Purpose: There is a clinical need for novel effective local therapies to treat spinal metastases at significant risk for fracture. Photodynamic therapy (PDT) is a promising cancer treatment that employs wavelength specific light combined with a photosensitizing agent to induce localized tumour destruction by photochemical generation of singlet oxygen. Using minimally invasive techniques developed for vertebroplasty to deliver light within the vertebral body, PDT is proposed as a potential new treatment for spinal metastases; however, the effects of PDT on bone are largely unknown. This study aims to determine if PDT affects the structural integrity of normal vertebral bone.

Methods: Sixteen Wistar rats were randomly assigned to control, 1-week treatment or 6-week treatment groups. Rats treated with PDT received an intracardiac injection of 2mg/kg BPD-MA activated at 15 minutes post-injection through administration of a non-thermal 690nm diode laser positioned adjacent to the L3 vertebral body via fluoroscopic guidance (150J at 150mW). Rats were sacrificed at 1-week or 6-weeks following a single treatment. |In vitro & #956;CT scans were taken of L2-L4 and 3D stereological quantities measured using a semiautomated volume shrinkage thresholding technique within the trabecular bone centrum. L2, L3 and L4 vertebral bodies were individually tested biomechanically to failure in axial compression. Yield stress and stiffness were calculated from generated load displacement curves.

Results: Bone surface area and bone volume significantly increased with treatment, through trabecular thickening, at both 1-week and 6-weeks vs. control group. The treated group demonstrated an increase in yield stress at 6-weeks vs. control (27%, p=0.023). An increase in stiffness (45%, p=0.010) was found in the 1-week treatment group vs. control, but was not maintained in the 6-week group.

Conclusions: PDT is a promising new treatment for spinal metastases that appears to strengthen vertebral bone. Further research must determine the mechanism of this action and verify if similar effects will occur in metastatically-involved vertebrae. If PDT proves to be effective in both destroying tumour cells and in strengthening remaining bone, it may provide a very attractive minimally invasive treatment option for patients with spinal metastases.

Funding : Other Education Grant

Funding Parties : Canadian Breast Cancer Foundation, Ontario Chapter

Purpose: Effectively quantifying metastatic tumour involvement in the spine requires accurate vertebral segmentation. Automated techniques such as thresholding or region growing have difficulty defining boundaries between tumour tissue and surrounding soft tissue if lytic disease breaches the vertebral cortical shell. It is hypothesized that the application of image registration techniques may afford a potential solution to automating segmentation of metastically-involved vertebrae with cortical shell destruction. The objective of this study is to validate deformable registration as a means to automate the segmentation of tumour-bearing vertebrae through the transformation of atlas segmentations.

Methods: CT scans were collected from 6 patients (T4-L5) with spinal metastases secondary to breast cancer. Healthy levels from the patients were cropped and segmented using a combination of thresholding and manual delineation (Amira 3.1.1, TGS Berlin) to obtain the atlas for each vertebral level. After spatial alignment, metastatically involved vertebral levels were segmented by a registration of the atlas scan by automated affine registration (Amira) and refined by demons deformable registration (ITK, NLM Bethesda). The algorithm was tested through comparison of 10 vertebral bodies (thoracic and lumbar) segmented using the automated approach against a gold standard segmentation produced by semi-manual thresholding. The quality of the automatic segmentation was determined by calculating how many voxels were concurrently within both automatic and manual segmentation of the scan.

Results: Deformable registration successfully segmented metastatically involved vertebrae with and without breach of the cortical shell. Similar performance was evident when using an atlas from an adjacent level as compared to using an atlas of the identical vertebral level. Quality of the automatic segmentation ranged from 87.67%–96.22% concurrency. Comparisons of inter-user semi-manual segmentations yielded a similar maximum of 96% concurrency. Analysis speed was 10 to 15 times faster using the automated technique.

Conclusions: By maintaining the atlas morphology, atlas-based segmentations are able to accurately differentiate between trans-cortical tumours and surrounding soft tissue, overcoming problems inherent to more conventional automated segmentation techniques. Clinical application of this segmentation algorithm centers on tumour quantification and tracking progression of treatment effect and metastatic disease pathology. Funding: Other Education Grant Funding Parties: Canadian Breast Cancer Research Alliance, Sunnybrook & Women`s College Research Institute

Purpose: The objective of this study was to establish an automated and objective method to quantitatively characterize the extent, spatial distribution, and temporal progression of metastatic disease in the bony spine.

Methods: Serial patient CT scans from GE Light-speed Plus CT Scanners were standardized to 120kVp, 1.25mm/2.5mm slice interval/ thickness, standard reconstruction, and 0.468mm/0.468mm pixel spacing. From 3D reconstructed CT images, trabecular regions within vertebral bodies (VBs) were segmented through atlas-based deformable registration (ITK, NLM, Bethesda). Voxel intensity histograms (voxel counts vs. Hounsfield Units) were used to characterize 32 healthy and 11 metastatically involved vertebrae (T5 to L5). Healthy histograms were fitted to Gaussian regression curves and compared using one-way repeated measures ANOVA (p< 0.05). Tumours were segmented as connected areas with voxel intensities between specified thresholds (Amira 3.1.1, TGS, Berlin).

Results: Histograms of healthy vertebrae were found to be Gaussian distributions (avg. RMSD = 30 voxel counts). The Gaussian mean & #956; ranged from 120 to 290HU, presumably due to inter-patient differences in age and activity. However, the histogram data sets were not significantly different (p> 0.8) across intra-patient vertebral levels T5-L5. Consequently, the Gaussian parameters, & #956; and standard deviation & #963;, determined from fitted healthy histograms could be used in adjacent metastatic levels to define patient-specific lytic and blastic thresholds for tumor segmentation. The ideal lytic and blastic segmentation thresholds were determined to be & #956;−& #963; and & #956;+2& #963; respectively: i.e. while histograms of metastatic VBs were non-Gaussian (RMSD of 56 voxels), subtracting from them the tumourous regions segmented accordingly restored the Gaussian nature of the distributions (RMSD of 24 voxels). Metastatic involvement can then be quantified from histograms of metastases in terms of: (1) lytic/ blastic volumes from areas under the curves; (2) severity of the pathologic involvement from the distribution and range; (3) tumor progression over time or treatment effects by taking the difference between sequential scans.

Conclusions: This proposed histogram-based method for characterizing spinal metastases shows great potential in extending the quantitative capacity of CT-based radiographic evaluations, especially in tracking meta-static progression and treatment effectiveness in clinical research applications. Funding: Other Education Grant Funding Parties: NSERC and CBCRA