Radiological Physics and Technology最新文献

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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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

Evaluation of patient-specific quality assurance for fractionated stereotactic treatment plans with 6 and 10MV photon beams in beam-matched linacs. 评估在光束匹配直列加速器中使用6MV和10MV光子束的分层立体定向治疗计划的患者特定质量保证。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-10-04 DOI: 10.1007/s12194-024-00848-0

Mageshraja Kannan, Sathiyan Saminathan, Varatharaj Chandraraj, B Shwetha, D Gowtham Raj, K M Ganesh

{"title":"Evaluation of patient-specific quality assurance for fractionated stereotactic treatment plans with 6 and 10MV photon beams in beam-matched linacs.","authors":"Mageshraja Kannan, Sathiyan Saminathan, Varatharaj Chandraraj, B Shwetha, D Gowtham Raj, K M Ganesh","doi":"10.1007/s12194-024-00848-0","DOIUrl":"https://doi.org/10.1007/s12194-024-00848-0","url":null,"abstract":"Beam-matched linear accelerators (LA's) require accurate and precise dosimetry for fractionated stereotactic treatment. In this study, the beam data were validated by comparing the three-beam-matched LA's measured data and the vendor reference data. Upon its validation, the accuracy of the volumetric dose delivery for eighty patient-specific fractionated stereotactic treatment plans was evaluated. Measurements of the percentage depth dose (PDD), beam profiles, output factors (OFs), absolute output, and dynamic multi-leaf collimator (MLC) transmission factors for 6 MV and 10 MV flattening filter (FF) and flattening filter-free (FFF) photon beams were obtained from three-beam-matched LA's. The patient-specific quality assurance evaluation for all eighty plans was performed using PTW Octavius 1000 SRS™ array detectors for two-dimensional (2D) fluence measurement. The following 2D gamma passing criteria were used: 1%/1 mm, 2%/1 mm, 1%/2 mm, 2%/2 mm and 3%/2 mm. In all three LA's, gamma analysis for PDD and profile were above 97% with gamma criteria of 1%/1 mm. The differences OFs, absolute output, and dynamic MLC transmission factors were less than ± 1% of base value. For all eighty cases, the median passing rates on the three LA's were above 76%, 88%, 92%, 96%, and 98% for the above-mentioned gamma criteria of the three LA's. The beam-matched LA's showed good agreement between the measured and treatment planning system (TPS) calculated values for fractionated stereotactic VMAT plans with 6 MV and 10 MV (FF and FFF) photon beams. Patients can be shifted and treated on any beam-matched linac without the need of re-planning.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373206","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

The effect on gastrointestinal peristalsis for magnetic resonance cholangiopancreatography during breath-holding methods. 憋气法对磁共振胰胆管造影胃肠道蠕动的影响。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-27 DOI: 10.1007/s12194-024-00846-2

Yuhei Otsuka, Tomoya Nakamura, Nao Kajihara, Takao Tashiro

{"title":"The effect on gastrointestinal peristalsis for magnetic resonance cholangiopancreatography during breath-holding methods.","authors":"Yuhei Otsuka, Tomoya Nakamura, Nao Kajihara, Takao Tashiro","doi":"10.1007/s12194-024-00846-2","DOIUrl":"https://doi.org/10.1007/s12194-024-00846-2","url":null,"abstract":"The breath-hold (BH) 3D magnetic resonance cholangiopancreatography method has been reported to suppress \"respiratory artifacts\"; however, the influence of gastrointestinal peristalsis around the target organs has not been discussed. In contrast, the autonomic nervous system has been reported to affect gastrointestinal peristalsis and BH imaging has been reported to influence venous blood flow signal (BFS) through its involvement with the autonomic nervous system. We examined the impact of BH imaging on gastrointestinal peristalsis. Seven healthy volunteers participated. Three respiratory patterns-free breathing (FB), BH at maximum inspiration (Insp-BH), and BH at maximum expiration (Exp-BH)-were used. Gastrointestinal peristalsis was measured using cine MRI. Cine MRI data were analyzed using the normalized interframe difference method, focusing on the duodenum and gastric body. Hemodynamic changes resulting from BH methods were evaluated using 2D phase contrast, targeting the inferior vena cava (IVC). The BFS was examined for all phases of each respiratory pattern. Peristalsis variation in the duodenum showed no significant differences among FB, Exp-BH, and Insp-BH. In the gastric body, no significant differences were observed between FB and Exp-BH or between Exp-BH and Insp-BH. However, a significant difference emerged between FB and Insp-BH. Regarding BFS, in the IVC, significant differences were observed between Exp-BH and Insp-BH and between FB and Insp-BH (both, p < 0.01), with no significant difference between FB and Exp-BH. Insp-BH reduces venous blood flow and suppresses the influence of peristalsis variation.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142356119","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

LIT-Unet: a lightweight and effective model for medical image segmentation. LIT-Unet：用于医学图像分割的轻量级有效模型。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-20 DOI: 10.1007/s12194-024-00844-4

Ru Wang, Qiqi Kou, Lina Dou

{"title":"LIT-Unet: a lightweight and effective model for medical image segmentation.","authors":"Ru Wang, Qiqi Kou, Lina Dou","doi":"10.1007/s12194-024-00844-4","DOIUrl":"https://doi.org/10.1007/s12194-024-00844-4","url":null,"abstract":"This study aimed to design a simple and efficient automatic segmentation model for medical images, so as to facilitate doctors to make more accurate diagnosis and treatment plan. A hybrid lightweight network LIT-Unet with symmetric encoder-decoder U-shaped architecture is proposed. Synapse multi-organ segmentation dataset and automated cardiac diagnosis challenge (ACDC) dataset were used to test the segmentation performance of the method. Two indexes, Dice similarity coefficient (DSC ↑) and 95% Hausdorff distance (HD95 ↓), were used to evaluate and compare the segmentation ability with the current advanced methods. Ablation experiments were conducted to demonstrate the lightweight nature and effectiveness of our model. For Synapse dataset, our model achieves a higher DSC score (80.40%), an improvement of 3.8% over the typical hybrid model (TransUnet). The 95 HD value is low at 20.67%. For ACDC dataset, LIT-Unet achieves the optimal average DSC (%) of 91.84 compared with other networks listed. Compared to patch expanding, the DSC of our model is intuitively improved by 1.62% with the help of deformable token merging (DTM). These results show that the proposed hierarchical LIT-Unet can achieve significant accuracy and is expected to provide a reliable basis for clinical diagnosis and treatment.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298279","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

Effect of frame rate on image quality in cardiology evaluated using an indirect conversion dynamic flat-panel detector. 使用间接转换动态平板探测器评估帧频对心脏病学图像质量的影响。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-18 DOI: 10.1007/s12194-024-00845-3

Akira Hasegawa, Yohan Kondo

引用次数: 0

An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis. 基于放射组学的人工智能（AI）方法在乳腺癌筛查和诊断中的最新概述。

IF 1.7

Radiological Physics and Technology Pub Date : 2024-09-16 DOI: 10.1007/s12194-024-00842-6

Reza Elahi, Mahdis Nazari

{"title":"An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.","authors":"Reza Elahi, Mahdis Nazari","doi":"10.1007/s12194-024-00842-6","DOIUrl":"https://doi.org/10.1007/s12194-024-00842-6","url":null,"abstract":"Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity and specificity and modest positive predictive power. The recent progress in image analysis using artificial intelligence (AI) has created great promise to improve BC diagnosis and subtype differentiation. In this case, novel quantitative computational methods, such as radiomics, have been developed to enhance the sensitivity and specificity of early BC diagnosis and classification. The potential of radiomics in improving the diagnostic efficacy of imaging studies has been shown in several studies. In this review article, we discuss the radiomics workflow and current handcrafted radiomics methods in the diagnosis and classification of BC based on the most recent studies on different imaging modalities, e.g., MRI, mammography, contrast-enhanced spectral mammography (CESM), ultrasound imaging, and digital breast tumosynthesis (DBT). We also discuss current challenges and potential strategies to improve the specificity and sensitivity of radiomics in breast cancer to help achieve a higher level of BC classification and diagnosis in the clinical setting. The growing field of AI incorporation with imaging information has opened a great opportunity to provide a higher level of care for BC patients.","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142298276","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