Improved Dynamic Cardiac Phantom Based on 4D NURBS and Tagged MRI

DENSE-SIM: A modular pipeline for the evaluation of cine displacement encoding with stimulated echoes images with sub-voxel ground-truth strain

BACKGROUND

Myocardial strain is a valuable biomarker for diagnosing and predicting cardiac conditions, offering additional prognostic information to traditional metrics such as ejection fraction. While cardiovascular magnetic resonance (CMR) methods, particularly cine displacement encoding with stimulated echoes (DENSE), are the gold standard for strain estimation, evaluation of regional strain estimation requires precise ground truth. This study introduces DENSE-SIM, an open-source simulation pipeline for generating realistic cine DENSE images with high-resolution known ground-truth strain, enabling evaluation of accuracy and precision in strain analysis pipelines.

METHODS

This pipeline is a modular tool designed for simulating cine DENSE images and evaluating strain estimation performance. It comprises four main modules: 1) anatomy generation, for creating end-diastolic cardiac shapes; 2) motion generation, to produce myocardial deformations over time and Lagrangian strain; 3) DENSE image generation, using Bloch equation simulations with realistic noise, spiral sampling, and phase cycling; and 4) strain evaluation. To illustrate the pipeline, a synthetic dataset of 180 short-axis slices was created and analyzed using the commonly used DENSEanalysis tool. The impact of the spatial regularization parameter (k) in DENSEanalysis was evaluated against the ground-truth pixel strain, to particularly assess the resulting bias and variance characteristics.

RESULTS

Simulated strain profiles were generated with a myocardial signal-to-noise ratio (SNR) ranging from 3.9 to 17.7. For end-systolic radial strain, DENSEanalysis average signed error (ASE) in Green strain ranged from 0.04 ± 0.09 (true-calculated, mean ± std) for a typical regularization (k = 0.9), to -0.01 ± 0.21 at low regularization (k = 0.1). Circumferential strain ASE ranged from -0.00 ± 0.04 at k = 0.9 to -0.01 ± 0.10 at k = 0.1. This demonstrates that the circumferential strain closely matched the ground truth, while radial strain displayed more significant underestimations, particularly near the endocardium. A lower regularization parameter from 0.3 to 0.6 depending on the myocardial SNR would be more appropriate to estimate the radial strain, as a compromise between noise compensation and global strain accuracy.

CONCLUSION

Generating realistic cine DENSE images with high-resolution ground-truth strain and myocardial segmentation enables accurate evaluation of strain analysis tools, while reproducing key in-vivo acquisition features, and will facilitate the future development of deep-learning models for myocardial strain analysis, enhancing clinical CMR workflows.

A simulation-based phantom model for generating synthetic mitral valve image data-application to MRI acquisition planning

PURPOSE

Numerical phantom methods are widely used in the development of medical imaging methods. They enable quantitative evaluation and direct comparison with controlled and known ground truth information. Cardiac magnetic resonance has the potential for a comprehensive evaluation of the mitral valve (MV). The goal of this work is the development of a numerical simulation framework that supports the investigation of MRI imaging strategies for the mitral valve.

METHODS

We present a pipeline for synthetic image generation based on the combination of individual anatomical 3D models with a position-based dynamics simulation of the mitral valve closure. The corresponding images are generated using modality-specific intensity models and spatiotemporal sampling concepts. We test the applicability in the context of MRI imaging strategies for the assessment of the mitral valve. Synthetic images are generated with different strategies regarding image orientation (SAX and rLAX) and spatial sampling density.

RESULTS

The suitability of the imaging strategy is evaluated by comparing MV segmentations against ground truth annotations. The generated synthetic images were compared to ones acquired with similar parameters, and the result is promising. The quantitative analysis of annotation results suggests that the rLAX sampling strategy is preferable for MV assessment, reaching accuracy values that are comparable to or even outperform literature values.

CONCLUSION

The proposed approach provides a valuable tool for the evaluation and optimization of cardiac valve image acquisition. Its application to the use case identifies the radial image sampling strategy as the most suitable for MV assessment through MRI.

MIRD Pamphlet No. 28, Part 2: Comparative Evaluation of MIRDcalc Dosimetry Software Across a Compendium of Diagnostic Radiopharmaceuticals

Radiopharmaceutical dosimetry is usually estimated via organ-level MIRD schema-style formalisms, which form the computational basis for commonly used clinical and research dosimetry software. Recently, MIRDcalc internal dosimetry software was developed to provide a freely available organ-level dosimetry solution that incorporates up-to-date models of human anatomy, addresses uncertainty in radiopharmaceutical biokinetics and patient organ masses, and offers a 1-screen user interface as well as quality assurance tools. The present work describes the validation of MIRDcalc and, secondarily, provides a compendium of radiopharmaceutical dose coefficients obtained with MIRDcalc. Biokinetic data for about 70 currently and historically used radiopharmaceuticals were obtained from the International Commission on Radiological Protection (ICRP) publication 128 radiopharmaceutical data compendium. Absorbed dose and effective dose coefficients were derived from the biokinetic datasets using MIRDcalc, IDAC-Dose, and OLINDA software. The dose coefficients obtained with MIRDcalc were systematically compared against the other software-derived dose coefficients and those originally presented in ICRP publication 128. Dose coefficients computed with MIRDcalc and IDAC-Dose showed excellent overall agreement. The dose coefficients derived from other software and the dose coefficients promulgated in ICRP publication 128 both were in reasonable agreement with the dose coefficients computed with MIRDcalc. Future work should expand the scope of the validation to include personalized dosimetry calculations.

MIRD Pamphlet No. 28, Part 1: MIRDcalc-A Software Tool for Medical Internal Radiation Dosimetry

Medical internal radiation dosimetry constitutes a fundamental aspect of diagnosis, treatment, optimization, and safety in nuclear medicine. The MIRD committee of the Society of Nuclear Medicine and Medical Imaging developed a new computational tool to support organ-level and suborgan tissue dosimetry (MIRDcalc, version 1). Based on a standard Excel spreadsheet platform, MIRDcalc provides enhanced capabilities to facilitate radiopharmaceutical internal dosimetry. This new computational tool implements the well-established MIRD schema for internal dosimetry. The spreadsheet incorporates a significantly enhanced database comprising details for 333 radionuclides, 12 phantom reference models (International Commission on Radiological Protection), 81 source regions, and 48 target regions, along with the ability to interpolate between models for patient-specific dosimetry. The software also includes sphere models of various composition for tumor dosimetry. MIRDcalc offers several noteworthy features for organ-level dosimetry, including modeling of blood source regions and dynamic source regions defined by user input, integration of tumor tissues, error propagation, quality control checks, batch processing, and report-preparation capabilities. MIRDcalc implements an immediate, easy-to-use single-screen interface. The MIRDcalc software is available for free download (www.mirdsoft.org) and has been approved by the Society of Nuclear Medicine and Molecular Imaging.

A Framework for Simulating Cardiac MR Images With Varying Anatomy and Contrast

One of the limiting factors for the development and adoption of novel deep-learning (DL) based medical image analysis methods is the scarcity of labeled medical images. Medical image simulation and synthesis can provide solutions by generating ample training data with corresponding ground truth labels. Despite recent advances, generated images demonstrate limited realism and diversity. In this work, we develop a flexible framework for simulating cardiac magnetic resonance (MR) images with variable anatomical and imaging characteristics for the purpose of creating a diversified virtual population. We advance previous works on both cardiac MR image simulation and anatomical modeling to increase the realism in terms of both image appearance and underlying anatomy. To diversify the generated images, we define parameters: 1)to alter the anatomy, 2) to assign MR tissue properties to various tissue types, and 3) to manipulate the image contrast via acquisition parameters. The proposed framework is optimized to generate a substantial number of cardiac MR images with ground truth labels suitable for downstream supervised tasks. A database of virtual subjects is simulated and its usefulness for aiding a DL segmentation method is evaluated. Our experiments show that training completely with simulated images can perform comparable with a model trained with real images for heart cavity segmentation in mid-ventricular slices. Moreover, such data can be used in addition to classical augmentation for boosting the performance when training data is limited, particularly by increasing the contrast and anatomical variation, leading to better regularization and generalization. The database is publicly available at https://osf.io/bkzhm/ and the simulation code will be available at https://github.com/sinaamirrajab/CMRI.

The 4D B-spline method of calculating left ventricular functional parameters of cardiac MRI to evaluate myocardial injury of the apical segment in patients with myocarditis: a case-controlled observational study

Background

Myocarditis does not have typical clinical manifestations and thus is difficult to accurately diagnose by virtue of infection history, and electrocardiogram (EKG) and peripheral blood abnormalities. Endomyocardial biopsy is the gold standard for diagnosis of myocarditis, but is invasive, high risk, and has an observational blind area. Cardiac magnetic resonance imaging (CMRI) is multiparameter and multidirectional with high spatial resolution and high contrast of soft tissue. However, the optimal method of calculating left ventricular (LV) function in patients with apical-segment-injured myocarditis is unresolved. We compared and analyzed the differences between two different methods (Simpson and 4D B-spline surface model (known as the 4D method)) of measuring LV function by CMRI in patients with myocarditis in the 17th segment of the left ventricle.

Methods

The basic clinical data of two groups (myocarditis and non-myocarditis) were statistically analyzed, and differences in the LV function parameters by the two imaging methods were compared in the myocarditis group. Receiver-operating characteristic curves of single parameters and combined parameters based on the Simpson and 4D methods were drawn and the area under the curve, diagnostic threshold, maximum sensitivity interval, and maximum specificity interval were calculated.

Results

In the myocarditis and non-myocarditis groups the respective number of patients was 22 and 17, the percentage of males was 54.55% and 47.06%, and the average age was 32.20±11.59 and 43.06±11.62 years. The difference in LV ejection fraction (LVEF) (P=0.033) and LV end systolic volume (LVESV) (P=0.030) in the myocarditis group was statistically significant. The respective AUCs based on the Simpson and 4D methods were LVEF 0.602 vs. 0.778, LVESV 0.556 vs. 0.751, LVEF-and-LVESV 0.634 vs. 0.775. Based on the 4D method, the diagnostic thresholds of LVEF and LVESV were 34.965 (sensitivity 0.882, specificity 0.591) and 69.090 (sensitivity 0.727, specificity 0.706), the maximum sensitivity intervals of LVEF and LVESV were (24.610, 27.450) and (35.355, 37.200), and the maximum specificity intervals of LVEF and LVESV were (60.530, 65.625) and (91.625, 95.835), respectively.

Conclusions

Compared with the Simpson method, the 4D method might be more effective for CMRI diagnosis of apical-segment-injured myocarditis. When the Simpson method is used, LVEF combined with LVESV is recommended for comprehensive evaluation to improve diagnostic efficiency. When the 4D method is used, LVEF might be the preferred parameter for evaluation of LV function.

Innovations in Computer Technologies Have Impacted Radiation Dosimetry Through Anatomically Realistic Phantoms and Fast Monte Carlo Simulations

Radiological physics principles have not changed in the past 60 y when computer technologies advanced exponentially. The research field of anatomical modeling for the purpose of radiation dose calculations has experienced an explosion in activity in the past two decades. Such an exciting advancement is due to the feasibility of creating three-dimensional geometric details of the human anatomy from tomographic imaging and of performing Monte Carlo radiation transport simulations on increasingly fast and cheap personal computers. The advent of a new type of high-performance computing hardware in recent years-graphics processing units-has made it feasible to carry out time-consuming Monte Carlo calculations at near real-time speeds. This paper introduces the history of three generations of computational human phantoms (the stylized medical internal radiation dosimetry-type phantoms, the voxelized tomographic phantoms, and the boundary representation deformable phantoms) and new development of the graphics processing unit-based Monte Carlo radiation dose calculations. Examples are given for research projects performed by my students in applying computational phantoms and a new Monte Carlo code, ARCHER, to problems in radiation protection, imaging, and radiotherapy. Finally, the paper discusses challenges and future opportunities for research.

An initial investigation of hyperpolarized gas tagging magnetic resonance imaging in evaluating deformable image registration-based lung ventilation

BACKGROUND

Deformable image registration (DIR)-based lung ventilation mapping is attractive due to its simplicity, and also challenging due to its susceptibility to errors and uncertainties. In this study, we explored the use of 3D Hyperpolarized (HP) gas tagging MRI to evaluate DIR-based lung ventilation.

METHOD AND MATERIAL

Three healthy volunteers included in this study underwent both 3D HP gas tagging MRI (t-MRI) and 3D proton MRI (p-MRI) using balanced steady-state free precession pulse sequence at end of inhalation and end of exhalation. We first obtained the reference displacement vector fields (DVFs) from the t-MRIs by tracking the motion of each tagging grid between the exhalation and the inhalation phases. Then, we determined DIR-based DVFs from the p-MRIs by registering the images at the two phases with two commercial DIR algorithms. Lung ventilations were calculated from both the reference DVFs and the DIR-based DVFs using the Jacobian method and then compared using cross correlation and mutual information.

RESULTS

The DIR-based lung ventilations calculated using p-MRI varied considerably from the reference lung ventilations based on t-MRI among all three subjects. The lung ventilations generated using Velocity AI were preferable for the better spatial homogeneity and accuracy compared to the ones using MIM, with higher average cross correlation (0.328 vs 0.262) and larger average mutual information (0.528 vs 0.323).

CONCLUSION

We demonstrated that different DIR algorithms resulted in different lung ventilation maps due to underlining differences in the DVFs. HP gas tagging MRI provides a unique platform for evaluating DIR-based lung ventilation.

The development and initial evaluation of a realistic simulated SPECT dataset with simultaneous respiratory and cardiac motion for gated myocardial perfusion SPECT

We developed a realistic simulation dataset for simultaneous respiratory and cardiac (R&C) gated SPECT/CT using the 4D NURBS-based Cardiac-Torso (NCAT) Phantom and Monte Carlo simulation methods, and evaluated it for a sample application study. The 4D NCAT phantom included realistic respiratory motion and beating heart motion based on respiratory gated CT and cardiac tagged MRI data of normal human subjects. To model the respiratory motion, a set of 24 separate 3D NCAT phantoms excluding the heart was generated over a respiratory cycle. The beating heart motion was modeled separately with 48 frames per cardiac cycle for each of the 24 respiratory phases. The resultant set of 24  ×  48 3D NCAT phantoms provides a realistic model of a normal human subject at different phases of combined R&C motions. An almost noise-free SPECT projection dataset for each of the 1152 3D NCAT phantoms was generated using Monte Carlo simulation techniques and the radioactivity uptake distribution of (99m)Tc sestamibi in different organs. By grouping and summing the separate projection datasets, separate or simultaneous R&C gated acquired data with different gating schemes could be simulated. In the initial evaluation, we combined the projection datasets into ungated, 6 respiratory-gates only, 8 cardiac-gates only, and combined 6 respiratory-gates & 8 cardiac-gates projection datasets. Each dataset was reconstructed using 3D OS-EM without and with attenuation correction using the averaged and respiratory-gated attenuation maps, and the resulting reconstructed images were compared. These results were used to demonstrate the effects of R&C motions and the reduction of image artifact due to R&C motions by gating and attenuation corrections. We concluded that the realistic 4D NCAT phantom and Monte Carlo simulated SPECT projection datasets with R&C motions are powerful tools in the study of the effects of R&C motions, as well as in the development of R&C gating schemes and motion correction methods for improved SPECT/CT imaging.

An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history

Radiation dose calculation using models of the human anatomy has been a subject of great interest to radiation protection, medical imaging, and radiotherapy. However, early pioneers of this field did not foresee the exponential growth of research activity as observed today. This review article walks the reader through the history of the research and development in this field of study which started some 50 years ago. This review identifies a clear progression of computational phantom complexity which can be denoted by three distinct generations. The first generation of stylized phantoms, representing a grouping of less than dozen models, was initially developed in the 1960s at Oak Ridge National Laboratory to calculate internal doses from nuclear medicine procedures. Despite their anatomical simplicity, these computational phantoms were the best tools available at the time for internal/external dosimetry, image evaluation, and treatment dose evaluations. A second generation of a large number of voxelized phantoms arose rapidly in the late 1980s as a result of the increased availability of tomographic medical imaging and computers. Surprisingly, the last decade saw the emergence of the third generation of phantoms which are based on advanced geometries called boundary representation (BREP) in the form of Non-Uniform Rational B-Splines (NURBS) or polygonal meshes. This new class of phantoms now consists of over 287 models including those used for non-ionizing radiation applications. This review article aims to provide the reader with a general understanding of how the field of computational phantoms came about and the technical challenges it faced at different times. This goal is achieved by defining basic geometry modeling techniques and by analyzing selected phantoms in terms of geometrical features and dosimetric problems to be solved. The rich historical information is summarized in four tables that are aided by highlights in the text on how some of the most well-known phantoms were developed and used in practice. Some of the information covered in this review has not been previously reported, for example, the CAM and CAF phantoms developed in 1970s for space radiation applications. The author also clarifies confusion about 'population-average' prospective dosimetry needed for radiological protection under the current ICRP radiation protection system and 'individualized' retrospective dosimetry often performed for medical physics studies. To illustrate the impact of computational phantoms, a section of this article is devoted to examples from the author's own research group. Finally the author explains an unexpected finding during the course of preparing for this article that the phantoms from the past 50 years followed a pattern of exponential growth. The review ends on a brief discussion of future research needs (a supplementary file '3DPhantoms.pdf' to figure 15 is available for download that will allow a reader to interactively visualize the phantoms in 3D).

Modeling and Simulation of 4D PET-CT and PET-MR Images

The driving force in the research and development of new hybrid PET-CT/MR imaging scanners is the production of images with optimum quality, accuracy, and resolution. However, the acquisition process is limited by several factors. Key issues are the respiratory and cardiac motion artifacts that occur during an imaging session. In this article the necessary tools for modeling and simulation of realistic high-resolution four-dimensional PET-CT and PET-MR imaging data are described. Beyond the need for four-dimensional simulations, accurate modeling of the acquisition process can be included within the reconstruction algorithms assisting in the improvement of image quality and accuracy of estimation of physiologic parameters from four-dimensional hybrid PET imaging.

Comparison of different methods of incorporating respiratory motion for lung cancer tumor volume delineation on PET images: a simulation study

The interest of PET complementary information for the delineation of the target volume in radiotherapy of lung cancer is increasing. However, respiratory motion requires the determination of a functional internal target volume (ITV) on PET images for which several strategies have been proposed. The purpose of this study was the comparison of these strategies for taking into account respiratory motion and deriving the ITV: (1) adding fixed margins to the volume defined on a single binned image, (2) segmenting a motion averaged image and (3) considering the union of volumes delineated on binned frames. For this third strategy, binned frames were either non-corrected for motion, or corrected using two different methods: elastic registration or super resolution. The strategies' performances were assessed on realistic simulated datasets combining the NCAT phantom with a PET Philips GEMINI scanner model in GATE, and containing various configurations of tumor to background contrast, with both regular and irregular respiratory motion (with a range of motion amplitudes). The obtained ITVs' sensitivity (SE) and positive predictive value (PVE) with respect to the known true ITV were significantly higher (from 0.8 to 0.95) than all other techniques when using binned frames corrected for motion, independently of motion regularity, amplitude, or tumor to background contrast. Although the absolute difference was small and not always significant, images corrected using super resolution led to systematically better results than using elastic registration. The worst results were obtained when using the motion averaged image for SE (around 0.5-0.6) and using the margins added to a single frame for PPV (0.6-0.7), respectively. The best strategy to account for breathing motion for tumor ITV delineation in radiotherapy planning is to rely on the use of the union of volumes delineated on super resolution-corrected binned images.

Development and characterization of rodent cardiac phantoms: comparison with in vivo cardiac imaging

The increasing availability of rodent models of human cardiovascular disease has led to a need to translate noninvasive imaging techniques such as magnetic resonance imaging (MRI) from the clinic to the animal laboratory. The aim of this study was to develop phantoms simulating the short-axis view of left ventricular motion of rats and mice, thus reducing the need for live animals in the development of MRI.

Cylindrical phantoms were moulded from polyvinyl alcohol (PVA) Cryogel and attached via stiff water-filled tubing to a gear pump. Pulsatile distension of the phantoms was effected by suitable programming of the pump. Cine MRI scanning was carried out at 7 T and compared with in vivo rodent cardiac imaging.

Suitable pulsatile performance was achieved with phantoms for which the PVA material had been subjected to two freeze–thaw cycles, resulting in T1 and T2 relaxation time constants of 1656±124 ms and 55±10 ms, respectively. For the rat phantom operating at 240 beats per min (bpm), the dynamic range of the outer diameter was from 10.3 to 12.4 mm with the wall thickness varying between 1.9 and 1.2 mm. Corresponding figures for the mouse phantom at 480 bpm were outer diameter range from 5.4 to 6.4 mm and wall thickness from 1.5 to 1.2 mm.

Dynamic cardiac phantoms simulating rodent left ventricular motion in the short-axis view were successfully developed and compared with in vivo imaging. The phantoms can be used for future development work with reduced need of live animals.

Solid dynamic models for analysis of stress and strain in human hearts

This paper proposes a solid model based on four-dimensional trivariate B-spline for strain and stress analysis of ventricular myocardium. With a series of processing steps in the four-dimensional medical images, the feature points of ventricular inner and outer wall are obtained. A B-spline surface is then used to build the dynamic deformation model of the myocardial walls. With such a surface model, a hexahedron control mesh can be constructed by sweeping the cloud data, and the ventricular solid model is built by fitting the trivariate B-spline parameters. Based on these models, a method of isogeometric analysis can be applied to calculate the stress and strain continuously distributed in the ventricle. The model is represented smoothly in the cylindrical coordinate system and is easy to measure myocardium dynamics for finding abnormal motion. Experiments are carried out for comparing the stress and strain distribution. It is found that the solid model can determine ventricular dynamics which can well reflect the deformation distribution in the heart and imply early clues of cardiac diseases.

Development of a model of the coronary arterial tree for the 4D XCAT phantom

A detailed three-dimensional (3D) model of the coronary artery tree with cardiac motion has great potential for applications in a wide variety of medical imaging research areas. In this work, we first developed a computer-generated 3D model of the coronary arterial tree for the heart in the extended cardiac-torso (XCAT) phantom, thereby creating a realistic computer model of the human anatomy. The coronary arterial tree model was based on two datasets: (1) a gated cardiac dual-source computed tomography (CT) angiographic dataset obtained from a normal human subject and (2) statistical morphometric data of porcine hearts. The initial proximal segments of the vasculature and the anatomical details of the boundaries of the ventricles were defined by segmenting the CT data. An iterative rule-based generation method was developed and applied to extend the coronary arterial tree beyond the initial proximal segments. The algorithm was governed by three factors: (1) statistical morphometric measurements of the connectivity, lengths and diameters of the arterial segments; (2) avoidance forces from other vessel segments and the boundaries of the myocardium, and (3) optimality principles which minimize the drag force at the bifurcations of the generated tree. Using this algorithm, the 3D computational model of the largest six orders of the coronary arterial tree was generated, which spread across the myocardium of the left and right ventricles. The 3D coronary arterial tree model was then extended to 4D to simulate different cardiac phases by deforming the original 3D model according to the motion vector map of the 4D cardiac model of the XCAT phantom at the corresponding phases. As a result, a detailed and realistic 4D model of the coronary arterial tree was developed for the XCAT phantom by imposing constraints of anatomical and physiological characteristics of the coronary vasculature. This new 4D coronary artery tree model provides a unique simulation tool that can be used in the development and evaluation of instrumentation and methods for imaging normal and pathological hearts with myocardial perfusion defects.