Cambridge University Press (CUP)Acta Medica Okayama1460-3969252026Effects of sagging correction calibration error on radiation therapy equipment using image analysise5ENYasushiFujiiDepartment of Radiology, Chugoku Central Hospital of the Mutual Aid Association of Public School TeachersTakahiroNakayamaDepartment of Radiology, Chugoku Central Hospital of the Mutual Aid Association of Public School TeachersJunkiOshitaDepartment of Radiology, Chugoku Central Hospital of the Mutual Aid Association of Public School TeachersAyakaTsunodaDepartment of Radiology, Graduate School of Health Sciences, Okayama UniversityYusukeSaekiDepartment of Radiological Technology, Kawasaki Medical School HospitalYoshinoriTanabe Faculty of Medicine, Graduate School of Health Sciences, Okayama UniversityPurpose: This study investigates the effect of sagging correction errors on image quality and geometric coordinate accuracy.<br>
Methods: This study utilised the Elekta radiotherapy system, ball bearing (BB), Catphan phantom and MultiMet-WL phantom. Ten distinct flex maps (FMs) were acquired by positioning the BB at the accuracy isocentre and introducing shifts of 0.2, 0.4 and 0.6 mm in the left, table and up directions, respectively. Cone-beam computed tomography images of the Catphan phantom were acquired using 10 FMs. The images were analysed for modulation transfer function (MTF) values and geometric coordinates. Additionally, the Winston–Lutz (W-L) test was conducted under reference couch positions and with a 0.3 mm couch shift.<br>
Results: For the Catphan phantom analysis, the standard deviations of MTF10% across FMs were 0.19. The centre-of-gravity coordinates of the insert exhibited shifts of approximately 0.2, 0.4 and 0.6 mm when comparing reference images to those acquired with the shifted FMs. The results of the W-L test with a 0.3 mm couch shift showed radiation isocentre deviations exceeding 1 mm compared to the reference couch positions.<br>
Conclusions: Minor sagging correction calibration errors did not remarkably impact image quality; however, they altered the geometric coordinates of the image isocentre. These calibration errors decreased the accuracy of off-isocentre positioning.No potential conflict of interest relevant to this article was reported.Japanese Society of Radiological TechnologyActa Medica Okayama0369-43058222026放射線治療装置の回転座標系誤差が軸外targetの照射精度に及ぼす影響とTG142のトレランスの評価26-1566ENTakahiroNakayamaDepartment of Radiology, Public Mutual Aid Association Chugoku Central HospitalYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYasushiFujiiDepartment of Radiology, Public Mutual Aid Association Chugoku Central Hospital【目的】放射線治療装置の回転座標系の誤差が軸外targetの照射精度に及ぼす影響を定量的に評価し，TG142における回転座標系誤差（±1.0°）のトレランスの妥当性を検討する．【方法】Elekta社製放射線治療装置（Elekta, Stockholm, Sweden）とMultiMet-WL QAファントム（Sun Nuclear, Melbourne, FL, USA）を用いて，6個のtargetに対してoff isocenterのWinston–Lutz test（WL test）を実施した．Baselineの測定に加え，意図的にcollimator，gantry，couchに+0.5°, +1.0°回転誤差を加えた6条件で測定を行い，照射野中心とtarget中心のベクトル距離（S値）および各方向（gantry-target: GT, left-right: LR, anterior-posterior: AP）の位置ずれを解析した．【結果】Isocenterからの距離が大きいtargetほど位置ずれが顕著であった．特にcollimator回転誤差の影響が最も大きく，isocenterから7 cm離れたtargetでは0.5°の回転誤差でもS値が最大1.24 mmに達した．次に影響が大きかったのはcouch回転であり，gantry回転はtargetの配置が回転軸に近いものが多く相対的に影響が少なかった．回転座標系の誤差は幾何学的誤差の影響が強く，位置ずれに方向依存性があった．【結語】Collimatorやcouchの影響が大きく，0.5°の誤差でも1 mm以上の位置ずれが生じることがあった．Gantryの影響はtargetの配置依存があり，相対的に小さかった．軸外targetの照射において，TG142の±1.0°のトレランスは放射線治療装置の種類にかかわらず最低限遵守するべき基準であり，targetの配置次第では臨床的に十分なマージンを保証できない可能性が示された．Target配置に応じたより厳格な基準と定期的quality assurance（QA）の重要性が示唆された．No potential conflict of interest relevant to this article was reported.Springer Science and Business Media LLCActa Medica Okayama2662-47292025Evaluation of the small-field output factor in eclipse modeling methods using representative beam and measured data with averaged ionization chamber and diode detector measurementsENKunioNishiokaDepartment of Radiology, Tokuyama Central HospitalYukiKuniiDepartment of Radiology, Tokuyama Central HospitalYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYuichiSakamotoDepartment of Radiology, Tokuyama Central HospitalAkiraNakamotoDepartment of Radiology, Tokuyama Central HospitalShotaroTakahashiDepartment of Radiology, Tokuyama Central HospitalBeam modeling for radiotherapy treatment planning systems (RTPS) can be performed using representative beam data (RBD) or direct measurements. However, RBD typically excludes output factor (OPF) measurements for fields smaller than 3 × 3 cm2. The Eclipse treatment planning system addresses this limitation by incorporating measured OPF data for fields as small as 1 × 1 cm2. Although existing studies have primarily examined the accuracy of small-field OPFs for plastic scintillator detectors, studies directly comparing the OPF values obtained through RBD modeling with and without OPF measurements for small field sizes are limited. Therefore, this study proposes a novel measurement approach using data averaged from an ion chamber and diode detector for small-field dosimetry to provide critical insights into the integration of OPFs for these small field sizes in RBD-based beam modeling. We systematically evaluated the impact of small-field OPF measurements on beam modeling accuracy by comparing three distinct approaches: (1) RBD-based modeling without small-field OPF data, (2) RBD-based modeling incorporating measured small-field OPF data, and (3) modeling based solely on measured data, with and without the inclusion of 1 × 1 cm2 field sizes. In addition, we compared OPF values obtained from a W2 plastic scintillator detector with the averaged OPF values from a PinPoint 3D ion chamber and EDGE diode detector across multiple beam energies and flattening filter-free (FFF) configurations. Our analysis included field sizes ranging from 1 × 1 cm2 to 40 × 40 cm2. The results demonstrated that for square fields, OPF calculation differences between RBD modeling with and without measured data were < 1.5%, < 4.5%, and < 4.5% at 1 × 1 cm2, and < 0.5%, < 1.5%, and < 1.5% at 2 × 2 cm2, respectively. The RBD group exhibited a trend in which the OPF difference increased with the expansion of the irradiation field size. Notably, the most significant variations between modeling approaches occurred along the upper jaw expansion direction in rectangular fields. This suggests that a thorough evaluation is necessary for modeling results with an OPF ≤ 1 × 1 cm2. This study highlights the advantages and disadvantages of beam modeling using measured OPF and RBD, providing valuable insights for future facilities that rely solely on RBD for beam modeling.No potential conflict of interest relevant to this article was reported.Elsevier BVActa Medica Okayama1078-81743162025Evaluation of a method to predict positioning errors in orthopantomography using cephalography103174ENS.ImajoDivision of Radiology, Medical Support Department, Okayama University HospitalM.HondaDivision of Radiology, Medical Support Department, Okayama University HospitalY.TanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityIntroduction: Various radiographic examinations are used to diagnose diseases and determine treatment plans, and the quality of radiographic images affects diagnostic accuracy. This study assessed the relationship between orthopantomography and cephalometric analysis in predicting positioning errors before orthopantomography.<br>
Methods: This study evaluated four human head phantom types and included 300 patients aged ≥18 years who underwent orthopantomography. The correlation between the Frankfort horizontal plane and occlusal plane angles in the orthopantomogram was analyzed. The occlusal plane angle at a Frankfort horizontal plane of 0° was estimated using a linear approximation formula. Frankfort horizontal plane and occlusal plane angles were measured on the cephalograms, and their differences were analyzed for correlation with the occlusal plane angle at a Frankfort horizontal plane of 0° in the corresponding orthopantomograms. The cephalogram’s condylar plane–corpus line angle was also compared with orthopantomogram measurements.<br>
Results: Frankfort horizontal and occlusal plane angles demonstrated a strong negative correlation (r < −0.9) in phantom studies and moderate negative correlation (r < −0.4) in clinical orthopantomograms. In the phantoms, the occlusal plane at a Frankfort horizontal of 0° in the orthopantomogram strongly correlated with the difference between the Frankfort horizontal and condylar plane–corpus line angles in the cephalogram.<br>
Conclusion: Adjusting patient positioning based on individual skeletal differences and angles may reduce positioning errors and improve image quality. Cephalogram analysis could help determine an appropriate Frankfort plane angle for each patient when acquiring orthopantomograms.<br>
Implications for practice: Integrating cephalometric analysis into positioning protocols enhances radiographic accuracy, reduces retakes, and improves diagnostic reliability in clinical positioning. This research could improve image quality by identifying reference indicators for orthopantomography by incorporating data from images other than cephalograms, such as computed tomography and magnetic resonance imaging.No potential conflict of interest relevant to this article was reported.Springer Science and Business Media LLCActa Medica Okayama2090-47625612025Evaluating a discretized data acquisition method for couch modeling to streamline the commissioning process of radiological instruments64ENSyoutaTomimotoDepartment of Radiological Technology, Faculty of Medicine, Graduate School of Health Sciences, Okayama UniversityYusukeSaekiDepartment of Radiological Technology, Kawasaki Medical School HospitalOkihiroMotodaDepartment of Radiological Technology, Kawasaki Medical School HospitalMasatoTanakaDepartment of Radiological Technology, Kawasaki Medical School HospitalSyoukiTsumotoDepartment of Radiological Technology, Faculty of Medicine, Graduate School of Health Sciences, Okayama UniversityHanaNishikawaDepartment of Radiological Technology, Faculty of Medicine, Graduate School of Health Sciences, Okayama UniversityYukiMiyashimaDepartment of Radiological Technology, Kawasaki Medical School HospitalMakikoHiguchiDepartment of Radiological Technology, Kawasaki Medical School HospitalTadashiTaniDepartment of Radiological Technology, Kawasaki Medical School HospitalKuniakiKatsuiDepartment of Radiology, Kawasaki Medical SchoolYoshinoriTanabeDepartment of Radiological Technology, Faculty of Medicine, Graduate School of Health Sciences, Okayama UniversityBackground The commissioning of radiotherapy treatment planning system (RTPS) involves many time-consuming tests to maintain consistency between actual and planned dose. As the number of new technologies and peripheral devices increases year by year, there is a need for time-efficient and accurate commissioning of radiation therapy equipment. Couch modeling is one type of commissioning, and there are no recommended values for CT due to differences in equipment calibration between facilities. This study evaluated the optimal electron density (ED) for the couch using discretized gantry angles.<br>
Results All discrete-angle groups showed a high correlation between the surface ED and dose difference between the actual and planned doses (|r|> 0.9). AcurosXB did not demonstrate a significant correlation between dose differences and each energy. For a small number of discretized gantry groups, the optimal couch modeling results revealed several combinations of surface and interior ED with the same score. Upon adding all couch thickness scores, all energy scores, and both algorithm scores, the optimal surface and interior EDs with the highest score across all couch thicknesses were 0.4 and 0.07, respectively.<br>
Conclusions The optimal couch surface ED dose difference trend was identified, and the effectiveness indicated using the dose difference score from discrete-angle couch modeling. Using this method, couch modeling can be evaluated in a highly precise and quick manner, which helps in the commissioning of complicated linear accelerator and radiological treatment plans.No potential conflict of interest relevant to this article was reported.Springer Science and Business Media LLCActa Medica Okayama2662-47292025Impact of differences in computed tomography value-electron density/physical density conversion tables on calculate dose in low-density areasENMiaNomuraFaculty of Health Sciences, Department of Radiological Technology, Okayama University Medical School, Okayama UniversityShunsukeGotoGraduate School of Health Sciences, Department of Radiological Technology, Okayama UniversityMizukiYoshiokaFaculty of Health Sciences, Department of Radiological Technology, Okayama University Medical School, Okayama UniversityYuikoKatoFaculty of Health Sciences, Department of Radiological Technology, Okayama University Medical School, Okayama UniversityAyakaTsunodaFaculty of Health Sciences, Department of Radiological Technology, Okayama University Medical School, Okayama UniversityKunioNishiokaDepartment of Radiology, Tokuyama Central HospitalYoshinoriTanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityIn radiotherapy treatment planning, the extrapolation of computed tomography (CT) values for low-density areas without known materials may differ between CT scanners, resulting in different calculated doses. We evaluated the differences in the percentage depth dose (PDD) calculated using eight CT scanners. Heterogeneous virtual phantoms were created using LN-300 lung and − 900 HU. For the two types of virtual phantoms, the PDD on the central axis was calculated using five energies, two irradiation field sizes, and two calculation algorithms (the anisotropic analytical algorithm and Acuros XB). For the LN-300 lung, the maximum CT value difference between the eight CT scanners was 51 HU for an electron density (ED) of 0.29 and 8.8 HU for an extrapolated ED of 0.05. The LN-300 lung CT values showed little variation in the CT-ED/physical density data among CT scanners. The difference in the point depth for the PDD in the LN-300 lung between the CT scanners was < 0.5% for all energies and calculation algorithms. Using Acuros XB, the PDD at − 900 HU had a maximum difference between facilities of > 5%, and the dose difference corresponding to an LN-300 lung CT value difference of > 20 HU was > 1% at a field size of 2 × 2 cm2. The study findings suggest that the calculated dose of low-density regions without known materials in the CT-ED conversion table introduces a risk of dose differences between facilities because of the calibration of the CT values, even when the same CT-ED phantom radiation treatment planning and treatment devices are used.No potential conflict of interest relevant to this article was reported.Oxford University PressActa Medica Okayama0144-84202025Optimizing radiation dose and image quality in neonatal mobile radiographyncaf080ENTakahikoMaedaGraduate School of Health Sciences, Department of Radiological Technology, Okayama UniversityMakotoHaraDepartment of Radiology, Hyogo Prefectural Kobe Children’s HospitalHiroyukiYamasakiDepartment of Radiology, Hyogo Prefectural Kobe Children’s HospitalMakotoNakaharaDepartment of Radiology, Hyogo Prefectural Tamba Medical CenterYoshinoriTanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityChildren are more susceptible to radiation exposure than adults. Therefore, determining an appropriate radiation dose requires balancing and minimizing radiation exposure while maintaining image quality (IQ) for accurate diagnosis. We evaluated the optimal radiation dose parameters for neonatal chest and abdominal mobile radiography by assessing entrance surface dose and IQ indices. A range of exposure parameters was tested on neonatal and acrylic phantoms, and the optimal settings were determined through visual and physical evaluations. Overall, 65 kVp and 1.2 mAs provided the best balance between minimizing radiation exposure and maintaining high IQ for neonates. This study offers essential insights into optimizing radiographic conditions for neonatal care, contributing to safe and effective radiological practices. These optimized parameters can help guide future clinical applications by ensuring reduced radiation risk and enhanced diagnostic accuracy.No potential conflict of interest relevant to this article was reported.MDPIActa Medica Okayama2075-44181562025Robustness of Machine Learning Predictions for Determining Whether Deep Inspiration Breath-Hold Is Required in Breast Cancer Radiation Therapy668ENWlla E.Al-HammadDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityMasahiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityJamal, GhaidaAl JamalDepartment of Oral Medicine and Oral Surgery, Faculty of Dentistry, Jordan University of Science and TechnologyMamikoFujikuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityRyoKamizakiRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKazuhiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversitySuzukaYoshidaDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYoshihideNakamuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityYoshinoriTanabeRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKoheiSugimotoRadiological Technology, Graduate School of Health Sciences, Okayama UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityMajdBarhamDepartment of Dentistry and Dental Surgery, College of Medicine and Health Sciences, An-Najah National UniversityNouhaTekikiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityMikiHisatomiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityJunichiAsaumiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityBackground/Objectives: Deep inspiration breath-hold (DIBH) is a commonly used technique to reduce the mean heart dose (MHD), which is critical for minimizing late cardiac side effects in breast cancer patients undergoing radiation therapy (RT). Although previous studies have explored the potential of machine learning (ML) to predict which patients might benefit from DIBH, none have rigorously assessed ML model performance across various MHD thresholds and parameter settings. This study aims to evaluate the robustness of ML models in predicting the need for DIBH across different clinical scenarios. Methods: Using data from 207 breast cancer patients treated with RT, we developed and tested ML models at three MHD cut-off values (240, 270, and 300 cGy), considering variations in the number of independent variables (three vs. six) and folds in the cross-validation (three, four, and five). Robustness was defined as achieving high F2 scores and low instability in predictive performance. Results: Our findings indicate that the decision tree (DT) model demonstrated consistently high robustness at 240 and 270 cGy, while the random forest model performed optimally at 300 cGy. At 240 cGy, a threshold critical to minimize late cardiac risks, the DT model exhibited stable predictive power, reducing the risk of overestimating DIBH necessity. Conclusions: These results suggest that the DT model, particularly at lower MHD thresholds, may be the most reliable for clinical applications. By providing a tool for targeted DIBH implementation, this model has the potential to enhance patient-specific treatment planning and improve clinical outcomes in RT.No potential conflict of interest relevant to this article was reported.MDPIActa Medica Okayama2075-44181562025Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis790ENSuzukaYoshidaDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityMasahiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYoshihideNakamuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYukaFukumuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYukiNakamitsuRadiological Technology, Graduate School of Health Sciences, Okayama UniversityWlla E.Al-HammadDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityKazuhiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYudaiShimizuDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYoshinoriTanabeRadiological Technology, Graduate School of Health Sciences, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityMajdBarhamDepartment of Dentistry and Dental Surgery, College of Medicine and Health Sciences, An-Najah National UniversityNouhaTekikiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityNurul N.KamaruddinDepartment of Oral Rehabilitation and Regenerative Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityMikiHisatomiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYoshinobuYanagiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityJunichiAsaumiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityBackground/Objectives: Mean kurtosis (MK) values in simple diffusion kurtosis imaging (SDI)-a type of diffusion kurtosis imaging (DKI)-have been reported to be useful in the diagnosis of head and neck malignancies, for which pre-processing with smoothing filters has been reported to improve the diagnostic accuracy. Multi-parameter analysis using DKI in combination with other image types has recently been reported to improve the diagnostic performance. The purpose of this study was to evaluate the usefulness of machine learning (ML)-based multi-parameter analysis using the MK and apparent diffusion coefficient (ADC) values-which can be acquired simultaneously through SDI-for the differential diagnosis of benign and malignant head and neck tumors, which is important for determining the treatment strategy, as well as examining the usefulness of filter pre-processing. Methods: A total of 32 pathologically diagnosed head and neck tumors were included in the study, and a Gaussian filter was used for image pre-processing. MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. Results: Bi-parameter analysis with gradient boosting achieved the best diagnostic performance, with an AUC of 0.81. Conclusions: The usefulness of bi-parameter analysis with ML methods for the differential diagnosis of benign and malignant head and neck tumors using SDI data were demonstrated.No potential conflict of interest relevant to this article was reported.ElsevierActa Medica Okayama0958-39474942024Evaluation of the trend of set-up errors during the treatment period using set-up margin in prostate radiotherapy291297ENHinakoSasakiDepartment of Radiological Technology, Faculty of Health Sciences, Okayama University Medical SchoolTakumiMorishitaDepartment of Radiological Technology, Faculty of Health Sciences, Okayama University Medical SchoolNahoIrieDepartment of Radiological Technology, Faculty of Health Sciences, Okayama University Medical SchoolRenaKojimaDepartment of Radiological Technology, Faculty of Health Sciences, Okayama University Medical SchoolTetsukazuKiriyamaDepartment of Radiology, Uwajima City HospitalAkiraNakamotoDepartment of Radiology, Tokuyama Central HospitalKunioNishiokaDepartment of Radiology, Tokuyama Central HospitalShotaroTakahashiDepartment of Radiology, Tokuyama Central HospitalYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityAccurate information on set-up error during radiotherapy is essential for determining the optimal number of treatments in hypofractionated radiotherapy for prostate cancer. This necessitates careful control by the radiotherapy staff to assess the patient's condition. This study aimed to develop an evaluation method of the temporal trends in a patient's specific prostate movement during treatment using image matching and margin values. This study included 65 patients who underwent prostate volumetric modulated arc therapy (mean treatment time, 87.2 s). Set-up errors were assessed using bone, inter-, and intra-fraction marker matching across 39 fractions. The set-up margin was determined by dividing the four periods into 39 fractions using Stroom's formula and correlation coefficient. The intra-fraction set-up error was biased in the anterior-superior (AS) direction during treatment. The temporal trend of set-up errors during radiotherapy slightly increased based on bone matching and inter-fraction marker matching, with a 1.6-mm difference in the set-up margin fractions 11 to 20. The correlation coefficient of the mean prostate movement during treatment significantly decreased in the superior-inferior direction, while remaining high in the left-right and anterior-posterior directions. Image matching contributed significantly to the improvement of set-up errors; however, careful attention is needed for prostate movement in the AS direction, particularly during short treatment times. Understanding the trend of set-up errors during the treatment period is essential in numerical information sharing on patient condition and evaluating the margins for tailored hypo-fractionated radiotherapy, considering the facility's image-guided radiation therapy technology.No potential conflict of interest relevant to this article was reported.Springer Science and Business Media LLCActa Medica Okayama2662-47294732024Evaluation of output factors of different radiotherapy planning systems using Exradin W2 plastic scintillator detector11771189ENYasuharuAndoHiroshima City HospitalMasahiroOkadaHiroshima City North Medical Center Asa Citizens HospitalNatsukoMatsumotoHiroshima City North Medical Center Asa Citizens HospitalKawasakiIkuhiroHiroshima City North Medical Center Asa Citizens HospitalSoichiroIshiharaHiroshima City HospitalHiroshiKiriuHiroshima City HospitalYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityThis study aims to evaluate the output factors (OPF) of different radiation therapy planning systems (TPSs) using a plastic scintillator detector (PSD). The validation results for determining a practical field size for clinical use were verified. The implemented validation system was an Exradin W2 PSD. The focus was to validate the OPFs of the small irradiation fields of two modeled radiation TPSs using RayStation version 10.0.1 and Monaco version 5.51.10. The linear accelerator used for irradiation was a TrueBeam with three energies: 4, 6, and 10 MV. RayStation calculations showed that when the irradiation field size was reduced from 10 × 10 to 0.5 × 0.5 cm2, the results were within 2.0% of the measured values for all energies. Similarly, the values calculated using Monaco were within approximately 2.0% of the measured values for irradiation field sizes between 10 × 10 and 1.5 × 1.5 cm2 for all beam energies of interest. Thus, PSDs are effective validation tools for OPF calculations in TPS. A TPS modeled with the same source data has different minimum irradiation field sizes that can be calculated. These findings could aid in verification of equipment accuracy for treatment planning requiring highly accurate dose calculations and for third-party evaluation of OPF calculations for TPS.No potential conflict of interest relevant to this article was reported.MDPIActa Medica Okayama2077-03831362024Enhancing Diagnostic Precision: Evaluation of Preprocessing Filters in Simple Diffusion Kurtosis Imaging for Head and Neck Tumors1783ENYukiNakamitsuRadiological Technology, Graduate School of Health Sciences, Okayama UniversityMasahiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYudaiShimizuDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityKazuhiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYuukiYoshimuraRadiological Technology, Graduate School of Health Sciences, Okayama UniversitySuzukaYoshidaDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityYoshihideNakamuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityYukaFukumuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityRyoKamizakiRadiological Technology, Graduate School of Health Sciences, Okayama UniversityWlla E.Al-HammadDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityYoshinoriTanabeRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKoheiSugimotoRadiological Technology, Graduate School of Health Sciences, Okayama UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityMajdBarhamDepartment of Dentistry and Dental Surgery, College of Medicine and Health Sciences, An-Najah National UniversityNouhaTekikiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityJunichiAsaumiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama UniversityBackground: Our initial clinical study using simple diffusion kurtosis imaging (SDI), which simultaneously produces a diffusion kurtosis image (DKI) and an apparent diffusion coefficient map, confirmed the usefulness of SDI for tumor diagnosis. However, the obtained DKI had noticeable variability in the mean kurtosis (MK) values, which is inherent to SDI. We aimed to improve this variability in SDI by preprocessing with three different filters (Gaussian [G], median [M], and nonlocal mean) of the diffusion-weighted images used for SDI. Methods: The usefulness of filter parameters for diagnosis was examined in basic and clinical studies involving 13 patients with head and neck tumors. Results: The filter parameters, which did not change the median MK value, but reduced the variability and significantly homogenized the MK values in tumor and normal tissues in both basic and clinical studies, were identified. In the receiver operating characteristic curve analysis for distinguishing tumors from normal tissues using MK values, the area under curve values significantly improved from 0.627 without filters to 0.641 with G (sigma = 0.5) and 0.638 with M (radius = 0.5). Conclusions: Thus, image pretreatment with G and M for SDI was shown to be useful for improving tumor diagnosis in clinical practice.No potential conflict of interest relevant to this article was reported.Springer Science and Business Media LLCActa Medica Okayama2662-47294722024Evaluation of the effect of sagging correction calibration errors in radiotherapy software on image matching589596ENYumiYamazawaDepartment of Radiology, Niigata Prefectural Central HospitalAkitaneOsakaDepartment of Radiology, Niigata Prefectural Central HospitalYasushiFujiiDepartment of Radiology, Chugoku Central Hospital of the Mutual Aid Association of Public School TeachersTakahiroNakayamaDepartment of Radiology, Chugoku Central Hospital of the Mutual Aid Association of Public School TeachersKunioNishiokaDepartment of Radiology, Tokuyama Central HospitalYoshinoriTanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityTo investigate the impact of sagging correction calibration errors in radiotherapy software on image matching. Three software applications were used, with and without a polymethyl methacrylate rod supporting the ball bearings (BB). The calibration error for sagging correction across nine flex maps (FMs) was determined by shifting the BB positions along the Left–Right (LR), Gun–Target (GT), and Up–Down (UD) directions from the reference point. Lucy and pelvic phantom cone-beam computed tomography (CBCT) images underwent auto-matching after modifying each FM. Image deformation was assessed in orthogonal CBCT planes, and the correlations among BB shift magnitude, deformation vector value, and differences in auto-matching were analyzed. The average difference in analysis results among the three softwares for the Winston–Lutz test was within 0.1 mm. The determination coefficients (R2) between the BB shift amount and Lucy phantom matching error in each FM were 0.99, 0.99, and 1.00 in the LR-, GT-, and UD-directions, respectively. The pelvis phantom demonstrated no cross-correlation in the GT direction during auto-matching error evaluation using each FM. The correlation coefficient (r) between the BB shift and the deformation vector value was 0.95 on average for all image planes. Slight differences were observed among software in the evaluation of the Winston–Lutz test. The sagging correction calibration error in the radiotherapy imaging system was caused by an auto-matching error of the phantom and deformation of CBCT images.No potential conflict of interest relevant to this article was reported.SpringerActa Medica Okayama2090-47625512024Evaluating the index of panoramic X-ray image quality using K-means clustering method4ENSatoshiImajoDivision of Radiology, Medical Support Department, Okayama University HospitalYoshinoriTanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityNobueNakamuraDivision of Radiology, Medical Support Department, Okayama University HospitalMitsugiHondaDivision of Radiology, Medical Support Department, Okayama University HospitalMasahiroKurodaFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityBackground A panoramic X-ray image is generally considered optimal when the occlusal plane is slightly arched, presenting with a gentle curve. However, the ideal angle of the occlusal plane has not been determined. This study provides a simple evaluation index for panoramic X-ray image quality, built using various image and cluster analyzes, which can be used as a training tool for radiological technologists and as a reference for image quality improvement.<br>
Results A reference panoramic X-ray image was acquired using a phantom with the Frankfurt plane positioned horizontally, centered in the middle, and frontal plane centered on the canine teeth. Other images with positioning errors were acquired with anteroposterior shifts, vertical rotations of the Frankfurt plane, and horizontal left/right rotations. The reference and positioning-error images were evaluated with the cross-correlation coefficients for the occlusal plane profile, left/right angle difference, peak signal-to-noise ratio (PSNR), and deformation vector fields (DVF). The results of the image analyzes were scored for positioning-error images using K-means clustering analysis. Next, we analyzed the correlations between the total score, cross-correlation analysis of the occlusal plane curves, left/right angle difference, PSNR, and DVF. In the scoring, the positioning-error images with the highest quality were the ones with posterior shifts of 1 mm. In the analysis of the correlations between each pair of results, the strongest correlations (r = 0.7–0.9) were between all combinations of PSNR, DVF, and total score.<br>
Conclusions The scoring of positioning-error images using K-means clustering analysis is a valid evaluation indicator of correct patient positioning for technologists in training.No potential conflict of interest relevant to this article was reported.MDPIActa Medica Okayama2075-441813242023Characteristic Mean Kurtosis Values in Simple Diffusion Kurtosis Imaging of Dentigerous Cysts3619ENYukaFukumuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityMasahiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversitySuzukaYoshidaDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYoshihideNakamuraDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYukiNakamitsuRadiological Technology, Graduate School of Health Sciences, Okayama UniversityWllaAl-HammadDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityKazuhiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityRyoKamizakiRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYudaiShimizuDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYoshinoriTanabeRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKoheiSugimotoRadiological Technology, Graduate School of Health Sciences, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityMajdBarhamDepartment of Dentistry and Dental Surgery, College of Medicine and Health Sciences, An-Najah National UniversityNouhaTekikiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityNurulKamaruddinDepartment of Oral Rehabilitation and Regenerative Medicine, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityYoshinobuYanagiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityJunichiAsaumiDepartment of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityWe evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10−6 mm2/s, OKC: 925 × 10−6 mm2/s, R: 2718 × 10−6 mm2/s, and M: 2686 × 10−6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts.No potential conflict of interest relevant to this article was reported.Spandidos PublicationsActa Medica Okayama1792-09812652023Evaluation of the accuracy of heart dose prediction by machine learning for selecting patients not requiring deep inspiration breath‑hold radiotherapy after breast cancer surgery536ENRyoKamizakiDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityMasahiroKurodaDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityWllaAl‑HammadDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesNouhaTekikiDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesHinataIshizakaDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityKazuhiroKurodaDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityKoheiSugimotoDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityMajdBarhamDepartment of Dentistry and Dental Surgery, College of Medicine and Health Sciences, An‑Najah National UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityYukiNakamitsuDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityMasakiHiranoDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYukiMutoDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityHirokiIharaDepartment of Radiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversitySoichiSugiyamaDepartment of Proton Beam Therapy, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityIncreased heart dose during postoperative radiotherapy (RT) for left‑sided breast cancer (BC) can cause cardiac injury, which can decrease patient survival. The deep inspiration breath‑hold technique (DIBH) is becoming increasingly common for reducing the mean heart dose (MHD) in patients with left‑sided BC. However, treatment planning and DIBH for RT are laborious, time‑consuming and costly for patients and RT staff. In addition, the proportion of patients with left BC with low MHD is considerably higher among Asian women, mainly due to their smaller breast volume compared with that in Western countries. The present study aimed to determine the optimal machine learning (ML) model for predicting the MHD after RT to pre‑select patients with low MHD who will not require DIBH prior to RT planning. In total, 562 patients with BC who received postoperative RT were randomly divided into the trainval (n=449) and external (n=113) test datasets for ML using Python (version 3.8). Imbalanced data were corrected using synthetic minority oversampling with Gaussian noise. Specifically, right‑left, tumor site, chest wall thickness, irradiation method, body mass index and separation were the six explanatory variables used for ML, with four supervised ML algorithms used. Using the optimal value of hyperparameter tuning with root mean squared error (RMSE) as an indicator for the internal test data, the model yielding the best F2 score evaluation was selected for final validation using the external test data. The predictive ability of MHD for true MHD after RT was the highest among all algorithms for the deep neural network, with a RMSE of 77.4, F2 score of 0.80 and area under the curve‑receiver operating characteristic of 0.88, for a cut‑off value of 300 cGy. The present study suggested that ML can be used to pre‑select female Asian patients with low MHD who do not require DIBH for the postoperative RT of BC.No potential conflict of interest relevant to this article was reported.MDPIActa Medica Okayama1198-00523082023Mean Heart Dose Prediction Using Parameters of Single-Slice Computed Tomography and Body Mass Index: Machine Learning Approach for Radiotherapy of Left-Sided Breast Cancer of Asian Patients74127424ENWlla E.Al-HammadDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesMasahiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityRyoKamizakiRadiological Technology, Graduate School of Health Sciences, Okayama UniversityNouhaTekikiDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesHinataIshizakaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKazuhiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKoheiSugimotoRadiological Technology, Graduate School of Health Sciences, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityYoshinoriTanabeRadiological Technology, Graduate School of Health Sciences, Okayama UniversityMajdBarhamDepartment of Dentistry and Dental Surgery, College of Medicine and Health Sciences, An-Najah National UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityYudaiShimizuDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesYukiNakamitsuRadiological Technology, Graduate School of Health Sciences, Okayama UniversityJunichiAsaumiDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesDeep inspiration breath-hold (DIBH) is an excellent technique to reduce the incidental radiation received by the heart during radiotherapy in patients with breast cancer. However, DIBH is costly and time-consuming for patients and radiotherapy staff. In Asian countries, the use of DIBH is restricted due to the limited number of patients with a high mean heart dose (MHD) and the shortage of radiotherapy personnel and equipment compared to that in the USA. This study aimed to develop, evaluate, and compare the performance of ten machine learning algorithms for predicting MHD using a patient's body mass index and single-slice CT parameters to identify patients who may not require DIBH. Machine learning models were built and tested using a dataset containing 207 patients with left-sided breast cancer who were treated with field-in-field radiotherapy with free breathing. The average MHD was 251 cGy. Stratified repeated four-fold cross-validation was used to build models using 165 training data. The models were compared internally using their average performance metrics: F2 score, AUC, recall, accuracy, Cohen's kappa, and Matthews correlation coefficient. The final performance evaluation for each model was further externally analyzed using 42 unseen test data. The performance of each model was evaluated as a binary classifier by setting the cut-off value of MHD & GE; 300 cGy. The deep neural network (DNN) achieved the highest F2 score (78.9%). Most models successfully classified all patients with high MHD as true positive. This study indicates that the ten models, especially the DNN, might have the potential to identify patients who may not require DIBH.No potential conflict of interest relevant to this article was reported.SciendoActa Medica Okayama1898-03092922023Objective evaluation method using multiple image analyses for panoramic radiography improvement8591ENSatoshiImajoDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYoshinoriTanabeDepartment of Radiological Technology, Faculty of Health Sciences, Okayama UniversityNobueNakamuraDivision of Radiology, Medical Support Department, Okayama University HospitalMitsugiHondaDivision of Radiology, Medical Support Department, Okayama University HospitalMasahiroKurodaDepartment of Radiological Technology, Faculty of Health Sciences, Okayama UniversityIntroduction: In the standardization of panoramic radiography quality, the education and training of beginners on panoramic radiographic imaging are important. We evaluated the relationship between positioning error factors and multiple image analysis results for reproducible panoramic radiography.<br>
Material and methods: Using a panoramic radiography system and a dental phantom, reference images were acquired on the Frankfurt plane along the horizontal direction, midsagittal plane along the left-right direction, and for the canine on the forward-backward plane. Images with positioning errors were acquired with 1-5 mm shifts along the forward-backward direction and 2-10 degrees rotations along the horizontal (chin tipped high/low) and vertical (left-right side tilt) directions on the Frankfurt plane. The cross-correlation coefficient and angle difference of the occlusion congruent plane profile between the reference and positioning error images, peak signal-to-noise ratio (PSNR), and deformation vector value by deformable image registration were compared and evaluated.<br>
Results: The cross-correlation coefficients of the occlusal plane profiles showed the greatest change in the chin tipped high images and became negatively correlated from 6 degrees image rotation (r = -0.29). The angle difference tended to shift substantially with increasing positioning error, with an angle difference of 8.9 degrees for the 10 degrees chin tipped low image. The PSNR was above 30 dB only for images with a 1-mm backward shift. The positioning error owing to the vertical rotation was the largest for the deformation vector value.<br>
Conclusions: Multiple image analyses allow to determine factors contributing to positioning errors in panoramic radiography and may enable error correction. This study based on phantom imaging can support the education of beginners regarding panoramic radiography.No potential conflict of interest relevant to this article was reported.Okayama University Medical SchoolActa Medica Okayama0386-300X7732023Usefulness of Simple Diffusion Kurtosis Imaging for Head and Neck Tumors: An Early Clinical Study273280ENYudaiShimizuDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesMasahiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYukiNakamitsuRadiological Technology, Graduate School of Health Sciences, Okayama UniversityWlla E.Al-HammadDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesSuzukaYoshidaDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesYukaFukumuraDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesYoshihideNakamuraDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesKazuhiroKurodaRadiological Technology, Graduate School of Health Sciences, Okayama UniversityRyoKamizakiRadiological Technology, Graduate School of Health Sciences, Okayama UniversitySatoshiImajohRadiological Technology, Graduate School of Health Sciences, Okayama UniversityYoshinoriTanabeRadiological Technology, Graduate School of Health Sciences, Okayama UniversityKoheiSugimotoGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityBabatunde O.BamgboseDepartment of Oral Diagnostic Sciences, Faculty of Dentistry, Bayero UniversityYoshinobuYanagiDepartment of Dental Informatics, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityJunichiAsaumiDepartment of Oral and Maxillofacial Radiology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama UniversityOriginal Article10.18926/AMO/65492Diffusion kurtosis (DK) imaging (DKI), a type of restricted diffusion-weighted imaging, has been reported to be useful for tumor diagnoses in clinical studies. We developed a software program to simultaneously create DK images with apparent diffusion coefficient (ADC) maps and conducted an initial clinical study. Multi-shot echo-planar diffusion-weighted images were obtained at b-values of 0, 400, and 800 sec/mm2 for simple DKI, and DK images were created simultaneously with the ADC map. The usefulness of the DK image and ADC map was evaluated using a pixel analysis of all pixels and a median analysis of the pixels of each case. Tumor and normal tissues differed significantly in both pixel and median analyses. In the pixel analysis, the area under the curve was 0.64 for the mean kurtosis (MK) value and 0.77 for the ADC value. In the median analysis, the MK value was 0.74, and the ADC value was 0.75. The MK and ADC values correlated moderately in the pixel analysis and strongly in the median analysis. Our simple DKI system created DK images simultaneously with ADC maps, and the obtained MK and ADC values were useful for differentiating head and neck tumors from normal tissue.No potential conflict of interest relevant to this article was reported.Spandidos PublicationsActa Medica Okayama1792-09812532023Quantitative evaluation of the reduction of distortion and metallic artifacts in magnetic resonance images using the multiacquisition variable‑resonance image combination selective sequence109ENMasakiHiranoDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYukiMutoDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityMasahiroKurodaDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYutaFujiwaraDivision of Clinical Radiology Service, Okayama Central HospitalTomoakiSasakiDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityKazuhiroKurodaDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityRyoKamizakiDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversitySatoshiImajohDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityWllaE. Al-HammadDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesYukiNakamitsuDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama 700‑8558, JapanYudaiShimizuDepartment of Oral and Maxillofacial Radiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesKoheiSugimotoGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama University, Okayama, 770‑8558, JapanMasatakaOitaGraduate School of Interdisciplinary Sciences and Engineering in Health Systems, Okayama UniversityIrfanSugiantoDepartment of Oral Radiology, Faculty of Dentistry, Hasanuddin UniversityBabatundeO. BamgboseDepartment of Oral Diagnostic Sciences, Faculty of Dentistry, Bayero UniversityMagnetic resonance imaging (MRI) is superior to computed tomography (CT) in determining changes in tissue structure, such as those observed following inflammation and infection. However, when metal implants or other metal objects are present, MRI exhibits more distortion and artifacts compared with CT, which hinders the accurate measurement of the implants. A limited number of reports have examined whether the novel MRI sequence, multiacquisition variable-resonance image combination selective (MAVRIC SL), can accurately measure metal implants without distortion. Therefore, the present study aimed to demonstrate whether MAVRIC SL could accurately measure metal implants without distortion and whether the area around the metal implants could be well delineated without artifacts. An agar phantom containing a titanium alloy lumbar implant was used for the present study and was imaged using a 3.0 T MRI machine. A total of three imaging sequences, namely MAVRIC SL, CUBE and magnetic image compilation (MAGiC), were applied and the results were compared. Distortion was evaluated by measuring the screw diameter and distance between the screws multiple times in the phase and frequency directions by two different investigators. The artifact region around the implant was examined using a quantitative method following standardization of the phantom signal values. It was revealed that MAVRIC SL was a superior sequence compared with CUBE and MAGiC, as there was significantly less distortion, a lack of bias between the two different investigators and significantly reduced artifact regions. These results suggested the possibility of utilizing MAVRIC SL for follow-up to observe metal implant insertions.No potential conflict of interest relevant to this article was reported.ElsevierActa Medica Okayama2405-6316252023Patient-specific respiratory motion management using lung tumors vs fiducial markers for real-time tumor-tracking stereotactic body radiotherapy100405ENYoshinoriTanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityMichiruKiritaniFacilty of Health Sciences, Okayama University Medical SchoolTomomiDeguchiFacilty of Health Sciences, Okayama University Medical SchoolNanamiHiraFacilty of Health Sciences, Okayama University Medical SchoolSyoutaTomimotoFacilty of Health Sciences, Okayama University Medical SchoolBackground and purpose: In real-time lung tumor-tracking stereotactic body radiotherapy (SBRT), tracking accuracy is related to radiotherapy efficacy. This study aimed to evaluate the respiratory movement relationship between a lung tumor and a fiducial marker position in each direction using four-dimensional (4D) computed tomography (CT) images.<br>
Materials and methods: A series of 31 patients with a fiducial marker for lung SBRT was retrospectively analyzed using 4DCT. In the upper (UG) and middle and lower lobe groups (MLG), the cross-correlation coefficients of respiratory movement between the lung tumor and fiducial marker position in four directions (anterior–posterior, left–right, superior–inferior [SI], and three-dimensional [3D]) were calculated for each gating window (≤1, ≤2, and ≤ 3 mm). Subsequently, the proportions of phase numbers in unplanned irradiation (with lung tumors outside the gating window and fiducial markers inside the gating window) were calculated for each gating window.<br>
Results: In the SI and 3D directions, the cross-correlation coefficients were significantly different between UG (mean r = 0.59, 0.63, respectively) and MLG (mean r = 0.95, 0.97, respectively). In both the groups, the proportions of phase numbers in unplanned irradiation were 11 %, 28 %, and 63 % for the ≤ 1-, ≤2-, and ≤ 3-mm gating windows, respectively.<br>
Conclusions: Compared with MLG, fiducial markers for UG have low cross-correlation coefficients between the lung tumor and the fiducial marker position. Using 4DCT to assess the risk of unplanned irradiation in a gating window setting and selecting a high cross-correlation coefficient fiducial marker in advance are important for accurate treatment using lung SBRT.No potential conflict of interest relevant to this article was reported.Elsevier B.V.Acta Medica Okayama24056316242022Statistical evaluation of the effectiveness of dual amplitude-gated stereotactic body radiotherapy using fiducial markers and lung volume8287ENYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityHidekazuTanakaDepartment of Radiation Oncology, Yamaguchi University Graduate School of MedicineBackground and purpose: The low tracking accuracy of lung stereotactic body radiotherapy (SBRT) risks reduced treatment efficacy. We used four-dimensional computed tomography (4DCT) images to determine the correlation between changes in fiducial marker positions and lung volume for lung tumors, and we evaluated the effectiveness of the combined use of these images in lung SBRT.<br>
Materials and methods: Data of 30 patients who underwent fiducial marker placement were retrospectively analyzed. We calculated the motion amplitudes of the center of gravity coordinates of the lung tumor and fiducial markers in each phase and the ipsilateral, contralateral, and bilateral lung volumes using 4DCT. Moreover, we calculated the cross-correlation coefficient between the fiducial marker position and the lung volume changes waveform for the motion amplitude waveform of the lung tumor over three gating windows (all phases, ≤2 mm3, and ≤3 mm3).<br>
Results: Compared with the lung volume, approximately 30 % of the fiducial markers demonstrated a low correlation with the lung tumor. In the ≤2 mm3 and ≤3 mm3 gating windows, the cross-correlation coefficients between the lung tumor and the optimal marker (r > 0.9: 83 % and 86 %) were significantly different for all fiducial markers (r > 0.9: 39 %, 53 %) and the ipsilateral (r > 0.9: 35 % and 40 %), contralateral (r > 0.9: 44 % and 41 %), and bilateral (r > 0.9: 39 % and 45 %) lung volumes.<br>
Conclusions: Some of the fiducial markers showed a low correlation with the lung tumor. This study indicated that the combined use of lung volume monitoring can improve tracking accuracy.No potential conflict of interest relevant to this article was reported.Elsevier BVActa Medica Okayama0958-39474742022Statistical analysis of correlation of gamma passing results for two quality assurance phantoms used for patient-specific quality assurance in volumetric modulated arc radiotherapy329333ENYukiKuniiDepartment of Radiology, Tokuyama Central HospitalYoshinoriTanabeFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityAkiraNakamotoDepartment of Radiology, Tokuyama Central HospitalKunioNishiokaDepartment of Radiology, Tokuyama Central HospitalPatient-specific quality assurance (QA) data must be migrated from outdated QA systems to new ones to produce objective results that can be understood by oncologists. We aimed to evaluate a method for obtaining a high correlation of dose distributions according to various gamma passing rates among two types of 2D detectors for the migration of patient-specific QA data of volumetric modulated arc therapy (VMAT). The patient-specific QA of 20 patients undergoing VMAT was measured in two different modes: standard single measurement (SM) mode and multiple merged measurements (MM) techniques using Ar-cCHECK (AC) and OCTAVIUS (OT). The correlation of the measured and calculated dose distributions was evaluated according to varying gamma passing rates (3%/3 mm, 2%/3 mm, 2%/2 mm, and 1%/1 mm). The gamma passing rates were analyzed using the Anderson-Darling normality test. Treatment plan dose dis-tributions were calculated by intentionally shifting the calculation isocenter position (x,y,z +/- 0.5, +/- 1.0, +/- 1.5, and +/- 2.0 mm). The highest correlation between the SM and MM was observed with a gamma passing rate of 1%/1 mm with AC (r = 0.866) and 3%/2 mm with OT (r = 0.916). However, SM and MM did not follow a normal distribution with a rate of 3%/2 mm in OT. The second-highest correlation was obtained with a rate of 2%/2 mm (r = 0.900). Among the two 2D detectors, the highest correlation be-tween the calculated and measured dose distributions was obtained for a gamma passing rate of 1%/1 mm using SM in AC and 2%/2 mm using MM in OT (r = 0.716). Adjusting the gamma passing rate and measurement mode of AC and OT resulted in higher correlations between measured and calculated dose distributions. The high correlation between different 2D detectors objectively indicated a potential mi-gration method. This enabled the sharing of more accurate patient-specific QA data from 2D detectors with different phantoms. A high correlation was observed between the two types of detectors in this study (r = 0.716); therefore, the proposed method should be useful for oncologists to share information regarding patient-specific QA for VMAT.No potential conflict of interest relevant to this article was reported.Elsevier BVActa Medica Okayama0958-39474722022Evaluation of patient-specific motion management for radiotherapy planning computed tomography using a statistical methodE13E18ENYoshinoriTanabeDepartment of Radiological Technology, Graduate School of Health Sciences, Okayama UniversityHidetoshiEtoDepartment of Radiology, Yamaguchi University HospitalWe evaluated the probabilistic randomness of predictions by using individual numerical data based on general data for treatment planning computed tomography (CT) and evaluated the importance of patient-specific management through statistical analysis of our facility's data in lung stereotactic body radiotherapy (SBRT) and prostate volumetric modulated arc therapy (VMAT). The subjects were 30 patients who underwent lung SBRT with fiducial markers and 24 patients who underwent prostate VMAT. The average 3-dimensional (3D) displacement error between the fiducial marker and lung mass in 4DCT of lung SBRT was calculated and then compared with the 3D displacement error between the upper-lobe group (UG) and middle- or lower-lobe group (LG). The duty cycles between the lung tumor and fiducial marker at the <2-mm3 ambush area were compared between the UG and LG. In the prostate VMAT, the Shewhart control chart was analyzed by comparing multiple acquisition planning CT (MPCT) and cone-beam CT (CBCT) during the treatment period. The average 3D displacement errors in 4DCT for the lung tumor and fiducial marker were significantly different between the UG and middle- or lower-lobe group, but there was no correlation with the duty cycle. The Shewhart control chart for 3D displacement errors of the prostate for MPCT and CBCT showed that errors of >8 mm exceeded the control limit. In lung SBRT and prostate VMAT, overall statistical data from planning CT showed probabilistic randomness in predictions during the treatment period, and patient-specific motion management was needed to increase accuracy. A radiotherapy planning CT report showing a statistical analysis graph would be useful to objective share with staff.No potential conflict of interest relevant to this article was reported.