Investigating end-to-end accuracy of image guided radiation treatment delivery using a micro-irradiator.

There is significant interest in delivering precisely targeted small-volume radiation treatments, in the pre-clinical setting, to study dose-volume relationships with tumour control and normal tissue damage. For these studies it is vital that image guidance systems and target positioning are accurately aligned (IGRT), in order to deliver dose precisely and accurately according to the treatment plan. In this work we investigate the IGRT targeting accuracy of the X-RAD 225 Cx system from Precision X-Ray using high-resolution 3D dosimetry techniques. Small cylindrical PRESAGE® dosimeters were used with optical-CT readout (DMOS) to verify the accuracy of 2.5, 1.0, and 5.0 mm X-RAD cone attachments. The dosimeters were equipped with four target points, visible on both CBCT and optical-CT, at which a 7-field coplanar treatment plan was delivered with the respective cone. Targeting accuracy (distance to agreement between the target point and delivery isocenter) and cone alignment (isocenter precision under gantry rotation) were measured using the optical-CT images. Optical-CT readout of the first 2.5 mm cone dosimeter revealed a significant targeting error of 2.1 ± 0.6 mm and a cone misalignment of 1.3 ± 0.1 mm. After the IGRT hardware and software had been recalibrated, these errors were reduced to 0.5 ± 0.1 and 0.18 ± 0.04 mm respectively, within the manufacturer specified 0.5 mm. Results from the 1.0 mm cone were 0.5 ± 0.3 mm targeting accuracy and 0.4 ± 0.1 mm cone misalignment, within the 0.5 mm specification. The results from the 5.0 mm cone were 1.0 ± 0.2 mm targeting accuracy and 0.18 ± 0.06 mm cone misalignment, outside of accuracy specifications. Quality assurance of small field IGRT targeting and delivery accuracy is a challenging task. The use of a 3D dosimetry technique, where targets are visible on both CBCT and optical-CT, enabled identification and quantification of a targeting error in 3D. After correction, the targeting accuracy of the irradiator was verified to be within 0.5 mm (or 1.0 mm for the 5.0 mm cone) and the cone alignment was verified to be within 0.2 mm (or 0.4 mm for the 1.0 mm cone). The PRESAGE®/DMOS system proved valuable for end-to-end verification of small field IGRT capabilities.

How effective can optical-CT 3D dosimetry be without refractive fluid matching?

Achieving accurate optical CT 3D dosimetry without the use of viscous refractive index (RI) matching fluids would greatly increase convenience. Software has been developed to simulate optical CT 3D dosimetry for a range of scanning configurations including parallel-beam, point and converging light sources. For each configuration the efficacy of 3 refractive media were investigated: air, water, and a fluid closely matched to Presage (RI = 1.00, 1.33 and 1.49 respectively). The results revealed that the useable radius of the dosimeter (i.e. where data was within 2% of truth) reduced to 68% for water-matching, and 31% for dry-scanning in air. Point source incident ray geometry produced slightly more favourable results, although variation between the three geometries was relatively small. The required detector size however, increased by a factor six for dry-scanning, introducing cost penalties. For applications where dose information is not required in the periphery, some dry and low-viscous matching configurations may be feasible.

How accurate is image guided radiation therapy (IGRT) delivered with a micro-irradiator?

There is significant interest in delivering precisely targeted small-volume radiation treatments, in the pre-clinical setting, to study dose-volume relationships with tumor control and normal tissue damage. In this work we investigate the IGRT targeting accuracy of the XRad225Cx system from Precision x-Ray using high resolution 3D dosimetry techniques. Initial results revealed a significant targeting error of about 2.4mm. This error was reduced to within 0.5mm after the IGRT hardware and software had been recalibrated. The facility for 3D dosimetry was essential to gain a comprehensive understanding of the targeting error in 3D.

Towards comprehensive characterization of Cs-137 Seeds using PRESAGE® dosimetry with optical tomography.

We describe a method to directly measure the radial dose and anisotropy functions of brachytherapy sources using polyurethane based dosimeters read out with optical CT. We measured the radial dose and anisotropy functions for a Cs-137 source using a PRESAGE® dosimeter (9.5cm diameter, 9.2cm height) with a 0.35cm channel drilled for source placement. The dosimeter was immersed in water and irradiated to 5.3Gy at 1cm. Pre- and post-irradiation optical CT scans were acquired with the Duke Large field of view Optical CT Scanner (DLOS) and dose was reconstructed with 0.5mm isotropic voxel size. The measured radial dose factor matched the published fit to within 3% for radii between 0.5-3.0cm, and the anisotropy function matched to within 4% except for θ near 0° and 180° and radii >3cm. Further improvements in measurement accuracy may be achieved by optimizing dose, using the high dynamic range scanning capability of DLOS, and irradiating multiple dosimeters. Initial simulations indicate an 8 fold increase in dose is possible while still allowing sufficient light transmission during optical CT. A more comprehensive measurement may be achieved by increasing dosimeter size and flipping the source orientation between irradiations.

A nonparametric feature for neonatal EEG seizure detection based on a representation of pseudo-periodicity.

Automated methods of neonatal EEG seizure detection attempt to highlight the evolving, stereotypical, pseudo-periodic, nature of EEG seizure while rejecting the nonstationary, modulated, coloured stochastic background in the presence of various EEG artefacts. An important aspect of neonatal seizure detection is, therefore, the accurate representation and detection of pseudo-periodicity in the neonatal EEG. This paper describes a method of detecting pseudo-periodic components associated with neonatal EEG seizure based on a novel signal representation; the nonstationary frequency marginal (NFM). The NFM can be considered as an alternative time-frequency distribution (TFD) frequency marginal. This method integrates the TFD along data-dependent, time-frequency paths that are automatically extracted from the TFD using an edge linking procedure and has the advantage of reducing the dimension of a TFD. The reduction in dimension simplifies the process of estimating a decision statistic designed for the detection of the pseudo-periodicity associated with neonatal EEG seizure. The use of the NFM resulted in a significant detection improvement compared to existing stationary and nonstationary methods. The decision statistic estimated using the NFM was then combined with a measurement of EEG amplitude and nominal pre- and post-processing stages to form a seizure detection algorithm. This algorithm was tested on a neonatal EEG database of 18 neonates, 826 h in length with 1389 seizures, and achieved comparable performance to existing second generation algorithms (a median receiver operating characteristic area of 0.902; IQR 0.835-0.943 across 18 neonates).

A matching pursuit-based signal complexity measure for the analysis of newborn EEG.

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity (RSC), which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed RSC measure is used in the analysis of newborn electroencephalogram (EEG). To do this, firstly, a time-frequency decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).