Browsing by Subject "SPECT"

Purpose: Single photon emission computed tomography (SPECT) is considered as a functional nuclear medicine imaging technique which is commonly used in the clinic. However, it suffers from low resolution and high noise because of the physical structure and photon scatter and attenuation. This research aims to develop a compact neural network reconstructing SPECT images from projection data, with better resolution and low noise. Methods and Materials: This research developed a MATLAB program to generate 2-D brain phantoms. We totally generated 20,000 2-D phantoms and corresponding projection data. Furthermore, those projection data were processed with Gaussian filter and Poisson noise to simulate the real clinical situation. And 16,000 of them were used to train the neural network, 2,000 for validation, and the final 2,000 for testing. To simulate the real clinical situation, there are five groups of projection data with decreasing acquisition views are used to train the network. Inspired by the SPECTnet, we used a two-step training strategy for network design. The full-size phantom images (128×128 pixels) were compressed into a vector (256×1) at first, then they were decompressed to full-size images again. This process was achieved by the AutoEncoder (AE) consisting of encoder and decoder. The compressed vector generated by the encoder works as targets in the second network, which map projection to compressed images. Then those compressed vectors corresponding to the projection were reconstructed to full-size images by the decoder. Results: A total of 10,000 testing dataset divided into 5 groups with 360 degrees, 180 degrees, 150 degrees, 120 degrees and 90 degrees acquisition, respectively, are generated by the developed neural network. Results were compared with those generated by conventional FBP methods. Compared with FBP algorithm, the neural network can provide reconstruction images with high resolution and low noise, even if under the limited-angles acquisitions. In addition, the new neural network had a better performance than SPECTnet. Conclusions: The network successfully reconstruct projection data to activity images. Especially for the groups whose view angles is less than 180 degrees, the reconstruction images by neural network have the same excellent quality as other images reconstructed by projection data over 360 degrees, even has a higher efficiency than the SPECTnet. Keywords: SPECT; SPECT image reconstruction; Deep learning; convolution neural network. Purpose: Single photon emission computed tomography (SPECT) is considered as a functional nuclear medicine imaging technique which is commonly used in the clinic. However, it suffers from low resolution and high noise because of the physical structure and photon scatter and attenuation. This research aims to develop a compact neural network reconstructing SPECT images from projection data, with better resolution and low noise. Methods and Materials: This research developed a MATLAB program to generate 2-D brain phantoms. We totally generated 20,000 2-D phantoms and corresponding projection data. Furthermore, those projection data were processed with Gaussian filter and Poisson noise to simulate the real clinical situation. And 16,000 of them were used to train the neural network, 2,000 for validation, and the final 2,000 for testing. To simulate the real clinical situation, there are five groups of projection data with decreasing acquisition views are used to train the network. Inspired by the SPECTnet, we used a two-step training strategy for network design. The full-size phantom images (128×128 pixels) were compressed into a vector (256×1) at first, then they were decompressed to full-size images again. This process was achieved by the AutoEncoder (AE) consisting of encoder and decoder. The compressed vector generated by the encoder works as targets in the second network, which map projection to compressed images. Then those compressed vectors corresponding to the projection were reconstructed to full-size images by the decoder. Results: A total of 10,000 testing dataset divided into 5 groups with 360 degrees, 180 degrees, 150 degrees, 120 degrees and 90 degrees acquisition, respectively, are generated by the developed neural network. Results were compared with those generated by conventional FBP methods. Compared with FBP algorithm, the neural network can provide reconstruction images with high resolution and low noise, even if under the limited-angles acquisitions. In addition, the new neural network had a better performance than SPECTnet. Conclusions: The network successfully reconstruct projection data to activity images. Especially for the groups whose view angles is less than 180 degrees, the reconstruction images by neural network have the same excellent quality as other images reconstructed by projection data over 360 degrees, even has a higher efficiency than the SPECTnet. Keywords: SPECT; SPECT image reconstruction; Deep learning; convolution neural network.

AbstractPinhole imaging is a widely used method for high spatial resolution single gamma imaging with a small required field of view (FOV). Many factors affect pinhole imaging: (I) the geometric parameters of the pinhole imaging system, such as the pinhole diameter, focal length and opening angle; (II) the position, range, sampling interval, and sampling time of the pinhole trajectory; and (III) the image reconstruction algorithm. These differences result in different trade-offs between resolution, sensitivity, noise level, imaging FOV, and data-sampling integrity levels. In pinhole imaging, many different pinhole trajectories might be considered. The conventional approach to assessing different trajectories is to reconstruct images from the various trajectories and then assess which image is best. Such an approach is however time consuming, since (I) image reconstruction is time-consuming and (II) image analysis often requires ensembles of images, where the ensemble is time consuming to calculate, consumes considerable computer storage, and requires investigator time to organize and analyze. The object of this project is to develop a method to rapidly select the optimal SPECT pinhole trajectory from among several candidate trajectories. Equivalent Resolution Geometric Efficiency (ERGE) is proposed to represent the spatial resolution and geometric efficiency; a higher ERGE means a better trajectory. To verify this metric, two-dimensional and three-dimensional visualizations of the pinhole trajectory are implemented in software as a way to assess trajectories visually and qualitatively. Several different trajectories are employed, projection data are computer-simulated, including spatial resolution blurring and pseudo-random Poisson noise, and image reconstruction is performed using the OSEM algorithm. The reconstructed images are analyzed to characterize the performance of the different trajectories to assess whether the best trajectory can be determined by the sensitivity and resolution characteristics of the individual pinhole locations that make up the trajectory. Ultimately, the method proved to be effective. In this study, a relatively simple low-cost prospective method for selecting the optimal SPECT pinhole trajectory has been shown to be effective. Only very fast and simple calculations, utilizing Microsoft Excel for example, are required. The method does not require simulating or acquiring projection data and does not require image reconstruction. The ranking of ERGE matches well with the ranking of reconstructed images based on Root Mean Square Error (RMSE). In clinical and scientific research, many different pinhole trajectories might be considered for pinhole 3D SPECT imaging, but it is too time-consuming to assess each trajectory via reconstructed images. By demonstrating the validity of this method for assessing trajectories, it may facilitate the improved use of 3D pinhole SPECT imaging in clinical and scientific research. Keywords: Pinhole Trajectory, SPECT, Forward Projection, OSEM, Equivalent Resolution Geometric Efficiency (ERGE), Root Mean Square Error (RMSE).

Theranostics is an evolving approach in nuclear medicine that aims to combine diagnostic and therapeutic value into a single agent of delivery. With increased interest in alpha-emitting radionuclides for their short effective range and high linear energy transfer, astatine-211 is a promising radionuclide for therapy applications. Previously at Duke University, the ability to image and quantitate images of astatine-211 was investigated and determined to be a challenge due to attenuation and collimation effects on desired photons for imaging, and undesirable high energy emission contributions. This research builds on that previous work to investigate the image quality extent of single photon planar and SPECT imaging for astatine-211 when considering relevant organs that could be at risk for radiation damage based on the distribution of the molecule carrying the At-211. The investigation is broken down into several experiments that provide the basis for understanding the potential of astatine-211 to perform as an imaging radionuclide, and the needed factors for image reconstruction including the appropriate linear attenuation coefficient and k-factor for dual-energy scatter correction. Two phantom designs were created. One was used to provide a baseline image quality comparison of four radionuclides (F-18 for PET, Tc-99m, Lu-177, and At-211 for single photon planar imaging). The other represented the salivary glands in the head and kidneys and tumors in the torso. Imaging the same realistically large phantom showed that only the fluorine-18 PET images 1 cm targets successfully, while technetium-99m and lutetium-177 are comparable in imaging 2 cm and 3 cm targets, and astatine-211 can only image 3 cm targets. This work successfully simulated the salivary glands and kidneys in an anthropomorphic phantom. The results indicated that the use of a k-factor of 1.1 is reasonable in the scatter correction of imaging astatine-211, which effectively reduced downscattered gamma rays in the images. Additionally, the results confirm that the medium energy general purpose collimator is better suited than the low energy high resolution collimator for imaging astatine-211 with improved SNR and comparable noise quality.

This thesis research builds upon prior work that developed separate SPECT and CT (computed mammotomography, or breast CT) devices that were independently capable of imaging an uncompressed breast in 3D space. To further develop the system as a clinically viable device, it was necessary to integrate the separate imaging systems onto a single gantry, and to simultaneously design a patient-friendly bed that could routinely and effectively position the patient during dual-modality imaging of her uncompressed breast in the system's common field of view. This thesis describes this process and also investigates practical challenges associated with dedicated breast imaging of a prone patient using the integrated SPECT-CT device.

We initially characterized the practicability of implementing the novel x-ray beam ultra-thick K-edge filtration scheme designed for routine use with the breast CT system. Extensive computer simulations and physical measurements were performed to characterize the x-ray beam produced using K-edge filtration with cerium and to compare it to beams produced using other filtration methods and materials. The advantages of using this heavily filtered x-ray beam for uncompressed breast CT imaging were then further evaluated by measuring the dose absorbed by an uncompressed cadaver breast during the course of a routine tomographic scan. It was found that the breast CT device is indeed capable of imaging uncompressed breasts at dose levels below that of the maximum utilized for dual-view screening mammography.

To prepare the separate SPECT and CT systems for integration onto a single platform, the cross contamination of the image of one modality by primary and scattered photons of the complementary modality was quantified. It was found that contamination levels of the emission (SPECT) image by the x-ray transmission source were generally far less than 2% when using photopeak energy windows up to ±8%. In addition, while there was some quantifiable evidence of a variation in the transmission image in response to the presence of 99mTc photons in the patient, the effect of primary and scattered 99mTc photons on the visibility of 5 mm acrylic photons in a low contrast x-ray transmission environment was negligible.

A novel, tiered, stainless steel patient bed was then designed to allow dual-modality imaging using the integrated SPECT-CT system. The performance of the hybrid SPECT-CT system was evaluated during early stage dual-modality patient imaging trials with particular emphasis placed on the performance of the patient bed. The bed was successful in its primary task of enabling dual-modality imaging of a patient's breast in the common field of view, but practical challenges to more effective patient imaging were identified as well as some novel solutions to these challenges.

In the final section of the thesis research, the feasibility of using two of these solutions was investigated with a view to imaging more of the patient's posterior breast volume. Limited angle tomographic trajectories and trajectories that involve raising or lowering the patient bed in mid tomographic acquisition were initially investigated using various geometric phantoms. A very low contrast imaging task was then tested using an observer study to quantify the effect of these trajectories on the ability of observers to maintain visibility of small geometric objects.

This initial integrated SPECT-CT imaging system has demonstrated its ability to successfully perform low dose, dual-modality imaging of the uncompressed breast. Challenges and solutions have been identified here that will make future SPECT-CT designs even more powerful and a clinically relevant technique for molecular imaging of the breast.

The overall goal of this dissertation is to optimize and evaluate the performance of the single photon emission computed tomography (SPECT) subsystem of a dedicated three-dimensional (3D) dual-modality breast imaging system for enhanced semi-automated, quantitative clinical imaging. This novel hybrid imaging system combines functional or molecular information obtained with a SPECT subsystem with high-resolution anatomical imaging obtained with a low dose x-ray Computed Tomography (CT) subsystem. In this new breast imaging paradigm, coined "mammotomography," the subject is imaged lying prone while the individual subsystems sweep 3-dimensionally about her uncompressed, pendant breast, providing patient comfort compared to traditional compression-based imaging modalities along with high fidelity and information rich images for the clinician.

System evaluation includes a direct comparison between dedicated 3D SPECT and dedicated 2D scintimammography imaging using the same high performance, semi-conductor gamma camera. Due to the greater positioning flexibility of the SPECT system gantry, under a wide range of measurement conditions, statistically significantly (p<0.05) more lesions and smaller lesion sizes were detected with dedicated breast SPECT than with compressed breast scintimammography. The importance of good energy resolution for uncompressed SPECT breast imaging was also investigated. Results clearly illustrate both visual and quantitative differences between the various energy windows, with energy windows slightly wider than the system resolution having the best image contrast and quality.

An observer-based contrast-detail study was performed in an effort to evaluate the limits of object detectability under various imaging conditions. The smallest object detail was observed using a 45-degree tilted trajectory acquisition. The complex 3D projected sine wave acquisition, however, had the most consistent combined intra and inter-observer results, making it potentially the best imaging approach for consistent clinical imaging.

Automatic ROR contouring is implemented using a dual-layer light curtain design, ensuring that an arbitrarily shaped breast is within ~1 cm of the camera face, but no closer than 0.5 cm at every projection angle of a scan. Autocontouring enables simplified routine scanning using complex 3D trajectories, and yields improved image quality. Absolute quantification capabilities are also integrated into the SPECT system, allowing the calculation of in vivo total lesion activity. Initial feasibility studies in controlled low noise experiments show promising results with total activity agreement within 10% of the dose calibrator values.

The SPECT system is integrated with a CT scanner for added diagnostic power. Initial human subject studies demonstrate the clinical potential of the hybrid SPECT-CT breast imaging system. The reconstructed SPECT-CT images illustrate the power of fusing functional SPECT information to localize lesions not easily seen in the anatomical CT images. Enhanced quantitative 3D SPECT-CT breast imaging, now with the ability to dynamically contour any sized breast, has high potential to improve detection, diagnosis, and characterization of breast cancer in upcoming larger-scale clinical testing.

The work presented in this dissertation focuses on evaluation of absolute quantification accuracy in dedicated breast SPECT-CT. The overall goal was to investigate through simulations and measurements the impact and utilization of various correction methods for scattered and attenuated photons, characterization of incomplete charge collection in Cadmium Zinc Telluride detectors as a surrogate means of improving scatter correction, and resolution recovery methods for modeling collimator blur during image reconstruction. The quantification accuracy of attenuation coefficients in CT reconstructions was evaluated in geometric phantoms, and a slice-by-slice breast segmentation algorithm was developed to separate adipose and glandular tissue. All correction and segmentation methods were then applied to a pilot study imaging parathyroid patients to determine the average uptake of Tc-99m Sestamibi in healthy breast tissue, including tissue specific uptake in adipose and glandular tissue.

Monte Carlo methods were utilized to examine the changes in incident scatter energy distribution on the SPECT detector as a function of 3D detector position about a pendant breast geometry. A simulated prone breast geometry with torso, heart, and liver was designed. An ideal detector was positioned at various azimuthal and tilted positions to mimic the capabilities of the breast SPECT subsystem. The limited near-photopeak scatter energy range in simulated spectra was linearly fit and the slope used to characterize changes in scatter distribution as a function of detector position. Results show that the detected scatter distribution changes with detector tilt, with increasing incidence of high energy scattered photons at larger detector tilts. However, reconstructions of various simulated trajectories show minimal impact on quantification (<5%) compared to a primary-only reconstruction.

Two scatter compensation methods were investigated and compared to a narrow photopeak-only windowing for quantification accuracy in large uniform regions and small, regional uptake areas: 1) a narrow ±4% photopeak energy window to minimize scatter in the photopeak window, 2) the previously calibrated dual-energy window scatter correction method, and 3) a modified dual-energy window correction method that attempts to account for the effects of incomplete charge collection in Cadmium Zinc Telluride detectors. Various cylindrical phantoms, including those with imbedded hot and cold regions, were evaluated. Results show that the Photopeak-only and DEW methods yield reasonable quantification accuracy (within 10%) for a wide range of activity concentrations and phantom configurations. The mDEW demonstrated highly accurate quantification measurements in large, uniform regions with improved uniformity compared to the DEW method. However, the mDEW method is susceptible to the calibration parameters and the activity concentration of the scanned phantom. The sensitivity of the mDEW to these factors makes it a poor choice for robust quantification applications. Thus, the DEW method using a high-performance CZT gamma camera is still a better choice for quantification purposes

Phantoms studies were performed to investigate the application of SPECT vs CT attenuation correction. Minor differences were observed between SPECT and CT maps when assuming a uniformly filled phantom with the attenuation coefficient of water, except when the SPECT attenuation map volume was significantly larger than the CT volume. Material specific attenuation coefficients reduce the corresponding measured activity concentrations compared to a water-only correction, but the results do not appear more accurate than a water-only attenuation map. Investigations on the impact of image registration show that accurate registration is necessary for absolute quantification, with errors up to 14% observed for 1.5cm shifts.

A method of modeling collimator resolution within the SPECT reconstruction algorithm was investigated for its impact on contrast and quantification accuracy. Three levels of resolution modeling, each with increasing ray-sampling, were investigated. The resolution model was applied to both cylindrical and anthropomorphic breast phantoms with hot and cold regions. Large volume quantification results (background measurements) are unaffected by the application of resolution modeling. For smaller chambers and simulated lesions, contrast generally increases with resolution modeling. Edges of lesions also appear sharper with resolution modeling. No significant differences were seen between the various levels of resolution modeling. However, Gibbs artifacts are amplified at the boundaries of high contrast regions, which can significantly affect absolute quantification measurements. Convergence with resolution modeling is also notably slower, requiring more iterations with OSEM to reach a stable mean activity concentration. Additionally, reconstructions require far more computing time with resolution modeling due to the increase in number of sampling rays. Thus while the edge enhancement and contrast improvements may benefit lesion detection, the artifacts, slower convergence, and increased reconstruction time limit the utility of resolution modeling for both absolute quantification and clinical imaging studies.

Finally, a clinical pilot study was initiated to measure the average uptake of Tc-99m Sestamibi in healthy breast tissue. Subjects were consented from those undergoing diagnostic parathyroid studies at Duke. Each subject was injected with 25mCi of Sestamibi as part of their pre-surgical parathyroid SPECT imaging studies and scanned with the dedicated breast SPECT-CT system before their diagnostic parathyroid SPECT scan. Based on phantom studies of CT reconstructed attenuation coefficient accuracy, a slice-by-slice segmentation algorithm was developed to separate breast CT data into adipose and glandular tissue. SPECT data were scatter, attenuation, and decay corrected to the time of injection. Segmented CT images were used to measure average radiotracer concentration in the whole breast, as well as adipose and glandular tissue. With 8 subjects scanned, the average measured whole breast activity concentration was found to be 0.10µCi/mL. No significant differences were seen between adipose and glandular tissue uptake.

In conclusion, the application of various characterization and correct methods for quantitative SPECT imaging were investigated. Changes in detected scatter distribution appear to have minimal impact on quantification, and characterization of low-energy tailing for a modified scatter subtraction method yields inferior overall quantification results. Comparable quantification accuracy is seen with SPECT and CT-based attenuation maps, assuming the SPECT-based volume is fairly accurate. In general, resolution recovery within OSEM yields higher contrast, but quantification accuracy appears more susceptible to measurement location. Finally, scatter, attenuation, and resolution recovery methods, along with a breast segmentation algorithm, were implemented in a clinical imaging study for quantifying Tc-99m Sestamibi uptake. While the average whole breast uptake was measured to be 0. 10µCi/mL, no significant differences were seen between adipose and glandular tissue or when implementing resolution recovery. Thus, for future clinical imaging, it's recommended that the application of the investigated correction methods should be limited to the traditional DEW method and CT-based attenuation maps for quantification studies.

On-board imaging is useful for guiding radiation to patients in the treatment position; however, current treatment-room imaging modalities are not sensitive to physiology - features that may differentiate tumor from nearby tissue or identify biological targets, e.g., hypoxia, high tumor burden, or increased proliferation. Single photon emission computed tomography (SPECT) is sensitive to physiology. We propose on-board SPECT for biological target localization.

Localization performance was studied in computer-simulated and scanner-acquired parallel-hole SPECT images. Numerical observers were forced to localize hot targets in limited search volumes that account for uncertainties common to radiation therapy delivery. Localization performance was studied for spherical targets of various diameters, activity ratios, and anatomical locations. Also investigated were the effects of detector response function compensation (DRC) and observer normalization on target localization. Localization performance was optimized as a function of iteration number and degree of post-reconstruction smoothing. Localization error patterns were analyzed for directional dependencies and were related to the detector trajectory. Localization performance and the effect of the detector trajectory were investigated in a hardware study using a whole-body phantom.

Typically targets of 6:1 activity were localized as accurately using 4-minute scans as those of 3:1 activity using 20-minute scans. This trend is consistent with the relationship between contrast and noise in the contrast-to-noise ratio (CNR) and implies that higher contrast targets are better candidates for on-board SPECT because of time constraints in the treatment room. Using 4-minute scans, mean localization errors were within 2 mm for superficial targets of 6:1 activity that were proximal to the detector trajectory and of at least 14 mm in diameter. Localization was significantly better (p < 0.05, Wilcoxon signed-rank test) with than without observer normalization and DRC at 5 of 6 superficial tumor sites. Observer normalization improved localization substantially for a target proximal to the much hotter heart. Localization error patterns were shown to be anisotropic and dependent on target position relative to the detector trajectory. Detector views of close approach and of minimal attenuation were predictive of directions with the smallest (magnitude) localization bias and precision. The detector trajectory had a substantial effect on localization performance. In scanner-acquired SPECT images, mean localization errors of a 22-mm-diameter superficial target were 0.8, 1.5, and 6.9 mm respectively using proximal 180°, 360°, and distal 180° detector trajectories, thus demonstrating the benefits of using a proximal 180° detector trajectory.

In conclusion, the potential performance characteristics of on-board SPECT were investigated using computer-simulation and real-detector studies. Mean localization errors < 2 mm were obtained for proximal, superficial targets with diameters >14 mm and of 6:1 activity relative to background using scan times of approximately 5 minutes. The observed direction-dependent localization errors are related to the detector trajectory and have important implications for radiation therapy. This works shows that parallel-hole SPECT could be useful for localizing certain biological targets.

AbstractIntroduction: SPECT and PET are long established methods for functional imaging of bone lesions, including lesions in bone marrow and bone metastasis. These imaging modalities are however limited by poor spatial resolution which degrades quantitative accuracy and precise localization. This limitation in quantitative accuracy corresponds to the partial volume effect (PVE), in which a portion of the radiotracer activity truly in one structure appears, in the image, to be in nearby image voxels. To some extent PVEs can be corrected by iterative image reconstruction algorithms, such as ordered-subsets expectation maximization (OSEM), that model spatial resolution. This approach is however limited by noise, which is amplified as spatial resolution is recovered and PVEs are reduced. SPECT and PET imaging often involves CT as well. CT provides very high-resolution anatomical information which can be used to correct PVEs in SPECT and PET. One approach to PVE correction is using Markov Random Fields (MRFs) that incorporate anatomical information. However, there has been relatively little investigation on MRF-based PVE correction for SPECT/PET bone imaging using CT information. In this work, two types of CT anatomical information are considered: (i) partial anatomical information (pAI) which distinguishes, for example, compact bone from bone marrow but does not otherwise distinguish the tumor from surrounding tissue and (ii) full anatomical information (fAI), which fully distinguishes tumor from surrounding tissue. Image reconstructions involving pAI and fAI are referred to as RpAI and RfAI, respectively. RfAI is expected to provide the best correction of tumor PVEs, but RpAI may be more often available from CT images. The objective of the work is to assess the effectiveness of RpAI as compared to RfAI and OSEM.

Methods: Radiotracer (SPECT/PET) and attenuation coefficient (CT) phantoms were generated using XCAT software. Tumor lesions with high activity were added to the bone marrow in the radiotracer phantom. Two CT phantoms, pAI and fAI, were generated, with the fAI CT phantom including reduced CT number in the tumor-lesion locations. Projection data were simulated, and images were reconstructed using the computer code SPECT-MAP, with modeled spatial resolutions of 12mm (SPECT-like data) and 6mm (PET-like data). The RpAI and RfAI image reconstructions were performed using the iterative coordinate descent (ICD) algorithm and the Bowsher prior. The reconstructions were performed with projection data at 4 noise levels: 5M-, 50M-, and 100M-counts and noise-free. Reconstructed images were evaluated by visual inspection and by root-mean-square (RMS) error across the entire image and in 2 small ROIs (ROI-1 and ROI-2) surrounding the tumor lesions.

Results: The estimated rmsemin calculated from ROI-1 and ROI-2 reconstructed images of noisy (5M counts) projection data with res-12mm using OSEM, RpAI and RfAI were 0.92E-5 & 0.82E-5 (both at iteration 5, subset 9), 0.76E-5 & 0.65E-5 (both at OPS of 1.0E+4), and 0.44E-5 & 0.44E-5 (both at OPS of 1.0E+4), respectively; while for res-6mm, the rmsemin were 0.85E-5 & 0.81E-5 (both at iteration 10, subset 9), 0.57E-5 & 0.53E-5 (both at OPS of 1.0E+4), 0.37E-5 & 0.37E-5 (both at OPS of 1.0E+4), respectively. At both spatial resolutions, the RpAI reconstructions, using partial anatomical information only, provided reduced RMS errors compared to OSEM. Conclusions: At spatial resolutions characteristic of SPECT and PET, the partial anatomical information available from normal bone structures such as marrow and compact bone can improve estimation of hot-spot lesions, as measured by visual inspection and RMS error.