Image acquisition and processing

Patients with avascular necrosis of the femoral head were recruited as part of a medical device clinical trial initiated by DePuy Synthes Joint Reconstruction (Leeds, UK). The trial was run in two hospitals in Bangkok (Chulalongkorn Memorial Hospital, Rama 4 Road, Bangkok and Ramathibodi Hospital, Isarapap Min Buri Road, Bangkok), one hospital in Hong Kong (Queen Mary Hospital, Pok Fu Lam Road, Hong Kong) and one in Melbourne (St. Vincent’s Private Hospital, Victoria Parade, Melbourne).

The clinical trial protocol was approved by DePuy Synthes and by the independent hospital ethics committees at each site. The protocol and patient consent forms both included the intention to use the information collected on each patient during the trial for further scientific research. Approval to use patient-confidential data at the University of Leeds was obtained from the University of Leeds, Faculty of Engineering Research Ethics Committee (reference MEEC 10-011).

Each patient recruited into the trial received concurrent pre-operative CT and MR scans as part of their normal standard of care. The scans and patient demographic data were uploaded onto a secure server administered by Intelemage (Cincinnati, OH). The administrator’s responsibilities included a quality review to evaluate data integrity and conformance to image acquisition protocols. They also provided confirmation of anonymity before the images and demographic data were made available to DePuy Synthes and subsequently this study.

All CT and MR scans were collected following standardised protocols (Appendix D: Clinical data). MR scans were obtained using multiple protocols but only T1 weighted scans with turbo spin echo³ were used in this research.

Eleven patients were evaluated for inclusion in this study. Two patients were excluded because the lesion did not extend into the slices defined in Table 50. A third patient was excluded because multiple lesions were present in the slices making the analysis inconsistent.

5.2.2 Method

Three-dimensional geometry models were generated for each patient using spatially aligned CT and MR scans from each patient. Bone geometry was segmented from the CT scan and the

3 Turbo spin echo is used to shorten scan times compared to a conventional MR scan protocol and was the standard of care at both hospitals in the trial.

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lesion boundary was segmented from the MR scan. The native spacial resolutions of the CT and MR scans were 0.5mm x 0.5mm x 0.5mm and 1mm x 2mm x 2mm respectively.

Image acquisition and registration

Three dimensional geometric models of the proximal femur of each patient included in the study were generated in ScanIP (Simpleware Ltd., Exeter, UK). Each patient-specific model was generated from a co-registered pair of CT and MR scans.

Both scans were taken with the patient lying in a supine position. The consistent orientation of the long axis of the femurs relative to the scan co-ordinate systems indicated there was little variation in flexion angle between scan modes, thus flexion in both the CT and MR was assumed to be approximately neutral. The degree of rotation and abduction or adduction varied between modes so co-registration of the images using translation, internal / external rotation and abduction / adduction rotation was necessary. All femurs were oriented in a neutral stance position with approximately 20° of femoral neck anteversion (external rotation) to obtain consistency in orientation across the patient cohort. The diaphysis was aligned to the global Y-axis (vertically upwards) and the medial direction oriented to the global X-Y-axis (Figure 91). For right hips the anterior direction was aligned to the global Z-axis, for left hips the posterior direction was aligned to the global Z-axis.

Figure 91. Schematic diagram of a neutrally oriented right femur with a lesion in the anterior-medial quadrant. The diaphysis was aligned to the global Y axis; the medial direction was aligned to the X axis. Approximately 20° of femoral anteversion (external rotation) was applied.

A method of co-registering the CT and MR scans was developed to allow models that represented both the bony geometry and lesion boundary to be developed. CT segmentation was based on a protocol described previously (Buie et al., 2007); MR segmentation was based on the manual process described in a second study (Zoroofi et al., 2001). In addition to generating masks that represented the external geometry of the femur and the lesion, a mask that was the inverse of femur geometry was generated. This equated to the filler used in the conforming contact methodology described in Section 4.3. A summary of the process is shown

Y Y

X Z

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in Figure 92. A detailed explanation of each sub-step is shown in Figures 93-97.

Figure 92. Summary of process used to develop head, lesion and filler masks for patient 01_001. Note that the process is shown in two dimensions for simplicity but the steps were carried out in 3D.

Page 198 of 273 CT data segmentation

CT scans were used to identify the geometry of the proximal femur. They were imported into ScanIP as a stack of images in DICOM format and cropped to generate a volume of interest⁴ (VoI) around the proximal femur, terminating distally below the lesser trochanter and oriented a consistent position (neutral flexion, approximately 20° anteversion) before being down-sampled to a voxel resolution of 1mm³. This resolution was chosen because the re-meshing algorithm described in the following section generated a finer mesh than the native mesh exported from ScanIP and exporting the meshed geometry with a target element edge length of 1mm resulted in a final element edge length of approximately 0.5mm.

An automated method of segmenting cortical and trabecular compartments using two thresholds and a closing function to generate a mask has been described previously (Buie et al., 2007).

Developing an automated method was not justified in this study as there were only a small number of samples. A simplified manual approach was possible in this study because a homogenous material was assumed so there was no requirement to differentiate cortical bone from cancellous. The workflow is summarised in Figure 93.

Subchondral fractures were not represented in the geometry models and therefore all eight geometry models simulated intact femoral heads. The presence of a fracture did not alter the external geometry in the two cases where a fracture was present.

Figure 93. Schematic representation of the workflow used to segment the femur geometry from the CT scan (in this case of patient 01_001) using ScanIP. The process was based on that presented in an earlier study (Buie et al., 2007) and had six key steps: Importing the image and cropping it to establish a volume of interest; thresholding to identify the bone region; manually deselecting voxels (un-painting) associated with the acetabulum; using a closing function to solidify the construct; manually painting any gaps in the external surface that remained after the close function was used and smoothing the final surface.

4 The volume of interest is the three dimensional space that contains the borders of an object under consideration. In this study it was a rectangular volume that contained the proximal femur.

Import image Threshold Remove acetabulum (Unpaint) Close (2x2x2)

Paint and flood fill Gaussian recursive smoothing

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The segmented femoral head mask was copied and inverted to generate a negative of the femoral head geometry. This negative mask was used to create the lower half of the filler component in the final FE assemblies. Once the CT image had been completely processed the entire VoI was represented by the combination of these two masks (Figure 94).

Figure 94. Schematic representation of the completed femur and filler masks in the X-Y and Y-Z orientations. The filler occupied the entire volume of interest.

Registration of the MR image to the CT mask

MR images were used to generate lesion geometry because the inner border between healthy and necrotic bone can be indistinct in CT scans. To generate a model that contained femur and lesion geometry, the MR image had to be spatially aligned to the masks generated from the CT image.

The transition from dense subchondral bone to cartilage is not well defined in a T1 weighted MR image as both tissues have a low fat content. This made the femoral head appear smaller on MR images compared to CT. In the first stage of registration, the MR images were resampled to the same spacial resolution (1mm x 1mm x 1mm) before being manually aligned by translating the MR stack in the X-, Y- and Z-directions. The head centre was maintained as the origin for subsequent rotation adjustments. Landmarks for rotational alignment were the apices of the greater and lesser trochanters and the cortex in the diaphysis. Alignment about the three axes was obtained incrementally as gross changes to one orientation altered the apparent position of the landmarks in the other orientations. Final orientation was verified using both the filler (Figure 95) and femur masks.

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Figure 95. Alignment of the MR scan to the CT derived mask for patient 01_001. Left: the high intensity region of the MR image representing the proximal femur is misaligned relative to the (purple) filler mask; Right: final alignment of the MR image relative to the filler mask. This was obtained by rotating and translating the MR image relative to the filler mask.

The MR image stack was oriented relative to the filler mask using the rotation and translation functions available in ScanIP. Using the filler mask compensated for the lack of information on cortical geometry in the MR scan but required that some assumptions be made regarding the position of the MR image relative to the mask. These assumptions were:

1. The thickness of the diaphyseal cortex was approximately equal in the sagittal and coronal views at each transverse level⁵.

2. The thickness of the cartilage and subchondral bone on the femoral head was symmetrical in the transverse view and the head centres shown in both modalities aligned

3. The thickness of the cortices on the greater and lesser trochanters was uniform in all views.

Following these rules enabled each anatomic landmark visible in the MR images to be aligned to the boundary of the equivalent feature in the filler mask.

MR data segmentation

The necrotic lesion was identified by the presence of low-intensity (black) bands on T1-weighted MR images (Sakamoto et al., 1997; Seyler et al., 2008; Takao et al., 2010). An example scan showing the low intensity banding is shown in Table 48. These bands can be an indication of a fibrovascular reactive interface, osteolysis, cysts, reparative tissue or subchondral fracture (Gardeniers, 1993; Kim et al., 2000) and correlate to areas that lack hydrogen-rich marrow fat (Fordyce and Solomon, 1993).

5This assumption was verified by checking the alignment of the medullary cavity on the CT scan to the high intensity region representing bone marrow in the MR scan.