Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

Predicting the likelihood of QA failure using treatment plan accuracy metrics

This study used automated data processing techniques to calculate a set of novel treatment plan accuracy metrics, and investigate their usefulness as predictors of quality assurance (QA) success and failure. 151 beams from 23 prostate and cranial IMRT treatment plans were used in this study. These plans had been evaluated before treatment using measurements with a diode array system. The TADA software suite was adapted to allow automatic batch calculation of several proposed plan accuracy metrics, including mean field area, small-aperture, off-axis and closed-leaf factors. All of these results were compared the gamma pass rates from the QA measurements and correlations were investigated. The mean field area factor provided a threshold field size (5 cm2, equivalent to a 2.2 x 2.2 cm2 square field), below which all beams failed the QA tests. The small aperture score provided a useful predictor of plan failure, when averaged over all beams, despite being weakly correlated with gamma pass rates for individual beams. By contrast, the closed leaf and off-axis factors provided information about the geometric arrangement of the beam segments but were not useful for distinguishing between plans that passed and failed QA. This study has provided some simple tests for plan accuracy, which may help minimise time spent on QA assessments of treatments that are unlikely to pass.

Using narrow beam profiles to quantify focal spot size, for accurate Monte Carlo simulations of SRS/SRT systems

This study investigates the variation of photon field penumbra shape with initial electron beam diameter, for very narrow beams. A Varian Millenium MLC (Varian Medical Systems, Palo Alto, USA) and a Brainlab m3 microMLC (Brainlab AB. Feldkirchen, Germany) were used, with one Varian iX linear accelerator, to produce fields that were (nominally) 0.20 cm across. Dose profiles for these fields were measured using radiochromic film and compared with the results of simulations completed using BEAMnrc and DOSXYZnrc, where the initial electron beam was set to FWHM = 0.02, 0.10, 0.12, 0.15, 0.20 and 0.50 cm. Increasing the electron-beam FWHM produced increasing occlusion of the photon source by the closely spaced collimator leaves and resulted in blurring of the simulated profile widths from 0.26 to 0.64 cm, for the MLC, from 0.12 to 0.43 cm, for the microMLC. Comparison with measurement data suggested that the electron spot size in the clinical linear accelerator was between FWHM = 0.10 and 0.15 cm, encompassing the result of our previous output-factor based work, which identified a FWHM of 0.12. Investigation of narrow-beam penumbra variation has been found to be a useful procedure, with results varying noticeably with linear accelerator spot size and allowing FWHM estimates obtained using other methods to be verified.

The influence of Monte Carlo source parameters on detector design and dose perturbation in small field dosimetry

To obtain accurate Monte Carlo simulations of small radiation fields, it is important model the initial source parameters (electron energy and spot size) accurately. However recent studies have shown that small field dosimetry correction factors are insensitive to these parameters. The aim of this work is to extend this concept to test if these parameters affect dose perturbations in general, which is important for detector design and calculating perturbation correction factors. The EGSnrc C++ user code cavity was used for all simulations. Varying amounts of air between 0 and 2 mm were deliberately introduced upstream to a diode and the dose perturbation caused by the air was quantified. These simulations were then repeated using a range of initial electron energies (5.5 to 7.0 MeV) and electron spot sizes (0.7 to 2.2 FWHM). The resultant dose perturbations were large. For example 2 mm of air caused a dose reduction of up to 31% when simulated with a 6 mm field size. However these values did not vary by more than 2 % when simulated across the full range of source parameters tested. If a detector is modified by the introduction of air, one can be confident that the response of the detector will be the same across all similar linear accelerators and the Monte Carlo modelling of each machine is not required.

Differential substrate behaviours of ethylene oxide and propylene oxide towards human glutathione transferase theta hGSTT1-1

The transformation of ethylene oxide (EO), propylene oxide (PO) and 1- butylene oxide (1-BuO) by human glutathione transferase theta (hGSTT1-1) was studied comparatively using 'conjugator' (GSTT1 + individuals) erythrocyte lysates. The relative sequence of velocity of enzymic transformation was PO > EO >> 1-BuO. The faster transformation of PO compared to EO was corroborated in studies with human and rat GSTT1-1 (hGSTT1-1 and rGSTT1-1, respectively) expressed by Salmonella typhimurium TA1535. This sequence of reactivities of homologous epoxides towards GSTT1-1 contrasts to the sequence observed in homologous alkyl halides (methyl bromide, MBr; ethyl bromide, EtBr; n-propyl bromide, PrBr) where the relative sequence MeBr >> EtBr > PrBr is observed. The higher reactivity towards GSTT1-1 of propylene oxide compared to ethylene oxide is consistent with a higher chemical reactivity. This is corroborated by experimental data of acid-catalysed hydrolysis of a number of aliphatic epoxides, including ethylene oxide and propylene oxide and consistent with semi-empirical molecular orbital modelings.

The spectrum of HIV-1 related cancers in South Africa

Despite the high prevalence of infection by the Human Immunodeficiency Virus (HIV) in South Africa, information on its association with cancer is sparse. Our study was carried out to examine the relationship between HIV and a number of cancer types or sites that are common in South Africa. A total of 4,883 subjects, presenting with a cancer or cardiovascular disease at the 3 tertiary referral hospitals in Johannesburg, were interviewed and had blood tested for HIV. Odds ratios associated with HIV infection were calculated by using unconditional logistic regression models for 16 major cancer types where data was available for 50 or more patients. In the comparison group, the prevalence of HIV infection was 8.3% in males and 9.1% in females. Significant excess risks associated with HIV infection were found for Kaposi's sarcoma (OR=21.9, 95% CI=12.5–38.6), non-Hodgkin lymphoma (OR=5.0, 95%CI=2.7–9.5), vulval cancer (OR=4.8, 95%CI=1.9–12.2) and cervical cancer (OR=1.6, 95%CI=1.1–2.3) but not for any of the other major cancer types examined, including Hodgkin disease, multiple myeloma and lung cancer. In Johannesburg, South Africa, HIV infection was associated with significantly increased risks of Kaposi's sarcoma, non-Hodgkin lymphoma and cancers of the cervix and the vulva. The relative risks for Kaposi's sarcoma and non-Hodgkin lymphoma associated with HIV infection were substantially lower than those found in the West.