Kyle A. Salem

Validation of a human vision model for image quality evaluation of fast interventional magnetic resonance imaging

Perceptual difference models (PDMs) have become popular for evaluating the perceived degradation of an image by a process such as compression. We used a PDM to evaluate interventional magnetic resonance imaging (iMRI) methods that rapidly acquire an image at the expense of some anticipated image degradation compared to a conventional slower diagnostic technique. In particular, we examined MR keyhole techniques whereby only a portion of the spatial frequency domain, or k-space, was acquired, thereby reducing the time for the creation of image updates. We used a PDM based on the architecture of another visual differencemodel and validated it for noise and blur, degrading processes present in fast iMRI. The PDM showed superior correlation with human observer ratings of noise and blur compared to the mean squared error (MSE). In an example application, we simulated four keyhole techniques and compared them to a slower, full k-space diagnostic acquisition. For keyhole images, the MSE gave erratic results compared to the ratings by interventional radiologists. The PDM performed much better and gave an Az value >0.9 in a receiver operating characteristic analysis. Keyhole simulations showed that a single, central stripe acquisition, which sampled 25% of k-space, provided stable image quality within a clinically acceptable range, unlike three other keyhole schemes described in the literature. Our early experience shows the PDM to be an objective, promising tool for the evaluation of fast iMRI methods. It allows one to quantitatively make engineering decisions in the design of iMRI pulse sequences.

X-ray computed tomography methods for in vivo evaluation of local drug release systems

Recent advances in drug delivery techniques have necessitated the development of tools for in vivo monitoring of drug distributions. Gamma emission imaging and magnetic resonance imaging suffer from problems of resolution and sensitivity, respectively. We propose that the combination of X-ray CT imaging and image analysis techniques provides an excellent method for the evaluation of the transport of platinum-containing drugs from a localized, controlled release source. We correlated local carboplatin concentration with CT intensity, producing a linear relationship with a sensitivity of 62.6 /spl mu/g/mL per Hounsfield unit. As an example application, we evaluated the differences in drug transport properties between normal and ablated rabbit liver from implanted polymer millirods. The use of three-dimensional visualization provided a method of evaluating the placement of the drug delivery device in relation to the surrounding anatomy, and registration and reformatting allowed the accurate comparison of the sequence of temporal CT volumes acquired over a period of 24 h. Taking averages over radial lines extending away from the center of the implanted millirods and integrating over clinically appropriate regions, yielded information about drug release from the millirod and transport in biological tissues. Comparing implants in normal and ablated tissues, we found that ablation prior to millirod implantation greatly decreased the loss of drug from the immediate area, resulting in a higher average dose to the surrounding tissue. This work shows that X-ray CT imaging is a useful technique for the in vivo evaluation of the pharmacokinetics of platinated agents.

Noninvasive monitoring of local drug release in a rabbit radiofrequency (RF) ablation model using X-ray computed tomography

In this study, X-ray computed tomography (CT) was utilized as a noninvasive method to directly examine local drug release kinetics in livers before and following radiofrequency thermal ablation. Iohexol, a CT contrast agent, was used as a drug-mimicking molecule. Release of iohexol in healthy and ablated rabbit livers over 48 h was quantified and correlated with the release profiles from phosphate-buffered saline (PBS) in vitro. The results show that iohexol release in ablated livers is significantly slower than both release in normal livers and in vitro. The time at which 50% of the drug was released (t(1/2)) into ablated liver (20.6+/-5.9 h) was 1.7 times longer than in normal liver (12.1+/-5.4 h) and approximately two times longer than that in PBS (10.1+/-1.2 h). The slower release in ablated livers is a result of severe tissue damage inflicted by thermal ablation, as supported by histological examination. This data suggests that a noninvasive imaging method provides a superior measurement over in vitro release studies in accurately quantifying the local release kinetics of an agent in an altered physiological system in vivo. Because the development of a successful local drug therapy is dependent on the understanding of the agent release kinetics at the implantation site, the noninvasive data may be indispensable in effectively predicting the implant behavior in a physiological system.

Perceptual difference paradigm for analyzing image quality of fast MRI techniques

We are developing a method to objectively quantify image quality and applying it to the optimization of fast magnetic resonance imaging methods. In MRI, to capture the details of a dynamic process, it is critical to have both high temporal and spatial resolution. However, there is typically a trade-off between the two, making the sequence engineer choose to optimize imaging speed or spatial resolution. In response to this problem, a number of different fast MRI techniques have been proposed. To evaluate different fast MRI techniques quantitatively, we use a perceptual difference model (PDM) that incorporates various components of the human visual system. The PDM was validated using subjective image quality ratings by naive observers and task-based measures as defined by radiologists. Using the PDM, we investigated the effects of various imaging parameters on image quality and quantified the degradation due to novel imaging techniques including keyhole, keyhole Dixon fat suppression, and spiral imaging. Results have provided significant information about imaging time versus quality tradeoffs aiding the MR sequence engineer. The PDM has been shown to be an objective tool for measuring image quality and can be used to determine the optimal methodology for various imaging applications.

Optimization of Spiral MRI Using a Perceptual Difference Model

We systematically evaluated a variety of MR spiral imaging acquisition and reconstruction schemes using a computational perceptual difference model (PDM) that models the ability of humans to perceive a visual difference between a degraded “fast” MRI image with subsampling of k-space and a “gold standard” image mimicking full acquisition. Human subject experiments performed using a modified double-stimulus continuous-quality scale (DSCQS) correlated well with PDM, over a variety of images. In a smaller set of conditions, PDM scores agreed very well with human detectability measurements of image quality. Having validated the technique, PDM was used to systematically evaluate 2016 spiral image conditions (six interleave patterns, seven sampling densities, three density compensation schemes, four reconstruction methods, and four noise levels). Voronoi (VOR) with conventional regridding gave the best reconstructions. At a fixed sampling density, more interleaves gave better results. With noise present more interleaves and samples were desirable. With PDM, conditions were determined where equivalent image quality was obtained with 50% sampling in noise-free conditions. We conclude that PDM scoring provides an objective, useful tool for the assessment of fast MR image quality that can greatly aid the design of MR acquisition and signal processing strategies.

Optimization of noisy nonuniform sampling and image reconstruction for fast MRI using a human vision model

We are developing clinical magnetic resonance imaging (MRI) strategies using spiral acquisition techniques that sample k-space nonuniformly. These methods require a regridding process. Multiple regridding and reconstruction algorithms have been proposed, and we use a perceptual difference model (PDM) to optimize them. We acquired sixteen in vivo MR brain images and simulated reconstruction from a spiral k-space trajectory. Regridding was done by the conventional method of Jackson et al., the block uniform resampling algorithm (BURS), and a newly developed method named matrix rescaling. Each of 16 reference images was reconstructed with multiple parameter sets resulting in a total of over 800 different images. The spiral MR images were compared to the original, fully sampled image using a PDM. Of the three reconstruction methods, the conventional and high-level matrix rescaling methods produce high quality images, but the latter method executed much faster. BURS worked only in extremely low- noise instances, making it often inappropriate. We also demonstrated the effect of display parameters, such as grayscale windowing on image quality. We believe that the PDM techniques provide a promising tool for the evaluation of MR image quality that can aid the engineering design process.

Human vision model for the objective evaluation of perceived image quality applied to MRI and image restoration

We are developing a method to objectively quantify image quality and applying it to the optimization of interventional magnetic resonance imaging (iMRI). In iMRI, images are used for live-time guidance of interventional procedures such as the minimally invasive treatment of cancer. Hence, not only does one desire high quality images, but they must also be acquired quickly. In iMRI, images are acquired in the Fourier domain, or k-space, and this allows many creative ways to image quickly such as keyhole imaging where k-space is preferentially subsampled, yielding suboptimal images at very high frame rates. Other techniques include spiral, radial, and the combined acquisition technique. We have built a perceptual difference model (PDM) that incorporates various components of the human visual system. The PDM was validated using subjective image quality ratings by naive observers and task-based measures defined by interventional radiologists. Using the PDM, we investigated the effects of various imaging parameters on image quality and quantified the degradation due to novel imaging techniques. Results have provided significant information about imaging time versus quality tradeoffs aiding the MR sequence engineer. The PDM has also been used to evaluate other applications such as Dixon fat suppressed MRI and image restoration. In image restoration, the PDM has been used to evaluate the Generalized Minimal Residual (GMRES) image restoration method and to examine the ability to appropriately determine a stopping condition for such iterative methods. The PDM has been shown to be an objective tool for measuring image quality and can be used to determine the optimal methodology for various imaging applications.

Lessons from image perception studies for the design of medical imaging systems

Our laboratory uses image perception studies to optimize the acquisition and processing of image sequences from x-ray fluoroscopy and interventional MRI (iMRI) both of which are used to guide complex minimally invasive treatments of cancer and vascular disease. Fluoroscopy consists of high frame rate, quantum-limited image sequences. Since it accounts for over half of the diagnostic population x-ray dose, we attempt to reduce dose by optimizing image acquisition and filtering. We quantify image quality using human detection experiments and modeling. Human spatio-temporal processing greatly affects results. For example, spatial noise reduction filtering is significantly more effective on image sequences than on single image frames where it gives relatively little improvement due to the deleterious effect of spatial noise correlation. At CWRU, we use iMRI to guide a radio-frequency probe used for the thermal ablation of cancer. Improving the speed and accuracy of insertion to the target will reduce patient risk and discomfort. We are investigating keyhole imaging whereby one updates only a portion of the Fourier domain at each time step, producing a fast, approximate image sequence. To optimize the very large number of techniques and parameters, we use a perceptual difference model that quantifies the degrading effects introduced by fast MR imaging, including the blurring of interventional devices. Preliminary studies show that a perpendicular frequency encoding direction provides superior image quality in the region of interest compared to other keyhole stripe orientations. Together these two applications illustrate that image perception studies can impact the design of medical imaging systems.

Quantitative image quality evaluation of spiral MRI techniques under noisy conditions

Spiral sampling of k-space is a popular technique in fast MRI. Many methods are available for spiral acquisition and reconstruction. We used a Perceptual Difference Model (PDM) to evaluate these selections and to examine the effects of noise. PDM is a human observer model that calculates the visual difference between a “test image” and a “gold standard image.” PDM has been shown to correlate well with human observers in a variety of MR experiments including added noise, increased blurring, keyhole imaging, and spiral imaging. We simulated MR images from six different interleave patterns, seven different sampling levels, three different density compensation methods, and four different reconstruction options under zero noise and three noise levels. By comparing results with and without noise, we can separate noise effects from reconstruction errors. Comparing many different conditions, Voronoi (VOR) plus conventional regridding was good for high SNR data. In low SNR conditions, area density function (ADF) was better. One can also quantitatively compare different acquisition parameters; smaller numbers of interleaves and high number of samples were very desirable when noise was applied, because high frequency sampling was ensured. We conclude that PDM scoring provides an objective, useful tool for the assessment of spiral MR image quality and can greatly aid the design of MR acquisition and signal processing strategies.

Validation and application of a perceptual difference model for keyhole MR imaging

To optimize the many parameters in keyhole MR imaging, we validated and applied a human visual system (HVS) perceptual difference model (PDM) to simulated keyhole images. A series of full k-space images were acquired during the insertion of a needle into ex vivo bovine liver. Human observers rated the quality of images, and we compared ratings with the PDM output to validate and calibrate the model. In a second experiment, eight keyhole sequences were evaluated by the HVS PDM. A linear relationship with R/sup 2/=99.68% was found by regressing the model output versus human observer ratings. According to the perceptual model, the quality of the entire image is preserved most favorably with a stripe parallel to the direction of insertion. For a region of interest around the needle, a perpendicular stripe resulted in the lowest level of image error. Examination of rotating stripes of k-space show that a step of 45 degrees gives better image quality. Initial experience indicates that the HVS model is an objective, promising tool for the automated evaluation and optimization of keyhole imaging sequences.