Dense motion propagation from sparse samples.

There are many applications for which sparse, or partial sampling of dynamic image data can be used for articulating or estimating motion within the medical imaging area. In this new work, we propose a generalized framework for dense motion propagation from sparse samples which represents an example of transfer learning and manifold alignment, allowing the transfer of knowledge across imaging sources of different domains which exhibit different features. Many such examples exist in medical imaging, from mapping 2D ultrasound or fluoroscopy to 3D or 4D data or monitoring dynamic dose delivery from partial imaging data in radiotherapy. To illustrate this approach we animate, or articulate, a high resolution static MR image with 4D free breathing respiratory motion derived from low resolution sparse planar samples of motion. In this work we demonstrate that sparse sampling of dynamic MRI may be used as a viable approach to successfully build models of free- breathing respiratory motion by constrained articulation. Such models demonstrate high contrast, and high temporal and spatial resolution that have so far been hitherto unavailable with conventional imaging methods. The articulation is based on using a propagation model, in the eigen domain, to estimate complete 4D motion vector fields from sparsely sampled free-breathing dynamic MRI data. We demonstrate that this approach can provide equivalent motion vector fields compared to fully sampled 4D dynamic data, whilst preserving the corresponding high resolution/high contrast inherent in the original static volume. Validation is performed on three 4D MRI datasets using eight extracted slices from a fast 4D acquisition (0.7 s per volume). The estimated deformation fields from sparse sampling are compared to the fully sampled equivalents, resulting in an rms error of the order of 2 mm across the entire image volume. We also present exemplar 4D high contrast, high resolution articulated volunteer datasets using this methodology. This approach facilitates greater freedom in the acquisition of free breathing respiratory motion sequences which may be used to inform motion modelling methods in a range of imaging modalities and demonstrates that sparse sampling of free breathing data may be used within a manifold alignment and transfer learning paradigm to estimate fully sampled motion. The method may also be applied to other examples of sparse sampling to produce dense motion propagation.

The effect of time-of-flight and point spread function modeling on 82Rb myocardial perfusion imaging of obese patients.

BACKGROUND: The effect of time-of-flight (TOF) and point spread function (PSF) modeling in image reconstruction has not been well studied for cardiac PET. This study assesses their separate and combined influence on 82Rb myocardial perfusion imaging in obese patients. METHODS: Thirty-six obese patients underwent rest-stress 82Rb cardiac PET. Images were reconstructed with and without TOF and PSF modeling. Perfusion was quantitatively compared using the AHA 17-segment model for patients grouped by BMI, cross-sectional body area in the scanner field of view, gender, and left ventricular myocardial volume. Summed rest scores (SRS), summed stress scores (SSS), and summed difference scores (SDS) were compared. RESULTS: TOF improved polar map visual uniformity and increased septal wall perfusion by up to 10%. This increase was greater for larger patients, more evident for patients grouped by cross-sectional area than by BMI, and more prominent for females. PSF modeling increased perfusion by about 1.5% in all cardiac segments. TOF modeling generally decreased SRS and SSS with significant decreases between 2.4 and 3.0 (P < .05), which could affect risk stratification; SDS remained about the same. With PSF modeling, SRS, SSS, and SDS were largely unchanged. CONCLUSION: TOF and PSF modeling affect regional and global perfusion, SRS, and SSS. Clinicians should consider these effects and gender-dependent differences when interpreting 82Rb perfusion studies.

Effect of obesity and type 2 diabetes, and glucose ingestion on circulating spexin concentration in adolescents.

Spexin is a novel peptide that has been reported to be down regulated in obese adults and children and in normoglycemic adults following glucose ingestion. Spexin may therefore have a role in metabolic regulation. The purpose of the current study was to determine the effect of obesity and type 2 diabetes (T2DM), and the effect of glucose ingestion on circulating spexin concentration in adolescents. Boys and girls (mean age 16 years old) classified as healthy normal weight (NW, n = 22), obese (Ob, n = 10), or obese with T2DM (n = 12) completed measurements of body composition, blood pressure, cardiorespiratory fitness, and blood concentrations of glucose, insulin, and lipids. The median fasting serum spexin concentration did not differ between groups (NW: 0.35; Ob: 0.38, T2DM: 0.34 ng/mL, respectively). In 10 NW participants who completed a standard oral glucose tolerance test, spexin concentration was unchanged at 30 and 120 minutes relative to the fasting baseline. Finally, spexin was not significantly correlated with any of the body composition, fitness, or blood biochemical measurements. These data do not support the proposed role of spexin as a metabolic regulator or biomarker of glucose control in adolescents.

Correction of hysteretic respiratory motion in SPECT myocardial perfusion imaging: Simulation and patient studies.

PURPOSE: Amplitude-based respiratory gating is known to capture the extent of respiratory motion (RM) accurately but results in residual motion in the presence of respiratory hysteresis. In our previous study, we proposed and developed a novel approach to account for respiratory hysteresis by applying the Bouc-Wen (BW) model of hysteresis to external surrogate signals of anterior/posterior motion of the abdomen and chest with respiration. In this work, using simulated and clinical SPECT myocardial perfusion imaging (MPI) studies, we investigate the effects of respiratory hysteresis and evaluate the benefit of correcting it using the proposed BW model in comparison with the abdomen signal typically employed clinically. METHODS: The MRI navigator data acquired in free-breathing human volunteers were used in the specially modified 4D NCAT phantoms to allow simulating three types of respiratory patterns: monotonic, mild hysteresis, and strong hysteresis with normal myocardial uptake, and perfusion defects in the anterior, lateral, inferior, and septal locations of the mid-ventricular wall. Clinical scans were performed using a Tc-99m sestamibi MPI protocol while recording respiratory signals from thoracic and abdomen regions using a visual tracking system (VTS). The performance of the correction using the respiratory signals was assessed through polar map analysis in phantom and 10 clinical studies selected on the basis of having substantial RM. RESULTS: In phantom studies, simulations illustrating normal myocardial uptake showed significant differences (P < 0.001) in the uniformity of the polar maps between the RM uncorrected and corrected. No significant differences were seen in the polar map uniformity across the RM corrections. Studies simulating perfusion defects showed significantly decreased errors (P < 0.001) in defect severity and extent for the RM corrected compared to the uncorrected. Only for the strong hysteretic pattern, there was a significant difference (P < 0.001) among the RM corrections. The errors in defect severity and extent for the RM correction using abdomen signal were significantly higher compared to that of the BW (severity = -4.0%, P < 0.001; extent = -65.4%, P < 0.01) and chest (severity = -4.1%, P < 0.001; extent = -52.5%, P < 0.01) signals. In clinical studies, the quantitative analysis of the polar maps demonstrated qualitative and quantitative but not statistically significant differences (P = 0.73) between the correction methods that used the BW signal and the abdominal signal. CONCLUSIONS: This study shows that hysteresis in respiration affects the extent of residual motion left in the RM-binned data, which can impact wall uniformity and the visualization of defects. Thus, there appears to be the potential for improved accuracy in reconstruction in the presence of hysteretic RM with the BW model method providing a possible step in the direction of improvement.

Glycemic Variability Is Associated with Markers of Vascular Stress in Adolescents.

OBJECTIVES: We used continuous glucose monitoring to test the hypothesis that mean amplitude of glycemic excursions (MAGE) is associated with circulating markers of oxidative and vascular stress in adolescents with habitually low physical activity classified as healthy weight, healthy obese, or obese with type 2 diabetes mellitus (T2DM). STUDY DESIGN: A group of 13- to 21-year-olds (healthy weight = 12, healthy obese = 10, T2DM = 12) wore a continuous glucose monitor and step activity monitor for 5 days. RESULTS: Physical activity was similar among groups (6551 ± 401 steps/d), but aerobic fitness (peak rate of oxygen consumption) was lower (P < .05) in T2DM (15.6 ± 1.8 mL/kg/min) than either healthy weight (26.2 ± 2.2) or healthy obese (24.4 ± 2.5). MAGE (mg/dL) was higher (P < .01) in T2DM (82 ± 10) vs healthy obese (33 ± 3) and healthy weight (30 ± 3). Average glucose followed a similar pattern as MAGE. Oxidized low density lipoprotein was higher (P < .05) in T2DM (70.3 ± 5.0 U/L) and healthy obese (58.1 ± 3.8) than healthy weight (48.4 ± 2) and positively correlated with MAGE (r = 0.77). Other stress markers that were both elevated in T2DM and correlated with MAGE included E-selectin (r = 0.50), intercellular adhesion molecule 1 (r = 0.35), and C-reactive protein (r = 0.52); soluble receptor for advanced glycosylation end product was lower in T2DM and inversely correlated with MAGE (r = -0.38). CONCLUSIONS: MAGE is highest in obese youth with T2DM. The associations between MAGE and oxidative stress markers support the proposed contribution of glycemic variability to risk for future cardiovascular disease.

Oxidized HDL and LDL in adolescents with type 2 diabetes compared to normal weight and obese peers.

OBJECTIVE: Obesity and type 2 diabetes mellitus (T2DM) are associated with oxidative stress. Oxidative damage of high-density lipoprotein (oxHDL) leads to a dysfunctional molecule, potentially a mediator and/or marker of cardiometabolic disease. We tested the hypothesis that circulating concentration of oxHDL is higher in obese (Ob) or T2DM adolescents compared to normal-weight (NW) peers. METHODS: In 37 NW, 38 Ob, and 42 T2DM adolescents, ages 11-18 y, fasting concentrations of HDL and LDL cholesterol, oxHDL, oxidized low-density lipoprotein (oxLDL), and myeloperoxidase (MPO) were measured. RESULTS: Compared to the NW group, oxHDL in the Ob group was not different, but was 65% higher (p < 0.01) in the T2DM group. Within the T2DM group oxHDL was higher in boys than in girls, but this sex difference was not evident in NW or Ob groups. OxLDL was 23% higher in Ob (p = 0.02), and 56% higher in T2DM (p < 0.01) versus NW and did not differ between boys and girls. MPO was not different between NW and Ob but was 88% (p < 0.02) higher in T2DM compared to NW. Contrary to our hypothesis MPO and insulin resistance (HOMA-IR) were not correlated with oxHDL. OxHDL was positively associated with oxLDL and lean body mass while oxLDL was positively associated with apolipoprotein B, triglycerides, HOMA-IR and trunk fat. CONCLUSIONS: The higher concentrations of oxHDL and oxLDL, along with higher MPO in children with T2DM reflect higher oxidative stress compared with obesity alone and potentially increased cardiovascular disease risk in youth with T2DM.

Adaptation of the modified Bouc-Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: testing using MRI.

PURPOSE: Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc-Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors' previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart. METHODS: In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior-inferior direction during free breathing using MRI navigators. A visual tracking system (vts) synchronized with MRI acquisition tracked the anterior-posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc-Wen model by inputting the vts derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson's linear correlation coefficient between the abdomen, chest, average of chest and abdomen markers, and Bouc-Wen derived signals versus the true internal motion of the heart from MRI was used to judge the signals match to the heart motion. RESULTS: The results show that the Bouc-Wen model generated signals demonstrated strong correlation with the heart motion. This correlation was slightly larger on average than that of the external surrogate signals derived from the abdomen marker, and average of the abdomen and chest markers, but was not statistically significantly different from them. CONCLUSIONS: The results suggest that the proposed model has the potential to be a unified framework for modeling hysteresis in respiratory motion in cardiac perfusion studies and beyond.

Digital anthropomorphic phantoms of non-rigid human respiratory and voluntary body motion for investigating motion correction in emission imaging.

The development of methods for correcting patient motion in emission tomography has been receiving increased attention. Often the performance of these methods is evaluated through simulations using digital anthropomorphic phantoms, such as the commonly used extended cardiac torso (XCAT) phantom, which models both respiratory and cardiac motion based on human studies. However, non-rigid body motion, which is frequently seen in clinical studies, is not present in the standard XCAT phantom. In addition, respiratory motion in the standard phantom is limited to a single generic trend. In this work, to obtain a more realistic representation of motion, we developed a series of individual-specific XCAT phantoms, modeling non-rigid respiratory and non-rigid body motions derived from the magnetic resonance imaging (MRI) acquisitions of volunteers. Acquisitions were performed in the sagittal orientation using the Navigator methodology. Baseline (no motion) acquisitions at end-expiration were obtained at the beginning of each imaging session for each volunteer. For the body motion studies, MRI was again acquired only at end-expiration for five body motion poses (shoulder stretch, shoulder twist, lateral bend, side roll, and axial slide). For the respiratory motion studies, an MRI was acquired during free/regular breathing. The magnetic resonance slices were then retrospectively sorted into 14 amplitude-binned respiratory states, end-expiration, end-inspiration, six intermediary states during inspiration, and six during expiration using the recorded Navigator signal. XCAT phantoms were then generated based on these MRI data by interactive alignment of the organ contours of the XCAT with the MRI slices using a graphical user interface. Thus far we have created five body motion and five respiratory motion XCAT phantoms from the MRI acquisitions of six healthy volunteers (three males and three females). Non-rigid motion exhibited by the volunteers was reflected in both respiratory and body motion phantoms with a varying extent and character for each individual. In addition to these phantoms, we recorded the position of markers placed on the chest of the volunteers for the body motion studies, which could be used as external motion measurement. Using these phantoms and external motion data, investigators will be able to test their motion correction approaches for realistic motion obtained from different individuals. The non-uniform rational B-spline data and the parameter files for these phantoms are freely available for downloading and can be used with the XCAT license.

MRI Investigation of the Linkage Between Respiratory Motion of the Heart and Markers on Patient's Abdomen and Chest: Implications for Respiratory Amplitude Binning List-Mode PET and SPECT Studies.

Respiratory motion of the heart impacts the diagnostic accuracy of myocardial-perfusion emission-imaging studies. Amplitude binning has come to be the method of choice for binning list-mode based acquisitions for correction of respiratory motion in PET and SPECT. In some subjects respiratory motion exhibits hysteretic behavior similar to damped non-linear cyclic systems. The detection and correction of hysteresis between the signals from surface movement of the patient's body used in binning and the motion of the heart within the chest remains an open area for investigation. This study reports our investigation in nine volunteers of the combined MRI tracking of the internal respiratory motion of the heart using Navigators with stereo-tracking of markers on the volunteer's chest and abdomen by a visual-tracking system (VTS). The respiratory motion signals from the internal organs and the external markers were evaluated for hysteretic behavior analyzing the temporal correspondence of the signals. In general, a strong, positive correlation between the external marker motion (AP direction) and the internal heart motion (SI direction) during respiration was observed. The average ± standard deviation in the Spearman's ranked correlation coefficient (ρ) over the nine volunteer studied was 0.92 ± 0.1 between the external abdomen marker and the internal heart, and 0.87 ± 0.2 between the external chest marker and the internal heart. However despite the good correlation on average for the nine volunteers, in three studies a poor correlation was observed due to hysteretic behavior between inspiration and expiration for either the chest marker and the internal motion of the heart, or the abdominal marker and the motion of the heart. In all cases we observed a good correlation of at least either the abdomen or the chest with the heart. Based on this result, we propose the use of marker motion from both the chest and abdomen regions when estimating the internal heart motion to detect and address hysteresis when binning list-mode emission data.

Use of MRI to assess the prediction of heart motion with gross body motion in myocardial perfusion imaging by stereotracking of markers on the body surface.

PURPOSE: The aim of this study is to determine using MRI in volunteers whether the rigid-body-motion (RBM) model can be approximately used to estimate the gross body-motion of the heart from that of external markers on patient's chest. Our target clinical application is to use a visual-tracking-system (VTS) which employs stereoimaging to estimate heart motion during SPECT/CT and PET∕CT myocardial perfusion imaging. METHODS: To investigate body-motion separate from the respiration the authors had the volunteers hold their breath during the acquisition of a sequence of two sets of EKG-triggered MRI sagittal slices. The first set was acquired pre-motion, and the second postmotion. The motion of the heart within each breath-hold set of slices was estimated by registration to the semiautomatic 3D segmentation of the heart region in a baseline set acquired using the Navigator technique. The motion of the heart between the pre- and postmotion sets was then determined as the difference in the individual motions in comparison to the Navigator sets. An analysis of the combined motion of the individual markers on the chest was used to obtain an estimate of the six-degree-of-freedom RBM from the VTS system. The metric for judging agreement between the motion estimated by MRI and the VTS was the average error. This was defined as the average of the magnitudes of the differences in the vector displacements of all voxels in the heart region. Studies with the Data Spectrum Anthropomorphic Phantom and "No-Motion" studies in which the volunteer did not intentionally move were used to establish a baseline for agreement. With volunteer studies a t-test was employed to determine when statistically significant differences in Average Errors occurred compared to the No-motion studies. RESULTS: For phantom acquisitions, the Average Error when the motion was just translation was 0.1 mm. With complex motions, which included a combination of rotations and translations, the Average Error increased to 3.6 mm. In the volunteers the Average Error averaged over all No-Motion acquisitions was 1.0 mm. For the case of translational motion, which might be expected to be RBM, the Average Error averaged over all volunteer studies increased to 2.6 mm, which was statistically different from the No-Motion studies. For the case of bends and twists of the torso, which would be expected to challenge the RBM model, the Average Error averaged over all such volunteer studies was 4.9 mm and was again statistically different. Investigations of motion of the arm including just bending at the elbow and leg motion resulted in Average Errors which were not statistically different from the No-Motion studies. However, when shoulder movement was included with arm motion the Average Error was near that of torso bends and twists, and statistically different. CONCLUSIONS: Use of the RBM model with VTS predictions of heart motion during reconstruction should decrease the extent of artifacts for the types of patient motion studied. The impact of correction would be less for torso bends and twists, and arm motion which includes the shoulders.