Table of contents

The axial field of view (AFOV) of the current generation of clinical whole-body PET scanners range from 15–22 cm, which limits sensitivity and renders applications such as whole-body dynamic imaging or imaging of very low activities in whole-body cellular tracking studies, almost impossible. Generally, extending the AFOV significantly increases the sensitivity and count-rate performance. However, extending the AFOV while maintaining detector thickness has significant cost implications. In addition, random coincidences, detector dead time, and object attenuation may reduce scanner performance as the AFOV increases. In this paper, we use Monte Carlo simulations to find the optimal scanner geometry (i.e. AFOV, detector thickness and acceptance angle) based on count-rate performance for a range of scintillator volumes ranging from 10 to 93 l with detector thickness varying from 5 to 20 mm. We compare the results to the performance of a scanner based on the current Siemens Biograph mCT geometry and electronics. Our simulation models were developed based on individual components of the Siemens Biograph mCT and were validated against experimental data using the NEMA NU-2 2007 count-rate protocol. In the study, noise-equivalent count rate (NECR) was computed as a function of maximum ring difference (i.e. acceptance angle) and activity concentration using a 27 cm diameter, 200 cm uniformly filled cylindrical phantom for each scanner configuration. To reduce the effect of random coincidences, we implemented a variable coincidence time window based on the length of the lines of response, which increased NECR performance up to 10% compared to using a static coincidence time window for scanners with a large maximum ring difference values. For a given scintillator volume, the optimal configuration results in modest count-rate performance gains of up to 16% compared to the shortest AFOV scanner with the thickest detectors. However, the longest AFOV of approximately 2 m with 20 mm thick detectors resulted in performance gains of 25–31 times higher NECR relative to the current Siemens Biograph mCT scanner configuration.

The purpose of this study was to analyze factors affecting proton stopping-power-ratio (SPR) estimations and range uncertainties in proton therapy planning using the standard stoichiometric calibration. The SPR uncertainties were grouped into five categories according to their origins and then estimated based on previously published reports or measurements. For the first time, the impact of tissue composition variations on SPR estimation was assessed and the uncertainty estimates of each category were determined for low-density (lung), soft, and high-density (bone) tissues. A composite, 95th percentile water-equivalent-thickness uncertainty was calculated from multiple beam directions in 15 patients with various types of cancer undergoing proton therapy. The SPR uncertainties (1σ) were quite different (ranging from 1.6% to 5.0%) in different tissue groups, although the final combined uncertainty (95th percentile) for different treatment sites was fairly consistent at 3.0–3.4%, primarily because soft tissue is the dominant tissue type in the human body. The dominant contributing factor for uncertainties in soft tissues was the degeneracy of Hounsfield numbers in the presence of tissue composition variations. To reduce the overall uncertainties in SPR estimation, the use of dual-energy computed tomography is suggested. The values recommended in this study based on typical treatment sites and a small group of patients roughly agree with the commonly referenced value (3.5%) used for margin design. By using tissue-specific range uncertainties, one could estimate the beam-specific range margin by accounting for different types and amounts of tissues along a beam, which may allow for customization of range uncertainty for each beam direction.

The purpose of this paper is to investigate the feasibility of a novel four-material decomposition technique for assessing the vulnerability of plaque with two contrast materials spectral computer tomography (CT) using two independent markers: plaque's inflammation and spotty calcification. A simulation study was conducted using an energy-sensitive photon-counting detector for k-edge imaging of the coronary arteries. In addition to detecting the inflammation status, which is known as a biological marker of a plaque's vulnerability, we use spotty calcium concentration as an independent marker to test a plaque's vulnerability. We have introduced a new method for detecting and quantifying calcium concentrations in the presence of two contrast materials (iodine and gold), calcium and soft tissue background. In this method, four-material decomposition was performed on a pixel-by-pixel basis, assuming there was an arbitrary mixture of materials in the voxel. The concentrations of iodine and gold were determined by the k-edge material decomposition based on the maximum likelihood method. The calibration curves of the attenuation coefficients, with respect to the concentrations of different materials, were used to separate the calcium signal from both contrast materials and different soft tissues in the mixtures. Three different materials (muscle, blood and lipid) were independently used as soft tissue. The simulations included both ideal and more realistic energy resolving detectors to measure the polychromatic photon spectrum in single slice parallel beam geometry. The ideal detector was used together with a 3 cm diameter digital phantom to demonstrate the decomposition method while a more realistic detector and a 33 × 24 cm² digital chest phantom were simulated to validate the vulnerability assessment technique. A 120 kVp spectrum was generated to produce photon flux sufficient for detecting contrast materials above the k-edges of iodine (33.2 keV) and gold (80.7 keV). By performing simulations on a 3 cm diameter digital phantom, we successfully identified four materials that were simultaneously present in the mixture at different proportions and in multiple locations on the phantom. Quantitative analysis with a chest digital phantom showed that the results for iodine, gold and calcium were highly correlated with the known concentrations. The analysis revealed a potentially powerful technique for assessing a plaque's vulnerability with two independent markers. High correlation and low relative errors between calculated and known materials' concentrations showed that the method is feasible. This technique can potentially have a high clinical impact.

Intensity modulated radiation therapy (IMRT) inverse planning using total-variation (TV) regularization has been proposed to reduce the complexity of fluence maps and facilitate dose delivery. Conventionally, the optimization problem with L-1 norm is solved with quadratic programming (QP), which is time consuming and memory expensive due to the second-order Newton update. This study proposes to use a new algorithm, template for first-order conic solver (TFOCS), for fast and memory-efficient optimization in IMRT inverse planning. The TFOCS utilizes dual-variable updates and first-order approaches for TV minimization without the need to compute and store the enlarged Hessian matrix required for Newton update in the QP technique. To evaluate the effectiveness and efficiency of the proposed method, two clinical cases were used for IMRT inverse planning: a head and neck case and a prostate case. For comparison, the conventional QP-based method for the TV form was adopted to solve the fluence map optimization problem in the above two cases. The convergence criteria and algorithm parameters were selected to achieve similar dose conformity for a fair comparison between the two methods. Compared with conventional QP-based approach, the proposed TFOCS-based method shows a remarkable improvement in computational efficiency for fluence map optimization, while maintaining the conformal dose distribution. Compared with QP-based algorithms, the computational speed using TFOCS for fluence optimization is increased by a factor of 4 to 6, and at the same time the memory requirement is reduced by a factor of 3 to 4. Therefore, TFOCS provides an effective, fast and memory-efficient method for IMRT inverse planning. The unique features of the approach should be particularly important in inverse planning involving a large number of beams, such as in VMAT and dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT).

Training active shape models requires collecting manual ground-truth meshes in a large image database. While shape information can be reused across multiple imaging modalities, intensity information needs to be imaging modality and protocol specific. In this context, this study has two main purposes: (1) to test the potential of using intensity models learned from MRI simulated datasets and (2) to test the potential of including a measure of reliability during the matching process to increase robustness. We used a population of 400 virtual subjects (XCAT phantom), and two clinical populations of 40 and 45 subjects. Virtual subjects were used to generate simulated datasets (MRISIM simulator). Intensity models were trained both on simulated and real datasets. The trained models were used to segment the left ventricle (LV) and right ventricle (RV) from real datasets. Segmentations were also obtained with and without reliability information. Performance was evaluated with point-to-surface and volume errors. Simulated intensity models obtained average accuracy comparable to inter-observer variability for LV segmentation. The inclusion of reliability information reduced volume errors in hypertrophic patients (EF errors from 17 ± 57% to 10 ± 18%; LV MASS errors from −27 ± 22 g to −14 ± 25 g), and in heart failure patients (EF errors from −8 ± 42% to −5 ± 14%). The RV model of the simulated images needs further improvement to better resemble image intensities around the myocardial edges. Both for real and simulated models, reliability information increased segmentation robustness without penalizing accuracy.

Time-of-flight (ToF) camera technology provides a real-time depth map of a scene with adequate frequency for the monitoring of physiological patient motion. However, dynamic surface motion estimation using a ToF camera is limited by issues such as the raw measurement accuracy and the absence of fixed anatomical landmarks. In this work we propose to overcome these limitations using surface modeling through B-splines. This approach was assessed in terms of both motion estimation accuracy and associated variability improvements using acquisitions of an anthropomorphic surface phantom for a range of observation distances (0.6–1.4 m). In addition, feasibility was demonstrated on patient acquisitions. Using the proposed B-spline modeling, the mean motion estimation error and associated repeatability with respect to the raw measurements decreased by a factor of 3. Significant correlation was found between patients' surfaces motion extracted using the proposed B-spline approach applied to the ToF data and the one extracted from synchronized 4D-CT acquisitions as the ground truth. ToF cameras represent a promising alternative for contact-less patient surface monitoring for respiratory motion synchronization or modeling in imaging and/or radiotherapy applications.

Several positron emitting radioisotopes such as ¹¹C and ¹³N can be used in plant biology research. The ¹¹CO₂ tracer is used to facilitate plant biology research toward optimization of plant productivity, biofuel development and carbon sequestration in biomass. Positron emission tomography (PET) imaging has been used to study carbon transport in live plants using ¹¹CO₂. Because plants typically have very thin leaves, little medium is present for the emitted positrons to undergo an annihilation event. The emitted positrons from ¹¹C (maximum energy 960 keV) could require up to approximately 4 mm of water equivalent material for positron annihilation. Thus many of the positrons do not annihilate inside the leaf, resulting in limited sensitivity for PET imaging. To address this problem we have developed a compact beta-positive, beta-minus particle imager (PhytoBeta imager) for ¹¹CO₂ leaf imaging. The detector is based on a Hamamatsu H8500 position sensitive photomultiplier tube optically coupled via optical grease to a 0.5 mm thick Eljen EJ-212 plastic scintillator. The detector is equipped with a flexible arm to allow its placement and orientation over or under the leaf to be studied while maintaining the leaf's original orientation. To test the utility of the system the detector was used to measure carbon translocation in a leaf of the spicebush (Lindera benzoin) under two transient light conditions.

The purpose of this study was to investigate the possibility of estimating pediatric thyroid doses from CT using surface neck doses. Optically stimulated luminescence dosimeters were used to measure the neck surface dose of 25 children ranging in ages between one and three years old. The neck circumference for each child was measured. The relationship between obtained surface doses and thyroid dose was studied using acrylic phantoms of various sizes and with holes of different depths. The ratios of hole-to-surface doses were used to convert patients' surface dose to thyroid dose. ImPACT software was utilized to calculate thyroid dose after applying the appropriate age correction factors. A paired t-test was performed to compare thyroid doses from our approach and ImPACT. The ratio of thyroid to surface dose was found to be 1.1. Thyroid doses ranged from 20 to 80 mGy. Comparison showed no statistical significance (p = 0.18). In addition, the average of surface dose variation along the z-axis in helical scans was studied and found to range between 5% (in 10 cm diameter phantom/24 mm collimation/pitch 1.0) and 8% (in 16 cm diameter phantom/12 mm collimation/pitch 0.7). We conclude that surface dose is an acceptable predictor for pediatric thyroid dose from CT. The uncertainty due to surface dose variability may be reduced if narrower collimation is used with a pitch factor close to 1.0. Also, the results did not show any effect of thyroid depth on the measured dose.

Active scanning delivery systems take full advantage of ion beams to best conform to the tumor and to spare surrounding healthy tissues; however, it is also a challenging technique for quality assurance. In this perspective, we upgraded the GATE/GEANT4 Monte Carlo platform in order to recalculate the treatment planning system (TPS) dose distributions for active scanning systems. A method that allows evaluating the TPS dose distributions with the GATE Monte Carlo platform has been developed and applied to the XiO TPS (Elekta), for the IBA proton pencil beam scanning (PBS) system. First, we evaluated the specificities of each dose engine. A dose-conversion scheme that allows one to convert dose to medium into dose to water was implemented within GATE. Specific test cases in homogeneous and heterogeneous configurations allowed for the estimation of the differences between the beam models implemented in XiO and GATE. Finally, dose distributions of a prostate treatment plan were compared. In homogeneous media, a satisfactory agreement was generally obtained between XiO and GATE. The maximum stopping power difference of 3% occurred in a human tissue of 0.9 g cm⁻³ density and led to a significant range shift. Comparisons in heterogeneous configurations pointed out the limits of the TPS dose calculation accuracy and the superiority of Monte Carlo simulations. The necessity of computing dose to water in our Monte Carlo code for comparisons with TPSs is also presented. Finally, the new capabilities of the platform are applied to a prostate treatment plan and dose differences between both dose engines are analyzed in detail. This work presents a generic method to compare TPS dose distributions with the GATE Monte Carlo platform. It is noteworthy that GATE is also a convenient tool for imaging applications, therefore opening new research possibilities for the PBS modality.

Magnetic resonance electrical impedance tomography (MREIT) is a technique that produces images of conductivity in tissues and phantoms. In this technique, electrical currents are applied to an object and the resulting magnetic flux density is measured using magnetic resonance imaging (MRI) and the conductivity distribution is reconstructed using these MRI data. Currently, the technique is used in research environments, primarily studying phantoms and animals. In order to translate MREIT to clinical applications, strict safety standards need to be established, especially for safe current limits. However, there are currently no standards for safe current limits specific to MREIT. Until such standards are established, human MREIT applications need to conform to existing electrical safety standards in medical instrumentation, such as IEC601. This protocol limits patient auxiliary currents to 100 µA for low frequencies. However, published MREIT studies have utilized currents 10–400 times larger than this limit, bringing into question whether the clinical applications of MREIT are attainable under current standards. In this study, we investigated the feasibility of MREIT to accurately reconstruct the relative conductivity of a simple agarose phantom using 200 µA total injected current and tested the performance of two MREIT reconstruction algorithms. These reconstruction algorithms used are the iterative sensitivity matrix method (SMM) by Ider and Birgul (1998 Elektrik6 215–25) with Tikhonov regularization and the harmonic B_Z proposed by Oh et al (2003 Magn. Reason. Med.50 875–8). The reconstruction techniques were tested at both 200 µA and 5 mA injected currents to investigate their noise sensitivity at low and high current conditions. It should be noted that 200 µA total injected current into a cylindrical phantom generates only 14.7 µA current in imaging slice. Similarly, 5 mA total injected current results in 367 µA in imaging slice. Total acquisition time for 200 µA and 5 mA experiments was about 1 h and 8.5 min, respectively. The results demonstrate that conductivity imaging is possible at low currents using the suggested imaging parameters and reconstructing the images using iterative SMM with Tikhonov regularization, which appears to be more tolerant to noisy data than harmonic B_Z.

Clinical trials on ¹⁷⁷Lu–⁹⁰Y therapy used empirical activity ratios. Radionuclides (RN) with larger beta maximal range could favourably replace ⁹⁰Y. Our aim is to provide RN dose-deposition kernels and to compare the tumour control probability (TCP) of RN combinations. Dose kernels were derived by integration of the mono-energetic beta-ray dose distributions (computed using Monte Carlo) weighted by their respective beta spectrum. Nine homogeneous spherical tumours (1–25 mm in diameter) and four spherical tumours including a lattice of cold, but alive, spheres (1, 3, 5, 7 mm in diameter) were modelled. The TCP for ⁹³Y, ⁹⁰Y and ¹²⁵Sn in combination with ¹⁷⁷Lu in variable proportions (that kept constant the renal cortex biological effective dose) were derived by 3D dose kernel convolution. For a mean tumour-absorbed dose of 180 Gy, 2 mm homogeneous tumours and tumours including 3 mm diameter cold alive spheres were both well controlled (TCP > 0.9) using a 75–25% combination of ¹⁷⁷Lu and ⁹⁰Y activity. However, ¹²⁵Sn–¹⁷⁷Lu achieved a significantly better result by controlling 1 mm-homogeneous tumour simultaneously with tumours including 5 mm diameter cold alive spheres. Clinical trials using RN combinations should use RN proportions tuned to the patient dosimetry. ¹²⁵Sn production and its coupling to somatostatin analogue appear feasible. Assuming similar pharmacokinetics ¹²⁵Sn is the best RN for combination with ¹⁷⁷Lu in peptide receptor radiotherapy justifying pharmacokinetics studies in rodent of ¹²⁵Sn-labelled somatostatin analogues.

Image-guided alignment procedures in radiotherapy aim at minimizing discrepancies between the planned and the real patient setup. For that purpose, we developed a 2D/3D approach which rigidly registers a computed tomography (CT) with two x-rays by maximizing the agreement in pixel intensity between the x-rays and the corresponding reconstructed radiographs from the CT. Moreover, the algorithm selects regions of interest (masks) in the x-rays based on 3D segmentations from the pre-planning stage. For validation, orthogonal x-ray pairs from different viewing directions of 80 pelvic cone-beam CT (CBCT) raw data sets were used. The 2D/3D results were compared to corresponding standard 3D/3D CBCT-to-CT alignments. Outcome over 8400 2D/3D experiments showed that parametric errors in root mean square were <0.18° (rotations) and <0.73 mm (translations), respectively, using rank correlation as intensity metric. This corresponds to a mean target registration error, related to the voxels of the lesser pelvis, of <2 mm in 94.1% of the cases. From the results we conclude that 2D/3D registration based on sequentially acquired orthogonal x-rays of the pelvis is a viable alternative to CBCT-based approaches if rigid alignment on bony anatomy is sufficient, no volumetric intra-interventional data set is required and the expected error range fits the individual treatment prescription.

The purpose of this paper is to develop a technique for the construction of a two-compartment anthropomorphic breast phantom specific to an individual patient's pendant breast anatomy. Three-dimensional breast images were acquired on a prototype dedicated breast computed tomography (bCT) scanner as part of an ongoing IRB-approved clinical trial of bCT. The images from the breast of a patient were segmented into adipose and glandular tissue regions and divided into 1.59 mm thick breast sections to correspond to the thickness of polyethylene stock. A computer-controlled water-jet cutting machine was used to cut the outer breast edge and the internal regions corresponding to glandular tissue from the polyethylene. The stack of polyethylene breast segments was encased in a thermoplastic 'skin' and filled with water. Water-filled spaces modeled glandular tissue structures and the surrounding polyethylene modeled the adipose tissue compartment. Utility of the phantom was demonstrated by inserting 200 µm microcalcifications as well as by measuring point dose deposition during bCT scanning. Affine registration of the original patient images with bCT images of the phantom showed similar tissue distribution. Linear profiles through the registered images demonstrated a mean coefficient of determination (r²) between grayscale profiles of 0.881. The exponent of the power law describing the anatomical noise power spectrum was identical in the coronal images of the patient's breast and the phantom. Microcalcifications were visualized in the phantom at bCT scanning. The real-time air kerma rate was measured during bCT scanning and fluctuated with breast anatomy. On average, point dose deposition was 7.1% greater than the mean glandular dose. A technique to generate a two-compartment anthropomorphic breast phantom from bCT images has been demonstrated. The phantom is the first, to our knowledge, to accurately model the uncompressed pendant breast and the glandular tissue distribution for a specific patient. The modular design of the phantom allows for studies of a single breast segment and the entire breast volume. Insertion of other devices, materials and tissues of interest into the phantom provide a robust platform for future breast imaging and dosimetry studies.

Quantification in cardiac mouse positron emission tomography (PET) imaging is limited by the imaging spatial resolution. Spillover of left ventricle (LV) myocardial activity into adjacent organs results in partial volume (PV) losses leading to underestimation of myocardial activity. A PV correction method was developed to restore accuracy of the activity distribution for FDG mouse imaging. The PV correction model was based on convolving an LV image estimate with a 3D point spread function. The LV model was described regionally by a five-parameter profile including myocardial, background and blood activities which were separated into three compartments by the endocardial radius and myocardium wall thickness. The PV correction was tested with digital simulations and a physical 3D mouse LV phantom. In vivo cardiac FDG mouse PET imaging was also performed. Following imaging, the mice were sacrificed and the tracer biodistribution in the LV and liver tissue was measured using a gamma-counter. The PV correction algorithm improved recovery from 50% to within 5% of the truth for the simulated and measured phantom data and image uniformity by 5–13%. The PV correction algorithm improved the mean myocardial LV recovery from 0.56 (0.54) to 1.13 (1.10) without (with) scatter and attenuation corrections. The mean image uniformity was improved from 26% (26%) to 17% (16%) without (with) scatter and attenuation corrections applied. Scatter and attenuation corrections were not observed to significantly impact PV-corrected myocardial recovery or image uniformity. Image-based PV correction algorithm can increase the accuracy of PET image activity and improve the uniformity of the activity distribution in normal mice. The algorithm may be applied using different tracers, in transgenic models that affect myocardial uptake, or in different species provided there is sufficient image quality and similar contrast between the myocardium and surrounding structures.

Time irreversibility can be qualitatively defined as the degree of a signal for temporal asymmetry. Recently, a time irreversibility characterization method based on entropies of positive and negative increments has been proposed for experimental signals and applied to heart rate variability (HRV) data (central cardiovascular system (CVS)). The results led to interesting information as a time asymmetry index was found different for young subjects and elderly people or heart disease patients. Nevertheless, similar analyses have not yet been conducted on laser Doppler flowmetry (LDF) signals (peripheral CVS). We first propose to further investigate the above-mentioned characterization method. Then, LDF signals, LDF signals reduced to samples acquired during ECG R peaks (LDF_R_ECG signals) and HRV recorded simultaneously in healthy subjects are processed. Entropies of positive and negative increments for LDF signals show a nonmonotonic pattern: oscillations—more or less pronounced, depending on subjects—are found with a period matching the one of cardiac activity. However, such oscillations are not found with LDF_R_ECG nor with HRV. Moreover, the asymmetry index for LDF is markedly different from the ones of LDF_R_ECG and HRV. The cardiac activity may therefore play a dominant role in the time irreversibility properties of LDF signals.

A novel approach to read out radiochromic film was introduced recently by the manufacturer of GafChromic film. In this study, the performance of this triple-channel film dosimetry method was compared against the conventional single-red-channel film dosimetry procedure, with and without inclusion of a pre-irradiation (pre-IR) film scan, using EBT2 film and kilo- and megavoltage photon beams up to 10 Gy. When considering regions of interest averaged doses, the triple-channel method and both single-channel methods produced equivalent results. Absolute dose discrepancies between the triple-channel method, both single-channel methods and the treatment planning system calculated dose values, were no larger than 5 cGy for dose levels up to 2.2 Gy. Signal to noise in triple-channel dose images was found to be similar to signal to noise in single-channel dose images. The accuracy of resulting dose images from the triple- and single-channel methods with inclusion of pre-IR film scan was found to be similar. Results of a comparison of EBT2 data from a kilovoltage depth dose experiment to corresponding Monte Carlo depth dose data produced dose discrepancies of 9.5 ± 12 cGy and 7.6 ± 6 cGy for the single-channel method with inclusion of a pre-IR film scan and the triple-channel method, respectively. EBT2 showed to be energy sensitive at low kilovoltage energies with response differences of 11.9% and 15.6% in the red channel at 2 Gy between 50–225 kVp and 80–225 kVp photon spectra, respectively. We observed that the triple-channel method resulted in non-uniformity corrections of ±1% and consistency values of 0–3 cGy for the batches and dose levels studied. Results of this study indicate that the triple-channel radiochromic film read-out method performs at least as well as the single-channel method with inclusion of a pre-IR film scan, reduces film non-uniformity and saves time with elimination of a pre-IR film scan.

In light ion therapy, the knowledge of the spectra of both primary and secondary particles in the target volume is needed in order to accurately describe the treatment. The transport of ions in matter is complex and comprises both atomic and nuclear processes involving primary and secondary ions produced in the cascade of events. One of the critical issues in the simulation of ion transport is the modeling of inelastic nuclear reaction processes, in which projectile nuclei interact with target nuclei and give rise to nuclear fragments. In the Monte Carlo code SHIELD-HIT, inelastic nuclear reactions are described by the Many Stage Dynamical Model (MSDM), which includes models for the different stages of the interaction process. In this work, the capability of SHIELD-HIT to simulate the nuclear fragmentation of carbon ions in tissue-like materials was studied. The value of the parameter κ, which determines the so-called freeze-out volume in the Fermi break-up stage of the nuclear interaction process, was adjusted in order to achieve better agreement with experimental data. In this paper, results are shown both with the default value κ = 1 and the modified value κ = 10 which resulted in the best overall agreement. Comparisons with published experimental data were made in terms of total and partial charge-changing cross-sections generated by the MSDM, as well as integral and differential fragment yields simulated by SHIELD-HIT in intermediate and thick water targets irradiated with a beam of 400 MeV u⁻¹¹²C ions. Better agreement with the experimental data was in general obtained with the modified parameter value (κ = 10), both on the level of partial charge-changing cross-sections and fragment yields.

Vertebral metastases are a common manifestation of many cancers, potentially leading to vertebral collapse and neurological complications. Conventional treatment often involves percutaneous vertebroplasty/kyphoplasty followed by external beam radiation therapy. As a more convenient alternative, we have introduced radioactive bone cement, i.e. bone cement incorporating a radionuclide. In this study, we used a previously developed Monte Carlo radiation transport modeling method to evaluate dose distributions from phosphorus-32 radioactive cement in simulated clinical scenarios. Isodose curves were generally concentric about the surface of bone cement injected into cadaveric vertebrae, indicating that dose distributions are relatively predictable, thus facilitating treatment planning (cement formulation and dosimetry method are patent pending). Model results indicated that a therapeutic dose could be delivered to tumor/bone within ∼4 mm of the cement surface while maintaining a safe dose to radiosensitive tissue beyond this distance. This therapeutic range should be sufficient to treat target volumes within the vertebral body when tumor ablation or other techniques are used to create a cavity into which the radioactive cement can be injected. With further development, treating spinal metastases with radioactive bone cement may become a clinically useful and convenient alternative to the conventional two-step approach of percutaneous strength restoration followed by radiotherapy.

Targeted α-particle therapy is a promising treatment modality for cancer. Due to the short path-length of α-particles, the potential efficacy and toxicity of these agents is best evaluated by microscale dosimetry calculations instead of whole-organ, absorbed fraction-based dosimetry. Yet time-integrated activity (TIA), the necessary input for dosimetry, can still only be quantified reliably at the organ or macroscopic level. We describe a nephron- and cellular-based kidney dosimetry model for α-particle radiopharmaceutical therapy, more suited to the short range and high linear energy transfer of α-particle emitters, which takes as input kidney or cortex TIA and through a macro to micro model-based methodology assigns TIA to micro-level kidney substructures. We apply a geometrical model to provide nephron-level S-values for a range of isotopes allowing for pre-clinical and clinical applications according to the medical internal radiation dosimetry (MIRD) schema. We assume that the relationship between whole-organ TIA and TIA apportioned to microscale substructures as measured in an appropriate pre-clinical mammalian model also applies to the human. In both, the pre-clinical and the human model, microscale substructures are described as a collection of simple geometrical shapes akin to those used in the Cristy–Eckerman phantoms for normal organs. Anatomical parameters are taken from the literature for a human model, while murine parameters are measured ex vivo. The murine histological slides also provide the data for volume of occupancy of the different compartments of the nephron in the kidney: glomerulus versus proximal tubule versus distal tubule. Monte Carlo simulations are run with activity placed in the different nephron compartments for several α-particle emitters currently under investigation in radiopharmaceutical therapy. The S-values were calculated for the α-emitters and their descendants between the different nephron compartments for both the human and murine models. The renal cortex and medulla S-values were also calculated and the results compared to traditional absorbed fraction calculations. The nephron model enables a more optimal implementation of treatment and is a critical step in understanding toxicity for human translation of targeted α-particle therapy. The S-values established here will enable a MIRD-type application of α-particle dosimetry for α-emitters, i.e. measuring the TIA in the kidney (or renal cortex) will provide meaningful and accurate nephron-level dosimetry.

In many studies, the estimation of the apparent diffusion coefficient (ADC) of lesions in visceral organs in diffusion-weighted (DW) magnetic resonance images requires an accurate lesion-segmentation algorithm. To evaluate these lesion-segmentation algorithms, region-overlap measures are used currently. However, the end task from the DW images is accurate ADC estimation, and the region-overlap measures do not evaluate the segmentation algorithms on this task. Moreover, these measures rely on the existence of gold-standard segmentation of the lesion, which is typically unavailable. In this paper, we study the problem of task-based evaluation of segmentation algorithms in DW imaging in the absence of a gold standard. We first show that using manual segmentations instead of gold-standard segmentations for this task-based evaluation is unreliable. We then propose a method to compare the segmentation algorithms that does not require gold-standard or manual segmentation results. The no-gold-standard method estimates the bias and the variance of the error between the true ADC values and the ADC values estimated using the automated segmentation algorithm. The method can be used to rank the segmentation algorithms on the basis of both the ensemble mean square error and precision. We also propose consistency checks for this evaluation technique.

Contact currents flow from/into a charged human body when touching a grounded conductive object. An electrostatic discharge (ESD) or spark may occur just before contact or upon release. The current may stimulate muscles and peripheral nerves. In order to clarify the difference in the induced electric field between different sized human models, the in-situ electric fields were computed in anatomically based models of adults and a child for a contact current in a human body following ESD. A dispersive finite-difference time-domain method was used, in which biological tissue is assumed to obey a four-pole Debye model. From our computational results, the first peak of the discharge current was almost identical across adult and child models. The decay of the induced current in the child was also faster due mainly to its smaller body capacitance compared to the adult models. The induced electric fields in the forefingers were comparable across different models. However, the electric field induced in the arm of the child model was found to be greater than that in the adult models primarily because of its smaller cross-sectional area. The tendency for greater doses in the child has also been reported for power frequency sinusoidal contact current exposures as reported by other investigators.

In radiotherapy, cone-beam computerized tomography (CBCT) scans are used for position correction for various tumour sites. At the start of the treatment, a CT scan that serves as input for a treatment planning is acquired. A CBCT scan is made prior to the irradiation of the tumour. Because there might be significant interfractional tumour movement, online recalculation of the dose improves decision making on how to proceed. A prerequisite for such recalculation is an accurately delineated body contour. In this note, we present an automatic delineation method for the body contour in the unprocessed CBCT scans, that employs a novel delineation boosting technique. The main idea of this technique is to construct an accurate delineation by combining the strength of several edge detectors in an innovative way. Quantitative validation reveals that the algorithm performs comparably with the manual delineations of two trained observers. Furthermore, because of the generic nature of the delineation boosting procedure, the algorithm can easily be extended with additional edge detectors to further increase the accuracy. Finally, the processing time of one scan when delineated manually is 3 h, and the total processing time is 24 min for one scan if the algorithm is used in its present form. Current investigation includes the conversion of the Matlab algorithm to C++ and the development of a visual tool to quickly detect which automatically delineated slices need manual correction. From this we expect further speeding up of the process, allowing online computation.

Mathematical phantoms are essential for the development and early stage evaluation of image reconstruction algorithms in x-ray computed tomography (CT). This note offers tools for computer simulations using a two-dimensional (2D) phantom that models the central axial slice through the FORBILD head phantom. Introduced in 1999, in response to a need for a more robust test, the FORBILD head phantom is now seen by many as the gold standard. However, the simple Shepp–Logan phantom is still heavily used by researchers working on 2D image reconstruction. Universal acceptance of the FORBILD head phantom may have been prevented by its significantly higher complexity: software that allows computer simulations with the Shepp–Logan phantom is not readily applicable to the FORBILD head phantom. The tools offered here address this problem. They are designed for use with Matlab®, as well as open-source variants, such as FreeMat and Octave, which are all widely used in both academia and industry. To get started, the interested user can simply copy and paste the codes from this PDF document into Matlab® M-files.

The full text of this article is available in the PDF provided.