Dataset Information

Model-Interpolated Gating for Magnetic Resonance Image-Guided Radiation Therapy.

ABSTRACT: PURPOSE:To develop and validate a technique for radiation therapy gating using slow (?1 frame per second) magnetic resonance imaging (MRI) and a motion model. Proposed uses of the technique include radiation therapy gating using T2-weighted images and conducting additional imaging studies during gated treatments. METHODS AND MATERIALS:The technique uses a physiologically guided breathing motion model to interpolate deformed target position between 2-dimensional (2D) MRI images acquired every 1 to 3 seconds. The model is parameterized by a 1-dimensional respiratory bellows surrogate and is continuously updated with the most recently acquired 2D images. A phantom and 8 volunteers were imaged with a 0.35T MRI-guided radiation therapy system. A balanced steady-state free precession sequence with a 2D frame rate of 3 frames per second was used to evaluate the technique. The accuracy and beam-on positive predictive value (PPV) of the model-based gating decisions were evaluated using the gating decisions derived from imaging as a ground truth. A T2-weighted gating offline proof-of-concept study using a half-Fourier, single-shot, turbo-spin echo sequence is reported. RESULTS:Model-interpolated gating accuracy, beam-on PPV, and median absolute distances between model and image-tracked target centroids were, on average, 98.3%, 98.4%, and 0.33 mm, respectively, in the balanced steady-state free precession phantom studies and 93.7%, 92.1%, and 0.86 mm, respectively, in the volunteer studies. T2 model-interpolated gating in 6 volunteers yielded an average accuracy and PPV of 94.3% and 92.5%, respectively, and the mean absolute median distance between modeled and imaged target centroids was 0.86 mm. CONCLUSIONS:This work demonstrates the concept of model-interpolated gating for MRI-guided radiation therapy. The technique was found to be potentially sufficiently accurate for clinical use. Further development is needed to accommodate out-of-plane motion and the use of an internal MR-based respiratory surrogate.

SUBMITTER: Ginn JS

PROVIDER: S-EPMC6542358 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Model-Interpolated Gating for Magnetic Resonance Image-Guided Radiation Therapy.

Ginn John S JS O'Connell Dylan D Thomas David H DH Low Daniel A DA Lamb James M JM

International journal of radiation oncology, biology, physics 20180514 4

<h4>Purpose</h4>To develop and validate a technique for radiation therapy gating using slow (≤1 frame per second) magnetic resonance imaging (MRI) and a motion model. Proposed uses of the technique include radiation therapy gating using T2-weighted images and conducting additional imaging studies during gated treatments.<h4>Methods and materials</h4>The technique uses a physiologically guided breathing motion model to interpolate deformed target position between 2-dimensional (2D) MRI images acq ...[more]

PMID: 29970314

Similar Datasets

Project description:To investigate the undesired irradiations outside of the treatment field by electron streams in air (air-electron-stream) during magnetic-resonance image-guided radiation therapy (MR-IGRT). A custom-made support phantom adjusting angles between the beam central axis (CAX) and the phantom surface (termed phantom-angles), were used. Using the ViewRay system, a rectangular parallelepiped phantom placed on the support phantom, was irradiated with field sizes of 6.3 cm × 6.3 cm (FS6.3) and 12.6 cm × 12.6 cm (FS12.6) at gantry angles of 0°, 30°, and 330°, and phantom-angles of 10°, 20°, and 30°. For each beam delivery, the isocenter was located at the center of mass of the phantom and 3 Gy was delivered to the isocenter (prescription dose = 3 Gy). The doses given by the air-electron-streams were measured using the EBT3 films on the panels placed orthogonal to the direction of the magnetic field at distances of 10 and 17 cm from CAX. Two dose distributions per irradiation were measured on the panel facing the phantom surface of the incident beam (front panel) and on the panel facing the phantom surface of the beam exit (end panel). We investigated the doses by the air-electron-streams by calculating the average doses inside the circles drawn around a point of the maximum dose with radii of x cm (DRx) from the dose distributions on the panels (x = 1-5 cm). The largest value of DRx was DR1 (1.64 Gy, 55% of the prescription dose) at 10 cm distance from CAX, with FS12.6, at 30° phantom-angle and 330° gantry angle. The average difference of the DR1 at the end panels (FS12.6) between the calculations and measurements was 1.36 Gy. The average global gamma passing rate with 3%/3 mm on the dose distributions at the end panels (FS12.6) was 40.3%. The calculated dose distributions on both panels were not coincident with the measured dose distributions. The Spearman's rank correlation coefficients between the projected areas and the DRx values were always higher than 0.75 (all with p < 0.001). The doses by the air-electron-streams increased with the projected areas of the cross-sections of the treatment beams on the panels.

Project description:Purpose:Magnetic resonance image guided radiation therapy (MR-IGRT) has been used at our institution since 2014. We report on more than 2 years of clinical experience in treating patients with the world's first MR-IGRT system. Methods and materials:A clinical service was opened for MR-IGRT in January 2014 with an MR-IGRT system consisting of a split 0.35T magnetic resonance scanner that straddles a ring gantry with 3 multileaf collimator-equipped 60Co heads. The service was expanded to include online adaptive radiation therapy (ART) MR-IGRT and cine gating after 6 and 9 months, respectively. Patients selected for MR-IGRT were enrolled in a prospective registry between January 2014 and June 2016. Patients were treated with a variety of radiation therapy techniques including intensity modulated radiation therapy and stereotactic body radiation therapy (SBRT). When applicable, online ART was performed and gating on sagittal 2-dimensional cine MR was used. The charts of patients treated with MR-IGRT were reviewed to report on the clinical and treatment characteristics of the initial patients who were treated with this novel technique. Results:A total of 316 patients have been treated with the MR-IGRT system, which has been integrated into a high-volume clinic. The cases were most commonly selected for improved soft tissue visualization, ART, and cine gating. Seventy-six patients were treated with 3-dimensional conformal radiation therapy, 146 patients with intensity modulated radiation therapy, and 94 patients with SBRT. The most commonly treated disease sites were the abdomen (28%), breast (26%), pelvis (22%), thorax (19%), and head and neck (5%). Sixty-seven patients were treated with online ART over a total of 244 adapted fractions. Cine treatment gating was used for a total of 81 patients. Conclusions:MR-IGRT has been successfully implemented in a high-volume radiation clinic and provides unique advantages in the treatment of a variety of malignancies. Additional clinical trials are in development to formally evaluate MR-IGRT in the treatment of multiple disease sites with techniques such as SBRT and ART.

Project description:Purpose:Magnetic resonance-guided online adaptive radiation therapy (MRgOART) requires accurate and efficient segmentation. However, the performance of current autosegmentation tools is generally poor for magnetic resonance imaging (MRI) owing to day-to-day variations in image intensity and patient anatomy. In this study, we propose a patient-specific autosegmentation strategy using multiple-input deformable image registration (DIR; PASSMID) to improve segmentation accuracy and efficiency for MRgOART. Methods and materials:Longitudinal MRI scans acquired on a 1.5T MRI-Linac for 10 patients with abdominal cancer were used. The proposed PASSMID includes 2 steps: applying a patient-specific image processing pipeline to longitudinal MRI scans, and populating all contours from previous sessions/fractions to a new fractional MRI using multiple DIRs and combining the resulted contours using simultaneous truth and performance level estimation (STAPLE) to obtain the final consensus segmentation. Five contour propagation strategies were compared: planning computed tomography to fractional MRI scans through rigid body registration (RDR), pretreatment MRI to fractional MRI scans through RDR and DIR, and the proposed multi-input DIR/STAPLE without preprocessing, and the PASSMID. Dice similarity coefficient (DSC) and mean distance to agreement (MDA) with ground truth contours were calculated slice by slice to quantify the contour accuracy. A quantitative index, defined as the ratio of acceptable slices, was introduced using a criterion of DSC > 0.8 and MDA < 2 mm. Results:The proposed PASSMID performed well with an average 2-dimensional DSC/MDA of 0.94/1.78 mm, 0.93/1.04 mm, 0.93/1.06 mm, 0.93/1.14 mm, 0.92/0.83 mm, 0.84/1.53 mm, 0.86/2.39 mm, 0.81/2.49 mm, 0.72/5.48 mm, and 0.70/5.03 mm for the liver, left kidney, right kidney, spleen, aorta, pancreas, stomach, duodenum, small bowel, and colon, respectively. Starting from the third fractions, the contour accuracy was significantly improved with PASSMID compared with the single-DIR strategy (P < .05). The mean ratio of acceptable slices were 13.9%, 17.5%, 60.8%, 70.6%, and 71.8% for the 5 strategies, respectively. Conclusions:The proposed PASSMID solution, by combining image processing, multi-input DIRs, and STAPLE, can significantly improve the accuracy of autosegmentation for intrapatient MRI scans, reducing the time required for further contour editing, thereby facilitating the routine practice of MRgOART.

Project description:PurposeMagnetic resonance-guided online adaptive radiation therapy (MRgOART) requires accurate and efficient segmentation. However, the performance of current autosegmentation tools is generally poor for magnetic resonance imaging (MRI) owing to day-to-day variations in image intensity and patient anatomy. In this study, we propose a patient-specific autosegmentation strategy using multiple-input deformable image registration (DIR; PASSMID) to improve segmentation accuracy and efficiency for MRgOART.Methods and materialsLongitudinal MRI scans acquired on a 1.5T MRI-Linac for 10 patients with abdominal cancer were used. The proposed PASSMID includes 2 steps: applying a patient-specific image processing pipeline to longitudinal MRI scans, and populating all contours from previous sessions/fractions to a new fractional MRI using multiple DIRs and combining the resulted contours using simultaneous truth and performance level estimation (STAPLE) to obtain the final consensus segmentation. Five contour propagation strategies were compared: planning computed tomography to fractional MRI scans through rigid body registration (RDR), pretreatment MRI to fractional MRI scans through RDR and DIR, and the proposed multi-input DIR/STAPLE without preprocessing, and the PASSMID. Dice similarity coefficient (DSC) and mean distance to agreement (MDA) with ground truth contours were calculated slice by slice to quantify the contour accuracy. A quantitative index, defined as the ratio of acceptable slices, was introduced using a criterion of DSC > 0.8 and MDA < 2 mm.ResultsThe proposed PASSMID performed well with an average 2-dimensional DSC/MDA of 0.94/1.78 mm, 0.93/1.04 mm, 0.93/1.06 mm, 0.93/1.14 mm, 0.92/0.83 mm, 0.84/1.53 mm, 0.86/2.39 mm, 0.81/2.49 mm, 0.72/5.48 mm, and 0.70/5.03 mm for the liver, left kidney, right kidney, spleen, aorta, pancreas, stomach, duodenum, small bowel, and colon, respectively. Starting from the third fractions, the contour accuracy was significantly improved with PASSMID compared with the single-DIR strategy (P < .05). The mean ratio of acceptable slices were 13.9%, 17.5%, 60.8%, 70.6%, and 71.8% for the 5 strategies, respectively.ConclusionsThe proposed PASSMID solution, by combining image processing, multi-input DIRs, and STAPLE, can significantly improve the accuracy of autosegmentation for intrapatient MRI scans, reducing the time required for further contour editing, thereby facilitating the routine practice of MRgOART.

Dataset Information

Model-Interpolated Gating for Magnetic Resonance Image-Guided Radiation Therapy.

Publications

Model-Interpolated Gating for Magnetic Resonance Image-Guided Radiation Therapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets