Evaluation of three scatter correction methods based on estimation of photopeak scatter spectrum in SPECT imaging: A simulation study

Three practical methods for scatter correction of Tc-99m SPECT images are evaluated. Among these, two methods, three-energy window (TEW) methods using the trapezoidal and triangular approximations, have been described previously by investigators, and a new approximation is offered in this work. The SIMIND (SIMulation of Imaging Nuclear Detectors) Monte Carlo program is used to simulate a line source placed at on-axis and 5 cm off-axis locations, a cold-sphere/hot-background phantom, a hot-sphere/cold-background phantom, and a more clinically realistic NCAT (Nonuniform Rational B-spline-based CArdiac-Torso) phantom. For evaluation of these methods, the scatter line-spread functions and scatter fractions for the on- and off-axis line source, image contrast, signal-to-noise ratio and relative noise for the cold spheres, and recovery coefficient for the hot spheres of different diameters are compared. For the NCAT phantom, a line profile through a slice of the reconstructed image is considered before and after scatter correction, and also image contrast defined by this profile is used to compare the correction methods. The results of this study indicate that for the line source simulation the scatter fractions obtained from the proposed method are a better estimation of true scatter fractions. Also, for both the sphere simulation and NCAT simulation, the proposed method improves the image contrast as compared to the two other methods.     

Segmentation of center brains and optic lobes in 3D confocal images of adult fruit fly brains

Automatic alignment (registration) of 3D images of adult fruit fly brains is often influenced by the significant displacement of the relative locations of the two optic lobes (OLs) and the center brain (CB). In one of our ongoing efforts to produce a better image alignment pipeline of adult fruit fly brains, we consider separating CB and OLs and align them independently. This paper reports our automatic method to segregate CB and OLs, in particular under conditions where the signal to noise ratio (SNR) is low, the variation of the image intensity is big, and the relative displacement of OLs and CB is substantial.We design an algorithm to find a minimum-cost 3D surface in a 3D image stack to best separate an OL (of one side, either left or right) from CB. This surface is defined as an aggregation of the respective minimum-cost curves detected in each individual 2D image slice. Each curve is defined by a list of control points that best segregate OL and CB. To obtain the locations of these control points, we derive an energy function that includes an image energy term defined by local pixel intensities and two internal energy terms that constrain the curve’s smoothness and length. Gradient descent method is used to optimize this energy function. To improve both the speed and robustness of the method, for each stack, the locations of optimized control points in a slice are taken as the initialization prior for the next slice. We have tested this approach on simulated and real 3D fly brain image stacks and demonstrated that this method can reasonably segregate OLs from CBs despite the aforementioned difficulties.     

Exploring Variability in CT Characterization of Tumors: A Preliminary Phantom Study

PURPOSE: To explore the effects of computed tomography (CT) slice thickness and reconstruction algorithm on quantification of image features to characterize tumors using a chest phantom. MATERIALS AND METHODS: Twenty-two phantom lesions of known sizes (10 and 20 mm), shapes (spherical, elliptical, lobulated, and spiculated), and densities [-630, -10, and +100 Hounsfield Unit (HU)] were inserted into an anthropomorphic thorax phantom and scanned three times with relocations. The raw data were reconstructed using six imaging settings, i.e., a combination of three slice thicknesses of 1.25, 2.5, and 5 mm and two reconstruction kernels of lung and standard. Lesions were segmented and 14 image features representing lesion size, shape, and texture were calculated. Differences in the measured image features due to slice thickness and reconstruction algorithm were compared using linear regression method by adjusting three confounding variables (size, density, and shape). RESULTS: All 14 features were significantly different between 1.25 and 5 mm slice images. The 1.25 and 2.5 mm slice thicknesses were better than 5 mm for volume, density mean, density SD gray-level co-occurrence matrix (GLCM) energy and homogeneity. As for the reconstruction algorithm, there was no significant difference in uni-dimension, volume, shape index 9, and compactness. Lung reconstruction was better for density mean, whereas standard reconstruction was better for density SD. CONCLUSIONS: CT slice thickness and reconstruction algorithm can significantly affect the quantification of image features. Thinner (1.25 and 2.5 mm) and thicker (5 mm) slice images should not be used interchangeably. Sharper and smoother reconstructions significantly affect the density-based features.     

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.     

A detection method for streak artifacts and radiological noise in a non-uniform region in a CT image

By using the CT images obtained by subtracting two CT images acquired under the same conditions and slice locations, we have devised a method for detecting streak artifacts in non-uniform regions and only radiological noise components in CT images. A chest phantom was scanned using 16- and 64-multidetector row helical CT scanners with various mAs values at 120 kVp. The upper lung slice image was employed as a target image for evaluating the streak artifacts and radiological noise. One hundred parallel line segments with a length of 80 pixels were placed on the subtracted CT image, and the largest CT value in each CT value profile was employed as a feature variable of the streak artifacts; these feature variables were analyzed with the extreme value theory (Gumbel distribution). To detect only the radiological noise, all CT values contained in the 100 line profile were plotted on normal probability paper and the standard deviation was estimated from the inclination of its fitted line for the CT value plots. The two detection methods devised in this study were able to evaluate the streak artifacts and radiological noise in the CT images with high accuracy.     

Fabs enable single particle cryoEM studies of small proteins

In spite of its recent achievements, the technique of single particle electron cryomicroscopy (cryoEM) has not been widely used to study proteins smaller than 100 kDa, although it is a highly desirable application of this technique. One fundamental limitation is that images of small proteins embedded in vitreous ice do not contain adequate features for accurate image alignment. We describe a general strategy to overcome this limitation by selecting a fragment antigen binding (Fab) to form a stable and rigid complex with a target protein, thus providing a defined feature for accurate image alignment. Using this approach, we determined a three-dimensional structure of an ～65 kDa protein by single particle cryoEM. Because Fabs can be readily generated against a wide range of proteins by phage display, this approach is generally applicable to study many small proteins by single particle cryoEM.     

Comparison of image registration performed with MV cone beam CT and CT on rails and Syngo™ Adaptive Targeting software

BackgroundMinimization of geometric errors in treatment delivery is essential in modern conformal and intensity-modulated techniques.AimIn this paper two Siemens systems, MVision megavoltage cone beam CT, and CTVision (CT on rails), are compared.Material and MethodsThe reproducibility and uncertainty of the image registration procedure performed with Adaptive Targeting (AT) software were evaluated. Both systems were evaluated by means of simulating the clinical situation with an anthropomorphic phantom in three anatomical sites: head & neck, thorax and pelvis.ResultsThe results for two methods of image registration, manual and automatic, were evaluated separately. The manual procedure was used by two users, more and less experienced.ConclusionsThe MVision system and CTVision and the Therapist Adaptive software ensure image registration with the uncertainty of about 2.0 mm (2 standard deviations). In the case of the automatic registration method better reproducibility of image registration was obtained for MVision. For CTVision the necessity of manual identification of the machine isocentre made the registration less reproducible. In the case of MVision, the automatic method was more reproducible than the manual one (smaller dispersion of results). In the case of CTVision, similar results were obtained for both registration methods. In the case of manual registration slightly better reproducibility for CT data acquired at 2 mm slice thickness and 2 mm slice separation than for data acquired at 5 mm slice thickness and 5 mm slice separation were obtained. Similar results of manual registration performed by more and less experienced users were obtained.     

Calibration of 192Ir high dose rate brachytherapy source using different calibration procedures

Aim

To calibrate Ir-192 high dose rate (HDR) brachytherapy source using different calibration methods and to determine the accuracy and suitability of each method for routine calibrations.

Background

The source calibration is an essential part of the quality assurance programme for dosimetry of brachytherapy sources. The clinical use of brachytherapy source requires an independent measurement of the air kerma strength according to the recommendations of medical physics societies.

Materials and methods

The Ir-192 HDR brachytherapy source from Gammamed plus machine (Varian Medical Systems, Palo Alto, CA) was calibrated using three different procedures, one using the well-type ionization chamber, second by the in-air calibration method and third using solid water phantoms. The reference air kerma rate (RAKR) of the source was determined using Deutsche Gesellschaft fur Medizinische Physik (DGMP) recommendations.

Results

The RAKR determined using different calibration methods are in good agreement with the manufacturer stated value. The mean percentage variations of 0.21, −0.94, −0.62 and 0.58 in RAKR values with respect to the manufacturer quoted values were observed with the well-type chamber, in-air calibration, cylindrical phantom and slab phantom measurements, respectively.

Conclusion

Measurements with a well-type chamber are relatively simple to perform. For in-air measurements, the indigenously designed calibration jig provides an accurate positioning of the source and chamber with minimum scatter contribution. The slab phantom system has an advantage that no additional phantom and chamber are required other than those used for external beam therapy dosimetry. All the methods of calibration discussed in this study are effective to be used for routine calibration purposes.     

Brown-Roberts-Wells stereotactic frame modifications to accomplish magnetic resonance imaging guidance in three planes

The Brown-Roberts-Wells (BRW) computer tomography (CT) stereotactic guidance system has been modified to accommodate magnetic resonance imaging (MRI). A smaller head ring, which fits in standard MRI head coils, is constructed of a non-ferromagnetic aluminum ring that is split to prevent eddy currents and anodized to prevent MRI image distortion and resolution degradation. A new localizing device has been designed in a box configuration, which allows BRW stereotactic coordinates to be calculated from coronal and sagittal MRI images, in addition to axial images. The system was tested utilizing a phantom and T1- and T2-weighted images. Using 5-mm MRI scan slices, targets were localized accurately to a 5-mm cube in three combined planes. Optimized calibration of both low field strength (0.3 T) and high field strength (1.5 T) MRI systems is necessary to obtain thin slice (5 mm) images with acceptable image resolution. To date, 10 patients have had MRI stereotactic localization of brain lesions that were better defined by MRI than CT.     

Interpolated Compressed Sensing for 2D Multiple Slice Fast MR Imaging

Sparse MRI has been introduced to reduce the acquisition time and raw data size by undersampling the k-space data. However, the image quality, particularly the contrast to noise ratio (CNR), decreases with the undersampling rate. In this work, we proposed an interpolated Compressed Sensing (iCS) method to further enhance the imaging speed or reduce data size without significant sacrifice of image quality and CNR for multi-slice two-dimensional sparse MR imaging in humans. This method utilizes the k-space data of the neighboring slice in the multi-slice acquisition. The missing k-space data of a highly undersampled slice are estimated by using the raw data of its neighboring slice multiplied by a weighting function generated from low resolution full k-space reference images. In-vivo MR imaging in human feet has been used to investigate the feasibility and the performance of the proposed iCS method. The results show that by using the proposed iCS reconstruction method, the average image error can be reduced and the average CNR can be improved, compared with the conventional sparse MRI reconstruction at the same undersampling rate.     

Enhanced contrast acoustic‐resolution photoacoustic microscopy using double‐stage delay‐multiply‐and‐sum beamformer for vasculature imaging

In acoustic‐resolution photoacoustic microscopy (AR‐PAM) systems, the lateral resolution in the focal zone of the ultrasound (US) transducer is determined by the numerical aperture (NA) of the transducer. To have a high lateral resolution, a large NA is used. However, the larger the NA, the smaller the depth of focus [DOF]. As a result, the lateral resolution is deteriorated at depths out of the focal region. The synthetic aperture focusing technique (SAFT) along with a beamformer can be used to improve the resolution outside the focal region. In this work, for image formation in AR‐PAM, we propose the double‐stage delay‐multiply‐and‐sum (DS_DMAS) algorithm to be combined with SAFT. The proposed method is evaluated experimentally using hair targets and in vivo vasculature imaging. It is shown that DS_DMAS provides a higher resolution and contrast compared to other methods. For the B‐mode images obtained using the hair phantom, the proposed method reduces the average noise level for all the depths by about 134%, 57% and 23%, compared to the original low‐ resolution, SAFT+DAS and SAFT+DMAS methods, respectively. All the results indicate that the proposed method can be an appropriate algorithm for image formation in AR‐PAM systems.      

Augmenting intraoperative ultrasound with preoperative magnetic resonance planning models for percutaneous renal access

ABSTRACT: BACKGROUND: Ultrasound (US) is a commonly-used intraoperative imaging modality for guiding percutaneous renal access (PRA). However, the anatomy identification and target localization abilities of the US imaging are limited. This paper evaluates the feasibility and efficiency of a proposed image-guided PRA by augmenting the intraoperative US with preoperative magnetic resonance (MR) planning models. METHODS: First, a preoperative surgical planning approach is presented to define an optimal needle trajectory using MR volume data. Then, a MR to US registration is proposed to transfer the preoperative planning into the intraoperative context. The proposed registration makes use of orthogonal US slices to avoid local minima while reduce processing time. During the registration, a respiratory gating method is used to minimize the impact of kidney deformation. By augmenting the intraoperative US with preoperative MR models and a virtual needle, a visual guidance is provided to guarantee the correct execution of the surgical planning. The accuracy, robustness and processing time of the proposed registration were evaluated by four urologists on human data from four volunteers. Furthermore, the PRA experiments were performed by the same four urologists on a kidney phantom. The puncture accuracy in terms of the needle-target distance was measured, while the perceptual quality in using the proposed image guidance was evaluated according to custom scoring method. RESULTS: The mean registration accuracy in terms of the root mean square (RMS) target registration error (TRE) is 3.53mm. The RMA distance from the registered feature points to their average is 0.81mm. The mean operating time of the registration is 6'4". In the phantom evaluation, the mean needle-target distance is 2.08mm for the left lesion and 1.85mm for the right one. The mean duration for all phantom PRA tests was 4'26". According to the custom scoring method, the mean scores of the Intervention Improvement, Workflow Impact, and Clinical Relevance were 4.0, 3.3 and 3.9 respectively. CONCLUSIONS: The presented image guidance is feasible and promising for PRA procedure. With careful setup it can be efficient for overcoming the limitation of current US-guided PRA.     

Anatomical evaluation of CT-MRI combined femoral model

Background

Breast density is a significant breast cancer risk factor. Currently, there is no standard method for measuring this important factor. Work presented here represents an essential component of an ongoing project that seeks to determine the appropriate method for calibrating (standardizing) mammography image data to account for the x-ray image acquisition influences. Longer term goals of this project are to make accurate breast density measurements in support of risk studies.

Methods

Logarithmic response calibration curves and effective x-ray attenuation coefficients were measured from two full field digital mammography (FFDM) systems with breast tissue equivalent phantom imaging and compared. Normalization methods were studied to assess the possibility of reducing the amount of calibration data collection. The percent glandular calibration map functional form was investigated. Spatial variations in the calibration data were used to assess the uncertainty in the calibration application by applying error propagation analyses.

Results

Logarithmic response curves are well approximated as linear. Measured effective x-ray attenuation coefficients are characteristic quantities independent of the imaging system and are in agreement with those predicted numerically. Calibration data collection can be reduced by applying a simple normalization technique. The calibration map is well approximated as linear. Intrasystem calibration variation was on the order of four percent, which was approximately half of the intersystem variation.

Conclusion

FFDM systems provide a quantitative output, and the calibration quantities presented here may be used for data acquired on similar FFDM systems.     

Image quality characteristics for virtual monoenergetic images using dual-layer spectral detector CT: Comparison with conventional tube-voltage images

PurposeTo investigate the image quality characteristics for virtual monoenergetic images compared with conventional tube-voltage image with dual-layer spectral CT (DLCT).MethodsHelical scans were performed using a first-generation DLCT scanner, two different sizes of acrylic cylindrical phantoms, and a Catphan phantom. Three different iodine concentrations were inserted into the phantom center. The single-tube voltage for obtaining virtual monoenergetic images was set to 120 or 140 kVp. Conventional 120- and 140-kVp images and virtual monoenergetic images (40–200-keV images) were reconstructed from slice thicknesses of 1.0 mm. The CT number and image noise were measured for each iodine concentration and water on the 120-kVp images and virtual monoenergetic images. The noise power spectrum (NPS) was also calculated.ResultsThe iodine CT numbers for the iodinated enhancing materials were similar regardless of phantom size and acquisition method. Compared with the iodine CT numbers of the conventional 120-kVp images, those for the monoenergetic 40-, 50-, and 60-keV images increased by approximately 3.0-, 1.9-, and 1.3-fold, respectively. The image noise values for each virtual monoenergetic image were similar (for example, 24.6 HU at 40 keV and 23.3 HU at 200 keV obtained at 120 kVp and 30-cm phantom size). The NPS curves of the 70-keV and 120-kVp images for a 1.0-mm slice thickness over the entire frequency range were similar.ConclusionVirtual monoenergetic images represent stable image noise over the entire energy spectrum and improved the contrast-to-noise ratio than conventional tube voltage using the dual-layer spectral detector CT.     

Marker Configuration Model-Based Roentgen Fluoroscopic Analysis

It remains unknown if and how the polyethylene bearing in mobile bearing knees moves during dynamic activities with respect to the tibial base plate. Marker Configuration Model-Based Roentgen Fluoroscopic Analysis (MCM-based RFA) uses a marker configuration model of inserted tantalum markers in order to accurately estimate the pose of an implant or bone using single plane Roentgen images or fluoroscopic images. The goal of this study is to assess the accuracy of (MCM-Based RFA) in a standard fluoroscopic set-up using phantom experiments and to determine the error propagation with computer simulations. The experimental set-up of the phantom study was calibrated using a calibration box equipped with 600 tantalum markers, which corrected for image distortion and determined the focus position. In the computer simulation study the influence of image distortion, MC-model accuracy, focus position, the relative distance between MC-models and MC-model configuration on the accuracy of MCM-Based RFA were assessed. The phantom study established that the in-plane accuracy of MCM-Based RFA is 0.1 mm and the out-of-plane accuracy is 0.9 mm. The rotational accuracy is 0.1 degrees. A ninth-order polynomial model was used to correct for image distortion. Marker-Based RFA was estimated to have, in a worst case scenario, an in vivo translational accuracy of 0.14 mm (x-axis), 0.17 mm (y-axis), 1.9 mm (z-axis), respectively, and a rotational accuracy of 0.3 degrees. When using fluoroscopy to study kinematics, image distortion and the accuracy of models are important factors, which influence the accuracy of the measurements. MCM-Based RFA has the potential to be an accurate, clinically useful tool for studying kinematics after total joint replacement using standard equipment.     

A microcomputer based system for three-dimensional reconstructions from tomographic or histologic sections

The reconstructions of three-dimensional (3-D) objects from serial two-dimensional (2-D) images can contribute to the understanding of many biologic structures, from organelles to organs and tissues. The 3-D reconstruction of sections can be divided into several major tasks: image acquisition, alignment of slices, internal object definition, object reconstruction and rotation of the completed image. A fast, versatile, interactive system was devised for the reconstruction of 3-D objects from serial 2-D images using a low-cost microcomputer, original programs and commercial software. The system allows reconstruction from any serial images, e.g., electron micrographs, histologic sections or computed tomograms. A photographic image or a microscopic field is acquired into the computer memory using a video digitizer. Slices are superimposed and aligned to each other using an operator-interactive program. A contour-(edge-) finding algorithm isolates an object of interest from the background image by "subtraction" of the image from an overlaid, slightly shifted identical image. Contours for each slice are input to a reconstruction procedure, which calculates the x, y and z coordinates of every point in a slice and the thickness and number of slices. It then calculates the illumination for every point using a given point source of light and an intensity-fading coefficient. Finally, the points are represented by cubes to provide dimension and reflective surfaces. A cube of appropriate shade and color represents in 2-D the equivalent of a 3-D object; this results in a very effective 3-D image. The reconstruction is rotated by recalculating the positions of every point defining the object and rebuilding the image.(ABSTRACT TRUNCATED AT 250 WORDS)     

Development of a dynamic deformable thorax phantom for the quality management of deformable image registration

The purpose of this study was to develop a novel dynamic deformable thorax phantom for deformable image registration (DIR) quality assurance (QA) and to verify as a tool for commissioning and DIR QA.The phantom consists of a base phantom, an inner phantom, and a motor-derived piston. The base phantom is an acrylic cylinder phantom with a diameter of 180 mm. The inner phantom consists of deformable, 20 mm thick disk-shaped sponges. To evaluate the physical characteristics of the phantom, we evaluated its image quality and deformation. DIR accuracies were evaluated using the three types of commercially DIR software (MIM, RayStation, and Velocity AI) to test the feasibility of this phantom. We used different DIR parameters to test the impact of parameters on DIR accuracy in various phantom settings. To evaluate DIR accuracy, a target registration error (TRE) was calculated using the anatomical landmark points.The three locations (i.e., distal, middle, and proximal positions) had different displacement amounts. This result indicated that the inner phantom was not moved but deformed. In cases with different phantom settings and marker settings, the ranges of the average TRE were 0.63–15.60 mm (MIM). In cases with different DIR parameters settings, the ranges of the average TRE were as follows: 0.73–7.10 mm (MIM), 8.25–8.66 mm (RayStation), and 8.26–8.43 mm (Velocity). These results suggest that our phantom could evaluate the detailed DIR behaviors with TRE. Therefore, this is indicative of the potential usefulness of our phantom in DIR commissioning and QA.     

Development of an RSA calibration system with improved accuracy and precision

In this study, a new radiostereometric analysis (RSA) calibration cage was developed with the aim of improving the accuracy and precision of RSA. This development consisted of three steps: a numerical simulation technique was first used to design the new cage; a synthetic imaging method was then implemented to predict the performance of the designed cage before it was actually fabricated; and an experimental phantom test was finally conducted to verify the actual performance of the new cage and compare with two currently widely used cages. Accuracy was calculated as the 95% prediction intervals from regression analyses between the measured and actual displacements, and precision was defined as the standard deviation of repeated measurements. The final experimental phantom tests showed that the accuracy and precision of the new calibration cage were improved by about 40% over an existing biplanar cage and by about 70% compared to a uniplanar cage design. This new cage can be used with any skeletal joints, in either static or kinematic examination, which is helpful for the standardization of the RSA application.     

Geometric inaccuracy and co-registration errors for CT,DynaCT and MRI images used in robotic stereotactic radiosurgery treatment planning

PurposeTo measure the combined errors due to geometric inaccuracy and image co-registration on secondary images (dynamic CT angiography (dCTA), 3D DynaCT angiography (DynaCTA), and magnetic resonance images (MRI)) that are routinely used to aid in target delineation and planning for stereotactic radiosurgery (SRS).MethodsThree phantoms (one commercial and two in-house built) and two different analysis approaches (commercial and MATLAB based) were used to quantify the magnitude of geometric image distortion and co-registration errors for different imaging modalities within CyberKnife’s MultiPlan treatment planning software. For each phantom, the combined errors were reported as a mean target registration error (TRE). The mean TRE’s for different intramodality imaging parameters (e.g., mAs, kVp, and phantom set-ups) and for dCTA, DynaCTA, and MRI systems were measured.ResultsOnly X-ray based imaging can be performed with the commercial phantom, and the mean TRE ± standard deviation values were large compared to the in-house analysis using MATLAB. With the 3D printed phantom, even drastic changes in treatment planning CT imaging protocols did not greatly influence the mean TRE (<0.5 mm for a 1 mm slice thickness CT). For all imaging modalities, the largest mean TRE was found on DynaCT, followed by T2-weighted MR images (albeit all <1 mm).ConclusionsThe user may overestimate the mean TRE if the commercial phantom and MultiPlan were used solely. The 3D printed phantom design is a sensitive and suitable quality assurance tool for measuring 3D geometric inaccuracy and co-registration errors across all imaging modalities.     

Time Efficient 3D Radial UTE Sampling with Fully Automatic Delay Compensation on a Clinical 3T MR Scanner

This work’s aim was to minimize the acquisition time of a radial 3D ultra-short echo-time (UTE) sequence and to provide fully automated, gradient delay compensated, and therefore artifact free, reconstruction. The radial 3D UTE sequence (echo time 60 μs) was implemented as single echo acquisition with center-out readouts and improved time efficient spoiling on a clinical 3T scanner without hardware modifications. To assess the sequence parameter dependent gradient delays each acquisition contained a quick calibration scan and utilized the phase of the readouts to detect the actual k-space center. This calibration scan does not require any user interaction. To evaluate the robustness of this automatic delay estimation phantom experiments were performed and 19 in vivo imaging data of the head, tibial cortical bone, feet and lung were acquired from 6 volunteers. As clinical application of this fast 3D UTE acquisition single breath-hold lung imaging is demonstrated. The proposed sequence allowed very short repetition times (TR~1ms), thus reducing total acquisition time. The proposed, fully automated k-phase based gradient delay calibration resulted in accurate delay estimations (difference to manually determined optimal delay −0.13 ± 0.45 μs) and allowed unsupervised reconstruction of high quality images for both phantom and in vivo data. The employed fast spoiling scheme efficiently suppressed artifacts caused by incorrectly refocused echoes. The sequence proved to be quite insensitive to motion, flow and susceptibility artifacts and provides oversampling protection against aliasing foldovers in all directions. Due to the short TR, acquisition times are attractive for a wide range of clinical applications. For short T2* mapping this sequence provides free choice of the second TE, usually within less scan time as a comparable dual echo UTE sequence.