Radiological Physics and Technology最新文献_第6页

Effectiveness of the air-gap method for reducing radiation dose in neonate CT examinations. 气隙法降低新生儿 CT 检查辐射剂量的有效性。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-11-05 DOI: 10.1007/s12194-024-00855-1

Takanori Masuda, Yoshinori Funama, Takeshi Nakaura, Tomoyasu Sato, Takayuki Oku, Atsushi Ono, Kazuo Awai

{"title":"Effectiveness of the air-gap method for reducing radiation dose in neonate CT examinations.","authors":"Takanori Masuda, Yoshinori Funama, Takeshi Nakaura, Tomoyasu Sato, Takayuki Oku, Atsushi Ono, Kazuo Awai","doi":"10.1007/s12194-024-00855-1","DOIUrl":"https://doi.org/10.1007/s12194-024-00855-1","url":null,"abstract":"The air-gap method is a technique employed to control dose distribution and radiation scattering in medical imaging. By introducing a layer of air between the radiation source and the object, this method effectively reduces the impact of scattered radiation. The purpose of this study was to investigate the suitability of the air-gap method for radiation dose reduction in pediatric patients during computed tomography (CT) examinations. Only one type of neonate phantom is used with 64 detector-row CT scanner while helical scanning the chest. The distance between the CT table and the subject was 0 mm at the conventional method and 150 mm at the air-gap method. The values of the real-time skin dosimeter on the dorsal surface of the body, and on the left and right mammary glands and image noise are measured and compared for each method. Compared with the conventional method, it was possible to reduce the exposure dose and image noise by approximately 10% and 15%, respectively, using the air-gap method (p < 0.05). The air-gap method was useful for reducing the radiation dose during pediatric CT examinations compared with the conventional method.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584691","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}

引用次数: 0

Optimization of image shoot timing for cerebral veins 3D-digital subtraction angiography by interventional angiography systems. 通过介入血管造影系统优化脑静脉三维数字减影血管造影的图像拍摄时机。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-10-29 DOI: 10.1007/s12194-024-00852-4

Kazuya Saeki, Takayuki Tamura, Shingo Kouno, Eiji Nishimaru, Masao Kiguchi, Takafumi Mitsuhara, Kazuo Awai

{"title":"Optimization of image shoot timing for cerebral veins 3D-digital subtraction angiography by interventional angiography systems.","authors":"Kazuya Saeki, Takayuki Tamura, Shingo Kouno, Eiji Nishimaru, Masao Kiguchi, Takafumi Mitsuhara, Kazuo Awai","doi":"10.1007/s12194-024-00852-4","DOIUrl":"https://doi.org/10.1007/s12194-024-00852-4","url":null,"abstract":"3D-digital subtraction angiography (3D-DSA) is essential for understanding the anatomical structure of cerebral veins, crucial in brain tumor surgery. 3D-DSA produces three-dimensional images of veins by adjusting the X-ray delay time after contrast agent injection, but the delineation of veins varies with the delay in X-ray timing. Our study aimed to refine the delay time using time-enhancement curve (TEC) analysis from 2D-DSA conducted before 3D-DSA imaging. We retrospectively reviewed 26 meningioma patients who underwent cerebral angiography from March 2020 to August 2021. Using 2D-DSA, we analyzed arterial and venous TECs to determine the contrast agent's peak time and estimated the optimal imaging timing. Cases performed near this optimal time were in Group A, and others in Group B, with cerebral venous pixel values compared between them. TEC analysis identified peak times: internal carotid artery: 2.8 ± 0.7 s, middle cerebral artery (M4): 4.1 ± 0.9 s, superior sagittal sinus: 8.3 ± 1.1 s, sigmoid sinus: 9.5 ± 1.3 s, and venous structures near tumors: 7.3 ± 1.0 s. We observed several veins peaking immediately after arterial contrast passage, suggesting the optimal X-ray delay should incorporate the arterial contrast agent's transit time. Statistical analysis revealed that Group A, with imaging timed to reflect the contrast agent transit time, demonstrated significantly better contrast effects than Group B. The X-ray delay time for 3D-DSA imaging of cerebral veins can be optimized in angiography systems by incorporating the contrast agent transit time, calculated from TEC analysis of cerebral 2D-DSA images.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548213","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}

引用次数: 0

Anomaly detection scheme for lung CT images using vector quantized variational auto-encoder with support vector data description. 使用支持向量数据描述的向量量化变异自动编码器的肺部 CT 图像异常检测方案。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-10-26 DOI: 10.1007/s12194-024-00851-5

Zhihui Gao, Ryohei Nakayama, Akiyoshi Hizukuri, Shoji Kido

{"title":"Anomaly detection scheme for lung CT images using vector quantized variational auto-encoder with support vector data description.","authors":"Zhihui Gao, Ryohei Nakayama, Akiyoshi Hizukuri, Shoji Kido","doi":"10.1007/s12194-024-00851-5","DOIUrl":"https://doi.org/10.1007/s12194-024-00851-5","url":null,"abstract":"This study aims to develop an anomaly-detection scheme for lesions in CT images. Our database consists of lung CT images obtained from 1500 examinees. It includes 1200 normal and 300 abnormal cases. In this study, SVDD (Support Vector Data Description) mapping the normal latent variables into a hypersphere as small as possible on the latent space is introduced to VQ-VAE (Vector Quantized-Variational Auto-Encoder). VQ-VAE with SVDD is constructed from two encoders, two decoders, and an embedding space. The first encoder compresses the input image into the latent-variable map, whereas the second encoder maps the normal latent variables into a hypersphere as small as possible. The first decoder then up-samples the mapped latent variables into a latent-variable map with the original size. The second decoder finally reconstructs the input image from the latent-variable map replaced by the embedding representations. The data of each examinee is classified as abnormal or normal based on the anomaly score defined as the combination of the difference between the input image and the reconstructed image and the distance between the latent variables and the center of the hypersphere. The area under the ROC curve for VQ-VAE with SVDD was 0.76, showing an improvement when compared with the conventional VAE (0.63, p < .001). VQ-VAE with SVDD developed in this study can yield higher anomaly-detection accuracy than the conventional VAE. The proposed method is expected to be useful for identifying examinees with lesions and reducing interpretation time in CT screening.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510159","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}

引用次数: 0

Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation. 基于深度学习的方法缩短肺移植术后患者通气 SPECT 的采集时间

IF 1.7

Radiological Physics and Technology Pub Date : 2024-10-23 DOI: 10.1007/s12194-024-00853-3

Masahiro Nakashima, Ryohei Fukui, Seiichiro Sugimoto, Toshihiro Iguchi

{"title":"Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation.","authors":"Masahiro Nakashima, Ryohei Fukui, Seiichiro Sugimoto, Toshihiro Iguchi","doi":"10.1007/s12194-024-00853-3","DOIUrl":"https://doi.org/10.1007/s12194-024-00853-3","url":null,"abstract":"We aimed to evaluate the image quality and diagnostic performance of chronic lung allograft dysfunction (CLAD) with lung ventilation single-photon emission computed tomography (SPECT) images acquired briefly using a convolutional neural network (CNN) in patients after lung transplantation and to explore the feasibility of short acquisition times. We retrospectively identified 93 consecutive lung-transplant recipients who underwent ventilation SPECT/computed tomography (CT). We employed a CNN to distinguish the images acquired in full time from those acquired in a short time. The image quality was evaluated using the structural similarity index (SSIM) loss and normalized mean square error (NMSE). The correlation between functional volume/morphological volume (F/M) ratios of full-time SPECT images and predicted SPECT images was evaluated. Differences in the F/M ratio were evaluated using Bland-Altman plots, and the diagnostic performance was compared using the area under the curve (AUC). The learning curve, obtained using MSE, converged within 100 epochs. The NMSE was significantly lower (P < 0.001) and the SSIM was significantly higher (P < 0.001) for the CNN-predicted SPECT images compared to the short-time SPECT images. The F/M ratio of full-time SPECT images and predicted SPECT images showed a significant correlation (r = 0.955, P < 0.0001). The Bland-Altman plot revealed a bias of -7.90% in the F/M ratio. The AUC values were 0.942 for full-time SPECT images, 0.934 for predicted SPECT images and 0.872 for short-time SPECT images. Our findings suggest that a deep-learning-based approach can significantly curtail the acquisition time of ventilation SPECT, while preserving the image quality and diagnostic accuracy for CLAD.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510160","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}

引用次数: 0

Visualization of X-ray fields, overlaps, and over-beaming on surface of the head in spiral computed tomography using computer-aided design-based X-ray beam modeling. 利用基于计算机辅助设计的 X 射线束建模，对螺旋计算机断层扫描中头部表面的 X 射线场、重叠和过束进行可视化。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-10-17 DOI: 10.1007/s12194-024-00849-z

Atsushi Fukuda, Nao Ichikawa, Takuma Hayashi, Ayaka Hirosawa, Kosuke Matsubara

引用次数: 0

Optimization of image reconstruction technique for respiratory-gated lung stereotactic body radiotherapy treatment planning using four-dimensional CT: a phantom study. 利用四维 CT 优化呼吸门控肺立体定向体放射治疗规划的图像重建技术：一项模型研究。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-10-16 DOI: 10.1007/s12194-024-00850-6

Kenji Yasue, Hiraku Fuse, Minori Takaoka, Shin Miyakawa, Norikazu Koori, Masato Takahashi, Kazuya Shinoda, Hideaki Ikoma, Tatsuya Fujisaki, Shinji Abe

{"title":"Optimization of image reconstruction technique for respiratory-gated lung stereotactic body radiotherapy treatment planning using four-dimensional CT: a phantom study.","authors":"Kenji Yasue, Hiraku Fuse, Minori Takaoka, Shin Miyakawa, Norikazu Koori, Masato Takahashi, Kazuya Shinoda, Hideaki Ikoma, Tatsuya Fujisaki, Shinji Abe","doi":"10.1007/s12194-024-00850-6","DOIUrl":"https://doi.org/10.1007/s12194-024-00850-6","url":null,"abstract":"Patient respiration is characterized by respiratory parameters, such as cycle, amplitude, and baseline drift. In treatment planning using four-dimensional computed tomography (4DCT) images, the target dose may be affected by variations in image reconstruction techniques and respiratory parameters. This study aimed to optimize 4DCT image reconstruction techniques for the treatment planning of lung stereotactic body radiotherapy (SBRT) based on respiratory parameters using respiratory motion phantom. We quantified respiratory parameters using 30 respiratory motion datasets. The 4DCT images were acquired, and the phase- and amplitude-based reconstruction images (RI) were created. The target dose was calculated based on these reconstructed images. Statistical analysis was performed using Pearson's correlation coefficient (r) to determine the relationship between respiratory parameters and target dose in each reconstructed technique and respiratory region. In the inhalation region of phase-based RI, r of the target dose and baseline drift was -0.52. In particular, the target dose was significantly reduced for respiratory parameters with a baseline drift of 0.8 mm/s and above. No other respiratory parameters or respiratory regions were significantly correlated with target dose in phase-based RI. In amplitude-based RI, there were no significant differences in the correlation between all respiratory parameters and target dose in the exhalation or inhalation regions. These results showed that the target dose of the amplitude-based RI did not depend on changes in respiratory parameters or respiratory regions, compared to the phase-based RI. However, it is possible to guarantee the target dose by considering respiratory parameters during the inhalation region of the phase-based RI.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477342","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}

引用次数: 0

Analytical parameterization of Bragg curves for proton beams in muscle, bone, and polymethylmethacrylate. 质子束在肌肉、骨骼和聚甲基丙烯酸甲酯中的布拉格曲线分析参数化。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-01 Epub Date: 2024-06-01 DOI: 10.1007/s12194-024-00816-8

Behzad Aminafshar, Hamid Reza Baghani, Ali Asghar Mowlavi

引用次数: 0

Dosimetric effects of small field size, dose grid size, and variable split-arc methods on gamma pass rates in radiation therapy. 小场尺寸、剂量网格尺寸和可变分弧法对放射治疗中伽马通过率的剂量学影响。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-01 Epub Date: 2024-05-20 DOI: 10.1007/s12194-024-00809-7

Tsunekazu Kuwae, Takuro Ariga, Takeaki Kusada, Akihiro Nishie

{"title":"Dosimetric effects of small field size, dose grid size, and variable split-arc methods on gamma pass rates in radiation therapy.","authors":"Tsunekazu Kuwae, Takuro Ariga, Takeaki Kusada, Akihiro Nishie","doi":"10.1007/s12194-024-00809-7","DOIUrl":"10.1007/s12194-024-00809-7","url":null,"abstract":"This study investigates the influence of calculation accuracy in peripheral low-dose regions on the gamma pass rate (GPR), utilizing the Acuros XB (AXB) algorithm and ArcCHECK™ measurement. The effects of varying small field sizes, dose grid sizes, and split-arc techniques on GPR were analyzed. Various small field sizes were employed. Thirty-two single-arc plans with dose grid sizes of 2 mm and 1 mm and prescribed doses of 2, 5, 10, and 20 Gy were calculated using the AXB algorithm. In total, 128 GPR plans were examined. These plans were categorized into three sub-fields (3SF), four sub-fields (4SF), and six sub-fields (6SF). The GPR results deteriorated with smaller target sizes and a 2 mm dose grid size in a single arc. A similar degradation in GPR was observed with smaller target sizes and a 1 mm dose grid size. However, the 1 mm dose grid size generally resulted in better GPR compared with the 2 mm dose grid size for the same target sizes. The GPR improved with finer split angles and a 2 mm dose grid size in the split-arc method. However, no statistically significant improvement was observed with finer split angles and a 1 mm dose grid size. This study demonstrates that coarser dose grid sizes result in lower GPRs in peripheral low-dose regions as calculated by AXB with ArcCHECK™ measurement. To enhance GPR, employing split-arc methods and finer dose grid sizes could be beneficial.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"620-628"},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141065569","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}

引用次数: 0

Deep learning-based correction for time truncation in cerebral computed tomography perfusion. 基于深度学习的脑计算机断层扫描灌注时间截断校正。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-01 Epub Date: 2024-06-11 DOI: 10.1007/s12194-024-00818-6

Shota Ichikawa, Makoto Ozaki, Hideki Itadani, Hiroyuki Sugimori, Yohan Kondo

{"title":"Deep learning-based correction for time truncation in cerebral computed tomography perfusion.","authors":"Shota Ichikawa, Makoto Ozaki, Hideki Itadani, Hiroyuki Sugimori, Yohan Kondo","doi":"10.1007/s12194-024-00818-6","DOIUrl":"10.1007/s12194-024-00818-6","url":null,"abstract":"Cerebral computed tomography perfusion (CTP) imaging requires complete acquisition of contrast bolus inflow and washout in the brain parenchyma; however, time truncation undoubtedly occurs in clinical practice. To overcome this issue, we proposed a three-dimensional (two-dimensional + time) convolutional neural network (CNN)-based approach to predict missing CTP image frames at the end of the series from earlier acquired image frames. Moreover, we evaluated three strategies for predicting multiple time points. Seventy-two CTP scans with 89 frames and eight slices from a publicly available dataset were used to train and test the CNN models capable of predicting the last 10 image frames. The prediction strategies were single-shot prediction, recursive multi-step prediction, and direct-recursive hybrid prediction.Single-shot prediction predicted all frames simultaneously, while recursive multi-step prediction used prior predictions as input for subsequent steps, and direct-recursive hybrid prediction employed separate models for each step with prior predictions as input for the next step. The accuracies of the predicted image frames were evaluated in terms of image quality, bolus shape, and clinical perfusion parameters. We found that the image quality metrics were superior when multiple CTP images were predicted simultaneously rather than recursively. The bolus shape also showed the highest correlation (r = 0.990, p < 0.001) and the lowest variance (95% confidence interval, -453.26-445.53) in the single-shot prediction. For all perfusion parameters, the single-shot prediction had the smallest absolute differences from ground truth. Our proposed approach can potentially minimize time truncation errors and support the accurate quantification of ischemic stroke.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"666-678"},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141301853","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}

引用次数: 0

New liver window width in detecting hepatocellular carcinoma on dynamic contrast-enhanced computed tomography with deep learning reconstruction. 利用深度学习重建技术在动态对比增强计算机断层扫描中检测肝细胞癌的新肝窗宽度

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-01 Epub Date: 2024-06-05 DOI: 10.1007/s12194-024-00817-7

Naomasa Okimoto, Koichiro Yasaka, Shinichi Cho, Saori Koshino, Jun Kanzawa, Yusuke Asari, Nana Fujita, Takatoshi Kubo, Yuichi Suzuki, Osamu Abe

{"title":"New liver window width in detecting hepatocellular carcinoma on dynamic contrast-enhanced computed tomography with deep learning reconstruction.","authors":"Naomasa Okimoto, Koichiro Yasaka, Shinichi Cho, Saori Koshino, Jun Kanzawa, Yusuke Asari, Nana Fujita, Takatoshi Kubo, Yuichi Suzuki, Osamu Abe","doi":"10.1007/s12194-024-00817-7","DOIUrl":"10.1007/s12194-024-00817-7","url":null,"abstract":"Changing a window width (WW) alters appearance of noise and contrast of CT images. The aim of this study was to investigate the impact of adjusted WW for deep learning reconstruction (DLR) in detecting hepatocellular carcinomas (HCCs) on CT with DLR. This retrospective study included thirty-five patients who underwent abdominal dynamic contrast-enhanced CT. DLR was used to reconstruct arterial, portal, and delayed phase images. The investigation of the optimal WW involved two blinded readers. Then, five other blinded readers independently read the image sets for detection of HCCs and evaluation of image quality with optimal or conventional liver WW. The optimal WW for detection of HCC was 119 (rounded to 120 in the subsequent analyses) Hounsfield unit (HU), which was the average of adjusted WW in the arterial, portal, and delayed phases. The average figures of merit for the readers for the jackknife alternative free-response receiver operating characteristic analysis to detect HCC were 0.809 (reader 1/2/3/4/5, 0.765/0.798/0.892/0.764/0.827) in the optimal WW (120 HU) and 0.765 (reader 1/2/3/4/5, 0.707/0.769/0.838/0.720/0.791) in the conventional WW (150 HU), and statistically significant difference was observed between them (p < 0.001). Image quality in the optimal WW was superior to those in the conventional WW, and significant difference was seen for some readers (p < 0.041). The optimal WW for detection of HCC was narrower than conventional WW on dynamic contrast-enhanced CT with DLR. Compared with the conventional liver WW, optimal liver WW significantly improved detection performance of HCC.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":"658-665"},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11341740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248828","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}

引用次数: 0