Phil Evans

Assessing the effect of electron density in photon dose calculations.

Photon dose calculation algorithms (such as the pencil beam and collapsed cone, CC) model the attenuation of a primary photon beam in media other than water, by using pathlength scaling based on the relative mass density of the media to water. In this study, we assess if differences in the electron density between the water and media, with different atomic composition, can influence the accuracy of conventional photon dose calculations algorithms. A comparison is performed between an electron-density scaling method and the standard mass-density scaling method for (i) tissues present in the human body (such as bone, muscle, etc.), and for (ii) water-equivalent plastics, used in radiotherapy dosimetry and quality assurance. We demonstrate that the important material property that should be taken into account by photon dose algorithms is the electron density, and not the mass density. The mass-density scaling method is shown to overestimate, relative to electrondensity predictions, the primary photon fluence for tissues in the human body and water-equivalent plastics, where 6%-7% and 10% differences were observed respectively for bone and air. However, in the case of patients, differences are expected to be smaller due to the large complexity of a treatment plan and of the patient anatomy and atomic composition and of the smaller thickness of bone/air that incident photon beams of a treatment plan may have to traverse. Differences have also been observed for conventional dose algorithms, such as CC, where an overestimate of the lung dose occurs, when irradiating lung tumors. The incorrect lung dose can be attributed to the.incorrect modeling of the photon beam attenuation through the rib cage (thickness of 2-3 cm in bone upstream of the lung tumor) and through the lung and the oversimplified modeling of electron transport in convolution algorithms. In the present study, the overestimation of the primary photon fluence, using the mass-density scaling method, was shown to be a consequence of the differences in the hydrogen content between the various media studied and water. On the other hand, the electron-density scaling method was shown to predict primary photon fluence in media other than water to within 1%-2% for all the materials studied and for energies up to 5 MeV. For energies above 5 MeV, the accuracy of the electron-density scaling method was shown to depend on the photon energy, where for materials with a high content of calcium (such as bone, cortical bone) or for primary photon energies above 10 MeV, the pair-production process could no longer be neglected. The electron-density scaling method was extended to account for pair-production attenuation of the primary photons. Therefore the scaling of the dose distributions in media other than water became dependent on the photon energy. The extended electron-scaling method was shown to estimate the photon range to within 1% for all materials studied and for energies from 100 keV to 20 MeV, allowing it to be used to scale dose distributions to media other than water and generated by clinical radiotherapy photon beams with accelerator energies from 4 to 20 MV.

Monte Carlo modelling of a-Si EPID response: The effect of spectral variations with field size and position

This study focused on predicting the electronic portal imaging device (EPID) image of intensity modulated radiation treatment (IMRT) fields in the absence of attenuation material in the beam with Monte Carlo methods. As IMRT treatments consist of a series of segments of various sizes that are not always delivered on the central axis, large spectral variations may be observed between the segments. The effect of these spectral variations on the EPID response was studied with fields of various sizes and off-axis positions. A detailed description of the EPID was implemented in a Monte Carlo model. The EPID model was validated by comparing the EPID output factors for field sizes between 1 x 1 and 26 x 26 cm2 at the isocenter. The Monte Carlo simulations agreed with the measurements to within 1.5%. The Monte Carlo model succeeded in predicting the EPID response at the center of the fields of various sizes and offsets to within 1% of the measurements. Large variations (up to 29%) of the EPID response were observed between the various offsets. The EPID response increased with field size and with field offset for most cases. The Monte Carlo model was then used to predict the image of a simple test IMRT field delivered on the beam axis and with an offset. A variation of EPID response up to 28% was found between the on- and off-axis delivery. Finally, two clinical IMRT fields were simulated and compared to the measurements. For all IMRT fields, simulations and measurements agreed within 3%-0.2 cm for 98% of the pixels. The spectral variations were quantified by extracting from the spectra at the center of the fields the total photon yield (Ytotal), the photon yield below 1 MeV (Ylow), and the percentage of photons below 1 MeV (Plow). For the studied cases, a correlation was shown between the EPID response variation and Ytotal, Ylow, and Plow.

Proton radiography and tomography with application to proton therapy

Proton radiography and tomography have long promised benefit for proton therapy. Their first suggestion was in the early 1960s and the first published proton radiographs and CT images appeared in the late 1960s and 1970s, respectively. More than just providing anatomical images, proton transmission imaging provides the potential for the more accurate estimation of stopping-power ratio inside a patient and hence improved treatment planning and verification. With the recent explosion in growth of clinical proton therapy facilities, the time is perhaps ripe for the imaging modality to come to the fore. Yet many technical challenges remain to be solved before proton CT scanners become commonplace in the clinic. Research and development in this field is currently more active than at any time with several prototype designs emerging. This review introduces the principles of proton radiography and tomography, their historical developments, the raft of modern prototype systems and the primary design issues.

The use of the Active Breathing Coordinator throughout radical non-small-cell lung cancer (NSCLC) radiotherapy.

PURPOSE To assess feasibility and reproducibility of an Active Breathing Coordinator (ABC) used throughout radical radiotherapy for non-small-cell lung cancer, and compare lung dosimetric parameters between free-breathing and ABC plans. METHODS AND MATERIALS A total of 18 patients, recruited into an approved study, had free-breathing and ABC breath-hold treatment plans generated. Lung volume, the percentage volume of lung treated to a dose of ≥20 Gy (V(20)), and mean lung dose (MLD) were compared. Treatment (64 Gy in 32 fractions, 5 days/week) was delivered in breath-hold. Repeat breath-hold computed tomography scans were used to assess change in gross tumor volume (GTV) size and position. Setup error was also measured and potential GTV-planning target volume (PTV) margins calculated. RESULTS Seventeen of 18 patients completed radiotherapy using ABC daily. Intrafraction tumor position was consistent, but interfraction variation had mean (range) values of 5.1 (0-25), 3.6 (0-9.7), and 3.5 (0-16.6) mm in the superoinferior (SI), right-left (RL), and anteroposterior (AP) directions, respectively. Tumor moved partially outside the PTV in 5 patients. Mean reduction in GTV from planning to end of treatment was 25% (p = 0.003). Potentially required PTV margins were 18.1, 11.9, and 11.9 mm in SI, RL, and AP directions. ABC reduced V(20) by 13% (p = 0.0001), V(13) by 12% (p = 0.001), and MLD by 13% (p < 0.001) compared with free-breathing; lung volume increased by 41% (p < 0.001). CONCLUSIONS Clinically significant movements of GTV were seen during radiotherapy for non-small-cell lung cancer using ABC. Image guidance is recommended with ABC. The use of ABC can reduce dose volume parameters determining lung toxicity, and might allow for equitoxic radiotherapy dose escalation.

A margin model to account for respiration-induced tumour motion and its variability

In order to reduce the sensitivity of radiotherapy treatments to organ motion, compensation methods are being investigated such as gating of treatment delivery, tracking of tumour position, 4D scanning and planning of the treatment, etc. An outstanding problem that would occur with all these methods is the assumption that breathing motion is reproducible throughout the planning and delivery process of treatment. This is obviously not a realistic assumption and is one that will introduce errors. A dynamic internal margin model (DIM) is presented that is designed to follow the tumour trajectory and account for the variability in respiratory motion. The model statistically describes the variation of the breathing cycle over time, i.e. the uncertainty in motion amplitude and phase reproducibility, in a polar coordinate system from which margins can be derived. This allows accounting for an additional gating window parameter for gated treatment delivery as well as minimizing the area of normal tissue irradiated. The model was illustrated with abdominal motion for a patient with liver cancer and tested with internal 3D lung tumour trajectories. The results confirm that the respiratory phases around exhale are most reproducible and have the smallest variation in motion amplitude and phase (approximately 2 mm). More importantly, the margin area covering normal tissue is significantly reduced by using trajectory-specific margins (as opposed to conventional margins) as the angular component is by far the largest contributor to the margin area. The statistical approach to margin calculation, in addition, offers the possibility for advanced online verification and updating of breathing variation as more data become available.

Tumour bed delineation for partial breast/breast boost radiotherapy: What is the optimal number of implanted markers?

PURPOSE International consensus has not been reached regarding the optimal number of implanted tumour bed (TB) markers for partial breast/breast boost radiotherapy target volume delineation. Four common methods are: insertion of 6 clips (4 radial, 1 deep and 1 superficial), 5 clips (4 radial and 1 deep), 1 clip at the chest wall, and no clips. We compared TB volumes delineated using 6, 5, 1 and 0 clips in women who have undergone wide-local excision (WLE) of breast cancer (BC) with full-thickness closure of the excision cavity, in order to determine the additional margin required for breast boost or partial breast irradiation (PBI) when fewer than 6 clips are used. METHODS Ten patients with invasive ductal BC who had undergone WLE followed by implantation of six fiducial markers (titanium clips) each underwent CT imaging for radiotherapy planning purposes. Retrospective processing of the DICOM image datasets was performed to remove markers and associated imaging artefacts, using an in-house software algorithm. Four observers outlined TB volumes on four different datasets for each case: (1) all markers present (CT6M); (2) the superficial marker removed (CT(5M)); (3) all but the chest wall marker removed (CTCW); (4) all markers removed (CT(0M)). For each observer, the additional margin required around each of TB(0M), TBCW, and TB(5M) in order to encompass TB(6M) was calculated. The conformity level index (CLI) and differences in centre-of-mass (COM) between observers were quantified for CT(0M), CTCW, CT(5M), CT(6M). RESULTS The overall median additional margins required to encompass TB(6M) were 8mm (range 0-28 mm) for TB(0M), 5mm (range 1-13 mm) for TBCW, and 2mm (range 0-7 mm) for TB(5M). CLI were higher for TB volumes delineated using CT(6M) (0.31) CT(5M) (0.32) than for CTCW (0.19) and CT(0M) (0.15). CONCLUSIONS In women who have undergone WLE of breast cancer with full-thickness closure of the excision cavity and who are proceeding to PBI or breast boost RT, target volume delineation based on 0 or 1 implanted markers is not recommended as large additional margins are required to account for uncertainty over true TB location. Five implanted markers (one deep and four radial) are likely to be adequate assuming the addition of a standard 10-15 mm TB-CTV margin. Low CLI values for all TB volumes reflect the sensitivity of low volumes to small differences in delineation and are unlikely to be clinically significant for TB(5M) and TB(6M) in the context of adequate TB-CTV margins.

The susceptibility of IMRT dose distributions to intrafraction organ motion: An investigation into smoothing filters derived from four dimensional computed tomography data

This study investigated the sensitivity of static planning of intensity-modulated beams (IMBs) to intrafraction deformable organ motion and assessed whether smoothing of the IMBs at the treatment-planning stage can reduce this sensitivity. The study was performed with a 4D computed tomography (CT) data set for an IMRT treatment of a patient with liver cancer. Fluence profiles obtained from inverse-planning calculations on a standard reference CT scan were redelivered on a CT scan from the 4D data set at a different part of the breathing cycle. The use of a nonrigid registration model on the 4D data set additionally enabled detailed analysis of the overall intrafraction motion effects on the IMRT delivery during free breathing. Smoothing filters were then applied to the beam profiles within the optimization process to investigate whether this could reduce the sensitivity of IMBs to intrafraction organ motion. In addition, optimal fluence profiles from calculations on each individual phase of the breathing cycle were averaged to mimic the convolution of a static dose distribution with a motion probability kernel and assess its usefulness. Results from nonrigid registrations of the CT scan data showed a maximum liver motion of 7mm in superior-inferior direction for this patient. Dose-volume histogram (DVH) comparison indicated a systematic shift when planning treatment on a motion-frozen, standard CT scan but delivering over a full breathing cycle. The ratio of the dose to 50% of the normal liver to 50% of the planning target volume (PTV) changed up to 28% between different phases. Smoothing beam profiles with a median-window filter did not overcome the substantial shift in dose due to a difference in breathing phase between planning and delivery of treatment. Averaging of optimal beam profiles at different phases of the breathing cycle mainly resulted in an increase in dose to the organs at risk (OAR) and did not seem beneficial to compensate for organ motion compared with using a large margin. Additionally, the results emphasized the need for 4D CT scans when aiming to reduce the internal margin (IM). Using only a single planning scan introduces a systematic shift in the dose distribution during delivery. Smoothing beam profiles either based on a single scan or over the different breathing phases was not beneficial for reducing this shift.

Expected proton signal sizes in the PRaVDA Range Telescope for proton Computed Tomography

Proton radiotherapy has demonstrated benefits in the treatment of certain cancers. Accurate measurements of the proton stopping powers in body tissues are required in order to fully optimise the delivery of such treaments. The PRaVDA Consortium is developing a novel, fully solid state device to measure these stopping powers. The PRaVDA Range Telescope (RT), uses a stack of 24 CMOS Active Pixel Sensors (APS) to measure the residual proton energy after the patient. We present here the ability of the CMOS sensors to detect changes in the signal sizes as the proton traverses the RT, compare the results with theory, and discuss the implications of these results on the reconstruction of proton tracks.

CMOS Active Pixel Sensors as energy-range detectors for proton Computed Tomography

Since the first proof of concept in the early 70s, a number of technologies has been proposed to perform proton CT (pCT), as a means of mapping tissue stopping power for accurate treatment planning in proton therapy. Previous prototypes of energy-range detectors for pCT have been mainly based on the use of scintillator-based calorimeters, to measure proton residual energy after passing through the patient. However, such an approach is limited by the need for only a single proton passing through the energy-range detector in a read-out cycle. A novel approach to this problem could be the use of pixelated detectors, where the independent read-out of each pixel allows to measure simultaneously the residual energy of a number of protons in the same read-out cycle, facilitating a faster and more efficient pCT scan. This paper investigates the suitability of CMOS Active Pixel Sensors (APSs) to track individual protons as they go through a number of CMOS layers, forming an energy-range telescope. Measurements performed at the iThemba Laboratories will be presented and analysed in terms of correlation, to confirm capability of proton tracking for CMOS APSs.

Modelling the Effects of IMRT Delivery: Constraints and Incorporation of Beam Smoothing into Inverse Planning

The problem of obtaining the optimal treatment plan parameters (such as type and energy of radiation, number and direction of beams, intensity profiles etc) for a prescribed dose distribution in radiotherapy is designated as the inverse problem. As indicated in [1], with the emphasis on obtaining the optimum intensity modulated beams (IMB), many inverse planning systems have ignored constraints applied to the functional form of the IMBs themselves.