Automated review of patient position in DIBH breast hybrid IMRT with EPID images.

Deep Inspiration Breath Hold (DIBH) is a respiratory-gating technique adopted in radiation therapy to lower cardiac irradiation. When performing DIBH treatments, it is important to have a monitoring system to ensure the patient's breath hold level is stable and reproducible at each fraction. In this retrospective study, we developed a system capable of monitoring DIBH breast treatments by utilizing cine EPID images taken during treatment. Setup error and intrafraction motion were measured for all fractions of 20 left-sided breast patients. All patients were treated with a hybrid static-IMRT technique, with EPID images from the static fields analyzed. Ten patients had open static fields and the other ten patients had static fields partially blocked with the multileaf collimator (MLC). Three image-processing algorithms were evaluated on their ability to accurately measure the chest wall position (CWP) in EPID images. CWP measurements were recorded along a 61-pixel region of interest centered along the midline of the image. The median and standard deviation of the CWP were recorded for each image. The algorithm showing the highest agreement with manual measurements was then used to calculate intrafraction motion and setup error. To measure intrafraction motion, the median CWP of the first EPID frame was compared with that of the subsequent EPID images of the treatment. The maximum difference was recorded as the intrafraction motion. The setup error was calculated as the difference in median CWP between the MV DRR and the first EPID image of the lateral tangential field. The results showed that the most accurate image-processing algorithm can identify the chest wall within 1.2 mm on both EPID and MV DRR images, and measures intrafraction motion and setup errors within 1.4 mm.

Evaluation of the ITV-margin and variables affecting bladder and mesorectal deformation during long course neoadjuvant radiotherapy for rectal cancer.

Internal target volume (ITV) margins were estimated by evaluating the movement of mesorectum and bladder during neoadjuvant long-course radiation therapy (RT) for rectal cancer. In this prospective study, 23 patients with rectal cancer had planning CT (pCT) and weekly cone beam CT (CBCT) in supine position during preoperative long-course RT. Mesorectal wall motion was analyzed based on the coordinates of the most anterior, posterior, left and right points on the pCT and CBCT. Overlap volume (OV) between the pCT bladder and CBCT mesorectum was generated. Variables that might affect relative bladder volume (ratio of CBCT to pCT bladder volumes), anterior mesorectal wall position, and OV were studied. ITV margins were also calculated. In females, smaller OV and less movement of the upper anterior mesorectal wall were identified, suggesting smaller ITV margins might be required compared to males. The relative bladder volume did not change significantly over time and was correlated with OV: the larger the relative bladder volume, the less the OV. ITV margin of 0.8 to 1.1 cm in right-left direction is satisfactory. Posteriorly, only 8 to 9 mm margin is required for upper and mid rectal regions but double of this is required for inferior third. Anteriorly, 1.3 cm margin is adequate for lower and mid rectal regions and 2.4 cm is required superiorly. An anisotropic ITV expansion of clinical target volume (CTV) for rectal cancer radiotherapy contouring provides a robust method to encompass the deformation of bladder and mesorectum. The ITV margin should take into account sex and distance from the anal verge.

Targeting the Tumor: Assessing the Impact of Bladder Volume and Position on Accuracy of Radiation Delivery for Patients with Bladder Cancer.

Context Daily variations in bladder size and position can negatively impact the ability to accurately deliver radiation. Aims We attempted to quantify how bladder volumes and positions change over the course of radiotherapy for muscle invasive bladder cancer and the planning target volume (PTV) margins required to account for such changes. Methods and material Cone-beam computed tomography (CT) images of 28 patients during their first, second, and third fractions and weekly thereafter were acquired. Bladders were contoured and the volume, centre of mass, and the maximal positions were recorded and compared to the planning CT scan. Statistical analysis Bladder parameters were analysed using regression analysis examining for time trends and correlation to the patient, tumour, or treatment-related factors. Results There was great variability in the mean bladder volumes during the radiotherapy courses (154.17 +/- 129.38 cm3). There were no statistically significant trends for volume changes. Deviations in bladder positions were seen but were small in magnitude. No patient factors were identified which could help predict bladder changes clinically. Bladder variability resulted in a high percentage of fractions (39.6%) in which part of the bladder was outside the PTV. Calculated PTV margins (for 90% of the population to receive 95% of the prescription dose) were 1.48 cm right, 1.15 cm left, 2.13 cm posterior, 1.52 cm anterior, 2.23 cm superior, and 0.52 cm inferior. Conclusions Because of random bladder changes, a significant number of fractions were treated in which the clinical target volume (CTV) fell outside of the PTV. Methods to minimize the amount of CTV that is missed on a fraction to fraction basis should be explored.

Characterization, prediction, and correction of geometric distortion in 3 T MR images.

The work presented herein describes our methods and results for predicting, measuring and correcting geometric distortions in a 3 T clinical magnetic resonance (MR) scanner for the purpose of image guidance in radiation treatment planning. Geometric inaccuracies due to both inhomogeneities in the background field and nonlinearities in the applied gradients were easily visualized on the MR images of a regularly structured three-dimensional (3D) grid phantom. From a computed tomography scan, the locations of just under 10 000 control points within the phantom were accurately determined in three dimensions using a MATLAB-based computer program. MR distortion was then determined by measuring the corresponding locations of the control points when the phantom was imaged using the MR scanner. Using a reversed gradient method, distortions due to gradient nonlinearities were separated from distortions due to inhomogeneities in the background B0 field. Because the various sources of machine-related distortions can be individually characterized, distortions present in other imaging sequences (for which 3D distortion cannot accurately be measured using phantom methods) can be predicted negating the need for individual distortion calculation for a variety of other imaging sequences. Distortions were found to be primarily caused by gradient nonlinearities and maximum image distortions were reported to be less than those previously found by other researchers at 1.5 T. Finally, the image slices were corrected for distortion in order to provide geometrically accurate phantom images.