Radiological Physics and Technology最新文献

{"title":"Deep learning-based multi-modality image conversion for evaluating dose calculation and position correction accuracy in image-guided radiation therapy.","authors":"Ryoma Tsuchiya, Keisuke Usui, Hajime Sakamoto, Shinsuke Kyogoku, Hiroyuki Daida","doi":"10.1007/s12194-026-01108-z","DOIUrl":"10.1007/s12194-026-01108-z","url":null,"abstract":"<p><p>Cone-beam CT (CBCT) is widely used in image-guided radiation therapy (IGRT). However, CBCT has limited image quality, which can reduce dose calculation and position correction accuracy. This study aimed to propose a deep learning-based multi-modality image synthesis framework to enhance the feasibility of adaptive radiation therapy (ART) and IGRT. Two conditional generative adversarial network (CGAN) models were developed: a CBCT-to-CT model to generate synthetic CT (sCT) from CBCT, and a CT-to-MRI model to generate synthetic MRI (sMRI) from CT. The models were trained with 80 cases and tested with another 20 cases. Image quality was evaluated using the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR). Moreover, a volumetric modulation arc therapy plan of 48 Gy in four fractions was recalculated using sCT images and compared with the dose distributions of original CT images. Each sMRI and original MRI were registered to the original CT, and displacements between each registered image were quantified based on the CT. The sCT generated using the CBCT-to-CT model improved SSIM from 0.15 to 0.82 and PSNR from 11.3 to 19.9 dB, while the sMRI generated using the CT-to-MRI model improved SSIM from 0.09 to 0.63 and PSNR from 10.3 to 23.9 dB. The dose distribution based on sCT achieved a gamma pass rate over 95%, and positional correction differences of sMRI were within 1 mm. Multi-modality image synthesis using CGAN enables high-fidelity image generation from CBCT, improving both dose calculation and position correction accuracy for ART and IGRT.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1255-1266"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148608553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Educational effectiveness of short-term e-learning intervention on chest radiograph assessment skills among radiological technology students: a pre- and post-comparative study.","authors":"Taku Kuramoto, Nao Ichikawa, Shin Nagamata, Hiroyuki Tsushima","doi":"10.1007/s12194-026-01090-6","DOIUrl":"10.1007/s12194-026-01090-6","url":null,"abstract":"<p><p>Medical imaging interpretation is central to clinical decision-making. However, a significant global radiologist shortage necessitates an expanded role for radiological technologists in providing image interpretation support. Preparing students for this role is challenging because undergraduate radiological technology curricula are notoriously crowded, restricting time for practical chest X-ray (CXR) interpretation training. To address this educational gap, we quantitatively evaluated the impact of a highly feasible, 180-minute e-learning intervention on students' CXR evaluation skills. Sixty-nine third-year radiological technology students completed a self-directed learning session using the diagnostic simulator simu.Doc. Accuracy rates and response times for a 50-case CXR test were measured pre- and post-intervention. To assess the method's versatility, participants were stratified into three proficiency levels based on pre-test scores. The overall mean accuracy rate significantly improved from 40.7 to 60.0% (p < 0.001), while the mean response time significantly decreased from 36.2 to 23.2 min (p < 0.001). Subgroup analysis demonstrated significant improvements across all proficiency levels. Furthermore, ANCOVA revealed no significant differences among the groups in post-test accuracy (p = 0.788) or response time (p = 0.653) when adjusted for pre-test scores. These results indicated that performance converged to a statistically uniform level regardless of baseline knowledge. This study provides quantitative evidence that a short, intensive e-learning program utilizing digital transformation can effectively and sustainably enhance CXR interpretation skills, facilitating the integration of image evaluation training into time-constrained undergraduate curricula.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1119-1128"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148621774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the spatial information loss of Dose-Volume Histograms in Gamma Knife radiosurgery via unsupervised 3D dose geometry embedding.","authors":"Omar Hamzaoui, Yassine Oulhouq, Mohammed Rezzoug, Mustapha Zerfaoui, Dikra Bakkari, Abdeslem Rrhioua","doi":"10.1007/s12194-026-01093-3","DOIUrl":"10.1007/s12194-026-01093-3","url":null,"abstract":"<p><p>Dose-Volume Histograms (DVH) discard spatial information by summarizing 3D distributions into 1D curves. This study quantifies this loss in Gamma Knife radiosurgery and introduces TopoGK, a novel unsupervised deep learning framework capturing full 3D dose geometry. Ninety-six vestibular schwannoma plans were analyzed. Dose grids were tumor-centered, resampled to [Formula: see text] voxels, and normalized to [Formula: see text]. A 3D Convolutional Variational Autoencoder compressed each dose-mask volume into a 64dimensional spatial embedding. Spatial information loss was quantified by comparing pairwise DVH and latent distances both globally and within volume-stratified subgroups. Physical validation employed hotspot center-of-mass displacement, gradient anisotropy, and a novel Spatial Discordance Index (SDI). Five-fold cross-validation ensured generalizability. A linear PCA baseline was included for comparison. The correlation between DVH and spatial similarity was weak ([Formula: see text] within volume-matched pairs). Among DVH-matched pairs, the hotspot exhibited a median physical displacement of 2.81 mm (90th percentile: 4.69 mm), and 61.8-76.5% exceeded heuristic geometric SDI thresholds. Multivariate regression ([Formula: see text]; volume-adjusted [Formula: see text]) confirmed that the learned embedding is driven by spatial metrics-hotspot displacement ([Formula: see text]) and anisotropy ( [Formula: see text]) rather than DVH ([Formula: see text]). Held-out reconstruction SSIM reached [Formula: see text]. TopoGK outperformed PCA in spatial correlation ( [Formula: see text] 0.451 vs. 0.287). DVH similarity does not guarantee spatial dose equivalence. The proposed framework provides a physically validated spatial fingerprint capturing geometric variations invisible to conventional plan evaluation. As a proof-of-concept in single-fraction vestibular schwannoma radiosurgery, these results motivate further investigation toward spatially-aware quality assurance in stereotactic radiosurgery.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1153-1167"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148521173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical usefulness of slab-selective three-dimensional magnetic resonance angiography using radial stack-of-stars acquisition and UTE sampling (STARS UTE-MRA) after treatment of cerebral aneurysms with metallic devices.","authors":"Daichi Murayama, Masami Yoneyama, Tsubasa Okuyama, Takayuki Sakai, Hidehisa Hatakeyama, Shigehiro Ochi","doi":"10.1007/s12194-026-01102-5","DOIUrl":"10.1007/s12194-026-01102-5","url":null,"abstract":"<p><p>Three-dimensional time-of-flight magnetic resonance angiography (3D TOF-MRA) is widely used for follow-up after treatment of cerebral aneurysms, but signal loss around metallic devices often limits evaluation of the parent vessel. We clinically evaluated slab-selective three-dimensional magnetic resonance angiography using radial stack-of-stars acquisition and UTE sampling (STARS UTE-MRA) in 89 patients after coil embolization and surgical clipping. STARS UTE-MRA was compared with conventional 3D TOF-MRA using full width at half-minimum (FWHM) of signal-intensity profiles and visual scores assigned by four readers. STARS UTE-MRA showed significantly smaller FWHM values and higher visual scores than 3D TOF-MRA for coils 10-15 mm in long-axis length and for all clip-length subgroups, whereas no clear advantage was observed in smaller coil cases. STARS UTE-MRA may be a useful supplementary sequence for postoperative follow-up, particularly in aneurysms treated with larger coil or surgical clips.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1444-1449"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148521208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monte Carlo study of air ionization by X-ray photons and backscattering under diagnostic conditions using the developed Irradose code.","authors":"Omar El Basraoui, Oumayma Qassimi, Chaymae Yahyaoui, Lahcen El Amri, Najim Tahiri, Omar El Bounagui","doi":"10.1007/s12194-026-01094-2","DOIUrl":"10.1007/s12194-026-01094-2","url":null,"abstract":"<p><p>Irradiation of air by X-rays, particularly during diagnostic and medical imaging procedures, induces a temporary ionization of its constituents and may lead to the formation of reactive species such as O₂⁺, O₂^- and O₂²⁻. This study analyzes photon transport as well as scattering and backscattering phenomena in air and tissue-equivalent media, in order to evaluate dose, energy, and angular distributions. A Monte Carlo code named Irradose has been developed to simulate these processes in cylindrical geometries containing air, an HCNO phantom representing the patient, and an aqueous medium. The model was validated by comparison with the PHITS and Geant4 codes, showing good agreement with deviations below 5%. The results highlight a progressive attenuation of the beam dose in air between the source and the phantom, estimated at 1.2%. They also show a higher dose deposition in the HCNO phantom. Backscatter from this medium contributes significantly to the secondary photon field in air, with a maximum of 14.62% at 0.15 MeV and a dominant angular distribution around 2.4 rad. The ionic species O₂⁺, O₂^- and O₂^2- are discussed, as well as the limitations of this work and the associated perspectives.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1141-1152"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148430214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated sternocleidomastoid ROI placement on carotid black-blood T1-weighted MRI: toward standardized plaque-to-muscle ratio assessment.","authors":"Masayoshi Mori, Takanori Masuda, Kohei Sugimoto, Toshinori Matsushige, Mikako Takeuchi, Takashi Fujimoto, Jun Araki, Masaki Ishikawa","doi":"10.1007/s12194-026-01113-2","DOIUrl":"10.1007/s12194-026-01113-2","url":null,"abstract":"<p><p>In carotid black-blood T1-weighted imaging (BB T1WI), plaque-to-muscle ratio (PMR) is used for quantitative assessment of plaque hyperintensity. However, sternocleidomastoid muscle (SCM) signal measurement depends on reader region of interest (ROI) placement, which may reduce reproducibility. We aimed to develop and evaluate a segmentation-based automated pipeline for SCM ROI placement and signal measurement to standardize PMR assessment. In this study, 66 patients were used for model development, patient-level 5-fold cross-validation, and final model training, and an independent historical cohort of 60 patients was used for independent ROI testing. BB T1WI was acquired on a 3.0-T scanner. A 2.5D U-Net segmented bilateral SCM on standardized axial reformats. Automated circular ROIs were placed within segmented SCM on three predefined slices centered at the carotid bifurcation. Segmentation performance was assessed using Dice, intersection-over-union, and average surface distance. Agreement between automated and manual SCM measurements was evaluated in patients with complete bilateral automated ROI placement using intraclass correlation coefficients, Bland-Altman analysis, and mean absolute error. In patient-level 5-fold cross-validation, Dice, intersection-over-union, and average surface distance were 0.858 ± 0.029, 0.782 ± 0.028, and 2.563 ± 1.155 pixels, respectively. In the independent cohort, complete bilateral automated ROI placement was achieved in 56 of 60 patients (93.3%). Agreement between automated measurements and the three-reader mean was excellent (intraclass correlation coefficient, 0.991; 95% confidence interval, 0.983-0.995). Automated SCM ROI placement on carotid BB T1WI was feasible and agreed excellently with manual SCM measurements. This method may support standardized SCM-referenced assessment in carotid plaque MRI.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1350-1360"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148608548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cost-effective 3D-printed phantom insert for enhanced small-field patient specific quality assurance for stereotactic radiotherapy plans.","authors":"Syeda Masooma Tayyab, Muhammad Shahban, Asrar Ahmad, Muhammad Ali","doi":"10.1007/s12194-026-01058-6","DOIUrl":"10.1007/s12194-026-01058-6","url":null,"abstract":"<p><p>Stereotactic radiotherapy on CyberKnife demands high precision in dosimetry due to the involvement of small-field treatments. This study addresses the geometric and dosimetric limitations of conventional phantom setups when using small-volume ionization chambers by designing and validating a 3D-printed polylactic acid (PLA) insert for the Sun Nuclear StereoPhan phantom, optimized for the PTW PinPoint 31022 chamber. The insert was designed to eliminate air gaps and misalignments, ensuring accurate and reproducible point-dose measurements. Radiological suitability was confirmed through CT imaging, with the PLA insert showing a mean Hounsfield Unit (HU) of 137 ± 10 compared to 119 ± 5 for PMMA, demonstrating equivalence. Dosimetric validation on Varian TrueBeam and Accuray CyberKnife systems showed clinically acceptable accuracy, with dose deviations ≤ 1.98% for TrueBeam VMAT/IMRT plans and ≤ 3.502 ± 1.23 for CyberKnife cones as small as 5 mm. In contrast, conventional Farmer chamber setup showed deviations as high as 5.08%. In retrospective CyberKnife patient-specific QA, 87.8% of PLA-PinPoint measurements were within ± 5% and 93.9% within ± 10% of TPS-calculated doses across 33 plans, with a mean absolute deviation of 3.55% with a minimum error of 0.4% and a maximum error of -16%, compared to 11.63% for the SNC125c chamber. These findings demonstrate the feasibility of a cost-effective 3D-printed insert as a promising alternative to conventional phantoms, particularly for small-field CyberKnife QA in resource-limited settings.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"926-937"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148176899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-based reconstruction from low-resolution acquisitions for diffusion MRI: evaluation of FOD similarity.","authors":"Akihiro Kasahara, Yuichi Suzuki, Kazuki Endo, Ryosuke Mori, Ryutaro Yano, Hiroshi Kusahara, Toshihiro Hayashi, Osamu Abe","doi":"10.1007/s12194-026-01103-4","DOIUrl":"10.1007/s12194-026-01103-4","url":null,"abstract":"<p><p>MRI provides essential insights into tissue microstructure, and high angular resolution diffusion imaging (HARDI) enables detailed assessment of complex white matter architecture through fiber orientation distribution (FOD) analysis. However, HARDI requires high b-values and multiple diffusion directions, leading to reduced signal-to-noise ratio (SNR) and long scan times. Conventional zero-fill interpolation processing (ZIP) is widely used for super-resolution but is limited by edge blurring and artifacts. This study evaluated an AI-based reconstruction method, Precise IQ Engine (PIQE). Specifically, low-resolution diffusion data were reconstructed to standard resolution and compared with standard-resolution acquisitions. Ten healthy volunteers underwent HARDI at 3T, and FOD were estimated using constrained spherical deconvolution. Quantitative comparisons with reference data demonstrated that PIQE exhibited higher distributional similarity (lower Jensen-Shannon divergence) and directional agreement (higher angular correlation coefficient) compared with ZIP+Advanced Intelligent Clear-IQ Engine (AiCE), with statistically significant similarity observed. These findings indicate potential usefulness in advanced diffusion MRI applications.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1434-1443"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13546164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"^99mTechnetium SPECT-guided functional liver-sparing radiotherapy planning for recurrent hepatocellular carcinoma: a dosimetric comparison.","authors":"Takuya Taniguchi, Kazutaka Miki, Kosei Adachi, Shuto Nakaya, Kaede Kawagchi, Osamu Tanaka, Masayuki Matsuo","doi":"10.1007/s12194-026-01114-1","DOIUrl":"10.1007/s12194-026-01114-1","url":null,"abstract":"<p><p>The aim of this study was to establish an optimal treatment strategy for functional liver-sparing radiotherapy by incorporating technetium-99 m galactosyl human serum albumin (^99mTc-GSA) single-photon emission computed tomography (SPECT) into radiotherapy planning for recurrent hepatocellular carcinoma (rHCC). Three irradiation techniques-volumetric-modulated arc therapy (VMAT), intensity-modulated radiotherapy (IMRT), and three-dimensional conformal radiotherapy (3D-CRT)-were systematically compared. Six patients with rHCC who underwent stereotactic body radiotherapy (SBRT) were included. Eligible patients had previously received SBRT to a different hepatic segment and had undergone ^99mTc-GSA SPECT before the current course of radiotherapy. For treatment planning, planning computed tomography (CT) images were rigidly registered with ^99mTc-GSA SPECT images, and functional liver regions were manually contoured by radiation oncologists. Using identical functional liver contours, three treatment plans-VMAT, IMRT, and 3D-CRT-were independently generated by medical physicists. The prescribed dose was 40 Gy, delivered in four fractions. These treatment plans were retrospectively created for research purposes and were separate from actual clinical treatments. Under identical planning target volume dose-coverage conditions, the dose-volume histogram indices (V2-V40) of the functional liver were compared among the three techniques. VMAT consistently demonstrated the best preservation of functional liver regions, particularly in the low-dose range, followed by IMRT and 3D-CRT. These findings demonstrate the feasibility of ^99mTc-GSA SPECT-guided function-avoidance radiotherapy planning for the re-irradiation of rHCC and suggest that VMAT provides an optimal balance between target coverage and functional liver preservation.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1338-1349"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13546335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of fat-suppression-related sequence operations for stiffness stability in spin-echo echo-planar imaging magnetic resonance elastography: a phantom study.","authors":"Yuuki Yoshimura, Kohei Sugimoto","doi":"10.1007/s12194-026-01078-2","DOIUrl":"10.1007/s12194-026-01078-2","url":null,"abstract":"<p><p>Spin-echo echo-planar imaging (SE-EPI)-based magnetic resonance elastography (MRE) is susceptible to chemical shift artifacts, making sequence-related operations important for stable measurements. This phantom study evaluated the influence of fat-suppression-related sequence operations on stiffness measurement variability in SE-EPI MRE. Imaging was performed at 3-T under six conditions, with five repeated acquisitions and four slices per scan. Mean stiffness, variability, and measurable area were assessed using the average coefficient of variation (aCV), and signal-to-noise ratio (SNR) was quantitatively evaluated. All conditions yielded stiffness values within the expected range. Spectral attenuated inversion recovery with strong showed the lowest aCV (0.7%), whereas water excitation showed the highest aCV (6.0%) and the smallest measurable area. Sequence-related differences were associated with variability, suggesting contributions from SNR and sequence-dependent signal characteristics affecting stiffness stability.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"1373-1379"},"PeriodicalIF":1.6,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148206274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}