Computed Tomography Polymer Gel Dosimetry Research Articles

Accuracy and reproducibility in x-ray computed tomography polymer gel dosimetry

This work assesses the overall reproducibility and accuracy of an x-ray computed tomography (CT) polymer gel dosimetry (PGD) system using a N-isopropyl-acrylamide (NIPAM) based polymer gel and investigated what effects the use of generic, inter-batch, and intra-batch gel calibration have on dosimetric and spatial accuracy. Overall excellent spatial and dosimetric accuracy was found with this system for generic, inter-batch calibration methods.

SU-E-T-70: Commissioning a Multislice CT Scanner for X-Ray CT Polymer Gel Dosimetry

Purpose: To commission a multislice computed tomography (CT) scanner for fast and reliable readout of radiation therapy (RT) dose distributions using CT polymer gel dosimetry (PGD). Methods: Commissioning was performed for a 16-slice CT scanner using images acquired through a 1L cylinder filled with water. Additional images were collected using a single slice machine for comparison purposes. The variability in CT number associated with the anode heel effect was evaluated and used to define a new slice-by-slice background image subtraction technique. Image quality was assessed for the multislice system by comparing image noise and uniformity to that of the single slice machine. The consistency in CT number across slices acquired simultaneously using the multislice detector array was also evaluated. Finally, the variability in CT number due to increasing x-ray tube load was measured for the multislice scanner and compared to the tube load effects observed on the single slice machine. Results: Slice-by-slice background subtraction effectively removes the variability in CT number across images acquired simultaneously using the multislice scanner and is the recommended background subtraction method when using a multislice CT system. Image quality for the multislice machine was found to be comparable to that of the single slice scanner.more » Further study showed CT number was consistent across image slices acquired simultaneously using the multislice detector array for each detector configuration of the slice thickness examined. In addition, the multislice system was found to eliminate variations in CT number due to increasing x-ray tube load and reduce scanning time by a factor of 4 when compared to imaging a large volume using a single slice scanner. Conclusion: A multislice CT scanner has been commissioning for CT PGD, allowing images of an entire dose distribution to be acquired in a matter of minutes. Funding support provided by the Natural Sciences and Engineering Research Council of Canada (NSERC)« less

An x-ray CT polymer gel dosimetry prototype: II. Gel characterization and clinical application

This article reports on the dosimetric properties of a new N-isopropylacrylamide, high %T, polymer gel formulation (19.5%T, 23%C), optimized for x-ray computed tomography (CT) polymer gel dosimetry (PGD). In addition, a new gel calibration technique is introduced together with an intensity-modulated radiation therapy (IMRT) treatment validation as an example of a clinical application of the new gel dosimeter. The dosimetric properties investigated include the temporal stability, spatial stability, batch reproducibility and dose rate dependence. The polymerization reaction is found to stabilize after 15 h post-irradiation. Spatial stability investigations reveal a small overshoot in response for gels imaged later than 36 h post-irradiation. Based on these findings, it is recommended that the new gel formulation be imaged between 15–36 h after irradiation. Intra- and inter-batch reproducibility are found to be excellent over the entire range of doses studied (0–28 Gy). A significant dose rate dependence is found for gels irradiated between 100–600 MU min−1. Overall, the new gel is shown to have promising characteristics for CT PGD, however the implication of the observed dose rate dependence for some clinical applications remains to be determined. The new gel calibration method, based on pixel-by-pixel matching of dose and measured CT numbers, is found to be robust and to agree with the previously used region of interest technique. Pixel-by-pixel calibration is the new recommended standard for CT PGD. The dose resolution for the system was excellent, ranging from 0.2–0.5 Gy for doses between 0–20 Gy and 0.3–0.6 Gy for doses beyond 20 Gy. Comparison of the IMRT irradiation with planned doses yields excellent results: gamma pass rate (3%, 3 mm) of 99.3% at the isocentre slice and 93.4% over the entire treated volume.

Adaptive mean filtering for noise reduction in CT polymer gel dosimetry

X-ray computed tomography (CT) as a method of extracting 3D dose information from irradiated polymer gel dosimeters is showing potential as a practical means to implement gel dosimetry in a radiation therapy clinic. However, the response of CT contrast to dose is weak and noise reduction is critical in order to achieve adequate dose resolutions with this method. Phantom design and CT imaging technique have both been shown to decrease image noise. In addition, image postprocessing using noise reduction filtering techniques have been proposed. This work evaluates in detail the use of the adaptive mean filter for reducing noise in CT gel dosimetry. Filter performance is systematically tested using both synthetic patterns mimicking a range of clinical dose distribution features as well as actual clinical dose distributions. Both low and high signal-to-noise ratio (SNR) situations are examined. For all cases, the effects of filter kernel size and the number of iterations are investigated. Results indicate that adaptive mean filtering is a highly effective tool for noise reduction CT gel dosimetry. The optimum filtering strategy depends on characteristics of the dose distributions and image noise level. For low noise images (SNR approximately 20), the filtered results are excellent and use of adaptive mean filtering is recommended as a standard processing tool. For high noise images (SNR approximately 5) adaptive mean filtering can also produce excellent results, but filtering must be approached with more caution as spatial and dose distortions of the original dose distribution can occur.

Investigation of optimal scanning protocol for X-ray computed tomography polymer gel dosimetry

X-ray computed tomography is one of the potential tool used to evaluate the polymer gel dosimeters in three dimensions. The purpose of this study is to investigate the factors which affect the image noise for X-ray CT polymer gel dosimetry. A cylindrical water filled phantom was imaged with single slice Siemens Somatom Emotion CT scanner. The imaging parameters like tube voltage, tube current, slice scan time, slice thickness and reconstruction algorithm were varied independently to study the dependence of noise on each other. Reductions of noise with number of images to be averaged and spatial uniformity of the image were also investigated. Normoxic polymer gel PAGAT was manufactured and irradiated using Siemens Primus linear accelerator. The radiation induced change in CT number was evaluated using X-ray CT scanner. From this study it is clear that image noise is reduced with increase in tube voltage, tube current, slice scan time, slice thickness and also reduced with increasing the number of images averaged. However to reduce the tube load and total scan time, it was concluded that tube voltage of 130 kV, tube current of 200 mA, scan time of 1.5 s, slice thickness of 3 mm for high dose gradient and 5 mm for low dose gradient were optimal scanning protocols for this scanner. Optimum number of images to be averaged was concluded to be 25 for X-ray CT polymer gel dosimetry. Choice of reconstruction algorithm was also critical. From the study it is also clear that CT number increase with imaging tube voltage and shows the energy dependency of polymer gel dosimeter. Hence for evaluation of polymer gel dosimeters with X-ray CT scanner needs the optimization of scanning protocols to reduce the image noise.

Investigation of a 2D two-point maximum entropy regularization method for signal-to-noise ratio enhancement: application to CT polymer gel dosimetry

This study presents a new method of image signal-to-noise ratio (SNR) enhancement by utilizing a newly developed 2D two-point maximum entropy regularization method (TPMEM). When utilized as an image filter, it is shown that 2D TPMEM offers unsurpassed flexibility in its ability to balance the complementary requirements of image smoothness and fidelity. The technique is evaluated for use in the enhancement of x-ray computed tomography (CT) images of irradiated polymer gels used in radiation dosimetry. We utilize a range of statistical parameters (e.g. root-mean square error, correlation coefficient, error histograms, Fourier data) to characterize the performance of TPMEM applied to a series of synthetic images of varying initial SNR. These images are designed to mimic a range of dose intensity patterns that would occur in x-ray CT polymer gel radiation dosimetry. Analysis is extended to a CT image of a polymer gel dosimeter irradiated with a stereotactic radiation therapy dose distribution. Results indicate that TPMEM performs strikingly well on radiation dosimetry data, significantly enhancing the SNR of noise-corrupted images (SNR enhancement factors >15 are possible) while minimally distorting the original image detail (as shown by the error histograms and Fourier data). It is also noted that application of this new TPMEM filter is not restricted exclusively to x-ray CT polymer gel dosimetry image data but can in future be extended to a wide range of radiation dosimetry data.

Investigations in x‐ray computed tomography polyacrylamide gel dosimetry

Polyacrylamide gels (PAGs) are radiosensitive materials currently under development for use as three‐dimensional (3D) dosimeters in radiation therapy. Dose information is recorded in the gels and extracted through imaging. X‐ray computed tomography (CT) has emerged as a promising gel imaging method due to a change in gel density that occurs upon irradiation. The accessibility of CT technology to cancer hospitals makes CT read out clinically attractive; however, the technique remains of limited clinical use due in part to poor dose resolution. This thesis investigates the use of CT for extracting dose information from PAGs with an overall goal of improving achievable dose resolution. Thesis results are divided into three studies: a gel‐compositional study, a study of noise and dose resolution, and a digital filtering study. The first study investigates the effects of gel composition on PAG CT dose response and the underlying density change. Results indicate dramatic variation in CT dose response sensitivity and range with gel composition. A model is developed to describe gel density change with dose, revealing two fundamental properties of the density to dose response: the density change per unit polymer yield is highest for gels with low and high concentrations of crosslinking molecules, and dose response sensitivity is linearly dependent on the total concentration of monomers in the gel. The second study investigates strategies for minimizing noise in CT polymer gel dosimetry and assesses system performance. Specifically, the effects of phantom design, scanning technique, and voxel size on image noise are investigated and the effect of scanning protocol on imaging time is established. The dose resolution achievable with an optimized system is then calculated, given voxel size and imaging time constraints, and compared with published values for magnetic resonance imaging (MRI) and optical CT gel dosimetry. The third study investigates the potential of image filtering for improved dose resolution in CT gel dosimetry. CT image noise is characterized and appropriate filters are tested on a CT image of a PAG irradiated with a clinically relevant dose distribution. Filter performance is found to vary dramatically, with the best filters more than halving the dose resolution without significantly distorting the spatial distribution of dose. In summary, this thesis provides insight into the fundamental nature of PAG density to dose response, develops strategies for minimizing image noise, quantifies system performance, and demonstrates that digital image filtering is an effective tool to provide additional improvements to dose resolution.

Effects of gel composition on the radiation induced density change in PAG polymer gel dosimeters: a model and experimental investigations

Due to a density change that occurs in irradiated polyacrylamide gel (PAG), x-ray computed tomography (CT) has emerged as a feasible method of performing polymer gel dosimetry. However, applicability of the technique is currently limited by low sensitivity of the density change to dose. This work investigates the effect of PAG composition on the radiation induced density change and provides direction for future work in improving the sensitivity of CT polymer gel dosimetry. A model is developed that describes the PAG density change (Δρgel) as a function of both polymer yield (%P) and an intrinsic density change, per unit polymer yield, that occurs on conversion of monomer to polymer (Δρpolymer). %P is a function of the fraction of monomer consumed and the weight fraction of monomer in the unirradiated gel (%T). Applying the model to experimental CT and Raman spectroscopic data, two important fundamental properties of the response of PAG density to dose (Δρgel dose response) are discovered. The first property is that Δρpolymer depends on PAG %C (cross-linking fraction of total monomer) such that low and high %C PAGs exhibit a higher Δρpolymer than do more intermediate %C PAGs. This relationship is opposite to the relationship of polymer yield to %C and is explained by the effect of %C on the type of polymer formed. The second property is that the Δρgel dose response is linearly dependent on %T. From the model, the inference is that, at least for %T⩽12%, monomer consumption and Δρpolymer depend solely on %C. In terms of optimizing CT polymer gel dosimetry for high sensitivity, these results indicate that Δρpolymer can be expected to vary with each polymer gel system and thus should be considered when choosing a polymer gel for CT gel dosimetry. However, Δρpolymer and %P cannot be maximized simultaneously and maximizing %P, by choosing gels with intermediate %C and high %T, is found to have the greatest impact on increasing the sensitivity of PAG density to dose. As such, future research into new gel formulations for high sensitivity CT polymer gel dosimetry should focus on gels that exhibit an intrinsic density change and maximizing polymer yield in these systems.

The response of PAG density to dose: a model and experimental investigations

X-ray computed tomography (CT) has emerged as a promising method of extracting three-dimensional (3D) dose information from polymer gel dosimeters. CT gel dosimetry has many practical advantages: ease of use, relatively low cost and accessibility to cancer hospitals and has been shown to have clinical potential. However, a primary disadvantage remains poor dose resolution due in part to the low sensitivity of CT contrast to dose. This CT contrast is the result of a small density change that occurs on polymerization and advanced understanding of this density change is required in order to optimize gel sensitivity to CT. This work proposes a simple model that describes the radiation induced density change in polyacrylamide gel (PAG) as a function of polymer yield and an intrinsic density change that occurs, independent of polymer yield, on polymerization. Using this model in combination with experimental CT and Raman spectroscopy work, several fundamental properties of the PAG density response to dose are discovered. The result is a valuable framework on which to focus future developments of more sensitive CT polymer gel dosimetry systems.

Image filtering for improved dose resolution in CT polymer gel dosimetry

X-ray computed tomography (CT) has been established as a feasible method of performing dosimetry using polyacrylamide gels (PAGs). A small density change occurs in PAG upon irradiation that provides contrast in PAG CT images. However, low dose resolution limits the clinical usefulness of the technique. This work investigates the potential of using image filtering techniques on PAG CT images in order to reduce image noise and improve dose resolution. CT image noise for the scanner and protocol used for the gel images is analyzed and found to be Gaussian distributed and independent of the contrast level in the images. As a result, several filters for reducing spatially invariant noise are investigated: mean, median, midpoint, adaptive mean, alpha-trimmed mean, sigma mean, and a relatively new filter called SUSAN (smallest univalue segment assimilating nucleus). All filters are applied, using 3x3, 5x5, and 7x7 pixel masks, to a CT image of a PAG irradiated with a stereotactic radiosurgery dose distribution. The dose resolution within 95% confidence (D(delta)95%) is calculated and compared for each filtered image, as well the unfiltered image. In addition, the ability of the filters to maintain the spatial integrity of the dose distribution is evaluated and compared. Results clearly indicate that the filters are not equal in their ability to improve D(delta)95% or in their effect on the spatial integrity of the dose distribution. In general, increasing mask size improves D(delta)95% but simultaneously degrades spatial dose information. The mean filter provides the greatest improvement in D(delta)95%, but also the greatest loss of spatial dose information. The SUSAN, mean adaptive, and alpha-trimmed mean filters all provide comparable, but slightly poorer dose resolution. In addition, the SUSAN and adaptive filters both excel at maintaining the spatial distribution of dose and overall are the best performing filters for this application. The midpoint filter, normally useful for Gaussian noise, is poor all-round, dramatically distorting the dose distribution for masks greater than 3x3. The median filter, a common edge preserving noise reduction filter, performs moderately well, but artificially increases high dose gradients. The sigma filter preserves the spatial distribution of dose very well but is least effective at improving dose resolution. In summary, dose resolution can be significantly improved in CT PAG dosimetry through postprocessing of CT images using spatial noise reduction filters. However, such filters are not equal in their ability to improve dose resolution or to maintain the spatial integrity of the dose distribution and an appropriate filter must be chosen depending on clinical demands of the application.