Table of contents

Microbubble contrast agents and the associated imaging systems have developed over the past 25 years, originating with manually-agitated fluids introduced for intra-coronary injection. Over this period, stabilizing shells and low diffusivity gas materials have been incorporated in microbubbles, extending stability in vitro and in vivo. Simultaneously, the interaction of these small gas bubbles with ultrasonic waves has been extensively studied, resulting in models for oscillation and increasingly sophisticated imaging strategies. Early studies recognized that echoes from microbubbles contained frequencies that are multiples of the microbubble resonance frequency. Although individual microbubble contrast agents cannot be resolved—given that their diameter is on the order of microns—nonlinear echoes from these agents are used to map regions of perfused tissue and to estimate the local microvascular flow rate. Such strategies overcome a fundamental limitation of previous ultrasound blood flow strategies; the previous Doppler-based strategies are insensitive to capillary flow. Further, the insonation of resonant bubbles results in interesting physical phenomena that have been widely studied for use in drug and gene delivery. Ultrasound pressure can enhance gas diffusion, rapidly fragment the agent into a set of smaller bubbles or displace the microbubble to a blood vessel wall. Insonation of a microbubble can also produce liquid jets and local shear stress that alter biological membranes and facilitate transport. In this review, we focus on the physical aspects of these agents, exploring microbubble imaging modes, models for microbubble oscillation and the interaction of the microbubble with the endothelium.

In proton therapy, the radiological thickness of a material is commonly expressed in terms of water equivalent thickness (WET) or water equivalent ratio (WER). However, the WET calculations required either iterative numerical methods or approximate methods of unknown accuracy. The objective of this study was to develop a simple deterministic formula to calculate WET values with an accuracy of 1 mm for materials commonly used in proton radiation therapy. Several alternative formulas were derived in which the energy loss was calculated based on the Bragg–Kleeman rule (BK), the Bethe–Bloch equation (BB) or an empirical version of the Bethe–Bloch equation (EBB). Alternative approaches were developed for targets that were 'radiologically thin' or 'thick'. The accuracy of these methods was assessed by comparison to values from an iterative numerical method that utilized evaluated stopping power tables. In addition, we also tested the approximate formula given in the International Atomic Energy Agency's dosimetry code of practice (Technical Report Series No 398, 2000, IAEA, Vienna) and stopping power ratio approximation. The results of these comparisons revealed that most methods were accurate for cases involving thin or low-Z targets. However, only the thick-target formulas provided accurate WET values for targets that were radiologically thick and contained high-Z material.

This paper describes a novel method for estimating tissue motion in two-dimensional intravascular ultrasound (IVUS) images of a coronary artery. It is based on the classical Lukas–Kanade (LK) algorithm for optical flow (OF). The OF vector field quantifies the amount of misalignment between two consecutive frames in a sequence of images. From the theoretical standpoint, two fundamental improvements are proposed in this paper. First, using a simplified representation of the vessel wall as a medium with randomly distributed scatterers, it was shown that the OF equation satisfies the integral brightness conservation law. Second, a scale-space embedding for the OF equation was derived under the assumption of spatial consistency in IVUS acquisitions. The spatial coherence is equivalent to a locally affine motion model. The latter effectively captures and appropriately describes a complex deformation pattern of the coronary vessel wall under the varying physiological conditions (i.e. pulsatile blood pressure). The accuracy of OF tracking was estimated on the tissue-mimicking phantoms subjected to the controlled amount of angular deviation. Moreover, the performance of the classical LK and proposed approach was compared using the simulated IVUS images with an atherosclerotic lesion. The experimental results showed robust and reliable performance of up to 5° of rotation, which is within the plausible range of circumferential displacement of the coronary arteries. Subsequently, the algorithm was used to analyze vessel wall motion in 18 IVUS pullbacks from 16 patients. The in vivo experiments revealed that the motion of coronary arteries is primarily determined by the cardiac contraction.

A compact filtered backprojection algorithm that suppresses the undesirable effects of skin circulation for near-infrared diffuse optical topography is proposed. Our approach centers around a depth-selective filtering algorithm that uses an inverse problem technique and extracts target signals from observation data contaminated by noise from a shallow region. The filtering algorithm is reduced to a compact matrix and is therefore easily incorporated into a real-time system. To demonstrate the validity of this method, we developed a demonstration prototype for depth-selective diffuse optical topography and performed both computer simulations and phantom experiments. The results show that the proposed method significantly suppresses the noise from the shallow region with a minimal degradation of the target signal.

Cardiac diffusion tensor magnetic resonance imaging (DT-MRI) is noise sensitive, and the noise can induce numerous systematic errors in subsequent parameter calculations. This paper proposes a sparse representation-based method for denoising cardiac DT-MRI images. The method first generates a dictionary of multiple bases according to the features of the observed image. A segmentation algorithm based on nonstationary degree detector is then introduced to make the selection of atoms in the dictionary adapted to the image's features. The denoising is achieved by gradually approximating the underlying image using the atoms selected from the generated dictionary. The results on both simulated image and real cardiac DT-MRI images from ex vivo human hearts show that the proposed denoising method performs better than conventional denoising techniques by preserving image contrast and fine structures.

Plastic scintillators are used in the dosimetry of photons in radiotherapy. Their use in diagnostic radiology is affected by the drop in response at lower photon energies due to inadequate composition (effective atomic number) and chemical quenching. To compensate for this deficiency, a method for the production of composite polystyrene-based plastic scintillators was devised allowing the incorporation of inorganic scintillation powder. Disks of 10 mm diameter and 1 mm thickness optimized for a flat energy response referred to kerma in air were produced using CaWO₄, ZnS:Ag and CaF₂:Eu as additives. In an HVL range of 2.26–13.69 mmAl, the response was within an interval of ±2.8% for CaF₂:Eu as additive, ±3.2% for CaWO₄ and ±10.9% for ZnS:Ag, respectively. The response of a commercial plastic scintillator (BC470) stays within ±13.6%. The temperature dependence of the composite scintillator using CaF₂:Eu is lowest with a variation of +3.7% to −3.6% in an interval from 5 °C to 45 °C. The deficiency in photon absorption at lower energies due to the effective atomic number is reduced but not fully compensated by the additive scintillators. The optimized concentrations were established for the scintillator dimensions used.

We have derived an analytic geometric transfer function (GTF) for a convergent slit-slat collimator that treats the parallel slit-slat collimator as a special case. The effective point spread function (EPSF) is then derived from the GTF through the Fourier transform. The results of these derivations give an accurate description of the complete geometric response for a slit-slat collimator that includes the effects of the shape and orientation of the slit and slats. We have also derived exact and approximate sensitivity formulae and spatial resolution formulae using the EPSF.

Voxel-based prescriptions of deliberately non-uniform dose distributions based on molecular imaging, so-called dose painting or theragnostic radiation therapy, require specification of a transformation that maps the image data intensities to prescribed doses. However, the functional form of this transformation is currently unknown. An investigation into the sensitivity of optimized dose distributions resulting from several possible prescription functions was conducted. Transformations between the radiotracer activity concentrations from Cu-ATSM PET images, as a surrogate of tumour hypoxia, and dose prescriptions were implemented to yield weighted distributions of prescribed dose boosts in high uptake regions. Dose escalation was constrained to reflect clinically realistic whole tumour doses and constant normal tissue doses. Optimized heterogeneous dose distributions were found by minimizing a voxel-by-voxel quadratic objective function in which all tumour voxels were given equal weight. Prescriptions based on a polynomial mapping function were found to be least constraining on their optimized plans, while prescriptions based on a sigmoid mapping function were the most demanding to deliver. A prescription formalism that fixed integral dose was less sensitive to errors in the choice of the mapping function than one that boosted integral dose. Integral doses to normal tissue and critical structures were insensitive to the shape of the prescription function. Planned target dose conformity improved with smaller beamlet dimensions until the inherent spatial resolution of the functional image was matched. Clinical implementation of dose painting depends on advances in absolute quantification of functional images and improvements in delivery techniques over smaller spatial scales.

PET imaging with non-standard nuclides has limitations due to the reduced spatial resolution from the positron range and from the concurrent emission of other gamma rays during the decay process. Particularly in high-resolution small animal PET imaging, these factors become detrimental for accurate quantitation of the activity concentrations from the reconstructed images. This paper presents an evaluation for imaging with such a nuclide, ⁷⁶Br, through imaging of specifically designed phantoms in a high-resolution small animal PET scanner. A model is presented for the calculation and removal of fortuitous cascade gamma ray coincidences based on estimation of the activity distribution and the attenuation correction file. In this evaluation, it is shown that 2 mm spatial resolution can be achieved with ⁷⁶Br while 1.7 mm was achieved with ¹⁸F using a filtered back projection algorithm despite the much higher end-point energy of the positrons from ⁷⁶Br. A detailed evaluation of the point spread function for this nuclide was fitted by a double Gaussian function and explained the long tail from the high-energy positrons. These evaluations are crucial for accurate correction for partial volume effects and to provide accurate measurement of the activity concentrations in small animal PET imaging.

This paper presents a mathematical tissue-equivalent breast phantom for linear slot-scanning digital mammography. A recently developed prototype linear slot-scanning digital mammography system was used for model validation; image quality metrics such as image contrast and contrast-to-noise ratio were calculated. The results were in good agreement with values measured using a physical breast-equivalent phantom designed for mammography. The estimated pixel intensity of the mathematical phantom, the analogue-to-digital conversion gain and the detector additive noise showed good agreement with measured values with correlation of nearly 1. An application of the model, to examine the feasibility of using a monochromatic filter for dose reduction and improvement of image quality in slot-scanning digital mammography, is presented.

In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks—ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

We present different in vitro experimental models which allow us to evaluate the effect of spatially fractionated dose distributions on metabolic activity. We irradiated a monolayer of MCF-7/6 human breast cancer cells with a steep and a smooth 6 MV x-ray dose gradient. In the steep gradient model, we irradiated the cells with three separate small fields. We also developed two smooth gradient models. In the first model, the cells are cultured in a T25 flask and irradiated with a smooth dose gradient over the length of the flask, while in the second one, the cells are cultured in a 96-well plate and also irradiated over the length of the plate. In an attempt to correlate the spatially fractionated dose distributions with metabolic activity, the effect of irradiation was evaluated by means of the MTT assay. This assay is used to determine the metabolic activity by measuring the amount of formazan formed after the conversion of MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) by cellular dehydrogenases. The results obtained with our different models suggest a dose-specific effect on metabolic activity, characterized by an increased formazan optical density occurring in the dose range 1.0–4.0 Gy in the steep dose gradient model and in the dose ranges 4.2–6.5 Gy and 2.3–5.1 Gy in the two smooth dose gradient models. The corresponding times for maximal formazan accumulation were 5–7 days in the steep dose gradient model and day 9–13 and day 9–11 in the smooth dose gradient models. Altogether, our results suggest that the MTT assay may be used as a biological dose-response meter to monitor the radiotherapeutic effectiveness.

Gamma knife has been the treatment of choice for various brain tumors and functional disorders. Current gamma knife radiosurgery is planned in a 'ball-packing' approach and delivered in a 'step-and-shoot' manner, i.e. it aims to 'pack' the different sized spherical high-dose volumes (called 'shots') into a tumor volume. We have developed a dynamic scheme for gamma knife radiosurgery based on the concept of 'dose-painting' to take advantage of the new robotic patient positioning system on the latest Gamma Knife C™ and Perfexion™ units. In our scheme, the spherical high dose volume created by the gamma knife unit will be viewed as a 3D spherical 'paintbrush', and treatment planning reduces to finding the best route of this 'paintbrush' to 'paint' a 3D tumor volume. Under our dose-painting concept, gamma knife radiosurgery becomes dynamic, where the patient moves continuously under the robotic positioning system. We have implemented a fully automatic dynamic gamma knife radiosurgery treatment planning system, where the inverse planning problem is solved as a traveling salesman problem combined with constrained least-square optimizations. We have also carried out experimental studies of dynamic gamma knife radiosurgery and showed the following. (1) Dynamic gamma knife radiosurgery is ideally suited for fully automatic inverse planning, where high quality radiosurgery plans can be obtained in minutes of computation. (2) Dynamic radiosurgery plans are more conformal than step-and-shoot plans and can maintain a steep dose gradient (around 13% per mm) between the target tumor volume and the surrounding critical structures. (3) It is possible to prescribe multiple isodose lines with dynamic gamma knife radiosurgery, so that the treatment can cover the periphery of the target volume while escalating the dose for high tumor burden regions. (4) With dynamic gamma knife radiosurgery, one can obtain a family of plans representing a tradeoff between the delivery time and the dose distributions, thus giving the clinician one more dimension of flexibility of choosing a plan based on the clinical situations.

Stereotactic body radiation therapy (SBRT) uses high doses of radiation to treat tumors. The cell survival behavior at these high doses is subject to debate. We investigated this high-dose region by fitting a variety of formulas to cell survival data. Each of the formulas is motivated by a discussion of the theory of cell survival. Fourteen cell lines are examined. These are fit to a variety of equations. Among the equations include the traditional single-hit multi-target and linear quadratic as well as recent proposals such as the universal survival curve (USC). The χ²/df of each fit is compared to determine the best fit. While no formula is clearly superior for all cell lines, the newer formulas often provide better fits than the single-hit multi-target and linear quadratic. We recommend that the more recent formula discussed herein be used over the linear quadratic in dealing with the high-dose regions dealt with in SBRT.

The values of the replacement correction factors (P_repl, or in the IAEA's notation p_disp_cav) used for cylindrical chambers in high-energy photon beams represent one of the most significant differences between the AAPM and the IAEA dosimetry protocols. In a previous study (Wang L L W and Rogers D W O 2008 Med. Phys.35 1747–55), we found that the AAPM protocol adopted incorrect values of P_repl for cylindrical chambers in photon beams. For a ⁶⁰Co beam, the calculated P_repl value is 0.5% higher than the AAPM value and about 1% higher than the IAEA value. It was still not clear why the IAEA values, which are based on measurements by Johansson et al, are incorrect. In this study, EGSnrc Monte Carlo simulation codes are used to simulate Johansson et al's experimental procedures for determining P_repl values. The simulation results agree well with the measurements if the chamber responses versus depth are normalized at d_max as was apparently done in the experiments as it was believed that the chambers of different radii gave the same maximum reading at the respective d_max. However, if the chamber responses are not normalized, then the simulated experimental results lead to a result which agrees well with the P_repl values calculated by the standard Monte Carlo methods. This demonstrates that the normalization procedure used in the experiments is incorrect as is based on an incorrect assumption, and thus the interpretation of Johansson et al's experimental values as P_repl (p_dis) in the IAEA TRS-398 Code of Practice is wrong. The values of P_repl for cylindrical chambers of different radii in various high-energy photon beams are calculated and an empirical formula is given.

Monte Carlo simulation was employed to calculate the response of TLD-100 chips under irradiation conditions such as those found during accelerated partial breast irradiation with the MammoSite radiation therapy system. The absorbed dose versus radius in the last 0.5 cm of the treated volume was also calculated, employing a resolution of 20 µm, and a function that fits the observed data was determined. Several clinically relevant irradiation conditions were simulated for different combinations of balloon size, balloon-to-surface distance and contents of the contrast solution used to fill the balloon. The thermoluminescent dosemeter (TLD) cross-calibration factors were derived assuming that the calibration of the dosemeters was carried out using a Cobalt 60 beam, and in such a way that they provide a set of parameters that reproduce the function that describes the behavior of the absorbed dose versus radius curve. Such factors may also prove to be useful for those standardized laboratories that provide postal dosimetry services.

This paper describes a comprehensive method for determining the geometric alignment parameters for cone-beam scanners (often called calibrating the scanners or performing geometric calibration). The method is applicable to x-ray scanners using area detectors, or to SPECT systems using pinholes or cone-beam converging collimators. Images of an alignment test object (calibration phantom) fixed in the field of view of the scanner are processed to determine the nine geometric parameters for each view. The parameter values are found directly using formulae applied to the projected positions of the test object marker points onto the detector. Each view is treated independently, and no restrictions are made on the position of the cone vertex, or on the position or orientation of the detector. The proposed test object consists of 14 small point-like objects arranged with four points on each of three orthogonal lines, and two points on a diagonal line. This test object is shown to provide unique solutions for all possible scanner geometries, even when partial measurement information is lost by points superimposing in the calibration scan. For the many situations where the cone vertex stays reasonably close to a central plane (for circular, planar, or near-planar trajectories), a simpler version of the test object is appropriate. The simpler object consists of six points, two per orthogonal line, but with some restrictions on the positioning of the test object. This paper focuses on the principles and mathematical justifications for the method. Numerical simulations of the calibration process and reconstructions using estimated parameters are also presented to validate the method and to provide evidence of the robustness of the technique.

Absorbed dose distributions in 3D imparted by a single ⁹⁰Sr/⁹⁰Y beta particle seed source of the type used for intravascular brachytherapy were investigated. A polymer gel dosimetry medium was used as a dosemeter and phantom, while a special high-resolution laser CT scanner with a spatial resolution of 100 µm in all dimensions was used to quantify the data. We have measured the radial dose function, g_L(r), observing that g_L(r) increases to a maximum value and then decreases as the distance from the seed increases. This is in good agreement with previous data obtained with radiochromic film and thermoluminescent dosemeters (TLDs), even if the TLDs underestimate the dose at distances very close to the seed. Contrary to the measurements, g_L(r) calculated through Monte Carlo simulations and reported previously steadily decreases without a local maximum as a function of the distance from the seed. At distances less than 1.5 mm, differences of more than 20% are observed between the measurements and the Monte Carlo calculations. This difference could be due to a possible underestimation of the energy absorbed into the seed core and encapsulation in the Monte Carlo simulation, as a consequence of the unknown precise chemical composition of the core and its respective density for this seed. The results suggest that g_L(r) can be measured very close to the seed with a relative uncertainty of about 1% to 2%. The dose distribution is isotropic only at distances greater than or equal to 2 mm from the seed and is almost symmetric, independent of the depth. This study indicates that polymer gel coupled with the special small format laser CT scanner are valid and accurate methods for measuring the dose distribution at distances close to an intravascular brachytherapy seed.

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can give new insights into how the brain functions. However, the strong electromagnetic field of the MR scanner generates artifacts that obscure the EEG and diminish its readability. Among them, the ballistocardiographic artifact (BCGa) that appears on the EEG is believed to be related to blood flow in scalp arteries leading to electrode movements. Average artifact subtraction (AAS) techniques, used to remove the BCGa, assume a deterministic nature of the artifact. This assumption may be too strong, considering the blood flow related nature of the phenomenon. In this work we propose a new method, based on canonical correlation analysis (CCA) and blind source separation (BSS) techniques, to reduce the BCGa from simultaneously recorded EEG–fMRI. We optimized the method to reduce the user's interaction to a minimum. When tested on six subjects, recorded in 1.5 T or 3 T, the average artifact extracted with BSS–CCA and AAS did not show significant differences, proving the absence of systematic errors. On the other hand, when compared on the basis of intra-subject variability, we found significant differences and better performance of the proposed method with respect to AAS. We demonstrated that our method deals with the intrinsic subject variability specific to the artifact that may cause averaging techniques to fail.

The purpose of this work is to develop an online plan modification technique to compensate for the interfractional anatomic changes for prostate cancer intensity-modulated radiation therapy (IMRT) treatment based on daily cone beam CT (CBCT) images. In this proposed technique, pre-treatment CBCT images are acquired after the patient is set up on the treatment couch using an in-room laser with the guidance of the setup skin marks. Instead of moving the couch to rigidly align the target or re-planning using the CBCT images, we modify the original IMRT plan to account for the interfractional target motion and deformation based on the daily CBCT image feedback. The multileaf collimator (MLC) leaf positions for each subfield are automatically adjusted in the proposed algorithm based on the position and shape changes of target projection in the beam's eye view (BEV). Three typical prostate cases were adopted to evaluate the proposed technique, and the results were compared with those obtained with bony-structure-based rigid translation correction, prostate-based correction and CBCT-based re-planning strategies. The study revealed that the proposed modification technique is superior to the bony-structure-based and prostate-based correction techniques, especially when interfractional target deformation exists. Its dosimetric performance is closer to that of the re-planned strategy, but with much higher efficiency, indicating that the introduced online CBCT-guided plan modification technique may be an efficient and practical method to compensate for the interfractional target position and shape changes for prostate IMRT.

¹⁸F-fluoro-deoxy-glucose (¹⁸F-FDG) positron emission tomography (PET) is one of the most sensitive and specific imaging modalities for the diagnosis of non-small cell lung cancer. A drawback of PET is that it requires several minutes of acquisition per bed position, which results in images being affected by respiratory blur. Respiratory gating techniques have been developed to deal with respiratory motion in the PET images. However, these techniques considerably increase the level of noise in the reconstructed images unless the acquisition time is increased. The aim of this paper is to evaluate a four-dimensional (4D) image reconstruction algorithm that combines the acquired events in all the gates whilst preserving the motion deblurring. This algorithm was compared to classic ordered subset expectation maximization (OSEM) reconstruction of gated and non-gated images, and to temporal filtering of gated images reconstructed with OSEM. Two datasets were used for comparing the different reconstruction approaches: one involving the NEMA IEC/2001 body phantom in motion, the other obtained using Monte-Carlo simulations of the NCAT breathing phantom. Results show that 4D reconstruction reaches a similar performance in terms of the signal-to-noise ratio (SNR) as non-gated reconstruction whilst preserving the motion deblurring. In particular, 4D reconstruction improves the SNR compared to respiratory-gated images reconstructed with the OSEM algorithm. Temporal filtering of the OSEM-reconstructed images helps improve the SNR, but does not achieve the same performance as 4D reconstruction. 4D reconstruction of respiratory-gated images thus appears as a promising tool to reach the same performance in terms of the SNR as non-gated acquisitions while reducing the motion blur, without increasing the acquisition time.

Monte Carlo simulations play an important role in positron emission tomography (PET) imaging, as an essential tool for the research and development of new scanners and for advanced image reconstruction. PeneloPET, a PET-dedicated Monte Carlo tool, is presented and validated in this work. PeneloPET is based on PENELOPE, a Monte Carlo code for the simulation of the transport in matter of electrons, positrons and photons, with energies from a few hundred eV to 1 GeV. PENELOPE is robust, fast and very accurate, but it may be unfriendly to people not acquainted with the FORTRAN programming language. PeneloPET is an easy-to-use application which allows comprehensive simulations of PET systems within PENELOPE. Complex and realistic simulations can be set by modifying a few simple input text files. Different levels of output data are available for analysis, from sinogram and lines-of-response (LORs) histogramming to fully detailed list mode. These data can be further exploited with the preferred programming language, including ROOT. PeneloPET simulates PET systems based on crystal array blocks coupled to photodetectors and allows the user to define radioactive sources, detectors, shielding and other parts of the scanner. The acquisition chain is simulated in high level detail; for instance, the electronic processing can include pile-up rejection mechanisms and time stamping of events, if desired. This paper describes PeneloPET and shows the results of extensive validations and comparisons of simulations against real measurements from commercial acquisition systems. PeneloPET is being extensively employed to improve the image quality of commercial PET systems and for the development of new ones.

We investigated the physical characteristics of two complementary metal oxide semiconductor (CMOS) mammography detectors. The detectors featured 14-bit image acquisition, 50 µm detector element (del) size and an active area of 5 cm × 5 cm. One detector was a passive-pixel sensor (PPS) with signal amplification performed by an array of amplifiers connected to dels via data lines. The other detector was an active-pixel sensor (APS) with signal amplification performed at each del. Passive-pixel designs have higher read noise due to data line capacitance, and the APS represents an attempt to improve the noise performance of this technology. We evaluated the detectors' resolution by measuring the modulation transfer function (MTF) using a tilted edge. We measured the noise power spectra (NPS) and detective quantum efficiencies (DQE) using mammographic beam conditions specified by the IEC 62220-1-2 standard. Our measurements showed the APS to have much higher gain, slightly higher MTF, and higher NPS. The MTF of both sensors approached 10% near the Nyquist limit. DQE values near dc frequency were in the range of 55–67%, with the APS sensor DQE lower than the PPS DQE for all frequencies. Our results show that lower read noise specifications in this case do not translate into gains in the imaging performance of the sensor. We postulate that the lower fill factor of the APS is a possible cause for this result.

We investigate a novel detector using a lutetium oxyorthosilicate (LSO) scintillator and YGG (yttrium–aluminum–gallium oxide:cerium, Y₃(Al,Ga)₅O₁₂:Ce) phosphor to construct a detector with continuous depth-of-interaction (DOI) information. The far end of the LSO scintillator is coated with a thin layer of YGG phosphor powder which absorbs some fraction of the LSO scintillation light and emits wavelength-shifted photons with a characteristic decay time of ∼50 ns. The near end of the LSO scintillator is directly coupled to a photodetector. The photodetector detects a mixture of the LSO light and the light emitted by YGG. With appropriate placement of the coating, the ratio of the light converted from the YGG coating with respect to the unconverted LSO light can be made to depend on the interaction depth. DOI information can then be estimated by inspecting the overall light pulse decay time. Experiments were conducted to optimize the coating method. 19 ns decay time differences across the length of the detector were achieved experimentally when reading out a 1.5 × 1.5 × 20 mm³ LSO crystal with unpolished surfaces and half-coated with YGG phosphor. The same coating scheme was applied to a 4 × 4 LSO array. Pulse shape discrimination (PSD) methods were studied to extract DOI information from the pulse shape changes. The DOI full-width-half-maximum (FWHM) resolution was found to be ∼8 mm for this 2 cm thick array.

Hybrid pixel detectors, originally developed for tracking particles in high-energy physics experiments, have recently been used in material sciences and macromolecular crystallography. Their capability to count single photons and to apply a threshold on the photon energy suggests that they could be optimal digital x-ray detectors in low energy beams such as for small animal computed tomography (CT). To investigate this issue, we have studied the imaging performance of photon counting hybrid pixel detectors based on the XPAD3-S chip. Two detectors are considered, connected either to a Si or to a CdTe sensor, the latter being of interest for its higher efficiency. Both a standard 'International Electrotechnical Commission' (IEC) mammography beam and a beam used for mouse CT results published in the literature are employed. The detector stability, linearity and noise are investigated as a function of the dose for several imaging exposures (∼0.1–400 µGy). The perfect linearity of both detectors is confirmed, but an increase in internal noise for counting statistics higher than ∼5000 photons has been found, corresponding to exposures above ∼110 µGy and ∼50 µGy for the Si and CdTe sensors, respectively. The noise power spectrum (NPS), the modulation transfer function (MTF) and the detective quantum efficiency (DQE) are then measured for two energy threshold configurations (5 keV and 18 keV) and three doses (∼3, 30 and 300 µGy), in order to obtain a complete estimation of the detector performances. In general, the CdTe sensor shows a clear superiority with a maximal DQE(0) of ∼1, thanks to its high efficiency (∼100%). The DQE of the Si sensor is more dependent on the radiation quality, due to the energy dependence of its efficiency its maximum is ∼0.4 with respect to the softer radiation. Finally, we compare the XPAD3-S DQE with published curves of other digital devices in a similar radiation condition. The XPAD3-S/CdTe detector appears to be the best with the highest DQE at low frequency, although some improvements are expected to reduce the increase of noise with the counts statistics and to guarantee a better stability of the detector response.

Blood flow characteristics (e.g. velocity, pressure, shear stress, streamline and volumetric flow rate) are effective tools in diagnosis of cardiovascular diseases such as atherosclerotic plaque, aneurism and cardiac muscle failure. Noninvasive estimation of cardiovascular blood flow characteristics is mostly limited to the measurement of velocity components by medical imaging modalities. Once the velocity field is obtained from the images, other flow characteristics within the cardiovascular system can be determined using algorithms relating them to the velocity components. In this work, we propose an analytical flow phantom to evaluate these algorithms accurately. The Navier–Stokes equations are used to derive this flow phantom. The exact solution of these equations obtains analytical expression for the flow characteristics inside the domain. Features such as pulsatility, incompressibility and viscosity of flow are included in a three-dimensional domain. The velocity domain of the resulted system is presented as reference images. These images could be employed to evaluate the performance of different flow characteristic algorithms. In this study, we also present some applications of the obtained phantom. The calculation of pressure domain from velocity data, volumetric flow rate, wall shear stress and particle trace are the characteristics whose algorithms are evaluated here. We also present the application of this phantom in the analysis of noisy and low-resolution images. The presented phantom can be considered as a benchmark test to compare the accuracy of different flow characteristic algorithms.

Medical images usually suffer from a partial volume effect (PVE), which may degrade the accuracy of any quantitative information extracted from the images. Our aim was to recreate accurate radioactivity concentration and time–activity curves (TACs) by microPET R4 quantification using ensemble learning independent component analysis (EL-ICA). We designed a digital cardiac phantom for this simulation and in order to evaluate the ability of EL-ICA to correct the PVE, the simulated images were convoluted using a Gaussian function (FWHM = 1–4 mm). The robustness of the proposed method towards noise was investigated by adding statistical noise (SNR = 2–16). During further evaluation, another set of cardiac phantoms were generated from the reconstructed images, and Poisson noise at different levels was added to the sinogram. In real experiments, four rat microPET images and a number of arterial blood samples were obtained; these were used to estimate the metabolic rate of FDG (MR_FDG). Input functions estimated using the FastICA method were used for comparison. The results showed that EL-ICA could correct PVE in both the simulated and real cases. After correcting for the PVE, the errors for MR_FDG, when estimated by the EL-ICA method, were smaller than those when TACs were directly derived from the PET images and when the FastICA approach was used.

The authors of a recent paper (McNiven et al2008 Phys. Med. Biol.53 5029–43) measured the volume of a particular type of a small ionization chamber using CT images. Using four Exradin A1SL chambers, they find that the volume measured using CT imaging is, on average, 4.3% larger than the value derived from the chamber calibration coefficient. Although they point out that the effective chamber volume is defined by electric field lines between the collector and the chamber body, they do not estimate how the mechanical volume might differ from the effective volume. We have used a commercial software package to calculate the electric field in the cavity and we show that the field lines define a volume that is about 11% smaller than the mechanical volume. We also show that the effective volume is very sensitive to small changes in the chamber geometry near the base of the collector. We conclude that simply determining the mechanical volume without careful consideration of the electric field lines within the cavity is not a useful dosimetric technique.

Air ionization chamber dosimetry plays a crucial role in international dose calibration for the radiotherapy clinical environment. Micro-CT images of ion chambers can play an important role in quality assurance of these devices by detecting internal geometry, materials and defects non-invasively, as we demonstrated (McNiven et al 2008 Phys. Med. Biol.53 5029–43). We also suggested that electric-field simulation based upon these accurate chamber-specific 3D images rather than manufacturer blueprints could be valuable in assessing ionometric sensitivity. As recently performed by Ross et al these electric field simulations play a vital role in understanding key components that contribute to the chamber sensitive volume and ionization calibration coefficients.

In table 1, the 'Number of beamlets/beam spots' was reversed for IMPT-SS and IMPT-DGT. The actual number of beam spots for IMPT-SS was 45 590, and the number of beam spots for IMPT-DGT was 12 569.

In section 4.6, paragraph 2, sentence 2, '¹⁶Cu-ATSM' should read '⁶¹Cu-ATSM'.