anatomical, anatomical–mathematical boundary and mathematical mesh surface landmark determination as well as TPS transformation1 for creating boundary and surface homology in FMW and pFMW. Of particular interest was anatomical homologous boundary and point determination in pFMW, which is characterized by its fuzzy anatomical nature. PCA is considered to be the state of the art method in statistical model analysis and is generally performed without considering size variation 8, 15, 18, but in the present study this limits its validity for overall anatomical variability assessment. Therefore, the authors adapted the method by combining 3D statistical shape and size analysis (statistical form analysis) using unscaled FMW and pFMW regions. Size comparison between FMW and pFMW regions was made using standard surface area measurement, but the accuracy of this procedure may be compromised by certain image computing procedures (e.g. by surface smoothing procedures; depending on the number of meshes per area);12 this is a particular problem if more anatomically uneven and spiky areas are evaluated. As demonstrated in PCA analysis, the Frobenius Norm would be more appropriate statistically as a size measure, but it is a less comprehensible approach and the values generated are less understandable.

The results showed that most significant variation was due to inter-individual size variability, with males having significant larger FMW and pFMW than females. There were no gender related shape patterns. Therefore, in contrast to implant size, the authors consider implant shape to remain irrespective of the patient's gender. Compared with pFMW, the form variation of FMW is increased significantly and a larger number of implant forms would be required to fit the anatomy of a given clinical case. Even when precontoured, implants of too large a size would require additional manual contouring and would be more difficult to handle intraoperatively. As a further result of statistical modeling a FMW and pFMW mean form was created.

The authors report results of inter-individual form variability using an in vitro, virtual computer model environment of unaffected orbits, where the presumptive implant position was computed exactly. Even though the goal of an optimal precontoured implant could be achieved using the 3D statistical anatomical data presented, such as the mean form and the most relevant form variations, and considering surgical and technical implant design constraints, further reconstruction errors may occur in the clinical setting due to manual implant malpositioning. Complex orbital defects lack reliable anatomical landmarks that serve as guideline parameters for correct anatomical reconstruction. Therefore such fracture patterns are prone to implant malpositioning and the authors stress the importance of additional intraoperative position control in cases where the implant position cannot be assessed solely by visual judgement. This may be achieved using intraoperative imaging techniques7, 14 or intraoperative navigation control 16.

The authors discovered that shape and size play an important role in anatomical implant design. A follow up study is planned to evaluate the fit of an existing precontoured implant10 to assess orbital form and volume change induced by the discrepancies in orbits.

Exactly shaped, sized and positioned orbital implants for complex fracture pattern reconstruction for the posterior orbital floor and medial wall partition at primary surgery significantly contribute to preinjury orbital form and function restitution. Adequately preformed and optimally placed implants will aid improved repair of complex orbital defects resulting in a better surgical outcome.

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Conflict of interest 

None declared.

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Acknowledgements 

The authors are grateful to Prof. Dr. Paul Manson, MD, John Hopkins University Hospital, Dept of Surgery, Plastic Surgery, Baltimore, USA and PD Dr. Eberhard Kirsch, MD, cfc hirslanden Cranio Facial Center, Hirslanden Medical Center, Aarau, Switzerland for their valuable support for the project. The concept of this project was outlined in August 2005 in a dedicated research project, supported by the AO Research Fund of the AO Foundation, Davos, Switzerland (AO Research Grant 05-H37).

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PII: S0901-5027(10)00098-6

doi:10.1016/j.ijom.2010.03.005

International Journal of Oral & Maxillofacial Surgery
Volume 39, Issue 7 , Pages 666-672, July 2010

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