Intensity-modulated radiation therapy dose verification using fluence and portal imaging device.

Patient-specific quality assurance for intensity-modulated radiation therapy (IMRT) dose verification is essential. The aim of this study is to provide a new method based on the relative error distribution by comparing the fluence map from the treatment planning system (TPS) and the incident fluence deconvolved from the electronic portal imaging device (EPID) images. This method is validated for 10 head and neck IMRT cases. The fluence map of each beam was exported from the TPS and EPID images of the treatment beams were acquired. Measured EPID images were deconvolved to the incident fluence with proper corrections. The relative error distribution between the TPS fluence map and the incident fluence from the EPID was created. This was also created for a 2D diode array detector. The absolute point dose was measured with an ionization chamber, and the dose distribution was measured by a radiochromic film. In three cases, MLC leaf positions were intentionally changed to create the dose error as much as 5% against the planned dose and our fluence-based method was tested using gamma index. Absolute errors between the predicted dose of 2D diode detector and of our method and measurements were 1.26% ± 0.65% and 0.78% ± 0.81% respectively. The gamma passing rate (3% global / 3 mm) of the TPS was higher than that of the 2D diode detector (p< 0.02), and lower than that of the EPID (p < 0.04). The gamma passing rate (2% global / 2 mm) of the TPS was higher than that of the 2D diode detector, while the gamma passing rate of the TPS was lower than that of EPID (p < 0.02). For three modified plans, the predicted dose errors against the measured dose were 1.10%, 2.14%, and -0.87%. The predicted dose distributions from the EPID were well matched to the measurements. Our fluence-based method provides very accurate dosimetry for IMRT patients. The method is simple and can be adapted to any clinic for complex cases.

Three-dimensional dose prediction based on two-dimensional verification measurements for IMRT.

Dose verifications for intensity-modulated radiation therapy (IMRT) are generally performed once before treatment. A 39-fraction treatment course for prostate cancer delivers a dose prescription of 78 Gy in eight weeks. Any changes in multileaf collimator leaf position over the treatment course may affect the dosimetry. To evaluate the magnitude of deviations from the predicted dose over an entire treatment course with MLC leaf calibrations performed every two weeks, we tracked weekly changes in relative dose error distributions measured with two-dimensional (2D) beam-by-beam analysis. We compared the dosimetric results from 20 consecutive patient-specific IMRT quality assurance (QA) tests using beam-by-beam analysis and a 2D diode detector array to the dose plans calculated by the treatment planning system (TPS). We added back the resulting relative dose error measured weekly into the original dose grid for each beam. To validate the prediction method, the predicted doses and dose distributions were compared to the measurements using an ionization chamber and film. The predicted doses were in good agreement, within 2% of the measured doses, and the predicted dose distributions also presented good agreement with the measured distributions. Dose verification results measured once as a pretreatment QA test were not completely stable, as results of weekly beam-by-beam analysis showed some variation. Because dosimetric errors throughout the treatment course were averaged, the overall dosimetric impact to patients was small.

A convolution neural network for higher resolution dose prediction in prostate volumetric modulated arc therapy.

PURPOSE: This study aims to investigate the feasibility of using convolutional neural networks to predict an accurate and high resolution dose distribution from an approximated and low resolution input dose. METHODS: Sixty-six patients were treated for prostate cancer with VMAT. We created the treatment plans using the Acuros XB algorithm with 2 mm grid size, followed by the dose calculated using the anisotropic analytical algorithm with 5 mm grid with the same plan parameters. U-net model was used to predict 2 mm grid dose from 5 mm grid dose. We investigated the two models differing for the training data used as input, one used just the low resolution dose (D model) and the other combined the low resolution dose with CT data (DC model). Dice similarity coefficient (DSC) was calculated to ascertain how well the shape of the dose-volume is matched. We conducted gamma analysis for the following: DVH from the two models and the reference DVH for all prostate structures. RESULTS: The DSC values in the DC model were significantly higher than those in the D model (p < 0.01). For the CTV, PTV, and bladder, the gamma passing rates in the DC model were significantly higher than those in the D model (p < 0.002-0.02). The mean doses in the CTV and PTV for the DC model were significantly better matched to those in the reference dose (p < 0.0001). CONCLUSIONS: The proposed U-net model with dose and CT image used as input predicted more accurate dose.

Deep convolutional neural network for reduction of contrast-enhanced region on CT images.

This study aims to produce non-contrast computed tomography (CT) images using a deep convolutional neural network (CNN) for imaging. Twenty-nine patients were selected. CT images were acquired without and with a contrast enhancement medium. The transverse images were divided into 64 × 64 pixels. This resulted in 14 723 patches in total for both non-contrast and contrast-enhanced CT image pairs. The proposed CNN model comprises five two-dimensional (2D) convolution layers with one shortcut path. For comparison, the U-net model, which comprises five 2D convolution layers interleaved with pooling and unpooling layers, was used. Training was performed in 24 patients and, for testing of trained models, another 5 patients were used. For quantitative evaluation, 50 regions of interest (ROIs) were selected on the reference contrast-enhanced image of the test data, and the mean pixel value of the ROIs was calculated. The mean pixel values of the ROIs at the same location on the reference non-contrast image and the predicted non-contrast image were calculated and those values were compared. Regarding the quantitative analysis, the difference in mean pixel value between the reference contrast-enhanced image and the predicted non-contrast image was significant (P < 0.0001) for both models. Significant differences in pixels (P < 0.0001) were found using the U-net model; in contrast, there was no significant difference using the proposed CNN model when comparing the reference non-contrast images and the predicted non-contrast images. Using the proposed CNN model, the contrast-enhanced region was satisfactorily reduced.

Organ-specific modulation complexity score for the evaluation of dose delivery.

The purpose of this study was to correlate the modulation complexity score (MCS) with organ location and to predict potential dose errors for organs before beam delivery for intensity-modulated radiation therapy (IMRT) dosimetry. Sixteen head and neck cancer patients treated with IMRT were selected. Distribution of the relative dose error on each beam was performed using forward projection to the planned dose to compute the predicted dose after doing per-beam quality assurance. Original organ-specific modulation complexity score (oMCS) was created based on a modified MLC, which depended on organ location. First, MCS was calculated based on the change in leaf position between adjacent MLC leaves. Second, the segment edge map (SEM) calculated from the intensity map for each beam was applied to the calculation volume. The oMCS with segment edge (oMCSedge) was derived from the product of oMCS and SEM. The correlation between the dose errors (planned and predicted) and oMCSedge values was evaluated for the target and organs at risk. We have also expanded the original MCS concept to oMCSedge including the organ location. We observed a moderate correlation between the dose errors and oMCSedge for all organs and volumes of interest except the gross tumor volume, brain stem, and spinal cord. In other organs, a moderate improvement in sensitivity was observed on the SEM, which was correlated with dose errors. Although the implementation of oMCSedge would be impractical for normal clinical settings, it is expected that oMCSedge would help a treatment planner to judge whether or not the treatment plan would be acceptably delivered.

Robust plan optimization using edge-enhanced intensity for intrafraction organ deformation in prostate intensity-modulated radiation therapy.

This study evaluated a method for prostate intensity-modulated radiation therapy (IMRT) based on edge-enhanced (EE) intensity in the presence of intrafraction organ deformation using the data of 37 patients treated with step-and-shoot IMRT. On the assumption that the patient setup error was already accounted for by image guidance, only organ deformation over the treatment course was considered. Once the clinical target volume (CTV), rectum, and bladder were delineated and assigned dose constraints for dose optimization, each voxel in the CTV derived from the DICOM RT-dose grid could have a stochastic dose from the different voxel location according to the probability density function as an organ deformation. The stochastic dose for the CTV was calculated as the mean dose at the location through changing the voxel location randomly 1000 times. In the EE approach, the underdose region in the CTV was delineated and optimized with higher dose constraints that resulted in an edge-enhanced intensity beam to the CTV. This was compared to a planning target volume (PTV) margin (PM) approach in which a CTV to PTV margin equivalent to the magnitude of organ deformation was added to obtain an optimized dose distribution. The total monitor units, number of segments, and conformity index were compared between the two approaches, and the dose based on the organ deformation of the CTV, rectum, and bladder was evaluated. The total monitor units, number of segments, and conformity index were significantly lower with the EE approach than with the PM approach, while maintaining the dose coverage to the CTV with organ deformation. The dose to the rectum and bladder were significantly reduced in the EE approach compared with the PM approach. We conclude that the EE approach is superior to the PM with regard to intrafraction organ deformation.

Evaluation of the radiobiological gamma index with motion interplay in tangential IMRT breast treatment.

The purpose of this study was to evaluate the impact of the motion interplay effect in early-stage left-sided breast cancer intensity-modulated radiation therapy (IMRT), incorporating the radiobiological gamma index (RGI). The IMRT dosimetry for various breathing amplitudes and cycles was investigated in 10 patients. The predicted dose was calculated using the convolution of segmented measured doses. The physical gamma index (PGI) of the planning target volume (PTV) and the organs at risk (OAR) was calculated by comparing the original with the predicted dose distributions. The RGI was calculated from the PGI using the tumor control probability (TCP) and the normal tissue complication probability (NTCP). The predicted mean dose and the generalized equivalent uniform dose (gEUD) to the target with various breathing amplitudes were lower than the original dose (P < 0.01). The predicted mean dose and gEUD to the OARs with motion were higher than for the original dose to the OARs (P < 0.01). However, the predicted data did not differ significantly between the various breathing cycles for either the PTV or the OARs. The mean RGI gamma passing rate for the PTV was higher than that for the PGI (P < 0.01), and for OARs, the RGI values were higher than those for the PGI (P < 0.01). The gamma passing rates of the RGI for the target and the OARs other than the contralateral lung differed significantly from those of the PGI under organ motion. Provided an NTCP value <0.05 is considered acceptable, it may be possible, by taking breathing motion into consideration, to escalate the dose to achieve the PTV coverage without compromising the TCP.

Incorporation of gantry angle correction for 3D dose prediction in intensity-modulated radiation therapy.

Pretreatment dose verification with beam-by-beam analysis for intensity-modulated radiation therapy (IMRT) is commonly performed with a gantry angle of 0° using a 2D diode detector array. Any changes in multileaf collimator (MLC) position between the actual treatment gantry angle and 0° may result in deviations from the planned dose. We evaluated the effects of MLC positioning errors between the actual treatment gantry angles and nominal gantry angles. A gantry angle correction (GAC) factor was generated by performing a non-gap test at various gantry angles using an electronic portal imaging device (EPID). To convert pixel intensity to dose at the MLC abutment positions, a non-gap test was performed using an EPID and a film at 0° gantry angle. We then assessed the correlations between pixel intensities and doses. Beam-by-beam analyses for 15 prostate IMRT cases as patient-specific quality assurance were performed with a 2D diode detector array at 0° gantry angle to determine the relative dose error for each beam. The resulting relative dose error with or without GAC was added back to the original dose grid for each beam. We compared the predicted dose distributions with or without GAC for film measurements to validate GAC effects. A gamma pass rate with a tolerance of 2%/2 mm was used to evaluate these dose distributions. The gamma pass rate with GAC was higher than that without GAC (P = 0.01). The predicted dose distribution improved with GAC, although the dosimetric effect to a patient was minimal.

Novel Radiobiological Gamma Index for Evaluation of 3-Dimensional Predicted Dose Distribution.

PURPOSE: To propose a gamma index-based dose evaluation index that integrates the radiobiological parameters of tumor control (TCP) and normal tissue complication probabilities (NTCP). METHODS AND MATERIALS: Fifteen prostate and head and neck (H&N) cancer patients received intensity modulated radiation therapy. Before treatment, patient-specific quality assurance was conducted via beam-by-beam analysis, and beam-specific dose error distributions were generated. The predicted 3-dimensional (3D) dose distribution was calculated by back-projection of relative dose error distribution per beam. A 3D gamma analysis of different organs (prostate: clinical [CTV] and planned target volumes [PTV], rectum, bladder, femoral heads; H&N: gross tumor volume [GTV], CTV, spinal cord, brain stem, both parotids) was performed using predicted and planned dose distributions under 2%/2 mm tolerance and physical gamma passing rate was calculated. TCP and NTCP values were calculated for voxels with physical gamma indices (PGI) >1. We propose a new radiobiological gamma index (RGI) to quantify the radiobiological effects of TCP and NTCP and calculate radiobiological gamma passing rates. RESULTS: The mean RGI gamma passing rates for prostate cases were significantly different compared with those of PGI (P<.03-.001). The mean RGI gamma passing rates for H&N cases (except for GTV) were significantly different compared with those of PGI (P<.001). Differences in gamma passing rates between PGI and RGI were due to dose differences between the planned and predicted dose distributions. Radiobiological gamma distribution was visualized to identify areas where the dose was radiobiologically important. CONCLUSIONS: RGI was proposed to integrate radiobiological effects into PGI. This index would assist physicians and medical physicists not only in physical evaluations of treatment delivery accuracy, but also in clinical evaluations of predicted dose distribution.

Evaluation of imaging performance of megavoltage cone-beam CT over an extended period.

A linear accelerator vendor and the AAPM TG-142 report propose that quality assurance testing for image-guided devices such megavoltage cone-beam CT (MV-CBCT) be conducted on a monthly basis. In clinical settings, however, unpredictable errors such as image artifacts can occur even when quality assurance results performed at this frequency are within tolerance limits. Here, we evaluated the imaging performance of MV-CBCT on a weekly basis for ∼ 1 year using a Siemens ONCOR machine with a 6-MV X-ray and an image-quality phantom. Image acquisition was undertaken using 15 monitor units. Geometric distortion was evaluated with beads evenly distributed in the phantom, and the results were compared with the expected position in three dimensions. Image-quality characteristics of the system were measured and assessed qualitatively and quantitatively, including image noise and uniformity, low-contrast resolution, high-contrast resolution and spatial resolution. All evaluations were performed 100 times each. For geometric distortion, deviation between the measured and expected values was within the tolerance limit of 2 mm. However, a subtle systematic error was found which meant that the phantom was rotated slightly in a clockwise manner, possibly due to geometry calibration of the MV-CBCT system. Regarding image noise and uniformity, two incidents over tolerance occurred in 100 measurements. This phenomenon disappeared after dose calibration of beam output for MV-CBCT. In contrast, all results for low-contrast resolution, high-contrast resolution and spatial resolution were within their respective tolerances.

Quality assurance of MLC leaf position accuracy and relative dose effect at the MLC abutment region using an electronic portal imaging device.

We investigated an electronic portal image device (EPID)-based method to see whether it provides effective and accurate relative dose measurement at abutment leaves in terms of positional errors of the multi-leaf collimator (MLC) leaf position. A Siemens ONCOR machine was used. For the garden fence test, a rectangular field (0.2 20 cm) was sequentially irradiated 11 times at 2-cm intervals. Deviations from planned leaf positions were calculated. For the nongap test, relative doses at the MLC abutment region were evaluated by sequential irradiation of a rectangular field (2 20 cm) 10 times with a MLC separation of 2 cm without a leaf gap. The integral signal in a region of interest was set to position A (between leaves) and B (neighbor of A). A pixel value at position B was used as background and the pixel ratio (A/B 100) was calculated. Both tests were performed at four gantry angles (0, 90, 180 and 270°) four times over 1 month. For the nongap test the difference in pixel ratio between the first and last period was calculated. Regarding results, average deviations from planned positions with the garden fence test were within 0.5 mm at all gantry angles, and at gantry angles of 90 and 270° tended to decrease gradually over the month. For the nongap test, pixel ratio tended to increase gradually in all leaves, leading to a decrease in relative doses at abutment regions. This phenomenon was affected by both gravity arising from the gantry angle, and the hardware-associated contraction of field size with this type of machine.