Enhancing Expression of Functional Human Sodium Iodide Symporter and Somatostatin Receptor in Recombinant Oncolytic Vaccinia Virus for In Vivo Imaging of Tumors.

Oncolytic virus (OV) therapy has emerged as a novel tool in our therapeutic arsenals for fighting cancer. As a live biologic agent, OV has the ability to target and selectively amplify at the tumor sites. We have reported that a vaccinia-based OV (Pexa-Vec) has shown good efficacy in preclinical models and in clinical trials. To give an additional tool to clinicians to allow both treatment of the tumor and improved visualization of tumor margins, we developed new viral-based platforms with 2 specific gene reporters. METHODS: We incorporated the human sodium iodide symporter (hNIS) and the human somatostatin receptor 2 (hSSR2) in the vaccinia-based OV and tested viral constructs for their abilities to track and treat tumor development in vivo. RESULTS: Early and high-level expression of hNIS is detrimental to the recombinant virus, leading to the aggregation of hNIS protein and early cell death. Putting hNIS under a late synthetic promoter allowed a higher functional expression of the protein and much stronger 123I or 99Tc uptake. In vivo, the hNIS-containing virus infected and amplified in the tumor site, showing a better efficacy than the parental virus. The hNIS expression at the tumor site allowed for the imaging of viral infection and tumor regression. Similarly, hSSR2-containing OV vaccinia infected and lysed cancer cells. CONCLUSION: When tumor-bearing mice were given hNIS- and hSSR2-containing OV, 99Tc and 111In signals coalesced at the tumor, highlighting the power of using these viruses for tumor diagnosis and treatment.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome.

PURPOSE: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. METHODS: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. RESULTS: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). CONCLUSIONS: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

SPECT gated blood pool phase analysis of lateral wall motion for prediction of CRT response.

Amplitude, defined as the magnitude of contraction of the myocardium, is obtained from phase analysis but has not been investigated to the same extent as phase-based parameters for predicting the outcome of cardiac resynchronization therapy (CRT). The size of scar present in the lateral wall of the left ventricle (LV) has been shown in some studies to predict response to CRT. Scar is associated with impaired regional LV wall motion and is expected to result in a reduction in the corresponding amplitude values derived from phase analysis. Our objective was to determine the correlation between amplitude and scar, and to evaluate amplitude parameters as surrogates for scar in predicting response to CRT. 49 patients underwent a single photon emission computed tomography (SPECT) radionuclide angiography (RNA) scan as well as FDG viability and Rubidium-82 perfusion PET scans prior to undergoing CRT. Phase analysis was performed on the SPECT RNA data to extract amplitude values used to define amplitude size (AmpSize) and amplitude score (AmpScore) parameters. Scar size and scar score were obtained from the PET scans based on a 5 segment model. Scar parameters were then compared to amplitude parameters in the lateral wall for the whole population as well as both ischemic (N = 27) and non-ischemic (N = 22) populations using Pearson correlation. The ability of amplitude parameters to predict response to CRT was also investigated and compared to scar parameters. The largest ROC AUC values were obtained in the ischemic population where values of 0.67 and 0.68 were observed for lateral wall AmpSize and AmpScore respectively. Both parameters produced the same sensitivity and specificity values of 83 and 67 %. Amplitude size in the lateral wall showed significant correlation with lateral wall scar size in all patients (r = 0.51), which was further strengthened in the ischemic patient sub-group (r = 0.64). Lateral wall amplitude-based parameters obtained from SPECT RNA phase analysis produced an overall accuracy in predicting CRT response in ischemic patients that was not significantly different to that of PET lateral wall scar parameters. A significant correlation existed between amplitude size and scar size in the lateral wall.

Performance evaluation of real-time motion tracking using positron emission fiducial markers.

PURPOSE: Tumor motion due to patient breathing is a factor that limits the accuracy of dose distribution in radiotherapy. One of the methods to improve the accuracy is by applying respiratory gating or tumor tracking. Both techniques require a precise determination of the spatial location of the tumor. We present an experimental evaluation of the performance of PeTrack, a technique that can track internal fiducial markers in real-time for tumor tracking. METHODS: PeTrack uses position sensitive detectors to record annihilation coincidence gamma rays from fiducial positron emission markers implanted in or around the tumor. It uses an expectation-maximization clustering algorithm to track the position of the markers. A normalized least mean square adaptive filter was used to predict the position of the markers 100 and 200 ms in the future. We evaluated the performance of the tracking and of the prediction by using a dynamic anthropomorphic thorax phantom to generate three-dimensional (3D) motion of three fiducial markers. The algorithm was run with four different data sets. In the first run, the motion of the markers was based on a sinusoidal model of respiratory motion. Three additional runs were done with motion based on patient breathing data. RESULTS: In the case of the sinusoidal model, the average 3D root mean square error for all markers was 0.44 mm. For the three runs based on patient breathing data, the precision of the 3D localization was 0.49 mm. At a latency of 100 ms, the average 3D prediction error was 1.3 +/- 0.6 mm for the sinusoidal model and for the three patient breathing runs. At a latency of 200 ms, the average 3D prediction errors were 1.7 +/- 0.8 mm for the sinusoidal model and 1.4 +/- 0.7 mm for the breathing runs. CONCLUSIONS: We conclude that PeTrack can track multiple fiducial markers in real-time with an accuracy and precision smaller than 2 mm. PeTrack can have a direct application in tumor tracking for radiation therapy.

SPECT blood pool phase analysis can accurately and reproducibly quantify mechanical dyssynchrony.

OBJECTIVES: Phase analysis of SPECT blood pool imaging has the potential to assess mechanical dyssynchrony (MD). However, wall motion of the left ventricle (LV) from SPECT images can be based on either time-activity or time-distance curves. In this paper, these two techniques were compared using receiver-operator characteristics (ROC) analysis at detecting MD patients from a population of normal subjects. METHODS: SPECT phase analysis was performed on 48 normal subjects (LVEF > 55%, normal wall motion, QRS < 120 ms), and 55 MD patients (LVEF < 35%, QRS > 120 ms). ROC analysis was individually performed on each of three phase parameters (phase standard deviation, synchrony, and entropy) for each LV wall motion technique. ROC area differences were assessed using the Student t-test. Intra- and inter-observer reproducibilities were investigated using regression analysis. RESULTS: Time-activity-based phase analysis produced excellent ROC areas of .93 or better for all three phase parameters. The time-distance techniques produced significantly (P < .05) lower ROC areas in the range of .53-.76. Time-activity-based phase analysis had excellent intra- and inter-observer reproducibility with correlation coefficients >.96, compared to values of ~.85 for the time-distance methods. CONCLUSION: SPECT time-activity-based phase analysis had excellent sensitivity and specificity at detecting MD patients with very high intra- and inter-observer reproducibility.

Optimization and validation of radionuclide angiography phase analysis parameters for quantification of mechanical dyssynchrony.

INTRODUCTION: Cardiac resynchronization therapy (CRT) has the potential to improve the outcome of patients suffering from mechanical dyssynchrony and heart failure. It has been suggested that accurate quantification of baseline extent of mechanical dyssynchrony may lead to pre-selection of patients likely to respond to CRT. The standard deviation from a phase histogram (phaseSD), synchrony (S) and entropy (E) are parameters obtained from phase analysis of planar radionuclide angiography (RNA) that may provide an accurate means of assessing mechanical dyssynchrony. In this paper, the ability of phaseSD, S, and E to detect mechanical dyssynchrony was investigated and optimal values for image smoothing, histogram noise thresholding, and bin size were defined. Finally, the intra- and inter-observer reproducibility of the methodology was assessed. METHODS: PhaseSD, S, and E were calculated for 37 normal subjects (LVEF > 50%, end-diastolic volume < 120 mL, end-systolic volume < 60 mL, QRS < 120 ms, and normal wall motion) and 53 patients with mechanical dyssynchrony (LVEF < 30%, QRS > 120 ms, and typical LBBB). Receiver-operator characteristics (ROC) curves were created and the area under the curve (AUC), for each parameter, was determined using three different imaging filters (no filter and an order 5 Hann filter with cut-off of 5/50 and 10/50). The AUC was also determined using histogram threshold values varying between 0% and 50% (of the max amplitude value). Finally, AUC for E was determined for bins sizes varying between 1 degrees and 20 degrees . Inter- and intra-observer variability was calculated at optimal imaging values. RESULTS: No smoothing was found to maximize the AUC. The AUC was independent of histogram threshold value. However, a value of 20% provided optimal visualization of the phase image. The AUC was also independent of bin size. At the optimal imaging values, the sensitivity and specificity for all parameters for detection of mechanical dyssynchrony was measured to be 89-100%. Inter- and intra-observer correlation coefficients >0.99 were found for phaseSD, S and E. CONCLUSIONS: Optimized planar RNA phase analysis parameters, phaseSD, S, and E, were able to detect mechanical dyssynchrony with low inter- and intra-observer variability. Studies assessing the ability of these parameters to predict CRT outcome are required.

Collimator selection, acquisition speed, and visual assessment of 131I-tositumomab biodistribution in a phantom model.

UNLABELLED: (131)I-Tositumomab has been used in treating patients with non-Hodgkin's lymphoma. It is generally recommended that high-energy collimators be used to image patients before they receive (131)I-tositumomab therapy, to determine the effective half-life for therapeutic dose and gross biodistribution. Because many nuclear medicine departments do not possess high-energy collimators, this study was designed to assess the suitability of using medium-energy collimators. The effect of scanning speed was also investigated, in an attempt to optimize the acquisition time. METHODS: Measurements were taken using an elliptic anthropomorphic torso phantom and an organ-scanning phantom fitted with fillable spheres (1-5 cm in diameter) and organ inserts. Three phantom studies were performed with differing initial (131)I concentrations in the organs, the spheres, and the thoracic and abdominal chambers. Images were acquired with both high-energy and medium-energy collimators and at acquisition speeds of 20 and 100 cm/min. The half-life for each combination (study/collimator/speed) was calculated from a linear fit of the data. The contrast of the tumor sphere was assessed using 2 identical regions, placed on and beside the sphere, and averaged over several time points. Biodistribution and image quality were visually assessed by 2 independent observers. RESULTS: Measured half-life values and visual assessment of biodistribution showed no significant difference between the 2 collimators (P = 0.32) or acquisition speeds (P = 0.85). A significant difference in the contrast of the tumor spheres was observed between the 2 collimators (P < 0.01) but not between acquisition speeds. Visual assessment of the images showed increased noise on the image acquired at 100 cm/min, although this noise did not affect lesion detectability. CONCLUSION: Measured half-life is not significantly different between the 2 collimators; hence, calculation of the residence time would be nearly the same. Medium-energy collimators can be used to accurately calculate the (131)I-tositumomab therapeutic dose and detect alterations in biodistribution.