Iterative Deconvolution Approach Research Articles

Quantitative myocardial first-pass cardiovascular magnetic resonance perfusion imaging using hyperpolarized [1-13C] pyruvate

BackgroundThe feasibility of absolute myocardial blood flow quantification and suitability of hyperpolarized [1-13C] pyruvate as contrast agent for first-pass cardiovascular magnetic resonance (CMR) perfusion measurements are investigated with simulations and demonstrated in vivo in a swine model.MethodsA versatile simulation framework for hyperpolarized CMR subject to physical, physiological and technical constraints was developed and applied to investigate experimental conditions for accurate perfusion CMR with hyperpolarized [1-13C] pyruvate. Absolute and semi-quantitative perfusion indices were analyzed with respect to experimental parameter variations and different signal-to-noise ratio (SNR) levels. Absolute myocardial blood flow quantification was implemented with an iterative deconvolution approach based on Fermi functions. To demonstrate in vivo feasibility, velocity-selective excitation with an echo-planar imaging readout was used to acquire dynamic myocardial stress perfusion images in four healthy swine. Arterial input functions were extracted from an additional image slice with conventional excitation that was acquired within the same heartbeat.ResultsSimulations suggest that obtainable SNR and B0 inhomogeneity in vivo are sufficient for the determination of absolute and semi-quantitative perfusion with ≤25% error. It is shown that for expected metabolic conversion rates, metabolic conversion of pyruvate can be neglected over the short duration of acquisition in first-pass perfusion CMR. In vivo measurements suggest that absolute myocardial blood flow quantification using hyperpolarized [1-13C] pyruvate is feasible with an intra-myocardial variability comparable to semi-quantitative perfusion indices.ConclusionThe feasibility of quantitative hyperpolarized first-pass perfusion CMR using [1-13C] pyruvate has been investigated in simulations and demonstrated in swine. Using an approved and metabolically active compound is envisioned to increase the value of hyperpolarized perfusion CMR in patients.

Resolving the Detailed Spatiotemporal Slip Evolution of Deep Tremor in Western Japan

AbstractWe study the detailed spatiotemporal behavior of deep tremor in western Japan through the development and application of a new slip inversion method. Although many studies now recognize tremor as shear slip along the plate interface manifested in low‐frequency earthquake (LFE) swarms, a conventional slip inversion analysis is not available for tremor due to insufficient knowledge of source locations and Green's functions. Here we introduce synthetic template waveforms, which are typical tremor waveforms obtained by stacking LFE seismograms at arranged points along the plate interface. Using these synthetic template waveforms as substitutes for Green's functions, we invert the continuous tremor waveforms using an iterative deconvolution approach with Bayesian constraints. We apply this method to two tremor burst episodes in western and central Shikoku, Japan. The estimated slip distribution from a 12 day tremor burst episode in western Shikoku is heterogeneous, with several patchy areas of slip along the plate interface where rapid moment releases with durations of <100 s regularly occur. We attribute these heterogeneous spatiotemporal slip patterns to heterogeneous material properties along the plate interface. For central Shikoku, where we focus on a tremor burst episode that occurred coincidentally with a very low frequency earthquake (VLF), we observe that the source size of the VLF is much larger than that estimated from tremor activity in western Shikoku. These differences in the size of the slip region may dictate the visibility of VLF signals in observed seismograms, which has implications for the mechanics of slow earthquakes and subduction zone processes.

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 [11C] 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.

Deconvolution of mechanical properties of thin films from nanoindentation measurement via finite element optimization

A deconvolution method that combines nanoindentation testing with finite element analysis was developed to determine elastic modulus of thin films in a film-substrate bilayer system. In this method, an iterative deconvolution approach was developed to optimize the load–displacement curve obtained from a finite element nanoindentation model towards the experimentally measured curve. The method was verified by using SiNx/Si and Ni/Si film/substrate bilayer systems fabricated under different deposition conditions. The results obtained from this method agree very well with those from an empirical method.

MRI data driven partial volume effects correction in PET imaging using 3D local multi-resolution analysis

PET partial volume effects (PVE) resulting from the limited resolution of PET scanners is still a quantitative issue that PET/MRI scanners do not solve by themselves. A recently proposed voxel-based locally adaptive 3D multi-resolution PVE correction based on the mutual analysis of wavelet decompositions was applied on 12 clinical 18F-FLT PET/T1 MRI images of glial tumors, and compared to a PET only voxel-wise iterative deconvolution approach. Quantitative and qualitative results demonstrated the interest of exploiting PET/MRI information with higher uptake increases (19±8% vs. 11±7%, p=0.02), as well as more convincing visual restoration of details within tumors with respect to deconvolution of the PET uptake only. Further studies are now required to demonstrate the accuracy of this restoration with histopathological validation of the uptake in tumors.

SU‐E‐T‐294: A Method for Dosimetric Verification of Exit Dose Using Deconvolution of Integrated Cone Beam CT Images to Obtain Incident Fluence for Dose Reconstruction

Purpose: To create a method of determining in vivo patient dosimetry from exit EPID images by iterative determination of scatter and primary components of exit patient fluence. Methods: Exit fluence was simulated using a monoenergetic photon beam on an existent machine model in the BEAMnrc monte carlo computation engine. The exit fluence was used as input to a program designed to accept a CT dataset (e.g. from treatment cone beam CT) and exit fluence (e.g. output of an EPID after deconvolving the detector function) and return the fluence at entrance to the phantom. The program uses a superposition convolution algorithm to predict, and iteratively remove, the patient scatter component of the fluence at the detector. The result is then back‐projected through the phantom to generate an input phantom fluence. After suitable variance reduction in subsequent runs, the computed input fluence is accepted as the true fluence and used to compute dose to the phantom. Results: Initial results indicate that the algorithm described is capable of determining the dose to the patient by using exit simulated fluence. Conclusions: It has been demonstrated by others that EPID images may be deconvolved from the detector function to create a map of machine fluence at the plane of the detector. It has also been demonstrated by other researchers that a superposition‐convolution algorithm, when used with computed fluence, may be used to compute accurate dosimetry in a patient phantom (e.g. the CCC algorithm). This work demonstrates that combining these two algorithms and an iterative deconvolution approach can provide a method of determining in vivo dosimetry using only an EPID and a treatment time cone beam CT.

Analysis of an iterative deconvolution approach for estimating the source wavelet during waveform inversion of crosshole georadar data

A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures. ► Crosshole georadar waveform inversion is a powerful subsurface imaging method. ► Accurate source wavelet estimation is a major issue for waveform inversion approaches. ► Iterative deconvolution approach provides accurate estimation of source wavelet. ► This wavelet approach remains viable and robust even under challenging conditions.

The influence of image enhancement and reconstruction on quantitative coronary arteriography

In the coming years, cinefilm will gradually be replaced by some digital medium for the archiving of angiographic images. However, not only the question which digital archiving medium will be used in the future is important, but also which images are to be stored. Options are to either archive the raw, unprocessed images, or the enhanced images as they are displayed on the viewing monitor in the catheterization laboratory. In the first case, an off-line workstation will need additional hardware to display the images with the same image quality as they were acquired; in the second case, the question remains whether quantitative analysis programs still provide reliable results. Goal of this study was to investigate the possible effects of image enhancement and reconstruction on the results from quantitative coronary arteriographic (QCA) measurements with the Philips ACA-package (Automated Coronary Analysis). Image enhancement was achieved by an unsharp masking approach; the reconstruction of the original image from the enhanced image was attempted by an iterative deconvolution approach. The evaluation study consisted of two parts; a technical evaluation on eleven phantom tubes with known dimensions, and a clinical evaluation study on 48 coronary lesions. The results of the technical evaluation demonstrate that the measurement errors increase for the smaller vessel sizes (< 1.2 mm) when QCA is applied to reconstructed images. The systematic difference on the smallest phantom tube (0.687 mm) on unprocessed images was limited to 0.050 mm, while it increased to 0.089 mm for the reconstructed images. Moreover, the random differences for the smaller vessel sizes increased for all processed images: for 0.159 mm for the unprocessed image to 0.189 mm for the enhanced and 0.204 mm for the reconstructed image (p < 0.01). For the larger vessels, in general, no significant differences could be observed between the results of the unprocessed and processed images. The results of the clinical evaluation study demonstrate that especially the obstruction diameter is overestimated when QCA is applied to reconstructed images (0.113 mm). Although the measurements on the enhanced images did not show a significant overestimation of the obstruction diameter, the intra-observer random difference was much higher (0.199 mm for the enhanced images versus 0.140 mm for the unprocessed images, p < 0.01). In more general terms, applying QCA on enhanced images increases the random difference values, while reconstructing the original image from the enhanced images increases the systematic errors in the measured diameters. This study has clearly demonstrated that especially the smaller diameter values (< 1.2 mm) are influenced by image enhancement. Therefore, to obtain quantitative results with the desired small values for systematic and random differences, requires that the raw, unprocessed image data be archived.