Respiratory phase-correlated micro-CT imaging of free-breathing rodents

Micro-CT acquisition and image processing to track and characterize pulmonary nodules in mice

X-ray computed tomography is a reliable technique for the detection and longitudinal monitoring of pulmonary nodules. In preclinical stages of diagnostic or therapeutic development, the miniaturized versions of the clinical computed tomography scanners are ideally suited for carrying out translationally-relevant research in conditions that closely mimic those found in the clinic. In this Protocol, we provide image acquisition parameters optimized for low radiation dose, high-resolution and high-throughput computed tomography imaging using three commercially available micro-computed tomography scanners, together with a detailed description of the image analysis tools required to identify a variety of lung tumor types, characterized by specific radiological features. For each animal, image acquisition takes 4-8 min, and data analysis typically requires 10-30 min. Researchers with basic training in animal handling, medical imaging and software analysis should be able to implement this protocol across a wide range of lung cancer models in mice for investigating the molecular mechanisms driving lung cancer development and the assessment of diagnostic and therapeutic agents.

Intrinsic Respiratory Gating for Simultaneous Multi-Mouse μCT Imaging to Assess Liver Tumors

Small animal micro computed tomography (μCT) is an important tool in cancer research and is used to quantify liver and lung tumors. A type of cancer that is intensively investigated with μCT is hepatocellular carcinoma (HCC). μCT scans acquire projections from different angles of the gantry which rotates X-ray source and detector around the animal. Motion of the animal causes inconsistencies between the projections which lead to artifacts in the resulting image. This is problematic in HCC research, where respiratory motion affects the image quality by causing hypodense intensity at the liver edge and smearing out small structures such as tumors. Dealing with respiratory motion is particularly difficult in a high throughput setting when multiple mice are scanned together and projection removal by retrospective respiratory gating may compromise image quality and dose efficiency. In mice, inhalation anesthesia leads to a regular respiration with short gasps and long phases of negligible motion. Using this effect and an iterative reconstruction which can cope with missing angles, we discard the relatively few projections in which the gasping motion occurs. Moreover, since gated acquisition, i.e., acquiring multiple projections from a single gantry angle is not a requirement, this method can be applied to existing scans. We applied our method in a high throughput setting in which four mice with HCC tumors were scanned simultaneously in a multi-mouse bed. To establish a ground truth, we manually selected projections with visible respiratory motion. Our automated intrinsic breathing projection selection achieved an accordance of 97% with manual selection. We reconstructed volumetric images and demonstrated that our intrinsic gating method significantly reduces the hypodense depiction at the cranial liver edge and improves the detectability of small tumors. Furthermore, we show that projection removal in a four mice scan discards only 7.5% more projections than in a single-mouse setting, i.e., four mouse scanning does not substantially compromise dose efficiency or image quality. To the best of our knowledge, no comparable method that combines multi-mouse scans for high throughput, intrinsic respiratory gating, and an available iterative reconstruction has been described for liver tumor imaging before.

Frequency-Selective Computed Tomography: Applications During Periodic Thoracic Motion

We seek to use computed tomography (CT) to characterize regional lung parenchymal deformation during high-frequency and multi-frequency oscillatory ventilation. Periodic motion of thoracic structures results in artifacts of CT images obtained by standard reconstruction algorithms, especially for frequencies exceeding that of the X-ray source rotation. In this paper, we propose an acquisition and reconstruction technique for high-resolution imaging of the thorax during periodic motion. Our technique relies on phase-binning projections according to the frequency of subject motion relative to the scanner rotation, prior to volumetric reconstruction. The mathematical theory and limitations of the proposed technique are presented, and then validated in a simulated phantom as well as a living porcine subject during oscillatory ventilation. The 4-D image sequences obtained using this frequency-selective reconstruction technique yielded high-spatio-temporal resolution of the thorax during periodic motion. We conclude that the frequency-based selection of CT projections is ideal for characterizing dynamic deformations of thoracic structures that are ordinarily obscured by motion artifact using conventional reconstruction techniques.

Evaluation of intrinsic respiratory signal determination methods for 4D CBCT adapted for mice

PURPOSE

4D CT imaging in mice is important in a variety of areas including studies of lung function and tumor motion. A necessary step in 4D imaging is obtaining a respiratory signal, which can be done through an external system or intrinsically through the projection images. A number of methods have been developed that can successfully determine the respiratory signal from cone-beam projection images of humans, however only a few have been utilized in a preclinical setting and most of these rely on step-and-shoot style imaging. The purpose of this work is to assess and make adaptions of several successful methods developed for humans for an image-guided preclinical radiation therapy system.

METHODS

Respiratory signals were determined from the projection images of free-breathing mice scanned on the X-RAD system using four methods: the so-called Amsterdam shroud method, a method based on the phase of the Fourier transform, a pixel intensity method, and a center of mass method. The Amsterdam shroud method was modified so the sharp inspiration peaks associated with anesthetized mouse breathing could be detected. Respiratory signals were used to sort projections into phase bins and 4D images were reconstructed. Error and standard deviation in the assignment of phase bins for the four methods compared to a manual method considered to be ground truth were calculated for a range of region of interest (ROI) sizes. Qualitative comparisons were additionally made between the 4D images obtained using each of the methods and the manual method.

RESULTS

4D images were successfully created for all mice with each of the respiratory signal extraction methods. Only minimal qualitative differences were noted between each of the methods and the manual method. The average error (and standard deviation) in phase bin assignment was 0.24 ± 0.08 (0.49 ± 0.11) phase bins for the Fourier transform method, 0.09 ± 0.03 (0.31 ± 0.08) phase bins for the modified Amsterdam shroud method, 0.09 ± 0.02 (0.33 ± 0.07) phase bins for the intensity method, and 0.37 ± 0.10 (0.57 ± 0.08) phase bins for the center of mass method. Little dependence on ROI size was noted for the modified Amsterdam shroud and intensity methods while the Fourier transform and center of mass methods showed a noticeable dependence on the ROI size.

CONCLUSIONS

The modified Amsterdam shroud, Fourier transform, and intensity respiratory signal methods are sufficiently accurate to be used for 4D imaging on the X-RAD system and show improvement over the existing center of mass method. The intensity and modified Amsterdam shroud methods are recommended due to their high accuracy and low dependence on ROI size.

Advanced Motion Compensation Methods for Intravital Optical Microscopy

Intravital microscopy has emerged in the recent decade as an indispensible imaging modality for the study of the micro-dynamics of biological processes in live animals. Technical advancements in imaging techniques and hardware components, combined with the development of novel targeted probes and new mice models, have enabled us to address long-standing questions in several biology areas such as oncology, cell biology, immunology and neuroscience. As the instrument resolution has increased, physiological motion activities have become a major obstacle that prevents imaging live animals at resolutions analogue to the ones obtained in vitro. Motion compensation techniques aim at reducing this gap and can effectively increase the in vivo resolution. This paper provides a technical review of some of the latest developments in motion compensation methods, providing organ specific solutions.

Non-contact respiration monitoring for in-vivo murine micro computed tomography: characterization and imaging applications

A cone beam micro-CT has previously been utilized along with a pressure-tracking respiration sensor to acquire prospectively gated images of both wild-type mice and various adult murine disease models. While the pressure applied to the abdomen of the subject by this sensor is small and is generally without physiological effect, certain disease models of interest, as well as very young animals, are prone to atelectasis with added pressure, or they generate too weak a respiration signal with this method to achieve optimal prospective gating. In this work we present a new fibre-optic displacement sensor which monitors respiratory motion of a subject without requiring physical contact. The sensor outputs an analogue signal which can be used for prospective respiration gating in micro-CT imaging. The device was characterized and compared against a pneumatic air chamber pressure sensor for the imaging of adult wild-type mice. The resulting images were found to be of similar quality with respect to physiological motion blur; the quality of the respiration signal trace obtained using the non-contact sensor was comparable to that of the pressure sensor and was superior for gating purposes due to its better signal-to-noise ratio. The non-contact sensor was then used to acquire in-vivo micro-CT images of a murine model for congenital diaphragmatic hernia and of 11-day-old mouse pups. In both cases, quality CT images were successfully acquired using this new respiration sensor. Despite the presence of beam hardening artefacts arising from the presence of a fibre-optic cable in the imaging field, we believe this new technique for respiration monitoring and gating presents an opportunity for in-vivo imaging of disease models which were previously considered too delicate for established animal handling methods.

Quantitative monitoring of mouse lung tumors by magnetic resonance imaging

Primary lung cancer remains the leading cause of cancer-related death in the Western world, and the lung is a common site for recurrence of extrathoracic malignancies. Small-animal (rodent) models of cancer can have a very valuable role in the development of improved therapeutic strategies. However, detection of mouse pulmonary tumors and their subsequent response to therapy in situ is challenging. We have recently described MRI as a reliable, reproducible and nondestructive modality for the detection and serial monitoring of pulmonary tumors. By combining respiratory-gated data acquisition methods with manual and automated segmentation algorithms described by our laboratory, pulmonary tumor burden can be quantitatively measured in approximately 1 h (data acquisition plus analysis) per mouse. Quantitative, analytical methods are described for measuring tumor burden in both primary (discrete tumors) and metastatic (diffuse tumors) disease. Thus, small-animal MRI represents a novel and unique research tool for preclinical investigation of therapeutic strategies for treatment of pulmonary malignancies, and it may be valuable in evaluating new compounds targeting lung cancer in vivo.

Dynamic contrast-enhanced micro-CT on mice with mammary carcinoma for the assessment of antiangiogenic therapy response

OBJECTIVE

To evaluate the potential of in vivo dynamic contrast-enhanced micro-computed tomography (DCE micro-CT) for the assessment of antiangiogenic drug therapy response of mice with mammary carcinoma.

METHODS

20 female mice with implanted MCF7 tumours were split into control group and therapy group treated with a known effective antiangiogenic drug. All mice underwent DCE micro-CT for the 3D analysis of functional parameters (relative blood volume [rBV], vascular permeability [K], area under the time-enhancement curve [AUC]) and morphology. All parameters were determined for total, peripheral and central tumour volumes of interest (VOIs). Immunohistochemistry was performed to characterise tumour vascularisation. 3D dose distributions were determined.

RESULTS

The mean AUCs were significantly lower in therapy with P values of 0.012, 0.007 and 0.023 for total, peripheral and central tumour VOIs. K and rBV showed significant differences for the peripheral (P(per)(K) = 0.032, P(per) (rBV) = 0.029), but not for the total and central tumour VOIs (P(total)(K) = 0.108, P(central)(K) = 0.246, P(total) (rBV) = 0.093, P(central) (rBV) = 0.136). Mean tumour volume was significantly smaller in therapy (P (in vivo) = 0.001, P (ex vivo) = 0.005). Histology revealed greater vascularisation in the controls and central tumour necrosis. Doses ranged from 150 to 300 mGy.

CONCLUSIONS

This study indicates the great potential of DCE micro-CT for early in vivo assessment of antiangiogenic drug therapy response.

KEY POINTS

Dynamic contrast enhanced micro-CT (computed tomography) is a new experimental laboratory technique. DCE micro-CT allows early in vivo assessment of antiangiogenic drug therapy response. Pharmaceutical drugs can be tested before translation to clinical practice. Both morphological and functional parameters can be obtained using DCE micro-CT. Antiangiogenic effects can be visualised with DCE micro-CT.

Longitudinal assessment of lung cancer progression in the mouse using in vivo micro-CT imaging

PURPOSE

Small animal micro-CT imaging is being used increasingly in preclinical biomedical research to provide phenotypic descriptions of genomic models. Most of this imaging is coincident with animal death and is used to show the extent of disease as an end point. Longitudinal imaging overcomes the limitation of single time-point imaging because it enables tracking of the natural history of disease and provides qualitative and, where possible, quantitative assessments of the effects of an intervention. The pulmonary system is affected by many disease conditions, such as lung cancer, chronic obstructive pulmonary disease, asthma, and granulomatous disorders. Noninvasive imaging can accurately assess the lung phenotype within the living animal, evaluating not only global lung measures, but also regional pathology. However, imaging the lung in the living animal is complicated by rapid respiratory motion, which leads to image based artifacts. Furthermore, no standard mouse lung imaging protocols exist for longitudinal assessment, with each group needing to develop their own systematic approach.

METHODS

In this article, the authors present an outline for performing longitudinal breath-hold gated micro-CT imaging for the assessment of lung nodules in a mouse model of lung cancer. The authors describe modifications to the previously published intermittent isopressure breath-hold technique including a new animal preparation and anesthesia protocol, implementation of a ring artifact reduction, variable scanner geometry, and polynomial beam hardening correction. In addition, the authors describe a multitime-point data set registration and tumor labeling and tracking strategy.

RESULTS

In vivo micro-CT data sets were acquired at months 2, 3, and 4 posturethane administration in cancer mice (n = 5) and simultaneously in control mice (n = 3). 137 unique lung nodules were identified from the cancer mice while no nodules were detected in the control mice. A total of 411 nodules were segmented and labeled over the three time-points. Lung nodule metrics including RECIST, Ortho, WHO, and 3D volume were determined and extracted. A tumor incidence rate of 30.44 +/- 1.93 SEM for n = 5 was found with identification of nodules as small as 0.11 mm (RECIST) and as large as 1.66 mm (RECIST). In addition, the tumor growth and doubling rate between months 2-3 and 3-4 were calculated. Here, the growth rate was slightly higher in the second period based on the 3D volume data (0.12 +/- 0.13 to 0.13 +/- 0.17 microl) but significantly less based on the linear diameter metrics [RECIST (0.33 +/- 0.19 to 0.17 +/- 0.18 mm); Ortho (0.24 +/- 0.15 to 0.16 +/- 0.15 mm)], indicating the need to understand how each metric is obtained and how to correctly interpret change in tumor size.

CONCLUSIONS

In conclusion, micro-CT imaging provides a unique platform for in vivo longitudinal assessment of pulmonary lung cancer progression and potentially tracking of therapies at very high resolutions. The ability to evaluate the same subject over time provides for a sensitive assay that can be carried out on a smaller sample size. When integrated with image processing and analysis routines as detailed in this study, the data acquired from micro-CT imaging can now provide a very powerful assessment of pulmonary disease outcomes.

Perfusion measurements by micro-CT using prior image constrained compressed sensing (PICCS): initial phantom results

Micro-CT scanning has become an accepted standard for anatomical imaging in small animal disease and genome mutation models. Concurrently, perfusion imaging via tracking contrast dynamics after injection of an iodinated contrast agent is a well-established tool for clinical CT scanners. However, perfusion imaging is not yet commercially available on the micro-CT platform due to limitations in both radiation dose and temporal resolution. Recent hardware developments in micro-CT scanners enable continuous imaging of a given volume through the use of a slip-ring gantry. Now that dynamic CT imaging is feasible, data may be acquired to measure tissue perfusion using a micro-CT scanner (CT Imaging, Erlangen, Germany). However, rapid imaging using micro-CT scanners leads to high image noise in individual time frames. Using the standard filtered backprojection (FBP) image reconstruction, images are prohibitively noisy for calculation of voxel-by-voxel perfusion maps. In this study, we apply prior image constrained compressed sensing (PICCS) to reconstruct images with significantly lower noise variance. In perfusion phantom experiments performed on a micro-CT scanner, the PICCS reconstruction enabled a reduction to 1/16 of the noise variance of standard FBP reconstruction, without compromising the spatial or temporal resolution. This enables a significant increase in dose efficiency, and thus, significantly less exposure time is needed to acquire images amenable to perfusion processing. This reduction in required irradiation time enables voxel-by-voxel perfusion maps to be generated on micro-CT scanners. Sample perfusion maps using a deconvolution-based perfusion analysis are included to demonstrate the improvement in image quality using the PICCS algorithm.

Fully automated intrinsic respiratory and cardiac gating for small animal CT

A fully automated, intrinsic gating algorithm for small animal cone-beam CT is described and evaluated. A parameter representing the organ motion, derived from the raw projection images, is used for both cardiac and respiratory gating. The proposed algorithm makes it possible to reconstruct motion-corrected still images as well as to generate four-dimensional (4D) datasets representing the cardiac and pulmonary anatomy of free-breathing animals without the use of electrocardiogram (ECG) or respiratory sensors. Variation analysis of projections from several rotations is used to place a region of interest (ROI) on the diaphragm. The ROI is cranially extended to include the heart. The centre of mass (COM) variation within this ROI, the filtered frequency response and the local maxima are used to derive a binary motion-gating parameter for phase-sensitive gated reconstruction. This algorithm was implemented on a flat-panel-based cone-beam CT scanner and evaluated using a moving phantom and animal scans (seven rats and eight mice). Volumes were determined using a semiautomatic segmentation. In all cases robust gating signals could be obtained. The maximum volume error in phantom studies was less than 6%. By utilizing extrinsic gating via externally placed cardiac and respiratory sensors, the functional parameters (e.g. cardiac ejection fraction) and image quality were equivalent to this current gold standard. This algorithm obviates the necessity of both gating hardware and user interaction. The simplicity of the proposed algorithm enables adoption in a wide range of small animal cone-beam CT scanners.

Phase-selective image reconstruction of the lungs in small animals using Micro-CT

Gating in small animal imaging can compensate for artifacts due to physiological motion. This paper presents a strategy for sampling and image reconstruction in the rodent lung using micro-CT. The approach involves rapid sampling of free-breathing mice without any additional hardware to detect respiratory motion. The projection images are analyzed post-acquisition to derive a respiratory signal, which is used to provide weighting factors for each projection that favor a selected phase of the respiration (e.g. end-inspiration or end-expiration) for the reconstruction. Since the sampling cycle and the respiratory cycle are uncorrelated, the sets of projections corresponding to any of the selected respiratory phases do not have a regular angular distribution. This drastically affects the image quality of reconstructions based on simple filtered backprojection. To address this problem, we use an iterative reconstruction algorithm that combines the Simultaneous Algebraic Reconstruction Technique with Total Variation minimization (SART-TV). At each SART-TV iteration, backprojection is performed with a set of weighting factors that favor the desired respiratory phase. To reduce reconstruction time, the algorithm is implemented on a graphics processing unit. The performance of the proposed approach was investigated in simulations and in vivo scans of mice with primary lung cancers imaged with our in-house developed dual tube/detector micro-CT system. We note that if the ECG signal is acquired during sampling, the same approach could be used for phase-selective cardiac imaging.