Phantom Validation Research Articles

3D MR fingerprinting using Seiffert spirals

PurposeSeiffert spirals were recently explored as an efficient way to traverse 3D k‐space compared to traditional 3D techniques. Several studies have shown the ability of 3D MR fingerprinting (MRF) techniques to acquire T1 and T2 relaxation maps in a short period of time. However, these sequences do not sample across a large region of 3D k‐space every TR, especially in the way that Seiffert trajectories can.MethodsA 3D MRF sequence was designed using 8 Seiffert spirals rotated in 3D k‐space, with flip angle modulation for T1 and T2 sensitivity. The sequence was compared to an MRF sequence using a 2D spiral rotated in 3D k‐space using the tiny golden angle acquisition with similar resolution/readout duration. Both sequences were evaluated using simulations, phantom validation, and in vivo imaging.ResultsIn all experiments, the Seiffert spiral MRF sequence performed similar to if not better than the multi‐axis 2D spiral MRF sequence. Strong intraclass correlation coefficients (> 0.9) were found between conventional and MRF sequences in phantoms, whereas the in vivo results showed slightly less aliasing artifact with the Seiffert trajectory.ConclusionIn this study, Seiffert spirals were used within the MRF framework to acquire high‐resolution T1 and T2 relaxation time maps in less than 2.5 min. The reduced aliasing artifacts seen with the Seiffert sequence suggests that sampling over 3D k‐space evenly each TR can improve quantification or shorten scan times.

Phantom Validation of a Conservation of Activity-Based Partial Volume Correction Method for Arterial Input Function in Dynamic PET Imaging

Dynamic PET (dPET) imaging can be utilized to perform kinetic modelling of various physiologic processes, which are exploited by the constantly expanding range of targeted radiopharmaceuticals. To date, dPET remains primarily in the research realm due to a number of technical challenges, not least of which is addressing partial volume effects (PVE) in the input function. We propose a series of equations for the correction of PVE in the input function and present the results of a validation study, based on a purpose built phantom. 18F-dPET experiments were performed using the phantom on a set of flow tubes representing large arteries, such as the aorta (1” 2.54 cm ID), down to smaller vessels, such as the iliac arteries and veins (1/4” 0.635 cm ID). When applied to the dPET experimental images, the PVE correction equations were able to successfully correct the image-derived input functions by as much as 59 ± 35% in the presence of background, which resulted in image-derived area under the curve (AUC) values within 8 ± 9% of ground truth AUC. The peak heights were similarly well corrected to within 9 ± 10% of the scaled DCE-CT curves. The same equations were then successfully applied to correct patient input functions in the aorta and internal iliac artery/vein. These straightforward algorithms can be applied to dPET images from any PET-CT scanner to restore the input function back to a more clinically representative value, without the need for high-end Time of Flight systems or Point Spread Function correction algorithms.

Development of an independent MU calculation software for radiotherapy treatments with stereotactic cones.

PurposeDevelopment of an independent MU calculator (StereoCalc) with and without heterogeneity corrections for stereotactic treatments, in a Varian TrueBeam STx LINAC using stereotactic cones, with flattening filter‐free photon energies.MethodsMultiple depth curves and output factors were measured, following the dosimetry formalism for small fields proposed by the TRS‐483. The developed StereoCalc imports and processes the beam data files and calculates the patient plans with and without heterogeneity correction. Validation of the developed software was carried out using phantoms. The accuracy of the StereoCalc software was verified in stereotactic patient plans.ResultsA maximum difference of 2.47% and 2.07% was obtained in the phantom validation tests with and without heterogeneity correction, respectively. The mean percentual difference of StereoCalc from cone dose calculation (CDC) in the clinical testing was 2.86% ±1.27% and 0.78% ±0.48% with and without heterogeneity correction, respectively. The largest differences found were 7.34% and 1.98%, respectively.ConclusionsThe results obtained in this work show that the MU calculated with StereoCalc software is in good agreement with the values calculated by the treatment planning systems, both in static fields and arcs. We have also improved the software to consider heterogeneity corrections calculations. As expected, and as a major achievement of this work, some differences were observed when heterogeneities were considered. StereoCalc proved to be a powerful tool that can be integrated into the specific quality assurance program in a medical physics department for independent verification in stereotactic treatment with cones.

Monte Carlo simulations and phantom validation of low-dose radiotherapy to the lungs using an interventional radiology C-arm fluoroscope.

To use MC simulations and phantom measurements to investigate the dosimetry of a kilovoltage x-ray beam from an IR fluoroscope to deliver low-dose (0.3-1.0Gy) radiotherapy to the lungs. PENELOPE was used to model a 125kV, 5.94mm Al HVL x-ray beam produced by a fluoroscope. The model was validated through depth-dose, in-plane/cross-plane profiles and absorbed dose at 2.5-, 5.1-, 10.2- and 15.2-cm depths against the measured beam in an acrylic phantom. CT images of an anthropomorphic phantom thorax/lungs were used to simulate 0.5Gy dose distributions for PA, AP/PA, 3-field and 4-field treatments. DVHs were generated to assess the dose to the lungs and nearby organs. Gafchromic film was used to measure doses in the phantom exposed to PA and 4-field treatments, and compared to the MC simulations. Depth-dose and profile results were within 3.2% and 7.8% of the MC data uncertainty, respectively, while dose gamma analysis ranged from 0.7 to 1.0. Mean dose to the lungs were 1.1-, 0.8-, 0.9-, and 0.8- Gy for the PA, AP/PA, 3-field, and 4-field after isodose normalization to cover∼95% of each lung volume. Skin dose toxicity was highest for the PA and lowest for the 4-field, and both arrangements successfully delivered the treatment on the phantom. However, the dose distribution for the PA was highly non-uniform and produced skin doses up to 4Gy. The dose distribution for the 4-field produced a uniform 0.6Gy dose throughout the lungs, with a maximum dose of 0.73Gy. The average percent difference between experimental and Monte Carlo values were -0.1% (range -3% to +4%) for the PA treatment and 0.3% (range -10.3% to +15.2%) for the 4-field treatment. A 125kV x-ray beam from an IR fluoroscope delivered through two or more fields can deliver an effective low-dose radiotherapy treatment to the lungs. The 4-field arrangement not only provides an effective treatment, but also significant dose sparing to healthy organs, including skin, compared to the PA treatment. Use of fluoroscopy appears to be a viable alternative to megavoltage radiation therapy equipment for delivering low-dose radiotherapy to the lungs.

Hepatic dual-contrast CT imaging: slow triple kVp switching CT with CNN-based sinogram completion and material decomposition.

Purpose: Dual-contrast protocols are a promising clinical multienergy computed tomography (CT) application for focal liver lesion detection and characterization. One avenue to enable multienergy CT is the introduction of photon-counting detectors (PCD). Although clinical translation is highly desired because of the diagnostic benefits of PCDs, it will still be a decade or more before they are broadly available. In our work, we investigated an alternative solution that can be implemented on widely used conventional CT systems (single source and integrating detector) to perform multimaterial spectral decomposition for dual-contrast imaging. Approach: We propose to slowly alternate the x-ray tube voltage between 3 kVp levels so each kVp level covers a few degrees of gantry rotation. This leads to the challenge of sparsely sampled projection data in each energy level. Performing the material decomposition (MD) in the sinogram domain is not directly possible as the projection images of the three energy levels are not angularly aligned. In order to overcome this challenge, we developed a convolutional neural network (CNN) framework for sparse sinogram completion (SC) and MD. To evaluate the feasibility of the slow kVp switching scheme, simulation studies of an abdominal phantom, which included liver lesions, were conducted. Results: The line-integral SC network yielded sinograms with a pixel-wise of the line-integrals compared to the ground truth. This provided acceptable image quality up to a switching angle of 9deg per kVp. The MD network we developed allowed us to differentiate iodine and gadolinium in the sinogram domain. The average relative quantification errors for iodine and gadolinium were below 10%. Conclusions: We developed a slow triple kVp switching data acquisition scheme and a CNN-based data processing pipeline. Results from a digital phantom validation illustrate the potential for future applications of dual-contrast agent protocols on practically available single-energy CT systems.

Feasibility study of 2D Dixon-Magnetic Resonance Fingerprinting (MRF) of breast cancer

PurposeApplication of MRF to evaluate the feasibility of 2D Dixon blurring-corrected MRF (2DDb-cMRF) to differentiate breast cancer (BC) from normal fibroglandular tissue (FGT). MethodsProspective study on 14 patients with unilateral BC on 1.5 T system/axial T2w-TSE sequence, 2DDb-cMRF, B1 map, dynamic contrast-enhanced (DCE) T1-w GE-series. Mean T1 and T2 values and standard deviations were computed in the BC-/FGT-ROI on pre-/post-contrast MRF-maps and their differences were tested by two-tailed student t-test.Accuracy and repeatability of MRF were evaluated in a phantom experiment with gelatin with Primovist surrounded by fat.The T1 reduction between pre-/post-contrast MRF-maps was correlated to DCE signal enhancement in the last image post-contrast through the Pearson´s correlation coefficient (r) and for the phantom validation experiment through the Lin’s concordance correlation coefficient (CCC).Visual evaluation of cancers on MRF-Maps was performed by rating each MRF-Map by 3 radiologists. ResultsT1- and T2-MRF values of BC vs. FGT were for T1 and T2 pre-contrast respectively: 1147 ± 1 ms vs. 1052 ± 9 ms (p = 0.007) and 83 ± 1 ms vs. 73 ± 1 ms (p = 0.03); post-contrast respectively: 367.3 ± 121.5 ms vs. 690.3 ± 200.3 ms (p = 0.0005) and 76.9 ± 11.5 ms vs. 69.8 ± 15.2 ms (p = 0.12). r was positive (FGT r = 0.7; BC r = 0.6). CCC was 0.999 for T1 and 0.994 for T2. In the T1- and T2-MRF-Maps before contrast respectively (7,7,8)/14 and (5,9,8)/14 cancers were visible to the readers; afterwards, (11,12,12)/14 and (5,6,11)/14. ConclusionsMRF is promising for distinction between BC and FGT as well as for analyzing pre-/post-contrast T1 changes. However, its potential for differential diagnosis warrants further studies.

Direct left-ventricular global longitudinal strain (GLS) computation with a fully convolutional network

This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Encoding with Stimulated Echoes cardiac image phases acquired from 30 breast cancer patients and 30 healthy females were unwrapped via a DeepLabV3 + fully convolutional network (FCN). Myocardial strains were directly computed from the unwrapped phases with the Radial Point Interpolation Method. FCN-unwrapped phases of a phantom’s rotating gel were validated against quality-guided phase-unwrapping (QGPU) and robust transport of intensity equation (RTIE) phase-unwrapping. FCN performance on unwrapping human LV data was measured with F1 and Dice scores versus QGPU ground-truth. The reliability of FCN-based strains was assessed against RTIE-based strains with Cronbach's alpha (C-α) intraclass correlation coefficient. Mean squared error (MSE) of unwrapping the phantom experiment data at 0 dB signal-to-noise ratio were 1.6, 2.7 and 6.1 with FCN, QGPU and RTIE techniques. Human data classification accuracies were F1 = 0.95 (Dice = 0.96) with FCN and F1 = 0.94 (Dice = 0.95) with RTIE. GLS results from FCN and RTIE were −16 ± 3% vs. −16 ± 3% (C-α = 0.9) for patients and −20 ± 3% vs. −20 ± 3% (C-α = 0.9) for healthy subjects. The low MSE from the phantom validation demonstrates accuracy of phase-unwrapping with the FCN and comparable human subject results versus RTIE demonstrate GLS analysis accuracy. A deep-learning methodology for phase-unwrapping in medical images and GLS computation was developed and validated in a heterogeneous cohort.

Quantitative diffusion MRI of the abdomen and pelvis.

Diffusion MRI has enormous potential and utility in the evaluation of various abdominal and pelvic disease processes including cancer and noncancer imaging of the liver, prostate, and other organs. Quantitative diffusion MRI is based on acquisitions with multiple diffusion encodings followed by quantitative mapping of diffusion parameters that are sensitive to tissue microstructure. Compared to qualitative diffusion-weighted MRI, quantitative diffusion MRI can improve standardization of tissue characterization as needed for disease detection, staging, and treatment monitoring. However, similar to many other quantitative MRI methods, diffusion MRI faces multiple challenges including acquisition artifacts, signal modeling limitations, and biological variability. In abdominal and pelvic diffusion MRI, technical acquisition challenges include physiologic motion (respiratory, peristaltic, and pulsatile), image distortions, and low signal-to-noise ratio. If unaddressed, these challenges lead to poor technical performance (bias and precision) and clinical outcomes of quantitative diffusion MRI. Emerging and novel technical developments seek to address these challenges and may enable reliable quantitative diffusion MRI of the abdomen and pelvis. Through systematic validation in phantoms, volunteers, and patients, including multicenter studies to assess reproducibility, these emerging techniques may finally demonstrate the potential of quantitative diffusion MRI for abdominal and pelvic imaging applications.

Anthropomorphic brain phantoms for use in MRI systems: a systematic review.

To provide a systematic review of available brain MRI phantoms for comparison of structural and functional characteristics. Phantoms were identified from a literature search using two databases including Google Scholar and PubMed. Narrow inclusion criteria were followed for identification of only tissue-mimicking MRI phantoms excluding digital, computational, or numerical phantoms. Assessment criteria for the identified phantoms was based on three categories being anatomical accuracy, tissue-mimicking materials, and exhibiting relaxation times approximating in-vivo tissues. The available features and uses of each phantom were reported and discussed using the assessment criteria. Ten phantoms were identified after screening; each proposed phantom was then summarized in a table (Table 2). Significant features and characteristics were shown in the comparisons of phantom type in each category, being anthropomorphic vs. traditional phantoms. Anthropomorphic phantoms had more anatomically accurate features than traditional phantoms. On the other hand, traditional phantoms commonly used effective tissue-mimicking materials and accurate electromagnetic properties. The findings provide an overview of the different proposed tissue-mimicking MRI brain phantoms available. Various uses and features are highlighted by comparing criteria such as anatomical accuracy, tissue-mimicking material, and electromagnetic properties. Tissue-mimicking MRI phantoms are an extremely useful tool for researchers and clinicians. Future applications include personalized phantom technology and validation of MR imaging and segmentation methods.

Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data

PurposeA method named DECOMPOSE-QSM is developed to decompose bulk susceptibility measured with QSM into sub-voxel paramagnetic and diamagnetic components based on a three-pool complex signal model. MethodsMulti-echo gradient echo signal is modeled as a summation of three weighted exponentials corresponding to three types of susceptibility sources: reference susceptibility, diamagnetic and paramagnetic susceptibility relative to the reference. Paramagnetic component susceptibility (PCS) and diamagnetic component susceptibility (DCS) maps are constructed to represent the sub-voxel compartments by solving for linear and nonlinear parameters in the model. ResultsNumerical forward simulation and phantom validation confirmed the ability of DECOMPOSE-QSM to separate the mixture of paramagnetic and diamagnetic components. The PCS obtained from temperature-variant brainstem imaging follows the Curie's Law, which further validated the model and the solver. Initial in vivo investigation of human brain images showed the ability to extract sub-voxel PCS and DCS sources that produce visually enhanced contrast between brain structures comparing to threshold QSM.

A multicentre and multi-national evaluation of the accuracy of quantitative Lu-177 SPECT/CT imaging performed within the MRTDosimetry project

PurposePatient-specific dosimetry is required to ensure the safety of molecular radiotherapy and to predict response. Dosimetry involves several steps, the first of which is the determination of the activity of the radiopharmaceutical taken up by an organ/lesion over time. As uncertainties propagate along each of the subsequent steps (integration of the time–activity curve, absorbed dose calculation), establishing a reliable activity quantification is essential. The MRTDosimetry project was a European initiative to bring together expertise in metrology and nuclear medicine research, with one main goal of standardizing quantitative 177Lu SPECT/CT imaging based on a calibration protocol developed and tested in a multicentre inter-comparison. This study presents the setup and results of this comparison exercise.MethodsThe inter-comparison included nine SPECT/CT systems. Each site performed a set of three measurements with the same setup (system, acquisition and reconstruction): (1) Determination of an image calibration for conversion from counts to activity concentration (large cylinder phantom), (2) determination of recovery coefficients for partial volume correction (IEC NEMA PET body phantom with sphere inserts), (3) validation of the established quantitative imaging setup using a 3D printed two-organ phantom (ICRP110-based kidney and spleen). In contrast to previous efforts, traceability of the activity measurement was required for each participant, and all participants were asked to calculate uncertainties for their SPECT-based activities.ResultsSimilar combinations of imaging system and reconstruction lead to similar image calibration factors. The activity ratio results of the anthropomorphic phantom validation demonstrate significant harmonization of quantitative imaging performance between the sites with all sites falling within one standard deviation of the mean values for all inserts. Activity recovery was underestimated for total kidney, spleen, and kidney cortex, while it was overestimated for the medulla.ConclusionThis international comparison exercise demonstrates that harmonization of quantitative SPECT/CT is feasible when following very specific instructions of a dedicated calibration protocol, as developed within the MRTDosimetry project. While quantitative imaging performance demonstrates significant harmonization, an over- and underestimation of the activity recovery highlights the limitations of any partial volume correction in the presence of spill-in and spill-out between two adjacent volumes of interests.

On the separation of susceptibility sources in quantitative susceptibility mapping: Theory and phantom validation with an in vivo application to multiple sclerosis lesions of different age

PurposeIn biological tissue, phase contrast is determined by multiple substances such as iron, myelin or calcifications. Often, these substances occur co-located within the same measurement volume. However, quantitative susceptibility mapping can solely measure the average susceptibility per voxel. To provide new insight in disease progression and mechanisms in neurological diseases, where multiple processes such as demyelination and iron accumulation occur simultaneously in the same location, a separation of susceptibility sources is desirable to disentangle the underlying susceptibility proportions. MethodsThe basic concept of separating the susceptibility effects from sources with different sign within one voxel is to include information on relaxation rate ΔR2∗ in the quantitative susceptibility mapping reconstruction pipeline. The presented reconstruction algorithm is implemented as a constrained minimization problem and solved using conjugate gradients. The algorithm is evaluated using a software phantom and validated in MRI measurements with a phantom containing mixtures of microscopic positive and negative susceptibility sources. Data from three multiple sclerosis patients are used to show in vivo feasibility. ResultsIn numerical simulations, the feasibility of disentangling susceptibility sources within the same voxel was confirmed provided the critera of the static dephasing regime were fulfilled. In phantom experiments, the magnitude decay kernel, which is an essential reconstruction parameter of the algorithm, was determined to be Dm=194.5T-1s-1ppm-1, and susceptibility sources could be separated in MRI measurement data. ConclusionsIn conclusion, in this study a detailed description of the implementation of an algorithm for the separation of positive and negative susceptibility sources within the same volume element as well as its limitations is presented and validated quantitatively in both simulation and phantom experiments for the first time. An application to multiple sclerosis lesions shows promising results for in vivo usability.

Automatic 3D Monte-Carlo-based secondary dose calculation for online verification of 1.5 T magnetic resonance imaging guided radiotherapy.

Hybrid magnetic resonance linear accelerator (MR-Linac) systems represent a novel technology for online adaptive radiotherapy. 3D secondary dose calculation (SDC) of online adapted plans is required to assure patient safety. Currently, no 3D-SDC solution is available for 1.5T MR-Linac systems. Therefore, the aim of this project was to develop and validate a method for online automatic 3D-SDC for adaptive MR-Linac treatments. An accelerator head model was designed for an 1.5T MR-Linac system, neglecting the magnetic field. The use of this model for online 3D-SDC of MR-Linac plans was validated in a three-step process: (1) comparison to measured beam data, (2) investigation of performance and limitations in a planning phantom and (3) clinical validation using n = 100 patient plans from different tumor entities, comparing the developed 3D-SDC with experimental plan QA. The developed model showed median gamma passing rates compared to MR-Linac base data of 84.7%, 100% and 99.1% for crossplane, inplane and depth-dose-profiles, respectively. Comparison of 3D-SDC and full dose calculation in a planning phantom revealed that with 5 beams gamma passing rates 95% can be achieved for central target locations. With a median calculation time of 1:23 min, 3D-SDC of online adapted clinical MR-Linac plans demonstrated a median gamma passing rate of 98.9% compared to full dose calculation, whereas experimental plan QA reached 99.5%. Here, we describe the first technical 3D-SDC solution for online adaptive MR-guided radiotherapy. For clinical situations with peripheral targets and a small number of beams additional verification appears necessary. Further improvement may include 3D-SDC with consideration of the magnetic field.

Multimodal guided wave inversion for arterial stiffness: methodology and validation in phantoms

Arterial stiffness is an important biomarker for many cardiovascular diseases. Shear wave elastography is a recent technique aimed at estimating local arterial stiffness using guided wave inversion (GWI), i.e. matching the computed and measured wave dispersion. This paper develops and validates a new GWI approach by synthesizing various recent observations and algorithms: (a) refinements to signal processing to obtain more accurate experimental dispersion curves; (b) an efficient forward model to compute theoretical dispersion curves for immersed, incompressible cylindrical waveguides; (c) an optimization framework based on the recent observation that the measured dispersion curve is multimodal, i.e. it matches for not one but two different wave modes in two different frequency ranges. The resulting inversion approach is validated using extensive experimental data from rubber tube phantoms, not only for modulus estimation but also to simultaneously estimate modulus and wall thickness. The observations indicate that the modulus estimates are best performed with the information on wall thickness. The approach, which takes less than half a minute to run, is shown to be accurate, with the modulus estimated with less than 4% error for 70% of the experiments.

The LUCA device: a multi-modal platform combining diffuse optics and ultrasound imaging for thyroid cancer screening.

We present the LUCA device, a multi-modal platform combining eight-wavelength near infrared time resolved spectroscopy, sixteen-channel diffuse correlation spectroscopy and a clinical ultrasound in a single device. By simultaneously measuring the tissue hemodynamics and performing ultrasound imaging, this platform aims to tackle the low specificity and sensitivity of the current thyroid cancer diagnosis techniques, improving the screening of thyroid nodules. Here, we show a detailed description of the device, components and modules. Furthermore, we show the device tests performed through well established protocols for phantom validation, and the performance assessment for in vivo. The characterization tests demonstrate that LUCA device is capable of performing high quality measurements, with a precision in determining in vivo tissue optical and dynamic properties of better than 3%, and a reproducibility of better than 10% after ultrasound-guided probe repositioning, even with low photon count-rates, making it suitable for a wide variety of clinical applications.

Whole-brain amide CEST imaging at 3T with a steady-state radial MRI acquisition.

To develop a steady-state saturation with radial readout chemical exchange saturation transfer (starCEST) for acquiring CEST images at 3 Tesla (T). The polynomial Lorentzian line-shape fitting approach was further developed for extracting amideCEST intensities at this field. StarCEST MRI using periodically rotated overlapping parallel lines with enhanced reconstruction-based spatial sampling was implemented to acquire Z-spectra that are robust to brain motion. Multi-linear singular value decomposition postprocessing was applied to enhance the CEST SNR. The egg white phantom studies were performed at 3T to reveal the contributions to the 3.5 ppm CEST signal. Based on the phantom validation, the amideCEST peak was quantified using the polynomial Lorentzian line-shape fitting, which exploits the inverse relationship between Z-spectral intensity and the longitudinal relaxation rate in the rotating frame. The 3D turbo spin echo CEST was also performed to compare with the starCEST method. The amideCEST peak showed a negligible peak B1 dependence between 1.2 µT and 2.4 µT. The amideCEST images acquired with starCEST showed much improved image quality, SNR, and motion robustness compared to the conventional 3D turbo spin echo CEST method with the same scan time. The amideCEST contrast extracted by the polynomial Lorentzian line-shape fitting method trended toward a stronger gray matter signal (1.32% ± 0.30%) than white matter (0.92% ± 0.08%; P = .02, n = 5). When calculating the magnetization transfer contrast and T1 -corrected rotating frame relaxation rate maps, amideCEST again was not significantly different for white matter and gray matter. Rapid multi-slice amideCEST mapping can be achieved by the starCEST method (< 5 min) at 3T by combing with the polynomial Lorentzian line-shape fitting method.

Computational FEM Model and Phantom Validation of Microwave Ablation for Segmental Microcalcifications in Breasts Using a Coaxial Double-Slot Antenna.

Introduction Cancer is the second leading cause of death worldwide. Breast cancer is the second most common cause of cancer-related mortality, accounting for 11.6% of the total number of deaths. The main treatments for this disease are surgical removal of the tumor, radiotherapy, and chemotherapy. Recently, different minimally invasive technologies have been applied (e.g., emission of electromagnetic waves, thermal and chemical means) to overcome the important side effects of these treatment modalities. The objective of this study was to develop and evaluate a predictive computational model of microwave ablation. Materials and Methods The predictive computational model of microwave ablation was constructed by means of a dual-slot coaxial antenna. The model was compared with an experiment performed using a breast phantom, which emulates the dielectric properties of breast tissue with segmental microcalcifications. The standing wave ratio (SWR) was obtained for both methods to make a comparison and determine the feasibility of applying electromagnetic ablation to premalignant lesions in breasts. Specifically, for the analysis of segmental microcalcifications, a breast phantom with segmental microcalcifications was developed and two computational models were performed under the same conditions (except for blood perfusion, which was excluded in one of the models). Results The SWR was obtained by triplicate experiments in the phantom, and the measurements had a difference of 0.191 between the minimum and maximum SWR values, implying a change of power reflection of 0.8%. The average of the three measurements was compared with the simulation that did not consider blood perfusion. The comparison yielded a change of 0.104, representing a 0.2% change in power reflection. Discussion. Both experimentation in phantom and simulations demonstrated that ablation therapy can be performed using this antenna. However, an additional optimization procedure is warranted to increase the efficiency of the antenna.

In situ evaluation of spatiotemporal distribution of doxorubicin from Drug-eluting Beads in a tissue mimicking phantom

Understanding the intra-tumoral distribution of chemotherapeutic drugs is extremely important in predicting therapeutic outcome. Tissue mimicking gel phantoms are useful for studying drug distribution in vitro but quantifying distribution is laborious due to the need to section phantoms over the relevant time course and individually quantify drug elution. In this study we compare a bespoke version of the traditional phantom sectioning approach, with a novel confocal microscopy technique that enables dynamic in situ measurements of drug concentration. Release of doxorubicin from Drug-eluting Embolization Beads (DEBs) was measured in phantoms composed of alginate and agarose over comparable time intervals. Drug release from several different types of bead were measured. The non-radiopaque DC Bead™ generated a higher concentration at the boundary between the beads and the phantom and larger drug penetration distance within the release period, compared with the radiopaque DC Bead LUMI™. This is likely due to the difference of compositional and structural characteristics of the hydrogel beads interacting differently with the loaded drug. Comparison of in vitro results against historical in vivo data show good agreement in terms of drug penetration, when confounding factors such as geometry, elimination and bead chemistry were accounted for. Hence these methods have demonstrated potential for both bead and gel phantom validation, and provide opportunities for optimisation of bead design and embolization protocols through in vitro-in vivo comparison.

Shear wave cardiovascular MR elastography using intrinsic cardiac motion for transducer-free non-invasive evaluation of myocardial shear wave velocity

Changes in myocardial stiffness may represent a valuable biomarker for early tissue injury or adverse remodeling. In this study, we developed and validated a novel transducer-free magnetic resonance elastography (MRE) approach for quantifying myocardial biomechanics using aortic valve closure-induced shear waves. Using motion-sensitized two-dimensional pencil beams, septal shear waves were imaged at high temporal resolution. Shear wave speed was measured using time-of-flight of waves travelling between two pencil beams and corrected for geometrical biases. After validation in phantoms, results from twelve healthy volunteers and five cardiac patients (two left ventricular hypertrophy, two myocardial infarcts, and one without confirmed pathology) were obtained. Torsional shear wave speed in the phantom was 3.0 ± 0.1 m/s, corresponding with reference speeds of 2.8 ± 0.1 m/s. Geometrically-biased flexural shear wave speed was 1.9 ± 0.1 m/s, corresponding with simulation values of 2.0 m/s. Corrected septal shear wave speeds were significantly higher in patients than healthy volunteers [14.1 (11.0–15.8) m/s versus 3.6 (2.7–4.3) m/s, p = 0.001]. The interobserver 95%-limits-of-agreement in healthy volunteers were ± 1.3 m/s and interstudy 95%-limits-of-agreement − 0.7 to 1.2 m/s. In conclusion, myocardial shear wave speed can be measured using aortic valve closure-induced shear waves, with cardiac patients showing significantly higher shear wave speeds than healthy volunteers. This non-invasive measure may provide valuable insights into the pathophysiology of heart failure.

Toward real-time verification for MLC tracking treatments using time-resolved EPID imaging.

In multileaf collimator (MLC) tracking, the MLC positions from the original treatment plan are continuously modified to account for intrafraction tumor motion. As the treatment is adapted in real time, there is additional risk of delivery errors which cannot be detected using traditional pretreatment dose verification. The purpose of this work is to develop a system for real-time geometric verification of MLC tracking treatments using an electronic portal imaging device (EPID). MLC tracking was utilized during volumetric modulated arc therapy (VMAT). During these deliveries, treatment beam images were taken at 9.57 frames per second using an EPID and frame grabber computer. MLC positions were extracted from each image frame and used to assess delivery accuracy using three geometric measures: the location, size, and shape of the radiation field. The EPID-measured field location was compared to the tumor motion measured by implanted electromagnetic markers. The size and shape of the beam were compared to the size and shape from the original treatment plan, respectively. This technique was validated by simulating errors in phantom test deliveries and by comparison between EPID measurements and treatment log files. The method was applied offline to images acquired during the LIGHT Stereotactic Ablative Body Radiotherapy (SABR) clinical trial, where MLC tracking was performed for 17 lung cancer patients. The EPID-based verification results were subsequently compared to post-treatment dose reconstruction. Simulated field location errors were detected during phantom validation tests with an uncertainty of 0.28mm (parallel to MLC motion) and 0.38mm (perpendicular), expressed as a root-mean-square error (RMSError ). For simulated field size errors, the RMSError was 0.47 cm2 and field shape changes were detected for random errors with standard deviation≥2.5mm. For clinical lung SABR deliveries, field location errors of 1.6mm (parallel MLC motion) and 4.9mm (perpendicular) were measured (expressed as a full-width-half-maximum). The mean and standard deviation of the errors in field size and shape were 0.0±0.3 cm2 and 0.3±0.1 (expressed as a translation-invariant normalized RMS). No correlation was observed between geometric errors during each treatment fraction and dosimetric errors in the reconstructed dose to the target volume for this cohort of patients. A system for real-time delivery verification has been developed for MLC tracking using time-resolved EPID imaging. The technique has been tested offline in phantom-based deliveries and clinical patient deliveries and was used to independently verify the geometric accuracy of the MLC during MLC tracking radiotherapy.