Yongxian QianBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Ying-Chia LinBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Xingye ChenBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USAVilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA, Tiejun ZhaoSiemens Medical Solutions USA, New York, NY, USA, Karthik LakshmananBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Yulin GeBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Yvonne W. LuiBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USADepartment of Radiology, NYU Langone Health, New York, NY, USA, Fernando E. BoadaBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USANow at Department of Radiology, Stanford University, Stanford, CA, USA
Purpose. It is a long standing pursuit in sodium (23Na) MRI to separate signals between mono and bi exponential T2 decays in the human brain, due to lack of clinically translational solutions under the restriction of intrinsically low signal to noise ratio (SNR). Here we propose a new technique called multi TE single quantum (MSQ) sodium MRI to address the challenge. Methods. We exploit an intrinsic difference in T2 decay between mono and bi exponential sodium signals by acquiring SQ images at multiple TEs and performing voxel based matrix inversions on these SQ images. The MSQ method was then investigated on numerical models, agar phantoms, and human brains for the feasibility on clinical scanners at 3T. Results. The whole brain T2* spectrum of FID signals from the study subjects showed sparse peaks (2 to 4 peaks), suggesting a global set of T2* values (T2*fr, T2*bs, T2*bl) applicable to the separation. The simulations indicated a small impact (3.9 to 5.6 percent) of T2* variation on accuracy of the separation, and the phantom experiments showed a high accuracy of the separation, 95.8 percent for mono T2 sodium and 72.5 to 80.4 percent for biT2 sodium. The human studies demonstrated feasibility of the separation and potentials of highlighting abnormal brain regions in the biT2 sodium images. Conclusion. The MSQ technique has been shown, via the numerical simulations, phantom experiments, and human brain studies, to be able to separate mono and bi T2 sodium signals using a two TE sampling scheme and a global set of T2* values. However, MSQ has limitations and requires cautions in practice. Keywords. sodium MRI, single quantum MRI, triple quantum MRI, neuroimaging, neurodegeneration
{"title":"Separation of Sodium Signals Between Mono- and Bi-Exponential T2 Decays via Multi-TE Single-Quantum Sodium (23Na) MRI","authors":"Yongxian QianBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Ying-Chia LinBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Xingye ChenBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USAVilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA, Tiejun ZhaoSiemens Medical Solutions USA, New York, NY, USA, Karthik LakshmananBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Yulin GeBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA, Yvonne W. LuiBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USADepartment of Radiology, NYU Langone Health, New York, NY, USA, Fernando E. BoadaBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USANow at Department of Radiology, Stanford University, Stanford, CA, USA","doi":"arxiv-2407.09868","DOIUrl":"https://doi.org/arxiv-2407.09868","url":null,"abstract":"Purpose. It is a long standing pursuit in sodium (23Na) MRI to separate\u0000signals between mono and bi exponential T2 decays in the human brain, due to\u0000lack of clinically translational solutions under the restriction of\u0000intrinsically low signal to noise ratio (SNR). Here we propose a new technique\u0000called multi TE single quantum (MSQ) sodium MRI to address the challenge.\u0000Methods. We exploit an intrinsic difference in T2 decay between mono and bi\u0000exponential sodium signals by acquiring SQ images at multiple TEs and\u0000performing voxel based matrix inversions on these SQ images. The MSQ method was\u0000then investigated on numerical models, agar phantoms, and human brains for the\u0000feasibility on clinical scanners at 3T. Results. The whole brain T2* spectrum\u0000of FID signals from the study subjects showed sparse peaks (2 to 4 peaks),\u0000suggesting a global set of T2* values (T2*fr, T2*bs, T2*bl) applicable to the\u0000separation. The simulations indicated a small impact (3.9 to 5.6 percent) of\u0000T2* variation on accuracy of the separation, and the phantom experiments showed\u0000a high accuracy of the separation, 95.8 percent for mono T2 sodium and 72.5 to\u000080.4 percent for biT2 sodium. The human studies demonstrated feasibility of the\u0000separation and potentials of highlighting abnormal brain regions in the biT2\u0000sodium images. Conclusion. The MSQ technique has been shown, via the numerical\u0000simulations, phantom experiments, and human brain studies, to be able to\u0000separate mono and bi T2 sodium signals using a two TE sampling scheme and a\u0000global set of T2* values. However, MSQ has limitations and requires cautions in\u0000practice. Keywords. sodium MRI, single quantum MRI, triple quantum MRI,\u0000neuroimaging, neurodegeneration","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721240","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}
Ricardo Bravo, Ricardo Silva, Eric Barret, John Brunnings, Adianette Segarra
Field-Effect Transistors with graphene channels or GFETs are an interesting alternative for the detection of analytes in biological fluids since the electrical behavior of the channel changes when exposed to a sample (among other detection strategies). In this work a preliminary characterization is made in terms of the resistance of the channel for a commercial device that has GFETs of 1 and 3 channels for cases of dry and wet gate at atmospheric pressure. The channel resistance was obtained by sweeping the drain-source voltage from -1 to +1V and measuring the drain current in a test station developed for this purpose, for gate cases with and without a PBS 0.001X reference solution. The ohmic response of the channel is linear current with respect to voltage, being greater resistance in the case of wet gate. An increase in resistance with respect to voltage was observed that it is important to review. It was possible to make the ohmic characterization of the channel and a series of recommendations are suggested to continue this research.
{"title":"Characterization of a Biosensor Based on Graphene Field Effect Transistors for Body Fluid Analytes: Channel Resistance","authors":"Ricardo Bravo, Ricardo Silva, Eric Barret, John Brunnings, Adianette Segarra","doi":"arxiv-2407.09656","DOIUrl":"https://doi.org/arxiv-2407.09656","url":null,"abstract":"Field-Effect Transistors with graphene channels or GFETs are an interesting\u0000alternative for the detection of analytes in biological fluids since the\u0000electrical behavior of the channel changes when exposed to a sample (among\u0000other detection strategies). In this work a preliminary characterization is\u0000made in terms of the resistance of the channel for a commercial device that has\u0000GFETs of 1 and 3 channels for cases of dry and wet gate at atmospheric\u0000pressure. The channel resistance was obtained by sweeping the drain-source\u0000voltage from -1 to +1V and measuring the drain current in a test station\u0000developed for this purpose, for gate cases with and without a PBS 0.001X\u0000reference solution. The ohmic response of the channel is linear current with\u0000respect to voltage, being greater resistance in the case of wet gate. An\u0000increase in resistance with respect to voltage was observed that it is\u0000important to review. It was possible to make the ohmic characterization of the\u0000channel and a series of recommendations are suggested to continue this\u0000research.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141722459","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}
Devin W. Laurence, Patricia M. Sabin, Analise M. Sulentic, Matthew Daemer, Steve A. Maas, Jeffrey A. Weiss, Matthew A. Jolley
Finite element simulations are an enticing tool to evaluate heart valve function in healthy and diseased patients; however, patient-specific simulations derived from 3D echocardiography are hampered by several technical challenges. In this work, we present an open-source method to enforce matching between finite element simulations and in vivo image-derived heart valve geometry in the absence of patient-specific material properties, leaflet thickness, and chordae tendineae structures. We evaluate FEBio Finite Element Simulations with Shape Enforcement (FINESSE) using three synthetic test cases covering a wide range of model complexity. Our results suggest that FINESSE can be used to not only enforce finite element simulations to match an image-derived surface, but to also estimate the first principal leaflet strains within +/- 0.03 strain. Key FINESSE considerations include: (i) appropriately defining the user-defined penalty, (ii) omitting the leaflet commissures to improve simulation convergence, and (iii) emulating the chordae tendineae behavior via prescribed leaflet free edge motion or a chordae emulating force. We then use FINESSE to estimate the in vivo valve behavior and leaflet strains for three pediatric patients. In all three cases, FINESSE successfully matched the target surface with median errors similar to or less than the smallest voxel dimension. Further analysis revealed valve-specific findings, such as the tricuspid valve leaflet strains of a 2-day old patient with HLHS being larger than those of two 13-year old patients. The development of this open source pipeline will enable future studies to begin linking in vivo leaflet mechanics with patient outcomes
{"title":"FEBio FINESSE: An open-source finite element simulation approach to estimate in vivo heart valve strains using shape enforcement","authors":"Devin W. Laurence, Patricia M. Sabin, Analise M. Sulentic, Matthew Daemer, Steve A. Maas, Jeffrey A. Weiss, Matthew A. Jolley","doi":"arxiv-2407.09629","DOIUrl":"https://doi.org/arxiv-2407.09629","url":null,"abstract":"Finite element simulations are an enticing tool to evaluate heart valve\u0000function in healthy and diseased patients; however, patient-specific\u0000simulations derived from 3D echocardiography are hampered by several technical\u0000challenges. In this work, we present an open-source method to enforce matching\u0000between finite element simulations and in vivo image-derived heart valve\u0000geometry in the absence of patient-specific material properties, leaflet\u0000thickness, and chordae tendineae structures. We evaluate FEBio Finite Element\u0000Simulations with Shape Enforcement (FINESSE) using three synthetic test cases\u0000covering a wide range of model complexity. Our results suggest that FINESSE can\u0000be used to not only enforce finite element simulations to match an\u0000image-derived surface, but to also estimate the first principal leaflet strains\u0000within +/- 0.03 strain. Key FINESSE considerations include: (i) appropriately\u0000defining the user-defined penalty, (ii) omitting the leaflet commissures to\u0000improve simulation convergence, and (iii) emulating the chordae tendineae\u0000behavior via prescribed leaflet free edge motion or a chordae emulating force.\u0000We then use FINESSE to estimate the in vivo valve behavior and leaflet strains\u0000for three pediatric patients. In all three cases, FINESSE successfully matched\u0000the target surface with median errors similar to or less than the smallest\u0000voxel dimension. Further analysis revealed valve-specific findings, such as the\u0000tricuspid valve leaflet strains of a 2-day old patient with HLHS being larger\u0000than those of two 13-year old patients. The development of this open source\u0000pipeline will enable future studies to begin linking in vivo leaflet mechanics\u0000with patient outcomes","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721241","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}
Edward Wang, Ryan Au, Pencilla Lang, Sarah A. Mattonen
Evidence is accumulating in favour of using stereotactic ablative body radiotherapy (SABR) to treat multiple cancer lesions in the lung. Multi-lesion lung SABR plans are complex and require significant resources to create. In this work, we propose a novel two-stage latent transformer framework (LDFormer) for dose prediction of lung SABR plans with varying numbers of lesions. In the first stage, patient anatomical information and the dose distribution are encoded into a latent space. In the second stage, a transformer learns to predict the dose latent from the anatomical latents. Causal attention is modified to adapt to different numbers of lesions. LDFormer outperforms a state-of-the-art generative adversarial network on dose conformality in and around lesions, and the performance gap widens when considering overlapping lesions. LDFormer generates predictions of 3-D dose distributions in under 30s on consumer hardware, and has the potential to assist physicians with clinical decision making, reduce resource costs, and accelerate treatment planning.
{"title":"Latent Spaces Enable Transformer-Based Dose Prediction in Complex Radiotherapy Plans","authors":"Edward Wang, Ryan Au, Pencilla Lang, Sarah A. Mattonen","doi":"arxiv-2407.08650","DOIUrl":"https://doi.org/arxiv-2407.08650","url":null,"abstract":"Evidence is accumulating in favour of using stereotactic ablative body\u0000radiotherapy (SABR) to treat multiple cancer lesions in the lung. Multi-lesion\u0000lung SABR plans are complex and require significant resources to create. In\u0000this work, we propose a novel two-stage latent transformer framework (LDFormer)\u0000for dose prediction of lung SABR plans with varying numbers of lesions. In the\u0000first stage, patient anatomical information and the dose distribution are\u0000encoded into a latent space. In the second stage, a transformer learns to\u0000predict the dose latent from the anatomical latents. Causal attention is\u0000modified to adapt to different numbers of lesions. LDFormer outperforms a\u0000state-of-the-art generative adversarial network on dose conformality in and\u0000around lesions, and the performance gap widens when considering overlapping\u0000lesions. LDFormer generates predictions of 3-D dose distributions in under 30s\u0000on consumer hardware, and has the potential to assist physicians with clinical\u0000decision making, reduce resource costs, and accelerate treatment planning.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613007","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}
Praveenbalaji Rajendran, Yong Yang, Thomas R. Niedermayr, Michael Gensheimer, Beth Beadle, Quynh-Thu Le, Lei Xing, Xianjin Dai
Radiation therapy (RT) is one of the most effective treatments for cancer, and its success relies on the accurate delineation of targets. However, target delineation is a comprehensive medical decision that currently relies purely on manual processes by human experts. Manual delineation is time-consuming, laborious, and subject to interobserver variations. Although the advancements in artificial intelligence (AI) techniques have significantly enhanced the auto-contouring of normal tissues, accurate delineation of RT target volumes remains a challenge. In this study, we propose a visual language model-based RT target volume auto-delineation network termed Radformer. The Radformer utilizes a hierarichal vision transformer as the backbone and incorporates large language models to extract text-rich features from clinical data. We introduce a visual language attention module (VLAM) for integrating visual and linguistic features for language-aware visual encoding (LAVE). The Radformer has been evaluated on a dataset comprising 2985 patients with head-and-neck cancer who underwent RT. Metrics, including the Dice similarity coefficient (DSC), intersection over union (IOU), and 95th percentile Hausdorff distance (HD95), were used to evaluate the performance of the model quantitatively. Our results demonstrate that the Radformer has superior segmentation performance compared to other state-of-the-art models, validating its potential for adoption in RT practice.
{"title":"Large Language Model-Augmented Auto-Delineation of Treatment Target Volume in Radiation Therapy","authors":"Praveenbalaji Rajendran, Yong Yang, Thomas R. Niedermayr, Michael Gensheimer, Beth Beadle, Quynh-Thu Le, Lei Xing, Xianjin Dai","doi":"arxiv-2407.07296","DOIUrl":"https://doi.org/arxiv-2407.07296","url":null,"abstract":"Radiation therapy (RT) is one of the most effective treatments for cancer,\u0000and its success relies on the accurate delineation of targets. However, target\u0000delineation is a comprehensive medical decision that currently relies purely on\u0000manual processes by human experts. Manual delineation is time-consuming,\u0000laborious, and subject to interobserver variations. Although the advancements\u0000in artificial intelligence (AI) techniques have significantly enhanced the\u0000auto-contouring of normal tissues, accurate delineation of RT target volumes\u0000remains a challenge. In this study, we propose a visual language model-based RT\u0000target volume auto-delineation network termed Radformer. The Radformer utilizes\u0000a hierarichal vision transformer as the backbone and incorporates large\u0000language models to extract text-rich features from clinical data. We introduce\u0000a visual language attention module (VLAM) for integrating visual and linguistic\u0000features for language-aware visual encoding (LAVE). The Radformer has been\u0000evaluated on a dataset comprising 2985 patients with head-and-neck cancer who\u0000underwent RT. Metrics, including the Dice similarity coefficient (DSC),\u0000intersection over union (IOU), and 95th percentile Hausdorff distance (HD95),\u0000were used to evaluate the performance of the model quantitatively. Our results\u0000demonstrate that the Radformer has superior segmentation performance compared\u0000to other state-of-the-art models, validating its potential for adoption in RT\u0000practice.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588470","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}
Junyi Zhao, Chansoo Kim, Weilun Li, Zichao Wen, Zhili Xiao, Yong Wang, Shantanu Chakrabartty, Chuan Wang
Electronic textiles (E-textiles) offer great wearing comfort and unobtrusiveness, thus holding potential for next-generation health monitoring wearables. However, the practical implementation is hampered by challenges associated with poor signal quality, substantial motion artifacts, durability for long-term usage, and non-ideal user experience. Here, we report a cost-effective E-textile system that features 3D microfiber-based electrodes for greatly increasing the surface area. The soft and fluffy conductive microfibers disperse freely and securely adhere to the skin, achieving a low impedance at the electrode-skin interface even in the absence of gel. A superhydrophobic fluorinated self-assembled monolayer was deposited on the E-textile surface to render it waterproof while retaining the electrical conductivity. Equipped with a custom-designed motion-artifact canceling wireless data recording circuit, the E-textile system could be integrated into a variety of smart garments for exercise physiology and health monitoring applications. Real-time multimodal electrophysiological signal monitoring, including electrocardiogram (ECG) and electromyography (EMG), was successfully carried out during strenuous cycling and even underwater swimming activities. Furthermore, a multi-channel E-textile was developed and implemented in clinical patient studies for simultaneous real-time monitoring of maternal ECG and uterine EMG signals, incorporating spatial-temporal potential mapping capabilities.
{"title":"3D E-textile for Exercise Physiology and Clinical Maternal Health Monitoring","authors":"Junyi Zhao, Chansoo Kim, Weilun Li, Zichao Wen, Zhili Xiao, Yong Wang, Shantanu Chakrabartty, Chuan Wang","doi":"arxiv-2407.07954","DOIUrl":"https://doi.org/arxiv-2407.07954","url":null,"abstract":"Electronic textiles (E-textiles) offer great wearing comfort and\u0000unobtrusiveness, thus holding potential for next-generation health monitoring\u0000wearables. However, the practical implementation is hampered by challenges\u0000associated with poor signal quality, substantial motion artifacts, durability\u0000for long-term usage, and non-ideal user experience. Here, we report a\u0000cost-effective E-textile system that features 3D microfiber-based electrodes\u0000for greatly increasing the surface area. The soft and fluffy conductive\u0000microfibers disperse freely and securely adhere to the skin, achieving a low\u0000impedance at the electrode-skin interface even in the absence of gel. A\u0000superhydrophobic fluorinated self-assembled monolayer was deposited on the\u0000E-textile surface to render it waterproof while retaining the electrical\u0000conductivity. Equipped with a custom-designed motion-artifact canceling\u0000wireless data recording circuit, the E-textile system could be integrated into\u0000a variety of smart garments for exercise physiology and health monitoring\u0000applications. Real-time multimodal electrophysiological signal monitoring,\u0000including electrocardiogram (ECG) and electromyography (EMG), was successfully\u0000carried out during strenuous cycling and even underwater swimming activities.\u0000Furthermore, a multi-channel E-textile was developed and implemented in\u0000clinical patient studies for simultaneous real-time monitoring of maternal ECG\u0000and uterine EMG signals, incorporating spatial-temporal potential mapping\u0000capabilities.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613008","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}
Keith R Murphy, Tulika Nandi, Benjamin Kop, Takahiro Osada, W Apoutou N'Djin, Maximilian Lueckel, Kevin A Caulfield, Anton Fomenko, Hartwig R Siebner, Yoshikazu Ugawa, Lennart Verhagen, Sven Bestmann, Eleanor Martin, Kim Butts Pauly, Elsa Fouragnan, Til Ole Bergmann
Low-intensity Transcranial Ultrasonic Stimulation (TUS) is a non-invasive brain stimulation technique enabling cortical and deep brain targeting with unprecedented spatial accuracy. Given the high rate of adoption by new users with varying levels of expertise and interdisciplinary backgrounds, practical guidelines are needed to ensure state-of-the-art TUS application and reproducible outcomes. Therefore, the International Transcranial Ultrasonic Stimulation Safety and Standards (ITRUSST) consortium has formed a subcommittee, endorsed by the International Federation of Clinical Neurophysiology (IFCN), to develop recommendations for best practice in TUS applications in humans. The practical guide presented here provides a brief introduction into ultrasound physics and sonication parameters. It explains the requirements of TUS lab equipment and transducer selection and discusses experimental design and procedures alongside potential confounds and control conditions. Finally, the guide elaborates on essential steps of application planning for stimulation safety and efficacy, as well as considerations when combining TUS with neuroimaging, electrophysiology, or other brain stimulation techniques. We hope that this practical guide to TUS will assist both novice and experienced users in planning and conducting high-quality studies and provide a solid foundation for further advancements in this promising field.
低强度经颅超声波刺激（TUS）是一种非侵入性脑刺激技术，能以前所未有的空间精确度瞄准大脑皮层和大脑深部。鉴于具有不同专业水平和跨学科背景的新用户的采用率很高，因此需要制定实用指南，以确保 TUS 的应用达到最先进的水平，并取得可重复的结果。因此，国际经颅超声刺激安全与标准（ITRUSST）联盟成立了一个由国际临床神经生理学联合会（IFCN）认可的小组委员会，以制定人体 TUS 应用的最佳实践建议。本实用指南简要介绍了超声物理学和超声参数。它解释了 TUS 实验室设备和换能器选择的要求，并讨论了实验设计和程序以及潜在的混杂因素和控制条件。最后，指南详细阐述了刺激安全性和有效性应用规划的基本步骤，以及将 TUS 与神经影像学、电生理学或其他脑刺激技术相结合时的注意事项。我们希望这本实用的 TUS 指南能帮助新手和有经验的用户规划和开展高质量的研究，并为这一前景广阔的领域的进一步发展奠定坚实的基础。
{"title":"A Practical Guide to Transcranial Ultrasonic Stimulation from the IFCN-endorsed ITRUSST Consortium","authors":"Keith R Murphy, Tulika Nandi, Benjamin Kop, Takahiro Osada, W Apoutou N'Djin, Maximilian Lueckel, Kevin A Caulfield, Anton Fomenko, Hartwig R Siebner, Yoshikazu Ugawa, Lennart Verhagen, Sven Bestmann, Eleanor Martin, Kim Butts Pauly, Elsa Fouragnan, Til Ole Bergmann","doi":"arxiv-2407.07646","DOIUrl":"https://doi.org/arxiv-2407.07646","url":null,"abstract":"Low-intensity Transcranial Ultrasonic Stimulation (TUS) is a non-invasive\u0000brain stimulation technique enabling cortical and deep brain targeting with\u0000unprecedented spatial accuracy. Given the high rate of adoption by new users\u0000with varying levels of expertise and interdisciplinary backgrounds, practical\u0000guidelines are needed to ensure state-of-the-art TUS application and\u0000reproducible outcomes. Therefore, the International Transcranial Ultrasonic\u0000Stimulation Safety and Standards (ITRUSST) consortium has formed a\u0000subcommittee, endorsed by the International Federation of Clinical\u0000Neurophysiology (IFCN), to develop recommendations for best practice in TUS\u0000applications in humans. The practical guide presented here provides a brief\u0000introduction into ultrasound physics and sonication parameters. It explains the\u0000requirements of TUS lab equipment and transducer selection and discusses\u0000experimental design and procedures alongside potential confounds and control\u0000conditions. Finally, the guide elaborates on essential steps of application\u0000planning for stimulation safety and efficacy, as well as considerations when\u0000combining TUS with neuroimaging, electrophysiology, or other brain stimulation\u0000techniques. We hope that this practical guide to TUS will assist both novice\u0000and experienced users in planning and conducting high-quality studies and\u0000provide a solid foundation for further advancements in this promising field.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584616","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}
Nils Marquardt, Tobias Hengsbach, Marco Mauritz, Benedikt Wirth, Klaus Schäfers
Cell tracking is a subject of active research gathering great interest in medicine and biology. Positron emission tomography (PET) is well suited for tracking radio-labeled cells in vivo due to its exceptional sensitivity and whole-body capability. For validation, ground-truth data is desirable that realistically mimics the flow of cells in a clinical situation. This study develops a workflow (CeFloPS) for simulating moving radio-labeled cells in a human phantom. From the XCAT phantom, the blood vessels are reduced to nodal networks along which cells can move and distribute to organs and tissues. The movement is directed by the blood flow which is calculated in each node using the Hagen-Poiseuille equation and Kirchhoffs laws assuming laminar flow. Organs are voxelized and movement of cells from artery entry to vein exit is generated via a biased 3D random walk. The probabilities of whether cells move or stay in tissues are derived from rate constants of physiologically based compartment modeling. PET listmode data is generated using the Monte-Carlo simulation framework GATE based on the definition of a large-body PET scanner with cell paths as moving radioactive sources and the XCAT phantom providing attenuation data. From the flow simulation of 10000 cells, 100 sample cells were further processed by GATE and listmode data was reconstructed into images for comparison. As demonstrated by comparisons of simulated and reconstructed cell distributions, CeFloPS can realistically simulate the cell behavior of whole-body PET providing valuable data for development and validation of cell tracking algorithms.
细胞追踪是医学和生物学领域的一个热门研究课题。正电子发射断层扫描（PET）具有极高的灵敏度和全身追踪能力，非常适合在体内追踪放射性标记的细胞。为了进行验证，我们需要能真实模拟临床情况下细胞流动的地面实况数据。本研究开发了一种工作流程（CeFloPS），用于模拟人体模型中移动的放射性标记细胞。在 XCAT 模型中，血管被简化为节点网络，细胞可以沿着节点网络移动并分布到器官和组织中。移动由血流引导，每个节点的血流都是通过哈根-普瓦耶方程和假设层流的基尔霍夫定律计算得出的。器官是体素化的，细胞从动脉入口到静脉出口的运动是通过有偏差的三维随机行走产生的。细胞在组织内移动或停留的概率来自基于生理学的隔室模型的速率常数。PET 列表模式数据使用蒙特卡罗模拟框架 GATE 生成，该框架基于大体 PET 扫描仪的定义，细胞路径是移动放射源，XCAT 模型提供衰减数据。从 10000 个细胞的流动模拟中，GATE 进一步处理了 100 个样本细胞，并将列表模式数据重建为图像以供比较。通过比较模拟和重建的细胞分布，CeFloPS 可以真实地模拟全身 PET 的细胞行为，为开发和验证细胞追踪算法提供了宝贵的数据。
{"title":"Motion simulation of radio-labeled cells in whole-body positron emission tomography","authors":"Nils Marquardt, Tobias Hengsbach, Marco Mauritz, Benedikt Wirth, Klaus Schäfers","doi":"arxiv-2407.07709","DOIUrl":"https://doi.org/arxiv-2407.07709","url":null,"abstract":"Cell tracking is a subject of active research gathering great interest in\u0000medicine and biology. Positron emission tomography (PET) is well suited for\u0000tracking radio-labeled cells in vivo due to its exceptional sensitivity and\u0000whole-body capability. For validation, ground-truth data is desirable that\u0000realistically mimics the flow of cells in a clinical situation. This study\u0000develops a workflow (CeFloPS) for simulating moving radio-labeled cells in a\u0000human phantom. From the XCAT phantom, the blood vessels are reduced to nodal\u0000networks along which cells can move and distribute to organs and tissues. The\u0000movement is directed by the blood flow which is calculated in each node using\u0000the Hagen-Poiseuille equation and Kirchhoffs laws assuming laminar flow. Organs\u0000are voxelized and movement of cells from artery entry to vein exit is generated\u0000via a biased 3D random walk. The probabilities of whether cells move or stay in\u0000tissues are derived from rate constants of physiologically based compartment\u0000modeling. PET listmode data is generated using the Monte-Carlo simulation\u0000framework GATE based on the definition of a large-body PET scanner with cell\u0000paths as moving radioactive sources and the XCAT phantom providing attenuation\u0000data. From the flow simulation of 10000 cells, 100 sample cells were further\u0000processed by GATE and listmode data was reconstructed into images for\u0000comparison. As demonstrated by comparisons of simulated and reconstructed cell\u0000distributions, CeFloPS can realistically simulate the cell behavior of\u0000whole-body PET providing valuable data for development and validation of cell\u0000tracking algorithms.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584614","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}
James A. Pollock, Kaye Morgan, Linda C. P. Croton, Emily J. Pryor, Kelly J. Crossley, Christopher J. Hall, Daniel Hausermann, Anton Maksimenko, Stuart B. Hooper, Marcus J. Kitchen
Many lung diseases and abnormalities require detailed visualisation of the lungs for accurate diagnosis and treatment. High-resolution computed tomography (CT) is the gold-standard technique for non-invasive lung disease detection, but it presents a risk to the patient through the relatively high ionising radiation dose required. Utilising the X-ray phase information may allow improvements in image resolution at equal or lower radiation levels than current clinical imaging. Propagation-based phase-contrast imaging requires minimal adaption of existing medical systems, and is well suited to lung imaging due to the strong phase gradients introduced by the lung-air material interface. Herein, propagation-based phase contrast CT is demonstrated for large animals, namely lambs, as a model for paediatric patients, using monochromatic radiation and a photon-counting detector at the Imaging and Medical Beamline of the Australian Synchrotron. Image quality, normalised against radiation dose, was optimised as a function of the beam energy and propagation distance, with the optimal conditions used to test the available image quality at very low radiation dose. Noise-limited spatial resolution was measured using Fourier ring correlation, and dosimetry was performed through Monte Carlo simulation calibrated against air kerma. The resulting CT images demonstrate superior resolution to existing high-resolution CT systems, pushing dose to the quantum limit to comply with current Australian guidelines for infant chest CT exposure (<2.5 mSv effective dose). Constituent raw projections are shown to have significant proportions of pixels with zero photon counts that would create severe information loss in conventional CT, which was prevented through phase retrieval.
许多肺部疾病和异常情况都需要对肺部进行详细观察，以便准确诊断和治疗。高分辨率计算机断层扫描（CT）是无创肺部疾病检测的黄金标准技术，但它所需的离子辐射剂量相对较高，对病人有一定风险。利用 X 射线相位信息可以在与目前临床成像相同或更低的辐射水平下提高图像分辨率。基于传播的相位对比成像只需对现有医疗系统进行最小限度的调整，并且由于肺-空气材料界面引入的强相位梯度，非常适合肺部成像。澳大利亚同步加速器成像和医疗光束线使用单色辐射和光子计数探测器，为大型动物（即羔羊）演示了基于传播的相衬 CT，并将其作为儿科患者的模型。作为光束能量和传播距离的函数，对图像质量（归一化为辐射剂量）进行了优化，最佳条件用于测试极低辐射剂量下的可用图像质量。使用傅立叶环相关测量了噪声限制的空间分辨率，并通过蒙特卡洛模拟（Monte Carlo simulation）进行了剂量测定，该模拟根据空气辐照度（air kerma）进行校准。结果显示，CT 图像的分辨率优于现有的高分辨率 CT 系统，剂量达到量子极限，符合澳大利亚现行的婴儿胸部 CT 暴露指南（有效剂量小于 2.5 mSv）。其原始投影图像中有很大一部分像素的光子计数为零，这在传统 CT 中会造成严重的信息丢失，而通过相位检索则可避免这种情况。
{"title":"Low-dose, high-resolution CT of infant-sized lungs via propagation-based phase contrast","authors":"James A. Pollock, Kaye Morgan, Linda C. P. Croton, Emily J. Pryor, Kelly J. Crossley, Christopher J. Hall, Daniel Hausermann, Anton Maksimenko, Stuart B. Hooper, Marcus J. Kitchen","doi":"arxiv-2407.06527","DOIUrl":"https://doi.org/arxiv-2407.06527","url":null,"abstract":"Many lung diseases and abnormalities require detailed visualisation of the\u0000lungs for accurate diagnosis and treatment. High-resolution computed tomography\u0000(CT) is the gold-standard technique for non-invasive lung disease detection,\u0000but it presents a risk to the patient through the relatively high ionising\u0000radiation dose required. Utilising the X-ray phase information may allow\u0000improvements in image resolution at equal or lower radiation levels than\u0000current clinical imaging. Propagation-based phase-contrast imaging requires\u0000minimal adaption of existing medical systems, and is well suited to lung\u0000imaging due to the strong phase gradients introduced by the lung-air material\u0000interface. Herein, propagation-based phase contrast CT is demonstrated for\u0000large animals, namely lambs, as a model for paediatric patients, using\u0000monochromatic radiation and a photon-counting detector at the Imaging and\u0000Medical Beamline of the Australian Synchrotron. Image quality, normalised\u0000against radiation dose, was optimised as a function of the beam energy and\u0000propagation distance, with the optimal conditions used to test the available\u0000image quality at very low radiation dose. Noise-limited spatial resolution was\u0000measured using Fourier ring correlation, and dosimetry was performed through\u0000Monte Carlo simulation calibrated against air kerma. The resulting CT images\u0000demonstrate superior resolution to existing high-resolution CT systems, pushing\u0000dose to the quantum limit to comply with current Australian guidelines for\u0000infant chest CT exposure (<2.5 mSv effective dose). Constituent raw projections\u0000are shown to have significant proportions of pixels with zero photon counts\u0000that would create severe information loss in conventional CT, which was\u0000prevented through phase retrieval.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141575154","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}
This study aims to validate if MRI can measure anisotropic mesoscopic Larmor frequency shifts from white matter axonal microstructure relative to the B0 direction and if dMRI can estimate this anisotropy. Recent models describe how mesoscopic Larmor frequency shifts depend on induced magnetic fields by axons, described by an orientation distribution function. Using Monte-Carlo simulations of MRI signals in mesoscopic white matter axon substrates, we show MRI can estimate this mesoscopic frequency shift and dMRI can estimate its orientation dependence.
{"title":"Predicting Mesoscopic Larmor Frequency Shifts in White Matter with Diffusion MRI -- An In-Silico Monte-Carlo Study","authors":"Anders Dyhr Sandgaard, Sune Nørhøj Jespersen","doi":"arxiv-2407.06694","DOIUrl":"https://doi.org/arxiv-2407.06694","url":null,"abstract":"This study aims to validate if MRI can measure anisotropic mesoscopic Larmor\u0000frequency shifts from white matter axonal microstructure relative to the B0\u0000direction and if dMRI can estimate this anisotropy. Recent models describe how\u0000mesoscopic Larmor frequency shifts depend on induced magnetic fields by axons,\u0000described by an orientation distribution function. Using Monte-Carlo\u0000simulations of MRI signals in mesoscopic white matter axon substrates, we show\u0000MRI can estimate this mesoscopic frequency shift and dMRI can estimate its\u0000orientation dependence.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141575155","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}
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