M. S. Smyczynski

Effect of block-iterative acceleration on Ga-67 tumor detection in thoracic SPECT

A combination of human localization receiver operating characteristic (LROC) and channelized Hotelling observer (CHO) ROC psychophysical studies were used to investigate how accelerated ordered-subset expectation maximization (OSEM) and rescaled block-iterative (RBI) EM reconstruction affect tumor detection in simulated Ga-67 SPECT images, The tumors were 1-cm-diameter spheres within the chest region of the three-dimensional mathematical cardiac-torso phantom. Previous work with iterative detector resolution compensation showed that eight iterations of the OSEM algorithm with a subset size of eight (16 subsets) offered optimal observer performance. For the LROC study in this paper, the OSEM and RBI algorithms were implemented using subset sizes P and iterations K that satisfied the relation P=K for P=1, 2, 4, and 8. The CHO was applied to reconstruction strategies that deviated from this relation. Results show that using P/spl les/2 penalized observer performance compared to strategies with larger subset sizes. Other researchers have reported on the more stable convergence and noise properties of the RBI algorithm [(Byrne, 1996) and (Lalush and Tsui, 2000)]. In a similar vein, we found that an RBI strategy with a subset size of P produced the same performance as an OSEM strategy with subset size 2P. As neither algorithm displayed a decisive advantage in speed over the other, we conclude that the RBI algorithm is the better choice for accelerating the Ga-67 reconstructions.

An evaluation of iterative reconstruction strategies based on mediastinal lesion detection using hybrid Ga-67 SPECT images.

Using psychophysical studies, the authors have evaluated the effectiveness of various strategies for compensating for physical degradations in SPECT imaging. The particular application was Ga-67-citrate imaging of mediastinal tumors, which was chosen because Ga-67 is a particularly challenging radionuclide for imaging. The test strategies included compensations for nonuniform attenuation, distance-dependent spatial resolution, and scatter applied in various combinations as part of iterative reconstructions with the rescaled block iterative-expectation maximization (RBI-EM) algorithm. The authors also evaluated filtered backprojection reconstructions. Strategies were compared on the basis of human-observer studies of lesion localization and detection accuracy using the localization receiver operating characteristics (LROC) paradigm. These studies involved hybrid images which were obtained by adding the projections of Monte Carlo-simulated lesions to disease-free clinical projection data. The background variability in these images can provide a more realistic assessment of the relative utility of reconstruction strategies than images from anthropomorphic digital phantoms. The clinical datasets were obtained using a GE-VG dual-detector SPECT system with CT-estimated attenuation maps. After determining a target lesion contrast, they conducted pilot LROC studies to obtain a near-optimal set of reconstruction parameters for each strategy, and then conducted the strategy comparison study. The results indicate improved detection accuracy with RBI-EM as more compensations are applied within the reconstruction. The relative rankings of the test strategies agreed in most cases with those of previous studies that employed simulated projections of digital anthropomorphic phantoms, thus confirming the findings of those studies.

Impact of respiratory motion on the detection of small pulmonary nodules in SPECT imaging

The objective of this investigation is to determine the impact of respiratory motion on the detection of small solitary pulmonary nodules (SPN) in single photon emission computed tomographic (SPECT) imaging. We have previously modeled the respiratory motion of SPN based on the change of location of anatomic structures within the lungs identified on breath-held CT images of volunteers acquired at two different stages of respiration. This information on respiratory motion within the lungs was combined with the end-expiration and time-averaged NCAT phantoms to allow the creation of source and attenuation maps for the normal background distribution of Tc-99m NeoTect. With the source and attenuation distribution thus defined, the SIMIND Monte Carlo program was used to produce SPECT projection data for the normal background and separately for each of 150 end-expiration and time-averaged simulated 1.0 cm tumors. Normal and tumor SPECT projection sets each containing one lesion were combined with a clinically realistic noise level and counts. These were reconstructed with RBI-EM using 1) no correction (NC), 2) attenuation correction (AC), 3) detector response correction (RC), and 4) attenuation correction, detector response correction, and scatter correction (ACRCSC). The post-reconstruction parameters of number of iterations and 3-D Gaussian filtering were optimized by human- observer studies. Comparison of lesion detection by human- observer LROC studies reveals that respiratory motion degrades tumor detection for all four reconstruction strategies, and that the magnitude of this effect is greatest for NC and RC, and least for AC RC SC. Additionally, the AC RC SC strategy results in the best detection of lesions.

Investigation of respiration motion of the heart based on semi-automated segmentation and modeling of respiratory-gated CT data

One of the factors limiting the diagnostic accuracy of cardiac SPECT perfusion imaging is the respiratory motion of the heart. Several authors have investigated the motion of heart due to respiration. In this work we have 4D-CT data for 7 patients, consisting of 10 respiration gated non-contrast CT datasets covering the heart region for each patient. We perform a segmentation and registration of the heart datasets in sequence to determine the gross rigid-body motion of the heart due to respiration. For each patient, we segment the heart with a prior shape with an initial pose on one coronal slice of one of the respiration stages, and then the algorithm tracks the object through the other coronal slices. The segmentation results for first stage of respiration are used to initiate the segmentation of the heart at second stage, and so on for the other stages of respiration. A 6-parameter rigid-body registration of the first stage of respiration to the 9 consequent stages estimates the gross motion of the heart. The results of tracking heart motion for the 7 patients indicate a SI axis translation with an (absolute) range of 2.6 to 10.7 mm and mean of 5.7 mm, and standard deviation of 3.7 mm, during expiration. Mean rotations of 3.5 deg about the AP-axis, and 1.2 deg about the RL axis were also observed

Impact of respiratory motion on the detection of solitary pulmonary nodules with SPECT tumor imaging of NeoTect

We have previously modeled the respiratory motion of solitary pulmonary nodules (SPN) based on the change of location of anatomic structures within the lungs identified on breath-held CT images of volunteers acquired at two different stages of respiration. The goal of this investigation is to make use of this modeling to investigate the impact of respiratory motion on the detection of solitary pulmonary nodules with single photon emission computed tomographic (SPECT) imaging using Tc-99m labeled NeoTect. To do this, end-expiration and respiration-averaged source and attenuation maps were created from the NCAT phantom and input to the SIMIND Monte Carlo package.

Accounting for anatomical noise in SPECT with a visual-search human-model observer

Reliable human-model observers for clinically realistic detection studies are of considerable interest in medical imaging research, but current model observers require frequent revalidation with human data. A visual-search (VS) observer framework may improve reliability by better simulating realistic etection-localization tasks. Under this framework, model observers execute a holistic search to identify tumor-like candidates and then perform careful analysis of these candidates. With emission tomography, anatomical noise in the form of elevated uptake in neighboring tissue often complicates the task. Some scanning model observers simulate the human ability to read around such noise by presubtracting the mean normal background from the test image, but this backgroundknown- exactly (BKE) assumption has several drawbacks. The extent to which the VS observer can overcome these drawbacks was investigated by comparing it against humans and a scanning observer for detection of solitary pulmonary nodules in a simulated SPECT lung study. Our results indicate that the VS observer offers a robust alternative to the scanning observer for modeling humans.

LROC Investigation of Three Strategies for Reducing the Impact of Respiratory Motion on the Detection of Solitary Pulmonary Nodules in SPECT

The objective of this investigation was to determine the effectiveness of three motion reducing strategies in diminishing the degrading impact of respiratory motion on the detection of small solitary pulmonary nodules (SPNs) in single-photon emission computed tomographic (SPECT) imaging in comparison to a standard clinical acquisition and the ideal case of imaging in the absence of respiratory motion. To do this nonuniform rational B-spline cardiac-torso (NCAT) phantoms based on human-volunteer CT studies were generated spanning the respiratory cycle for a normal background distribution of Tc-99 m NeoTect. Similarly, spherical phantoms of 1.0-cm diameter were generated to model small SPN for each of the 150 uniquely located sites within the lungs whose respiratory motion was based on the motion of normal structures in the volunteer CT studies. The SIMIND Monte Carlo program was used to produce SPECT projection data from these. Normal and single-lesion containing SPECT projection sets with a clinically realistic Poisson noise level were created for the cases of 1) the end-expiration (EE) frame with all counts, 2) respiration-averaged motion with all counts, 3) one fourth of the 32 frames centered around EE (Quarter Binning), 4) one half of the 32 frames centered around EE (Half Binning), and 5) eight temporally binned frames spanning the respiratory cycle. Each of the sets of combined projection data were reconstructed with RBI-EM with system spatial-resolution compensation (RC). Based on the known motion for each of the 150 different lesions, the reconstructed volumes of respiratory bins were shifted so as to superimpose the locations of the SPN onto that in the first bin (Reconstruct and Shift). Five human observers performed localization receiver operating characteristics (LROC) studies of SPN detection. The observer results were analyzed for statistical significance differences in SPN detection accuracy among the three correction strategies, the standard acquisition, and the ideal case of the absence of respiratory motion. Our human-observer LROC determined that Quarter Binning and Half Binning strategies resulted in SPN detection accuracy statistically significantly below ( ) that of standard clinical acquisition, whereas the Reconstruct and Shift strategy resulted in a detection accuracy not statistically significantly different from that of the ideal case. This investigation demonstrates that tumor detection based on acquisitions associated with less than all the counts which could potentially be employed may result in poorer detection despite limiting the motion of the lesion. The Reconstruct and Shift method results in tumor detection that is equivalent to ideal motion correction.

Effectiveness of three alternative strategies in reducing the degrading impact of respiratory motion on the detection of small pulmonary nodules in SPECT imaging

The objective of this investigation is to determine the effectiveness of three methods in reducing the impact of respiratory motion on the detection of small solitary pulmonary nodules in single photon emission computed tomographic imaging. Based on our previous work, 32 NCAT normal torso phantoms were generated over the entire respiratory cycle to create source and attenuation maps for the normal background distribution of Tc-99m NeoTect. Similarly, 32 NCAT sphere phantoms of 1.0 cm diameter were generated over the entire respiratory cycle for each of 150 uniquely located points within the lungs. The SIMIND Monte Carlo program was used to produce SPECT projection data for the normal background and separately for each of 150 lesions for all 32 frames and for a time-averaged case. Normal and tumor SPECT projection sets each containing one lesion were combined with a clinically realistic noise level and counts as follows: 1) end-expiration with all counts (frame 1), 2) time-averaged with all counts (frame av), and 3) each of the 32 frames containing 1/32 of the total counts. Projection data of the 32 frames was combined to form ten different bins. The first eight bins each consisted of 4 frames. The 9th bin, centered about end-expiration, consisted of 8 frames (quarter binning). The 10th bin, also centered about end-expiration, consisted of 16 frames (half binning). Each of the twelve sets of combined projection data was reconstructed with RBI-EM with RC. Based on known motion for each of the 150 different lesions, the reconstructed volumes of the first eight bins were shifted to superimpose the reconstructions over each of the 150 lesions. Comparison of lesion detection by human-observer LROC studies reveals that quarter binning results in the lowest rate of detection and that the reconstruct and shift method results in the greatest rate of detection. Additionally, the rate of detection by superimposing the reconstructions over the lesion is even superior to frame 1.

An evaluation of iterative reconstruction strategies on mediastinal lesion detection using hybrid Ga-67 SPECT images

Hybrid LROC studies can be used to more realistically assess the impact of reconstruction strategies, compared to those constructed with digital phantoms. This is because hybrid data provides the background variability that is present in clinical imaging, as well as, control over critical imaging parameters, required to conduct meaningful tests. Hybrid data is obtained by adding Monte Carlo simulated lesions to disease free clinical projection data. Due to Ga-67 being a particularly challenging radionuclide for imaging, we use Ga- 67 hybrid SPECT data to study the effectiveness of the various correction strategies developed to account for degradations in SPECT imaging. Our data was obtained using GE-VG dual detector SPECT-CT camera. After determining a target lesion contrast we conduct pilot LROC studies to obtain a near-optimal set of reconstruction parameters for the different strategies individually. These near-optimal parameters are then used to reconstruct the final evaluation study sets. All LROC study results reported here were obtained employing human observers only. We use final LROC study results to assess the impact of attenuation compensation, scatter compensation and detector resolution compensation on data reconstructed with the RBI-EM algorithm. We also compare these with FBP reconstructions of the same dataset. Our experiment indicates an improvement in detection accuracy, as various degradations inherent in the image acquisition process are compensated for in the reconstruction process.

An investigation of reconstruction strategies for mediastinal lesion detection using hybrid Ga-67 SPECT images

Ga-67 SPECT studies are especially useful in the pretreatment staging and post-treatment follow-up of patients with Hodgkins and non-Hodgkins lymphoma. Ga-67 is however a particularly challenging radionuclide for imaging. Patient specific background variability, which manifests itself as structured noise, can further impact lesion detection accuracy. A number of MCAT phantom studies with simulated lesions and idealized source distributions have been done to study the impact of compensation strategies on lesion detection accuracy. However, to more accurately assess the impact of various correction strategies on lesion detection a study employing actual clinical images with true clinical distributions is of interest. The approach we chose for conducting such an investigation was performing LROC studies employing hybrid images. Hybrid images are normal Ga-67 studies with their projection data modified by the addition of Monte Carlo simulated lesions. Our datasets consist of clinically normal Ga-67 SPECT/CT acquisitions obtained using the GE-VG dual detector SPECT/CT camera. After determining a target image contrast using human observers, we conducted pilot LROC studies to determine the optimal parameters for the reconstruction methods using human observers. Herein we report on the optimization for the forthcoming comparison of attenuation compensation, scatter compensation, and detector resolution compensation strategies used with the RBI reconstruction method and FBP reconstruction