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Tomography is published by MDPI from Volume 7 Issue 1 (2021). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Grapho, LLC.

Tomography, Volume 3, Issue 1 (March 2017) – 8 articles

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Communication
MRI-Guided Stereotactic Biopsy of Murine GBM for Spatiotemporal Molecular Genomic Assessment
Tomography 2017, 3(1), 9-15; https://doi.org/10.18383/j.tom.2017.00112 - 01 Sep 2017
Cited by 3 | Viewed by 148
Abstract
Brain tumor biopsies that are routinely performed in clinical settings significantly aid in diagnosis and staging. The aim of this study is to develop and evaluate a methodological image-guided approach that would allow for routine sampling of glioma tissue from orthotopic mouse brain [...] Read more.
Brain tumor biopsies that are routinely performed in clinical settings significantly aid in diagnosis and staging. The aim of this study is to develop and evaluate a methodological image-guided approach that would allow for routine sampling of glioma tissue from orthotopic mouse brain tumor models. A magnetic resonance imaging-guided biopsy method is presented to allow for spatially precise stereotaxic sampling of a murine glioma coupled with genome-scale technology to provide unbiased characterization of intra- and intertumoral clonal heterogeneity. Longitudinal and multiregional sampling of intracranial tumors allows for successful collection of tumor biopsy samples, thus allowing for a pathway-enrichment analysis and a transcriptional profiling of RNA sequencing data. Spatiotemporal gene expression pattern variations revealing genomic heterogeneity were found. Full article
Article
A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials
Tomography 2017, 3(1), 41-49; https://doi.org/10.18383/j.tom.2016.00286 - 01 Aug 2017
Cited by 15 | Viewed by 214
Abstract
The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we [...] Read more.
The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T1 and T2* changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials. Full article
Article
Intrathoracic Fat Measurements Using Multidetector Computed Tomography (MDCT): Feasibility and Reproducibility
Tomography 2017, 3(1), 33-40; https://doi.org/10.18383/j.tom.2017.00103 - 01 Aug 2017
Cited by 3 | Viewed by 133
Abstract
Intrathoracic fat volume, more specifically, epicardial fat volume, is an emerging imaging biomarker of adverse cardiovascular events. The purpose of this work is to show the feasibility and reproducibility of intrathoracic fat volume measurement applied to contrast-enhanced multidetector computed tomography images. A retrospective [...] Read more.
Intrathoracic fat volume, more specifically, epicardial fat volume, is an emerging imaging biomarker of adverse cardiovascular events. The purpose of this work is to show the feasibility and reproducibility of intrathoracic fat volume measurement applied to contrast-enhanced multidetector computed tomography images. A retrospective cohort study of 62 subjects free of cardiovascular disease (55% females, age = 49 ± 11 years) conducted from 2008 to 2011 formed the study group. Intrathoracic fat volume was defined as all fat voxels measuring −50 to −250 Hounsfield Unit within the intrathoracic cavity from the level of the pulmonary artery bifurcation to the heart apex. The intrathoracic fat was separated into epicardial and extrapericardial fat by tracing the pericardium. The measurements were obtained by 2 readers and compared for interrater reproducibility. The fat volume measurements for the study group were 141 ± 72 cm3 for intrathoracic fat, 58 ± 27 cm3 for epicardial fat, and 84 ± 50 cm3 for extrapericardial fat. There was no statistically significant difference in intrathoracic fat volume measurements between the 2 readers, with correlation coefficients of 0.88 (P = .55) for intrathoracic fat volume and −0.12 (P = .33) for epicardial fat volume. Voxel-based measurement of intrathoracic fat, including the separation into epicardial and extrapericardial fat, is feasible and highly reproducible from multidetector computed tomography scans. Full article
Article
DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response
Tomography 2017, 3(1), 23-32; https://doi.org/10.18383/j.tom.2016.00241 - 01 Aug 2017
Cited by 37 | Viewed by 255
Abstract
This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) [...] Read more.
This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6–8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature–map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature–map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response. Full article
Article
Quantitative Analysis of the Spatial Distribution of Metastatic Brain Lesions
Tomography 2017, 3(1), 16-22; https://doi.org/10.18383/j.tom.2016.00268 - 01 Aug 2017
Cited by 7 | Viewed by 130
Abstract
Brain metastases (BMs) are the most common intracranial malignancy and afflict ∼10%–20% of patients with cancer. BMs tend to present at the boundaries of gray and white matter because of the distribution of small vessels. In addition, metastases may not be randomly distributed [...] Read more.
Brain metastases (BMs) are the most common intracranial malignancy and afflict ∼10%–20% of patients with cancer. BMs tend to present at the boundaries of gray and white matter because of the distribution of small vessels. In addition, metastases may not be randomly distributed across gross anatomical regions of the brain, but this has not previously been quantified. We retrospectively analyzed a series of 28 patients with recurrent BMs with a total of 150 lesions. Each lesion was manually defined based on T1 gadolinium-enhanced imaging. Standard brain atlases were used to identify the anatomical brain region affected by each BM and the frequency of metastases in each region was compared with the expected probability, which was assumed to be a random distribution based on the brain volume. After correction for multiple comparisons, the paracingulate gyrus was found to have a statistically significant increase (P = 4.731 × 10−9) in the rate of BMs relative to the random spatial distribution. A nonstochastic spatial distribution of metastases may be used to guide partial brain radiotherapy with risk-adapted dose delivery and reduce the risk of neurotoxicity due to overtreatment. Full article
Communication
Ferritin–EGFP Chimera as an Endogenous Dual-Reporter for Both Fluorescence and Magnetic Resonance Imaging in Human Glioma U251 Cells
Tomography 2017, 3(1), 1-8; https://doi.org/10.18383/j.tom.2015.00181 - 01 Aug 2017
Cited by 5 | Viewed by 139
Abstract
A unique hybrid protein ferritin–enhanced green fluorescent protein (EGFP) was built to serve as an endogenous dual reporter for both fluorescence and magnetic resonance imaging (MRI). It consists of a human ferritin heavy chain (an iron-storage protein) at the N terminus, a flexible [...] Read more.
A unique hybrid protein ferritin–enhanced green fluorescent protein (EGFP) was built to serve as an endogenous dual reporter for both fluorescence and magnetic resonance imaging (MRI). It consists of a human ferritin heavy chain (an iron-storage protein) at the N terminus, a flexible polypeptide in the middle as a linker, and an EGFP at the C terminus. Through antibiotic screening, we established stable human glioma U251 cell strains that expressed ferritin–EGFP under the control of tetracycline. These cells emitted bright green fluorescence and were easily detected by a fluorescent microscope. Ferritin–EGFP overexpression proved effective in triggering obvious intracellular iron accumulation as shown by Prussian blue staining and by MRI. Further, we found that ferritin–EGFP overexpression did not cause proliferation differences between experimental and control group cells when ferritin–EGFP was expressed for <96 hours. Application of this novel ferritin–EGFP chimera has a promising future for combined optical and MRI approaches to study in vivo imaging at a cellular level. Full article
Article
Low-Noise Active Decoupling Circuit and its Application to 13C Cryogenic RF Coils at 3 T
Tomography 2017, 3(1), 60-66; https://doi.org/10.18383/j.tom.2016.00280 - 01 Mar 2017
Cited by 10 | Viewed by 191
Abstract
We analyze the loss contributions in a small, 50-mm-diameter receive-only coil for carbon-13 (13C) magnetic resonance imaging at 3 T for 3 different circuits, which, including active decoupling, are compared in terms of their Q-factors and signal-to-noise ratio (SNR). The results [...] Read more.
We analyze the loss contributions in a small, 50-mm-diameter receive-only coil for carbon-13 (13C) magnetic resonance imaging at 3 T for 3 different circuits, which, including active decoupling, are compared in terms of their Q-factors and signal-to-noise ratio (SNR). The results show that a circuit using unsegmented tuning and split matching capacitors can provide >20% SNR enhancement at room temperature compared with that using more traditional designs. The performance of the proposed circuit was also measured when cryogenically cooled to 105 K, and an additional 1.6-fold SNR enhancement was achieved on a phantom. The enhanced circuit performance is based on the low capacitance needed to match to 50 Ω when coil losses are low, which significantly reduces the proportion of the current flowing through the matching network and therefore minimizes this loss contribution. This effect makes this circuit particularly suitable for receive-only cryogenic coils and/or small coils for low-gamma nuclei. Full article
Article
An MR-Based Viscosity-Type Regularization Method for Electrical Property Tomography
Tomography 2017, 3(1), 50-59; https://doi.org/10.18383/j.tom.2016.00283 - 01 Mar 2017
Cited by 11 | Viewed by 240
Abstract
Here, a method based on viscosity-type regularization is proposed for magnetic resonance electrical property tomography (MREPT) to mitigate persistent artifacts when it is used to reconstruct a map of electrical properties based on data from a magnetic resonance imaging scanner. The challenges for [...] Read more.
Here, a method based on viscosity-type regularization is proposed for magnetic resonance electrical property tomography (MREPT) to mitigate persistent artifacts when it is used to reconstruct a map of electrical properties based on data from a magnetic resonance imaging scanner. The challenges for solving the corresponding partial differential equation (PDE) are discussed in detail. The existing artifacts in the numerical results are pointed out and classified. The methods in the literature for MREPT are mainly based on an assumption of local homogeneity, which makes the approach simple but leads to artifacts in the transition region where electrical properties vary rapidly. Recent work has focused on eliminating the assumption of local homogeneity, and one of the solutions is convection–reaction MREPT that is based on a first-order PDE. Numerical solutions of the PDE have persistent artifacts in certain regions and global spurious oscillations. Here, a method based on viscosity-type regularization is proposed to effectively mitigate the aforementioned problems. Finite difference method is used for discretizing the governing PDE. Numerical experiments are presented to analyze the problem in detail. Electrical properties of different phantoms are successfully retrieved. The efficiency, accuracy, and noise tolerance of the proposed method are illustrated with numerical results. Full article
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