MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera

Small animal PET: a review of what we have done and where we are going

Small animal research is an essential tool in studying both pharmaceutical biodistributions and disease progression over time. Furthermore, through the rapid development of in vivo imaging technology over the last few decades, small animal imaging (also referred to as preclinical imaging) has become a mainstay for all fields of biologic research and a center point for most preclinical cancer research. Preclinical imaging modalities include optical, MRI and MRS, microCT, small animal PET, ultrasound, and photoacoustic, each with their individual strengths. The strong points of small animal PET are its translatability to the clinic; its quantitative imaging capabilities; its whole-body imaging ability to dynamically trace functional/biochemical processes; its ability to provide useful images with only nano- to pico‑ molar concentrations of administered compounds; and its ability to study animals serially over time. This review paper gives an overview of the development and evolution of small animal PET imaging. It provides an overview of detector designs; system configurations; multimodality PET imaging systems; image reconstruction and analysis tools; and an overview of research and commercially available small animal PET systems. It concludes with a look toward developing technologies/methodologies that will further enhance the impact of small animal PET imaging on medical research in the future.

Prediction of major torso organs in low-contrast micro-CT images of mice using a two-stage deeply supervised fully convolutional network

Delineation of major torso organs is a key step of mouse micro-CT image analysis. This task is challenging due to low soft tissue contrast and high image noise, therefore anatomical prior knowledge is needed for accurate prediction of organ regions. In this work, we develop a deeply supervised fully convolutional network which uses the organ anatomy prior learned from independently acquired contrast-enhanced micro-CT images to assist the segmentation of non-enhanced images. The network is designed with a two-stage workflow which firstly predicts the rough regions of multiple organs and then refines the accuracy of each organ in local regions. The network is trained and evaluated with 40 mouse micro-CT images. The volumetric prediction accuracy (Dice score) varies from 0.57 for the spleen to 0.95 for the heart. Compared to a conventional atlas registration method, our method dramatically improves the Dice of the abdominal organs by 18%-26%. Moreover, the incorporation of anatomical prior leads to more accurate results for small-sized low-contrast organs (e.g. the spleen and kidneys). We also find that the localized stage of the network has better accuracy than the global stage, indicating that localized single organ prediction is more accurate than global multiple organ prediction. With this work, the accuracy and efficiency of mouse micro-CT image analysis are greatly improved and the need for using contrast agent and high x-ray dose is potentially reduced.

Imaging of Mouse Brain Fixated in Ethanol in Micro-CT

Micro-CT imaging is a well-established morphological method for the visualization of animal models. We used ethanol fixation of the mouse brains to perform high-resolution micro-CT scans showing in great details brain grey and white matters. It was possible to identify more than 50 neuroanatomical structures on the 5 selected coronal sections. Among white matter structures, we identified fornix, medial lemniscus, crossed tectospinal pathway, mammillothalamic tract, and the sensory root of the trigeminal ganglion. Among grey matter structures, we identified basal nuclei, habenular complex, thalamic nuclei, amygdala, subparts of hippocampal formation, superior colliculi, Edinger-Westphal nucleus, and others. We suggest that micro-CT of the mouse brain could be used for neurohistological lesions evaluation as an alternative to classical neurohistology because it does not destroy brain tissue.

Estimation of thyroid volume from scintigraphy through 2D/3D registration of a statistical shape model

Accurate measurement of thyroid volume is important for thyroid disease diagnosis and therapy. In nuclear medicine, the thyroid volume is usually estimated from scintigraphy images using empirical equations. However, due to the lack of volumetric information from the scintigraphy image, the accuracy of equation-based estimation is imperfect. To solve this problem, this paper proposes a method which registers a 3D thyroid statistical shape model (SSM) to a single-view scintigraphy image to achieve more accurate volume estimation. The SSM was constructed based on a training set of segmented 3D CT images, and the thyroid shape variations between the training subjects were modelled using the point distribution model. For thyroid volume estimation, the SSM was projected into the scintigraphy image of the target patient, and then the projected model shape was nonrigidly registered with the patient's scintigraphy image. The resultant 2D deformation file was back-projected to 3D space to guide the deformation of the 3D SSM. This process was repeated iteratively until convergence, and the volume of the finally deformed SSM was considered as the estimation of the patient's thyroid volume. For validation, this method was evaluated based on a test set of 20 scintigraphy images, achieving an estimation error of  -2.10%  ±  5.20% which was much less than the error of the conventional equation-based method (35.76%  ±  15.20%) based on the same test set. The robustness of this method was further tested using a challenging case, i.e. a scintigraphy image with a large thyroid tumor. For this case, the volume estimation error was only 6.08%. Our method has significantly improved the accuracy of thyroid volume estimation from scintigraphy images, and it will enhance the value of scintigraphy imaging for thyroid disease diagnosis and radioiodine therapy.

Automated quantification of bioluminescence images

We developed a computer-aided analysis tool for quantitatively determining bioluminescent reporter distributions inside small animals. The core innovations are a body-fitting animal shuttle and a statistical mouse atlas, both of which are spatially aligned and scaled according to the animal’s weight, and hence provide data congruency across animals of varying size and pose. In conjunction with a multispectral bioluminescence tomography technique capitalizing on the spatial framework of the shuttle, the in vivo biodistribution of luminescent reporters can rapidly be calculated and, thus, enables operator-independent and computer-driven data analysis. We demonstrate its functionality by quantitatively monitoring a bacterial infection, where the bacterial organ burden was determined and validated with the established serial-plating method. In addition, the statistical mouse atlas was validated and compared to existing techniques providing an anatomical reference. The proposed data analysis tool promises to increase data throughput and data reproducibility and accelerate human disease modeling in mice.

Analysis of bioluminescence images of bacterial distributions in living animals is mostly manual and semiquantitative. Here, the authors present an analysis platform featuring an animal mold, a probabilistic organ atlas, and a mirror gantry to perform automatic in vivo bioluminescence quantification.

Estimation of subject coregistration errors during multimodal preclinical imaging using separate instruments: origins and avoidance of artifacts

We use high-resolution [Formula: see text] data in multiple experiments to estimate the sources of error during coregistration of images acquired on separate preclinical instruments. In combination with experiments with phantoms, we completed in vivo imaging on mice, aimed at identifying the possible sources of registration errors, caused either by transport of the animal, movement of the animal itself, or methods of coregistration. The same imaging cell was used as a holder for phantoms and animals. For all procedures, rigid coregistration was carried out using a common landmark coregistration system, placed inside the imaging cell. We used the fiducial registration error and the target registration error to analyze the coregistration accuracy. We found that moving an imaging cell between two preclinical devices during a multimodal procedure gives an error of about [Formula: see text] at most. Therefore, it could not be considered a source of coregistration errors. Errors linked to spontaneous movements of the animal increased with time, to nearly 1 mm at most, excepted for body parts that were properly restrained. This work highlights the importance of animal intrinsic movements during a multiacquisition procedure and demonstrates a simple method to identify and quantify the sources of error during coregistration.

Canny edge-based deformable image registration

This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.

A deformable atlas of the laboratory mouse

PURPOSE

This paper presents a deformable mouse atlas of the laboratory mouse anatomy. This atlas is fully articulated and can be positioned into arbitrary body poses. The atlas can also adapt body weight by changing body length and fat amount.

PROCEDURES

A training set of 103 micro-CT images was used to construct the atlas. A cage-based deformation method was applied to realize the articulated pose change. The weight-related body deformation was learned from the training set using a linear regression method. A conditional Gaussian model and thin-plate spline mapping were used to deform the internal organs following the changes of pose and weight.

RESULTS

The atlas was deformed into different body poses and weights, and the deformation results were more realistic compared to the results achieved with other mouse atlases. The organ weights of this atlas matched well with the measurements of real mouse organ weights. This atlas can also be converted into voxelized images with labeled organs, pseudo CT images and tetrahedral mesh for phantom studies.

CONCLUSIONS

With the unique ability of articulated pose and weight changes, the deformable laboratory mouse atlas can become a valuable tool for preclinical image analysis.

Optimization of the Energy Window for PETbox4, a Preclinical PET Tomograph With a Small Inner Diameter

Small animal positron emission tomography (PET) systems are often designed by employing close geometry configurations. Due to the different characteristics caused by geometrical factors, these tomographs require data acquisition protocols that differ from those optimized for conventional large diameter ring systems. In this work we optimized the energy window for data acquisitions with PETbox4, a 50 mm detector separation (box-like geometry) pre-clinical PET scanner, using the Geant4 Application for Tomographic Emission (GATE). The fractions of different types of events were estimated using a voxelized phantom including a mouse as well as its supporting chamber, mimicking a realistic mouse imaging environment. Separate code was developed to extract additional information about the gamma interactions for more accurate event type classification. Three types of detector backscatter events were identified in addition to the trues, phantom scatters and randoms. The energy window was optimized based on the noise equivalent count rate (NECR) and scatter fraction (SF) with lower-level discriminators (LLD) corresponding to energies from 150 keV to 450 keV. The results were validated based on the calculated image uniformity, spillover ratio (SOR) and recovery coefficient (RC) from physical measurements using the National Electrical Manufacturers Association (NEMA) NU-4 image quality phantom. These results indicate that when PETbox4 is operated with a more narrow energy window (350-650 keV), detector backscatter rejection is unnecessary. For the NEMA NU-4 image quality phantom, the SOR for the water chamber decreases by about 45% from 15.1% to 8.3%, and the SOR for the air chamber decreases by 31% from 12.0% to 8.3% at the LLDs of 150 and 350 keV, without obvious change in uniformity, further supporting the simulation based optimization. The optimization described in this work is not limited to PETbox4, but also applicable or helpful to other small inner diameter geometry scanners.

Individually ventilated cages impose cold stress on laboratory mice: a source of systemic experimental variability

Individual ventilated cages (IVC) are increasing in popularity. Although mice avoid IVC in preference testing, they show no aversion when provided additional nesting material or the cage is not ventilated. Given the high ventilation rate in IVC, we developed 3 hypotheses: that mice housed in IVC experience more cold stress than do mice housed in static cages; that IVC-induced cold stress affects the results of experiments using mice; and that, when provided shelters, mice behaviorally thermoregulate and thereby rescue the cold-stress effects of IVC. To test these hypotheses, we housed mice in IVC, IVC with shelters, and static cages maintained at 20 to 21 °C. We quantified the cold stress of each housing system on mice by assessing nonshivering thermogenesis and brown adipose vacuolation. To test housing effects in a common, murine model of human disease, we implanted mice with subcutaneous epidermoid carcinoma cells and quantified tumor growth, tumor metabolism, and adrenal weight. Mice housed in IVC had histologic signs of cold stress and significantly higher nonshivering thermogenesis, smaller subcutaneous tumors, lower tumor metabolism, and larger adrenal weights than did mice in static cages. Shelters rescued IVC-induced nonshivering thermogenesis, adrenal enlargement, and phenotype-dependent cold-mediated histologic changes in brown adipose tissue and tumor size. IVC impose chronic cold stress on mice, alter experimental results, and are a source of systemic confounders throughout rodent-dependent research. Allowing mice to exhibit behavioral thermoregulation through seeking shelter markedly rescues the experiment-altering effects of housing-imposed cold stress, improves physiologic uniformity, and increases experimental reproducibility across housing systems.

The hidden cost of housing practices: using noninvasive imaging to quantify the metabolic demands of chronic cold stress of laboratory mice

Laboratory mice routinely are housed at 20 to 22 °C-well below the murine thermoneutral zone of 29 to 34 °C. Chronic cold stress requires greater energy expenditure to maintain core body temperature and can lead to the failure of mouse models to emulate human physiology. We hypothesized that mice housed at ambient temperatures of 20 to 22 °C are chronically cold-stressed, have greater energy expenditure, and have high glucose utilization in brown adipose tissue. To test our hypotheses, we used indirect calorimetry to measure energy expenditure and substrate utilization in C57BL/6J and Crl:NU-Foxn1(nu) nude mice at routine vivarium (21 °C), intermediate (26 °C), and heated (31 °C) housing temperatures. We also examined the activation of interscapular brown adipose tissue, the primary site of nonshivering thermogenesis, via thermography and glucose uptake in this region by using positron emission tomography. Energy expenditure of mice was significantly higher at routine vivarium temperatures compared with intermediate and heated temperatures and was associated with a shift in metabolism toward glucose utilization. Brown adipose tissue showed significant activation at routine vivarium and intermediate temperatures in both hirsuite and nude mice. Crl:NU-Foxn1(nu) mice experienced greater cold stress than did C57BL/6J mice. Our data indicate mice housed under routine vivarium conditions are chronically cold stress. This novel use of thermography can measure cold stress in laboratory mice housed in vivaria, a key advantage over classic metabolic measurement tools. Therefore, thermography is an ideal tool to evaluate novel husbandry practices designed to alleviate murine cold stress.

NEMA NU-4 performance evaluation of PETbox4, a high sensitivity dedicated PET preclinical tomograph

PETbox4 is a new, fully tomographic bench top PET scanner dedicated to high sensitivity and high resolution imaging of mice. This manuscript characterizes the performance of the prototype system using the National Electrical Manufacturers Association NU 4-2008 standards, including studies of sensitivity, spatial resolution, energy resolution, scatter fraction, count-rate performance and image quality. The PETbox4 performance is also compared with the performance of PETbox, a previous generation limited angle tomography system. PETbox4 consists of four opposing flat-panel type detectors arranged in a box-like geometry. Each panel is made by a 24 × 50 pixelated array of 1.82 × 1.82 × 7 mm bismuth germanate scintillation crystals with a crystal pitch of 1.90 mm. Each of these scintillation arrays is coupled to two Hamamatsu H8500 photomultiplier tubes via a glass light guide. Volumetric images for a 45 × 45 × 95 mm field of view (FOV) are reconstructed with a maximum likelihood expectation maximization algorithm incorporating a system model based on a parameterized detector response. With an energy window of 150-650 keV, the peak absolute sensitivity is approximately 18% at the center of FOV. The measured crystal energy resolution ranges from 13.5% to 48.3% full width at half maximum (FWHM), with a mean of 18.0%. The intrinsic detector spatial resolution is 1.5 mm FWHM in both transverse and axial directions. The reconstructed image spatial resolution for different locations in the FOV ranges from 1.32 to 1.93 mm, with an average of 1.46 mm. The peak noise equivalent count rate for the mouse-sized phantom is 35 kcps for a total activity of 1.5 MBq (40 µCi) and the scatter fraction is 28%. The standard deviation in the uniform region of the image quality phantom is 5.7%. The recovery coefficients range from 0.10 to 0.93. In comparison to the first generation two panel PETbox system, PETbox4 achieves substantial improvements on sensitivity and spatial resolution. The overall performance demonstrates that the PETbox4 scanner is suitable for producing high quality images for molecular imaging based biomedical research.

A method of 2D/3D registration of a statistical mouse atlas with a planar X-ray projection and an optical photo

The development of sophisticated and high throughput whole body small animal imaging technologies has created a need for improved image analysis and increased automation. The registration of a digital mouse atlas to individual images is a prerequisite for automated organ segmentation and uptake quantification. This paper presents a fully-automatic method for registering a statistical mouse atlas with individual subjects based on an anterior-posterior X-ray projection and a lateral optical photo of the mouse silhouette. The mouse atlas was trained as a statistical shape model based on 83 organ-segmented micro-CT images. For registration, a hierarchical approach is applied which first registers high contrast organs, and then estimates low contrast organs based on the registered high contrast organs. To register the high contrast organs, a 2D-registration-back-projection strategy is used that deforms the 3D atlas based on the 2D registrations of the atlas projections. For validation, this method was evaluated using 55 subjects of preclinical mouse studies. The results showed that this method can compensate for moderate variations of animal postures and organ anatomy. Two different metrics, the Dice coefficient and the average surface distance, were used to assess the registration accuracy of major organs. The Dice coefficients vary from 0.31 ± 0.16 for the spleen to 0.88 ± 0.03 for the whole body, and the average surface distance varies from 0.54 ± 0.06 mm for the lungs to 0.85 ± 0.10mm for the skin. The method was compared with a direct 3D deformation optimization (without 2D-registration-back-projection) and a single-subject atlas registration (instead of using the statistical atlas). The comparison revealed that the 2D-registration-back-projection strategy significantly improved the registration accuracy, and the use of the statistical mouse atlas led to more plausible organ shapes than the single-subject atlas. This method was also tested with shoulder xenograft tumor-bearing mice, and the results showed that the registration accuracy of most organs was not significantly affected by the presence of shoulder tumors, except for the lungs and the spleen.

Evaluation of the Genisys4, a bench-top preclinical PET scanner

The Genisys4 is a small bench-top preclinical PET scanner designed to enable imaging in biology, biochemistry, and pharmacology laboratories and imaging centers. Here, we compare its performance with that of a well-established preclinical PET scanner.

METHODS

Subcutaneous and lung tumor xenografts were used to compare lesion detectability and treatment responses to chemotherapy (gemcitabine) using (18)F-FDG PET. The size of subcutaneous xenografts (L1210 and L1210-10K leukemia cells) and lung metastases (B-16 melanoma cells) was measured on small-animal CT images. Tumor (18)F-FDG uptake was expressed as percentage injected dose per gram. Using list-mode data, serial images of the left ventricular blood pool were used to generate time-activity curves.

RESULTS

Subcutaneous xenografts (range, 4-12 mm; mean ± SD, 6.1 ± 1.7 mm) and lung metastases (range, 1-5 mm; mean, 2.1 ± 1.2 mm) were detected equally well with both scanners. Tumor (18)F-FDG uptake measured with both scanners was highly correlated for subcutaneous xenografts (r(2) = 0.93) and lung metastases (r(2) = 0.83). The new Genisys4 scanner and the established scanner provided comparable treatment response information (r(2) = 0.93). Dynamic imaging sequences permitted the generation of left ventricular blood-pool time-activity curves with both scanners.

CONCLUSION

Using subcutaneous and lung xenografts, a novel and an established preclinical PET scanner provided equivalent information with regard to lesion detection, tumor (18)F-FDG uptake, tumor response to treatment, and generation of time-activity curves. Thus, the Genisys4 provides a small, efficient bench-top preclinical PET alternative for quantitatively studying murine tumor models in biology, biochemistry, and pharmacology laboratories and preclinical imaging centers.