David S. Lake

Spatio-temporal directional filtering for improved inversion of MR elastography images

Dynamic magnetic resonance elastography can visualize and measure propagating shear waves in tissue-like materials subjected to harmonic mechanical excitation. This allows the calculation of local values of material parameters such as shear modulus and attenuation. Various inversion algorithms to perform such calculations have been proposed, but they are sensitive to areas of low displacement amplitude (and hence low SNR) that result from interference patterns due to reflection and refraction. A spatio-temporal directional filter applied as a pre-processing step can separate interfering waves so they can be processed separately. Weighted combinations of inversions from such directionally separated data sets can significantly improve reconstructions of shear modulus and attenuation.

Adaptive nonlocal means filtering based on local noise level for CT denoising

PURPOSE To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. METHODS A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analytical noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. RESULTS The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the shape and peak frequency of the noise power spectrum better than commercial smoothing kernels, and indicate that the spatial resolution at low contrast levels is not significantly degraded. Both the subjective evaluation using the ACR phantom and the objective evaluation on a low-contrast detection task using a CHO model observer demonstrate an improvement on low-contrast performance. The GPU implementation can process and transfer 300 slice images within 5 min. On patient data, the adaptive NLM algorithm provides more effective denoising of CT data throughout a volume than standard NLM, and may allow significant lowering of radiation dose. After a two week pilot study of lower dose CT urography and CT enterography exams, both GI and GU radiology groups elected to proceed with permanent implementation of adaptive NLM in their GI and GU CT practices. CONCLUSIONS This work describes and validates a computationally efficient technique for noise map estimation directly from CT images, and an adaptive NLM filtering based on this noise map, on phantom and patient data. Both the noise map calculation and the adaptive NLM filtering can be performed in times that allow integration with clinical workflow. The adaptive NLM algorithm provides effective denoising of CT data throughout a volume, and may allow significant lowering of radiation dose.

Quantitative shear wave magnetic resonance elastography: Comparison to a dynamic shear material test

Magnetic resonance elastography (MRE), a phase contrast MRI technique, images the propagation of applied mechanical waves in tissue, allowing shear stiffness to be quantified in vivo. This MRE technique has been validated with static mechanical compression tests. Dynamic mechanical analysis (DMA) may be a more appropriate comparison to MRE because it directly measures the shear modulus dynamically, while compression tests convert the measured elastic modulus to shear modulus with an assumed Poisson ratio. This study compared the shear stiffness estimated with various MRE inversion algorithms (i.e., manual calculation, local frequency estimate, phase gradient, direct inversion, and matched filter) to the dynamic mechanical test. The shear stiffness of five agarose gels with concentrations ranging from 1.5 to 3.5% were measured using MRE and DMA. The phase gradient inversion algorithm overestimated the shear modulus at higher concentrations (i.e., 3–3.5% agar), while the results from the other techniques correlated well with the dynamic mechanical test. Magn Reson Med 53:1197–1201, 2005.

Measuring the effects of aging and sex on regional brain stiffness with MR elastography in healthy older adults.

Changes in tissue composition and cellular architecture have been associated with neurological disease, and these in turn can affect biomechanical properties. Natural biological factors such as aging and an individuals sex also affect underlying tissue biomechanics in different brain regions. Understanding the normal changes is necessary before determining the efficacy of stiffness imaging for neurological disease diagnosis and therapy monitoring. The objective of this study was to evaluate global and regional changes in brain stiffness as a function of age and sex, using improved MRE acquisition and processing that have been shown to provide median stiffness values that are typically reproducible to within 1% in global measurements and within 2% for regional measurements. Furthermore, this is the first study to report the effects of age and sex over the entire cerebrum volume and over the full frontal, occipital, parietal, temporal, deep gray matter/white matter (insula, deep gray nuclei and white matter tracts), and cerebellum volumes. In 45 volunteers, we observed a significant linear correlation between age and brain stiffness in the cerebrum (P<.0001), frontal lobes (P<.0001), occipital lobes (P=.0005), parietal lobes (P=.0002), and the temporal lobes (P<.0001) of the brain. No significant linear correlation between brain stiffness and age was observed in the cerebellum (P=.74), and the sensory-motor regions (P=.32) of the brain, and a weak linear trend was observed in the deep gray matter/white matter (P=.075). A multiple linear regression model predicted an annual decline of 0.011 ± 0.002 kPa in cerebrum stiffness with a theoretical median age value (76 years old) of 2.56 ± 0.08 kPa. Sexual dimorphism was observed in the temporal (P=.03) and occipital (P=.001) lobes of the brain, but no significant difference was observed in any of the other brain regions (P>.20 for all other regions). The model predicted female occipital and temporal lobes to be 0.23 kPa and 0.09 kPa stiffer than males of the same age, respectively. This study confirms that as the brain ages, there is softening; however, the changes are dependent on region. In addition, stiffness effects due to sex exist in the occipital and temporal lobes.

Methods for Clinical Evaluation of Noise Reduction Techniques in Abdominopelvic CT

Most noise reduction methods involve nonlinear processes, and objective evaluation of image quality can be challenging, since image noise cannot be fully characterized on the sole basis of the noise level at computed tomography (CT). Noise spatial correlation (or noise texture) is closely related to the detection and characterization of low-contrast objects and may be quantified by analyzing the noise power spectrum. High-contrast spatial resolution can be measured using the modulation transfer function and section sensitivity profile and is generally unaffected by noise reduction. Detectability of low-contrast lesions can be evaluated subjectively at varying dose levels using phantoms containing low-contrast objects. Clinical applications with inherent high-contrast abnormalities (eg, CT for renal calculi, CT enterography) permit larger dose reductions with denoising techniques. In low-contrast tasks such as detection of metastases in solid organs, dose reduction is substantially more limited by loss of lesion conspicuity due to loss of low-contrast spatial resolution and coarsening of noise texture. Existing noise reduction strategies for dose reduction have a substantial impact on lowering the radiation dose at CT. To preserve the diagnostic benefit of CT examination, thoughtful utilization of these strategies must be based on the inherent lesion-to-background contrast and the anatomy of interest. The authors provide an overview of existing noise reduction strategies for low-dose abdominopelvic CT, including analytic reconstruction, image and projection space denoising, and iterative reconstruction; review qualitative and quantitative tools for evaluating these strategies; and discuss the strengths and limitations of individual noise reduction methods.

Calculation of shear stiffness in noise dominated magnetic resonance elastography data based on principal frequency estimation

Magnetic resonance elastography (MRE) is a non-invasive phase-contrast-based method for quantifying the shear stiffness of biological tissues. Synchronous application of a shear wave source and motion encoding gradient waveforms within the MRE pulse sequence enable visualization of the propagating shear wave throughout the medium under investigation. Encoded shear wave-induced displacements are then processed to calculate the local shear stiffness of each voxel. An important consideration in local shear stiffness estimates is that the algorithms employed typically calculate shear stiffness using relatively high signal-to-noise ratio (SNR) MRE images and have difficulties at an extremely low SNR. A new method of estimating shear stiffness based on the principal spatial frequency of the shear wave displacement map is presented. Finite element simulations were performed to assess the relative insensitivity of this approach to decreases in SNR. Additionally, ex vivo experiments were conducted on normal rat lungs to assess the robustness of this approach in low SNR biological tissue. Simulation and experimental results indicate that calculation of shear stiffness by the principal frequency method is less sensitive to extremely low SNR than previously reported MRE inversion methods but at the expense of loss of spatial information within the region of interest from which the principal frequency estimate is derived.

GASTRIC MOTOR DISTURBANCES IN PATIENTS WITH IDIOPATHIC RAPID GASTRIC EMPTYING

Background  The mechanisms of ‘idiopathic’ rapid gastric emptying, which are associated with functional dyspepsia and functional diarrhea, are not understood. Our hypotheses were that increased gastric motility and reduced postprandial gastric accommodation contribute to rapid gastric emptying.

Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction

PURPOSE To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). MATERIALS AND METHODS This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per-malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than -0.10. RESULTS Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: -0.041 [95% CI: -0.090, 0.009] and -0.003 [95% CI: -0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: -0.077, 0.106]), whereas lower-dose FBP images were not (difference -0.049 [95% CI: -0.140, 0.043]). In 37 patients with SAFIRE reconstructions, the three lower-dose alternatives were found to be noninferior to the routine-dose FBP. CONCLUSION At moderate levels of dose reduction, lower-dose FBP images without ANLM or SAFIRE were noninferior to routine-dose images for abdominal CT but not for liver or pancreas CT.

Characterization and evaluation of inversion algorithms for MR elastography

Magnetic resonance elastography (MRE) can visualize and measure acoustic shear waves in tissue-like materials subjected to harmonic mechanical excitation. This allows the calculation of local values of material parameters such as shear modulus and attenuation. Various inversion algorithms to perform such calculations have been proposed. Under certain assumptions (discussed in detail), the problem reduces to local inversion of the Helmholtz equation. Three algorithms are considered to perform this inversion: Direct Inversion, Local Frequency Estimation, and Matched Filter. To study the noise sensitivity, resolution, and accuracy of these techniques, studies were conducted on synthetic and physical phantoms and on in-vivo breast data. All three algorithms accurately reconstruct shear modulus, demarcate differences between tissues, and identify tumors as areas of higher stiffness, but they vary in noise sensitivity and resolution. The Matched Filter, designed for optimal behavior in noise, provides the best combination of sharpness and smoothness. Challenges remain in pulse sequence design, delivering sufficient signal to certain areas of the body, and improvements in processing algorithms, but MRE shows great potential for non-invasive in vivo determination of mechanical properties.

In vivo, high-frequency three-dimensional cardiac MR elastography: Feasibility in normal volunteers: In Vivo, High-Frequency 3D Cardiac MRE

Noninvasive stiffness imaging techniques (elastography) can image myocardial tissue biomechanics in vivo. For cardiac MR elastography (MRE) techniques, the optimal vibration frequency for in vivo experiments is unknown. Furthermore, the accuracy of cardiac MRE has never been evaluated in a geometrically accurate phantom. Therefore, the purpose of this study was to determine the necessary driving frequency to obtain accurate three‐dimensional (3D) cardiac MRE stiffness estimates in a geometrically accurate diastolic cardiac phantom and to determine the optimal vibration frequency that can be introduced in healthy volunteers.