Increased Mortality and Vascular Phenotype in a Knock-In Mouse Model of Retinal Vasculopathy With Cerebral Leukoencephalopathy and Systemic Manifestations.

Background and Purpose- Retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations (RVCL-S) is an autosomal dominant small vessel disease caused by C-terminal frameshift mutations in the TREX1 gene that encodes the major mammalian 3' to 5' DNA exonuclease. RVCL-S is characterized by vasculopathy, especially in densely vascularized organs, progressive retinopathy, cerebral microvascular disease, white matter lesions, and migraine, but the underlying mechanisms are unknown. Methods- Homozygous transgenic RVCL-S knock-in mice expressing a truncated Trex1 (three prime repair exonuclease 1) protein (similar to what is seen in patients) and wild-type littermates, of various age groups, were subjected to (1) a survival analysis, (2) in vivo postocclusive reactive hyperemia and ex vivo Mulvany myograph studies to characterize the microvascular and macrovascular reactivity, and (3) experimental stroke after transient middle cerebral artery occlusion with neurological deficit assessment. Results- The mutant mice show increased mortality starting at midlife (P=0.03 with hazard ratio, 3.14 [95% CI, 1.05-9.39]). The mutants also show a vascular phenotype as evidenced by attenuated postocclusive reactive hyperemia responses (across all age groups; F[1, 65]=5.7, P=0.02) and lower acetylcholine-induced relaxations in aortae (in 20- to 24-month-old mice; RVCL-S knock-in: Emax: 37±8% versus WT: Emax: 65±6%, P=0.01). A vascular phenotype is also suggested by the increased infarct volume seen in 12- to 14-month-old mutant mice at 24 hours after infarct onset (RVCL-S knock-in: 75.4±2.7 mm3 versus WT: 52.9±5.6 mm3, P=0.01). Conclusions- Homozygous RVCL-S knock-in mice show increased mortality, signs of abnormal vascular function, and increased sensitivity to experimental stroke and can be instrumental to investigate the pathology seen in patients with RVCL-S.

Transit time mapping in the mouse brain using time-encoded pCASL.

The cerebral blood flow (CBF) is a potential biomarker for neurological disease. However, the arterial transit time (ATT) of the labeled blood is known to potentially affect CBF quantification. Furthermore, ATT could be an interesting biomarker in itself, as it may reflect underlying macro- and microvascular pathologies. Currently, no optimized magnetic resonance imaging (MRI) sequence exists to measure ATT in mice. Recently, time-encoded labeling schemes have been implemented in rats and humans, enabling ATT mapping with higher signal-to-noise ratio (SNR) and shorter scan time than multi-delay arterial spin labeling (ASL). In this study, we show that time-encoded pseudo-continuous arterial spin labeling (te-pCASL) also enables transit time measurements in mice. As an optimal design that takes the fast blood flow in mice into account, time encoding with 11 sub-boli of 50 ms is proposed to accurately probe the inflow of labeled blood. For perfusion imaging, a separate, traditional pCASL scan was employed. From the six studied brain regions, the hippocampus showed the shortest ATT (169 ± 11 ms) and the auditory/visual cortex showed the longest (284 ± 16 ms). Furthermore, ATT was found to be preserved in old wild-type mice. In a mouse with an induced carotid artery occlusion, prolongation of ATT was shown. In conclusion, this study shows the successful implementation of te-pCASL in mice, making it possible, for the first time, to measure ATT in mice in a time-efficient manner.

Morphological maturation of the mouse brain: An in vivo MRI and histology investigation.

With the wide access to studies of selected gene expressions in transgenic animals, mice have become the dominant species as cerebral disease models. Many of these studies are performed on animals of not more than eight weeks, declared as adult animals. Based on the earlier reports that full brain maturation requires at least three months in rats, there is a clear need to discern the corresponding minimal animal age to provide an "adult brain" in mice in order to avoid modulation of disease progression/therapy studies by ongoing developmental changes. For this purpose, we have studied anatomical brain alterations of mice during their first six months of age. Using T2-weighted and diffusion-weighted MRI, structural and volume changes of the brain were identified and compared with histological analysis of myelination. Mouse brain volume was found to be almost stable already at three weeks, but cortex thickness kept decreasing continuously with maximal changes during the first three months. Myelination is still increasing between three and six months, although most dramatic changes are over by three months. While our results emphasize that mice should be at least three months old when adult animals are needed for brain studies, preferred choice of one particular metric for future investigation goals will result in somewhat varying age windows of stabilization.

Brain maturation of the adolescent rat cortex and striatum: changes in volume and myelination.

Longitudinal studies on brain pathology and assessment of therapeutic strategies rely on a fully mature adult brain to exclude confounds of cerebral developmental changes. Thus, knowledge about onset of adulthood is indispensable for discrimination of developmental phase and adulthood. We have performed a high-resolution longitudinal MRI study at 11.7T of male Wistar rats between 21days and six months of age, characterizing cerebral volume changes and tissue-specific myelination as a function of age. Cortical thickness reaches final value at 1month, while volume increases of cortex, striatum and whole brain end only after two months. Myelin accretion is pronounced until the end of the third postnatal month. After this time, continuing myelination increases in cortex are still seen on histological analysis but are no longer reliably detectable with diffusion-weighted MRI due to parallel tissue restructuring processes. In conclusion, cerebral development continues over the first three months of age. This is of relevance for future studies on brain disease models which should not start before the end of month 3 to exclude serious confounds of continuing tissue development.

Evaluation of acute esophageal radiation-induced damage using magnetic resonance imaging: a feasibility study in mice.

BACKGROUND: Thoracic and head and neck cancer radiation therapy (RT) can cause damage to nearby healthy organs such as the esophagus, causing acute radiation-induced esophageal damage (ARIED). A non-invasive method to detect and monitor ARIED can facilitate optimizing RT to avoid ARIED while improving local tumor control. Current clinical guidelines are limited to scoring the esophageal damage based on the symptoms of patients. Magnetic resonance imaging (MRI) is a non-invasive imaging modality that may potentially visualize radiation-induced organ damage. We investigated the feasibility of using T2-weighted MRI to detect and monitor ARIED using a two-phased study in mice. METHODS: The first phase aimed to establish the optimal dose level at which ARIED is inducible and to determine the time points where ARIED is detectable. Twenty four mice received a single dose delivery of 20 and 40 Gy at proximal and distal spots of 10.0 mm (in diameter) on the esophagus. Mice underwent MRI and histopathology analysis with esophageal resection at two, three, and 4 weeks post-irradiation, or earlier in case mice had to be euthanized due to humane endpoints. In the second phase, 32 mice received a 40 Gy single dose and were studied at two, three, and 7 days post-irradiation. We detected ARIED as a change in signal intensity of the MRI images. We measured the width of the hyperintense area around the esophagus in all mice that underwent MRI prior to and after irradiation. We conducted a blind qualitative comparison between MRI findings and histopathology as the gold standard. RESULTS/CONCLUSIONS: A dose of 40 Gy was needed to induce substantial ARIED. MRI detected ARIED as high signal intensity, visible from 2 days post-irradiation. Quantitative MRI analysis showed that the hyperintense area around the esophagus with severe ARIED was 1.41 mm wider than with no damage and MRI-only mice. The overall sensitivity and specificity were 56 and 43% respectively to detect any form of ARIED. However, in this study MRI correctly detected 100% of severe ARIED cases. Our two-phased preclinical study showed that MRI has the potential to detect ARIED as a change in signal intensity and width of enhancement around the esophagus.

Optical coherence tomography to detect acute esophageal radiation-induced damage in mice: A validation study.

Radiation therapy for patients with non-small-cell lung cancer is hampered by acute radiation-induced toxicity in the esophagus. This study aims to validate that optical coherence tomography (OCT), a minimally invasive imaging technique with high resolution (~10 µm), is able to visualize and monitor acute radiation-induced esophageal damage (ARIED) in mice. We compare our findings with histopathology as the gold standard. Irradiated mice receive a single dose of 40 Gy at proximal and distal spots of the esophagus of 10.0 mm in diameter. We scan mice using OCT at two, three, and seven days post-irradiation. In OCT analysis, we define ARIED as a presence of distorted esophageal layering, change in backscattering signal properties, or change in the esophageal wall thickness. The average esophageal wall thickness is 0.53 mm larger on OCT when ARIED is present based on histopathology. The overall sensitivity and specificity of OCT to detect ARIED compared to histopathology are 94% and 47%, respectively. However, the overall sensitivity of OCT to assess ARIED is 100% seven days post-irradiation. We validate the capability of OCT to detect ARIED induced by high doses in mice. Nevertheless, clinical studies are required to assess the potential role of OCT to visualize ARIED in humans.

Influence of full-length dystrophin on brain volumes in mouse models of Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) affects besides muscle also the brain, resulting in memory and behavioral problems. The consequences of dystrophinopathy on gross macroscopic alterations are unclear. To elucidate the effect of full-length dystrophin expression on brain morphology, we used high-resolution post-mortem MRI in mouse models that either express 0% (mdx), 100% (BL10) or a low amount of full-length dystrophin (mdx-XistΔhs). While absence or low amounts of full-length dystrophin did not significantly affect whole brain volume and skull morphology, we found differences in volume of individual brain structures. The results are in line with observations in humans, where whole brain volume was found to be reduced only in patients lacking both full-length dystrophin and the shorter isoform Dp140.

Automated Ischemic Lesion Segmentation in MRI Mouse Brain Data after Transient Middle Cerebral Artery Occlusion.

Magnetic resonance imaging (MRI) has become increasingly important in ischemic stroke experiments in mice, especially because it enables longitudinal studies. Still, quantitative analysis of MRI data remains challenging mainly because segmentation of mouse brain lesions in MRI data heavily relies on time-consuming manual tracing and thresholding techniques. Therefore, in the present study, a fully automated approach was developed to analyze longitudinal MRI data for quantification of ischemic lesion volume progression in the mouse brain. We present a level-set-based lesion segmentation algorithm that is built using a minimal set of assumptions and requires only one MRI sequence (T2) as input. To validate our algorithm we used a heterogeneous data set consisting of 121 mouse brain scans of various age groups and time points after infarct induction and obtained using different MRI hardware and acquisition parameters. We evaluated the volumetric accuracy and regional overlap of ischemic lesions segmented by our automated method against the ground truth obtained in a semi-automated fashion that includes a highly time-consuming manual correction step. Our method shows good agreement with human observations and is accurate on heterogeneous data, whilst requiring much shorter average execution time. The algorithm developed here was compiled into a toolbox and made publically available, as well as all the data sets.

Precise Anatomic Localization of Accumulated Lipids in Mfp2 Deficient Murine Brains Through Automated Registration of SIMS Images to the Allen Brain Atlas.

Mass spectrometry imaging (MSI) is a powerful tool for the molecular characterization of specific tissue regions. Histochemical staining provides anatomic information complementary to MSI data. The combination of both modalities has been proven to be beneficial. However, direct comparison of histology based and mass spectrometry-based molecular images can become problematic because of potential tissue damages or changes caused by different sample preparation. Curated atlases such as the Allen Brain Atlas (ABA) offer a collection of highly detailed and standardized anatomic information. Direct comparison of MSI brain data to the ABA allows for conclusions to be drawn on precise anatomic localization of the molecular signal. Here we applied secondary ion mass spectrometry imaging at high spatial resolution to study brains of knock-out mouse models with impaired peroxisomal ß-oxidation. Murine models were lacking D-multifunctional protein (MFP2), which is involved in degradation of very long chain fatty acids. SIMS imaging revealed deposits of fatty acids within distinct brain regions. Manual comparison of the MSI data with the histologic stains did not allow for an unequivocal anatomic identification of the fatty acids rich regions. We further employed an automated pipeline for co-registration of the SIMS data to the ABA. The registration enabled precise anatomic annotation of the brain structures with the revealed lipid deposits. The precise anatomic localization allowed for a deeper insight into the pathology of Mfp2 deficient mouse models.

Interactive local super-resolution reconstruction of whole-body MRI mouse data: a pilot study with applications to bone and kidney metastases.

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.

Segmentation and visual analysis of whole-body mouse skeleton microSPECT.

Whole-body SPECT small animal imaging is used to study cancer, and plays an important role in the development of new drugs. Comparing and exploring whole-body datasets can be a difficult and time-consuming task due to the inherent heterogeneity of the data (high volume/throughput, multi-modality, postural and positioning variability). The goal of this study was to provide a method to align and compare side-by-side multiple whole-body skeleton SPECT datasets in a common reference, thus eliminating acquisition variability that exists between the subjects in cross-sectional and multi-modal studies. Six whole-body SPECT/CT datasets of BALB/c mice injected with bone targeting tracers (99m)Tc-methylene diphosphonate ((99m)Tc-MDP) and (99m)Tc-hydroxymethane diphosphonate ((99m)Tc-HDP) were used to evaluate the proposed method. An articulated version of the MOBY whole-body mouse atlas was used as a common reference. Its individual bones were registered one-by-one to the skeleton extracted from the acquired SPECT data following an anatomical hierarchical tree. Sequential registration was used while constraining the local degrees of freedom (DoFs) of each bone in accordance to the type of joint and its range of motion. The Articulated Planar Reformation (APR) algorithm was applied to the segmented data for side-by-side change visualization and comparison of data. To quantitatively evaluate the proposed algorithm, bone segmentations of extracted skeletons from the correspondent CT datasets were used. Euclidean point to surface distances between each dataset and the MOBY atlas were calculated. The obtained results indicate that after registration, the mean Euclidean distance decreased from 11.5±12.1 to 2.6±2.1 voxels. The proposed approach yielded satisfactory segmentation results with minimal user intervention. It proved to be robust for "incomplete" data (large chunks of skeleton missing) and for an intuitive exploration and comparison of multi-modal SPECT/CT cross-sectional mouse data.

Articulated whole-body atlases for small animal image analysis: construction and applications.

PURPOSE: Using three publicly available small-animal atlases (Sprague-Dawley rat, MOBY, and Digimouse), we built three articulated atlases and present several applications in the scope of molecular imaging. PROCEDURES: Major bones/bone groups were manually segmented for each atlas skeleton. Then, a kinematic model for each atlas was built: each joint position was identified and the corresponding degrees of freedom were specified. RESULTS: The articulated atlases enable automated registration into a common coordinate frame of multimodal small-animal imaging data. This eliminates the postural variability (e.g., of the head, back, and front limbs) that occurs in different time steps and due to modality differences and nonstandardized acquisition protocols. CONCLUSIONS: The articulated atlas proves to be a useful tool for multimodality image combination, follow-up studies, and image processing in the scope of molecular imaging. The proposed models were made publicly available.

Classifier-assisted metric for chromosome pairing.

Cytogenetics plays a central role in the detection of chromosomal abnormalities and in the diagnosis of genetic diseases. A karyogram is an image representation of human chromosomes arranged in order of decreasing size and paired in 23 classes. In this paper we propose an approach to automatically pair the chromosomes into a karyogram, using the information obtained in a rough SVM-based classification step, to help the pairing process mainly based on similarity metrics between the chromosomes. Using a set of geometric and band pattern features extracted from the chromosome images, the algorithm is formulated on a Bayesian framework, combining the similarity metric with the results from the classifier. The solution is obtained solving a mixed integer program. Two datasets with contrasting quality levels and 836 chromosomes each were used to test and validate the algorithm. Relevant improvements with respect to the algorithm described by the authors in [1] were obtained with average paring rates above 92%, close to the rates obtained by human operators.

A novel metric for bone marrow cells chromosome pairing.

Karyotyping is a set of procedures, in the scope of the cytogenetics, that produces a visual representation of the 46 chromosomes observed during the metaphase step of the cellular division, called mitosis, paired and arranged in decreasing order of size. Automatic pairing of bone marrow cells is a difficult task because these chromosomes appear distorted, overlapped, and their images are usually blurred with undefined edges and low level of detail. In this paper, a new metric is proposed to compare this type of chromosome images toward the design of an automatic pairing algorithm for leukemia diagnostic purposes. Besides the features used in the traditional karyotyping procedures, a new feature, based on mutual information , is proposed to increase the discriminate power of the G-banding pattern dissimilarity between chromosomes and improve the performance of the classifier. The pairing algorithm is formulated as a combinatorial optimization problem where the distances between homologous chromosomes are minimized and the distances between nonhomologous ones are maximized. The optimization task is solved by using an integer programming approach. A new bone marrow chromosome dataset--Lisbon-K1 (LK1) chromosome dataset with 9200 chromosomes---was build for this study. These chromosomes have much lower quality than the classic Copenhagen, Edinburgh, and Philadelphia datasets, and its classification and pairing is therefore more difficult. Experiments using real images from the LK(1) and Grisan et al. datasets based on a leave-one-out cross-validation strategy are performed to test and validate the pairing algorithm.

Automatic chromosome pairing using mutual information.

Cytogenetics is a key tool in the detection of acquired chromosomal abnormalities and in the diagnosis of genetic diseases such as leukemia. The karyotyping is a set of procedures, in the scope of the cytogenetics, that produces a visual representation of the 46 chromosomes (called karyogram), paired and arranged in decreasing order of size. The pairing procedure aims to identify all pairs of homologous chromosomes.The pairing criterion is based on dimensional, morphological,and textural features similarity. This process is time consuming when performed manually, and demanding from a technical point of view. An automatic pairing algorithm would thus bring benefits, but it remains an open problem to date.In this paper a new strategy for automatic pairing of homologous chromosomes is proposed. Besides the traditional features described in the literature, the Mutual Information (MI) is used to discriminate chromosome textural differences. A supervised non-linear classifier is trained by using manual classifications provided by expert technicians, combining the different features computed from each pair.Simulations using 836 real chromosome images, obtained with a Leica Optical Microscope DM 2500, in a leave-one-out cross validation fashion, were performed for training and testing the algorithm.Promising and relevant results were found, despite the poor quality of the original chromosome images, contrasting with state-of the-art algorithms and datasets found in the literature.