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Contains fulltext : 236817.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 236817.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 236817.pdf (Publisher’s version ) (Open Access)

Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large volume under investigation. To address these challenges, most deep learning approaches typically enhance their learning capability by substantially increasing the complexity or the number of trainable parameters within their models. Consequently, these models generally require long inference time on standard workstations operating clinical MR systems and are restricted to high-performance computing hardware due to their large memory requirement. Further, to fit 3D dataset through these large models using limited computer memory, trade-off techniques such as patch-wise training are often used which sacrifice the fine-scale geometric information from input images which could be clinically significant for diagnostic purposes. To address these challenges, we present a compact convolutional neural network with a shallow memory footprint to efficiently reduce the number of model parameters required for state-of-art performance. This is critical for practical employment as most clinical environments only have low-end hardware with limited computing power and memory. The proposed network can maintain data integrity by directly processing large full-size 3D input volumes with no patches required and significantly reduces the computational time required for both training and inference. We also propose a novel loss function with extra shape constraint to improve the accuracy for imbalanced classes in 3D MR images., Comment: 21 pages, 7 figures

Medical image translation (e.g. CT to MR) is a challenging task as it requires I) faithful translation of domain-invariant features (e.g. shape information of anatomical structures) and II) realistic synthesis of target-domain features (e.g. tissue appearance in MR). In this work, we propose Manifold Disentanglement Generative Adversarial Network (MDGAN), a novel image translation framework that explicitly models these two types of features. It employs a fully convolutional generator to model domain-invariant features, and it uses style codes to separately model target-domain features as a manifold. This design aims to explicitly disentangle domain-invariant features and domain-specific features while gaining individual control of both. The image translation process is formulated as a stylisation task, where the input is "stylised" (translated) into diverse target-domain images based on style codes sampled from the learnt manifold. We test MDGAN for multi-modal medical image translation, where we create two domain-specific manifold clusters on the manifold to translate segmentation maps into pseudo-CT and pseudo-MR images, respectively. We show that by traversing a path across the MR manifold cluster, the target output can be manipulated while still retaining the shape information from the input.

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Contains fulltext : 202831.pdf (publisher's version ) (Closed access)

Item does not contain fulltext

Contains fulltext : 202831.pdf (publisher's version ) (Closed access)

Contains fulltext : 202831.pdf (publisher's version ) (Closed access)

Background and purpose: Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2(W)) MR images of the pelvis.Materials and methods: This study developed a generalized dual model HU conversion method to convert standard T2(W) MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors.Results: For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 +/- 6 HUs (34 HUs) and -46 +/- 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 +/- 0.4% (-1.3%).Conclusions: The study provides a generalized method for sCT creation from standard T2(W) images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences. (c) 2017 Elsevier B.V. All rights reserved.

Background and purpose: Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2(W)) MR images of the pelvis.Materials and methods: This study developed a generalized dual model HU conversion method to convert standard T2(W) MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors.Results: For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 +/- 6 HUs (34 HUs) and -46 +/- 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 +/- 0.4% (-1.3%).Conclusions: The study provides a generalized method for sCT creation from standard T2(W) images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences. (c) 2017 Elsevier B.V. All rights reserved.

Objective: Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. Methods: Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. Results: In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4 mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. Conclusions: Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models.

Objective: Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. Methods: Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. Results: In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4 mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. Conclusions: Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models.

Objective: Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. Methods: Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. Results: In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4 mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. Conclusions: Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models.

Objective: Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. Methods: Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. Results: In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4 mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. Conclusions: Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models.

To quantify the dose calculation error and resulting optimization uncertainty caused by performing inverse treatment planning on inaccurate electron density data (pseudo-CT) as needed for adaptive radiotherapy and Magnetic Resonance Imaging (MRI) based treatment planning. Planning Computer Tomography (CT) data from 10 cervix cancer patients was used to generate 4 pseudo-CT data sets. Each pseudo-CT was created based on an available method of assigning electron density to an anatomic image. An inversely modulated radiotherapy (IMRT) plan was developed on each planning CT. The dose calculation error caused by each pseudo-CT data set was quantified by comparing the dose calculated each pseudo-CT data set with that calculated on the original planning CT for the same IMRT plan. The optimization uncertainty introduced by the dose calculation error was quantified by re-optimizing the same optimization parameters on each pseudo-CT data set and comparing against the original planning CT. Dose differences were quantified by assessing the Equivalent Uniform Dose (EUD) for targets and relevant organs at risk. Across all pseudo-CT data sets and all organs, the absolute mean dose calculation error was 0.2 Gy, and was within 2 % of the prescription dose in 98.5 % of cases. Then absolute mean optimisation error was 0.3 Gy EUD, indicating that that inverse optimisation is impacted by the dose calculation error. However, the additional uncertainty introduced to plan optimisation is small compared the sources of variation which already exist. Use of inaccurate electron density data for inverse treatment planning results in a dose calculation error, which in turn introduces additional uncertainty into the plan optimization process. In this study, we showed that both of these effects are clinically acceptable for cervix cancer patients using four different pseudo-CT data sets. Dose calculation and inverse optimization on pseudo-CT is feasible for this patient cohort.

Purpose: Current amorphous silicon electronic portal imaging devices (a-Si EPIDs) that are frequently used in radiotherapy applications employ a metal platephosphor screen configuration to optimize x-ray detection efficiency. The phosphor acts to convert x rays into an optical signal that is detected by an underlying photodiode array. The dosimetric response of EPIDs has been well characterized, in part through the development of computational models. Such models, however, have generally made simplifying assumptions with regards to the transport of optical photons within these detectors. The goal of this work was to develop and experimentally validate a new Monte Carlo (MC) model of an a-Si EPID that simulates both x-ray and optical photon transport in a self-contained manner. Using this model the authors establish a definitive characterization of the effects of optical transport on the dosimetric response of a-Si EPIDs employing gadolinium oxysulfide phosphor screens. Methods: The Geant4 MC toolkit was used to develop a model of an a-Si EPID that employs standard electromagnetic and optical physics classes. The sensitivity of EPID response to uncertainties in optical transport parameters was evaluated by investigating their effects on the EPID point spread function (PSF). An optical blur kernel was also calculated to isolate the component of the PSF resulting purely from optical transport. A 6 MV photon source model was developed and integrated into the MC model to investigate EPID dosimetric response. Field size output factors and relative dose profiles were calculated for a set of open fields by separately scoring energy deposited in the phosphor and optical absorption events in the photodiode. These were then compared to quantify effects resulting from optical photon transport. The EPID model was validated against experimental measurements taken using a research EPID. Results: Optical photon scatter within the phosphor screen noticeably broadened the PSF. Variat

Purpose: Standard amorphous silicon electronic portal imaging devices (a-Si EPIDs) are x-ray imagers used frequently in radiotherapy that indirectly detect incident x-rays using a metal plate and phosphor screen. These detectors may also be used as two-dimensional dosimeters; however, they have a well-characterized nonwater-equivalent dosimetric response. Plastic scintillating (PS) fibers, on the other hand, have been shown to respond in a water-equivalent manner to x-rays in the energy range typically encountered during radiotherapy. In this study, the authors report on the first experimental measurements taken with a novel prototype PS a-Si EPID developed for the purpose of performing simultaneous imaging and dosimetry in radiotherapy. This prototype employs an array of PS fibers in place of the standard metal plate and phosphor screen. The imaging performance and dosimetric response of the prototype EPID were evaluated experimentally and compared to that of the standard EPID. Methods: Clinical 6 MV photon beams were used to first measure the detector sensitivity, linearity of dose response, and pixel noise characteristics of the prototype and standard EPIDs. Second, the dosimetric response of each EPID was evaluated relative to a reference water-equivalent dosimeter by measuring the off-axis and field size response in a nontransit configuration, along with the off-axis, field size, and transmission response in a transit configuration using solid water blocks. Finally, the imaging performance of the prototype and standard EPIDs was evaluated quantitatively by using an image quality phantom to measure the contrast to noise ratio (CNR) and spatial resolution of images acquired with each detector, and qualitatively by using an anthropomorphic phantom to acquire images representative of human anatomy. Results: The prototype EPID's sensitivity was 0.37 times that of the standard EPID. Both EPIDs exhibited responses that were linear with delivered dose over a range of 1

Radiation therapy treatment verification is currently limited to image-guided radiotherapy to verify patient and target location. There is no widely available method for direct verification of the delivered dose. Imaging has been widely implemented with amorphous silicon (a-Si) flat panel imagers. a- Si imagers can also be used to verify dose delivered to the patient, but current detector designs are problematic for dosimetry. Our group is investigating new detector designs optimized for simultaneous imaging and dosimetry. Detector specifications for megavoltage radiographic imaging and radiation dosimetry are in some respects contradictory to each other, presenting a significant technical challenge for detector design. The first generation of our prototype detectors consist of plastic scintillator fiber arrays interfaced directly onto a-Si imagers. Experimental and modeling studies are being conducted to optimize this design and determine the feasibility. Results to-date demonstrate excellent dosimetry and promising imaging performance, with significant potential for improvement. Ongoing detector developments are focused on improving detective quantum efficiency for imaging performance. We have demonstrated the feasibility of the plastic scintillator based detector and continue to optimize the design to develop a detector for comprehensive radiation therapy treatment verification.

Purpose: Standard amorphous silicon electronic portal imaging devices (a-Si EPIDs) are x-ray imagers used frequently in radiotherapy that indirectly detect incident x-rays using a metal plate and phosphor screen. These detectors may also be used as two-dimensional dosimeters; however, they have a well-characterized nonwater-equivalent dosimetric response. Plastic scintillating (PS) fibers, on the other hand, have been shown to respond in a water-equivalent manner to x-rays in the energy range typically encountered during radiotherapy. In this study, the authors report on the first experimental measurements taken with a novel prototype PS a-Si EPID developed for the purpose of performing simultaneous imaging and dosimetry in radiotherapy. This prototype employs an array of PS fibers in place of the standard metal plate and phosphor screen. The imaging performance and dosimetric response of the prototype EPID were evaluated experimentally and compared to that of the standard EPID. Methods: Clinical 6 MV photon beams were used to first measure the detector sensitivity, linearity of dose response, and pixel noise characteristics of the prototype and standard EPIDs. Second, the dosimetric response of each EPID was evaluated relative to a reference water-equivalent dosimeter by measuring the off-axis and field size response in a nontransit configuration, along with the off-axis, field size, and transmission response in a transit configuration using solid water blocks. Finally, the imaging performance of the prototype and standard EPIDs was evaluated quantitatively by using an image quality phantom to measure the contrast to noise ratio (CNR) and spatial resolution of images acquired with each detector, and qualitatively by using an anthropomorphic phantom to acquire images representative of human anatomy. Results: The prototype EPID's sensitivity was 0.37 times that of the standard EPID. Both EPIDs exhibited responses that were linear with delivered dose over a range of 1

Radiation therapy treatment verification is currently limited to image-guided radiotherapy to verify patient and target location. There is no widely available method for direct verification of the delivered dose. Imaging has been widely implemented with amorphous silicon (a-Si) flat panel imagers. a- Si imagers can also be used to verify dose delivered to the patient, but current detector designs are problematic for dosimetry. Our group is investigating new detector designs optimized for simultaneous imaging and dosimetry. Detector specifications for megavoltage radiographic imaging and radiation dosimetry are in some respects contradictory to each other, presenting a significant technical challenge for detector design. The first generation of our prototype detectors consist of plastic scintillator fiber arrays interfaced directly onto a-Si imagers. Experimental and modeling studies are being conducted to optimize this design and determine the feasibility. Results to-date demonstrate excellent dosimetry and promising imaging performance, with significant potential for improvement. Ongoing detector developments are focused on improving detective quantum efficiency for imaging performance. We have demonstrated the feasibility of the plastic scintillator based detector and continue to optimize the design to develop a detector for comprehensive radiation therapy treatment verification.

Radiation therapy treatment verification is currently limited to image-guided radiotherapy to verify patient and target location. There is no widely available method for direct verification of the delivered dose. Imaging has been widely implemented with amorphous silicon (a-Si) flat panel imagers. a- Si imagers can also be used to verify dose delivered to the patient, but current detector designs are problematic for dosimetry. Our group is investigating new detector designs optimized for simultaneous imaging and dosimetry. Detector specifications for megavoltage radiographic imaging and radiation dosimetry are in some respects contradictory to each other, presenting a significant technical challenge for detector design. The first generation of our prototype detectors consist of plastic scintillator fiber arrays interfaced directly onto a-Si imagers. Experimental and modeling studies are being conducted to optimize this design and determine the feasibility. Results to-date demonstrate excellent dosimetry and promising imaging performance, with significant potential for improvement. Ongoing detector developments are focused on improving detective quantum efficiency for imaging performance. We have demonstrated the feasibility of the plastic scintillator based detector and continue to optimize the design to develop a detector for comprehensive radiation therapy treatment verification.

Purpose: Standard amorphous silicon electronic portal imaging devices (a-Si EPIDs) are x-ray imagers used frequently in radiotherapy that indirectly detect incident x-rays using a metal plate and phosphor screen. These detectors may also be used as two-dimensional dosimeters; however, they have a well-characterized nonwater-equivalent dosimetric response. Plastic scintillating (PS) fibers, on the other hand, have been shown to respond in a water-equivalent manner to x-rays in the energy range typically encountered during radiotherapy. In this study, the authors report on the first experimental measurements taken with a novel prototype PS a-Si EPID developed for the purpose of performing simultaneous imaging and dosimetry in radiotherapy. This prototype employs an array of PS fibers in place of the standard metal plate and phosphor screen. The imaging performance and dosimetric response of the prototype EPID were evaluated experimentally and compared to that of the standard EPID. Methods: Clinical 6 MV photon beams were used to first measure the detector sensitivity, linearity of dose response, and pixel noise characteristics of the prototype and standard EPIDs. Second, the dosimetric response of each EPID was evaluated relative to a reference water-equivalent dosimeter by measuring the off-axis and field size response in a nontransit configuration, along with the off-axis, field size, and transmission response in a transit configuration using solid water blocks. Finally, the imaging performance of the prototype and standard EPIDs was evaluated quantitatively by using an image quality phantom to measure the contrast to noise ratio (CNR) and spatial resolution of images acquired with each detector, and qualitatively by using an anthropomorphic phantom to acquire images representative of human anatomy. Results: The prototype EPID's sensitivity was 0.37 times that of the standard EPID. Both EPIDs exhibited responses that were linear with delivered dose over a range of 1

Radiation therapy treatment verification is currently limited to image-guided radiotherapy to verify patient and target location. There is no widely available method for direct verification of the delivered dose. Imaging has been widely implemented with amorphous silicon (a-Si) flat panel imagers. a- Si imagers can also be used to verify dose delivered to the patient, but current detector designs are problematic for dosimetry. Our group is investigating new detector designs optimized for simultaneous imaging and dosimetry. Detector specifications for megavoltage radiographic imaging and radiation dosimetry are in some respects contradictory to each other, presenting a significant technical challenge for detector design. The first generation of our prototype detectors consist of plastic scintillator fiber arrays interfaced directly onto a-Si imagers. Experimental and modeling studies are being conducted to optimize this design and determine the feasibility. Results to-date demonstrate excellent dosimetry and promising imaging performance, with significant potential for improvement. Ongoing detector developments are focused on improving detective quantum efficiency for imaging performance. We have demonstrated the feasibility of the plastic scintillator based detector and continue to optimize the design to develop a detector for comprehensive radiation therapy treatment verification.

Radiotherapy is an effective therapy in the treatment of cervix cancer. However tumor and normal tissue motion and shape deformation of the cervix, the bladder and the rectum over the course of the treatment can limit the efficacy of radiotherapy and safe delivery of the dose. A number of studies have presented the potential benefits of adaptive radiotherapy for cervix cancer with high soft tissue contrast magnetic resonance images. To enable practical implementation of adaptive radiotherapy for the cervix, computer aided segmentation is necessary. Accurate computer aided automatic or semi-automatic segmentation of the cervix is a challenging task due to inter patient shape variation, soft tissue deformation, organ motion, and anatomical changes during the course of the treatment. This article reviews the methods developed for cervix segmentation in magnetic resonance images. The objective of this work is to present different methods for cervix segmentation in the literature highlighting their similarities, differences, strengths and weaknesses.

Purpose: Standard amorphous silicon electronic portal imaging devices (a-Si EPIDs) are x-ray imagers used frequently in radiotherapy that indirectly detect incident x-rays using a metal plate and phosphor screen. These detectors may also be used as two-dimensional dosimeters; however, they have a well-characterized nonwater-equivalent dosimetric response. Plastic scintillating (PS) fibers, on the other hand, have been shown to respond in a water-equivalent manner to x-rays in the energy range typically encountered during radiotherapy. In this study, the authors report on the first experimental measurements taken with a novel prototype PS a-Si EPID developed for the purpose of performing simultaneous imaging and dosimetry in radiotherapy. This prototype employs an array of PS fibers in place of the standard metal plate and phosphor screen. The imaging performance and dosimetric response of the prototype EPID were evaluated experimentally and compared to that of the standard EPID. Methods: Clinical 6 MV photon beams were used to first measure the detector sensitivity, linearity of dose response, and pixel noise characteristics of the prototype and standard EPIDs. Second, the dosimetric response of each EPID was evaluated relative to a reference water-equivalent dosimeter by measuring the off-axis and field size response in a nontransit configuration, along with the off-axis, field size, and transmission response in a transit configuration using solid water blocks. Finally, the imaging performance of the prototype and standard EPIDs was evaluated quantitatively by using an image quality phantom to measure the contrast to noise ratio (CNR) and spatial resolution of images acquired with each detector, and qualitatively by using an anthropomorphic phantom to acquire images representative of human anatomy. Results: The prototype EPID's sensitivity was 0.37 times that of the standard EPID. Both EPIDs exhibited responses that were linear with delivered dose over a range of 1

Current electronic portal imaging devices (EPIDs) are generally used for megavoltage imaging in radiotherapy and employ a thin Cu plate/phosphor screen to convert x-ray energies into optical photons . In order to achieve a high spatial resolution, thin screens are used which subsequently results in low x-ray absorption and thus a low detective quantum efficiency (DQE) for megavoltage x-rays. Additionally, the high atomic number Cu/phosphor screen materials is not ideal for dosimetric applications. To improve the imaging and dosimetry dual-functionality of EPIDs, water equivalent plastic scintillators have been proposed. Plastic scintillator fibers may however be susceptible to radiation damage caused primarily by ionizations from low energy secondary electrons. An accumulation or clustering of these ionization events, within regions corresponding to the volume of the plastic polymer chains, may lead to chain breaks. This could result in changes to the optical photon absorption properties and optical yield of the fiber, affecting the overall imaging performance of the detector. Here we used Monte Carlo radiation transport simulations for a preliminary investigation into the distribution of ionizations within a single plastic fiber. We find a large number of ionization events can accumulate along the fiber length, which over repeated exposures could lead to damage. To determine the effect of damage on the imaging performance, two fiber arrays were modeled with and without areas of damage. The damaged fiber array was found to produce approximately half the number of counts as the undamaged array.

Purpose: Current amorphous silicon electronic portal imaging devices (a-Si EPIDs) that are frequently used in radiotherapy applications employ a metal platephosphor screen configuration to optimize x-ray detection efficiency. The phosphor acts to convert x rays into an optical signal that is detected by an underlying photodiode array. The dosimetric response of EPIDs has been well characterized, in part through the development of computational models. Such models, however, have generally made simplifying assumptions with regards to the transport of optical photons within these detectors. The goal of this work was to develop and experimentally validate a new Monte Carlo (MC) model of an a-Si EPID that simulates both x-ray and optical photon transport in a self-contained manner. Using this model the authors establish a definitive characterization of the effects of optical transport on the dosimetric response of a-Si EPIDs employing gadolinium oxysulfide phosphor screens. Methods: The Geant4 MC toolkit was used to develop a model of an a-Si EPID that employs standard electromagnetic and optical physics classes. The sensitivity of EPID response to uncertainties in optical transport parameters was evaluated by investigating their effects on the EPID point spread function (PSF). An optical blur kernel was also calculated to isolate the component of the PSF resulting purely from optical transport. A 6 MV photon source model was developed and integrated into the MC model to investigate EPID dosimetric response. Field size output factors and relative dose profiles were calculated for a set of open fields by separately scoring energy deposited in the phosphor and optical absorption events in the photodiode. These were then compared to quantify effects resulting from optical photon transport. The EPID model was validated against experimental measurements taken using a research EPID. Results: Optical photon scatter within the phosphor screen noticeably broadened the PSF. Variat