阿部 幸太

PURPOSE: Differences in the contours created during magnetic resonance imaging-guided online adaptive radiotherapy (MRgOART) affect dose distribution. This study evaluated the interobserver error in delineating the organs at risk (OARs) in patients with pancreatic cancer treated with MRgOART. Moreover, we explored the effectiveness of drugs that could suppress peristalsis in restraining intra-fractional motion by evaluating OAR visualization in multiple patients. METHODS: This study enrolled three patients who underwent MRgOART for pancreatic cancer. The study cohort was classified into three conditions based on the MRI sequence and butylscopolamine administration (Buscopan): 1, T2 imaging without butylscopolamine administration; 2, T2 imaging with butylscopolamine administration; and 3, multi-contrast imaging with butylscopolamine administration. Four blinded observers visualized the OARs (stomach, duodenum, small intestine, and large intestine) on MR images acquired during the initial and final MRgOART sessions. The contour was delineated on a slice area of ±2 cm surrounding the planning target volume. The dice similarity coefficient (DSC) was used to evaluate the contour. Moreover, the OARs were visualized on both MR images acquired before and after the contour delineation process during MRgOART to evaluate whether peristalsis could be suppressed. The DSC was calculated for each OAR. RESULTS: Interobserver errors in the OARs (stomach, duodenum, small intestine, large intestine) for the three conditions were 0.636, 0.418, 0.676, and 0.806; 0.725, 0.635, 0.762, and 0.821; and 0.841, 0.677, 0.762, and 0.807, respectively. The DSC was higher in all conditions with butylscopolamine administration compared with those without it, except for the stomach in condition 2, as observed in the last session of MR image. The DSCs for OARs (stomach, duodenum, small intestine, large intestine) extracted before and after contouring were 0.86, 0.78, 0.88, and 0.87; 0.97, 0.94, 0.90, and 0.94; and 0.94, 0.86, 0.89, and 0.91 for conditions 1, 2, and 3, respectively. CONCLUSION: Butylscopolamine effectively reduced interobserver error and intra-fractional motion during the MRgOART treatment.

BACKGROUND: Megavoltage computed tomography (MVCT) images acquired during each radiotherapy session may be useful for delta radiomics. However, no studies have examined whether the MVCT-based radiomics has prognostic power. Therefore, the purpose of this study was to examine the prognostic power of the MVCT-based radiomics for head and neck squamous cell carcinoma (HNSCC) patients. METHODS: 100 HNSCC patients who received definitive radiotherapy were analyzed and divided into two groups: training (n = 70) and test (n = 30) sets. MVCT images obtained using TomoTherapy for the first fraction of radiotherapy and planning kilovoltage CT (kVCT) images obtained using Aquilion LB CT scanner were analyzed. Primary gross tumor volume (GTV) was propagated from kVCT to MVCT images using rigid registration, and 107 radiomic features were extracted from the GTV in MVCT and kVCT images. Least absolute shrinkage and selection operator (LASSO) Cox regression model was used to examine the association between overall survival (OS) and rad score calculated for each patient by weighting the feature value through the coefficient when features were selected. Then, the predictive values of MVCT-based and kVCT-based rad score and patient-, treatment-, and tumor-specific factors were evaluated. RESULTS: C-indices of the rad score for MVCT- and kVCT-based radiomics were 0.667 and 0.685, respectively. The C-indices of 6 clinical factors were 0.538-0.622. The 3-year OS was significantly different between high- and low-risk groups according to the MVCT-based rad score (50% vs. 83%; p < 0.01). CONCLUSIONS: Our results suggested that MVCT-based radiomics had stronger prognostic power than any single clinical factor and was a useful prognostic factor when predicting OS in HNSCC patients.

Background Demyelinating peripheral neuropathy is characteristic of both polyneuropathy, organomegaly, endocrinopathy, M-protein, and skin changes (POEMS) syndrome and chronic inflammatory demyelinating polyneuropathy (CIDP). We hypothesized that the different pathogeneses underlying these entities would affect the sonographic imaging features. Purpose To investigate whether ultrasound (US)-based radiomic analysis could extract features to describe the differences between CIDP and POEMS syndrome. Material and Methods In this retrospective study, we evaluated nerve US images from 26 with typical CIDP and 34 patients with POEMS syndrome. Cross-sectional area (CSA) and echogenicity of the median and ulnar nerves were evaluated in each US image of the wrist, forearm, elbow, and mid-arm. Radiomic analysis was performed on these US images. All radiomic features were examined using receiver operating characteristic analysis. Optimal features were selected using a three-step feature selection method and were inputted into XGBoost to build predictive machine-learning models. Results The CSAs were more enlarged in patients with CIDP than in those with POEMS syndrome without significant differences, except for that of the ulnar nerve at the wrist. Nerve echogenicity was significantly more heterogeneous in patients with CIDP than in those with POEMS syndrome. The radiomic analysis yielded four features with the highest area under the curve (AUC) value of 0.83. The machine-learning model showed an AUC of 0.90. Conclusion US-based radiomic analysis has high AUC values in differentiating POEM syndrome from CIDP. Machine-learning algorithms further improved the discriminative ability.

Abstract Purpose The aim of this study was to develop a new workflow for 1.5-T magnetic resonance (MR)-guided on-line adaptive radiation therapy (MRgART) and assess its feasibility in achieving dose constraints. Materials and methods We retrospectively evaluated the clinical data of patients who underwent on-line adaptive radiation therapy using a 1.5-T MR linear accelerator (MR-Linac). The workflow in MRgART was established by reviewing the disease site, number of fractions, and re-planning procedures. Five cases of prostate cancer were selected to evaluate the feasibility of the new workflow with respect to achieving dose constraints. Results Between December 2021 and September 2022, 50 consecutive patients underwent MRgART using a 1.5-T MR-Linac. Of these, 20 had prostate cancer, 10 had hepatocellular carcinoma, 6 had pancreatic cancer, 5 had lymph node oligo-metastasis, 3 had renal cancer, 3 had bone metastasis, 2 had liver metastasis from colon cancer, and 1 had a mediastinal tumor. Among a total of 247 fractions, 235 (95%) were adapt-to-shape (ATS)-based re-planning. The median ATS re-planning time in all 50 cases was 17 min. In the feasibility study, all dose constraint sets were met in all 5 patients by ATS re-planning. Conversely, a total of 14 dose constraints in 5 patients could not be achieved by virtual plan without using adaptive re-planning. These dose constraints included the minimum dose received by the highest irradiated volume of 1 cc in the planning target volume and the maximum dose of the rectal/bladder wall. Conclusion A new workflow of 1.5-T MRgART was established and found to be feasible. Our evaluation of the dose constraint achievement demonstrated the effectiveness of the workflow.

Abstract Introduction Dosimetric accuracy is critical when a patient treated with volumetric modulated arc therapy (VMAT) is transferred to another beam‐matched linac. To evaluate the performance of Accelerated Go Live (AGL) service, the measured beam characteristics and patient specific quality assurance (QA) results between two AGL‐matched linacs were compared. Materials and Methods Two VersaHD linacs were installed using the AGL service. After the installation, the beam data such as percentage depth dose (PDD), lateral profiles and output factors for all photon beams were measured. Relative doses were also measured as a function of the multi‐leaf collimator (MLC) leaf gap width. Subsequently, VMAT plans were created for prostate, pelvis, head and neck, liver, lung cancers and multiple brain metastases. Dose distributions and point doses were measured by multi‐dimensional detectors and ionization chambers for patient specific quality assurance, and comparisons were made between the two linacs. Results Dose differences in PDDs were all within ± 1% except the entrance region, and the averaged gamma indices of the lateral profiles were within 0.3. The differences in doses as a function of the MLC leaf gap width between the two linacs were within ±0.5%. For all the plans, gamma passing rates were all higher than 95% with criteria of 2%/2 mm. The average and the SD of dose differences on the multi‐dimensional detector between both measurements was 0.06 ± 2.12%, and the average of point dose differences was −0.03 ± 0.33%. Conclusion We have evaluated the AGL performance in the context of beam characteristics and patient specific QA. It was demonstrated that the AGL service provides an accurate VMAT treatment reproducibility for many tumor sites with gamma pass rates greater than 95% under criteria of 2%/2 mm.

Abstract We report the commissioning results of Elekta Unity for the dosimetric performance and mechanical quality assurance (QA), and propose additional commissioning procedures. Mechanical tests included multi-leaf collimator (MLC) positional accuracy, radiation isocenter diameter at the center and off-center position, and coincidence between the magnetic resonance (MR) image center and radiation isocenter. Comparisons between the measurements and calculations of the simple irradiated field, intensity modulated radiation therapy (IMRT) commissioning, MLC output factor ratio, validation of independent dose calculation software and end-to-end testing were performed to evaluate dosimetric performance. The average values of the MLC positional accuracy for film- and imaging device-based analysis were −0.1 and 0.3 mm, respectively. The measured radiation isocenter size was 0.41 mm, and the off-center results were within 1 mm. The coincidence was −0.21, −1.19 and 0.49 mm along the x-, y- and z-axes, respectively. The calculated percent depth doses (PDD) and profiles agreed with the measurements. The results of independent dose calculation were within the action level recommended by American Associations of Physicist in Medicine. The gamma passing rate (GPR) for IMRT commissioning was 98.6 ± 0.9%, and end-to-end testing of adapted plans showed agreement within 2% between the measurement and calculation. We reported the results of mechanical and dosimetric performances of Elekta Unity, and proposed novel commissioning procedures. Our results should provide knowledge to the physics community for enhancing the QA programs.

PURPOSE: Radiomics is a new technique that enables noninvasive prognostic prediction by extracting features from medical images. Homology is a concept used in many branches of algebra and topology that can quantify the contact degree. In the present study, we developed homology-based radiomic features to predict the prognosis of non-small-cell lung cancer (NSCLC) patients and then evaluated the accuracy of this prediction method. METHODS: Four datasets were used: two to provide training and test data and two for the selection of robust radiomic features. All the datasets were downloaded from The Cancer Imaging Archive (TCIA). In two-dimensional cases, the Betti numbers consist of two values: b0 (zero-dimensional Betti number), which is the number of isolated components, and b1 (one-dimensional Betti number), which is the number of one-dimensional or "circular" holes. For homology-based evaluation, computed tomography (CT) images must be converted to binarized images in which each pixel has two possible values: 0 or 1. All CT slices of the gross tumor volume were used for calculating the homology histogram. First, by changing the threshold of the CT value (range: -150 to 300 HU) for all its slices, we developed homology-based histograms for b0 , b1 , and b1 /b0 using binarized images. All histograms were then summed, and the summed histogram was normalized by the number of slices. 144 homology-based radiomic features were defined from the histogram. To compare the standard radiomic features, 107 radiomic features were calculated using the standard radiomics technique. To clarify the prognostic power, the relationship between the values of the homology-based radiomic features and overall survival was evaluated using LASSO Cox regression model and the Kaplan-Meier method. The retained features with nonzero coefficients calculated by the LASSO Cox regression model were used for fitting the regression model. Moreover, these features were then integrated into a radiomics signature. An individualized rad score was calculated from a linear combination of the selected features, which were weighted by their respective coefficients. RESULTS: When the patients in the training and test datasets were stratified into high-risk and low-risk groups according to the rad scores, the overall survival of the groups was significantly different. The C-index values for the homology-based features (rad score), standard features (rad score), and tumor size were 0.625, 0.603, and 0.607, respectively, for the training datasets and 0.689, 0.668, and 0.667 for the test datasets. This result showed that homology-based radiomic features had slightly higher prediction power than the standard radiomic features. CONCLUSIONS: Prediction performance using homology-based radiomic features had a comparable or slightly higher prediction power than standard radiomic features. These findings suggest that homology-based radiomic features may have great potential for improving the prognostic prediction accuracy of CT-based radiomics. In this result, it is noteworthy that there are some limitations.

We evaluated an anthropomorphic head and neck phantom with tissue heterogeneity, produced using a personal 3D printer, with quality assurance (QA), specific to patients undergoing intensity-modulated radiation therapy (IMRT). Using semi-automatic segmentation, 3D models of bone, soft tissue, and an air-filled cavity were created based on computed tomography (CT) images from patients with head and neck cancer treated with IMRT. For the 3D printer settings, polylactide was used for soft tissue with 100% infill. Bone was reproduced by pouring plaster into the cavity created by the 3D printer. The average CT values for soft tissue and bone were 13.0 ± 144.3 HU and 439.5 ± 137.0 HU, respectively, for the phantom and 12.1 ± 124.5 HU and 771.5 ± 405.3 HU, respectively, for the patient. The gamma passing rate (3%/3 mm) was 96.1% for a nine-field IMRT plan. Thus, this phantom may be used instead of a standard shape phantom for patient-specific QA in IMRT.

PURPOSE: We determined correction factors for absorbed dose energy dependence and intrinsic energy dependence for measurements of absorbed dose to water around an 192 Ir source using a radiophotoluminescent glass dosimeter (RPLD) calibrated with a 4-MV photon beam. METHODS: The ratio of the absorbed dose to the water and the average absorbed dose to RPLD for the 192 Ir beam relative to the same ratio in a 4 MV photon beam defines the absorbed dose energy dependence and was determined at distances of 2-10 cm (at intervals of 1 cm) from the 192 Ir source in a water phantom using the egs_chamber user code. The RPLD was calibrated to measure absorbed dose to water, Dw , in a 4 MV photon beam using an ionization chamber, which was also used to measure absorbed dose to water, Dw , in a water phantom using the 192 Ir source. The detector response radiophotoluminescence (RPL signal per average absorbed dose in the detector) in the 192 Ir beam relative to that in the 4 MV photon beam (the relative intrinsic efficiency) was determined experimentally. Finally, the beam quality correction factor was obtained as the quotient between the absorbed dose energy dependence and the relative intrinsic efficiency and corrects for the difference between the beam quality Q0 used at calibration and the beam quality Q used in the measurements. RESULTS: The relative dose ratio of the average absorbed dose to water relative to RPLD ranged from 0.930 to 0.746, and the beam quality correction factor ranged from 0.999 to 0.794 for distances of 2-10 cm from the 192 Ir source. The relative detector response to an 192 Ir source and a 4-MV photon beam was 0.930, and it did not vary significantly with distance. CONCLUSIONS: These results demonstrate that corrections for absorbed dose energy dependence and intrinsic energy dependence are required when using an RPLD to measure with sources different from the reference source providing the primary calibration.

We evaluated the impact of model-based dose calculation algorithms (MBDCAs) on high-dose-rate brachytherapy (HDR-BT) treatment planning for patients with cervical cancer. Seven patients with cervical cancer treated using HDR-BT were studied. Tandem and ovoid applicators were used in four patients, a vaginal cylinder in one, and interstitial needles in the remaining two patients. MBDCAs were applied to the Advanced Collapsed cone Engine (ACE; Elekta, Stockholm, Sweden). All plans, which were originally calculated using TG-43, were re-calculated using both ACE and Monte Carlo (MC) simulations. Air was used as the rectal material. The mean difference in the rectum D2cm3 between ACErec-air and MCrec-air was 8.60 ± 4.64%, whereas that in the bladder D2cm3 was -2.80 ± 1.21%. Conversely, in the small group analysis (n = 4) using water instead of air as the rectal material, the mean difference in the rectum D2cm3 between TG-43 and ACErec-air was 11.87 ± 2.65%, whereas that between TG-43 and ACErec-water was 0.81 ± 2.04%, indicating that the use of water as the rectal material reduced the difference in D2cm3 between TG-43 and ACE. Our results suggested that the differences in the dose-volume histogram (DVH) parameters of TG-43 and ACE were large for the rectum when considerable air (gas) volume was present in it, and that this difference was reduced when the air (gas) volume was reduced. Also, ACE exhibited better dose calculation accuracy than that of TG-43 in this situation. Thus, ACE may be able to calculate the dose more accurately than TG-43 for HDR-BT in treating cervical cancers, particularly for patients with considerable air (gas) volume in the rectum.