925 research outputs found

    Quantifying the image quality and dose reduction of respiratory triggered 4D cone-beam computed tomography with patient-measured breathing.

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    Respiratory triggered four dimensional cone-beam computed tomography (RT 4D CBCT) is a novel technique that uses a patient's respiratory signal to drive the image acquisition with the goal of imaging dose reduction without degrading image quality. This work investigates image quality and dose using patient-measured respiratory signals for RT 4D CBCT simulations. Studies were performed that simulate a 4D CBCT image acquisition using both the novel RT 4D CBCT technique and a conventional 4D CBCT technique. A set containing 111 free breathing lung cancer patient respiratory signal files was used to create 111 pairs of RT 4D CBCT and conventional 4D CBCT image sets from realistic simulations of a 4D CBCT system using a Rando phantom and the digital phantom, XCAT. Each of these image sets were compared to a ground truth dataset from which a mean absolute pixel difference (MAPD) metric was calculated to quantify the degradation of image quality. The number of projections used in each simulation was counted and was assumed as a surrogate for imaging dose. Based on 111 breathing traces, when comparing RT 4D CBCT with conventional 4D CBCT, the average image quality was reduced by 7.6% (Rando study) and 11.1% (XCAT study). However, the average imaging dose reduction was 53% based on needing fewer projections (617 on average) than conventional 4D CBCT (1320 projections). The simulation studies have demonstrated that the RT 4D CBCT method can potentially offer a 53% saving in imaging dose on average compared to conventional 4D CBCT in simulation studies using a wide range of patient-measured breathing traces with a minimal impact on image quality

    Quality assurance for the clinical implementation of kilovoltage intrafraction monitoring for prostate cancer VMAT.

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    PURPOSE: Kilovoltage intrafraction monitoring (KIM) is a real-time 3D tumor monitoring system for cancer radiotherapy. KIM uses the commonly available gantry-mounted x-ray imager as input, making this method potentially more widely available than dedicated real-time 3D tumor monitoring systems. KIM is being piloted in a clinical trial for prostate cancer patients treated with VMAT (NCT01742403). The purpose of this work was to develop clinical process and quality assurance (QA) practices for the clinical implementation of KIM. METHODS: Informed by and adapting existing guideline documents from other real-time monitoring systems, KIM-specific QA practices were developed. The following five KIM-specific QA tests were included: (1) static localization accuracy, (2) dynamic localization accuracy, (3) treatment interruption accuracy, (4) latency measurement, and (5) clinical conditions accuracy. Tests (1)-(4) were performed using KIM to measure static and representative patient-derived prostate motion trajectories using a 3D programmable motion stage supporting an anthropomorphic phantom with implanted gold markers to represent the clinical treatment scenario. The threshold for system tolerable latency is <1 s. The tolerances for all other tests are that both the mean and standard deviation of the difference between the programmed trajectory and the measured data are <1 mm. The (5) clinical conditions accuracy test compared the KIM measured positions with those measured by kV/megavoltage (MV) triangulation from five treatment fractions acquired in a previous pilot study. RESULTS: For the (1) static localization, (2) dynamic localization, and (3) treatment interruption accuracy tests, the mean and standard deviation of the difference are <1.0 mm. (4) The measured latency is 350 ms. (5) For the tests with previously acquired patient data, the mean and standard deviation of the difference between KIM and kV/MV triangulation are <1.0 mm. CONCLUSIONS: Clinical process and QA practices for the safe clinical implementation of KIM, a novel real-time monitoring system using commonly available equipment, have been developed and implemented for prostate cancer VMAT

    Multileaf Collimator Tracking Improves Dose Delivery for Prostate Cancer Radiation Therapy: Results of the First Clinical Trial.

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    PURPOSE: To test the hypothesis that multileaf collimator (MLC) tracking improves the consistency between the planned and delivered dose compared with the dose without MLC tracking, in the setting of a prostate cancer volumetric modulated arc therapy trial. METHODS AND MATERIALS: Multileaf collimator tracking was implemented for 15 patients in a prostate cancer radiation therapy trial; in total, 513 treatment fractions were delivered. During each treatment fraction, the prostate trajectory and treatment MLC positions were collected. These data were used as input for dose reconstruction (multiple isocenter shift method) to calculate the treated dose (with MLC tracking) and the dose that would have been delivered had MLC tracking not been applied (without MLC tracking). The percentage difference from planned for target and normal tissue dose-volume points were calculated. The hypothesis was tested for each dose-volume value via analysis of variance using the F test. RESULTS: Of the 513 fractions delivered, 475 (93%) were suitable for analysis. The mean difference and standard deviation between the planned and treated MLC tracking doses and the planned and without-MLC tracking doses for all 475 fractions were, respectively, PTV D99% -0.8% ± 1.1% versus -2.1% ± 2.7%; CTV D99% -0.6% ± 0.8% versus -0.6% ± 1.1%; rectum V65% 1.6% ± 7.9% versus -1.2% ± 18%; and bladder V65% 0.5% ± 4.4% versus -0.0% ± 9.2% (P<.001 for all dose-volume results). CONCLUSION: This study shows that MLC tracking improves the consistency between the planned and delivered doses compared with the modeled doses without MLC tracking. The implications of this finding are potentially improved patient outcomes, as well as more reliable dose-volume data for radiobiological parameter determination

    Determining appropriate imaging parameters for kilovoltage intrafraction monitoring: an experimental phantom study.

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    Kilovoltage intrafraction monitoring (KIM) utilises the kV imager during treatment for real-time tracking of prostate fiducial markers. However, its effectiveness relies on sufficient image quality for the fiducial tracking task. To guide the performance characterisation of KIM under different clinically relevant conditions, the effect of different kV parameters and patient size on image quality, and quantification of MV scatter from the patient to the kV detector panel were investigated in this study. Image quality was determined for a range of kV acquisition frame rates, kV exposure, MV dose rates and patient sizes. Two methods were used to determine image quality; the ratio of kV signal through the patient to the MV scatter from the patient incident on the kilovoltage detector, and the signal-to-noise ratio (SNR). The effect of patient size and frame rate on MV scatter was evaluated in a homogeneous CIRS pelvis phantom and marker segmentation was determined utilising the Rando phantom with embedded markers. MV scatter incident on the detector was shown to be dependent on patient thickness and frame rate. The segmentation code was shown to be successful for all frame rates above 3 Hz for the Rando phantom corresponding to a kV to MV ratio of 0.16 and an SNR of 1.67. For a maximum patient dimension less than 36.4 cm the conservative kV parameters of 5 Hz at 1 mAs can be used to reduce dose while retaining image quality, where the current baseline kV parameters of 10 Hz at 1 mAs is shown to be adequate for marker segmentation up to a patient dimension of 40 cm. In conclusion, the MV scatter component of image quality noise for KIM has been quantified. For most prostate patients, use of KIM with 10 Hz imaging at 1 mAs is adequate however image quality can be maintained and imaging dose reduced by altering existing acquisition parameters

    Determining appropriate imaging parameters for kilovoltage intrafraction monitoring: an experimental phantom study.

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    Kilovoltage intrafraction monitoring (KIM) utilises the kV imager during treatment for real-time tracking of prostate fiducial markers. However, its effectiveness relies on sufficient image quality for the fiducial tracking task. To guide the performance characterisation of KIM under different clinically relevant conditions, the effect of different kV parameters and patient size on image quality, and quantification of MV scatter from the patient to the kV detector panel were investigated in this study. Image quality was determined for a range of kV acquisition frame rates, kV exposure, MV dose rates and patient sizes. Two methods were used to determine image quality; the ratio of kV signal through the patient to the MV scatter from the patient incident on the kilovoltage detector, and the signal-to-noise ratio (SNR). The effect of patient size and frame rate on MV scatter was evaluated in a homogeneous CIRS pelvis phantom and marker segmentation was determined utilising the Rando phantom with embedded markers. MV scatter incident on the detector was shown to be dependent on patient thickness and frame rate. The segmentation code was shown to be successful for all frame rates above 3 Hz for the Rando phantom corresponding to a kV to MV ratio of 0.16 and an SNR of 1.67. For a maximum patient dimension less than 36.4 cm the conservative kV parameters of 5 Hz at 1 mAs can be used to reduce dose while retaining image quality, where the current baseline kV parameters of 10 Hz at 1 mAs is shown to be adequate for marker segmentation up to a patient dimension of 40 cm. In conclusion, the MV scatter component of image quality noise for KIM has been quantified. For most prostate patients, use of KIM with 10 Hz imaging at 1 mAs is adequate however image quality can be maintained and imaging dose reduced by altering existing acquisition parameters

    Audiovisual Biofeedback Improves Cine-Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency.

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    PURPOSE: To assess the impact of an audiovisual (AV) biofeedback on intra- and interfraction tumor motion for lung cancer patients. METHODS AND MATERIALS: Lung tumor motion was investigated in 9 lung cancer patients who underwent a breathing training session with AV biofeedback before 2 3T magnetic resonance imaging (MRI) sessions. The breathing training session was performed to allow patients to become familiar with AV biofeedback, which uses a guiding wave customized for each patient according to a reference breathing pattern. In the first MRI session (pretreatment), 2-dimensional cine-MR images with (1) free breathing (FB) and (2) AV biofeedback were obtained, and the second MRI session was repeated within 3-6 weeks (mid-treatment). Lung tumors were directly measured from cine-MR images using an auto-segmentation technique; the centroid and outlier motions of the lung tumors were measured from the segmented tumors. Free breathing and AV biofeedback were compared using several metrics: intra- and interfraction tumor motion consistency in displacement and period, and the outlier motion ratio. RESULTS: Compared with FB, AV biofeedback improved intrafraction tumor motion consistency by 34% in displacement (P=.019) and by 73% in period (P<.001). Compared with FB, AV biofeedback improved interfraction tumor motion consistency by 42% in displacement (P<.046) and by 74% in period (P=.005). Compared with FB, AV biofeedback reduced the outlier motion ratio by 21% (P<.001). CONCLUSIONS: These results demonstrated that AV biofeedback significantly improved intra- and interfraction lung tumor motion consistency for lung cancer patients. These results demonstrate that AV biofeedback can facilitate consistent tumor motion, which is advantageous toward achieving more accurate medical imaging and radiation therapy procedures

    Real-Time 3D Image Guidance Using a Standard LINAC: Measured Motion, Accuracy, and Precision of the First Prospective Clinical Trial of Kilovoltage Intrafraction Monitoring-Guided Gating for Prostate Cancer Radiation Therapy.

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    PURPOSE: Kilovoltage intrafraction monitoring (KIM) is a new real-time 3-dimensional image guidance method. Unlike previous real-time image guidance methods, KIM uses a standard linear accelerator without any additional equipment needed. The first prospective clinical trial of KIM is underway for prostate cancer radiation therapy. In this paper we report on the measured motion accuracy and precision using real-time KIM-guided gating. METHODS AND MATERIALS: Imaging and motion information from the first 200 fractions from 6 patient prostate cancer radiation therapy volumetric modulated arc therapy treatments were analyzed. A 3-mm/5-second action threshold was used to trigger a gating event where the beam is paused and the couch position adjusted to realign the prostate to the treatment isocenter. To quantify the in vivo accuracy and precision, KIM was compared with simultaneously acquired kV/MV triangulation for 187 fractions. RESULTS: KIM was successfully used in 197 of 200 fractions. Gating events occurred in 29 fractions (14.5%). In these 29 fractions, the percentage of beam-on time, the prostate displacement was >3 mm from the isocenter position, reduced from 73% without KIM to 24% with KIM-guided gating. Displacements >5 mm were reduced from 16% without KIM to 0% with KIM. The KIM accuracy was measured at <0.3 mm in all 3 dimensions. The KIM precision was <0.6 mm in all 3 dimensions. CONCLUSIONS: Clinical implementation of real-time KIM image guidance combined with gating for prostate cancer eliminates large prostate displacements during treatment delivery. Both in vivo KIM accuracy and precision are well below 1 mm

    Evaluating the informatics for integrating biology and the bedside system for clinical research

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    <p>Abstract</p> <p>Background</p> <p>Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive.</p> <p>Methods</p> <p>Our evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone.</p> <p>Results</p> <p>We found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc.</p> <p>Conclusion</p> <p>The i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.</p
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