Carotid near-occlusion frequently has high peak systolic velocity on Doppler ultrasound.

PURPOSE: Carotid near-occlusion is a tight atherosclerotic stenosis of the internal carotid artery (ICA) resulting in decrease in diameter of the vessel lumen distal to the stenosis. Near-occlusions can be classified as with or without full collapse, and may have high peak systolic velocity (PSV) across the stenosis, mimicking conventional > 50% carotid artery stenosis. We aimed to determine how frequently near-occlusions have high PSV in the stenosis and determine how accurately carotid Doppler ultrasound can distinguish high-velocity near-occlusion from conventional stenosis. METHODS: Included patients had near-occlusion or conventional stenosis with carotid ultrasound and CT angiogram (CTA) performed within 30 days of each other. CTA examinations were analyzed by two blinded expert readers. Velocities in the internal and common carotid arteries were recorded. Mean velocity, pulsatility index, and ratios were calculated, giving 12 Doppler parameters for analysis. RESULTS: Of 136 patients, 82 had conventional stenosis and 54 had near-occlusion on CTA. Of near-occlusions, 40 (74%) had high PSV (≥ 125 cm/s) across the stenosis. Ten Doppler parameters significantly differed between conventional stenosis and high-velocity near-occlusion groups. However, no parameter was highly sensitive and specific to separate the groups. CONCLUSION: Near-occlusions frequently have high PSV across the stenosis, particularly those without full collapse. Carotid Doppler ultrasound does not seem able to distinguish conventional stenosis from high-velocity near-occlusion. These findings question the use of ultrasound alone for preoperative imaging evaluation.

Spine labeling in MRI via regularized distribution matching.

PURPOSE: This study investigates an efficient (nearly real-time) two-stage spine labeling algorithm that removes the need for an external training while being applicable to different types of MRI data and acquisition protocols. METHODS: Based solely on the image being labeled (i.e., we do not use training data), the first stage aims at detecting potential vertebra candidates following the optimization of a functional containing two terms: (i) a distribution-matching term that encodes contextual information about the vertebrae via a density model learned from a very simple user input, which amounts to a point (mouse click) on a predefined vertebra; and (ii) a regularization constraint, which penalizes isolated candidates in the solution. The second stage removes false positives and identifies all vertebrae and discs by optimizing a geometric constraint, which embeds generic anatomical information on the interconnections between neighboring structures. Based on generic knowledge, our geometric constraint does not require external training. RESULTS: We performed quantitative evaluations of the algorithm over a data set of 90 mid-sagittal MRI images of the lumbar spine acquired from 45 different subjects. To assess the flexibility of the algorithm, we used both T1- and T2-weighted images for each subject. A total of 990 structures were automatically detected/labeled and compared to ground-truth annotations by an expert. On the T2-weighted data, we obtained an accuracy of 91.6% for the vertebrae and 89.2% for the discs. On the T1-weighted data, we obtained an accuracy of 90.7% for the vertebrae and 88.1% for the discs. CONCLUSION: Our algorithm removes the need for external training while being applicable to different types of MRI data and acquisition protocols. Based on the current testing data, a subject-specific model density and generic anatomical information, our method can achieve competitive performances when applied to T1- and T2-weighted MRI images.

Normal appearing white matter permeability: a marker of inflammation and information processing speed deficit among relapsing remitting multiple sclerosis patients.

PURPOSE: Blood-brain barrier breakdown (BBBB) occurs in relapsing remitting multiple sclerosis (RRMS). Relative recirculation (rR), a BBBB surrogate, may show inflammation undetectable by gadolinium. We compared normal appearing white matter (NAWM) rR in patients with and without disability measured with Symbol Digit Modalities Test and the Expanded Disability Status Scale (EDSS). METHODS: Thirty-nine RRMS patients were prospectively recruited and classified as impaired or non-impaired based on the SDMT and EDSS threshold ≥3. Significant demographic, MRI structural and regional rR characteristics were advanced into multivariate analysis to assess the association with impairment of cognition and EDSS. Bonferroni corrected p < 0.025 was applied to demographic and rR group comparisons; p < 0.05 was used in the final multivariate logistic regression. RESULTS: rR was higher in NAWM (p = 0.012), NAGM (p = 0.004), and basal ganglia (p = 0.007) in cognitively impaired versus non-impaired patients. The difference between NAWM and T2HL rR was significant in cognitively non-impaired patients and approximated that of T2HL in impairment (0.084 vs. 0.075, p = 0.008; 0.118 vs. 0.101, p = 0.091, respectively). After adjusting for confounders, rR elevation for NAWM (OR 1.777; 95% CI 1.068-2.956; p = 0.026), NAGM (OR 2.138; 1.100-4.157; p = 0.025), and basal ganglia (OR 2.192; 1.120-4.289; p = 0.022) remained significantly predictive of cognitive impairment. NAWM area under the curve (AUC) for cognitive impairment was 0.783. No significant group differences or associations were seen for rR and EDSS impairment. No NAGM and cortical lesion rR difference was present within any of the impaired or non-impaired groups. CONCLUSION: rR elevation in NAWM, NAGM, and basal ganglia appears sensitive to cognitive impairment but not EDSS.

The relationship between white matter fiber damage and gray matter perfusion in large-scale functionally defined networks in multiple sclerosis.

BACKGROUND: Recent studies utilizing perfusion as a surrogate of cortical integrity show promise for overall cognition, but the association between white matter (WM) damage and gray matter (GM) integrity in specific functional networks is not previously studied. OBJECTIVE: To investigate the relationship between WM fiber integrity and GM node perfusion within six functional networks of relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS) patients. METHODS: Magnetic resonance imaging (MRI) and neurocognitive testing were performed on 19 healthy controls (HC), 39 RRMS, and 45 SPMS patients. WM damage extent and severity were quantified with T2-hyper/T1-hypointense (T2h/T1h) lesion volume and degree of perfusion reduction in lesional and normal-appearing white matter (NAWM), respectively. A two-step linear regression corrected for confounders was employed. RESULTS: Cognitive impairment was present in 20/39 (51%) RRMS and 25/45 (53%) SPMS patients. GM node perfusion was associated with WM fiber damage severity (WM hypoperfusion) within each network-including both NAWM ( R2 = 0.67-0.89, p < 0.0001) and T2h ( R2 = 0.39-0.62, p < 0.0001) WM regions-but was not significantly associated ( p > 0.01) with WM fiber damage extent (i.e. T2h/T1h lesion volumes). CONCLUSION: Overall, GM node perfusion was associated with severity rather than extent of WM network damage, supporting a primary etiology of GM hypoperfusion.

Spine labeling in axial magnetic resonance imaging via integral kernels.

This study investigates a fast integral-kernel algorithm for classifying (labeling) the vertebra and disc structures in axial magnetic resonance images (MRI). The method is based on a hierarchy of feature levels, where pixel classifications via non-linear probability product kernels (PPKs) are followed by classifications of 2D slices, individual 3D structures and groups of 3D structures. The algorithm further embeds geometric priors based on anatomical measurements of the spine. Our classifier requires evaluations of computationally expensive integrals at each pixel, and direct evaluations of such integrals would be prohibitively time consuming. We propose an efficient computation of kernel density estimates and PPK evaluations for large images and arbitrary local window sizes via integral kernels. Our method requires a single user click for a whole 3D MRI volume, runs nearly in real-time, and does not require an intensive external training. Comprehensive evaluations over T1-weighted axial lumbar spine data sets from 32 patients demonstrate a competitive structure classification accuracy of 99%, along with a 2D slice classification accuracy of 88%. To the best of our knowledge, such a structure classification accuracy has not been reached by the existing spine labeling algorithms. Furthermore, we believe our work is the first to use integral kernels in the context of medical images.

Perfusion reduction in the absence of structural differences in cognitively impaired versus unimpaired RRMS patients.

BACKGROUND: Cognitive impairment affects 40%-68% of relapsing-remitting multiple sclerosis (RRMS) patients. Gray matter (GM) demyelination is complicit in cognitive impairment, yet cortical lesions are challenging to image clinically. We wanted to determine whether cortical cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) differences exist between cognitively impaired (CI) and unimpaired (NI) RRMS. METHODS: Prospective study of healthy controls (n = 19), CI (n = 20), and NI (n = 19) undergoing magnetic resonance imaging (MRI) and cognitive testing <1 week apart. White matter (WM) T2 hyperintense lesions and T1 black holes were traced. General linear regression assessed the relationship between lobar WM volume and cortical and WM CBF, CBV, and MTT. Relationship between global and lobar cortical CBF, CBV, and MTT and cognitive impairment was tested using a generalized linear model. Adjusted Bonferroni p < 0.005 was considered significant. RESULTS: No significant differences for age, gender, disease duration, and any fractional brain or lesion volume were demonstrated for RRMS subgroups. Expanded Disability Status Scale (EDSS) and Hospital Anxiety and Depression Scale-Depression (HADS-D) were higher in CI. Lobar cortical CBF and CBV were associated with cognitive impairment (p < 0.0001) after controlling for confounders. Cortical CBV accounted for 7.2% of cognitive impairment increasing to 8.7% with cortical CBF (p = 0.06), while WM and cortical CBF accounted for 8.2% of variance (p = 0.04). CONCLUSION: Significant cortical CBF and CBV reduction was present in CI compared to NI in the absence of structural differences.

Regional reduction in cortical blood flow among cognitively impaired adults with relapsing-remitting multiple sclerosis patients.

PURPOSE: Detection of cortical abnormalities in relapsing-remitting multiple sclerosis (RRMS) remains elusive. Structural magnetic resonance imaging (MRI) measures of cortical integrity are limited, although functional techniques such as pseudo-continuous arterial spin labeling (pCASL) show promise as a surrogate marker of disease severity. We sought to determine the utility of pCASL to assess cortical cerebral blood flow (CBF) in RRMS patients with (RRMS-I) and without (RRMS-NI) cognitive impairment. METHODS: A total of 19 age-matched healthy controls and 39 RRMS patients were prospectively recruited. Cognition was assessed using the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) battery. Cortical CBF was compared between groups using a mass univariate voxel-based morphometric analysis accounting for demographic and structural variable covariates. RESULTS: Cognitive impairment was present in 51.3% of patients. Significant CBF reduction was present in the RRMS-I compared to other groups in left frontal and right superior frontal cortex. Compared to healthy controls, RRMS-I displayed reduced CBF in the frontal, limbic, parietal and temporal cortex, and putamen/thalamus. RRMS-I demonstrated reduced left superior frontal lobe cortical CBF compared to RRMS-NI. No significant cortical CBF differences were present between healthy controls and RRMS-NI. CONCLUSION: Significant cortical CBF reduction occurs in RRMS-I compared to healthy controls and RRMS-NI in anatomically significant regions after controlling for structural and demographic differences.

Can micro-imaging based analysis methods quantify structural integrity of rat vertebrae with and without metastatic involvement?

This study compares the ability of µCT image-based registration, 2D structural rigidity analyses and multimodal continuum-level finite element (FE) modeling in evaluating the mechanical stability of healthy, osteolytic, and mixed osteolytic/osteoblastic metastatically involved rat vertebrae. µMR and µCT images (loaded and unloaded) were acquired of lumbar spinal motion segments from 15rnu/rnu rats (five per group). Strains were calculated based on image registration of the loaded and unloaded µCT images and via analysis of FE models created from the µCT and µMR data. Predicted yield load was also calculated through 2D structural rigidity analysis of the axial unloaded µCT slices. Measures from the three techniques were compared to experimental yield loads. The ability of these methods to predict experimental yield loads were evaluated and image registration and FE calculated strains were directly compared. Quantitatively for all samples, only limited weak correlations were found between the image-based measures and experimental yield load. In comparison to the experimental yield load, we observed a trend toward a weak negative correlation with median strain calculated using the image-based strain measurement algorithm (r=-0.405, p=0.067), weak significant correlations (p<0.05) with FE based median and 10th percentile strain values (r=-0.454, -0.637, respectively), and a trend toward a weak significant correlation with FE based mean strain (r=-0.366, p=0.09). Individual group analyses, however, yielded more and stronger correlations with experimental results. Considering the image-based strain measurement algorithm we observed moderate significant correlations with experimental yield load (p<0.05) in the osteolytic group for mean and median strain values (r=-0.840, -0.832, respectively), and in the healthy group for median strain values (r=-0.809). Considering the rigidity-based predicted yield load, we observed a strong significant correlation with the experimental yield load in the mixed osteolytic/osteoblastic group (r=0.946) and trend toward a moderate correlation with the experimental yield load in the osteolytic group (r=0.788). Qualitatively, strain patterns in the vertebral bodies generated using image registration and FEA were well matched, yet quantitatively a significant correlation was found only between mean strains in the healthy group (r=0.934). Large structural differences in metastatic vertebrae and the complexity of motion segment loading may have led to varied modes of failure. Improvements in load characterization, material properties assignments and resolution are necessary to yield a more generalized ability for image-based registration, structural rigidity and FE methods to accurately represent stability in healthy and pathologic scenarios.

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.

Non-destructive evaluation of the effects of combined bisphosphonate and photodynamic therapy on bone strain in metastatic vertebrae using image registration.

Skeletal metastases most frequently affect the vertebral column and may lead to severe consequences including fracture. Clinical management of skeletal metastases often utilizes a multimodal treatment approach, including bisphosphonates (BPs). Previous work has demonstrated the synergistic potential of photodynamic therapy (PDT) in combination with BP in treating osteolytic disease through structural, histologic, and destructive mechanical testing analyses. Recent work has developed and validated image-based methods that may be used to non-destructively determine mechanical stability in whole bones, and enable their use for additional (i.e. histologic) analysis. In this work we use an intensity-based 3D image registration technique to compare the strain patterns throughout untreated control and BP + PDT treated rnu/rnu rat spinal motion segments with osteolytic metastases. It was hypothesized that the combination treatment will reduce average and maximum strain values and restore the pattern of strain to that of healthy vertebrae. Mean, median, and 90th percentile strains in the control group were significantly higher than the treatment group. High strain areas in both groups were observed around the endplates; in the control group, large areas of high strains were also observed around the lesions and adjacent to the dorsal wall. Absence of high strains adjacent to the dorsal wall (similar to healthy vertebrae) may correspond to a reduced risk of burst fracture following BP + PDT therapy. This study demonstrates the application of non-destructive image analysis to quantify the positive mechanical effects of combined BP + PDT treatment in the metastatic spine.

Automated quantitative microstructural analysis of metastatically involved vertebrae: effects of stereologic model and spatial resolution.

SUMMARY OF BACKGROUND DATA: Preclinical models of spinal metastases allow for the application of micro-image based structural assessments, however, large data sets resulting from high resolution scanning motivate a need for robust automated analysis tools. Accurate assessment of changes in vertebral architecture, however, may depend both on the resolution of images acquired and the models used to represent the structural data. OBJECTIVE: To apply a recently developed automated µCT based analysis tool to quantify the effect of diffuse metastatic disease on rat vertebral architecture at multiple resolutions. It was hypothesized that automated methods could accurately quantify differences in vertebral microstructure and that diffuse metastatic disease could be shown to have significant negative architectural effects on trabecular bone independent of stereologic model and resolution. METHODS: µCT images acquired at 14 µm(3) of healthy and metastatically involved whole lumbar rat vertebrae were analyzed at high, medium and low (8.725, 17.45, and 34.9 µm(3)) resolutions using an automated algorithm to yield micro-structural measures of the trabecular centrum and cortical shell. The images analyzed at different resolutions were obtained via up/downsampling of the acquired image data. Trabecular thickness was evaluated with the Parfitt and Hildebrand models, and anisotropy was evaluated through calculation of mean intercept length. RESULTS: Significant differences in microstructural parameters measured in comparing healthy and metastatically involved vertebrae were affected by resolution, however, relative anisotropy was maintained. The Parfitt and Hilderbrand models yielded similar structural differences between healthy and metastatic vertebrae, however, the Hildebrand model was limited due to segmentation accuracy required for its automated application. CONCLUSIONS: Differences in microstructural parameters generated through automated analysis at high resolution suggest that diffuse MT1 osteolytic destruction in whole rat vertebrae results primarily in loss of trabeculae in the metastatic vertebrae, as opposed to trabecular thinning. The sensitivity of the bony architectural parameters to resolution motivates the need for high resolution scanning or post-processing of images.

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.

A technique for the quantification of the 3D connectivity of thin articulations in bony sutures.

The anatomy and development of cranial and facial sutures have been studied in detail using histological sections, 2D radiographs and more recently CT imaging. However, little attention has been paid to evaluating and quantifying the connectivity of these thin cortical bone articulations. More recent technological advances such as micro-CT imaging has the potential to be used to provide quantitative measurements of 3D connectivity in bony articulations. This study presents a new technique for quantifying the connectivity of bony projections inside cranial and facial sutures using a combination of skeletonization, thinning algorithms and 3D intensity mapping. The technique is demonstrated in five sutures through semi-automated analysis and image processing of microCT scans. In the sagittal, coronal and frontozygomatic sutures an average bone connectivity of 6.6-11.6% was found with multiple bony projections providing an interlocking structure between adjacent bones. Much higher bone connectivity was present in the zygomaticotemporal and zygomaticomaxillary sutures (22.7-37.4%) with few bony projections. This method combining microCT scanning and image processing techniques was successfully used to quantify the connectivity of thin bone articulations and allowed detailed assessment of sutural fusion in 3D. The wider application of this technique may allow quantification of connectivity in other structures, in particular fracture healing of long bones.