17 research outputs found
A customized protocol to assess bone quality in the metacarpal head, metacarpal shaft and distal radius: a high resolution peripheral quantitative computed tomography precision study
Analysis techniques and bone developmental patterns in normal and swim-trained mice using micro-computed tomography
Bibliography: p. 163-187Some pages are in colour
A customized protocol to assess bone quality in the metacarpal head, metacarpal shaft and distal radius: a high resolution peripheral quantitative computed tomography precision study
Background:
High Resolution-Peripheral Quantitative Computed Tomography (HR-pQCT) is an emerging technology for evaluation of bone quality in Rheumatoid Arthritis (RA). However, there are limitations with standard HR-pQCT imaging protocols for examination of regions of bone commonly affected in RA. We developed a customized protocol for evaluation of volumetric bone mineral density (vBMD) and microstructure at the metacarpal head (MH), metacarpal shaft (MS) and ultra-ultra-distal (UUD) radius; three sites commonly affected in RA. The purpose was to evaluate short-term measurement precision for bone density and microstructure at these sites.
Methods:
12 non-RA participants, individuals likely to have no pre-existing bone damage, consented to participate [8 females, aged 23 to 71 y [median (IQR): 44 (28) y]. The custom protocol includes more comfortable/stable positioning and adapted cortical segmentation and direct transformation analysis methods. Dominant arm MH, MS and UUD radius scans were completed on day one; repeated twice (with repositioning) three to seven days later. Short-term precision for repeated measures was explored using intraclass correlational coefficient (ICC), mean coefficient of variation (CV%), root mean square coefficient of variation (RMSCV%) and least significant change (LSC%95).
Results:
Bone density and microstructure precision was excellent: ICCs varied from 0.88 (MH2 trabecular number) to .99 (MS3 polar moment of inertia); CV% varied from  3 on 5 point scale.
Conclusion:
In our facility, this custom protocol extends the potential for in vivo HR-pQCT imaging to assess, with high precision, regional differences in bone quality at three sites commonly affected in RA. Our methods are easy to adopt and we recommend other users of HR-pQCT consider this protocol for further evaluations of its precision and feasibility in their imaging facilities.Family Practice, Department ofMedicine, Faculty ofOrthopaedics, Department ofPhysical Therapy, Department ofOther UBCNon UBCReviewedFacult
Validation of VDA with a human cell line.
<p>(<b>A</b>) Bioluminescence images taken just prior to DMXAA treatment, as well as at 6 and 24 hrs post treatment of NIH-III mice bearing subcutaneous tumors composed of luciferase-expressing MDA-MB-231 breast cancer cells. (<b>B</b>) Quantification of the photon flux from representative tumors demonstrates a large drop in bioluminescent signal by 6 hours. (<b>C</b>) 3-D micro-CT renderings of tumors (gray), and embedded vasculature (red), of the MDA-MB-231-Luc2 tumors. (<b>D</b>) Quantification of the binarized images demonstrating vessel volume (VV), and vessel density (VV/TV). Data represents averages ± s.e.m. (N = 3), asterisks indicate p<0.05.</p
Microfil combined with micro-CT.
<p>(<b>A</b>) Image of a Microfil-perfused tumor grown subcutaneously in a mouse (top). The Microfil polymer is yellow, allowing one to visualize the effectiveness of the perfusion. Images of a non-perfused tumor (bottom left), and of the perfused dermis without a tumor (bottom right) are included as a control. (<b>B</b>) 3-D reconstructions of the tumor in (<b>A</b>) showing a surface rendering of the vasculature (top left), the thickness of the vessels demonstrated by a heat map and the intravascular distances (top right), or vessel separation demonstrated with a sphere-filling model (bottom left – full view, bottom right – cross-section through centre of tumor). Note that the vessels are not shown in the sphere-filled images, only the inter-vessel spaces.</p
Quantification of vessel thickness.
<p>(<b>A</b>) 3-D renderings of vasculature (red  =  vessel diameters of 0.2 mm or greater) showing the organized kidney vasculature versus the disorganized, irregular vessel diameters in the NSCLC tumors (344SQ, 7417PF and H1299). (<b>B</b>) Quantification of vessel thickness of two human and two murine cell lines over the entire spectrum of vessel diameters, showing very significant differences between normal and tumor vasculature, with most of the tumors only having vessels up to 0.5 mm, while the kidneys had vessels up to 1.25 mm in diameter (note the log scale on Y axis).</p
Assessing the effects of a vascular disrupting agent.
<p>(<b>A</b>) Bioluminescence images of luciferase-expressing 344SQ-EL cell line-derived subcutaneous tumors. Images were taken prior to treatment, and again at 6 and 24 hrs post DMXAA treatment. This agent led to a dramatic loss of bioluminescence. (<b>B</b>) Quantification of changes in photon emission rates of the DMXAA-treated, and control tumors (data represent averages ± s.e.m., N = 20). (<b>C</b>) 3-D micro-CT surface renderings (gray and red) and cross-sectional maximal-spheres filling model rendering (red  =  vessel diameters of 2 mm or greater) for representative subcutaneous tumors treated with either DMXAA or vehicle control, and perfused with Microfil after 24 hrs. The images demonstrate a large increase in the necrotic regions following DMXAA treatment. (<b>D</b>) Quantification of the vessel volume, density, and separation of DMXAA-treated tumors. There was a decrease in vessel volume and density, and in well-vascularized areas, as indicated by the drop in spheres present with sizes between 0–100 µm. This result was consistent with an increase in the size of the necrotic areas in the DMXAA-treated tumors. Data indicate averages ± s.e.m., N = 6 per sample. Asterisks indicate: * p<0.05, ** p<0.01.</p
Quantitative <em>Ex-Vivo</em> Micro-Computed Tomographic Imaging of Blood Vessels and Necrotic Regions within Tumors
<div><p>Techniques for visualizing and quantifying the microvasculature of tumors are essential not only for studying angiogenic processes but also for monitoring the effects of anti-angiogenic treatments. Given the relatively limited information that can be gleaned from conventional 2-D histological analyses, there has been considerable interest in methods that enable the 3-D assessment of the vasculature. To this end, we employed a polymerizing intravascular contrast medium (Microfil) and micro-computed tomography (micro-CT) in combination with a maximal spheres direct 3-D analysis method to visualize and quantify <em>ex-vivo</em> vessel structural features, and to define regions of hypoperfusion within tumors that would be indicative of necrosis. Employing these techniques we quantified the effects of a vascular disrupting agent on the tumor vasculature. The methods described herein for quantifying whole tumor vascularity represent a significant advance in the 3-D study of tumor angiogenesis and evaluation of novel therapeutics, and will also find potential application in other fields where quantification of blood vessel structure and necrosis are important outcome parameters.</p> </div
Imaging and quantification of avascular necrosis.
<p>(<b>A</b>) 3-D renderings from the kidney and NSCLC tumors following application of the maximal sphere-filling model; intact sample views above and cross-sectional images below (red indicating 2 mm or greater diameter of sphere). The presence of red (avascular) areas can be seen in all the tumor cell lines tested. (<b>B</b>) Histogram quantification of the maximal-spheres of two human and two murine cell lines by evaluating the total number of spheres present at increasing ranges of diameters (from 10 µm to 5 mm) (note the log scale on Y axis). Considerable variability is evident within both the vascularised and avascular areas within the tumors, with significantly more avascular areas being present in tumors, in contrast to the well-vascularized kidneys. Data indicate averages ± s.e.m. (N = 3–6 tumors per cell line). Asterisks indicate: * p<0.05, ** p<0.01, *** p<0.001.</p