Rat Brain Imaging Research Articles

PET imaging in rat brain shows opposite effects of acute and chronic alcohol exposure on phosphodiesterase-4B, an indirect biomarker of cAMP activity.

The cyclic adenosine monophosphate (cAMP) cascade is thought to play an important role in regulating alcohol-dependent behaviors, with potentially opposite effects following acute versus chronic administration. Phosphodiesterase 4 (PDE4) is the primary brain enzyme that metabolizes cAMP, thereby terminating its signal. Radioligand binding to PDE4 serves as an indirect biomarker of cAMP activity, as cAMP-protein kinase A (PKA)-mediated phosphorylation of PDE4 increases its affinity for radioligand binding ~10-fold. Of the four PDE4 subtypes, PDE4B polymorphisms are known to be strongly associated with alcohol and substance use disorders. This study imaged rats with the PDE4B-preferring positron emission tomography (PET) radioligand [18F]PF-06445974 following acute and chronic ethanol administration, aiming to explore the potential of PDE4B PET imaging for future human studies. Compared to the control group treated with saline, acute alcohol administration (i.p. ethanol 0.5 g/kg) significantly increased whole brain uptake of [18F]PF-06445974 as early as 30 minutes post-exposure. This effect persisted at 2 hours, peaked at 4 hours, and diminished at 6 hours and 24 hours post-exposure. In contrast, in a rat model of alcohol dependence, [18F]PF-06445974 brain uptake was significantly reduced at 5 hours post-exposure and was normalized by 3 days. This reduction may reflect long-term adaptation to repeated alcohol-induced activation of cAMP signaling with chronic exposure. Taken together, the results suggest that PET imaging of PDE4B in individuals with alcohol use disorder (AUD) should be considered in conjunction with ongoing trials of PDE4 inhibitors to treat alcohol withdrawal and reduce alcohol consumption.

Hadamard Coded Multiplane Wave based Ultrafast Doppler for Rat Brain Imaging

Abstract This study explores the application of Hadamard multiplane-wave coding in ultrafast power and color Doppler imaging for enhanced visualization of rat brain vasculature. By implementing an 8-order Hadamard matrix, an approximate 10 dB improvement in signal-to-noise ratio was significantly achieved, particularly in deep brain regions and the hippocampus. The enhanced imaging technique, compared to classical plane wave coherent compounding, demonstrates its potential for applications requiring deep penetration and high sensitivity to small blood flow without compromising the ultrafast frame rate.

Mechanically Adjustable 4-Channel RF Transceiver Coil Array for Rat Brain Imaging in a Whole-Body 7 T MR Scanner.

Investigations of human brain disorders are frequently conducted in rodent models using magnetic resonance imaging. Due to the small specimen size and the increase in signal-to-noise ratio with the static magnetic field strength, dedicated small-bore animal scanners can be used to acquire high-resolution data. Ultra-high-field (≥7 T) whole-body human scanners are increasingly available, and they can also be used for animal investigations. Dedicated sensors, in this case, radiofrequency coils, are required to achieve sufficient sensitivity for the high spatial resolution needed for imaging small anatomical structures. In this work, a four-channel transceiver coil array for rat brain imaging at 7 T is presented, which can be adjusted for use on a wide range of differently sized rats, from infants to large adults. Three suitable array designs (with two to four elements covering the whole rat brain) were compared using full-wave 3D electromagnetic simulation. An optimized static B1+ shim was derived to maximize B1+ in the rat brain for both small and big rats. The design, together with a 3D-printed adjustable coil housing, was tested and validated in ex vivo rat bench and MRI measurements.

Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy

Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated microbubbles, resulting in prolonged imaging time to obtain detailed microvascular maps. Here, we introduce LOcalization with Context Awareness (LOCA)-ULM, a deep learning-based microbubble simulation and localization pipeline designed to enhance localization performance in high microbubble concentrations. In silico, LOCA-ULM enhanced microbubble detection accuracy to 97.8% and reduced the missing rate to 23.8%, outperforming conventional and deep learning-based localization methods up to 17.4% in accuracy and 37.6% in missing rate reduction. In in vivo rat brain imaging, LOCA-ULM revealed dense cerebrovascular networks and spatially adjacent microvessels undetected by conventional ULM. We further demonstrate the superior localization performance of LOCA-ULM in functional ULM (fULM) where LOCA-ULM significantly increased the functional imaging sensitivity of fULM to hemodynamic responses invoked by whisker stimulations in the rat brain.

A novel restrainer device for acquistion of brain images in awake rats

Functional neuroimaging methods like fMRI and PET are vital in neuroscience research, but require that subjects remain still throughout the scan. In animal research, anesthetic agents are typically applied to facilitate the acquisition of high-quality data with minimal motion artifact. However, anesthesia can have profound effects on brain metabolism, selectively altering dynamic neural networks and confounding the acquired data. To overcome the challenge, we have developed a novel head fixation device designed to support awake rat brain imaging. A validation experiment demonstrated that the device effectively minimizes animal motion throughout the scan, with mean absolute displacement and mean relative displacement of 0.0256 (SD: 0.001) and 0.009 (SD: 0.002), across eight evaluated subjects throughout fMRI image acquisition (total scanning time per subject: 31 min, 12 s). Furthermore, the awake scans did not induce discernable stress to the animals, with stable physiological parameters throughout the scan (Mean HR: 344, Mean RR: 56, Mean SpO2: 94 %) and unaltered serum corticosterone levels (p = 0.159). In conclusion, the device presented in this paper offers an effective and safe method of acquiring functional brain images in rats, allowing researchers to minimize the confounding effects of anesthetic use.

Automatic brain extraction for rat magnetic resonance imaging data using U2-Net

Objective. Skull stripping is a key step in the pre-processing of rodent brain magnetic resonance images (MRI). This study aimed to develop a new skull stripping method via U2-Net, a neural network model based on deep learning method, for rat brain MRI. Approach. In this study, 599 rats were enrolled and U2-Net was applied to segment MRI images of rat brain. The intercranial tissue of each rat was manually labeled. 476 rats (approximate 80%) were used for training set while 123 rats (approximate 20%) were used to test the performance of the trained U2-Net model. For evaluation, the segmentation result by the U2-Net model is compared with the manual label, and traditional segment methods. Quantitative evaluation, including Dice coefficient, Jaccard coefficient, Sensitivity, Specificity, Pixel accuracy, Hausdorff coefficient, True positive rate, False positive rate and the volumes of whole brain, were calculated to compare the segmentation results among different models. Main results. The U2-Net model was performed better than the software of RATS and BrainSuite, in which the quantitative values of training U2-Net model were 0.9907 ± 0.0016 (Dice coefficient), 0.9816 ± 0.0032 (Jaccard coefficient), 0.9912 ± 0.0020 (Sensitivity), 0.9989 ± 0.0002 (Specificity), 0.9982 ± 0.0003 (Pixel accuracy), 5.2390 ± 2.5334 (Hausdorff coefficient), 0.9902 ± 0.0025 (True positive rate), 0.0009 ± 0.0002(False positive rate) respectively. Significance. This study provides a new method that achieves reliable performance in rat brain skull stripping of MRI images, which could contribute to the processing of rat brain MRI.

Stretchable receive coil for 7T small animal MRI

Receive coils used in small animal MRI are rigid, inflexible surface loops that do not conform to the anatomy being imaged. The recent trend toward design of stretchable coils that are tailored to fit any anatomical curvature has been focused on human imaging. This work demonstrates the application of stretchable coils for small animal imaging at 7T. A stretchable coil measuring 3.5 × 3.5 cm was developed for acquisition of rat brain and spine images. The SNR maps of the stretchable coil were compared with those of a traditional flexible PCB coil and a commercial surface coil. Stretch and conformance testing of the coil was performed. Ex vivo images of rat brain and spine from the stretchable a coil was acquired using T1 FLASH and T2 Turbo RARE sequences. The axial phantom SNR maps showed that the stretchable coil provided 48.5% and 42.8% higher SNR than the commercial coil for T1-w and T2-w images within the defined ROI. A 33% increase in average penetration depth was observed within the ROI using the stretchable coil when compared to the commercial coil. The ex-vivo rat brain and spine images showed distinguishable anatomical details. Stretching the coil reduced the resonant frequency with reduction in SNR, while the conformance to varying sample volumes increased the resonant frequency with decreased SNR. This study also features an open-source plug-and-play system with preamplifiers that can be used to interface surface coils with the 7T Bruker scanner.

Perivascular network segmentations derived from high-field MRI and their implications for perivascular and parenchymal mass transport in the rat brain

A custom segmentation workflow was applied to ex vivo high-field MR images of rat brains acquired following in vivo intraventricular contrast agent infusion to generate maps of the perivascular spaces (PVS). The resulting perivascular network segmentations enabled analysis of perivascular connections to the ventricles, parenchymal solute clearance, and dispersive solute transport within PVS. Numerous perivascular connections between the brain surface and the ventricles suggest the ventricles integrate into a PVS-mediated clearance system and raise the possibility of cerebrospinal fluid (CSF) return from the subarachnoid space to the ventricles via PVS. Assuming rapid solute exchange between the PVS and CSF spaces primarily by advection, the extensive perivascular network decreased the mean clearance distance from parenchyma to the nearest CSF compartment resulting in an over 21-fold reduction in the estimated diffusive clearance time scale, irrespective of solute diffusivity. This corresponds to an estimated diffusive clearance time scale under 10 min for amyloid-beta which suggests that the widespread distribution of PVS may render diffusion an effective parenchymal clearance mechanism. Additional analysis of oscillatory solute dispersion within PVS indicates that advection rather than dispersion is likely the primary transport mechanism for dissolved compounds greater than 66 kDa in the long (> 2 mm) perivascular segments identified here, although dispersion may be significant for smaller compounds in shorter perivascular segments.

A Semi-Automatic Method for the Quantification of Astrocyte Number and Branching in Bulk Immunohistochemistry Images.

Immunohistochemical staining of cell and molecular targets in brain samples is a powerful tool that can provide valuable information on neurological mechanisms. However, post-processing of photomicrographs acquired after 3,3'-Diaminobenzidine (DAB) staining is particularly challenging due to the complexity associated with the size, samples number, analyzed targets, image quality, and even the subjectivity inherent to the analysis by different users. Conventionally, this analysis relies on the manual quantification of distinct parameters (e.g., the number and size of cells and the number and length of cell branching) in a large set of images. These represent extremely time-consuming and complex tasks, defaulting the processing of high amounts of information. Here we describe an improved semi-automatic method to quantify glial fibrillary acidic protein (GFAP)-labelled astrocytes in immunohistochemistry images of rat brains, at magnifications as low as 20×. This method is a straightforward adaptation of the Young & Morrison method, using ImageJ's plugin Skeletonize, coupled with intuitive data processing in datasheet-based software. It allows swifter and more efficient post-processing of brain tissue samples, regarding astrocyte size and number quantification, the total area occupied, as well as astrocyte branching and branch length (indicators of astrocyte activation), thus contributing to better understand the possible inflammatory response developed by astrocytes.

Visible CCD Camera-Guided Photoacoustic Imaging System for Precise Navigation during Functional Rat Brain Imaging

In photoacoustic (PA) imaging, tissue absorbs specific wavelengths of light. The absorbed energy results in thermal expansion that generates ultrasound waves that are reconstructed into images. Existing commercial PA imaging systems for preclinical brain imaging are limited by imprecise positioning capabilities and inflexible user interfaces. We introduce a new visible charge-coupled device (CCD) camera-guided photoacoustic imaging (ViCPAI) system that integrates an ultrasound (US) transducer and a data acquisition platform with a CCD camera for positioning. The CCD camera accurately positions the US probe at the measurement location. The programmable MATLAB-based platform has an intuitive user interface. In vitro carbon fiber and in vivo animal experiments were performed to investigate the precise positioning and imaging capabilities of the ViCPAI system. We demonstrated real-time capturing of bilateral cerebral hemodynamic changes during (1) forelimb electrical stimulation under normal conditions, (2) forelimb stimulation after right brain focal photothrombotic ischemia (PTI) stroke, and (3) progression of KCl-induced cortical spreading depression (CSD). The ViCPAI system accurately located target areas and achieved reproducible positioning, which is crucial in animal and clinical experiments. In animal experiments, the ViCPAI system was used to investigate bilateral cerebral cortex responses to left forelimb electrical stimulation before and after stroke, showing that the CBV and SO2 in the right primary somatosensory cortex of the forelimb (S1FL) region were significantly changed by left forelimb electrical stimulation before stroke. No CBV or SO2 changes were observed in the bilateral cortex in the S1FL area in response to left forelimb electrical stimulation after stroke. While monitoring CSD progression, the ViCPAI system accurately locates the S1FL area and returns to the same position after the probe moves, demonstrating reproducible positioning and reducing positioning errors. The ViCPAI system utilizes the real-time precise positioning capability of CCD cameras to overcome various challenges in preclinical and clinical studies.

Community Newsletter: Polyneuro risk score; rat brain imaging protocol

Community Newsletter: Polyneuro risk score; rat brain imaging protocol

A 5-channel local B0 shimming coil combined with a 3-channel RF receiver coil for rat brain imaging at 3T.

We aimed to improve B0 magnetic field homogeneity and minimize the interference between RF coils and local B0 shimming coils with few channel numbers. To design and construct the prototype for B0 shimming of the rat brain, we first evaluated the interferences of single shimming loops on RF receiver loops. Then, B0 shimming of the whole rat brain was implemented using an optimization procedure. The positions and currents of the local shimming coils with channel numbers from 3 to 6 were optimized to improve shimming performance. Based on the simulation results, a 5-channel local shimming coil, combined with a 3-channel RF receiver coil, was constructed and evaluated by animal experiments. There was marginal SNR loss within 5% after integrating the local shimming coil into the RF receiver coil. With respect to the Siemens standard shims up to second order, the B0 inhomogeneity in one whole rat brain was reduced from 39.6 Hz to 24.7Hz by using the local shimming coil. A large portion of the EPI distortions was recovered after using the 5-channel local shimming coil. The temporal SNR using the local shimming coil was higher than that using the Siemens standard shims up to second order, with an improvement of more than 24%. The local shimming coil can improve B0 magnetic field homogeneity despite minor effects on the RF coil and can benefit a variety of applications that are sensitive to B0 inhomogeneity. Nevertheless, EPI for rat brain is still very challenging.

Automatic method for individual parcellation of manganese-enhanced magnetic resonance imaging of rat brain.

AimsTo construct an automatic method for individual parcellation of manganese-enhanced magnetic resonance imaging (MEMRI) of rat brain with high accuracy, which could preserve the inherent voxel intensity and Regions of interest (ROI) morphological characteristics simultaneously.Methods and resultsThe transformation relationship from standardized space to individual space was obtained by firstly normalizing individual image to the Paxinos space and then inversely transformed. On the other hand, all the regions defined in the atlas image were separated and resaved as binary mask images. Then, transforming the mask images into individual space via the inverse transformations and reslicing using the 4th B-spline interpolation algorithm. The boundary of these transformed regions was further refined by image erosion and expansion operator, and finally combined together to generate the individual parcellations. Moreover, two groups of MEMRI images were used for evaluation. We found that the individual parcellations were satisfied, and the inherent image intensity was preserved. The statistical significance of case-control comparisons was further optimized.ConclusionsWe have constructed a new automatic method for individual parcellation of rat brain MEMRI images, which could preserve the inherent voxel intensity and further be beneficial in case-control statistical analyses. This method could also be extended to other imaging modalities, even other experiments species. It would facilitate the accuracy and significance of ROI-based imaging analyses.

Magnetic Resonance Imaging of Rat Brain in Assessment of the Neuroprotective Properties of Histochrome in Experimental Arterial Hypertension.

The neuroprotective effects of the course therapy with Histochrome in Wistar rats with modeled arterial hypertension were studied by using magnetic resonance imaging (MRI) in diffusion-weighted mode. The behavioral status of the animals was assessed using the open-field test. MRI analysis revealed more pronounced increase in the signaling characteristics of the brain tissue in hypertensive rats in comparison with the control (intact) animals. It was caused by excessive accumulation of fluid in the intra- and extracellular spaces of the brain tissue, which is associated with hypervolemia induced by the multifactorial cardiovasorenal model of hypertension. After a course of Histochrome injections to hypertensive rats, the cerebral microcirculation disorders were leveled, while the behavioral status was characterized by shortened latency of the visit to the center of the open field by 20% and improvement of cognitive activity (by 1.6 times) and the exploratory component (by 30%).

Multimodal Mass Spectrometry Imaging of Rat Brain Using IR-MALDESI and NanoPOTS-LC-MS/MS.

Multimodal mass spectrometry imaging (MSI) is a critical technique used for deeply investigating biological systems by combining multiple MSI platforms in order to gain the maximum molecular information about a sample that would otherwise be limited by a single analytical technique. The aim of this work was to create a multimodal MSI approach that measures metabolomic and proteomic data from a single biological organ by combining infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) for metabolomic MSI and nanodroplet processing in one pot for trace samples (nanoPOTS) LC-MS/MS for spatially resolved proteome profiling. Adjacent tissue sections of rat brain were analyzed by each platform, and each data set was individually analyzed using previously optimized workflows. IR-MALDESI data sets were annotated by accurate mass and spectral accuracy using HMDB, METLIN, and LipidMaps databases, while nanoPOTS-LC-MS/MS data sets were searched against the rat proteome using the Sequest HT algorithm and filtered with a 1% FDR. The combined data revealed complementary molecular profiles distinguishing the corpus callosum against other sampled regions of the brain. A multiomic pathway integration showed a strong correlation between the two data sets when comparing average abundances of metabolites and corresponding enzymes in each brain region. This work demonstrates the first steps in the creation of a multimodal MSI technique that combines two highly sensitive and complementary imaging platforms. Raw data files are available in METASPACE (https://metaspace2020.eu/project/pace-2021) and MassIVE (identifier: MSV000088211).

Identification of Alzheimer associated differentially expressed gene through microarray data and transfer learning-based image analysis

Major factors contribute to mental stress and enhance the progression of late-onset Alzheimer’s disease (AD). The factors that lead to neurodegeneration, such as tau protein hyperphosphorylation and increased amyloid-beta production, can be mimicked in animal stress models. The present study identifies differentially expressed genes (DEGs) data and its corresponding predictive image analysis in rat models. The gene expression profile of GSE72062, GSE85162, GSE143951 and GSE85238 was downloaded from NCBI, GEO archive to analyse DEGs. Functional enrichment and pathway relationship networks, gene signal, protein interaction and micro-RNA interaction DEGs networks were constructed and investigated. The image analysis of histopathological slides of rat brain images corresponding to AD microarray-based DEGs profile was undertaken using the convolution neural networks (ConvNets) model. Enrichment of network in terms of GO concluded with 10 DEGs, namely ARHGAP32, GNA11, NR5A1, GNAT3, FOSL1, HELZ2, NMUR2, BDKRB1, RPL3L and RPL39L as potential gene targets to control neurodegeneration and progression of sporadic AD. The image analysis of AD microarray-based DEGs profile builds a successful predictive model of 89% and 61% training and test accuracy with a minimum of 2.480% loss using transfer learning, VGG16 model. Interestingly, the ARHGAP32 gene, a Rho GTPase activating class, was identified to have a functional relationship with two significant genes BCL2 and MMP9, that are well explored in AD. The current investigation upgrades the traditional pre-clinical AD research using microarray data analysis and ConvNets. The model successfully predicts DEG from histopathology slides of rat brain samples, paving the way for image analysis to determine the underlying molecular makeup of the test samples.

Segmentation of Rat Brains and Cerebral Hemispheres in Triphenyltetrazolium Chloride-Stained Images after Stroke.

Ischemic stroke is one of the leading causes of death among the aged population in the world. Experimental stroke models with rodents play a fundamental role in the investigation of the mechanism and impairment of cerebral ischemia. For its celerity and veracity, the 2,3,5-triphenyltetrazolium chloride (TTC) staining of rat brains has been extensively adopted to visualize the infarction, which is subsequently photographed for further processing. Two important tasks are to segment the brain regions and to compute the midline that separates the brain. This paper investigates automatic brain extraction and hemisphere segmentation algorithms in camera-based TTC-stained rat images. For rat brain extraction, a saliency region detection scheme on a superpixel image is exploited to extract the brain regions from the raw complicated image. Subsequently, the initial brain slices are refined using a parametric deformable model associated with color image transformation. For rat hemisphere segmentation, open curve evolution guided by the gradient vector flow in a medial subimage is developed to compute the midline. A wide variety of TTC-stained rat brain images captured by a smartphone were produced and utilized to evaluate the proposed segmentation frameworks. Experimental results on the segmentation of rat brains and cerebral hemispheres indicated that the developed schemes achieved high accuracy with average Dice scores of 92.33% and 97.15%, respectively. The established segmentation algorithms are believed to be potential and beneficial to facilitate experimental stroke study with TTC-stained rat brain images.

Preliminary Evaluations of [11C]Verubulin: Implications for Microtubule Imaging With PET.

[11C]Verubulin (a.k.a.[11C]MCP-6827), [11C]HD-800 and [11C]colchicine have been developed for imaging microtubules (MTs) with positron emission tomography (PET). The objective of this work was to conduct an in vivo comparison of [11C]verubulin for MT imaging in mouse and rat brain, as well as an in vitro study with this radiotracer in rodent and human Alzheimer’s Disease tissue. Our preliminary PET imaging studies of [11C]verubulin in rodents revealed contradictory results between mouse and rat brain uptake under pretreatment conditions. In vitro autoradiography with [11C]verubulin showed an unexpected higher uptake in AD patient tissue compared with healthy controls. We also conducted the first comparative in vivo PET imaging study with [11C]verubulin, [11C]HD-800 and [11C]colchicine in a non-human primate. [11C]Verubulin and [11C]HD-800 require pharmacokinetic modeling and quantification studies to understand the role of how these radiotracers bind to MTs before translation to human use.

White matter imaging of ethanol-fixed rat brain by phase-contrast X-ray computed tomography.

Phase-contrast X-ray computed tomography imaging (PCI) based on crystal X-ray interferometry can detect minute density differences within biological soft tissues without contrast agents. Ethanol fixation yields increased tissue-background density differences due to the dehydrating and delipidifying effects of ethanol. To obtain high image contrast of cerebral white matter structures in PCI, tissue fixation using ethanol and routinely used formalin have been examined. Ethanol-fixed (EF) (n = 4) and formalin-fixed (FF) (n = 4) rat brains were imaged by crystal X-ray interferometry-based PCI. Tissue staining/microscopy was also performed for histological comparison and myelin density evaluation. Three-dimensional white matter tract images were reconstructed. Superior image contrast was obtained in the images of EF brains (EF images) compared to those of formalin-fixed brains (FF images), particularly for white matter structures. Significant density differences between the white matter structures and hippocampus (P < 0.01)/thalamus (P < 0.001) were observed in the EF, but not FF, images. Ethanol fixation enhanced the image contrast of white matter tracts by approximately sixfold compared to formalin fixation, and close agreement (r2 = 0.97; P < 0.05) between the density values on the CT images and the myelin density values in histological images was observed for the EF brains. Three-dimensional reconstruction of the white matter tracts was possible from the EF images, but not FF images. Ethanol fixation resulted in marked contrast enhancement of cerebral white matter structures in PCI. Thus, high-resolution PCI using ethanol for tissue fixation could be valuable for experimental neurological studies and postmortem neuropathology evaluation.

Highly stable and bright AIE dots for NIR-II deciphering of living rats

Abstract The emerging second near-infrared (NIR-II) fluorescence imaging has shown great promise for in vivo imaging of small animals such as mice, yet the onward movement to large-size animals such as rats is still undeveloped. In this work, for the first time, we report comprehensive NIR-II deciphering of brain blood vasculature and main organs of living rats based on aggregation-induced emission (AIE) dots. The AIE dots possess simultaneously high brightness, excellent stability with various treatments, and good biocompatibility. Thanks to the long emission range and high brightness, in vivo NIR-II fluorescence microscopic imaging with the AIE dots beyond 1200 nm allows for visualizing rat brain vasculature with high spatial resolution (∼4 μm) and deep penetration (700 μm), representing the highest penetration depth and best resolution of rat brain imaging yet achieved in the field. The NIR-II AIE dots also enable the detection of tiny vascular blockage in real time at the early stage of cerebral thrombosis. Furthermore, in vivo non-invasive monitoring of rat’s gastrointestinal tract and bladder in a high-contrast manner helps to better understand the digestive system and excretory processes. This work will inspire new insights into the development of advanced NIR-II technique for large animal imaging, rendering great promise for real applications.