novel alignment-based method for enhancing micropet/ct imaging and quantitation of early-stage microcalcifications

Longitudinal Quantification of Cardiovascular Calcification Using PET/CT Imaging

Cardiovascular disease is a leading global cause of morbidity and mortality, demanding rigorous exploration to uncover its mechanisms and to devise effective preventive and therapeutic strategies. Coronary artery calcification (CAC) is widely acknowledged by the experts in the field as a predictive factor for cardiovascular disease, significantly elevating the risk of cardiovascular mortality1,2,3,4,5. Microscopic calcifications are considered the earliest stages of calcific atherosclerosis, and the term &#34;microcalcifications&#34; has been used to refer to calcium deposits between 0.5 to 50 &#181;m6,7,8,9&#160;in diameter. These small calcifications are believed to coalesce to form larger calcium deposits, fueling the progression of calcific plaque6,7.
Positron emission tomography (PET) and computed tomography (CT) serve as valuable research tools, frequently employed for the non-invasive assessment of cardiovascular calcification in vivo5,10,11,12,13,14,15,16,17,18,19. These imaging modalities prove particularly advantageous for tracking vascular calcification progression in longitudinal studies involving small research animals11,12,13,19. MicroCT imaging has demonstrated effectiveness in providing anatomical images of relatively large calcium deposits11,12,13,19,20. However, its utility for imaging small calcium deposits in living animals is constrained by its spatial resolution of ~100 &#181;m8,14, making it challenging to investigate calcification during its initial phases.
A notable advancement is the adoption of combined microPET/microCT imaging with the PET tracer, fluoride-18-labeled sodium fluoride (18F-NaF), as the standard method for the detection of calcification based on its binding to the mineral surface area. This approach uses radiolabeled 18F-NaF, shown to identify the calcium mineral surface10,13 as the fluoride ions bind covalently to calcium hydroxyapatite, replacing hydroxyl groups to form fluoroapatite21. Consistent with the slower exchange rate relative to the radioactive decay of the 18F (half-life ~110 min) and to the clearance of the tracer through kidneys22, Irkle and colleagues13 found that 18F-NaF binding to calcified carotid specimens was limited to the surface at the time of detection. Thus, tracer uptake should relate directly with mineral surface area, which is greater when a given amount of mineral occurs in multiple small foci or in porous form than when present in few, large, solid deposits. By accentuating the earliest stages of mineralization with high sensitivity, 18F-NaF PET imaging may provide valuable insights into the early stages of disease, making it particularly useful in studying preventive as well as therapeutic strategies13,14,15.
Even with recent advancements in the combined microPET/microCT imaging of vascular calcification, there are opportunities for improving the accuracy of image analysis in longitudinal, cardiovascular calcification studies. Conventional approaches use labor-intensive, manual delineation of regions of interest (ROI) around each visible calcified region in every mouse at each individual time point throughout the longitudinal study. This method reduces precision, particularly in the early disease stages when the sizes of calcium deposits approach the scanners&#39; detection limits, potentially making invisible some areas with minuscule deposits arranged in low density.
In the realm of imaging, alignment generally refers to the spatial alignment of a series of images. Introducing alignment as a novel solution to the existing challenges, our proposed method allows investigators to use a consistent location for following the progression of calcification in serial images from individual subjects throughout a longitudinal study. Given that tissue calcification is known to arise from nanosized matrix vesicles (50-150 nm), which coalesce to form microscopic, then macroscopic hydroxyapatite mineral23, one may retrospectively identify where microcalcifications would have been located in early images before they are discernable.
Following that same location over time, made possible by image alignment, is the basis for this method. It obviates the need to identify the earliest calcification stages directly, as the ROI&#160;is assigned based on the latest stages when mineralization is readily identified. In this protocol, we present an improved, streamlined data analysis method that incorporates the alignment of a time series of images as a vital step, enhancing accurate quantitation of calcium deposition in longitudinal, combined, microPET/microCT imaging studies (Figure 1). While we use PET/CT data analysis as an example, this method can be applied to the analyses of other longitudinal imaging data, including single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), and optical imaging24.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66805/66805fig01.jpg" /> 
Figure 1: Protocol overview flowchart. Flowchart summarizing the novel protocol for quantifying cardiovascular calcification. General steps include longitudinal imaging, alignment of images acquired at different time points, and segmentation and quantification of the calcified region. <a href="https://www.jove.com/files/ftp_upload/66805/66805fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Author Spotlight: Enhanced Quantification of Cardiovascular Calcification Progression for Longitudinal Micro PET/CT Studies in Small Research Animals

Novel Quantification Protocol for Cardiovascular Calcification Progression Using Longitudinal MicroPET/MicroCT Images

This novel protocol entails the quantification of cardiovascular calcification from serial micro PET CT images in small research animals. Positron emission tomography and computed tomography serve as valuable research tools. They're frequently employed for the non-invasive assessment of cardiovascular calcification in vivo.These imaging modalities are particularly advantageous for tracking vascular calcification in longitudinal studies involving small research animals. Conventional approaches for quantifying calcification use labor intensive manual delineation of regions of interest around visible calcified regions in every mouse at each time point throughout the longitudinal study. These methods reduce precision, particularly in the early disease stages when the sizes of calcification approach the scanners detection limits.Our novel protocol presents a refined data analysis approach, integrating image alignment and ROI consistency to reduce the variability of data analysis between sequential images, thereby improving the validity of calcification assessment in longitudinal PET CT studies.

Novel Alignment-Based Method for Enhancing MicroPET/CT Imaging and Quantitation of Early-Stage Microcalcifications

To begin, perform MicroPET and CT imaging on female apolipoprotein E-deficient mice. After importing DICOM files in DICOM viewer software, turn off all PET images and turn on the base CT image. Click on one of the 2D views.Under the window leveling box, locate the opacity mapping dropdown and slide the opacity scale to the center. Then turn on the overlay CT image and repeat the opacity adjustment. To change the filter of the overlay CT image to distinguish it from the base CT image, go to the window leveling dropdown in the main tab and find the lookup table or LUT.Scroll through the LUT dropdown and select the red filter. In the data properties and settings dropdown, select the overlay image and click once to select one of the 2D views. Then locate the translate or rotate dropdown under the main tab and click the displace icon.Now click and drag the translate box in the lower left corner and rotate the pivot point in the center of the 2D view to move the overlay image roughly into alignment with the base image. Fine-tune the alignment by further translating and rotating the overlay CT image using the chest structures such as the thoracic cage, upper spine, and sternum as reference. Next, turn on the overlay CT image and its corresponding PET image by clicking the eye icon to the left of each image name.Change the opacity of both the PET and CT images to 50%Then use translate or rotate tools in the 2D views to align the PET image with its corresponding CT image based on the bone structure in the CT image and fluoride-18 labeled sodium fluoride bone surface in the PET image. To identify cardiovascular calcification, select the time point with the largest predicted calcified regions in the longitudinal study. Choose the image corresponding to this time point as the reference image.Then turn on the reference CT image by clicking the eye icon to the left of the image. Select the track tool under the manipulate dropdown and move the axis center around the cardiac region. Now zoom in to locate calcified regions superimposed over the cardiac silhouette between the thoracic cage, sternum, and spine.Then move the track axis to hover over the calcified region, ensuring visibility in all 2D views. Turn on the corresponding PET image to validate the presence of calcification. Turn off the PET reference image.Then make sure the CT reference image is turned on and selected. Find the shapes dropdown and choose the sphere shape. After that, navigate through the 2D views to carefully position the sphere.In the data properties and settings dropdown, right-click on the sphere name and choose add to region of interest. Then select new region of interest. Now assign an appropriate name to the newly created region of interest.Under geometry, select the CT image for which the region of interest is to be generated. To turn on the region of interest, click the eye icon to the left of the region of interest name and observe the colored region of interest corresponding to the size of the previously drawn sphere. Then find the segment tab to the left of the display screen next to the main tab.Select the reference region of interest in the data properties and settings dropdown. Locate the range dropdown under the segment tab and check the defined range option. Use the selected range box to change the defined range.Ensure the defined range encapsulates all noncalcified pixels with Hounsfield unit values below the calcium threshold. Once the selected range is configured, click remove to eliminate all pixels beneath the specified threshold from the sphere region of interest. Select the region of interest to be quantified from the data properties and settings dropdown.Find the statistical properties dropdown on the right side located below the basic properties dropdown. Then locate the dataset table under statistical properties. Using the dropdown menu on the right, choose the appropriate imaging dataset corresponding to the region of interest being quantified.Click refresh to acquire the quantified values of the selected calcified region. Use the mean values displayed for quantification. Locate the volume calculation at the top of the statistical properties box and use this volume for quantification.Calculate the volumetric calcium content by multiplying the mean region of interest value by the volume of the region of interest. To quantify the PET image, select the PET dataset corresponding to the region of interest. Convert the result to Becquerel's per cubic millimeter by dividing the mean region of interest value by the volume of the region of interest.The volumetric calcium content in the mouse increased from 15 months to 18 months. The fluoride-18 labeled sodium fluoride PET activity, which measures the surface area of the calcified region, decreased from 15 months to 18 months.

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25 visualizações. Para começar, realize imagens MicroPET e TC em camundongos fêmeas com deficiência de apolipoproteína E. Depois de importar arquivos DICOM no software visualizador DICOM, desligue todas as imagens PET e ative a imagem de TC de base. Clique em uma das visualizações 2D.Na caixa de nivelamento da janela, localize o menu suspenso de mapeamento de opacidade e deslize a escala de opacidade para o centro. Em seguida, ligue a imagem de TC de sobreposiçã...