Cherenkov radiation has recently emerged as an interesting phenomenon for a number of applications in the biomedical sciences. Its unique properties, including broadband emission spectrum, spectral weight in the ultraviolet and blue wavebands, and local generation of light within a given tissue, have made it an attractive new source of light within tissue for molecular imaging and phototherapy applications. While several studies have investigated the total Cherenkov light yield from radionuclides in units of [photons/decay], further consideration of the light propagation in tissue is necessary to fully consider the utility of this signal in vivo. Therefore, to help further guide the development of this novel field, quantitative estimates of the light fluence rate of Cherenkov radiation from both radionuclides and radiotherapy beams in a biological tissue are presented for the first time. Using Monte Carlo simulations, these values were found to be on the order of 0.01 – 1 nW/cm2 per MBq/g for radionuclides, and 1 – 100 µW/cm2 per Gy/sec for external radiotherapy beams, dependent on the given waveband, optical properties, and radiation source. For phototherapy applications, the total light fluence was found to be on the order of nJ/cm2 for radionuclides, and mJ/cm2 for radiotherapy beams. The results indicate that diagnostic potential is reasonable for Cherenkov excitation of molecular probes, but phototherapy may remain elusive at such exceedingly low fluence values. The simulation tools of this study are available upon request.
Cavitation events seeded by microbubbles have been previously reported to be associated with MR- or fluorescent-contrast enhancement after focused ultrasound (FUS)-induced blood-brain barrier (BBB) opening. However, it is still unknown whether bubble activity can be correlated with the reversibility (the duration of opening and the likelihood of safe reinstatement) and the permeability of opened BBB, which is critical for the clinical translation of using passive cavitation detection to monitor, predict and control the opening. In this study, the dependence of acoustic cavitation on the BBB opening duration, permeability coefficient and histological damage occurrence were thus investigated. Transcranial pulsed FUS at 1.5 MHz in the presence of systemically circulating microbubbles was applied in the mouse hippocampi (n = 60). The stable and inertial cavitation activities were monitored during sonication. Contrast-enhanced MRI was performed immediately after sonication and every 24 h up to 6 days thereafter, to assess BBB opening, brain tissue permeability and potential edema. Histological evaluations were used to assess the occurrence of neurovascular damages. It was found that stable cavitation was well correlated with: 1) the duration of the BBB opening (r2 = 0.77); 2) the permeability of the opened BBB (r2 = 0.82); 3) the likelihood of safe opening (P < 0.05, safe opening compared to cases of damage; P < 0.0001, no opening compared to safe opening). The inertial cavitation dose was correlated with the resulting BBB permeability (r2 = 0.72). Stable cavitation was found to be more reliable than inertial cavitation at assessing the BBB opening within the pressure range used in this study. This study demonstrates that the stable cavitation response during BBB opening holds promise for predicting and controlling the restoration and pharmacokinetics of FUS-opened BBB. The stable cavitation response therefore showed great promise in predicting the BBB opening duration, enabling thus control of opening according to the drug circulation time. In addition, avoiding adverse effects in the brain and assessing the pharmacokinetics of the compounds delivered can also be achieved by monitoring and controlling the stable cavitation emissions.
The use of Magnetic Resonance Imaging (MRI) in Radiotherapy (RT) planning is rapidly expanding. We review the wide range of image contrast mechanisms available to MRI and the way they are exploited for RT planning. However a number of challenges are also considered: the requirements that MR images are acquired in the RT treatment position, that they are geometrically accurate, that effects of patient motion during the scan are minimised, that tissue markers are clearly demonstrated, that an estimate of electron density can be obtained. These issues are discussed in detail, prior to the consideration of a number of specific clinical applications. This is followed by a brief discussion on the development of real-time MRI-guided RT.
MRI; magnetic resonance imaging; radiotherapy; planning
To investigate the characteristics of a hypo-intense laminar appearance in articular cartilage under external loading, microscopic MRI (μMRI) T1, T2 and T1ρ experiments of total 15 specimens of healthy and trypsin-degraded cartilage were performed at different soaking solutions (saline and 100 mM PBS). T2 and T1ρ images of the healthy tissue in saline showed no load-induced laminar appearance, while a hypo-intense layer was clearly visible in the deep part of the degraded tissue at the magic angle. Significant difference was found between T2 values at 0° and 55° (from 16.5 ± 2.8 ms to 20.2 ± 2.7 ms, p=0.0005), and at 0° and 90° (16.5 ± 2.8 ms to 21.3 ± 2.6 ms, p<0.0001) in saline solution. In contrast, this hypo-intense laminar appearance largely disappeared when tissue was soaked in PBS. The visualization of this hypo-intensity appearance in different soaking mediums calls for caution in interpreting the data of relaxation times, chemical exchange, and collagen fiber deformation.
T2; T1ρ; T1; MRI; cartilage; loading; magic angle; anisotropy; laminar appearance
The feasibility of real-time portal imaging during radiation therapy, through the Cherenkov emission (CE) effect is investigated via a medical linear accelerator (CyberKnife) irradiating a partially-filled water tank with a 60 mm circular beam. A graticule of lead/plywood and a number of tissue equivalent materials were alternatively placed at the beam entrance face while the induced Cherenkov emission (CE) at the exit face was imaged using a gated electron-multiplying-intensified-charged-coupled device (emICCD) for both stationary and dynamic scenarios. This was replicated on an Elekta Synergy® linear accelerator with portal images acquired using the iViewGT™ system. Profiles across the acquired portal images were analysed to reveal the potential resolution and contrast limits of this novel CE based portal imaging technique and compared against the current standard. The CE resolution study revealed that using the lead/plywood graticule, separations down to 3.4 ± 0.5 mm can be resolved. A 28 mm thick tissue-equivalent rod with electron density of 1.69 relative to water demonstrated a CE contrast of 15% through air and 14% through water sections, as compared to a corresponding contrast of 19% and 12% using the iViewGT™ system. For dynamic scenarios, video rate imaging with 30 frames per second was achieved. It is demonstrated that CE-based portal imaging is feasible to identify both stationary and dynamic objects within a CyberKnife radiotherapy treatment field.
Cherenkov Imaging; Portal Imaging; Radiotherapy; CyberKnife; Electronic Portal Imaging Device
Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the Neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.
We recently developed a dynamic multi-bed PET data acquisition framework to translate the quantitative benefits of Patlak voxel-wise analysis to the domain of routine clinical whole-body (WB) imaging. The standard Patlak (sPatlak) linear graphical analysis assumes irreversible PET tracer uptake, ignoring the effect of FDG dephosphorylation, which has been suggested by a number of PET studies. In this work: (i) a non-linear generalized Patlak (gPatlak) model is utilized, including a net efflux rate constant kloss, and (ii) a hybrid (s/g)Patlak (hPatlak) imaging technique is introduced to enhance contrast to noise ratios (CNRs) of uptake rate Ki images. Representative set of kinetic parameter values and the XCAT phantom were employed to generate realistic 4D simulation PET data, and the proposed methods were additionally evaluated on 11 WB dynamic PET patient studies. Quantitative analysis on the simulated Ki images over 2 groups of regions-of-interest (ROIs), with low (ROI A) or high (ROI B) true kloss relative to Ki, suggested superior accuracy for gPatlak. Bias of sPatlak was found to be 16–18% and 20–40% poorer than gPatlak for ROIs A and B, respectively. By contrast, gPatlak exhibited, on average, 10% higher noise than sPatlak. Meanwhile, the bias and noise levels for hPatlak always ranged between the other two methods. In general, hPatlak was seen to outperform all methods in terms of target-to-background ratio (TBR) and CNR for all ROIs. Validation on patient datasets demonstrated clinical feasibility for all Patlak methods, while TBR and CNR evaluations confirmed our simulation findings, and suggested presence of non-negligible kloss reversibility in clinical data. As such, we recommend gPatlak for highly quantitative imaging tasks, while, for tasks emphasizing lesion detectability (e.g. TBR, CNR) over quantification, or for high levels of noise, hPatlak is instead preferred. Finally, gPatlak and hPatlak CNR was systematically higher compared to routine SUV values.
Through this investigation we developed a methodology to evaluate and standardize CT image quality from routine abdomen protocols across different manufacturers and models. The influence of manufacturer-specific automated exposure control systems on image quality was directly assessed to standardize performance across a range of patient sizes. We evaluated 16 CT scanners across our health system, including Siemens, GE, and Toshiba models. Using each practice’s routine abdomen protocol, we measured spatial resolution, image noise, and scanner radiation output (CTDIvol). Axial and in-plane spatial resolutions were assessed through slice sensitivity profile (SSP) and modulation transfer function (MTF) measurements, respectively. Image noise and CTDIvol values were obtained for three different phantom sizes. SSP measurements demonstrated a bimodal distribution in slice widths: an average of 6.2 ± 0.2 mm using GE’s “Plus” mode reconstruction setting and 5.0 ± 0.1 mm for all other scanners. MTF curves were similar for all scanners. Average spatial frequencies at 50%, 10%, and 2% MTF values were 3.24 ± 0.37, 6.20 ± 0.34, and 7.84 ± 0.70 lp/cm, respectively. For all phantom sizes, image noise and CTDIvol varied considerably: 6.5–13.3 HU (noise) and 4.8–13.3 mGy (CTDIvol) for the smallest phantom; 9.1–18.4 HU and 9.3–28.8 mGy for the medium phantom; and 7.8–23.4 HU and 16.0–48.1 mGy for the largest phantom. Using these measurements and benchmark SSP, MTF, and image noise targets, CT image quality can be standardized across a range of patient sizes.
CT; protocol standardization; image noise; automatic exposure control
Proton therapy treatments are currently planned and delivered using the assumption that the proton relative biological effectiveness (RBE) relative to photons is 1.1. This assumption ignores strong experimental evidence that suggests the RBE varies along the treatment field, i.e. with linear energy transfer (LET) and with tissue type. A recent review study collected over 70 experimental reports on proton RBE, providing a comprehensive dataset for predicting RBE for cell survival. Using this dataset we developed a model to predict proton RBE based on dose, LET and the ratio of the linear-quadratic model parameters for the reference radiation (α/β)x, as the tissue specific parameter.
Methods and Materials
The relationship of the RBE on dose, dose average LET (LETd) and (α/β)x was explored using 287 experimental data points. A RBE model based on the linear quadratic model was derived from a nonlinear regression fitting to the data.
The proposed model predicts that the RBE increases with increasing LETd and decreases with increasing (α/β)x. The model additionally predicts a decrease in RBE with increasing dose.
The proposed phenomenological RBE model is derived using the most comprehensive collection of proton RBE experimental data to date. The model agrees with previous theoretical predictions on the relationship between RBE, LETd and (α/β)x and also makes predictions on the relationship between RBE and dose. The proposed model shows a relationship between both α and β with LETd. Previously published phenomenological models, based on a limited data set, may have to be revised.
relative biological effectiveness; proton therapy; cell survival; linear energy transfer
Obtaining accurate displacement estimates along both axial (parallel to the acoustic beam) and lateral (perpendicular to the beam) directions is an important task for several clinical applications such as shear strain imaging, modulus reconstruction and temperature imaging, where a full description of the two or three dimensional (2D/3D) deformation field is required. In this study we propose an improved speckle tracking algorithm where axial and lateral motion estimations are simultaneously performed to enhance motion tracking accuracy. More specifically, using conventional ultrasound echo data, this algorithm first finds an iso-contour in the vicinity of the peak correlation between two segments of the pre- and post-deformation ultrasound radiofrequency echo data. The algorithm then attempts to find the center of the iso-contour of the correlation function that corresponds to the unknown (sub-sample) motion vector between these two segments of echo data.
This algorithm has been tested using computer-simulated data, studies with a tissue-mimicking phantom, and in vivo breast lesion data. Computer simulation results show that the method improves the accuracy of both lateral and axial tracking. Such improvements are more significant when the deformation is small or along the lateral direction. Results from the tissue-mimicking phantom study are consistent with findings observed in computer simulations. Using in vivo breast lesion data we found that, compared to the 2D quadratic subsample displacement estimation methods, higher quality axial strain and shear strain images (e.g. 18.6% improvement in contrast-to-noise ratio for shear strain images) can be obtained for large deformations (up to 5% frame-to-frame and 15% local strains) in a multi-compression technique. Our initial results demonstrated that this conceptually and computationally simple method could improve the image quality of ultrasound-based strain elastography (SE) with current clinical equipment.
ultrasound; elasticity imaging; elastography; speckle tracking; strain elastography; shear strain
We propose a novel approach for detection of microcalcification clusters (MCs) using joint information from digital breast tomosynthesis (DBT) volume and planar projection (PPJ) image. A data set of 307 DBT views was collected with IRB approval using a prototype DBT system. The system acquires 21 projection views (PVs) from a wide tomographic angle of 60° (60°-21PV) at about twice the dose of a digital mammography (DM) system, which allows us the flexibility of simulating other DBT acquisition geometries using a subset of the PVs. In this study, we simulated a 30° DBT geometry using the central 11 PVs (30°-11PV). The narrower tomographic angle is closer to DBT geometries commercially available or under development and the dose is matched approximately to that of a DM. We developed a new joint-CAD system for detection of clustered microcalcifications. The DBT volume was reconstructed with a multiscale bilateral filtering regularized method and a PPJ image was generated from the reconstructed volume. Task-specific detection strategies were designed to combine information from the DBT volume and the PPJ image. The data set was divided into a training set (127 views with MCs) and an independent test set (104 views with MCs and 76 views without MCs). The joint-CAD system outperformed the individual CAD systems for DBT volume or PPJ image alone; the differences in the test performances were statistically significant (p<0.05) using JAFROC analysis.
digital breast tomosynthesis; computer-aided detection; microcalcification; multiscale enhancement; regularized reconstruction; planar projection image
Due to the lack of signal from solid bone in normal MR sequences for the purpose of MR-based attenuation correction, investigators have proposed using the ultrashort echo time (UTE) pulse sequence, which yields signal from bone. However, UTE-based segmentation approach might not fully capture the intra- and inter-subject bone density variation, which will inevitably lead to bias in reconstructed PET images. In this work, we investigated using the Water- And fat-Suppressed proton Projection Imaging (WASPI) sequence to obtain accurate and continuous attenuation for the bones. This approach is capable to account for intra- and inter-subject bone attenuation variations. Using data acquired from a phantom, we have found that that attenuation correction based on WASPI sequence is more accurate and precise when compared to either conventional MR attenuation correction or UTE based segmentation approaches.
PET-MR; attenuation correction; bone imaging
The purpose of this study was to determine optimal sets of b-values in diffusion-weighted MRI (DW-MRI) for obtaining monoexponential apparent diffusion coefficient (ADC) close to perfusion-insensitive intravoxel incoherent motion (IVIM) model ADC (ADCIVIM) in non-small cell lung cancer. Ten subjects had 40 DW-MRI scans before and during radiotherapy in a 1.5T MRI scanner. Respiratory triggering was applied to the echo-planar DW-MRI with TR ≈ 4500 ms, TE = 74 ms, eight b-values of 0–1000 µs/µm2, pixel size = 1.98×1.98 mm2, slice thickness = 6 mm, interslice gap = 1.2 mm, 7 axial slices and total acquisition time ≈ 6 min. One or more DW-MRI scans together covered the whole tumour volume. Monoexponential model ADC values using various b-value sets were compared to reference-standard ADCIVIM values using all eight b-values. Intra-scan coefficient of variation (CV) of active tumour volumes was computed to compare the relative noise in ADC maps. ADC values for one pre-treatment DW-MRI scan of each of the 10 subjects were computed using b-value pairs from DW-MRI images synthesized for b-values of 0–2000 µs/µm2 from the estimated IVIM parametric maps and corrupted by various Rician noise levels. The square root of mean of squared error percentage (RMSE) of the ADC value relative to the corresponding ADCIVIM for the tumour volume of the scan was computed. Monoexponential ADC values for the b-value sets of 250 and 1000; 250, 500 and 1000; 250, 650 and 1000; 250, 800 and 1000; and 250–1000 µs/µm2 were not significantly different from ADCIVIM values (p > 0.05, paired t-test). Mean error in ADC values for these sets relative to ADCIVIM were within 3.5%. Intra-scan CVs for these sets were comparable to that for ADCIVIM. The monoexponential ADC values for other sets- 0–1000; 50–1000; 100–1000; 500–1000; and 250 and 800 µs/µm2 were significantly different from the ADCIVIM values. From Rician noise simulation using b-value pairs, there was a wide range of acceptable b-value pairs giving small RMSE of ADC values relative to ADCIVIM. The pairs for small RMSE had lower b-values as the noise level increased. ADC values of a two b-value set- 250 and 1000 µs/µm2, and all three b-value sets with 250, 1000 µs/µm2 and an intermediate value approached ADCIVIM, with relative noise comparable to that of ADCIVIM. These sets may be used in lung tumours using comparatively short scan and post-processing times. Rician noise simulation suggested that the b-values in the vicinity of these experimental best b-values can be used with error within an acceptable limit. It also suggested that the optimal sets will have lower b-values as the noise level becomes higher.
DW-MRI; diffusion; ADC; IVIM model; Rician noise; lung cancer
Plastic scintillation detectors (PSDs) work well for radiation dosimetry. However, they show some temperature dependence, and a priori knowledge of the temperature surrounding the PSD is required to correct for this dependence. We present a novel approach to correct PSD response values for temperature changes instantaneously and without the need for prior knowledge of the temperature value. In addition to rendering the detector temperature-independent, this approach allows for actual temperature measurement using solely the PSD apparatus. With a temperature-controlled water tank, the temperature was varied from room temperature to more than 40°C and the PSD was used to measure the dose delivered from a cobalt-60 photon beam unit to within an average of 0.72% from the expected value. The temperature was measured during each acquisition with the PSD and a thermocouple and values were within 1°C of each other. The depth-dose curve of a 6-MV photon beam was also measured under warm non-stable conditions and this curve agreed to within an average of −0.98% from the curve obtained at room temperature. The feasibility of rendering PSDs temperature-independent was demonstrated with our approach, which also enabled simultaneous measurement of both dose and temperature. This novel approach improves both the robustness and versatility of PSDs.
A 3D-2D image registration method is presented that exploits knowledge of interventional devices (e.g., K-wires or spine screws – referred to as “known components”) to extend the functionality of intraoperative radiography/fluoroscopy by providing quantitative measurement and quality assurance (QA) of the surgical product.
The known-component registration (KC-Reg) algorithm uses robust 3D-2D registration combined with 3D component models of surgical devices known to be present in intraoperative 2D radiographs. Component models were investigated that vary in fidelity from simple parametric models (e.g., approximation of a screw as a simple cylinder, referred to as “parametrically-known” component [pKC] registration) to precise models based on device-specific CAD drawings (referred to as “exactly-known” component [eKC] registration). 3D-2D registration from three intraoperative radiographs was solved using the covariance matrix adaptation evolution strategy (CMA-ES) to maximize image-gradient similarity, relating device placement relative to 3D preoperative CT of the patient. Spine phantom and cadaver studies were conducted to evaluate registration accuracy and demonstrate QA of the surgical product by verification of the type of devices delivered and conformance within the “acceptance window” of the spinal pedicle.
Pedicle screws were successfully registered to radiographs acquired from a mobile C-arm, providing TRE 1–4 mm and <5° using simple parametric (pKC) models, further improved to <1 mm and <1° using eKC registration. Using advanced pKC models, screws that did not match the device models specified in the surgical plan were detected with an accuracy of >99%. Visualization of registered devices relative to surgical planning and the pedicle acceptance window provided potentially valuable QA of the surgical product and reliable detection of pedicle screw breach.
3D-2D registration combined with 3D models of known surgical devices offers a novel method for intraoperative QA. The method provides a near-real-time independent check against pedicle breach, facilitating revision within the same procedure if necessary and providing more rigorous verification of the surgical product.
3D-2D image registration; image-guided surgery; x-ray fluoroscopy; quality assurance; spine surgery
We demonstrate that a dual-layer, dual-color scintillator construct for microscopic CT, originally proposed to increase sensitivity in synchrotron imaging, can also be used to perform material quantification and classification when coupled with polychromatic illumination. We consider two different approaches to data handling: (1) a data-domain material decomposition whose estimation performance can be characterized by the Cramer-Rao Lower Bound formalism but which requires careful calibration and (2) an image-domain material classification approach that is more robust to calibration errors. The data-domain analysis indicates that useful levels of SNR (>5) could be achieved in one second or less at typical bending magnet fluxes for relatively large amounts of contrast (several mm path length, such as in a fluid flow experiment) and at typical undulator fluxes for small amount of contrast (tens of microns path length, such as an angiography experiment). The tools introduced could of course be used to study and optimize parameters for a wider range of potential applications. The image domain approach was analyzed in terms of its ability to distinguish different elemental stains by characterizing the angle between the lines traced out in a two-dimensional space of effective attenuation coefficient in the front and back layer images. This approach was implemented at a synchrotron and the results were consistent with simulation predictions.
Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling.
Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm × 25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise.
Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8 × higher CNR (at matched spatial resolution) compared to the constant penalty.
The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.
sparse sampling; iterative image reconstruction; discontinuous detectors; photon counting CT
Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014
44 460–7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice.
The study included 60 adult patients (age range: 18–70 years, weight range: 60–180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients (hOrgan) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate (CTDIvol)organ, convolution values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying (CTDIvol)organ, convolution with the organ dose coefficients (hOrgan). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The discrepancy between the estimated organ dose and dose simulated using TCM Monte Carlo program was quantified. We further compared the convolution-based organ dose estimation method with two other strategies with different approaches of quantifying the irradiation field.
The proposed convolution-based estimation method showed good accuracy with the organ dose simulated using the TCM Monte Carlo simulation. The average percentage error (normalized by CTDIvol) was generally within 10% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions.
This study developed an improved method that accurately quantifies the irradiation field under TCM scans. The results suggested that organ dose could be estimated in real-time both prospectively (with the localizer information only) and retrospectively (with acquired CT data).
CT; computed tomography; Monte Carlo; organ dose; tube current modulation; patient specific
We are developing a computerized system for bladder segmentation on CT urography (CTU), as a critical component for computer-aided detection of bladder cancer.
The presence of regions filled with intravenous contrast and without contrast presents a challenge for bladder segmentation. Previously, we proposed a Conjoint Level set Analysis and Segmentation System (CLASS). In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast-filled (C) region separately and automatically conjoins the NC and C region contours; however, inaccuracies in the NC and C region contours may cause the conjoint contour to exclude portions of the bladder. To alleviate this problem, we implemented a local contour refinement (LCR) method that exploits model-guided refinement (MGR) and energy-driven wavefront propagation (EDWP). MGR propagates the C region contours if the level set propagation in the C region stops prematurely due to substantial non-uniformity of the contrast. EDWP with regularized energies further propagates the conjoint contours to the correct bladder boundary. EDWP uses changes in energies, smoothness criteria of the contour, and previous slice contour to determine when to stop the propagation, following decision rules derived from training. A data set of 173 cases was collected for this study: 81 cases in the training set (42 lesions, 21 wall thickenings, 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, 13 normal bladders). For all cases, 3D hand segmented contours were obtained as reference standard and used for the evaluation of the computerized segmentation accuracy.
For CLASS with LCR, the average volume intersection ratio, average volume error, absolute average volume error, average minimum distance and Jaccard index were 84.2±11.4%, 8.2±17.4%, 13.0±14.1%, 3.5±1.9 mm, 78.8±11.6%, respectively, for the training set and 78.0±14.7%, 16.4±16.9%, 18.2±15.0%, 3.8±2.3 mm, 73.8±13.4% respectively, for the test set. With CLASS only, the corresponding values were 75.1±13.2%, 18.7±19.5%, 22.5±14.9%, 4.3±2.2 mm, 71.0±12.6%, respectively, for the training set and 67.3±14.3%, 29.3±15.9%, 29.4±15.6%, 4.9±2.6 mm, 65.0±13.3%, respectively, for the test set. The differences between the two methods for all five measures were statistically significant (p<0.001) for both the training and test sets.
The results demonstrate the potential of CLASS with LCR for segmentation of the bladder.
Acoustic attenuation represents the energy loss of the propagating wave through biological tissues and plays a significant role in both therapeutic and diagnostic ultrasound applications. Estimation of acoustic attenuation remains challenging but critical for tissue characterization. In this study, an attenuation estimation approach was developed using the radiation-force-based method of Harmonic Motion Imaging (HMI). 2D tissue displacement maps were acquired by moving the transducer in a raster-scan format. A linear regression model was applied on the logarithm of the HMI displacements at different depths in order to estimate the acoustic attenuation. Commercially available phantoms with known attenuations (n=5) and in vitro canine livers (n=3) were tested, as well as HIFU lesions in in vitro canine livers (n=5). Results demonstrated that attenuations obtained from the phantoms showed a good correlation (R2=0.976) with the independently obtained values reported by the manufacturer with an estimation error (compared to the values independently measured) varying within the range of 15-35%. The estimated attenuation in the in vitro canine livers was equal to 0.32±0.03 dB/cm/MHz, which is in good agreement with the existing literature. The attenuation in HIFU lesions was found to be higher (0.58±0.06 dB/cm/MHz) than that in normal tissues, also in agreement with the results from previous publications. Future potential applications of the proposed method include estimation of attenuation in pathological tissues before and after thermal ablation.
acoustic radiation force imaging; acoustic attenuation; linear regression; cross correlation; phantom; Harmonic Motion Imaging (HMI); HIFU lesions; in vitro canine liver
Chirp- and random-based coded excitation methods have been proposed to reduce standing wave formation and improve focusing of transcranial ultrasound. However, no clear evidence has been shown to support the benefits of these ultrasonic excitation sequences in vivo. This study evaluates the chirp and periodic selection of random frequency (PSRF) coded-excitation methods for opening the blood-brain barrier (BBB) in mice. Three groups of mice (n=15) were injected with polydisperse microbubbles and sonicated in the caudate putamen using the chirp/PSRF coded (bandwidth: 1.5-1.9 MHz, peak negative pressure: 0.52 MPa, duration: 30 s) or standard ultrasound (frequency: 1.5 MHz, pressure: 0.52 MPa, burst duration: 20 ms, duration: 5 min) sequences. T1-weighted contrast-enhanced MRI scans were performed to quantitatively analyze focused ultrasound induced BBB opening. The mean opening volumes evaluated from the MRI were 9.38±5.71 mm3, 8.91±3.91 mm3 and 35.47 ± 5.10 mm3 for the chirp, random and regular sonications, respectively. The mean cavitation levels were 55.40±28.43 V.s, 63.87±29.97 V.s and 356.52±257.15 V.s for the chirp, random and regular sonications, respectively. The chirp and PSRF coded pulsing sequences improved the BBB opening localization by inducing lower cavitation levels and smaller opening volumes compared to results of the regular sonication technique. Larger bandwidths were associated with more focused targeting but were limited by the frequency response of the transducer, the skull attenuation and the microbubbles optimal frequency range. The coded methods could therefore facilitate highly localized drug delivery as well as benefit other transcranial ultrasound techniques that use higher pressure levels and higher precision to induce the necessary bioeffects in a brain region while avoiding damage to the surrounding healthy tissue.
blood-brain barrier opening; chirp; coded ultrasonic excitation; focused ultrasound; standing wave; transcranial ultrasound
Computational finite element models are commonly used for the simulation of radiofrequency ablation (RFA) treatments. However, the accuracy of these simulations is limited by the lack of precise knowledge of tissue parameters. In this technical note, an inverse solver based on the unscented Kalman filter (UKF) is proposed to optimize values for specific heat, thermal conductivity, and electrical conductivity resulting in accurately simulated temperature elevations. A total of 15 RFA treatments were performed on ex vivo bovine liver tissue. For each RFA treatment, 15 finite-element simulations were performed using a set of deterministically chosen tissue parameters to estimate the mean and variance of the resulting tissue ablation. The UKF was implemented as an inverse solver to recover the specific heat, thermal conductivity, and electrical conductivity corresponding to the measured area of the ablated tissue region, as determined from gross tissue histology. These tissue parameters were then employed in the finite element model to simulate the position- and time-dependent tissue temperature. Results show good agreement between simulated and measured temperature.
Radiofrequency ablation; Temperature simulation; Finite element analysis; Unscented Kalman filter; Inverse problem
The purpose of this study is to evaluate the efficacy of the enhancement of docetaxel by pulsed focused ultrasound (pFUS) in combination with radiotherapy (RT) for treatment of prostate cancer in vivo. LNCaP cells were grown in the prostates of male nude mice. When the tumors reached a designated volume by MRI, tumor bearing mice were randomly divided into 7 groups (n=5): (1) pFUS alone; (2) RT alone; (3) docetaxel alone; (4) docetaxel + pFUS; (5) docetaxel + RT; (6) docetaxel + pFUS + RT; and (7) control. MR guided pFUS treatment was performed using a focused ultrasound treatment system (InSightec ExAblate 2000) with a 1.5T GE MR scanner. Animals were treated once with pFUS, docetaxel, RT or their combinations. Docetaxel was given by i.v. injection at 5 mg/kg before pFUS. RT was given 2 Gy after pFUS. Animals were euthanized 4 weeks after treatment. Tumor volumes were measured on MRI at 1 and 4 weeks post-treatment. Results showed that triple combination therapies of docetaxel, pFUS and RT provided the most significant tumor growth inhibition among all groups, which may have a potential for the treatment of prostate cancer due to an improved therapeutic ratio.
MRgFUS; docetaxel; RT; prostate cancer; in vivo
An atlas-based IMRT planning technique for prostate cancer was developed and evaluated. A multi-dose atlas was built based on the anatomy patterns of the patients, more specifically, the Percent Distance to the Prostate (PDP) and the concaveness angle formed by the seminal vesicles relative to the anterior-posterior axis. The 70-case dataset was classified using a k-medoids clustering analysis to recognize anatomy pattern variations in the dataset. The best classification, defined by the number of classes or medoids, was determined by the largest value of the average silhouette width. Reference plans from each class formed a multi-dose atlas. The atlas-guided planning (AGP) technique started with matching the new case anatomy pattern to one of the reference cases in the atlas; then a deformable registration between the atlas and new case anatomies transferred the dose from the atlas to the new case to guide inverse planning with full automation. Additional 20 clinical cases were re-planned to evaluate the AGP technique. Dosimetric properties between AGP and clinical plans were evaluated. The classification analysis determined that the 5-case atlas would best represent anatomy patterns for the patient cohort. AGP took approximately 1 min on average (corresponding to 70 iterations of optimization) for all cases. When dosimetric parameters were compared, the differences between AGP and clinical plans were less than 3.5%, albeit some statistical significances observed: Homogeneity index (p > 0.05), conformity index (p < 0.01), bladder gEUD (p < 0.01), and rectum gEUD (p = 0.02). Atlas-guided treatment planning is feasible and efficient. Atlas predicted dose can effectively guide the optimizer to achieve plan quality comparable to that of clinical plans.
pattern recognition; atlas; prostate cancer; IMRT
To develop tables of normalized glandular dose coefficients DgN for a range of anode–filter combinations and tube voltages used in contemporary breast imaging systems.
Previously published mono-energetic DgN values were used with various spectra to mathematically compute DgN coefficients. The tungsten anode spectra from TASMICS were used; Molybdenum and Rhodium anode-spectra were generated using MCNPx Monte Carlo code. The spectra were filtered with various thicknesses of Al, Rh, Mo or Cu. An initial HVL calculation was made using the anode and filter material. A range of the HVL values was produced with the addition of small thicknesses of polymethyl methacrylate (PMMA) as a surrogate for the breast compression paddle, to produce a range of HVL values at each tube voltage. Using a spectral weighting method, DgN coefficients for the generated spectra were calculated for breast glandular densities of 0%, 12.5%, 25%, 37.5%, 50% and 100% for a range of compressed breast thicknesses from 3 to 8 cm.
Eleven tables of normalized glandular dose (DgN) coefficients were produced for the following anode/filter combinations: W + 50 μm Ag, W + 500 μm Al, W + 700 μm Al, W + 200 μm Cu, W + 300 μm Cu, W + 50 μm Rh, Mo + 400 μm Cu, Mo + 30 μm Mo, Mo + 25 μm Rh, Rh + 400 μm Cu and Rh + 25 μm Rh. Where possible, these results were compared to previously published DgN values and were found to be on average less than 2% different than previously reported values.
Over 200-pages of DgN coefficients were computed for modeled x-ray system spectra that are used in a number of new breast imaging applications. The reported values were found to be in excellent agreement when compared to published values.