Rachid Fahmi

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.

Dose Reduction Assessment in Dynamic CT Myocardial Perfusion Imaging in a Porcine Balloon-Induced-Ischemia Model

We investigated the use of an advanced hybrid iterative reconstruction (IR) technique (iDose4, Philips Health- care) for low dose dynamic myocardial CT perfusion (CTP) imaging. A porcine model was created to mimic coronary stenosis through partial occlusion of the left anterior descending (LAD) artery with a balloon catheter. The severity of LAD occlusion was adjusted with FFR measurements. Dynamic CT images were acquired at end-systole (45% R-R) using a multi-detector CT (MDCT) scanner. Various corrections were applied to the acquired scans to reduce motion and imaging artifacts. Absolute myocardial blood flow (MBF) was computed with a deconvolution-based approach using singular value decomposition (SVD). We compared a high and a low dose radiation protocol corresponding to two different tube-voltage/tube-current combinations (80kV p/100mAs and 120kV p/150mAs). The corresponding radiation doses for these protocols are 7.8mSv and 34.3mSV , respectively. The images were reconstructed using conventional FBP and three noise-reduction strengths of the IR method, iDose. Flow contrast-to-noise ratio, CNRf, as obtained from MBF maps, was used to quantitatively evaluate the effect of reconstruction on contrast between normal and ischemic myocardial tissue. Preliminary results showed that the use of iDose to reconstruct low dose images provide better or comparable CNRf to that of high dose images reconstructed with FBP, suggesting significant dose savings. CNRf was improved with the three used levels of iDose compared to FBP for both protocols. When using the entire 4D dynamic sequence for MBF computation, a 77% dose reduction was achieved, while considering only half the scans (i.e., every other heart cycle) allowed even further dose reduction while maintaining relatively higher CNRf.

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 ow (MBF), which in concert with coronary CT angiography enable CT to provide a unique, comprehensive, fast analysis of both coronary anatomy and functional ow. 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 ow condition was obtained with balloon completely de ated. Partial occlusion was induced by balloon in ation 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 (iDose4, Philips Healthcare). Processing included: beam hardening (BH) correction, registration of image volumes using 3D cubic B-spline normalized mutual-information, and spatio-temporal bilateral ltering to reduce partial scan artifacts and noise variation. Absolute blood ow was calculated with a deconvolutionbased approach using singular value decomposition (SVD). Arterial input function was estimated from the left ventricle (LV) cavity. Regions of interest (ROIs) were identi ed in healthy and ischemic myocardium and compared in normal and occluded conditions. Under-perfusion was detected in the correct LAD territory and ow reduction agreed well with FFR measurements. Flow was reduced, on average, in LAD territories by 54%.

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 (CNRf ) 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.

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.

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.

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.

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.

Estimation of blood flow with confidence intervals in CT myocardial perfusion imaging (Conference Presentation)

We present a method to estimate myocardial blood flow confidence intervals (MBF-CI) for model-based analysis of CT myocardial perfusion imaging (CT-MPI). We have determined that good fits, as assessed with visual evaluation, root-mean-square error, and Akaike information criterion (AIC), can lead to very poor MBF estimates with >50% error. We develop the use of confidence intervals to help confirm that good models are leading to good MBF estimates. We assess MBF precision for multiple analysis models from the literature, including adiabatic approximation of tissue homogeneity (AATH), plasma tissue uptake (PTU), and a newly proposed robust physiologic model (RPM). For evaluation, we use a physiologic simulator, digital CT-MPI phantom, and in vivo CT-MPI data from a porcine model of coronary stenosis. MBF-CI was calculated using empirical likelihood to determine the range of MBF values that fall within the 95% joint parameter confidence region. On simulated data, although AIC was smallest (preferred) for AATH and greatest for RPM, standard deviation of MBF measurements was between 7-41 times greater for AATH than RPM, indicating RPM significantly improved MBF precision. MBF-CI appropriately selected RPM for best MBF precision. For the SNR=20 example condition, standard deviations were 1.7, 28.4, and 34.7mL/min/100g; MBF-CIs were 26, 375, and 435mL/min/100g; and AICs were 299.7, 253.4, and 245.3 for RPM, PTU, and AATH, respectively. Overall, best MBF precision was ranked RPM>PTU>AATH. These findings suggest that models with fewer free parameters, such as RPM, yield precise MBF measurements and that MBF-CI can select for models with good MBF measurement precision.

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.