Table of contents

The classic imaging geometry for computed tomography is for the collection of un-truncated projections and the reconstruction of a global image, with the Fourier transform as the theoretical foundation that is intrinsically non-local. Recently, interior tomography research has led to theoretically exact relationships between localities in the projection and image spaces and practically promising reconstruction algorithms. Initially, interior tomography was developed for x-ray computed tomography. Then, it was elevated to have the status of a general imaging principle. Finally, a novel framework known as 'omni-tomography' is being developed for a grand fusion of multiple imaging modalities, allowing tomographic synchrony of diversified features.

Murine models are used extensively in biological and translational research. For many of these studies it is necessary to access the vasculature for the injection of biologically active agents. Among the possible methods for accessing the mouse vasculature, tail vein injections are a routine but critical step for many experimental protocols. To perform successful tail vein injections, a high skill set and experience is required, leaving most scientists ill-suited to perform this task. This can lead to a high variability between injections, which can impact experimental results. To allow more scientists to perform tail vein injections and to decrease the variability between injections, a vascular access system (VAS) that semi-automatically inserts a needle into the tail vein of a mouse was developed. The VAS uses near infrared light, image processing techniques, computer controlled motors, and a pressure feedback system to insert the needle and to validate its proper placement within the vein. The VAS was tested by injecting a commonly used radiolabeled probe (FDG) into the tail veins of five mice. These mice were then imaged using micro-positron emission tomography to measure the percentage of the injected probe remaining in the tail. These studies showed that, on average, the VAS leaves 3.4% of the injected probe in the tail. With these preliminary results, the VAS system demonstrates the potential for improving the accuracy of tail vein injections in mice.

Based on experiments and numerical simulations, a study is carried out pertaining to the conversion of dose-to-graphite to dose-to-water in a carbon ion beam. This conversion is needed to establish graphite calorimeters as primary standards of absorbed dose in these beams. It is governed by the water-to-graphite mass collision stopping power ratio and fluence correction factors, which depend on the particle fluence distributions in each of the two media. The paper focuses on the experimental and numerical determination of this fluence correction factor for an 80 MeV/A carbon ion beam. Measurements have been performed in the nuclear physics laboratory INFN-LNS in Catania (Sicily, Italy). The numerical simulations have been made with a Geant4 Monte Carlo code through the GATE simulation platform. The experimental data are in good agreement with the simulated results for the fluence correction factors and are found to be close to unity. The experimental values increase with depth reaching 1.010 before the Bragg peak region. They have been determined with an uncertainty of 0.25%. Different numerical results are obtained depending on the level of approximation made in calculating the fluence correction factors. When considering carbon ions only, the difference between measured and calculated values is maximal just before the Bragg peak, but its value is less than 1.005. The numerical value is close to unity at the surface and increases to 1.005 near the Bragg peak. When the fluence of all charged particles is considered, the fluence correction factors are lower than unity at the surface and increase with depth up to 1.025 before the Bragg peak. Besides carbon ions, secondary particles created due to nuclear interactions have to be included in the analysis: boron ions (¹⁰B and ¹¹B), beryllium ions (⁷Be), alpha particles and protons. At the conclusion of this work, we have the conversion of dose-to-graphite to dose-to-water to apply to the response of a graphite calorimeter in an 80 MeV/A carbon ion beam. This conversion consists of the product of two contributions: the water-to-graphite electronic mass collision stopping power ratio, which is equal to 1.115, and the fluence correction factor which varies linearly with depth, as k_{fl, all} = 0.9995 + 0.0048 z_w-eq. The latter has been determined on the basis of experiments and numerical simulations.

The basic idea of Voxel2MCNP is to provide a framework supporting users in modeling radiation transport scenarios using voxel phantoms and other geometric models, generating corresponding input for the Monte Carlo code MCNPX, and evaluating simulation output. Applications at Karlsruhe Institute of Technology are primarily whole and partial body counter calibration and calculation of dose conversion coefficients. A new generic data model describing data related to radiation transport, including phantom and detector geometries and their properties, sources, tallies and materials, has been developed. It is modular and generally independent of the targeted Monte Carlo code. The data model has been implemented as an XML-based file format to facilitate data exchange, and integrated with Voxel2MCNP to provide a common interface for modeling, visualization, and evaluation of data. Also, extensions to allow compatibility with several file formats, such as ENSDF for nuclear structure properties and radioactive decay data, SimpleGeo for solid geometry modeling, ImageJ for voxel lattices, and MCNPX's MCTAL for simulation results have been added. The framework is presented and discussed in this paper and example workflows for body counter calibration and calculation of dose conversion coefficients is given to illustrate its application.

This paper introduces the concept of analytical probabilistic modeling (APM) to quantify uncertainties in quality indicators of radiation therapy treatment plans. Assuming Gaussian probability densities over the input parameters of the treatment plan quality indicators, APM enables the calculation of the moments of the induced probability density over the treatment plan quality indicators by analytical integration. This paper focuses on analytical probabilistic dose calculation algorithms and the implications of APM regarding treatment planning. We derive closed-form expressions for the expectation value and the (co)variance of (1) intensity-modulated photon and proton dose distributions based on a pencil beam algorithm and (2) the standard quadratic objective function used in inverse planning. Complex correlation models of high dimensional uncertain input parameters and the different nature of random and systematic uncertainties in fractionated radiation therapy are explicitly incorporated into APM. APM variance calculations on phantom data sets show that the correlation assumptions and the difference of random and systematic uncertainties of the input parameters have a crucial impact on the uncertainty of the resulting dose. The derivations regarding the quadratic objective function show that APM has the potential to enable robust planning at almost the same computational cost like conventional inverse planning after a single probabilistic dose calculation. Beneficial applications of APM in the context of radiation therapy treatment planning are feasible.

Differential phase-contrast computed tomography (DPC-CT) reconstruction problems are usually solved by using parallel-, fan- or cone-beam algorithms. For rod-shaped objects, the x-ray beams cannot recover all the slices of the sample at the same time. Thus, if a rod-shaped sample is required to be reconstructed by the above algorithms, one should alternately perform translation and rotation on this sample, which leads to lower efficiency. The helical cone-beam CT may significantly improve scanning efficiency for rod-shaped objects over other algorithms. In this paper, we propose a theoretically exact filter-backprojection algorithm for helical cone-beam DPC-CT, which can be applied to reconstruct the refractive index decrement distribution of the samples directly from two-dimensional differential phase-contrast images. Numerical simulations are conducted to verify the proposed algorithm. Our work provides a potential solution for inspecting the rod-shaped samples using DPC-CT, which may be applicable with the evolution of DPC-CT equipments.

This work aims to contribute to the study of the radiation dose distribution delivered to the hands of medical staff members during a general computed tomographic (CT) fluoroscopic guided procedure. In this study, both Monte Carlo simulations and measurements were performed. For free-in-air and computed tomography dose index (CTDI) body phantom measurements, a standard pencil ionization chamber (IC) 100 mm long was used. The CT scanner model was implemented using MCNPX (Monte Carlo N-Particle eXtended) and was successfully validated by comparing the simulated results with measurements. Subsequently, CT images of a hand, together with an anthropomorphic phantom, were voxelized and used with the MCNPX code for dose calculations. The hand dose distribution study was performed both by using thermo-luminescent detector measurements and Monte Carlo simulations. The validated simulation tool provides a new perspective for detailed investigations of CT-irradiation scenarios. Simulations show that there is a strong dose gradient, namely the even zones of the hand that are in precise vicinity to the x-ray beam only receive about 4% of the maximum dose delivered to adjacent areas which are directly exposed to the primary x-ray beam. Finally, the scatter contribution of the patient was also studied through MC simulations. The results show that for directly exposed parts of the hand surface, the dose is reduced by the body of the patient (due to the shielding), whereas the dose is increased by scattered radiation from the patient for parts of the skin that receive scattered radiation only.

Internal dosimetry of alpha particles is gaining attention due to the increasing applications in cancer treatment and also for the assessment of environmental contamination from radionuclides. We developed a Monte Carlo simulation in GEANT4 in order to calculate the absorbed fractions for monoenergetic alpha particles in the energy interval between 0.1 and 10 MeV, uniformly distributed in ellipsoids made of soft tissue. For each volume, we simulated a spherical shape, three oblate and three prolate ellipsoids, and one scalene shape. For each energy and for every geometrical configuration, an analytical relationship between the absorbed fraction and a 'generalized radius' was found; and the dependence of the fit parameters on the alpha energy is discussed and fitted by parametric functions. With the proposed formulation, the absorbed fraction for alpha particles in the energy range explored can be calculated for volumes and for ellipsoidal shapes of practical interest. This method can be applied to the evaluation of absorbed fraction from alpha-emitting radionuclides. The contribution to the deposited energy coming from electron and photon emissions can be accounted for exploiting the specific formulations previously introduced. As an example of application, the dosimetry of ²¹³Bi and its decay chain in ellipsoids is reported.

The feasibility of utilizing an electronic portal imaging device (EPID) for the quality assurance of electron beams was investigated. This work was conducted on a Varian 2100iX machine equipped with an amorphous silicon (aS1000) portal imager. The linearity of the imager pixel response as a function of exposed dose was first confirmed. The short-term reproducibility of the EPID response to electron beams was verified. Low (6 MeV), medium (12 MeV) and high (20 MeV) energies were tested, each along with small (6 × 6 cm²), medium (10 × 10 cm²) and large (20 × 20 cm²) applicators. Acquired EPID images were analyzed using an in-house MATLAB code for radiation field size, penumbra, symmetry and flatness. Field sizes and penumbra values agreed with those from film dosimetry to within 1 mm. Field symmetry and flatness constancies were measured over a period of three weeks. The results indicate that EPID can be used for routine quality assurance of electron beams.

Čerenkov emission is generated from ionizing radiation in tissue above 264 keV energy. This study presents the first examination of this optical emission as a surrogate for the absorbed superficial dose. Čerenkov emission was imaged from the surface of flat tissue phantoms irradiated with electrons, using a range of field sizes from 6 cm × 6 cm to 20 cm × 20 cm, incident angles from 0° to 50°, and energies from 6 to 18 MeV. The Čerenkov images were compared with the estimated superficial dose in phantoms from direct diode measurements, as well as calculations by Monte Carlo and the treatment planning system. Intensity images showed outstanding linear agreement (R² = 0.97) with reference data of the known dose for energies from 6 to 18 MeV. When orthogonal delivery was carried out, the in-plane and cross-plane dose distribution comparisons indicated very little difference (±2–4% differences) between the different methods of estimation as compared to Čerenkov light imaging. For an incident angle 50°, the Čerenkov images and Monte Carlo simulation show excellent agreement with the diode data, but the treatment planning system had a larger error (OPT = ±1∼2%, diode = ±2∼3%, TPS = ±6–8% differences) as would be expected. The sampling depth of superficial dosimetry based on Čerenkov radiation has been simulated in a layered skin model, showing the potential of sampling depth tuning by spectral filtering. Taken together, these measurements and simulations indicate that Čerenkov emission imaging might provide a valuable method of superficial dosimetry imaging from incident radiotherapy beams of electrons.

AX-PET is a novel PET detector based on axially oriented crystals and orthogonal wavelength shifter (WLS) strips, both individually read out by silicon photo-multipliers. Its design decouples sensitivity and spatial resolution, by reducing the parallax error due to the layered arrangement of the crystals. Additionally the granularity of AX-PET enhances the capability to track photons within the detector yielding a large fraction of inter-crystal scatter events. These events, if properly processed, can be included in the reconstruction stage further increasing the sensitivity. Its unique features require dedicated Monte-Carlo simulations, enabling the development of the device, interpreting data and allowing the development of reconstruction codes. At the same time the non-conventional design of AX-PET poses several challenges to the simulation and modeling tasks, mostly related to the light transport and distribution within the crystals and WLS strips, as well as the electronics readout. In this work we present a hybrid simulation tool based on an analytical model and a Monte-Carlo based description of the AX-PET demonstrator. It was extensively validated against experimental data, providing excellent agreement.

This study develops a new class of gellan gum-based tissue-mimicking phantom material and a model to predict and control the elastic modulus, thermal conductivity, and electrical conductivity by adjusting the mass fractions of gellan gum, propylene glycol, and sodium chloride, respectively. One of the advantages of gellan gum is its gelling efficiency allowing highly regulable mechanical properties (elastic modulus, toughness, etc). An experiment was performed on 16 gellan gum-based tissue-mimicking phantoms and a regression model was fit to quantitatively predict three material properties (elastic modulus, thermal conductivity, and electrical conductivity) based on the phantom material's composition. Based on these material properties and the regression model developed, tissue-mimicking phantoms of porcine spinal cord and liver were formulated. These gellan gum tissue-mimicking phantoms have the mechanical, thermal, and electrical properties approximately equivalent to those of the spinal cord and the liver.

Treatment plans for patched-field proton therapy may not be clinically acceptable due to the dose heterogeneity introduced in the target when combining the dose distributions from two separate fields. MCNPX simulations were performed for various configurations of the Mevion S250 beamline to determine spread-out Bragg peak dose distributions and patched-field treatment plans delivered using a rotating modulator wheel to depths in the clinically relevant range between 5.0 and 30.0 cm. The dose non-uniformity (DNU) metric was defined as the difference between the maximum and minimum dose relative to the prescription observed in a patched dose distribution. The DNU was first evaluated for dose distributions from a standard delivery using constant beam current and combining through-field lateral dose profiles and with patch-field distal dose profiles. Patch-field distal dose profiles were then optimized using beam current modulation in an attempt to better complement the through-field lateral dose profiles when combined into a patched dose distribution. Using standard deliveries, DNU was 10% or less only when patching lateral profiles 12.5–17.5 cm deep. Significantly greater DNU was observed for patches outside of this range, at times exceeding 35%. Using optimized distal profiles, DNU was reduced to 10% or less for all lateral profiles deeper than 15.0 cm. Optimizing beam current modulation was found to create distal profiles with more gradual dose falloff than found in a standard delivery, allowing optimized distal dose distributions to sum more homogeneously with lateral dose distributions. The hot or cold spots that often appear in patched dose distributions from standard deliveries may therefore be mitigated by optimizing beam current. This method may also be applied to systems other than the Mevion system to further improve patched-field dose homogeneity.

The purpose of this study was to investigate in vivo verification of radiation treatment with high energy photon beams using PET/CT to image the induced positron activity. The measurements of the positron activation induced in a preoperative rectal cancer patient and a prostate cancer patient following 50 MV photon treatments are presented. A total dose of 5 and 8 Gy, respectively, were delivered to the tumors. Imaging was performed with a 64-slice PET/CT scanner for 30 min, starting 7 min after the end of the treatment. The CT volume from the PET/CT and the treatment planning CT were coregistered by matching anatomical reference points in the patient. The treatment delivery was imaged in vivo based on the distribution of the induced positron emitters produced by photonuclear reactions in tissue mapped on to the associated dose distribution of the treatment plan. The results showed that spatial distribution of induced activity in both patients agreed well with the delivered beam portals of the treatment plans in the entrance subcutaneous fat regions but less so in blood and oxygen rich soft tissues. For the preoperative rectal cancer patient however, a 2 ± (0.5) cm misalignment was observed in the cranial-caudal direction of the patient between the induced activity distribution and treatment plan, indicating a beam patient setup error. No misalignment of this kind was seen in the prostate cancer patient. However, due to a fast patient setup error in the PET/CT scanner a slight mis-position of the patient in the PET/CT was observed in all three planes, resulting in a deformed activity distribution compared to the treatment plan. The present study indicates that the induced positron emitters by high energy photon beams can be measured quite accurately using PET imaging of subcutaneous fat to allow portal verification of the delivered treatment beams. Measurement of the induced activity in the patient 7 min after receiving 5 Gy involved count rates which were about 20 times lower than that of a patient undergoing standard ¹⁸F-FDG treatment. When using a combination of short lived nuclides such as ¹⁵O (half-life: 2 min) and ¹¹C (half-life: 20 min) with low activity it is not optimal to use clinical reconstruction protocols. Thus, it might be desirable to further optimize reconstruction parameters as well as to address hardware improvements in realizing in vivo treatment verification with PET/CT in the future. A significant improvement with regard to ¹⁵O imaging could also be expected by having the PET/CT unit located close to the radiation treatment room.

Model-based optoacoustic inversion methods are capable of eliminating image artefacts associated with the widely adopted back-projection reconstruction algorithms. Yet, significant image artefacts might also occur due to reflections and scattering of optoacoustically-induced waves from strongly acoustically-mismatched areas in tissues. Herein, we modify the model-based reconstruction methodology to incorporate statistically-based weighting in order to minimize these artefacts. The method is compared with another weighting procedure termed half-image reconstruction, yielding generally better results. The statistically-based weighting is subsequently verified experimentally, attaining quality improvement of the optoacoustic image reconstructions in the presence of acoustic mismatches in tissue phantoms and small animals ex-vivo.

Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion correction.

Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MCS engine given the large variety of physics processes available for targeting different medical imaging and radiotherapy applications. In addition, Geant4 is the MCS engine behind GATE which is actually the most popular medical applications' simulation platform. We propose the definition of a global strategy and associated structures for such a GPU based simulation implementation. Different photon and electron physics effects are resolved on the fly directly on GPU without any approximations with respect to Geant4. Validations have shown equivalence in the underlying photon and electron physics processes between the Geant4 and the GPU codes with a speedup factor of 80–90. More clinically realistic simulations in emission and transmission imaging led to acceleration factors of 400–800 respectively compared to corresponding GATE simulations.

A new method of generating realistic three dimensional simulated breast lesions known as diffusion limited aggregation (DLA) is presented, and compared with the random walk (RW) method. Both methods of lesion simulation utilize a physics-based method for inserting these simulated lesions into 2D clinical mammogram images that takes into account the polychromatic x-ray spectrum, local glandularity and scatter. DLA and RW masses were assessed for realism via a receiver operating characteristic (ROC) study with nine observers. The study comprised 150 images of which 50 were real pathology proven mammograms, 50 were normal mammograms with RW inserted masses and 50 were normal mammograms with DLA inserted masses. The average area under the ROC curve for the DLA method was 0.55 (95% confidence interval 0.51–0.59) compared to 0.60 (95% confidence interval 0.56–0.63) for the RW method. The observer study results suggest that the DLA method produced more realistic masses with more variability in shape compared to the RW method. DLA generated lesions can overcome the lack of complexity in structure and shape in many current methods of mass simulation.

A sparsity-exploiting algorithm intended for few-view single photon emission computed tomography (SPECT) reconstruction is proposed and characterized. The algorithm models the object as piecewise constant subject to a blurring operation. To validate that the algorithm closely approximates the true object in the noiseless case, projection data were generated from an object assuming this model and using the system matrix. Monte Carlo simulations were performed to provide more realistic data of a phantom with varying smoothness across the field of view and a cardiac phantom. Reconstructions were performed across a sweep of two primary design parameters. The results demonstrate that the algorithm recovers the object in a noiseless simulation case. While the algorithm assumes a specific blurring model, the results suggest that the algorithm may provide high reconstruction accuracy even when the object does not match the assumed blurring model. Generally, increased values of the blurring parameter and total variation weighting parameters reduced streaking artifacts, while decreasing spatial resolution. The proposed algorithm demonstrated higher correlation with respect to the true phantom compared to maximum-likelihood expectation maximization (MLEM) reconstructions. Images reconstructed with the proposed algorithm demonstrated reduced streaking artifacts when reconstructing from few views compared to MLEM. The proposed algorithm introduced patchy artifacts in some reconstructed images, depending on the noise level and the selected algorithm parameters. Overall, the results demonstrate preliminary feasibility of a sparsity-exploiting reconstruction algorithm which may be beneficial for few-view SPECT.

A motorized electron multileaf collimator (eMLC) was developed as an add-on device to the Varian linac for delivery of advanced electron beam therapy. It has previously been shown that electron beams collimated by an eMLC have very similar penumbra to those collimated by applicators and cutouts. Thus, manufacturing patient specific cutouts would no longer be necessary, resulting in the reduction of time taken in the cutout fabrication process. Moreover, cutout construction involves handling of toxic materials and exposure to toxic fumes that are usually generated during the process, while the eMLC will be a pollution-free device. However, undulation of the isodose lines is expected due to the finite size of the eMLC. Hence, the provided planned target volume (PTV) shape will not exactly follow the beam's-eye-view of the PTV, but instead will make a stepped approximation to the PTV shape. This may be a problem when the field edge is close to a critical structure. Therefore, in this study the capability of the eMLC to achieve the same clinical outcome as an applicator/cutout combination was investigated based on real patient computed tomographies (CTs). An in-house Monte Carlo based treatment planning system was used for dose calculation using ten patient CTs. For each patient, two plans were generated; one with electron beams collimated using the applicator/cutout combination; and the other plan with beams collimated by the eMLC. Treatment plan quality was compared for each patient based on dose distribution and dose–volume histogram. In order to determine the optimal position of the leaves, the impact of the different leaf positioning strategies was investigated. All plans with both eMLC and cutouts were generated such that 100% of the target volume receives at least 90% of the prescribed dose. Then the percentage difference in dose between both delivery techniques was calculated for all the cases. The difference in the dose received by 10% of the volume of the target was showing a mean percentage difference of 1.57%±1.65, while the difference in the dose received by 99% of the volume was showing a mean percentage difference of 1.08%±0.78. The mean percentage volume of Lung receiving a percentage dose equal to or greater than 20% of the prescribed dose was found to be 8.55%±7.3 and 8.67%±7 for the eMLC and applicator/cutout combination delivery methods respectively. Results have shown that target coverage and critical structure sparing can be effectively achieved by electron beams collimated with the eMLC. Positioning the eMLC leaves in such a way to avoids shielding any part of the projected treatment volume is most conservative and would be the recommended method to define the actual leaf position for the eMLC defined field. More optimal leaf positions can be achieved in shaping the same treatment field through the interplay of different leaf positioning strategies. We concluded that the eMLC represents an effective time saving and pollution-free device that can completely replace patient specific cutouts.

A number of B₁ mapping methods have been introduced. A model to facilitate choice among these methods is valuable, as the performance of each technique is affected by a variety of factors, including acquisition signal-to-noise ratio (SNR). The Bloch–Siegert shift B₁ mapping method has recently garnered significant interest. In this paper, we present a statistical model suitable for analysis of the Bloch–Siegert shift method. Unlike previously presented models, the analysis is valid in both low SNR and high SNR regimes. We present a detailed analysis of the performance of the Bloch–Siegert shift B₁ mapping method across a broad range of acquisition scenarios, and compare it to two other B₁ mapping techniques (the dual angle method and the phase sensitive method). Further validation of the model is presented through both Monte Carlo simulations and experimental results. The simulations and experimental results match the model well, lending confidence to its accuracy. Each technique is found to perform well with high acquisition SNR. However, our results suggest that the dual angle method is not reliable in low SNR environments. Furthermore, the phase sensitive method appears to outperform the Bloch–Siegert shift method in these low-SNR cases, although variations of the Bloch–Siegert method may be possible that improve its performance at low SNR.

Due to the higher LET of kilovoltage (kV) radiation, there is potential for an increase in relative biological effectiveness (RBE) of absorbed doses of radiation from kV cone beam computed tomography (CBCT) sources in reference to megavoltage or Co-60 doses. This work develops a method for accurately coupling a Monte Carlo (MC) radiation transport code (PENELOPE) with the damage simulation (MCDS) to predict relative numbers of DNA double strand breaks (DSBs). The MCDS accounts for slowing down of electrons and delta ray production within the cell nucleus; however, determining the spectrum of electrons incident on the cell nucleus from photons interacting in a larger region of tissue is not trivial. PENELOPE simulations were conducted with a novel tally algorithm invoked where electrons incident on a detection material were tracked and both the incident energy and the final deposited dose were recorded. The DSB yield predicted by a set of MCDS runs of monoenergetic electrons was then looked up in a table and weighted by the specific energy of the incident electron. Our results indicate that the RBE for DSB induction is 1.1 for diagnostic x-rays with energies from 80 to 125 kVp. We found no significant change in RBE with depth or filtration. The predicted absolute DSB yields are about three times lower for cells irradiated under anoxic conditions than the yield in cells irradiated under normoxic (5%) or fully aerobic (100%) conditions. However, oxygen concentration has a negligible (±0.02) effect on the RBE of kV CBCT x-rays.

Laser interstitial thermotherapy (LITT) is employed to destroy tumors in organs, and its outcome strongly depends on the temperature distribution inside the treated tissue. The recent introduction of computed tomography (CT) scan thermometry, based on the CT number dependence of the tissue with temperature, overcomes the invasiveness of other techniques used to monitor temperature during LITT. The averaged CT number (ROI = 0.02 cm²) of an ex vivo swine pancreas is monitored during LITT (Nd:YAG laser power of 3 W, treatment time: 120 s) at different distances from the applicator (from 4 to 30 mm). The averaged CT number shows a clear decrease during treatment: it is highest at 4 mm from the applicator (mean variation in the whole treatment of −0.256 HU s⁻¹) and negligible at 30 mm, since the highest temperature increase is present close to the applicator (i.e., 45 °C at 4 mm and 25 °C at 6 mm). To obtain the relationship between CT numbers and pancreas temperature, the reference temperature was measured by 12 fiber Bragg grating sensors. The CT number decreases as a function of temperature, showing a nonlinear trend with a mean thermal sensitivity of −0.50 HU °C⁻¹. Results here reported are the first assessment of pancreatic CT number dependence on temperature, at the best of our knowledge. Findings can be useful to further investigate CT scan thermometry during LITT on the pancreas.

Monitoring the stability of patient position is essential during high-precision radiotherapy such as spine stereotactic body radiotherapy (SBRT). We evaluated the combination of digital tomosynthesis (DTS) and triangulation for spine position detection, using non-clinical DTS software and an anthropomorphic pelvic phantom that includes a bone-like spine structure. Kilovoltage cone beam CT projection images over 2–16° gantry rotation were used to generate single slice DTS images. Each DTS slice was registered to a digitally reconstructed DTS derived from the planning CT scan to determine 2D shifts between actual phantom and treatment plan position. Two or more DTS registrations, central axes 4–22° apart, were triangulated to determine the 3D phantom position. Using sequentially generated DTS images, the phantom position can be updated every degree with a small latency of DTS and triangulation angle. The precision of position determination was investigated as function of DTS and triangulation angle. To mimic the scenario of spine SBRT, the effect on the standard deviation of megavoltage radiation delivery during kV image acquisition was tested. In addition, the ability of the system to detect different types of movement was investigated for a variety of small sudden and gradual movements during kV image acquisition.

Proton resonance frequency shift-based MR thermometry is a promising temperature monitoring approach for thermotherapy but its accuracy is vulnerable to inter-scan motion. Model-based referenceless thermometry has been proposed to address this problem but phase unwrapping is usually needed before the model fitting process. In this paper, a referenceless MR thermometry method using phase finite difference that avoids the time consuming phase unwrapping procedure is proposed. Unlike the previously proposed phase gradient technique, the use of finite difference in the new method reduces the fitting error resulting from the ringing artifacts associated with phase discontinuity in the calculation of the phase gradient image. The new method takes into account the values at the perimeter of the region of interest because of their direct relevance to the extrapolated baseline phase of the region of interest (where temperature increase takes place). In simulation study, in vivo and ex vivo experiments, the new method has a root-mean-square temperature error of 0.35 °C, 1.02 °C and 1.73 °C compared to 0.83 °C, 2.81 °C, and 3.76 °C from the phase gradient method, respectively. The method also demonstrated a slightly higher, albeit small, temperature accuracy than the original referenceless MR thermometry method. The proposed method is computationally efficient (∼0.1 s per image), making it very suitable for the real time temperature monitoring.

The majority of commercial radiotherapy treatment planning systems requires planners to iteratively adjust the plan parameters in order to find a satisfactory plan. This iterative trial-and-error nature of radiotherapy treatment planning results in an inefficient planning process and in order to reduce such inefficiency, plans can be accepted without achieving the best attainable quality. We propose a quality assessment method based on data envelopment analysis (DEA) to address this inefficiency. This method compares a plan of interest to a set of past delivered plans and searches for evidence of potential further improvement. With the assistance of DEA, planners will be able to make informed decisions on whether further planning is required and ensure that a plan is only accepted when the plan quality is close to the best attainable one. We apply the DEA method to 37 prostate plans using two assessment parameters: rectal generalized equivalent uniform dose (gEUD) as the input and D95 (the minimum dose that is received by 95% volume of a structure) of the planning target volume (PTV) as the output. The percentage volume of rectum overlapping PTV is used to account for anatomical variations between patients and is included in the model as a non-discretionary output variable. Five plans that are considered of lesser quality by DEA are re-optimized with the goal to further improve rectal sparing. After re-optimization, all five plans improve in rectal gEUD without clinically considerable deterioration of the PTV D95 value. For the five re-optimized plans, the rectal gEUD is reduced by an average of 1.84 Gray (Gy) with only an average reduction of 0.07 Gy in PTV D95. The results demonstrate that DEA can correctly identify plans with potential improvements in terms of the chosen input and outputs.

We introduce a new motion encoding concept for the displacement vector in multifrequency magnetic resonance elastography (MRE). Selective spectral displacement projection (SDP)-MRE can be applied to a vibration spectrum composed of three frequencies and exploits the filter condition of MRE for selecting one frequency each per spatial motion encoding direction. The selected components are simultaneously encoded in the phase of the MR signal. Therefore, the total MR phase is represented by a sum of phase portions, each corresponding to a distinct spatial projection and vibration frequency. The individual components can be obtained by applying a Fourier-transform to the temporally resolved phase images. SDP-MRE reduces the number of temporally resolved MRE experiments for data acquisition by a factor of 3, while providing similar wave images as found using conventional monofrequency MRE.

An optimal experiment design methodology was developed to select the framing schedule to be used in dynamic positron emission tomography (PET) for estimation of myocardial blood flow using ⁸²Rb. A compartment model and an arterial input function based on measured data were used to calculate a D-optimality criterion for a wide range of candidate framing schedules. To validate the optimality calculation, noisy time-activity curves were simulated, from which parameter values were estimated using an efficient and robust decomposition of the estimation problem. D-optimized schedules improved estimate precision compared to non-optimized schedules, including previously published schedules. To assess robustness, a range of physiologic conditions were simulated. Schedules that were optimal for one condition were nearly-optimal for others. The effect of infusion duration was investigated. Optimality was better for shorter than for longer tracer infusion durations, with the optimal schedule for the shortest infusion duration being nearly optimal for other durations. Together this suggests that a framing schedule optimized for one set of conditions will also work well for others and it is not necessary to use different schedules for different infusion durations or for rest and stress studies. The method for optimizing schedules is general and could be applied in other dynamic PET imaging studies.

In abdomen computed tomography (CT), repeated radiation exposures are often inevitable for cancer patients who receive surgery or radiotherapy guided by CT images. Low-dose scans should thus be considered in order to avoid the harm of accumulative x-ray radiation. This work is aimed at improving abdomen tumor CT images from low-dose scans by using a fast dictionary learning (DL) based processing. Stemming from sparse representation theory, the proposed patch-based DL approach allows effective suppression of both mottled noise and streak artifacts. The experiments carried out on clinical data show that the proposed method brings encouraging improvements in abdomen low-dose CT images with tumors.

Studies using simulated calcifications can be performed to measure the effect of different imaging factors on calcification detection in digital mammography. The simulated calcifications must be inserted into clinical images with realistic contrast and sharpness. MoCa is a program which modifies the contrast and sharpness of simulated calcification clusters extracted from images of mastectomy specimens acquired on a digital specimen cabinet at high magnification for insertion into clinical mammography images. This work determines whether the use of MoCa results in simulated calcifications with the correct contrast and sharpness. Aluminium foils (thickness 0.1–0.4 mm) and 1.60 µm thick gold discs (diameter 0.13–0.8 mm) on 0.5 mm aluminium were imaged with a range of thicknesses of polymethyl methacrylate (PMMA) using an amorphous selenium direct digital (DR) system and a powder phosphor computed radiography (CR) system (real images). Simulated images of the tests objects were also generated using MoCa. The contrast of the aluminium squares and the degradation of the contrast of the gold discs as a function of disc diameter were compared in the real and simulated images. The average ratios of the simulated-to-real aluminium contrasts over all aluminium and PMMA thicknesses were 1.03±0.04 (two standard errors in the mean) and 0.99±0.03 for the DR and CR systems, respectively. The ratio of the simulated-to-real degradations of contrast averaged over all disc diameters and PMMA thicknesses were 1.007±0.008 and 1.002±0.013 for DR and CR, respectively. The use of MoCa was accurate within the experimental errors.