Development of a 4-D digital mouse phantom for molecular imaging research

Automatic multiatlas based organ at risk segmentation in mice

OBJECTIVE:

During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow.

METHODS:

Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement.

RESULTS:

A good agreement between manual and automatic contouring was found for OARs with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney.

CONCLUSION:

The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARs with sharp organ boundaries performed better than low contrast OARs.

ADVANCES IN KNOWLEDGE:

A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow.

Monte Carlo GEANT4-based application for in vivo RBE study using small animals at LNS-INFN preclinical hadrontherapy facility

Preclinical studies represent an important step towards a deep understanding of the biological response to ionizing radiations. The effectiveness of proton therapy is higher than photons and, for clinical purposes, a fixed value of 1.1 is used for the relative biological effectiveness (RBE) of protons considered 1.1. Recent in vitro studies have reported that the RBE along the spread-out Bragg peak (SOBP) is not constant and, in particular, the RBE value increases on the distal part of SOBP. The present work has been carried-out in the perspective of a preclinical hadrontherapy facility at LNS-INFN and was focused on the experimental preparation of an in vivo study concerning the RBE variation along the SOBP. The main purpose of this work was to determine, using GEANT4-based Monte Carlo simulations, the best configuration for small animal treatments. The developed GEANT4 application simulates the proton-therapy beam line of LNS-INFN (CATANA facility) and allows to import the DICOM-CT images as targets. The RBE will be evaluated using a deterministic radiation damage like myelopathy as end-point. In fact, the dose at which the 50% of animals will show the myelopathy is supposed to be LET-dependent. In this work, we studied different treatment configurations in order to choose the best two that maximize the LET difference reducing as much as possible the dose released to healthy tissue. The results will be useful to plan hadrontherapy treatments for preclinical in vivo studies and, in particular, for the future in vivo RBE studies.

Image reconstruction in fluorescence molecular tomography with sparsity-initialized maximum-likelihood expectation maximization

We present a reconstruction method involving maximum-likelihood expectation maximization (MLEM) to model Poisson noise as applied to fluorescence molecular tomography (FMT). MLEM is initialized with the output from a sparse reconstruction-based approach, which performs truncated singular value decomposition-based preconditioning followed by fast iterative shrinkage-thresholding algorithm (FISTA) to enforce sparsity. The motivation for this approach is that sparsity information could be accounted for within the initialization, while MLEM would accurately model Poisson noise in the FMT system. Simulation experiments show the proposed method significantly improves images qualitatively and quantitatively. The method results in over 20 times faster convergence compared to uniformly initialized MLEM and improves robustness to noise compared to pure sparse reconstruction. We also theoretically justify the ability of the proposed approach to reduce noise in the background region compared to pure sparse reconstruction. Overall, these results provide strong evidence to model Poisson noise in FMT reconstruction and for application of the proposed reconstruction framework to FMT imaging.

Photobiomodulation Optimization for Spinal Cord Injury Rat Phantom Model

Spinal Cord Injury (SCI) causes interruption along the severed axonal tract(s) resulting in complete or partial loss of sensation and motor function. SCI can cause tetraplegia or paraplegia. Both these conditions can have lifelong excessive medical costs, as well as can reduce life expectancy. Preclinical research showed that Photobiomodulation therapy (PBMT), also known as Low-level laser (light) therapy (LLLT), possesses reparative and regenerative capabilities that have the potential to be used as a complimentary or supplementary SCI therapy. Despite the promising effects of PBMT, there are still no standardized irradiation parameters (i.e. different wavelengths, power, fluence, irradiance, beam type, beam diameters, and irradiation time) and there is also a lack of standardized experimental protocol(s), which makes it difficult to compare different studies. It is, nonetheless, essential to standardize such irradiation parameters in order to provide better PBMTs. The aim of this study, therefore, is to evaluate the delivery of light in a 3D voxelated SCI rat model for PBMT using different irradiation parameters (wavelengths: 660, 810, and 980 nm; beam types: Gaussian and Flat beam; and beam diameters: 0.04-1.2 cm) using Monte Carlo simulation. This study also aids in providing standardization for preclinical research for PBMT, which will eventually translate into clinical standardization upon clinical research studies and results.

A finite element analysis of diaphragmatic hernia repair on an animal model

The diaphragm is a mammalian skeletal muscle that plays a fundamental role in the process of respiration. Alteration of its mechanical properties due to a diaphragmatic hernia contributes towards compromising its respiratory functions, leading to the need for surgical intervention to restore the physiological conditions by means of implants. This study aims to assess via numerical modeling biomechanical differences between a diaphragm in healthy conditions and a herniated diaphragm surgically repaired with a polymeric implant, in a mouse model. Finite Element models of healthy and repaired diaphragms are developed from diagnostic images and anatomical samples. The mechanical response of the diaphragmatic tendon is described by assuming an isotropic hyperelastic model. A similar constitutive model is used to define the mechanical behavior of the polymeric implant, while the muscular tissue is modeled by means of a three-element Hill's model, specifically adapted to mouse muscle fibers. The Finite Element Analysis is addressed to simulate diaphragmatic contraction in the eupnea condition, allowing the evaluation of diaphragm deformation in healthy and herniated-repaired conditions. The polymeric implant reduces diaphragm excursion compared to healthy conditions. This explains the possible alteration in the mechanical functionality of the repaired diaphragm. Looking to the surgical treatment of diaphragmatic hernia in human neonatal subjects, this study suggests the implementation of alternative approaches based on the use of biological implants.

VOXSI: A voxelized single- and dual-energy CT scenario generator for quantitative imaging

BACKGROUND AND PURPOSE

Dedicated CT simulation models have the potential to investigate several acquisition, reconstruction, or post-processing parameters without giving any radiation dose to patients. A software program was developed for the simulation and the analysis of single-energy and dual-energy CT images. Simulation and analysis functionalities of the software are described.

MATERIALS AND METHODS

In the software, named VOXSI (VOXelized CT SImulator), the X-ray source, user specified simulation geometry, CT setup and the detector energy response can be varied. CT image reconstructions can be performed with an implementation of the ASTRA toolbox. In the DECT post processing toolkit, GUI tools are provided to calculate effective atomic number, relative electron density, pseudo-monoenergetic images, and material map images. Quantitative CT number validation, based on a RMI 467 tissue characterization phantom model, was performed between experimental and simulated CT scans at three different X-ray tube potentials (80, 120, and 140 kVp) with a third generation CT scanner.

RESULTS

Overall, a good agreement was found for the mean CT numbers of the RMI 467 inserts. For all energies, the maximum difference in CT numbers between experimental and simulated data was below 17 HU for the soft tissues and below 48 HU for the osseous tissues.

CONCLUSION

The software's simulation algorithm showed a good agreement between the CT measurements and CT simulations of the RMI 467 phantom at different energies. The capabilities of the software are demonstrated by an elaborated dual-energy CT research example.

Murine-specific Internal Dosimetry for Preclinical Investigations of Imaging and Therapeutic Agents

There is a growing need to estimate the absorbed dose to small animals from preclinical investigations involving diagnostic and therapeutic radiopharmaceuticals. This paper introduces a Monte Carlo-based dosimetry platform called RAPID, which is capable of calculating murine-specific three-dimensional (3D) dose distributions. A comparison is performed between absorbed doses calculated with RAPID and absorbed doses calculated in a commonly used reference mouse phantom called MOBY. Four test mice containing different xenografts underwent serial PET/CT imaging using a novel diagnostic therapy (theranostic) agent NM404, which can be labeled with I for imaging or I for therapy. Using the PET/CT data, 3D dose distributions from I-NM404 were calculated in the mice using RAPID. Mean organ doses in these four test mice were compared to mean organ doses derived by using two previously published I S-values datasets in MOBY. In addition, mean tumor doses calculated in RAPID were compared to mean organ doses derived from unit density spheres. Large differences were identified between mean organ doses calculated in the test mice using RAPID and those derived in the MOBY phantom. Mean absorbed dose percent errors in organs ranged between 0.3% and 333%. Overall, mass scaling improved agreement between MOBY phantom calculations and RAPID, where percent errors were all less than 26%, with the exception of the lung in which percent errors reached values of 48%. Percent errors in mean tumor doses in the test mice and unit density spheres were less pronounced but still ranged between 8% and 23%. This work demonstrates the limitations of using pre-computed S-values in computational phantoms to predict organ doses in small animals from theranostic procedures. RAPID can generate accurate 3D dose distributions in small animals and in turn offer much greater insight on the ability of a given theranostic agent to image and treat diseases.

Low-dose 4D cardiac imaging in small animals using dual source micro-CT

Micro-CT is widely used in preclinical studies, generating substantial interest in extending its capabilities in functional imaging applications such as blood perfusion and cardiac function. However, imaging cardiac structure and function in mice is challenging due to their small size and rapid heart rate. To overcome these challenges, we propose and compare improvements on two strategies for cardiac gating in dual-source, preclinical micro-CT: fast prospective gating (PG) and uncorrelated retrospective gating (RG). These sampling strategies combined with a sophisticated iterative image reconstruction algorithm provide faster acquisitions and high image quality in low-dose 4D (i.e. 3D  +  Time) cardiac micro-CT. Fast PG is performed under continuous subject rotation which results in interleaved projection angles between cardiac phases. Thus, fast PG provides a well-sampled temporal average image for use as a prior in iterative reconstruction. Uncorrelated RG incorporates random delays during sampling to prevent correlations between heart rate and sampling rate. We have performed both simulations and animal studies to validate these new sampling protocols. Sampling times for 1000 projections using fast PG and RG were 2 and 3 min, respectively, and the total dose was 170 mGy each. Reconstructions were performed using a 4D iterative reconstruction technique based on the split Bregman method. To examine undersampling robustness, subsets of 500 and 250 projections were also used for reconstruction. Both sampling strategies in conjunction with our iterative reconstruction method are capable of resolving cardiac phases and provide high image quality. In general, for equal numbers of projections, fast PG shows fewer errors than RG and is more robust to undersampling. Our results indicate that only 1000-projection based reconstruction with fast PG satisfies a 5% error criterion in left ventricular volume estimation. These methods promise low-dose imaging with a wide range of preclinical applications in cardiac imaging.

Optimization of an Adaptive SPECT System with the Scanning Linear Estimator

A method for optimization of an adaptive Single Photon Emission Computed Tomography (SPECT) system is presented. Adaptive imaging systems can quickly change their hardware configuration in response to data being generated in order to improve image quality for a specific task. In this work we simulate an adaptive SPECT system and propose a method for finding the adaptation that maximizes the performance on a signal estimation task. To start with, a simulated object model containing a spherical signal is imaged with a scout configuration. A Markov-Chain Monte Carlo (MCMC) technique utilizes the scout data to generate an ensemble of possible objects consistent with the scout data. This object ensemble is imaged by numerous simulated hardware configurations and for each system estimates of signal activity, size and location are calculated via the Scanning Linear Estimator (SLE). A figure of merit, based on a Modified Dice Index (MDI), quantifies the performance of each imaging configuration and it allows for optimization of the adaptive SPECT. This figure of merit is calculated by multiplying two terms: the first term uses the definition of the Dice similarity index to determine the percent of overlap between the actual and the estimated spherical signal, the second term utilizes an exponential function that measures the squared error for the activity estimate. The MDI combines the error in estimates of activity, size, and location, in one convenient metric and it allows for simultaneous optimization of the SPECT system with respect to all the estimated signal parameters. The results of our optimizations indicate that the adaptive system performs better than a non-adaptive one in conditions where the diagnostic scan has a low photon count - on the order of thousand photons per projection. In a statistical study, we optimized the SPECT system for one hundred unique objects and demonstrated that the average MDI on an estimation task is 0.84 for the adaptive system and 0.65 for the non-adaptive system.

Automated MicroSPECT/MicroCT Image Analysis of the Mouse Thyroid Gland

BACKGROUND

The ability of thyroid follicular cells to take up iodine enables the use of radioactive iodine (RAI) for imaging and targeted killing of RAI-avid thyroid cancer following thyroidectomy. To facilitate identifying novel strategies to improve 131I therapeutic efficacy for patients with RAI refractory disease, it is desired to optimize image acquisition and analysis for preclinical mouse models of thyroid cancer.

METHODS

A customized mouse cradle was designed and used for microSPECT/CT image acquisition at 1 hour (t1) and 24 hours (t24) post injection of 123I, which mainly reflect RAI influx/efflux equilibrium and RAI retention in the thyroid, respectively. FVB/N mice with normal thyroid glands and TgBRAFV600E mice with thyroid tumors were imaged. In-house CTViewer software was developed to streamline image analysis with new capabilities, along with display of 3D voxel-based 123I gamma photon intensity in MATLAB.

RESULTS

The customized mouse cradle facilitates consistent tissue configuration among image acquisitions such that rigid body registration can be applied to align serial images of the same mouse via the in-house CTViewer software. CTViewer is designed specifically to streamline SPECT/CT image analysis with functions tailored to quantify thyroid radioiodine uptake. Automatic segmentation of thyroid volumes of interest (VOI) from adjacent salivary glands in t1 images is enabled by superimposing the thyroid VOI from the t24 image onto the corresponding aligned t1 image. The extent of heterogeneity in 123I accumulation within thyroid VOIs can be visualized by 3D display of voxel-based 123I gamma photon intensity.

CONCLUSIONS

MicroSPECT/CT image acquisition and analysis for thyroidal RAI uptake is greatly improved by the cradle and the CTViewer software, respectively. Furthermore, the approach of superimposing thyroid VOIs from t24 images to select thyroid VOIs on corresponding aligned t1 images can be applied to studies in which the target tissue has differential radiotracer retention from surrounding tissues.

Sensitivity and accuracy of hybrid fluorescence-mediated tomography in deep tissue regions

Fluorescence-mediated tomography (FMT) enables noninvasive assessment of the three-dimensional distribution of near-infrared fluorescence in mice. The combination with micro-computed tomography (µCT) provides anatomical data, enabling improved fluorescence reconstruction and image analysis. The aim of our study was to assess sensitivity and accuracy of µCT-FMT under realistic in vivo conditions in deeply-seated regions. Accordingly, we acquired fluorescence reflectance images (FRI) and µCT-FMT scans of mice which were prepared with rectal insertions with different amounts of fluorescent dye. Default and high-sensitivity scans were acquired and background signal was analyzed for three FMT channels (670 nm, 745 nm, and 790 nm). Analysis was performed for the original and an improved FMT reconstruction using the µCT data. While FRI and the original FMT reconstruction could detect 100 pmol, the improved FMT reconstruction could detect 10 pmol and significantly improved signal localization. By using a finer sampling grid and increasing the exposure time, the sensitivity could be further improved to detect 0.5 pmol. Background signal was highest in the 670 nm channel and most prominent in the gastro-intestinal tract and in organs with high relative amounts of blood. In conclusion, we show that µCT-FMT allows sensitive and accurate assessment of fluorescence in deep tissue regions.

RODES software for dose assessment of rats and mice contaminated with radionuclides

In order to support animal experiments of chronic radionuclides intake with realistic dosimetry, voxel-based three-dimensional computer models of mice and rats of both sexes and three ages were built from magnetic resonance imaging. Radiation transport of mono-energetic photons of 11 energies and electrons of 7 energies was simulated with MCNPX 2.6c to assess specific absorbed fractions (SAFs) of energy emitted from 13 source regions and absorbed in 28 target regions. RODES software was developed to combine SAF with radiation emission spectra and user-supplied biokinetic data to calculate organ absorbed doses per nuclear transformation of radionuclides in source regions (S-factors) and for specific animal experiments with radionuclides. This article presents the design of RODES software including the simulation of the particles in the created rodent voxel phantoms. SAF and S-factor values were compared favourably with published results from similar studies. The results are discussed for rodents of different ages and sexes.

Simulation of nanoparticle-mediated near-infrared thermal therapy using GATE

Application of nanotechnology for biomedicine in cancer therapy allows for direct delivery of anticancer agents to tumors. An example of such therapies is the nanoparticle-mediated near-infrared hyperthermia treatment. In order to investigate the influence of nanoparticle properties on the spatial distribution of heat in the tumor and healthy tissues, accurate simulations are required. The Geant4 Application for Emission Tomography (GATE) open-source simulation platform, based on the Geant4 toolkit, is widely used by the research community involved in molecular imaging, radiotherapy and optical imaging. We present an extension of GATE that can model nanoparticle-mediated hyperthermal therapy as well as simple heat diffusion in biological tissues. This new feature of GATE combined with optical imaging allows for the simulation of a theranostic scenario in which the patient is injected with theranostic nanosystems that can simultaneously deliver therapeutic (i.e. hyperthermia therapy) and imaging agents (i.e. fluorescence imaging).

Scattered Dose Calculations and Measurements in a Life-Like Mouse Phantom

Anatomically accurate phantoms are useful tools for radiation dosimetry studies. In this work, we demonstrate the construction of a new generation of life-like mouse phantoms in which the methods have been generalized to be applicable to the fabrication of any small animal. The mouse phantoms, with built-in density inhomogeneity, exhibit different scattering behavior dependent on where the radiation is delivered. Computer models of the mouse phantoms and a small animal irradiation platform were devised in Monte Carlo N-Particle code (MCNP). A baseline test replicating the irradiation system in a computational model shows minimal differences from experimental results from 50 Gy down to 0.1 Gy. We observe excellent agreement between scattered dose measurements and simulation results from X-ray irradiations focused at either the lung or the abdomen within our phantoms. This study demonstrates the utility of our mouse phantoms as measurement tools with the goal of using our phantoms to verify complex computational models.

Preclinical positron emission tomography scanner based on a monolithic annulus of scintillator: initial design study

Positron emission tomography (PET) scanners designed for imaging of small animals have transformed translational research by reducing the necessity to invasively monitor physiology and disease progression. Virtually all of these scanners are based on the use of pixelated detector modules arranged in rings. This design, while generally successful, has some limitations. Specifically, use of discrete detector modules to construct PET scanners reduces detection sensitivity and can introduce artifacts in reconstructed images, requiring the use of correction methods. To address these challenges, and facilitate measurement of photon depth-of-interaction in the detector, we investigated a small animal PET scanner (called AnnPET) based on a monolithic annulus of scintillator. The scanner was created by placing 12 flat facets around the outer surface of the scintillator to accommodate placement of silicon photomultiplier arrays. Its performance characteristics were explored using Monte Carlo simulations and sections of the NEMA NU4-2008 protocol. Results from this study revealed that AnnPET's reconstructed spatial resolution is predicted to be [Formula: see text] full width at half maximum in the radial, tangential, and axial directions. Peak detection sensitivity is predicted to be 10.1%. Images of simulated phantoms (mini-hot rod and mouse whole body) yielded promising results, indicating the potential of this system for enhancing PET imaging of small animals.

Tensor-Based Dictionary Learning for Spectral CT Reconstruction

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods.

In Vivo Measurements of T2 Relaxation Time of Mouse Lungs during Inspiration and Expiration

Purpose

The interest in measurements of magnetic resonance imaging relaxation times, T1, T2, T2*, with intention to characterize healthy and diseased lungs has increased recently. Animal studies play an important role in this context providing models for understanding and linking the measured relaxation time changes to the underlying physiology or disease. The aim of this work was to study how the measured transversal relaxation time (T2) in healthy lungs is affected by normal respiration in mouse.

Method

T2 of lung was measured in anaesthetized freely breathing mice. Image acquisition was performed on a 4.7 T, Bruker BioSpec with a multi spin-echo sequence (Car-Purcell-Meiboom-Gill) in both end-expiration and end-inspiration. The echo trains consisted of ten echoes of inter echo time 3.5 ms or 4.0 ms. The proton density, T2 and noise floor were fitted to the measured signals of the lung parenchyma with a Levenberg-Marquardt least-squares three-parameter fit.

Results

T2 in the lungs was longer (p<0.01) at end-expiration (9.7±0.7 ms) than at end-inspiration (9.0±0.8 ms) measured with inter-echo time 3.5 ms. The corresponding relative proton density (lung/muscle tissue) was higher (p<0.001) during end-expiration, (0.61±0.06) than during end-inspiration (0.48±0.05). The ratio of relative proton density at end-inspiration to that at end-expiration was 0.78±0.09. Similar results were found for inter-echo time 4.0 ms and there was no significant difference between the T2 values or proton densities acquired with different interecho times. The T2 value increased linearly (p< 0.001) with proton density.

Conclusion

The measured T2 in-vivo is affected by diffusion across internal magnetic susceptibility gradients. In the lungs these gradients are modulated by respiration, as verified by calculations. In conclusion the measured T2 was found to be dependent on the size of the alveoli.

Design of a dual-resolution collimator for preclinical cardiac SPECT with a stationary triple-detector system

PURPOSE

One approach to preclinical single-photon emission computed tomography (SPECT) imaging that provides both high resolution and high sensitivity is based on imaging a mouse inside a collimating tube; many magnified pinhole projection images from a small target region, e.g., the heart, can be recorded simultaneously on multiple detectors with little multiplexing since each pinhole aperture's opening angle is restricted to view mostly the target organ. However, to obtain complete data for reconstruction, it may be necessary to scan the mouse through the target region of the tube. The authors are developing a different approach based on acquisition and reconstruction of both low-resolution and high-resolution projection data acquired sequentially through many pinholes embedded in two tungsten tube sections of different diameters, a "scout" section and a high-resolution section, placed end-to-end along the axis of a triple-head clinical SPECT scanner. This paper describes the design procedures used to determine the geometric parameters of two new collimator-tube sections, as well as one approach for joint reconstruction of data acquired from both sections.

METHODS

The high-resolution section was designed by projecting as many pinhole views of a simulated mouse heart as possible over each detector's camera, with no overlapping of heart projections and minimal overlapping between adjacent "hot" organ and cardiac projections. The authors then jointly optimized the geometric design of the scout section for a triple-detector camera system, as well as the number of maximum-likelihood expectation maximization (MLEM) iterations required to provide minimum mean-squared error of reconstructed voxel counts throughout a 7-cm axial range, with the constraints of fixed, 2.4-mm scout system resolution at the tube center for all apertures, limited multiplexing, and no detector motion. Simulated mouse projection data from both tube sections were then reconstructed to illustrate a simple approach for using high-resolution data to improve the whole-body scout images within a cylindrical region surrounding the heart.

RESULTS

The 2-cm-inner-radius high-resolution tube section accommodated 87 platinum-iridium pinhole inserts, each with a 0.3-mm square aperture; their radial distances from the centerline of the system ranged from 2.2 to 3.0 cm. The optimal radial distance to the closest scout pinhole and optimal number of MLEM iterations were 4.4 cm and 35 iterations, respectively, and the radial distances of the 39 scout pinholes ranged from 4.4 to 4.8 cm; aperture sizes ranged from 1.1 to 1.7 mm transaxially and 0.9-1.5 mm axially. After including data from the high-resolution section viewing the heart region into whole-body mouse reconstructions from scout data, the authors obtained high-resolution images of the heart, embedded within lower resolution images of the body, with minimal artifacts.

CONCLUSIONS

The authors have optimized a dual-resolution collimator tube that provides both whole-body projections of a mouse and more targeted projections centered on the heart that can be jointly reconstructed to obtain high-resolution images of the heart embedded within lower-resolution whole-body images.

Region-based diffuse optical tomography with registered atlas: in vivo acquisition of mouse optical properties

The reconstruction quality in the model-based optical tomography modalities can greatly benefit from a priori information of accurate tissue optical properties, which are difficult to be obtained in vivo with a conventional diffuse optical tomography (DOT) system alone. One of the solutions is to apply a priori anatomical structures obtained with anatomical imaging systems such as X-ray computed tomography (XCT) to constrain the reconstruction process of DOT. However, since X-ray offers low soft-tissue contrast, segmentation of abdominal organs from sole XCT images can be problematic. In order to overcome the challenges, the current study proposes a novel method of recovering a priori organ-oriented tissue optical properties, where anatomical structures of an in vivo mouse are approximately obtained by registering a standard anatomical atlas, i.e., the Digimouse, to the target XCT volume with the non-rigid image registration, and, in turn, employed to guide DOT for extracting the optical properties of inner organs. Simulative investigations have validated the methodological availability of such atlas-registration-based DOT strategy in revealing both a priori anatomical structures and optical properties. Further experiments have demonstrated the feasibility of the proposed method for acquiring the organ-oriented tissue optical properties of in vivo mice, making it as an efficient way of the reconstruction enhancement.

The influence of respiratory motion on dose delivery in a mouse lung tumour irradiation using the 4D MOBY phantom

OBJECTIVE

During precision irradiation of a preclinical lung tumour model, the tumour is subject to breathing motion and it can partially move out of the irradiation field. This work aimed to perform a quantitative analysis of the impact of respiratory motion on a mouse lung tumour irradiation with small fields.

METHODS

A four-dimensional digital mouse whole body phantom (MOBY) with a virtual 4-mm spherical lung tumour at different locations in both lungs is used to simulate a breathing anaesthetized mouse in different breathing phases representing a full breathing cycle. The breathing curve is determined by fluoroscopic imaging of an anaesthetized mouse. Each MOBY time frame is loaded in a dedicated treatment planning system (small animal radiotherapy-Plan) and is irradiated by a full arc with a 5-mm circular collimator. Mean and time-dependent organ doses are calculated for the tumour, heart and spinal cord.

RESULTS

Depending on the location of the lung tumour, an overestimation of the mean tumour dose up to 11% is found. The mean heart dose could be both overestimated or underestimated because the heart moves in or out of the irradiation field depending on the beam target location. The respiratory motion does not affect the mean spinal cord dose. A dose gradient is visible in the time-dependent tumour dose distribution.

CONCLUSION

In the future, new methods need to be developed to track the lung tumour motion before preclinical irradiation to adjust the irradiation plan. Margins, collimator diameter and target dose could be changed easily, but they all have their drawbacks. State-of-the-art clinical techniques such as respiratory gating or motion tracking may offer a solution for the cold spots in the time-dependent tumour dose. Advances in knowledge: A suitable method is found to quantify changes in organ dose due to respiratory motion in mouse lung tumour image-guided precision irradiation.

Development of computational small animal models and their applications in preclinical imaging and therapy research

The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

Modelling Random Coincidences in Positron Emission Tomography by Using Singles and Prompts: A Comparison Study

Random coincidences degrade the image in Positron Emission Tomography, PET. To compensate for their degradation effects, the rate of random coincidences should be estimated. Under certain circumstances, current estimation methods fail to provide accurate results. We propose a novel method, "Singles-Prompts" (SP), that includes the information conveyed by prompt coincidences and models the pile-up. The SP method has the same structure than the well-known "Singles Rate" (SR) approach. Hence, SP can straightforwardly replace SR. In this work, the SP method has been extensively assessed and compared to two conventional methods, SR and the delayed window (DW) method, in a preclinical PET scenario using Monte-Carlo simulations. SP offers accurate estimates for the randoms rates, while SR and DW tend to overestimate the rates (∼10%, and 5%, respectively). With pile-up, the SP method is more robust than SR (but less than DW). At the image level, the contrast is overestimated in SR-corrected images, +16%, while SP produces the correct value. Spill-over is slightly reduced using SP instead of SR. The DW images values are similar to those of SP except for low-statistic scenarios, where DW behaves as if randoms were not compensated for. In particular, the contrast is reduced, -16%. In general, the better estimations of SP translate into better image quality.

Spectrotemporal CT data acquisition and reconstruction at low dose

PURPOSE

X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D+dual energy+time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols.

METHODS

The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer.

RESULTS

Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol.

CONCLUSIONS

Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.

OSSI-PET: Open-Access Database of Simulated [(11)C]Raclopride Scans for the Inveon Preclinical PET Scanner: Application to the Optimization of Reconstruction Methods for Dynamic Studies

A wide range of medical imaging applications benefits from the availability of realistic ground truth data. In the case of positron emission tomography (PET), ground truth data is crucial to validate processing algorithms and assessing their performances. The design of such ground truth data often relies on Monte-Carlo simulation techniques. Since the creation of a large dataset is not trivial both in terms of computing time and realism, we propose the OSSI-PET database containing 350 simulated [(11)C]Raclopride dynamic scans for rats, created specifically for the Inveon pre-clinical PET scanner. The originality of this database lies on the availability of several groups of scans with controlled biological variations in the striata. Besides, each group consists of a large number of realizations (i.e., noise replicates). We present the construction methodology of this database using rat pharmacokinetic and anatomical models. A first application using the OSSI-PET database is presented. Several commonly used reconstruction techniques were compared in terms of image quality, accuracy and variability of the activity estimates and of the computed kinetic parameters. The results showed that OP-OSEM3D iterative reconstruction method outperformed the other tested methods. Analytical methods such as FBP2D and 3DRP also produced satisfactory results. However, FORE followed by OSEM2D reconstructions should be avoided. Beyond the illustration of the potential of the database, this application will help scientists to understand the different sources of noise and bias that can occur at the different steps in the processing and will be very useful for choosing appropriate reconstruction methods and parameters.

Multimodal Correlative Preclinical Whole Body Imaging and Segmentation

Segmentation of anatomical structures and particularly abdominal organs is a fundamental problem for quantitative image analysis in preclinical research. This paper presents a novel approach for whole body segmentation of small animals in a multimodal setting of MR, CT and optical imaging. The algorithm integrates multiple imaging sequences into a machine learning framework, which generates supervoxels by an efficient hierarchical agglomerative strategy and utilizes multiple SVM-kNN classifiers each constrained by a heatmap prior region to compose the segmentation. We demonstrate results showing segmentation of mice images into several structures including the heart, lungs, liver, kidneys, stomach, vena cava, bladder, tumor, and skeleton structures. Experimental validation on a large set of mice and organs, indicated that our system outperforms alternative state of the art approaches. The system proposed can be generalized to various tissues and imaging modalities to produce automatic atlas-free segmentation, thereby enabling a wide range of applications in preclinical studies of small animal imaging.

Radioimmunotherapy of prostate cancer targeting human kallikrein-related peptidase 2

Background

Prostate cancer ranks as the second most lethal malignancy in the Western world. Previous targeting of prostate-specific antigen and human kallikrein-related peptidase 2, two related enzymes abundantly expressed in prostatic malignancies, with radioimmunoconjugates intended for diagnostic purposes, have proven successful in rodent prostate cancer (PCa) models. In this study, we investigated the uptake and therapeutic efficacy of ¹⁷⁷Lu-m11B6, a human kallikrein-related peptidase 2 (hK2)-targeting radioimmunoconjugate in a pre-clinical setting.

Methods

The murine 11B6 antibody, m11B6, with high affinity for hK2, was labeled with ¹⁷⁷Lu. Therapy planning was done from a biokinetic study in LNCaP xenografts, and therapeutic activities of ¹⁷⁷Lu-m11B6 were administered to groups of mice. Body weight and general conditions of the mice were followed over a period of 120 days.

Results

The tumor uptake in LNCaP xenografts was 30 ± 8.2 % injected activity per gram 1 week post-injection. In vivo targeting was hK2-specific as verified by a 2.5-fold decrease in tumor uptake in pre-dosed xenografts or by a fourfold lower tumor accumulation in hK2-negative DU 145 xenografts. Therapy showed a dose-dependent efficacy in LNCaP xenografts treated with ¹⁷⁷Lu-m11B6. No therapeutic effect was seen in the control groups. The median survival for the lowest given activity of ¹⁷⁷Lu-m11B6 was 88 days compared to that of 38 days in mice given labeled non-specific IgG. For the higher administrated activities, total tumor regression was seen with minimal normal organ toxicity.

Conclusions

We have proven the possibility of radioimmunotherapy targeting hK2 in subcutaneous prostate cancer xenografts. ¹⁷⁷Lu-m11B6 exhibited high therapeutic efficacy, with low observed toxicity. Additionally, an evaluation of the concept of pre-therapy planning using a dosimetry model was included in this radioimmunotherapy study.

Determining organ dose conversion coefficients for external neutron irradiation by using a voxel mouse model

A set of fluence-to-dose conversion coefficients has been calculated for neutrons with energies <20 MeV using a developed voxel mouse model and Monte Carlo N-particle code (MCNP), for the purpose of neutron radiation effect evaluation. The calculation used 37 monodirectional monoenergetic neutron beams in the energy range 10(-9) MeV to 20 MeV, under five different source irradiation configurations: left lateral, right lateral, dorsal-ventral, ventral-dorsal, and isotropic. Neutron fluence-to-dose conversion coefficients for selected organs of the body were presented in the paper, and the effect of irradiation geometry conditions, neutron energy and the organ location on the organ dose was discussed. The results indicated that neutron dose conversion coefficients clearly show sensitivity to irradiation geometry at neutron energy below 1 MeV.

Constrained Total Generalized p-Variation Minimization for Few-View X-Ray Computed Tomography Image Reconstruction

Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems.

Simultaneous scanning of two mice in a small-animal PET scanner: a simulation-based assessment of the signal degradation

In PET imaging, research groups have recently proposed different experimental set ups allowing multiple animals to be simultaneously imaged in a scanner in order to reduce the costs and increase the throughput. In those studies, the technical feasibility was demonstrated and the signal degradation caused by additional mice in the FOV characterized, however, the impact of the signal degradation on the outcome of a PET study has not yet been studied. Here we thoroughly investigated, using Monte Carlo simulated [18F]FDG and [11C]Raclopride PET studies, different experimental designs for whole-body and brain acquisitions of two mice and assessed the actual impact on the detection of biological variations as compared to a single-mouse setting. First, we extended the validation of the PET-SORTEO Monte Carlo simulation platform for the simultaneous simulation of two animals. Then, we designed [18F]FDG and [11C]Raclopride input mouse models for the simulation of realistic whole-body and brain PET studies. Simulated studies allowed us to accurately estimate the differences in detection between single- and dual-mode acquisition settings that are purely the result of having two animals in the FOV. Validation results showed that PET-SORTEO accurately reproduced the spatial resolution and noise degradations that were observed with actual dual phantom experiments. The simulated [18F]FDG whole-body study showed that the resolution loss due to the off-center positioning of the mice was the biggest contributing factor in signal degradation at the pixel level and a minimal inter-animal distance as well as the use of reconstruction methods with resolution modeling should be preferred. Dual mode acquisition did not have a major impact on ROI-based analysis except in situations where uptake values in organs from the same subject were compared. The simulated [11C]Raclopride study however showed that dual-mice imaging strongly reduced the sensitivity to variations when mice were positioned side-by-side while no sensitivity reduction was observed when they were facing each other. This is the first study showing the impact of different experimental designs for whole-body and brain acquisitions of two mice on the quality of the results using Monte Carlo simulated [18F]FDG and [11C]Raclopride PET studies.

TandemPET- A High Resolution, Small Animal, Virtual Pinhole-Based PET Scanner: Initial Design Study

Mice are the perhaps the most common species of rodents used in biomedical research, but many of the current generation of small animal PET scanners are non-optimal for imaging these small rodents due to their relatively low resolution. Consequently, a number of researchers have investigated the development of high-resolution scanners to address this need. In this investigation, the design of a novel, high-resolution system based on the dual-detector, virtual-pinhole PET concept was explored via Monte Carlo simulations. Specifically, this system, called TandemPET, consists of a 5 cm × 5 cm high-resolution detector made-up of a 90 × 90 array of 0.5 mm × 0.5 mm × 10 mm (pitch= 0.55 mm) LYSO detector elements in coincidence with a lower resolution detector consisting of a 68 × 68 array of 1.5 mm × 1.5 mm × 10 mm LYSO detector elements (total size= 10.5 cm × 10.5 cm). Analyses indicated that TandemPET's optimal geometry is to position the high-resolution detector 3 cm from the center-of-rotation, with the lower resolution detector positioned 9 cm from center. Measurements using modified NEMA NU4-2008-based protocols revealed that the spatial resolution of the system is ~0.5 mm FWHM, after correction of positron range effects. Peak sensitivity is 2.1%, which is comparable to current small animal PET scanners. Images from a digital mouse brain phantom demonstrated the potential of the system for identifying important neurological structures.

Application of computational models to estimate organ radiation dose in rainbow trout from uptake of molybdenum-99 with comparison to iodine-131

This study compares three anatomical phantoms for rainbow trout (Oncorhynchus mykiss) for the purpose of estimating organ radiation dose and dose rates from molybdenum-99 ((99)Mo) uptake in the liver and GI tract. Model comparison and refinement is important to the process of determining accurate doses and dose rates to the whole body and the various organs. Accurate and consistent dosimetry is crucial to the determination of appropriate dose-effect relationships for use in environmental risk assessment. The computational phantoms considered are (1) a geometrically defined model employing anatomically relevant organ size and location, (2) voxel reconstruction of internal anatomy obtained from CT imaging, and (3) a new model utilizing NURBS surfaces to refine the model in (2). Dose Conversion Factors (DCFs) for whole body as well as selected organs of O. mykiss were computed using Monte Carlo modeling and combined with empirical models for predicting activity concentration to estimate dose rates and ultimately determine cumulative radiation dose (μGy) to selected organs after several half-lives of (99)Mo. The computational models provided similar results, especially for organs that were both the source and target of radiation (less than 30% difference between all models). Values in the empirical model as well as the 14 day cumulative organ doses determined from (99)Mo uptake are compared to similar models developed previously for (131)I. Finally, consideration is given to treating the GI tract as a solid organ compared to partitioning it into gut contents and GI wall, which resulted in an order of magnitude difference in estimated dose for most organs.

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.

Microdosimetric and Biological Effects of Photon Irradiation at Different Energies in Bone Marrow

To ensure reliability and reproducibility of radiobiological data, it is necessary to standardize dosimetry practices across all research institutions. The photoelectric effect predominates over other interactions at low energy and in high atomic number materials such as bone, which can lead to increased dose deposition in soft tissue adjacent to mineral bone due to secondary radiation particles. This may produce radiation effects that deviate from higher energy photon irradiation that best model exposure from clinical radiotherapy or nuclear incidences. Past theoretical considerations have indicated that this process should affect radiation exposure of neighboring bone marrow (BM) and account for reported differences in relative biological effectiveness (RBE) for hematopoietic failure in rodents. The studies described herein definitively estimate spatial dose distribution and biological effectiveness within the BM compartment for (137)Cs gamma rays and 320 kVp X rays at two levels of filtration: 1 and 4 mm Cu half-value layer (HVL). In these studies, we performed: 1. Monte Carlo simulations on a 5 μm resolution model of mouse vertebrae and femur derived from micro-CT images; 2. In vitro biological experiments irradiating BM cells plated directly on the surface of a bone-equivalent material (BEM); and 3. An in vivo study on BM cell survival in irradiated live mice. Simulation results showed that the relative dose increased in proximity to bone at the lower radiation energies and produced averaged values of relative dose over the entire BM volume within imaged trabecular bone of 1.17, 1.08 and 1.01 for beam qualities of 1 mm Cu HVL, 4 mm Cu HVL and (137)Cs, respectively. In accordance with Monte Carlo simulations, in vitro irradiation of BM cells located on BEM and in vivo whole-body irradiation at a prescribed dose to soft tissue of 6 Gy produced relative cell killing of hematopoietic progenitors (CFU-C) that significantly increased for the 1 mm Cu HVL X rays compared to radiation exposures of higher photon energies. Thus, we propose that X rays of the highest possible kVp and filtration be used to investigate radiation effects on the hematopoietic system, as this will allow for better comparisons with high-energy photon exposures applied in radiotherapy or as anticipated in a nuclear event.

Evaluation of Fisher Information Matrix-Based Methods for Fast Assessment of Image Quality in Pinhole SPECT

The accurate determination of the local impulse response and the covariance in voxels from penalized maximum likelihood reconstructed images requires performing reconstructions from many noise realizations of the projection data. As this is usually a very time-consuming process, efficient analytical approximations based on the Fisher information matrix (FIM) have been extensively used in PET and SPECT to estimate these quantities. For 3D imaging, however, additional approximations need to be made to the FIM in order to speed up the calculations. The most common approach is to use the local shift-invariant (LSI) approximation of the FIM, but this assumes specific conditions which are not always necessarily valid. In this paper we take a single-pinhole SPECT system and compare the accuracy of the LSI approximation against two other methods that have been more recently put forward: the non-uniform object-space pixelation (NUOP) and the subsampled FIM. These methods do not assume such restrictive conditions while still increasing the speed of the calculations considerably. Our results indicate that in pinhole SPECT the NUOP and subsampled FIM approaches could be more reliable than the LSI approximation, especially when a high accuracy is required.

4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging

Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity.

Construction of mouse phantoms from segmented CT scan data for radiation dosimetry studies

We present the complete construction methodology for an anatomically accurate mouse phantom made using materials which mimic the characteristics of tissue, lung, and bone for radiation dosimetry studies. Phantoms were constructed using 2 mm thick slices of tissue equivalent material which was precision machined to clear regions for insertion of lung and bone equivalent material where appropriate. Images obtained using a 3D computed tomography (CT) scan clearly indicate regions of tissue, lung, and bone that match their position within the original mouse CT scan. Additionally, radiographic films are used with the phantom to demonstrate dose mapping capabilities. The construction methodology presented here can be quickly and easily adapted to create a phantom of any specific small animal given a segmented CT scan of the animal. These physical phantoms are a useful tool to examine individual organ dose and dosimetry within mouse systems that are complicated by density inhomogeneity due to bone and lung regions.

LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation

Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector's intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which can have significant implications in preclinical and clinical ROI imaging applications.

A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications

In this paper, the authors' review the applicability of the open-source GATE Monte Carlo simulation platform based on the GEANT4 toolkit for radiation therapy and dosimetry applications. The many applications of GATE for state-of-the-art radiotherapy simulations are described including external beam radiotherapy, brachytherapy, intraoperative radiotherapy, hadrontherapy, molecular radiotherapy, and in vivo dose monitoring. Investigations that have been performed using GEANT4 only are also mentioned to illustrate the potential of GATE. The very practical feature of GATE making it easy to model both a treatment and an imaging acquisition within the same framework is emphasized. The computational times associated with several applications are provided to illustrate the practical feasibility of the simulations using current computing facilities.

Hybrid microPET imaging for dosimetric applications in mice: improvement of activity quantification in dynamic microPET imaging for accelerated dosimetry applied to 6-[18 F]fluoro-L-DOPA and 2-[18 F]fluoro-L-tyrosine

PURPOSE

Dynamic microPET imaging has advantages over traditional organ harvesting, but is prone to quantification errors in small volumes. Hybrid imaging, where microPET activities are cross-calibrated using post scan harvested organs, can improve quantification. Organ harvesting, dynamic imaging and hybrid imaging were applied to determine the human and mouse radiation dosimetry of 6-[18 F]fluoro-L-DOPA and 2-[18 F]fluoro-L-tyrosine and compared.

PROCEDURES

Two-hour dynamic microPET imaging was performed with both tracers in four separate mice for 18 F-FDOPA and three mice for 18 F-FTYR. Organ harvesting was performed at 2, 5, 10, 30, 60 and 120 min post tracer injection with n = 5 at each time point for 18 F-FDOPA and n = 3 at each time point for 18 F-FTYR. Human radiation dosimetry projected from animal data was calculated for the three different approaches for each tracer using OLINDA/EXM. S-factors for the MOBY phantom were used to calculate the animal dosimetry.

RESULTS

Correlations between dose estimates based on organ harvesting and imaging was improved from r = 0.997 to r = 0.999 for 18 F-FDOPA and from r = 0.985 to r = 0.996 (p < 0.0001 for all) for 18 F-FTYR by using hybrid imaging.

CONCLUSION

Hybrid imaging yields comparable results to traditional organ harvesting while partially overcoming the limitations of pure imaging. It is an advantageous technique in terms of number of animals needed and labour involved.