A thorough review of the q-space technique is presented starting from a discussion of Fick’s laws. The work presented here is primarily conceptual, theoretical and hopefully pedagogical. We offered the notion of molecular concentration to unify Fick’s laws and diffusion MRI within a coherent conceptual framework. The fundamental relationship between diffusion MRI and the Fick’s laws are carefully established. The conceptual and theoretical basis of the q-space technique is investigated from first principles.
MRI diffusion tensor imaging (DTI) studies of white matter integrity in behavioral variant frontotemporal dementia have consistently shown involvement of frontal and temporal white matter, corresponding to regional loss of cortical volume. Volumetric imaging has a suboptimal sensitivity as a diagnostic tool and thus we wanted to explore if DTI is a better method to discriminate patients and controls than volumetric imaging. We examined the anterior cingulum bundle in 14 patients with behavioral variant frontotemporal dementia and 22 healthy controls using deterministic manual diffusion tensor tractography, and compared DTI parameters with two measures of cortical atrophy, VBM and cortical thickness, of the anterior cingulate cortex (ACC). Statistically significant changes between patients and controls were detected in all DTI parameters, with large effect sizes. ROC-AUC was for the best DTI parameters: 0.92 (fractional anisotropy) to 0.97 (radial diffusivity), 0.82 for the best cortical parameter, VBM of the ACC. Results from the AUC were confirmed with binary logistic regression analysis including demographic variables, but only for fractional anisotropy and mean diffusivity. Ability to classify patient/nonpatient status was significantly better for mean diffusivity vs. VBM (p=0.031), and borderline significant for fractional anisotropy vs. VBM (p=0.062). The results indicate that DTI could offer advantages in comparison with the assessment of cortical volume in differentiating patients with behavioral variant frontotemporal dementia and controls.
Diffusion kurtosis imaging (DKI) is an emerging technique with the potential to quantify properties of tissue microstructure that may not be observable using diffusion tensor imaging (DTI). In order to help design DKI studies and improve interpretation of DKI results, we employed statistical power analysis to characterize three aspects of variability in four DKI parameters; the mean diffusivity, fractional anisotropy, mean kurtosis, and radial kurtosis. First, we quantified the variability in terms of the group size required to obtain a statistical power of 0.9. Second, we investigated the relative contribution of imaging and post-processing noise to the total variance, in order to estimate the benefits of longer scan times versus the inclusion of more subjects. Third, we evaluated the potential benefit of including additional covariates such as the size of the structure when testing for differences in group means. The analysis was performed in three major white matter structures of the brain: the superior cingulum, the corticospinal tract, and the mid-sagittal corpus callosum, extracted using diffusion tensor tractography and DKI data acquired in a healthy cohort. The results showed heterogeneous variability across and within the white matter structures. Thus, the statistical power varies depending on parameter and location, which is important to consider if a pathogenesis pattern is inferred from DKI data. In the data presented, inter-subject differences contributed more than imaging noise to the total variability, making it more efficient to include more subjects rather than extending the scan-time per subject. Finally, strong correlations between DKI parameters and the structure size were found for the cingulum and corpus callosum. Structure size should thus be considered when quantifying DKI parameters, either to control for its potentially confounding effect, or as a means of reducing unexplained variance.
In this paper we present a benchmarking framework for the validation of cardiac motion analysis algorithms. The reported methods are the response to an open challenge that was issued to the medical imaging community through a MICCAI workshop. The database included magnetic resonance (MR) and 3D ultrasound (3DUS) datasets from a dynamic phantom and 15 healthy volunteers. Participants processed 3D tagged MR datasets (3DTAG), cine steady state free precession MR datasets (SSFP) and 3DUS datasets, amounting to 1158 image volumes. Ground-truth for motion tracking was based on 12 landmarks (4 walls at 3 ventricular levels). They were manually tracked by two observers in the 3DTAG data over the whole cardiac cycle, using an in-house application with 4D visualization capabilities. The median of the inter-observer variability was computed for the phantom dataset (0.77 mm) and for the volunteer datasets (0.84 mm). The ground-truth was registered to 3DUS coordinates using a point based similarity transform. Four institutions responded to the challenge by providing motion estimates for the data: Fraunhofer MEVIS (MEVIS), Bremen, Germany; Imperial College London - University College London (IUCL), UK; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Inria-Asclepios project (INRIA), France. Details on the implementation and evaluation of the four methodologies are presented in this manuscript. The manually tracked landmarks were used to evaluate tracking accuracy of all methodologies. For 3DTAG, median values were computed over all time frames for the phantom dataset (MEVIS=1.20mm, IUCL=0.73 mm, UPF=1.10mm, INRIA=1.09 mm) and for the volunteer datasets (MEVIS=1.33 mm, IUCL=1.52 mm, UPF=1.09 mm, INRIA=1.32 mm). For 3DUS, median values were computed at end diastole and end systole for the phantom dataset (MEVIS=4.40 mm, UPF=3.48 mm, INRIA=4.78 mm) and for the volunteer datasets (MEVIS=3.51 mm, UPF=3.71 mm, INRIA=4.07 mm). For SSFP, median values were computed at end diastole and end systole for the phantom dataset(UPF=6.18 mm, INRIA=3.93 mm) and for the volunteer datasets (UPF=3.09 mm, INRIA=4.78 mm). Finally, strain curves were generated and qualitatively compared. Good agreement was found between the different modalities and methodologies, except for radial strain that showed a high variability in cases of lower image quality.
BACKGROUND: The purpose of the study was to develop a method for analysis of diffusion parameters along white matter (WM) tracts, using spatial normalization based on anatomical landmarks, and to introduce the apparent area coefficient (AAC). The method’s applicability was tested in the inferior fronto-occipital fasciculus (IFO) in patients with progressive supranuclear palsy (PSP) and healthy controls (HCs). METHODS: A framework for analysis of diffusion parameters was developed. Spatial normalization of the tracts was performed using anatomical landmarks, to avoid deformations caused by cerebral atrophy. Initially, 38 HCs were used to optimize a threshold for the minimal size of regions that differ between groups. The fractional anisotropy, mean diffusivity, AAC, and the hemispheric asymmetry index (AI), were compared between 11 PSP patients and 15 HCs. RESULTS: The method was feasible for analysis of PSP patients and HCs. The AI showed that the observed hemispheric asymmetry of AAC was significantly larger in PSP patients compared with HCs in small regions of the IFO. CONCLUSIONS: The method was successfully employed for analysis of diffusion parameters along the IFO in a patient group. This method can be potentially useful in studies of WM diseases, with or without cerebral atrophy.
In this paper, we propose a stochastic model of photoplethysmographic signals that is able to synthesize an arbitrary number of other statistically equivalent signals to the one under analysis. To that end, we first preprocess the pulse signal to normalize and time-align pulses. In a second stage, we design a single-pulse model, which consists of ten parameters. In the third stage, the time evolution of this ten-parameter vector is approximated by means of two autoregressive moving average models, one for the trend and one for the residue; this model is applied after a decorrelation step which let us to process each vector component in parallel. The experiments carried out show that the model we here propose is able to maintain the main features of the original signal; this is accomplished by means of both a linear spectral analysis and also by comparing two measures obtained from a nonlinear analysis. Finally, we explore the capability of the model to: 1) track physical activity; 2) obtain statistics of clinical parameters by model sampling; and 3) recover corrupted or missing signal epochs by synthesis.
The purpose of this study was to quantify and model various types of cell death for a small-cell lung cancer (SCLC) cell line (U1690) after exposure to a 137Cs source and as well as to compare the linear-quadratic (LQ) and repairable-conditionally repairable model (RCR). This study is based on four different experiments that were taken place at Cancer Centrum Karolinska (CCK). A human small-cell lung cancer (SCLC) cell line after the exposure to a 137Cs source was used for the extraction of the clonogenic cell survival curve. Additionally, for the determination and quantification of various modes of cell death the method of fluorescence staining was implemented, where the cell deaths were categorized based on morphological characteristics. The percentage of cells in each phase of the cell cycle was investigated with flow cytometry analysis. The quantification of senescent cells was performed by staining the samples with senescence-associated β-galactosidase (SA-β-Gal) solution and then scoring as senescent cells those that had incorporated the substance. These data were introduced into a maximum likelihood fitting to calculate the best estimates of the parameters used by the examined model. In this model, the modes of cell death are divided into three categories: apoptotic, senescent and other types of cell death (necrotic/apoptotic, necrotic, micronuclei and giant). In the clonogenic cell survival assay, the fitting of the RCR model gives a χ(2)-value of 6.10 whereas for the LQ model became 9.61. In the fluorescence microscopy and senescence assay, the probability of the three different modes of cell death on day 2 seems to increases with a dose up to about 10 Gy where there is saturation. On day 7 a significant induction of apoptosis in a dose- and time-dependent manner was evident, whereas senescence was slightly increased in response to dose but not to time. As for the ’other types of cell death’ mode on day 7 showed a higher probability than the one on day 2 and as well as a prominent dose-dependence. The RCR model fits better to the experimental data than the LQ model. On day 2 there is a slight increase of the apoptotic and senescent probability with dose. On the other hand, on day 7 the shape of the curve of apoptosis differs and a sigmoidal increase with dose is observed. At both time-points, the present model fits the data reasonably well. Due to the fact that the clonogenic survival does not coincide with the one extracted from the fluorescence microscopy, a more accurate way to quantify cell death needs to be used, e.g. computerized video time-lapse (CVTL).
Knowledge of microstructural features of nerve fascicles, such as their axon diameter, is crucial for understanding normal function in the central and peripheral nervous systems as well as assessing changes due to pathologies. In this study double-pulsed field gradient (d-PFG) filtered MRI was used to map the average axon diameter (AAD) in porcine spinal cord, which was then compared to AADs measured with optical microscopy of the same specimen, as a way to further validate this new MRI method. A novel 3D d-PFG acquisition scheme was used to obtain AADs in each voxel of a coronal slice of rat brain corpus callosum. AAD measurements were also acquired using optical microscopy performed on histological sections and validated using a glass capillary array phantom.
Spectral editing with CP and INEPT in (13)C MAS NMR enables identification of rigid and mobile molecular segments in concentrated assemblies of surfactants, lipids, and/or proteins. In order to get stricter definitions of the terms "rigid" and "mobile", as well as resolving some ambiguities in the interpretation of CP and INEPT data, we have developed a theoretical model for calculating the CP and INEPT intensities as a function of rotational correlation time τc and C-H bond order parameter SCH, taking the effects of MAS into account. According to the model, the range of τc can at typical experimental settings (5kHz MAS, 1ms ramped CP at 80-100kHz B1 fields) be divided into four regimes: fast (τc0.1ms). In the fast regime, the CP and INEPT intensities are independent of τc, but strongly dependent on |SCH|, with a cross-over from dominating INEPT to dominating CP at |SCH|>0.1. In the intermediate regime, neither CP nor INEPT yield signal on account of fast T1ρ and T2 relaxation. In both the fast-intermediate and slow regimes, there is exclusively CP signal. The theoretical predictions are tested by experiments on the glass-forming surfactant n-octyl-β-d-maltoside, for which τc can be varied continuously in the nano- to millisecond range by changing the temperature and the hydration level. The atomistic details of the surfactant dynamics are investigated with MD simulations. Based on the theoretical model, we propose a procedure for calculating CP and INEPT intensities directly from MD simulation trajectories. While MD shows that there is a continuous gradient of τc from the surfactant polar headgroup towards the methyl group at the end of the hydrocarbon chain, analysis of the experimental CP and INEPT data indicates that this gradient gets steeper with decreasing temperature and hydration level, eventually spanning four orders of magnitude at completely dry conditions.
Despite recognition that nearly one-third of the 6300 amphibian species are threatened with extinction, our understanding of the general ecology and population status of many amphibians is relatively poor. A widely-used method for monitoring amphibians involves injecting captured individuals with unique combinations of colored visible implant elastomer (VIE). We compared VIE identification to a less-invasive method - computer-assisted photographic identification (photoID) - in endangered Jollyville Plateau salamanders (Eurycea tonkawae), a species with a known range limited to eight stream drainages in central Texas. We based photoID on the unique pigmentation patterns on the dorsal head region of 1215 individual salamanders using identification software Wild-ID. We compared the performance of photoID methods to VIEs using both ’high-quality’ and ’low-quality’ images, which were taken using two different camera types and technologies. For high-quality images, the photoID method had a false rejection rate of 0.76% compared to 1.90% for VIEs. Using a comparable dataset of lower-quality images, the false rejection rate was much higher (15.9%). Photo matching scores were negatively correlated with time between captures, suggesting that evolving natural marks could increase misidentification rates in longer term capture-recapture studies. Our study demonstrates the utility of large-scale capture-recapture using photo identification methods for Eurycea and other species with stable natural marks that can be reliably photographed.
