Quantitative characterization of metastatic disease in the spine. Part I. Semiautomated segmentation using atlas-based deformable registration and the level set method

Spinal cord segmentation and injury detection using a Crow Search-Rider optimization algorithm

The damage in the spinal cord due to vertebral fractures may result in loss of sensation and muscle function either permanently or temporarily. The neurological condition of the patient can be improved only with the early detection and the treatment of the injury in the spinal cord. This paper proposes a spinal cord segmentation and injury detection system based on the proposed Crow search-Rider Optimization-based DCNN (CS-ROA DCNN) method, which can detect the injury in the spinal cord in an effective manner. Initially, the segmentation of the CT image of the spinal cord is performed using the adaptive thresholding method, followed by which the localization of the disc is performed using the Sparse FCM clustering algorithm (Sparse-FCM). The localized discs are subjected to a feature extraction process, where the features necessary for the classification process are extracted. The classification process is done using DCNN trained using the proposed CS-ROA, which is the integration of the Crow Search Algorithm (CSA) and Rider Optimization Algorithm (ROA). The experimentation is performed using the evaluation metrics, such as accuracy, sensitivity, and specificity. The proposed method achieved the high accuracy, sensitivity, and specificity of 0.874, 0.8961, and 0.8828, respectively that shows the effectiveness of the proposed CS-ROA DCNN method in spinal cord injury detection.

Biomechanical Properties of Metastatically Involved Osteolytic Bone

PURPOSE OF REVIEW

Skeletal metastasis involves the uncoupling of physiologic bone remodeling resulting in abnormal bone turnover and radical changes in bony architecture, density, and quality. Bone strength assessment and fracture risk prediction are critical in clinical treatment decision-making. This review focuses on bone tissue and structural mechanisms altered by osteolytic metastasis and the resulting changes to its material and mechanical behavior.

RECENT FINDINGS

Both organic and mineral phases of bone tissue are altered by osteolytic metastatic disease, with diminished bone quality evident at multiple length-scales. The mechanical performance of bone with osteolytic lesions is influenced by a combination of tissue-level and structural changes. This review considers the effects of osteolytic metastasis on bone biomechanics demonstrating its negative impact at tissue and structural levels. Future studies need to assess the cumulative impact of cancer treatments on metastatically involved bone quality, and its utility in directing multimodal treatment planning.

CT based quantitative measures of the stability of fractured metastatically involved vertebrae treated with spine stereotactic body radiotherapy

Mechanical instability secondary to vertebral metastases can lead to pathologic vertebral compression fracture (VCF) mechanical pain, neurological compromise, and the need for surgical stabilization. Stereotactic body radiation therapy (SBRT) as a treatment for spinal metastases is effective for pain and local tumor control, it has been associated with an increased risk of VCF. This study quantified computed tomography (CT) based stability measures in metastatic vertebrae with VCF treated with spine SBRT. It was hypothesized that semi-automated quantification of VCF based on CT metrics would be related to clinical outcomes. 128 SBRT treated spinal metastases patients were identified from a prospective database. Of these, 18 vertebral segments were identified with a VCF post-SBRT. A semi-automated system for quantifying VCF was developed based on CT imaging before and after SBRT. The system identified and segmented SBRT treated vertebral bodies, calculated stability metrics at single time points and changes over time. In the vertebrae that developed a new (n = 7) or progressive (n = 11) VCF following SBRT, the median time to VCF/VCF progression was 1.74 months (range 0.53-7.79 months). Fractured thoracolumbar vertebrae that went on to be stabilized (cemented and/or instrumented), had greater fractured vertebral body volume progression over time (12%) compared to those not stabilized (0.4%, p < 0.05). Neither the spinal instability neoplastic score (SINS) or any single timepoint stability metrics in post-hoc analyses correlated with future stabilization. This pilot study presents a quantitative semi-automated method assessing fractured thoracolumbar vertebrae based on CT. Increased fractured vertebral body volume progression post-SBRT was shown to predict those patients who were subsequently stabilized, motivating study of methods that assess temporal radiological changes toward augmenting existing clinical management in the metastatic spine.

Density-Dependent Material and Failure Criteria Equations Highly Affect the Accuracy and Precision of QCT/FEA-Based Predictions of Osteoporotic Vertebral Fracture Properties

About 700,000 vertebral fractures occur in the US as a result of bone loss. Quantitative computed tomography (QCT)-based finite element analysis (FEA) is a promising tool for fracture risk prediction that is becoming attractive in the clinical setting. The goals of this study were (1) to perform individual and pooled specimen optimization using inverse QCT/FEA modeling to obtain ash density-elastic modulus equations incorporating the whole vertebral body and accounting for all variables used during FE modeling, and (2) to determine the effect of material equations and failure criteria on the accuracy and precision of mechanical properties. Fifty-four (54) human vertebrae were used to optimize material equations based on experimental outcomes and, together with a previously proposed material equation, were implemented in our models using three different failure criteria to obtain fracture loads. Our robust QCT/FEA approach predicted 78% of the failure loads. Material equations resulted in poor accuracy in the predicted stiffness, yet yielded good precision and, more importantly, strong correlations with fracture loads. Both material and fracture criterion equations are equally important in estimating accurate and precise QCT/FEA predictions. Results suggest that both elastic modulus and fracture criterion equations should be validated against experimental outcomes to better explain the response of the tissue under various conditions.

Effect of metastatic lesion size and location on the load-bearing capacity of vertebrae using an optimized ash density-modulus equation

About 1.8 million new cancer cases are estimated in the US in 2019 from which 50-85% might metastasize to the thoracic and lumbar spines. Subject-specific quantitative computed tomography-based finite element analysis (QCT/FEA) is a promising used tool to predict vertebral fracture properties. The aims of this study were twofold: First, to develop an optimized equation for the elastic modulus accounting for all input parameters in FE modeling of fracture properties. Second, to assess the effect of lesion size and location on the predicted fracture loads. An inverse QCT/FEA method was implemented to determine optimal coefficients for the modulus equation as a function of ash density. Lesions of 16 and 20 mm were then virtually located at the center, off-centered, anterior, and posterior regions of the vertebrae. A total of 6426 QCT/FEA models were run to optimize the coefficients and evaluate the effect of lesions on fracture properties. QCT/FEA predicted stiffness showed high correlations (50%) with the experimentally measured values. Compared to a 16 mm lesion size, a 20 mm lesion had a reduction in failure load of 55%, 57%, 52%, and 44% at the center, off-centered, anterior cortex, and pedicle, respectively (p < 0.001). Lesions affecting mostly trabecular bone showed the largest reduction in predicted failure loads (about 55%), and females presented weaker outcomes than males. An optimal elastic modulus equation resulted in accurate vertebral stiffness predictions. A deterioration of the trabecular bone due to the presence of a lesion highly affected the predicted fracture loads, and this reduction was significantly higher in females compared to males.

Automated detection of bone metastatic changes using serial CT scans

Bone metastases resulting from a primary tumor invasion to the bone are common and cause significant morbidity in advanced cancer patients. Although the detection of bone metastases is often straightforward, it is difficult to identify their spread and track their changes, particularly in early stages. This paper presents a novel method that automatically finds the changes in appearance and the progress of bone metastases using longitudinal CT images. In contrast to previous methods based on nodule detection within a specific bone site in an individual CT scan, the approach in the present study is based on the subtraction between two registered CT volumes. The volumes registered using the proposed weighted-Demons registration and symmetric warping were subtracted with minimizing noise, and the Jacobian and false positive suppressions were performed to reduce false alarms. The proposed method detects the changes in bone metastases within 3min for entire chest bone structures covering the spine, ribs, and sternum. The method was validated based on 3-fold cross validation using the radiologists' markings of 459 lesions in 24 subjects and was performed with a sensitivity of 92.59%, a false positive volume of 2.58%, and 9.71 false positives per patient. Note that 113 lesions (24%) missed by the radiologists were identified by the present system and confirmed to be true metastases. Indeed, three patients diagnosed initially as normal, having no metastatic difference, by radiologists were found to be abnormal using the proposed system. Automatic detection method of bone metastatic changes in the entire chest bone was developed. Weighted Demons, symmetric warping, following false positive suppressions, and their parallel computing implementation enabled precise and fast computation of delicate changes in serial CT scans. The cross validation proved that this method can be quite useful for assisting radiologists in sensing minute metastatic changes from early stage.

Combined bone lesion analysis in 3D CT data of vertebrae

Two novel statistically based methods for bone lesion detection and classification are presented. Together with the previously published MRF method [15], they form a triad of mutually complementary methods that promise, when fused, to enable higher reliability of bone lesion assessment.

Automatic Segmentation of Spinal Canals in CT Images via Iterative Topology Refinement

Accurate segmentation of the spinal canals in computed tomography (CT) images is an important task in many related studies. In this paper, we propose an automatic segmentation method and apply it to our highly challenging image cohort that is acquired from multiple clinical sites and from the CT channel of the PET-CT scans. To this end, we adapt the interactive random-walk solvers to be a fully automatic cascaded pipeline. The automatic segmentation pipeline is initialized with robust voxelwise classification using Haar-like features and probabilistic boosting tree. Then, the topology of the spinal canal is extracted from the tentative segmentation and further refined for the subsequent random-walk solver. In particular, the refined topology leads to improved seeding voxels or boundary conditions, which allow the subsequent random-walk solver to improve the segmentation result. Therefore, by iteratively refining the spinal canal topology and cascading the random-walk solvers, satisfactory segmentation results can be acquired within only a few iterations, even for cases with scoliosis, bone fractures and lesions. Our experiments validate the capability of the proposed method with promising segmentation performance, even though the resolution and the contrast of our dataset with 110 patient cases (90 for testing and 20 for training) are low and various bone pathologies occur frequently.

A fully automated level-set based segmentation method of thoracic and lumbar vertebral bodies in Computed Tomography images

Spine is a structure commonly involved in several diseases. Identification and segmentation of the vertebral structures are of relevance to many medical applications related to the spine such as diagnosis, therapy or surgical intervention. However, the development of automatic and reliable methods are an unmet need. This work presents a fully automatic segmentation method of thoracic and lumbar vertebral bodies from Computed Tomography images. The procedure can be divided into four main stages: firstly, seed points were detected in the spinal canal in order to generate initial contours in the segmentation process, automating the whole process. Secondly, a processing step is performed to improve image quality. Third step was to carry out the segmentation using the Selective Binary Gaussian Filtering Regularized Level Set method and, finally, two morphological operations were applied in order to refine the segmentation result. The method was tested in clinical data coming from 10 trauma patients. To evaluate the result the average value of the DICE coefficient was calculated, obtaining a 90.86 ± 1.87% in the whole spine (thoracic and lumbar regions), a 86.08 ± 1.73% in the thoracic region and a 95,61 ±2,25% in the lumbar region. The results are highly competitive when compared to the results obtained in previous methods, especially for the lumbar region.

Development and evaluation of an articulated registration algorithm for human skeleton registration

Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index-DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the skeletons were deformed. Articulated registration is superior to rigid and deformable registrations by capturing global flexibility while preserving local rigidity inherent in skeleton registration. Therefore, articulated registration can be employed to accurately register the whole-body human skeletons, and it enables the treatment response assessment of various bone diseases.

Evaluation of whole-body MR to CT deformable image registration

Multimodality image registration plays a crucial role in various clinical and research applications. The aim of this study is to present an optimized MR to CT whole‐body deformable image registration algorithm and its validation using clinical studies. A 3D intermodality registration technique based on B‐spline transformation was performed using optimized parameters of the elastix package based on the Insight Toolkit (ITK) framework. Twenty‐eight (17 male and 11 female) clinical studies were used in this work. The registration was evaluated using anatomical landmarks and segmented organs. In addition to 16 anatomical landmarks, three key organs (brain, lungs, and kidneys) and the entire body volume were segmented for evaluation. Several parameters — such as the Euclidean distance between anatomical landmarks, target overlap, Dice and Jaccard coefficients, false positives and false negatives, volume similarity, distance error, and Hausdorff distance — were calculated to quantify the quality of the registration algorithm. Dice coefficients for the majority of patients (>75%) were in the 0.8–1 range for the whole body, brain, and lungs, which satisfies the criteria to achieve excellent alignment. On the other hand, for kidneys, Dice coefficients for volumes of 25% of the patients meet excellent volume agreement requirement, while the majority of patients satisfy good agreement criteria (>0.6). For all patients, the distance error was in 0–10 mm range for all segmented organs. In summary, we optimized and evaluated the accuracy of an MR to CT deformable registration algorithm. The registered images constitute a useful 3D whole‐body MR‐CT atlas suitable for the development and evaluation of novel MR‐guided attenuation correction procedures on hybrid PET‐MR systems.

PACS number: 07.05.Pj

An optimized process flow for rapid segmentation of cortical bones of the craniofacial skeleton using the level-set method

Accurate representation of skeletal structures is essential for quantifying structural integrity, for developing accurate models, for improving patient-specific implant design and in image-guided surgery applications. The complex morphology of thin cortical structures of the craniofacial skeleton (CFS) represents a significant challenge with respect to accurate bony segmentation. This technical study presents optimized processing steps to segment the three-dimensional (3D) geometry of thin cortical bone structures from CT images. In this procedure, anoisotropic filtering and a connected components scheme were utilized to isolate and enhance the internal boundaries between craniofacial cortical and trabecular bone. Subsequently, the shell-like nature of cortical bone was exploited using boundary-tracking level-set methods with optimized parameters determined from large-scale sensitivity analysis. The process was applied to clinical CT images acquired from two cadaveric CFSs. The accuracy of the automated segmentations was determined based on their volumetric concurrencies with visually optimized manual segmentations, without statistical appraisal. The full CFSs demonstrated volumetric concurrencies of 0.904 and 0.719; accuracy increased to concurrencies of 0.936 and 0.846 when considering only the maxillary region. The highly automated approach presented here is able to segment the cortical shell and trabecular boundaries of the CFS in clinical CT images. The results indicate that initial scan resolution and cortical-trabecular bone contrast may impact performance. Future application of these steps to larger data sets will enable the determination of the method's sensitivity to differences in image quality and CFS morphology.

High precision semiautomated computed tomography measurement of lumbar disk and vertebral heights

PURPOSE

Evaluation of treatments of many spine disorders requires precise measurement of the heights of vertebral bodies and disk spaces. The authors present a semiautomated computer algorithm measuring those heights from spine computed tomography (CT) scans and evaluate its precision.

METHODS

Eight patients underwent two spine CT scans in the same day. In each scan, five thoracolumbar vertebral heights and four disk heights were estimated using the algorithm. To assess precision, the authors computed the differences between the height measurements in the two scans, coefficients of variation (CV), and 95% limits of agreement. Intraoperator and interoperator precisions were evaluated. For local vertebral and disk height measurement (anterior, middle, posterior) the algorithm was compared to a manual mid-sagittal plane method.

RESULTS

The mean (standard deviation) interscan difference was as low as 0.043 (0.031) mm for disk heights and 0.044 (0.043) mm for vertebral heights. The corresponding 95% limits of agreement were [-0.085, 0.11] and [-0.10, 0.12] mm, respectively. Intraoperator and interoperator precision was high, with a maximal CV of 0.30%. For local vertebral and disk heights, the algorithm improved upon the precision of the manual mid-sagittal plane measurement by as much as a factor of 6 and 4, respectively.

CONCLUSIONS

The authors evaluated the precision of a novel computer algorithm for measuring vertebral body heights and disk heights using short term repeat CT scans of patients. The 95% limits of agreement indicate that the algorithm can detect small height changes of the order of 0.1 mm.

3D CT spine data segmentation and analysis of vertebrae bone lesions

A method is presented aiming at detecting and classifying bone lesions in 3D CT data of human spine, via Bayesian approach utilizing Markov random fields. A developed algorithm for necessary segmentation of individual possibly heavily distorted vertebrae based on 3D intensity modeling of vertebra types is presented as well.

Inter-rater reliability between musculoskeletal radiologists and orthopedic surgeons on computed tomography imaging features of spinal metastases

INTRODUCTION

The primary objective of this pilot study was to examine the inter-rater reliability in scoring the computed tomography (ct) imaging features of spinal metastases in patients referred for radiotherapy (rt) for bone pain.

METHODS

In a retrospective review, 3 musculoskeletal radiologists and 2 orthopedic spinal surgeons independently evaluated ct imaging features for 41 patients with spinal metastases treated with rt in an outpatient radiation clinic from January 2007 to October 2008. The evaluation used spinal assessment criteria that had been developed in-house, with reference to osseous and soft tissue tumour extent,presence of a pathologic fracture,severity of vertebral height loss, andpresence of kyphosis.The Cohen kappa coefficient between the two specialties was calculated.

RESULTS

Mean patient age was 69.2 years (30 men, 11 women). The mean total daily oral morphine equivalent was 73.4 mg. Treatment dose-fractionation schedules included 8 Gy/1 (n = 28), 20 Gy/5 (n = 12), and 20 Gy/8 (n = 1). Areas of moderate agreement in identifying the ct imaging appearance of spinal metastasis included extent of vertebral body involvement (κ = 0.48) and soft-tissue component (κ = 0.59). Areas of fair agreement included extent of pedicle involvement (κ = 0.28), extent of lamina involvement (κ = 0.35), and presence of pathologic fracture (κ = 0.20). Areas of poor agreement included nerve-root compression (κ = 0.14) and vertebral body height loss (κ = 0.19).

CONCLUSIONS

The range of agreement between musculoskeletal radiologists and orthopedic surgeons for most spinal assessment criteria is moderate to poor. A consensus for managing challenging vertebral injuries secondary to spinal metastases needs to be established so as to best triage patients to the most appropriate therapeutic modality.

Multimodal μCT/μMR based semiautomated segmentation of rat vertebrae affected by mixed osteolytic/osteoblastic metastases

PURPOSE

Multimodal microimaging in preclinical models is used to examine the effect of spinal metastases on bony structure; however, the evaluation of tumor burden and its effect on microstructure has thus far been mainly qualitative or semiquantitative. Quantitative analysis of multimodality imaging is a time consuming task, motivating automated methods. As such, this study aimed to develop a low complexity semiautomated multimodal μCT/μMR based approach to segment rat vertebral structure affected by mixed osteolytic/osteoblastic destruction.

METHODS

Mixed vertebral metastases were developed via intracardiac injection of Ace-1 canine prostate cancer cells in three 4-week-old rnu/rnu rats. μCT imaging (for high resolution bone visualization), T1-weighted μMR imaging (for bone registration), and T2-weighted μMR imaging (for osteolytic tumor visualization) were conducted on one L1, three L2, and one L3 vertebrae (excised). One sample (L1-L3) was processed for undecalcified histology and stained with Goldner's trichome. The μCT and μMR images were registered using a 3D rigid registration algorithm with a mutual information metric. The vertebral microarchitecture was segmented from the μCT images using atlas-based demons deformable registration, levelset curvature evolution, and intensity-based thresholding techniques. The μCT based segmentation contours of the whole vertebrae were used to mask the T2-weighted μMR images, from which the osteolytic tumor tissue was segmented (intensity-based thresholding).

RESULTS

Accurate registration of μCT and μMRI modalities yielded precise segmentation of whole vertebrae, trabecular centrums, individual trabeculae, and osteolytic tumor tissue. While the algorithm identified the osteoblastic tumor attached to the vertebral pereosteal surfaces, it was limited in segmenting osteoblastic tissue located within the trabecular centrums.

CONCLUSIONS

This semiautomated segmentation method yielded accurate registration of μCT and μMRI modalities with application to the development of mathematical models analyzing the mechanical stability of metastatically involved vertebrae and in preclinical applications evaluating new and existing treatment effects on tumor burden and skeletal microstructure.

Quantification of the effect of osteolytic metastases on bone strain within whole vertebrae using image registration

The vertebral column is the most frequent site of metastatic involvement of the skeleton with up to 1/3 of all cancer patients developing spinal metastases. Longer survival times for patients, particularly secondary to breast cancer, have increased the need for better understanding the impact of skeletal metastases on structural stability. This study aims to apply image registration to calculate strain distributions in metastatically involved rodent vertebrae utilizing µCT imaging. Osteolytic vertebral lesions were developed in five rnu/rnu rats 2-3 weeks post intracardiac injection with MT-1 human breast cancer cells. An image registration algorithm was used to calculate and compare strain fields due to axial compressive loading in metastatically involved and control vertebrae. Tumor-bearing vertebrae had greatly increased compressive strains, double the magnitude of strain compared to control vertebrae (p=0.01). Qualitatively strain concentrated within the growth plates in both tumor bearing and control vertebrae. Most interesting was the presence of strain concentrations at the dorsal wall in metastatically involved vertebrae, suggesting structural instability. Strain distributions, quantified by image registration were consistent with known consequences of lytic involvement. Metastatically involved vertebrae had greater strain magnitude than control vertebrae. Strain concentrations at the dorsal wall in only the metastatic vertebrae, were consistent with higher incidence of burst fracture secondary to this pathology. Future use of image registration of whole vertebrae will allow focused examination of the efficacy of targeted and systemic treatments in reducing strains and the related risk of fracture in pathologic bones under simple and complex loading.

Evaluating the effects of mixed osteolytic/osteoblastic metastasis on vertebral bone quality in a new rat model

Spinal metastases often show mixed areas of enhanced (osteoblastic) bone growth adjacent to areas of thinning (osteolytic) bone. This study aims to quantitatively characterize bone quality and tumor burden within a new rat model of mixed osteolytic/osteoblastic spinal metastases. Mixed vertebral metastases were analyzed in nude rats 21-days post intracardiac injection of Ace-1 canine prostate cancer cells. Vertebral micro-architecture was assessed in µCT images. Histologic processing quantified tumor burden (PTHrP), osteoclast activity (TRAP), and osteoid formation (Goldner's Trichrome) in ½ of all samples. Remaining samples were mechanically tested to failure in compression. Metastatically involved vertebrae exhibited extreme osteolysis, evident through an increase in osteoclasts leading to significantly reduced trabecular bone volume. Metastatically involved vertebrae also exhibited increased osteoid characteristic of osteoblastic lesions. While mechanical properties in tumor-bearing vertebrae were not significantly decreased compared to controls, a strong correlation was found between trabecular volumetric BMD and ultimate force. The highly aggressive Ace-1 skeletal metastases demonstrated predominant osteolysis with some areas of immature, new osteoblastic bone formation. Bone quality resulting from these lesions consisted of decreased structural properties, but without a significant impact on mechanical integrity.

Local treatment of mixed osteolytic/osteoblastic spinal metastases: is photodynamic therapy effective?

The widespread use of systemic and local therapies aimed at spinal metastatic lesions secondary to breast cancer has increased the incidence of mixed osteolytic/osteoblastic patterns of bony disease. The complex structure of these lesions requires novel therapeutic approaches to both reduce tumor burden and restore structural stability. In photodynamic therapy (PDT), a minimally invasive approach can be used to employ light to activate a photosensitizing agent that preferentially accumulates in tumor tissue, leading to cell toxicity and death. Previous work in an osteolytic rat model (MT-1) demonstrated that PDT effectively ablates tumor and improves vertebral structural properties. The aim of this study was to assess the efficacy of PDT in a rat model of mixed osteolytic/osteoblastic spinal metastases. Mixed spinal metastases were generated through intracardiac injection of Ace-1 canine prostate cancer cells into female athymic rats (day 0). A single PDT treatment was applied to lumbar vertebra L2 of tumor-bearing and healthy control rats (day 14). PDT-treated and untreated control rats were euthanized and excised spines imaged with μCT to assess bone quality (day 21). Spines were mechanically tested or histologically processed to assess mechanical integrity, tumor burden, and remodelling properties. Untreated tumor-bearing vertebrae showed large areas of osteolysis and areas of immature, new bone formation. The overall bone quality resulting from these lesions consisted of decreased structural properties but without a significant reduction in mechanical integrity. PDT was shown to significantly decrease tumor burden and osteoclastic activity, thereby improving vertebral bone structural properties. While non-tumor-bearing vertebrae exhibited significantly more new bone formation following PDT, the already heightened level of new bone formation in the mixed tumor-bearing vertebrae was not further increased. As such, the effect of PDT on mixed metastases may be more influenced by suppression of osteoclastic resorption as opposed to the triggering of new bone formation.

Micro-computed tomography-based highly automated 3D segmentation of the rat spine for quantitative analysis of metastatic disease

Noninvasive evaluation of metastatic disease in the spine has generally been limited to 2D qualitative or semiquantitative analysis techniques. This study aims to develop and evaluate a highly automated micro-CT-based quantitative analysis tool that can measure the architectural impact of metastatic involvement in whole vertebrae. Micro-CT analysis of rat whole vertebrae was conducted using a combination of demons deformable registration, level set curvature evolution, and intensity based thresholding techniques along with upsampling and edge enhancement techniques. The algorithm was applied to 6 lumbar vertebrae (L1-3) from 6 rnu/rnu rats (3 healthy rats and 3 with metastatic involvement). Osteolytic metastatic involvement was modeled via MT1 human breast cancer cells. Excellent volumetric concurrency was achieved in comparing the automated micro-CT-based segmentations of the whole vertebrae, trabecular centrums, and individual trabecular networks to manual segmentations (98.9%, 96.1%, and 98.3%, respectively; 6 specimens), and the automated segmentations were achieved in a fraction of the time. The algorithm successfully accounted for discontinuities in the cortical shell caused by vasculature and osteolytic destruction. As such, this work demonstrates the potential of this highly automated segmentation tool to permit rapid precise quantitative structural analysis of the spine with minimum user interaction in the analysis of both healthy and pathological (metastatically involved) vertebrae. Future optimization and the incorporation of lower-resolution imaging parameters may allow automated analysis of clinical CT-based measures in addition to preclinical micro-CT-based analyses of the structural impact and progression of pathological processes in the spine.

Binary segmentation masks can improve intrasubject registration accuracy of bone structures in CT images

Registration of bone structures is a common problem in medical research as well as in clinical applications. Intrasubject rigid 3D monomodality registration of segmented bone structures of CT images and multimodality registration of muMR and segmented muCT bone images were performed with the multiresolution intensity-based technique implemented in ITK. The registration results for binary volumes of interest (VOI) masks and for segmented gray value VOIs were compared. To determine the registration quality, in the monomodality case the sum of squared difference, the sum of absolute differences, and the normalized symmetric difference of binary masks and in the multimodality case Mattes mutual information were applied. The use of binary VOI masks was significantly superior to the use of gray value VOIs.

Beyond bisphosphonates: photodynamic therapy structurally augments metastatically involved vertebrae and destroys tumor tissue

Breast cancer patients commonly develop metastases in the spine, which compromises its mechanical stability and can lead to skeletal related events. The current clinical standard of treatment includes the administration of systemic bisphosphonates (BP) to reduce metastatically induced bone destruction. However, response to BPs can vary both within and between patients, which motivates the need for additional treatment options for spinal metastasis. Photodynamic therapy (PDT) has been shown to be effective at treating metastatic lesions secondary to breast cancer in an athymic rat model, and is proposed as a treatment for spinal metastasis. The objective of this study was to determine the effect of PDT, alone or in combination with previously administered systemic BPs, on the structural and mechanical integrity of both healthy and metastatically involved vertebrae. Human breast carcinoma cells (MT-1) were inoculated into athymic rats (day 0). At 14 days, a single PDT treatment was administered, with and without previous BP treatment at day 7. In addition to causing tumor necrosis in metastatically involved vertebrae, PDT significantly reduced bone loss, resulting in strengthening of the vertebrae compared to untreated controls. Combined treatment with BP + PDT further enhanced bone architecture and strength in both metastatically involved and healthy bone. Overall, the ability of PDT to both ablate malignant tissue and improve the structural integrity of vertebral bone motivates its consideration as a local minimally invasive treatment for spinal metastasis secondary to breast cancer.

Radiological changes following second-line zoledronic acid treatment in breast cancer patients with bone metastases

Initiation of bisphosphonate therapy in bisphosphonate-naïve patients is known to be associated with radiological changes such as increased bone density in both osteolytic and osteoblastic metastases. It is not known, however, whether switching from a second-generation bisphosphonate to a more potent agent is associated with similar changes. This study aimed to prospectively explore radiological changes, as assessed by thoracolumbar CT scanning, in patients switching from an early generation bisphosphonate (i.e., oral clodronate or intravenous pamidronate) to intravenous zoledronic acid. Patients with progressive bone metastases despite use of an earlier generation bisphosphonate were switched to zoledronic acid as part of a study to evaluate the palliative benefit of this intervention. Quantitative computed tomography (QCT) scanning of the thoracolumbar spine was carried out at baseline, and repeated 4 months after commencing zoledronic acid. The effect of this change of therapy was explored in terms of bone density, as well as volume of osteolytic and osteoblastic disease. Fifteen patients were assessed. Switching of bisphosphonate therapy was associated with a significant increase in bone density, and an increase in osteoblastic volume. There was an insignificant trend towards reduced osteolytic volume. In conclusion, switching from early generation bisphosphonates to a more potent agent is associated with radiological changes similar to those seen when commencing a bisphosphonate in treatment-naïve patients. This is consistent with the observed palliative benefit. The use of QCT may be of benefit in the monitoring of bone metastases.

The effective application of segmental image fusion in spinal radiosurgery for improved targeting of spinal tumours

PURPOSE

As a result of experiences of failed image fusion, an improved protocol for effective CT and MRI image fusion was developed. Image fusion is a critical part of image-guided stereotactic radiosurgery (IG-SRS) and greatly influences the accurate measurement of gross tumour volume (GTV) and optimal dosimetry. Avoidance of any positional discrepancy is vital for optimal image fusion and results in improved targeting, which improves clinical results. This paper describes a protocol for effective image fusion and how it impacted on the clinical outcome of stereotactic radiosurgery for spinal tumours.

METHODS

Fused MRI/CT images from 20 patients were examined and compared. A protocol for fusing images from thin slice MR images and CTs was developed for improved identification and measurement of tumour volume. Differences in individual GTV values both before and after image fusion were evaluated. The effectiveness of tumour targeting was also assessed by comparing discrepancies in individual and overall GTV values.

RESULTS

Differences in mean GTVs using either CT or MRI alone compared with the mean found through combined CT/MR image fusion showed a difference of 30.5 +/- 4.8% and 14.5 +/- 3.3% respectively. Additionally, the median GTV values from CT- and MR-based imaging were 11.64 +/- 7.8 cm(3) and 11.72 +/- 6.6 cm(3) vs 14.06 +/- 8.0 cm(3). Median GTV from CT-MR fusion was 14.06 +/- 8.0 cm(3). Improved information provided by the fused images enabled us to prescribe more effective dosages, as the fused images gave more accurate information about tumour se due to better delineation of tumour perimeters.

CONCLUSIONS

This protocol provides improved visualisation of spinal tumours and enables better treatment planning. Segmented image fusion was shown to provide significant advantages for planning stereotactic radiosurgery. Fused images provided more precise and accurate data and allowed better targeting of tumours, with improved tumour coverage that resulted in better clinical outcomes.

Comparison of computed tomography based parametric and patient-specific finite element models of the healthy and metastatic spine using a mesh-morphing algorithm

STUDY DESIGN

A comparative analysis of parametric and patient-specific finite element (FE) modeling of spinal motion segments.

OBJECTIVES

To develop patient-specific FE models of spinal motion segments using mesh-morphing methods applied to a parametric FE model. To compare strain and displacement patterns in parametric and morphed models for both healthy and metastatically involved vertebrae.

SUMMARY OF BACKGROUND DATA

Parametric FE models may be limited in their ability to fully represent patient-specific geometries and material property distributions. Generation of multiple patient-specific FE models has been limited because of computational expense. Morphing methods have been successfully used to generate multiple specimen-specific FE models of caudal rat vertebrae.

METHODS

FE models of a healthy and a metastatic T6-T8 spinal motion segment were analyzed with and without patient-specific material properties. Parametric and morphed models were compared using a landmark-based morphing algorithm.

RESULTS

Morphing of the parametric FE model and including patient-specific material properties both had a strong impact on magnitudes and patterns of vertebral strain and displacement.

CONCLUSION

Small but important geometric differences can be represented through morphing of parametric FE models. The mesh-morphing algorithm developed provides a rapid method for generating patient-specific FE models of spinal motion segments.

Orthopedic surgery implications of breast cancer

Breast cancer is the most common malignancy and the second leading cause of death in women. The metastatic involvement of bone denotes disease progression and decreased survival. Controversy exists regarding the exact pathophysiologic mechanism of metastasis and the different pathways that determine an osteoblastic versus osteoclastic bone compromise. Several breakthrough advances in imaging techniques aid in the detection, staging and follow-up of bone metastases. Although usually responsive to hormonal therapy and pharmacologic interventions, skeletal metastases often require some type of surgical intervention. Orthopedic surgeons should establish an active role in the multidisciplinary treatment of patients with breast cancer.

Mesh-morphing algorithms for specimen-specific finite element modeling

Despite recent advances in software for meshing specimen-specific geometries, considerable effort is still often required to produce and analyze specimen-specific models suitable for biomechanical analysis through finite element modeling. We hypothesize that it is possible to obtain accurate models by adapting a pre-existing geometry to represent a target specimen using morphing techniques. Here we present two algorithms for morphing, automated wrapping (AW) and manual landmarks (ML), and demonstrate their use to prepare specimen-specific models of caudal rat vertebrae. We evaluate the algorithms by measuring the distance between target and morphed geometries and by comparing response to axial loading simulated with finite element (FE) methods. First a traditional reconstruction process based on microCT was used to obtain two natural specimen-specific FE models. Next, the two morphing algorithms were used to compute mappings from the surface of one model, the source, to the other, the target, and to use this mapping to morph the source mesh to produce a target mesh. The microCT images were then used to assign element-specific material properties. In AW the mappings were obtained by wrapping the source and target surfaces with an auxiliary triangulated surface. In ML, landmarks were manually placed on corresponding locations on the surfaces of both source and target. Both morphing algorithms were successful in reproducing the shape of the target vertebra with a median distance between natural and morphed models of 18.8 and 32.2 microm, respectively, for AW and ML. Whereas AW-morphing produced a surface more closely resembling that of the target, ML guaranteed correspondence of the landmark locations between source and target. Morphing preserved the quality of the mesh producing models suitable for FE simulation. Moreover, there were only minor differences between natural and morphed models in predictions of deformation, strain and stress. We therefore conclude that it is possible to use mesh-morphing techniques to produce accurate specimen-specific FE models of caudal rat vertebrae. Mesh morphing techniques provide advantages over conventional specimen-specific finite element modeling by reducing the effort required to generate multiple target specimen models, facilitating intermodel comparisons through correspondence of nodes and maintenance of connectivity, and lends itself to parametric evaluation of "artificial" geometries with a focus on optimizing reconstruction.

Quantitative characterization of metastatic disease in the spine. Part II. Histogram-based analyses

Radiological imaging is essential to the appropriate management of patients with bone metastasis; however, there have been no widely accepted guidelines as to the optimal method for quantifying the potential impact of skeletal lesions or to evaluate response to treatment. The current inability to rapidly quantify the response of bone metastases excludes patients with cancer and bone disease from participating in clinical trials of many new treatments as these studies frequently require patients with so-called measurable disease. Computed tomography (CT) can provide excellent skeletal detail with a sensitivity for the diagnosis of bone metastases. The purpose of this study was to establish an objective method to quantitatively characterize disease in the bony spine using CT-based segmentations. It was hypothesized that histogram analysis of CT vertebral density distributions would enable standardized segmentation of tumor tissue and consequently allow quantification of disease in the metastatic spine. Thirty two healthy vertebral CT scans were first studied to establish a baseline characterization. The histograms of the trabecular centrums were found to be Gaussian distributions (average root-mean-square difference=30 voxel counts), as expected for a uniform material. Intrapatient vertebral level similarity was also observed as the means were not significantly different (p > 0.8). Thus, a patient-specific healthy vertebral body histogram is able to characterize healthy trabecular bone throughout that individual's thoracolumbar spine. Eleven metastatically involved vertebrae were analyzed to determine the characteristics of the lytic and blastic bone voxels relative to the healthy bone. Lytic and blastic tumors were segmented as connected areas with voxel intensities between specified thresholds. The tested thresholds were mu-1.0 sigma, mu - 1.5 sigma, and mu - 2.0 sigma, for lytic and mu + 2.0 sigma, mu+3.0 siema, and mu + 3.5 sigma for blastic tissue where mu and sigma were taken from the Gaussian characterization of a healthy level within the same patient. The ideal lytic and blastic segmentation thresholds were determined to be mu-sigma and mu + 2 sigma, respectively. Using the optimized thresholds to segment tumor tissue, a quantitative characterization of disease is possible to calculate tumor volumes, disease severity, and temporal progression or treatment effect. Our proposed histogram-based method for characterizing spinal metastases shows great potential in extending the quantitative capacity of CT-based radiographic evaluations.