Noriyuki Kadoya

Evaluation of various deformable image registration algorithms for thoracic images

We evaluated the accuracy of one commercially available and three publicly available deformable image registration (DIR) algorithms for thoracic four-dimensional (4D) computed tomography (CT) images. Five patients with esophagus cancer were studied. Datasets of the five patients were provided by DIR-lab (dir-lab.com) and consisted of thoracic 4D CT images and a coordinate list of anatomical landmarks that had been manually identified. Expert landmark correspondence was used for evaluating DIR spatial accuracy. First, the manually measured displacement vector field (mDVF) was obtained from the coordinate list of anatomical landmarks. Then the automatically calculated displacement vector field (aDVF) was calculated by using the following four DIR algorithms: B-spine implemented in Velocity AI (Velocity Medical, Atlanta, GA, USA), free-form deformation (FFD), Horn–Schunk optical flow (OF) and Demons in DIRART of MATLAB software. Registration error is defined as the difference between mDVF and aDVF. The mean 3D registration errors were 2.7 ± 0.8 mm for B-spline, 3.6 ± 1.0 mm for FFD, 2.4 ± 0.9 mm for OF and 2.4 ± 1.2 mm for Demons. The results showed that reasonable accuracy was achieved in B-spline, OF and Demons, and that these algorithms have the potential to be used for 4D dose calculation, automatic image segmentation and 4D CT ventilation imaging in patients with thoracic cancer. However, for all algorithms, the accuracy might be improved by using the optimized parameter setting. Furthermore, for B-spline in Velocity AI, the 3D registration error was small with displacements of less than ∼10 mm, indicating that this software may be useful in this range of displacements.

Evaluation of accuracy of B-spline transformation-based deformable image registration with different parameter settings for thoracic images

Deformable image registration (DIR) is fundamental technique for adaptive radiotherapy and image-guided radiotherapy. However, further improvement of DIR is still needed. We evaluated the accuracy of B-spline transformation-based DIR implemented in elastix. This registration package is largely based on the Insight Segmentation and Registration Toolkit (ITK), and several new functions were implemented to achieve high DIR accuracy. The purpose of this study was to clarify whether new functions implemented in elastix are useful for improving DIR accuracy. Thoracic 4D computed tomography images of ten patients with esophageal or lung cancer were studied. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomical landmarks that had been manually identified. DIR between peak-inhale and peak-exhale images was performed with four types of parameter settings. The first one represents original ITK (Parameter 1). The second employs the new function of elastix (Parameter 2), and the third was created to verify whether new functions improve DIR accuracy while keeping computational time (Parameter 3). The last one partially employs a new function (Parameter 4). Registration errors for these parameter settings were calculated using the manually determined landmark pairs. 3D registration errors with standard deviation over all cases were 1.78 (1.57), 1.28 (1.10), 1.44 (1.09) and 1.36 (1.35) mm for Parameter 1, 2, 3 and 4, respectively, indicating that the new functions are useful for improving DIR accuracy, even while maintaining the computational time, and this B-spline-based DIR could be used clinically to achieve high-accuracy adaptive radiotherapy.

Evaluation of On-Board kV Cone Beam Computed Tomography–Based Dose Calculation With Deformable Image Registration Using Hounsfield Unit Modifications

PURPOSE The purpose of this study was to estimate the accuracy of the dose calculation of On-Board Imager (Varian, Palo Alto, CA) cone beam computed tomography (CBCT) with deformable image registration (DIR), using the multilevel-threshold (MLT) algorithm and histogram matching (HM) algorithm in pelvic radiation therapy. METHODS AND MATERIALS One pelvis phantom and 10 patients with prostate cancer treated with intensity modulated radiation therapy were studied. To minimize the effect of organ deformation and different Hounsfield unit values between planning CT (PCT) and CBCT, we modified CBCT (mCBCT) with DIR by using the MLT (mCBCT(MLT)) and HM (mCBCT(HM)) algorithms. To evaluate the accuracy of the dose calculation, we compared dose differences in dosimetric parameters (mean dose [D(mean)], minimum dose [D(min)], and maximum dose [D(max)]) for planning target volume, rectum, and bladder between PCT (reference) and CBCTs or mCBCTs. Furthermore, we investigated the effect of organ deformation compared with DIR and rigid registration (RR). We determined whether dose differences between PCT and mCBCTs were significantly lower than in CBCT by using Student t test. RESULTS For patients, the average dose differences in all dosimetric parameters of CBCT with DIR were smaller than those of CBCT with RR (eg, rectum; 0.54% for DIR vs 1.24% for RR). For the mCBCTs with DIR, the average dose differences in all dosimetric parameters were less than 1.0%. CONCLUSIONS We evaluated the accuracy of the dose calculation in CBCT, mCBCT(MLT), and mCBCT(HM) with DIR for 10 patients. The results showed that dose differences in D(mean), D(min), and D(max) in mCBCTs were within 1%, which were significantly better than those in CBCT, especially for the rectum (P<.05). Our results indicate that the mCBCT(MLT) and mCBCT(HM) can be useful for improving the dose calculation for adaptive radiation therapy.

Quantification of residual dose estimation error on log file-based patient dose calculation.

PURPOSE The log file-based patient dose estimation includes a residual dose estimation error caused by leaf miscalibration, which cannot be reflected on the estimated dose. The purpose of this study is to determine this residual dose estimation error. METHODS AND MATERIALS Modified log files for seven head-and-neck and prostate volumetric modulated arc therapy (VMAT) plans simulating leaf miscalibration were generated by shifting both leaf banks (systematic leaf gap errors: ±2.0, ±1.0, and ±0.5mm in opposite directions and systematic leaf shifts: ±1.0mm in the same direction) using MATLAB-based (MathWorks, Natick, MA) in-house software. The generated modified and non-modified log files were imported back into the treatment planning system and recalculated. Subsequently, the generalized equivalent uniform dose (gEUD) was quantified for the definition of the planning target volume (PTV) and organs at risks. RESULTS For MLC leaves calibrated within ±0.5mm, the quantified residual dose estimation errors that obtained from the slope of the linear regression of gEUD changes between non- and modified log file doses per leaf gap are in head-and-neck plans 1.32±0.27% and 0.82±0.17Gy for PTV and spinal cord, respectively, and in prostate plans 1.22±0.36%, 0.95±0.14Gy, and 0.45±0.08Gy for PTV, rectum, and bladder, respectively. CONCLUSIONS In this work, we determine the residual dose estimation errors for VMAT delivery using the log file-based patient dose calculation according to the MLC calibration accuracy.

Dosimetric impact of 4-dimensional computed tomography ventilation imaging-based functional treatment planning for stereotactic body radiation therapy with 3-dimensional conformal radiation therapy

PURPOSE The purpose of this study was to clarify the dosimetric impact of 4-dimensional computed tomography (4D-CT)-derived, ventilation-guided functional avoidance for stereotactic body radiation therapy (SBRT) with 3-dimensional conformal radiation therapy. METHODS AND MATERIALS Eleven lung cancer patients with peripheral tumors no greater than 5 cm in size were studied (average planning target volume, 42.4 ± 32.5 cm(3)). Four-dimensional-CT ventilation imaging was performed using deformable image registration for spatial mapping of the peak-exhale 4D-CT image to the peak-inhale 4D-CT image and computation of the Jacobian-based ventilation metric. For each patient, anatomical and functional plans were created using 7 to 9 noncoplanar beams for SBRT (40-56 Gy/4-8 fractions). The anatomical plan was generated without incorporating ventilation information. In the functional plan, functional dose-volume constraints were applied in planning to spare the high-functional lung that was defined as the 90th percentile functional volume. The beam directions of the 2 plans were automatically determined by beam angle optimization. RESULTS The percentage of volume receiving a dose of ≥5 Gy (V5), V10, V20, and mean dose to the high-functional lung were 20.5%, 15.6%, 7.8%, and 4.6 Gy, respectively, for the anatomical plan, whereas they were 12.3%, 8.2%, 4.6%, and 3.2 Gy, respectively, for the functional plan. No significant differences in minimum dose, maximum dose, and conformity index of the planning target volume and in all dosimetric parameters for normal tissues between the anatomical and functional plans were seen. CONCLUSIONS We compared anatomical and functional plans for SBRT with 3-dimensional conformal radiation therapy for the first time. Our results demonstrated that a functional plan for SBRT reduced the dose in the high-functional regions without a significant change in the total lung or planning target volume even if the radiation technique cannot modulate beam intensity. Thus, this technique can be safely used in functional planning for SBRT.

Evaluation of patient DVH‐based QA metrics for prostate VMAT: correlation between accuracy of estimated 3D patient dose and magnitude of MLC misalignment

The purpose of this study was to evaluate the accuracy of commercially available software, using patient DVH‐based QA metrics, by investigating the correlation between estimated 3D patient dose and magnitude of MLC misalignments. We tested 3DVH software with an ArcCHECK. Two different calculating modes of ArcCHECK Planned Dose Perturbation (ACPDP) were used: “Normal Sensitivity” and “High Sensitivity”. Ten prostate cancer patients treated with hypofractionated VMAT (67.6 Gy/26 Fr) in our hospital were studied. For the baseline plan, we induced MLC errors (−0.75,−0.5,−0.25,0.25,0.5, and 0.75 mm for each single bank). We calculated the dose differences between the ACPDP dose with error and TPS dose with error using gamma passing rates and using DVH‐based QA metrics. The correlations between dose estimation error and MLC position error varied with each structure and metric. A comparison using 1%/1 mm gamma index showed that the larger was the MLC error‐induced, the worse were the gamma passing rates. Slopes of linear fit to dose estimation error versus MLC position error for mean dose and D95 to the PTV were 1.76 and 1.40% mm−1, respectively, for “Normal Sensitivity”, and −0.53 and 0.88% mm−1, respectively, for “High Sensitivity”, showing better accuracy for “High Sensitivity” than “Normal Sensitivity”. On the other hand, the slopes for mean dose to the rectum and bladder, V35 to the rectum and bladder and V55 to the rectum and bladder, were −1.00,−0.55,−2.56,−1.25,−3.53, and 1.85% mm−1, respectively, for “Normal Sensitivity”, and −2.89,−2.39,−4.54,−3.12,−6.24, and −4.11% mm−1, respectively, for “High Sensitivity”, showing significant better accuracy for “Normal Sensitivity” than “High Sensitivity”. Our results showed that 3DVH had some residual error for both sensitivities. Furthermore, we found that “Normal Sensitivity” might have better accuracy for the DVH metric for the PTV and that “High Sensitivity” might have better accuracy for DVH metrics for the rectum and bladder. We must be willing to tolerate this residual error in clinical care. PACS number: 87.55Qr

Assessment of myocardial metabolic disorder associated with mediastinal radiotherapy for esophageal cancer -a pilot study.

BackgroundTo evaluate the dose-effect relations for myocardial metabolic disorders after mediastinal radiotherapy (RT) by performing iodine-123 β-methyl-iodophenyl pentadecanoic acid (I-123 BMIPP) scintigraphy.MethodsBetween 2011 and 2012, we performed I-123 BMIPP scintigraphy for patients with esophageal cancer before and six months after curative mediastinal RT. Single photon emission computed tomography (SPECT) images of pre-RT and post-RT were registered into RT dose distributions. The myocardium was contoured, and the regional RT dose was calculated. Normalization is required to compare pre- and post-RT SPECT images because the uptake pattern is changed due to the breathing level. Normalization was applied on the mean of SPECT counts in regions of the myocardium receiving less than 5 Gy. Relative values in each dose region (interval of 5 Gy) were calculated on the basis of this normalization for each patient. The reduction in the percent of relative values was calculated.ResultsFive patients were enrolled in this study. None of the patients had a past history of cardiac disease. The left ventricle was partially involved in RT fields in all patients. The patients received RT with median total doses of 60-66 Gy for the primary tumor and metastatic lymph nodes. Concomitant chemotherapy consisting of cisplatin or nedaplatin and 5-fluorouracil with RT was performed in 4 patients. All patients had reduced uptake corresponding to RT fields. Dose-effect relations for reduced uptake tended to be observed at 6 months after RT with mean decreases of 8.96% in regions at 10-15 Gy, 12.6% in regions at 20-25 Gy, 15.6% in regions at 30-35 Gy, 19.0% in regions at 40-45 Gy and 16.0% in regions at 50-55 Gy.ConclusionsDose-effect relations for myocardial metabolic disorders tended to be observed. We may need to make an effort to reduce high-dose mediastinal RT to the myocardium in RT planning.

Comparison of DVH‐based plan verification methods for VMAT: ArcCHECK‐3DVH system and dynalog‐based dose reconstruction

Abstract The purpose of this study was comparing dose‐volume histogram (DVH)‐based plan verification methods for volumetric modulated arc therapy (VMAT) pretreatment QA. We evaluated two 3D dose reconstruction systems: ArcCHECK‐3DVH system (Sun Nuclear corp.) and Varian dynalog‐based dose reconstruction (DBDR) system, developed in‐house. Fifteen prostate cancer patients (67.6 Gy/26 Fr), four head and neck cancer patient (66 Gy/33 Fr), and four esophagus cancer patients (60 Gy/30 Fr) treated with VMAT were studied. First, ArcCHECK measurement was performed on all plans; simultaneously, the Varian dynalog data sets that contained the actual delivered parameters (leaf positions, gantry angles, and cumulative MUs) were acquired from the Linac control system. Thereafter, the delivered 3D patient dose was reconstructed by 3DVH software (two different calculating modes were used: High Sensitivity (3DVH‐HS) and Normal Sensitivity (3DVH‐NS)) and in‐house DBDR system. We evaluated the differences between the TPS‐calculated dose and the reconstructed dose using 3D gamma passing rates and DVH dose index analysis. The average 3D gamma passing rates (3%/3 mm) between the TPS‐calculated dose and the reconstructed dose were 99.1 ± 0.6%, 99.7 ± 0.3%, and 100.0 ± 0.1% for 3DVH–HS, 3DVH–NS, and DBDR, respectively. For the prostate cases, the average differences between the TPS‐calculated dose and reconstructed dose in the PTV mean dose were 1.52 ± 0.50%, −0.14 ± 0.55%, and −0.03 ± 0.07% for 3DVH–HS, 3DVH–NS, and DBDR, respectively. For the head and neck and esophagus cases, the dose difference to the TPS‐calculated dose caused by an effect of heterogeneity was more apparent under the 3DVH dose reconstruction than the DBDR. Although with some residual dose reconstruction errors, these dose reconstruction methods can be clinically used as effective tools for DVH‐based QA for VMAT delivery.

Evaluation of four-dimensional computed tomography (4D-CT)-based pulmonary ventilation: The high correlation between 4D-CT ventilation and 81mKr-planar images was found

PURPOSE To evaluate four-dimensional computed tomography (4D-CT)-derived pulmonary ventilation by comparing with (81m)Kr-gas ventilation (VRI). We also proposed two methods to improve the functional accuracy of 4D-CT ventilation images and evaluated these methods. METHODS AND MATERIALS Eleven lung cancer patients with 4D-CT and VRI were analyzed. Hounsfield unit-based (VHU) and a Jacobian-based (VJac) 4D-CT ventilation images were calculated. They were evaluated by voxel-by-voxel spearmans rank correlation coefficient (r) between 4D-CT ventilation and VRI images. After applying an averaging ventilation method and a slope calculating method, correlations were also calculated. RESULTS 4D-CT ventilation showed the high correlation to VRI (r=0.875 with VHU). An averaging method brought significantly higher (p=0.012) correlations to nuclear medicine images with VHU. The improvement was not significant (p=0.619) with VJac. Slope calculating method improved the correlation with VHU and slightly worsened the correlation with VJac. CONCLUSIONS The averaging method we proposed might be useful to improve 4D-CT ventilation images. We found good agreement between 4D-CT ventilation and nuclear medicine ventilation, indicating the high physiologic accuracy of 4D-CT ventilation.

Evaluation of deformable image registration between external beam radiotherapy and HDR brachytherapy for cervical cancer with a 3D‐printed deformable pelvis phantom

Purpose In this study, we developed a 3D‐printed deformable pelvis phantom for evaluating spatial DIR accuracy. We then evaluated the spatial DIR accuracies of various DIR settings for cervical cancer. Methods A deformable female pelvis phantom was created based on patient CT data using 3D printing. To create the deformable uterus phantom, we first 3D printed both a model of uterus and a model of the internal cavities of the vagina and uterus. We then made a mold using the 3D printed uterus phantom. Finally, urethane was poured into the mold with the model of the internal cavities in place, creating the deformable uterus phantom with a cavity into which an applicator could be inserted. To create the deformable bladder phantom, we first 3D printed models of the bladder and of the same bladder scaled down by 2 mm. We then made a mold using the larger bladder model. Finally, silicone was poured into the mold with the smaller bladder model in place to create the deformable bladder phantom with a wall thickness of 2 mm. To emulate the anatomical bladder, water was poured into the created bladder. We acquired phantom image without applicator for EBRT. Then, we inserted the applicator into the phantom to simulate BT. In this situation, we scanned the phantom again to obtain the phantom image for BT. We performed DIR using the two phantom images in two cases: Case A, with full bladder (170 ml) in both EBRT and BT images; and Case B with full bladder in the BT image and half‐full bladder (100 ml) in the EBRT image. DIR was evaluated using Dice similarity coefficients (DSCs) and 31 landmarks for the uterus and 25 landmarks for the bladder. A hybrid intensity and structure DIR algorithm implemented in RayStation with four DIR settings was evaluated. Results On visual inspection, reasonable agreement in shape of the uterus between the phantom and patient CT images was observed for both EBRT and BT, although some regional disagreements in shape of the bladder and rectum were apparent. The created phantom could reproduce the actual patients uterus deformation by the applicator. For both Case A and B, large variation was seen in landmark error among the four DIR parameters. In addition, although DSCs were comparable, moderate differences in landmark error existed between the two different DIR parameters selected from the four DIR parameters (i.e., DSC = 0.96, landmark error = 13.2 ± 5.7 mm vs. DSC = 0.97, landmark error = 9.7 ± 4.0 mm). This result suggests that landmark error evaluation might thus be more effective than DSC for evaluating DIR accuracy. Conclusions Our developed phantom enabled the evaluation of spatial DIR accuracy for the female pelvic region for the first time. Although the DSCs are high, the spatial errors can still be significant and our developed phantom facilitates their quantification. Our results showed that optimization is needed to identify suitable DIR settings. For determining suitable DIR settings, our method of evaluating spatial DIR accuracy using the 3D‐printed phantom may prove helpful.