阿部 幸太

PURPOSE: The purpose of the present study was to evaluate the impact of bone relative electron density (rED) assignment on radiotherapy planning for the abdominal region. METHODS: Twenty patients who received abdominal radiotherapy using MR-Linac and underwent magnetic resonance imaging (MRI) and computed tomography (CT) simulation were analyzed. The reference plan (RP) was established using both CT and MR image sets (RP_CT and RP_MRI). The RP_MRI utilized the bulk density method. The recalculated RPs derived from various rED assignment methods were evaluated for comparison on both datasets. The RPs were recalculated by excluding rED assignment for bones (scenario A). Based on the International Commission on Radiation Units and Measurements report, lung contours were assigned rED of 0.258, and body contours were assigned 1.000 (scenario B) and 1.019 (scenario C). Dose volume histogram (DVH) differences between the three recalculated scenarios and RPs were evaluated. D95, D99, and D1cc were evaluated for target volumes, including gross tumor volume, internal target volume, and planning target volume. DVH parameters, including D1cc for each abdominal organ at risk (OAR) and the mean dose to the liver and kidneys, were evaluated. Three-dimensional local gamma analysis was conducted to assess dose distribution differences between the three recalculated scenarios and RPs. RESULTS: In all scenarios of the CT- and MRI-based validation, the average gamma pass rates (2%/2 mm) were higher than 95%. In the CT-based validation, all target DVHs across the 20 patients showed that none exceeded 2% error in scenario A, whereas 2% and 14% exceeded the threshold in scenarios B and C, respectively. For OARs in CT and MRI-based validation, absolute maximum dose differences when compared with those of the RP were 0.19 Gy and 0.22 Gy, respectively, in scenario A. CONCLUSION: Excluding bone rED considerations in abdominal treatment planning may not yield notable clinical differences.

The purpose of this study was to evaluate the feasibility of treatment plans for prostate cancer with magnetic resonance (MR)-guided online adaptive radiotherapy, which are generated using deformable image registration (DIR)-created contours of the targets and organs. Totally, 150 fractions from 30 prostate cancer patients implanted with a hydrogel spacer and treated with the MR-Linac were studied. Reference treatment plans that satisfied all institutional dose constraints were initially created on planning MRI. The adaptive treatment plans were created on daily MRI based on the reference plan using the DIR-created contours, ensuring all dose constraints were met. Subsequently, a clinician manually created reference contours for each daily MRI. Finally, the dose volume histogram indices of the plan generated with DIR-created contours were re-evaluated with clinician created contours. The evaluated contours included the bladder wall, rectum wall, sigmoid, small bowel and planning target volume (PTV) for dose prescription. The PTV for dose prescription met the dose constraints in all fractions. The bladder and rectum walls met the dose constraint of maximum dose (D0.03 cc) in all fractions. Five patients failed to meet the sigmoid and small bowel dose constraints, with the largest deviation being 13.3% exceedance at D2 cc in the small bowel added 3 mm margin. This study suggests that most treatment plans created without modifying the DIR-created contours are clinically viable. However, dislodgements of the small bowel and sigmoid may exceed the extent of DIR propagation from the reference plan contours, and it is recommended that these contours be verified.

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.