Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.

Performance assessment of the single photon emission microscope: high spatial resolution SPECT imaging of small animal organs

The single photon emission microscope (SPEM) is an instrument developed to obtain high spatial resolution single photon emission computed tomography (SPECT) images of small structures inside the mouse brain. SPEM consists of two independent imaging devices, which combine a multipinhole collimator, a high-resolution, thallium-doped cesium iodide [CsI(Tl)] columnar scintillator, a demagnifying/intensifier tube, and an electron-multiplying charge-coupling device (CCD). Collimators have 300- and 450-µm diameter pinholes on tungsten slabs, in hexagonal arrays of 19 and 7 holes. Projection data are acquired in a photon-counting strategy, where CCD frames are stored at 50 frames per second, with a radius of rotation of 35 mm and magnification factor of one. The image reconstruction software tool is based on the maximum likelihood algorithm. Our aim was to evaluate the spatial resolution and sensitivity attainable with the seven-pinhole imaging device, together with the linearity for quantification on the tomographic images, and to test the instrument in obtaining tomographic images of different mouse organs. A spatial resolution better than 500 µm and a sensitivity of 21.6 counts·s-1·MBq-1 were reached, as well as a correlation coefficient between activity and intensity better than 0.99, when imaging 99mTc sources. Images of the thyroid, heart, lungs, and bones of mice were registered using 99mTc-labeled radiopharmaceuticals in times appropriate for routine preclinical experimentation of <1 h per projection data set. Detailed experimental protocols and images of the aforementioned organs are shown. We plan to extend the instrument's field of view to fix larger animals and to combine data from both detectors to reduce the acquisition time or applied activity.

Stochastic simulation to improve land-cover estimates derived from coarse spatial resolution satellite imagery = La simulation stochastique pour améliorer les estimations de la couverture des sols à partir d'images satellitales à résolution spatiale grossière

Thèse diffusée initialement dans le cadre d'un projet pilote des Presses de l'Université de Montréal/Centre d'édition numérique UdeM (1997-2008) avec l'autorisation de l'auteur.

The benefits of a compute cluster approach to high spatial resolution biodiversity richness modelling: projecting the impact of climate change on Mediterranean flora

High spatial resolution environmental data gives us a better understanding of the environmental factors affecting plant distributions at fine spatial scales. However, large environmental datasets dramatically increase compute times and output species model size stimulating the need for an alternative computing solution. Cluster computing offers such a solution, by allowing both multiple plant species Environmental Niche Models (ENMs) and individual tiles of high spatial resolution models to be computed concurrently on the same compute cluster. We apply our methodology to a case study of 4,209 species of Mediterranean flora (around 17% of species believed present in the biome). We demonstrate a 16 times speed-up of ENM computation time when 16 CPUs were used on the compute cluster. Our custom Java ‘Merge’ and ‘Downsize’ programs reduce ENM output files sizes by 94%. The median 0.98 test AUC score of species ENMs is aided by various species occurrence data filtering techniques. Finally, by calculating the percentage change of individual grid cell values, we map the projected percentages of plant species vulnerable to climate change in the Mediterranean region between 1950–2000 and 2020.

Effects of spatial resolution in the simulation of daily and subdaily precipitation in the southwestern US

We evaluate the effects of spatial resolution on the ability of a regional climate model to reproduce observed extreme precipitation for a region in the Southwestern United States. A total of 73 National Climate Data Center observational sites spread throughout Arizona and New Mexico are compared with regional climate simulations at the spatial resolutions of 50 km and 10 km for a 31 year period from 1980 to 2010. We analyze mean, 3-hourly and 24-hourly extreme precipitation events using WRF regional model simulations driven by NCEP-2 reanalysis. The mean climatological spatial structure of precipitation in the Southwest is well represented by the 10 km resolution but missing in the coarse (50 km resolution) simulation. However, the fine grid has a larger positive bias in mean summer precipitation than the coarse-resolution grid. The large overestimation in the simulation is in part due to scale-dependent deficiencies in the Kain-Fritsch convective parameterization scheme that generate excessive precipitation and induce a slow eastward propagation of the moist convective summer systems in the high-resolution simulation. Despite this overestimation in the mean, the 10 km simulation captures individual extreme summer precipitation events better than the 50 km simulation. In winter, however, the two simulations appear to perform equally in simulating extremes.

Sunlit fractions on urban facets: impact of spatial resolution and approach

The extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computational demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roof and roads over central London. Results indicate that the sunlit roads areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are found for roofs during mornings and evenings. Indications that sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.

MODIS aerosol optical depth Retrievals with high spatial resolution over an urban area using the critical reflectance

[1] The retrieval of aerosol optical depth (Ta) over land by satellite remote sensing is still a challenge when a high spatial resolution is required. This study presents a tool that uses satellite measurements to dynamically identify the aerosol optical model that best represents the optical properties of the aerosol present in the atmosphere. We use aerosol critical reflectance to identify the single scattering albedo of the aerosol layer. Two case studies show that the Sao Paulo region can have different aerosol properties and demonstrates how the dynamic methodology works to identify those differences to obtain a better T a retrieval. The methodology assigned the high single scattering albedo aerosol model (pi o( lambda = 0.55) = 0.90) to the case where the aerosol source was dominated by biomass burning and the lower pi(o) model (pi(o) (lambda = 0.55) = 0.85) to the case where the local urban aerosol had the dominant influence on the region, as expected. The dynamic methodology was applied using cloud-free data from 2002 to 2005 in order to retrieve Ta with Moderate Resolution Imaging Spectroradiometer ( MODIS). These results were compared with collocated data measured by AERONET in Sao Paulo. The comparison shows better results when the dynamic methodology using two aerosol optical models is applied (slope 1.06 +/- 0.08 offset 0.01 +/- 0.02 r(2) 0.6) than when a single and fixed aerosol model is used (slope 1.48 +/- 0.11 and offset - 0.03 +/- 0.03 r(2) 0.6). In conclusion the dynamical methodology is shown to work well with two aerosol models. Further studies are necessary to evaluate the methodology in other regions and under different conditions.

Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Determining spatial resolution in spatial load forecasting using a grid-based model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Preoperative mapping of arterial spinal supply using 3.0-T MR angiography with an intravasal contrast medium and high-spatial-resolution steady-state

Preoperative mapping of the arterial spinal supply prior to thoracoabdominal aortic aneurysm repair is highly relevant because of high risk for postoperative ischemic spinal cord injuries such as paraparesis or paraplegia.