Profiling and predicting distinct tau progression patterns: An unsupervised data-driven approach to flortaucipir positron emission tomography.

INTRODUCTION: How to detect patterns of greater tau burden and accumulation is still an open question. METHODS: An unsupervised data-driven whole-brain pattern analysis of longitudinal tau positron emission tomography (PET) was used first to identify distinct tau accumulation profiles and then to build baseline models predictive of tau-accumulation type. RESULTS: The data-driven analysis of longitudinal flortaucipir PET from studies done by the Alzheimer's Disease Neuroimaging Initiative, Avid Pharmaceuticals, and Harvard Aging Brain Study (N = 348 cognitively unimpaired, N = 188 mild cognitive impairment, N = 77 dementia), yielded three distinct flortaucipir-progression profiles: stable, moderate accumulator, and fast accumulator. Baseline flortaucipir levels, amyloid beta (Aß) positivity, and clinical variables, identified moderate and fast accumulators with 81% and 95% positive predictive values, respectively. Screening for fast tau accumulation and Aß positivity in early Alzheimer's disease, compared to Aß positivity with variable tau progression profiles, required 46% to 77% lower sample size to achieve 80% power for 30% slowing of clinical decline. DISCUSSION: Predicting tau progression with baseline imaging and clinical markers could allow screening of high-risk individuals most likely to benefit from a specific treatment regimen.

Comparison of automated beam hardening correction (ABHC) algorithms for myocardial perfusion imaging using computed tomography.

PURPOSE: Myocardial perfusion imaging using computed tomography (MPI-CT) and coronary CT angiography (CTA) have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening can prevent accurate blood flow estimation in dynamic MPI-CT and can create artifacts that resemble flow deficits in single-shot MPI-CT. In this work, we compare four automatic beam hardening correction algorithms (ABHCs) applied to CT images, for their ability to produce accurate single images of contrast and accurate MPI flow maps using images from conventional CT systems, without energy sensitivity. METHODS: Previously, we reported a method, herein called ABHC-1, where we iteratively optimized a cost function sensitive to beam hardening artifacts in MPI-CT images and used a low order polynomial correction on projections of segmentation-processed CT images. Here, we report results from two new algorithms with higher order polynomial corrections, ABHC-2 and ABHC-3 (with three and seven free parameters, respectively), having potentially better correction but likely reduced estimability. Additionally, we compared results to an algorithm reported by others in the literature (ABHC-NH). Comparisons were made on a digital static phantom with simulated water, bone, and iodine regions; on a digital dynamic anthropomorphic phantom, with simulated blood flow; and on preclinical porcine experiments. We obtained CT images on a prototype spectral detector CT (Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To test these methods' parameter optimization sensitivity to noise, we evaluated results on images obtained using different mAs. RESULTS: In images of the static phantom, ABHC-2 reduced beam hardening artifacts better than our previous ABHC-1 algorithm, giving artifacts smaller than 1.8 HU, even in the presence of high noise which should affect parameter optimization. Taken together, the quality of static phantom results ordered ABHC-2> ABHC-3> ABHC-1>> ABHC-NH. In an anthropomorphic MPI-CT simulator with homogeneous myocardial blood flow of 100 ml⋅min-1 ⋅100 g-1 , blood flow estimation results were 122 ± 24 (FBP), 135 ± 24 (ABHC-NH), 104 ± 14 (ABHC-1), 100 ± 12 (ABHC-2), and 108 ± 18 (ABHC-3) ml⋅min-1 ⋅100 g-1 , showing ABHC-2 as a clear winner. Visual and quantitative evaluations showed much improved homogeneity of myocardial flow with ABHC-2, nearly eliminating substantial artifacts in uncorrected flow maps which could be misconstrued as flow deficits. ABHC-2 performed universally better than ABHC-1, ABHC-3, and ABHC-NH in simulations with different acquisitions (varying noise and kVp values). In the presence of a simulated flow deficit, all ABHC methods retained the flow deficit, and ABHC-2 gave the most accurate flow ratio and homogeneity. ABHC-3 corrected phantom flow values were slightly better than ABHC-2, in noiseless images, suggesting that reduced quality in noisy images was due to reduced estimability. In an experiment with a pig expected to have uniform flow, ABHC-2 applied to conventional images improved flow maps to compare favorably to those from 70keV images. CONCLUSION: The automated algorithm can be used with different parametric BH correction models. ABHC-2 improved MPI-CT blood flow estimation as compared to other approaches and was robust to noisy images. In simulation and preclinical experiments, ABHC-2 gave results approaching gold standard 70 keV measurements.

Single-site 123I-FP-CIT reference values from individuals with non-degenerative parkinsonism-comparison with values from healthy volunteers.

PURPOSE: Iodine 123-radiolabeled 2ß-carbomethoxy-3ß-(4-iodophenyl)-N-(3-fluoropropyl) nortropane (123I-FP-CIT) SPECT can be performed to distinguish degenerative forms of movement disorders/parkinsonism/tremor from other entities such as idiopathic tremor or drug-induced parkinsonism. For equivocal cases, semi-quantification and comparison to reference values are a necessary addition to visual interpretation of 123I-FP-CIT scans. To overcome the challenges of multi-center recruitment and scanning of healthy volunteers, we generated 123I-FP-CIT reference values from individuals with various neurological conditions but without dopaminergic degeneration, scanned at a single center on the same SPECT-CT system following the same protocol, and compared them to references from a multi-center database built using healthy volunteers' data. METHODS: From a cohort of 1884 patients, we identified 237 subjects (120 men, 117 women, age range 16-88 years) through a two-stage selection process. Every patient had a final clinical diagnosis after a mean follow-up of 4.8 ± 1.3 years. Images were reconstructed using (1) Flash3D with scatter and CT-based attenuation corrections (AC) and (2) filtered back projection with Chang AC. Volume-of-interest analysis was performed using a commercial software to calculate specific binding ratios (SBRs), caudate-to-putamen ratios, and asymmetry values on different striatal regions. Generated reference values were assessed according to age and gender and compared with those from the ENC-DAT study, and their robustness was tested against a cohort of patients with different diagnoses. RESULTS: Age had a significant negative linear effect on all SBRs. Overall, the reduction rate per decade in SBR was between 3.80 and 5.70%. Women had greater SBRs than men, but this gender difference was only statistically significant for the Flash3D database. Linear regression was used to correct for age-dependency of SBRs and to allow comparisons to age-matched reference values and "normality" limits. Generated regression parameters and their 95% confidence intervals (CIs) were comparable to corresponding European Normal Control Database of DaTscan (ENC-DAT) results. For example, 95% CI mean slope for the striatum in women is - 0.015 ([- 0.019, - 0.011]) for the Flash3D database versus - 0.015 ([- 0.021, - 0.009]) for ENC-DAT. Caudate-to-putamen ratios and asymmetries were not influenced by age or gender. CONCLUSION: The generated 123I-FP-CIT references values have similar age-related distribution, with no increase in variance due to comorbidities when compared to values from a multi-center study with healthy volunteers. This makes it possible for sites to build their 123I-FP-CIT references from scans acquired during routine clinical practice.

Three-year changes of cortical 18F-FDG in amnestic vs. non-amnestic sporadic early-onset Alzheimer's disease.

PURPOSE: To examine and compare longitudinal changes of cortical glucose metabolism in amnestic and non-amnestic sporadic forms of early-onset Alzheimer's disease and assess potential associations with neuropsychological performance over a 3-year period time. METHODS: Eighty-two participants meeting criteria for early-onset (< 65 years) sporadic form of probable Alzheimer's disease and presenting with a variety of clinical phenotypes (47 amnestic and 35 non-amnestic forms) were included at baseline and followed up for 1.44 ± 1.23 years. All of the participants underwent a work-up at baseline and every year during the follow-up period, which includes clinical examination, neuropsychological testing, genotyping, cerebrospinal fluid biomarker assays, and structural MRI and 18F-FDG PET. Vertex-wise partial volume-corrected glucose metabolic maps across the entire cortical surface were generated and longitudinally assessed together with the neuropsychological scores using linear mixed-effects modeling as a function of amnestic and non-amnestic sporadic forms of early-onset Alzheimer's disease. RESULTS: Similar evolution patterns of glucose metabolic decline between amnestic and non-amnestic forms were observed in widespread neocortical cortices. However, only non-amnestic forms appeared to have a greater reduction of glucose metabolism in lateral orbitofrontal and bilateral medial temporal cortices associated with more severe declines of neuropsychological performance compared with amnestic forms. Furthermore, results suggest that glucose metabolic decline in amnestic forms would progress along an anterior-to-posterior axis, whereas glucose metabolic decline in non-amnestic forms would progress along a posterior-to-anterior axis. CONCLUSIONS: We found differences in spatial distribution and temporal trajectory of glucose metabolic decline between amnestic and non-amnestic early-onset Alzheimer's disease groups, suggesting that one might want to consider treating the two forms of the disease as two separate entities.

Using EQ·PET to reduce reconstruction-dependent variations in [18F]FDG-PET brain imaging.

This study aims at assessing whether EANM harmonisation strategy combined with EQ·PET methodology could be successfully applied to harmonize brain 2-deoxy-2[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) images. The NEMA NU 2 body phantom was prepared according to the EANM guidelines with an [18F]FDG solution. Raw PET phantom data were reconstructed with three different reconstruction protocols frequently used in clinical PET brain imaging: ([Formula: see text]) Ordered subset expectation maximization (OSEM) 3D with time of flight (TOF), 2 iterations and 21 subsets; ([Formula: see text]) OSEM 3D with TOF, 6 iterations and 21 subsets; and ([Formula: see text]) OSEM 3D with TOF, point spread function (PSF), and 8 iterations and 21 subsets. EQ·PET filters were computed as the Gaussian smoothing that best independently aligned the recovery coefficients (RCs) of reconstructions [Formula: see text] and [Formula: see text] with the RCs of the reference reconstruction, [Formula: see text]. The performance of the EQ·PET filter to reduce variations in quantification due to differences in reconstruction was investigated using clinical PET brain images of 35 early-onset Alzheimer's disease (EOAD) patients. Qualitative assessments and multiple quantitative metrics on the cortical surface at different scale levels with or without partial volume effect correction were evaluated on the [18F]FDG brain data before and after application of the EQ·PET filter. The EQ·PET methodology succeeded in finding the optimal smoothing that minimised root-mean-square error (RMSE) calculated using human brain [18F]FDG-PET datasets of EOAD patients, providing harmonized comparisons in the neurological context. Performance was superior for TOF than for TOF + PSF reconstructions. Results showed the capability of the EQ·PET methodology to minimize reconstruction-induced variabilities between brain [18F]FDG-PET images. However, moderate variabilities remained after harmonizing PSF reconstructions with standard non-PSF OSEM reconstructions, suggesting that precautions should be taken when using PSF modelling.

Calibration-free beam hardening correction for myocardial perfusion imaging using CT.

PURPOSE: Computed tomography myocardial perfusion imaging (CT-MPI) and coronary CTA have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening (BH) artifacts prevent accurate blood flow calculation in CT-MPI. BH correction methods require either energy-sensitive CT, not widely available, or typically, a calibration-based method in conventional CT. We propose a calibration-free, automatic BH correction (ABHC) method suitable for CT-MPI and evaluate its ability to reduce BH artifacts in single "static-perfusion" images and to create accurate myocardial blood flow (MBF) in dynamic CT-MPI. METHODS: In the algorithm, we used input CT DICOM images and iteratively optimized parameters in a polynomial BH correction until a BH-sensitive cost function was minimized on output images. An input image was segmented into a soft tissue image and a highly attenuating material (HAM) image containing bones and regions of high iodine concentrations, using mean HU and temporal enhancement properties. We forward projected HAM, corrected projection values according to a polynomial correction, and reconstructed a correction image to obtain the current iteration's BH corrected image. The cost function was sensitive to BH streak artifacts and cupping. We evaluated the algorithm on simulated CT and physical phantom images, and on preclinical porcine with optional coronary obstruction and clinical CT-MPI data. Assessments included measures of BH artifact in single images as well as MBF estimates. We obtained CT images on a prototype spectral detector CT (SDCT, Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To stress test the method, we evaluated results on images from a different scanner (iCT, Philips Healthcare) and different kVp values. RESULTS: In a CT-simulated digital phantom consisting of water with iodine cylinder insets, BH streak artifacts between simulated iodine inserts were reduced from 13 ± 2 to 0 ± 1 HU. In a similar physical phantom having higher iodine concentrations, BH streak artifacts were reduced from 48 ± 6 to 1 ± 5 HU and cupping was reduced by 86%, from 248 to 23 HU. In preclinical CT-MPI images without coronary obstruction, BH artifact was reduced from 24 ± 6 HU to less than 5 ± 4 HU at peak enhancement. Standard deviation across different regions of interest (ROI) along the myocardium was reduced from 13.26 to 6.86 HU for ABHC, comparing favorably to measurements in the corresponding virtual keV image. Corrections greatly reduced variations in preclinical MBF maps as obtained in normal animals without obstruction (FFR = 1). Coefficients of variations were 22% (conventional CT), 9% (ABHC), and 5% (virtual keV). Moreover, variations in flow tended to be localized after ABHC, giving result which would not be confused with a flow deficit in a coronary vessel territory. CONCLUSION: The automated algorithm can be used to reduce BH artifact in conventional CT and improve CT-MPI accuracy particularly by removing regions of reduced estimated flow which might be misinterpreted as flow deficits.

The role of acquisition and quantification methods in myocardial blood flow estimability for myocardial perfusion imaging CT.

In this work, we clarified the role of acquisition parameters and quantification methods in myocardial blood flow (MBF) estimability for myocardial perfusion imaging using CT (MPI-CT). We used a physiologic model with a CT simulator to generate time-attenuation curves across a range of imaging conditions, i.e. tube current-time product, imaging duration, and temporal sampling, and physiologic conditions, i.e. MBF and arterial input function width. We assessed MBF estimability by precision (interquartile range of MBF estimates) and bias (difference between median MBF estimate and reference MBF) for multiple quantification methods. Methods included: six existing model-based deconvolution models, such as the plug-flow tissue uptake model (PTU), Fermi function model, and single-compartment model (SCM); two proposed robust physiologic models (RPM1, RPM2); model-independent singular value decomposition with Tikhonov regularization determined by the L-curve criterion (LSVD); and maximum upslope (MUP). Simulations show that MBF estimability is most affected by changes in imaging duration for model-based methods and by changes in tube current-time product and sampling interval for model-independent methods. Models with three parameters, i.e. RPM1, RPM2, and SCM, gave least biased and most precise MBF estimates. The average relative bias (precision) for RPM1, RPM2, and SCM was ⩽11% (⩽10%) and the models produced high-quality MBF maps in CT simulated phantom data as well as in a porcine model of coronary artery stenosis. In terms of precision, the methods ranked best-to-worst are: RPM1 > RPM2 > Fermi > SCM > LSVD > MUP [Formula: see text] other methods. In terms of bias, the models ranked best-to-worst are: SCM > RPM2 > RPM1 > PTU > LSVD [Formula: see text] other methods. Models with four or more parameters, particularly five-parameter models, had very poor precision (as much as 310% uncertainty) and/or significant bias (as much as 493%) and were sensitive to parameter initialization, thus suggesting the presence of multiple local minima. For improved estimates of MBF from MPI-CT, it is recommended to use reduced models that incorporate prior knowledge of physiology and contrast agent uptake, such as the proposed RPM1 and RPM2 models.

18F-FDG PET hypometabolism patterns reflect clinical heterogeneity in sporadic forms of early-onset Alzheimer's disease.

Until now, hypometabolic patterns and their correlations with neuropsychological performance have not been assessed as a function of the various presentations of sporadic early-onset Alzheimer's disease (EOAD). Here, we processed and analyzed the patients' metabolic maps at the vertex and voxel levels by using a nonparametric, permutation method that also regressed out the effects of cortical thickness and gray matter volume, respectively. The hypometabolism patterns in several areas of the brain were significantly correlated with the clinical manifestations. These areas included the paralimbic regions for typical presentations of sporadic EOAD. For atypical presentations, the hypometabolic regions included Broca's and Wernicke's areas and the pulvinar in language forms, bilateral primary and higher processing visual regions (with right predominance) in visuospatial forms, and the bilateral prefrontal cortex in executive forms. Similar hypometabolism patterns were also observed in a correlation analysis of the 18F-FDG PET data versus domain-specific, neuropsychological test scores. These heterogeneities might reflect different underlying pathophysiological processes in particular clinical presentations of sporadic EOAD and should be taken into account in future longitudinal and therapeutic studies.

Quantitative myocardial perfusion imaging in a porcine ischemia model using a prototype spectral detector CT system.

We optimized and evaluated dynamic myocardial CT perfusion (CTP) imaging on a prototype spectral detector CT (SDCT) scanner. Simultaneous acquisition of energy sensitive projections on the SDCT system enabled projection-based material decomposition, which typically performs better than image-based decomposition required by some other system designs. In addition to virtual monoenergetic, or keV images, the SDCT provided conventional (kVp) images, allowing us to compare and contrast results. Physical phantom measurements demonstrated linearity of keV images, a requirement for quantitative perfusion. Comparisons of kVp to keV images demonstrated very significant reductions in tell-tale beam hardening (BH) artifacts in both phantom and pig images. In phantom images, consideration of iodine contrast to noise ratio and small residual BH artifacts suggested optimum processing at 70 keV. The processing pipeline for dynamic CTP measurements included 4D image registration, spatio-temporal noise filtering, and model-independent singular value decomposition deconvolution, automatically regularized using the L-curve criterion. In normal pig CTP, 70 keV perfusion estimates were homogeneous throughout the myocardium. At 120 kVp, flow was reduced by more than 20% on the BH-hypo-enhanced myocardium, a range that might falsely indicate actionable ischemia, considering the 0.8 threshold for actionable FFR. With partial occlusion of the left anterior descending (LAD) artery (FFR < 0.8), perfusion defects at 70 keV were correctly identified in the LAD territory. At 120 kVp, BH affected the size and flow in the ischemic area; e.g. with FFR ≈ 0.65, the anterior-to-lateral flow ratio was 0.29 ± 0.01, over-estimating stenosis severity as compared to 0.42 ± 0.01 (p < 0.05) at 70 keV. On the non-ischemic inferior wall (not a LAD territory), the flow ratio was 0.50 ± 0.04 falsely indicating an actionable ischemic condition in a healthy territory. This ratio was 1.00 ± 0.08 at 70 keV. Results suggest that projection-based keV imaging with the SDCT system and proper processing could enable useful myocardial CTP, much improved over conventional CT.

Comparison of quantitative myocardial perfusion imaging CT to fluorescent microsphere-based flow from high-resolution cryo-images.

Myocardial perfusion imaging using CT (MPI-CT) has the potential to provide quantitative measures of myocardial blood flow (MBF) which can aid the diagnosis of coronary artery disease. We evaluated the quantitative accuracy of MPI-CT in a porcine model of balloon-induced LAD coronary artery ischemia guided by fractional flow reserve (FFR). We quantified MBF at baseline (FFR=1.0) and under moderate ischemia (FFR=0.7) using MPI-CT and compared to fluorescent microsphere-based MBF from high-resolution cryo-images. Dynamic, contrast-enhanced CT images were obtained using a spectral detector CT (Philips Healthcare). Projection-based mono-energetic images were reconstructed and processed to obtain MBF. Three MBF quantification approaches were evaluated: singular value decomposition (SVD) with fixed Tikhonov regularization (ThSVD), SVD with regularization determined by the L-Curve criterion (LSVD), and Johnson-Wilson parameter estimation (JW). The three approaches over-estimated MBF compared to cryo-images. JW produced the most accurate MBF, with average error 33.3±19.2mL/min/100g, whereas LSVD and ThSVD had greater over-estimation, 59.5±28.3mL/min/100g and 78.3±25.6 mL/min/100g, respectively. Relative blood flow as assessed by a flow ratio of LAD-to-remote myocardium was strongly correlated between JW and cryo-imaging, with R2=0.97, compared to R2=0.88 and 0.78 for LSVD and ThSVD, respectively. We assessed tissue impulse response functions (IRFs) from each approach for sources of error. While JW was constrained to physiologic solutions, both LSVD and ThSVD produced IRFs with non-physiologic properties due to noise. The L-curve provided noise-adaptive regularization but did not eliminate non-physiologic IRF properties or optimize for MBF accuracy. These findings suggest that model-based MPI-CT approaches may be more appropriate for quantitative MBF estimation and that cryo-imaging can support the development of MPI-CT by providing spatial distributions of MBF.

Effect of Beam Hardening on Transmural Myocardial Perfusion Quantification in Myocardial CT Imaging.

The detection of subendocardial ischemia exhibiting an abnormal transmural perfusion gradient (TPG) may help identify ischemic conditions due to micro-vascular dysfunction. We evaluated the effect of beam hardening (BH) artifacts on TPG quantification using myocardial CT perfusion (CTP). We used a prototype spectral detector CT scanner (Philips Healthcare) to acquire dynamic myocardial CTP scans in a porcine ischemia model with partial occlusion of the left anterior descending (LAD) coronary artery guided by pressure wire-derived fractional flow reserve (FFR) measurements. Conventional 120 kVp and 70 keV projection-based mono-energetic images were reconstructed from the same projection data and used to compute myocardial blood flow (MBF) using the Johnson-Wilson model. Under moderate LAD occlusion (FFR~0.7), we used three 5 mm short axis slices and divided the myocardium into three LAD segments and three remote segments. For each slice and each segment, we characterized TPG as the mean "endo-to-epi" transmural flow ratio (TFR). BH-induced hypoenhancement on the ischemic anterior wall at 120 kVp resulted in significantly lower mean TFR value as compared to the 70 keV TFR value (0.29±0.01 vs. 0.55±0.01; p<1e-05). No significant difference was measured between 120 kVp and 70 keV mean TFR values on segments moderately affected or unaffected by BH. In the entire ischemic LAD territory, 120 kVp mean endocardial flow was significantly reduced as compared to mean epicardial flow (15.80±10.98 vs. 40.85±23.44 ml/min/100g; p<1e-04). At 70 keV, BH was effectively minimized resulting in mean endocardial MBF of 40.85±15.3407 ml/min/100g vs. 74.09±5.07 ml/min/100g (p=0.0054) in the epicardium. We also found that BH artifact in the conventional 120 kVp images resulted in falsely reduced MBF measurements even under non-ischemic conditions.

Calibration Free Beam Hardening Correction for Cardiac CT Perfusion Imaging.

Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration's BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12±2HU to 1±1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48±6HU to 1±5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28±6 HU to less than 4±4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction.

PURPOSE: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. METHODS: Detectability (d') was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre-Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, PC. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. RESULTS: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AICc. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. CONCLUSIONS: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

Dynamic Myocardial Perfusion in a Porcine Balloon-induced Ischemia Model using a Prototype Spectral Detector CT.

Myocardial CT perfusion (CTP) imaging is an application that should greatly benefit from spectral CT through the significant reduction of beam hardening (BH) artifacts using mono-energetic (monoE) image reconstructions. We used a prototype spectral detector CT (SDCT) scanner (Philips Healthcare) and developed advanced processing tools (registration, segmentation, and deconvolution-based flow estimation) for quantitative myocardial CTP in a porcine ischemia model with different degrees of coronary occlusion using a balloon catheter. The occlusion severity was adjusted with fractional flow reserve (FFR) measurements. The SDCT scanner is a single source, dual-layer detector system, which allows simultaneous acquisitions of low and high energy projections, hence enabling accurate projection-based material decomposition and effective reduction of BH-artifacts. In addition, the SDCT scanner eliminates partial scan artifacts with fast (0.27s), full gantry rotation acquisitions. We acquired CTP data under different hemodynamic conditions and reconstructed conventional 120kVp images and projection-based monoenergetic (monoE) images for energies ranging from 55keV-to-120keV. We computed and compared myocardial blood flow (MBF) between different reconstructions. With balloon completely deflated (FFR=1), we compared the mean attenuation in a myocardial region of interest before iodine arrival and at peak iodine enhancement in the left ventricle (LV), and we found that monoE images at 70keV effectively minimized the difference in attenuation, due to BH, to less than 1 HU compared to 14 HU with conventional 120kVp images. Flow maps under baseline condition (FFR=1) were more uniform throughout the myocardial wall at 70keV, whereas with 120kVp data about 12% reduction in blood flow was noticed on BH-hypoattenuated areas compared to other myocardial regions. We compared MBF maps at different keVs under an ischemic condition (FFR < 0.7), and we found that flow-contrast-to-noise-ratio (CNR f ) between LAD ischemic and remote healthy territories attains its maximum (2.87 ± 0.7) at 70keV. As energies diverge from 70keV, we noticed a steady decrease in CNRf and an overestimation of mean-MBF. Flow overestimation was also noticed for conventional 120kVp images in different myocardial regions.

Low dose dynamic myocardial CT perfusion using advanced iterative reconstruction.

Dynamic myocardial CT perfusion (CTP) can provide quantitative functional information for the assessment of coronary artery disease. However, x-ray dose in dynamic CTP is high, typically from 10mSv to >20mSv. We compared the dose reduction potential of advanced iterative reconstruction, Iterative Model Reconstruction (IMR, Philips Healthcare, Cleveland, Ohio) to hybrid iterative reconstruction (iDose4) and filtered back projection (FBP). Dynamic CTP scans were obtained using a porcine model with balloon-induced ischemia in the left anterior descending coronary artery to prescribed fractional flow reserve values. High dose dynamic CTP scans were acquired at 100kVp/100mAs with effective dose of 23mSv. Low dose scans at 75mAs, 50mAs, and 25mAs were simulated by adding x-ray quantum noise and detector electronic noise to the projection space data. Images were reconstructed with FBP, iDose4, and IMR at each dose level. Image quality in static CTP images was assessed by SNR and CNR. Blood flow was obtained using a dynamic CTP analysis pipeline and blood flow image quality was assessed using flow-SNR and flow-CNR. IMR showed highest static image quality according to SNR and CNR. Blood flow in FBP was increasingly over-estimated at reduced dose. Flow was more consistent for iDose4 from 100mAs to 50mAs, but was over-estimated at 25mAs. IMR was most consistent from 100mAs to 25mAs. Static images and flow maps for 100mAs FBP, 50mAs iDose4, and 25mAs IMR showed comparable, clear ischemia, CNR, and flow-CNR values. These results suggest that IMR can enable dynamic CTP at significantly reduced dose, at 5.8mSv or 25% of the comparable 23mSv FBP protocol.

Comparison of computational to human observer detection for evaluation of CT low dose iterative reconstruction.

Model observers were created and compared to human observers for the detection of low contrast targets in computed tomography (CT) images reconstructed with an advanced, knowledge-based, iterative image reconstruction method for low x-ray dose imaging. A 5-channel Laguerre-Gauss Hotelling Observer (CHO) was used with internal noise added to the decision variable (DV) and/or channel outputs (CO). Models were defined by parameters: (k1) DV-noise with standard deviation (std) proportional to DV std; (k2) DV-noise with constant std; (k3) CO-noise with constant std across channels; and (k4) CO-noise in each channel with std proportional to CO variance. Four-alternative forced choice (4AFC) human observer studies were performed on sub-images extracted from phantom images with and without a "pin" target. Model parameters were estimated using maximum likelihood comparison to human probability correct (PC) data. PC in human and all model observers increased with dose, contrast, and size, and was much higher for advanced iterative reconstruction (IMR) as compared to filtered back projection (FBP). Detection in IMR was better than FPB at 1/3 dose, suggesting significant dose savings. Model(k1,k2,k3,k4) gave the best overall fit to humans across independent variables (dose, size, contrast, and reconstruction) at fixed display window. However Model(k1) performed better when considering model complexity using the Akaike information criterion. Model(k1) fit the extraordinary detectability difference between IMR and FBP, despite the different noise quality. It is anticipated that the model observer will predict results from iterative reconstruction methods having similar noise characteristics, enabling rapid comparison of methods.

Dynamic CT Myocardial Perfusion Imaging: Detection of Ischemia in a Porcine Model with FFR Verification.

Dynamic cardiac CT perfusion (CTP) is a high resolution, non-invasive technique for assessing myocardial blood flow (MBF), which in concert with coronary CT angiography enable CT to provide a unique, comprehensive, fast analysis of both coronary anatomy and functional flow. We assessed perfusion in a porcine model with and without coronary occlusion. To induce occlusion, each animal underwent left anterior descending (LAD) stent implantation and angioplasty balloon insertion. Normal flow condition was obtained with balloon completely deflated. Partial occlusion was induced by balloon inflation against the stent with FFR used to assess the extent of occlusion. Prospective ECG-triggered partial scan images were acquired at end systole (45% R-R) using a multi-detector CT (MDCT) scanner. Images were reconstructed using FBP and a hybrid iterative reconstruction (iDose 4, Philips Healthcare). Processing included: beam hardening (BH) correction, registration of image volumes using 3D cubic B-spline normalized mutual-information, and spatio-temporal bilateral filtering to reduce partial scan artifacts and noise variation. Absolute blood flow was calculated with a deconvolution-based approach using singular value decomposition (SVD). Arterial input function was estimated from the left ventricle (LV) cavity. Regions of interest (ROIs) were identified in healthy and ischemic myocardium and compared in normal and occluded conditions. Under-perfusion was detected in the correct LAD territory and flow reduction agreed well with FFR measurements. Flow was reduced, on average, in LAD territories by 54%.

Reduced gyral window and corpus callosum size in autism: possible macroscopic correlates of a minicolumnopathy.

Minicolumnar changes that generalize throughout a significant portion of the cortex have macroscopic structural correlates that may be visualized with modern structural neuroimaging techniques. In magnetic resonance images (MRIs) of fourteen autistic patients and 28 controls, the present study found macroscopic morphological correlates to recent neuropathological findings suggesting a minicolumnopathy in autism. Autistic patients manifested a significant reduction in the aperture for afferent/efferent cortical connections, i.e., gyral window. Furthermore, the size of the gyral window directly correlated to the size of the corpus callosum. A reduced gyral window constrains the possible size of projection fibers and biases connectivity towards shorter corticocortical fibers at the expense of longer association/commisural fibers. The findings may help explain abnormalities in motor skill development, differences in postnatal brain growth, and the regression of acquired functions observed in some autistic patients.

Validation of finite element models of liver tissue using micro-CT.

In this work, we aim at validating some soft tissue deformation models using high-resolution micro-computed tomography (Micro-CT) images. The imaging technique plays a key role in detecting the tissue deformation details in the contact region between the tissue and the surgical tool (probe) for small force loads and provides good capabilities of creating accurate 3-D models of soft tissues. Surgical simulations rely on accurate representation of the mechanical response of soft tissues subjected to surgical manipulations. Several finite-element models have been suggested to characterize soft tissues. However, validating these models for specific tissues still remain a challenge. In this study, ex vivo lamb liver tissue is chosen to validate the linear elastic model (LEM), the linear viscoelastic model (LVEM), and the neo-Hooke hyperelastic model (NHM). We find that the LEM is more applicable to lamb liver than the LVEM for smaller force loads (< 20 g) and that the NHM is closer to reality than the LVEM for the range of force loads from 5 to 40 g.

New deformable registration technique using scale space and curve evolution theory and a finite element based validation framework.

In this paper, we present a novel and accurate approach for nonrigid registration. New feature descriptors are built as voxel signatures using scale space theory. These descriptors are used to capture the global motion of the imaged object. Local deformations are modelled through an evolution process of equi-spaced closed curves/surfaces (iso-contours/surfaces) which are generated using fast marching level sets and are matched using the built feature descriptors. The performance of the proposed approach is validated using the finite element method. Both 2D and 3D tissue deformations cases are simulated, and the registration accuracy is quantified by co-registering the deformed images with the original ones and comparing the recovered mesh point displacements with the simulated ones. The evaluation results show the potential of the proposed approach in handling local deformation better than some conventional approaches.