Radiological Physics and Technology最新文献

Optimum delineation of skin structure for dose calculation with the linear Boltzmann transport equation algorithm in radiotherapy treatment planning. 在放射治疗规划中使用线性玻尔兹曼传输方程算法计算剂量时的皮肤结构最佳划分。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-09 DOI: 10.1007/s12194-024-00840-8

Keisuke Hamada, Toshioh Fujibuchi, Hiroyuki Arakawa

引用次数: 0

Parameter optimisation for image acquisition and stacking in carbon dioxide digital subtraction angiography. 二氧化碳数字减影血管造影中图像采集和叠加的参数优化。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-09 DOI: 10.1007/s12194-024-00841-7

Kazuya Kakuta, Koichi Chida

{"title":"Parameter optimisation for image acquisition and stacking in carbon dioxide digital subtraction angiography.","authors":"Kazuya Kakuta, Koichi Chida","doi":"10.1007/s12194-024-00841-7","DOIUrl":"https://doi.org/10.1007/s12194-024-00841-7","url":null,"abstract":"The aim of this study was to optimise the vessel angle as well as the stack number from the profiles of carbon dioxide digital subtraction angiography (CO2-DSA) images of a water phantom containing an artificial vessel tilted at different angles which imitate arteries in the body. The artificial vessel was tilted at 0°, 15°, and 30° relative to the horizontal axis with its centre as the pivot point, and CO2-DSA images were acquired at each vessel tilt angle. The maximum opacity method was used to stack up to four images of the next frame one by one. The signal-to-noise ratio (SNR) was determined from the profile curves. The Wilcoxon rank sum test was used to evaluate whether the profile curve and SNR differed depending on the vessel tilt angle or stack number, and a p-value of less than 0.05 was considered statistically significant. Images acquired at 0° had a significantly lower SNR than images acquired at 15° (p = 0.10). When the vessel angle was 30°, the profile curves were significantly improved (p < 0.05) when two or more images were stacked over the original image. Images with a good SNR were acquired at the vessel tilt angle of 15°, and the shape of the profile curve was improved when two or more images were stacked on the original image. This study demonstrates that the quality of images acquired using CO2-DSA can be significantly improved through parameter optimisation for image acquisition and post-processing.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156304","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

Estimation of the lateral variation of photon beam energy spectra using the percentage depth dose reconstruction method. 利用百分比深度剂量重建法估算光子束能量谱的横向变化。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-06 DOI: 10.1007/s12194-024-00835-5

Puspen Chakraborty, Hidetoshi Saitoh, Yuta Miyake, Tenyoh Suzuki, Weishan Chang

{"title":"Estimation of the lateral variation of photon beam energy spectra using the percentage depth dose reconstruction method.","authors":"Puspen Chakraborty, Hidetoshi Saitoh, Yuta Miyake, Tenyoh Suzuki, Weishan Chang","doi":"10.1007/s12194-024-00835-5","DOIUrl":"https://doi.org/10.1007/s12194-024-00835-5","url":null,"abstract":"In photon-collapsed cone convolution (pCCC) algorithm of the Monaco treatment planning system (TPS), the central-axis energy spectrum is assumed constant throughout the entire irradiation area. To consider lateral variations, an off-axis softening factor is applied to attenuation coefficients during the total energy released per unit mass calculation. We evaluated this method through comparison studies of percentage depth doses (PDDs) and off-axis ratios (OARs) calculated by Monaco and measured for a 6 MV photon beam at various off-axis angles and depths. Significant differences were observed, with relative differences exceeding ± 1%. Therefore, this method may not accurately represent lateral variations of energy spectra. We propose directly implementing energy spectra on both central-axis and off-axis to improve dose calculation accuracy for large field. To this end, we introduce reconstruction of PDDs from monoenergetic depth doses (MDDs) along off-axis angles, thereby estimating energy spectra as functions of radial distance. This method derives energy spectra quickly without significantly increasing the beam modeling time. MDDs were computed through Monte Carlo simulations (DOSRZnrc). The variances between reconstructed and measured PDDs were minimized using the generalized-reduced-gradient method to optimize energy spectra. Reconstructed PDDs along off-axis angles of 0°, 1.15°, 2.29°, 3.43°, 4.57°, 5.71°, 6.84°, 7.97°, 9.09°, 10.2° to estimate energy spectra at radial distances of 0-18 cm in 2 cm increments and OARs calculated using estimated energy spectra at 5, 10, and 20 cm depths, well agreed with measurement (relative differences within ± 0.5%). In conclusion, our proposed method accurately estimates lateral energy spectrum variation, thereby improving dose calculation accuracy of pCCC algorithm.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142141310","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

Joint segmentation of sternocleidomastoid and skeletal muscles in computed tomography images using a multiclass learning approach. 利用多类学习方法联合分割计算机断层扫描图像中的胸锁乳突肌和骨骼肌

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-06 DOI: 10.1007/s12194-024-00839-1

Kosuke Ashino, Naoki Kamiya, Xiangrong Zhou, Hiroki Kato, Takeshi Hara, Hiroshi Fujita

{"title":"Joint segmentation of sternocleidomastoid and skeletal muscles in computed tomography images using a multiclass learning approach.","authors":"Kosuke Ashino, Naoki Kamiya, Xiangrong Zhou, Hiroki Kato, Takeshi Hara, Hiroshi Fujita","doi":"10.1007/s12194-024-00839-1","DOIUrl":"https://doi.org/10.1007/s12194-024-00839-1","url":null,"abstract":"Deep-learning-based methods can improve robustness against individual variations in computed tomography (CT) images of the sternocleidomastoid muscle, which is a challenge when using conventional methods based on probabilistic atlases are used for automatic segmentation. Thus, this study proposes a novel multiclass learning approach for the joint segmentation of the sternocleidomastoid and skeletal muscles in CT images, and it employs a two-dimensional U-Net architecture. The proposed method concurrently learns and segmented segments the sternocleidomastoid muscle and the entire skeletal musculature. Consequently, three-dimensional segmentation results are generated for both muscle groups. Experiments conducted on a dataset of 30 body CT images demonstrated segmentation accuracies of 82.94% and 92.73% for the sternocleidomastoid muscle and entire skeletal muscle compartment, respectively. These results outperformed those of conventional methods, such as the single-region learning of a target muscle and multiclass learning of specific muscle pairs. Moreover, the multiclass learning paradigm facilitated a robust segmentation performance regardless of the input image range. This highlights the method's potential for cases that present muscle atrophy or reduced muscle strength. The proposed method exhibits promising capabilities for the high-accuracy joint segmentation of the sternocleidomastoid and skeletal muscles and is effective in recognizing skeletal muscles, thus, it holds promise for integration into computer-aided diagnostic systems for comprehensive musculoskeletal analysis. These findings are expected to enhance medical image analysis techniques and their applications in clinical decision support systems.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146574","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":null,"pages":null},"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":null,"pages":null},"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

Modulation transfer function of digital breast tomosynthesis: a comparison of various edge devices. 数字乳腺断层摄影的调制传递函数：各种边缘设备的比较。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-01 Epub Date: 2024-05-23 DOI: 10.1007/s12194-024-00815-9

Takashi Shirato, Kazuhiko Doryo, Shiori Yamada, Yutaka Ozaki

引用次数: 0

Enhanced radio-photodynamic therapy potential of advanced gold-based nanoclusters for breast cancer treatment. 先进金基纳米团簇在乳腺癌治疗中的放射光动力治疗潜力。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-01 Epub Date: 2024-07-16 DOI: 10.1007/s12194-024-00824-8

Omid Talaee, Reza Faghihi, Banafsheh Rastegari, Sedigheh Sina

{"title":"Enhanced radio-photodynamic therapy potential of advanced gold-based nanoclusters for breast cancer treatment.","authors":"Omid Talaee, Reza Faghihi, Banafsheh Rastegari, Sedigheh Sina","doi":"10.1007/s12194-024-00824-8","DOIUrl":"10.1007/s12194-024-00824-8","url":null,"abstract":"The purpose of current study was to assess the impact of ALA-coated gold nanoclusters (Au NPs) on the combined therapeutic effects of radiotherapy (RT) and photodynamic therapy (PDT) on healthy MCF-10A and MCF-7 breast cancer cells. The Au NPs were covered with ALA using PEG polymer, resulting in the synthesis of Au@ALA NPs. The successful synthesis of the final NPs was confirmed through FTIR, XRD, TEM, and UV-Vis tests. MCF-10A and MCF-7 cell lines were treated with different concentrations of Au@ALA NPs and exposed to irradiation of 2 and 4 Gy (using MV X-ray) and 630 nm laser light irradiation. Cytotoxicity was assessed using a multifaceted approach involving the MTT assay, real-time PCR, and colony forming assay. The findings revealed that the damage inflicted by Au@ALA NPs on cancerous tissue was significantly greater than that on normal tissue. The cytotoxic effects of all experimental groups exhibited a direct correlation with increasing concentrations and radiation doses. The combination of Au@ALA NPs with RT doses of 2 and 4 Gy resulted in a reduction in cell viability by a factor of 1.58 (P = 0.001) and 1.73 (P = 0.004), respectively. Furthermore, the simultaneous intervention of NPs with PDT and RT at doses of 2 and 4 Gy led to a decrease in cell viability by a factor of 2.10 (P = 0.001) and 3.08 (P = 0.001) in turn. Furthermore, the real-time PCR and colonogenic assay results demonstrated that the combined treatment significantly increased phosphorylation of ATM and expression of TP53, indicating an adequate synergistic effect on breast cancer cells. The concurrent application of Au@ALA NPs in RT and PDT successfully enhanced the radiosensitization of breast cancer cells to megavoltage RT and PDT.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141628064","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":null,"pages":null},"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