In magnetic resonance imaging (MRI), the spectrometer is a fundamental component of MRI systems, responsible for the transmission of radiofrequency (RF) pulses that excite hydrogen nuclei and the subsequent acquisition of MR signals for processing. However, detailed knowledge about this component remains largely inaccessible due to the proprietary nature of commercial systems. To address this gap, we present an FPGA-based platform specifically designed for MRI signal transmission and reception in low-field MRI applications. Additionally, with appropriate chip replacements, this platform can be adapted for use in mid- and high-field MRI systems. This platform leverages Direct Digital Synthesis (DDS) technology to generate RF pulses, offering the flexibility to quickly and precisely adjust soft pulse parameters to meet the specific requirements of the MRI system. Additionally, the platform processes MRI signals through digital downconversion techniques and utilizes CIC and FIR filters to obtain baseband signals. Experimental testing of this platform has yielded promising results. We hope that this work will inspire further research and development in the field of MRI spectrometer design. Furthermore, it is worth noting that with the replacement of relevant chips, this system can also be adapted for use in mid- and high-field MRI systems.
{"title":"A Low-Field Magnetic Resonance Signal Transmission and Reception Processing Platform","authors":"Zesong Jiang, Muhang Zhang, Qing Zhang, Yuchong Xie","doi":"arxiv-2409.08671","DOIUrl":"https://doi.org/arxiv-2409.08671","url":null,"abstract":"In magnetic resonance imaging (MRI), the spectrometer is a fundamental\u0000component of MRI systems, responsible for the transmission of radiofrequency\u0000(RF) pulses that excite hydrogen nuclei and the subsequent acquisition of MR\u0000signals for processing. However, detailed knowledge about this component\u0000remains largely inaccessible due to the proprietary nature of commercial\u0000systems. To address this gap, we present an FPGA-based platform specifically\u0000designed for MRI signal transmission and reception in low-field MRI\u0000applications. Additionally, with appropriate chip replacements, this platform\u0000can be adapted for use in mid- and high-field MRI systems. This platform\u0000leverages Direct Digital Synthesis (DDS) technology to generate RF pulses,\u0000offering the flexibility to quickly and precisely adjust soft pulse parameters\u0000to meet the specific requirements of the MRI system. Additionally, the platform\u0000processes MRI signals through digital downconversion techniques and utilizes\u0000CIC and FIR filters to obtain baseband signals. Experimental testing of this\u0000platform has yielded promising results. We hope that this work will inspire\u0000further research and development in the field of MRI spectrometer design.\u0000Furthermore, it is worth noting that with the replacement of relevant chips,\u0000this system can also be adapted for use in mid- and high-field MRI systems.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259867","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}
Domagoj Bošnjak, Gian Marco Melito, Katrin Ellermann, Thomas-Peter Fries
The effects of the aortic geometry on its mechanics and blood flow, and subsequently on aortic pathologies, remain largely unexplored. The main obstacle lies in obtaining patient-specific aorta models, an extremely difficult procedure in terms of ethics and availability, segmentation, mesh generation, and all of the accompanying processes. Contrastingly, idealized models are easy to build but do not faithfully represent patient-specific variability. Additionally, a unified aortic parametrization in clinic and engineering has not yet been achieved. To bridge this gap, we introduce a new set of statistical parameters to generate synthetic models of the aorta. The parameters possess geometric significance and fall within physiological ranges, effectively bridging the disciplines of clinical medicine and engineering. Smoothly blended realistic representations are recovered with convolution surfaces. These enable high-quality visualization and biological appearance, whereas the structured mesh generation paves the way for numerical simulations. The only requirement of the approach is one patient-specific aorta model and the statistical data for parameter values obtained from the literature. The output of this work is SynthAorta, a dataset of ready-to-use synthetic, physiological aorta models, each containing a centerline, surface representation, and a structured hexahedral finite element mesh. The meshes are structured and fully consistent between different cases, making them imminently suitable for reduced order modeling and machine learning approaches.
{"title":"SynthAorta: A 3D Mesh Dataset of Parametrized Physiological Healthy Aortas","authors":"Domagoj Bošnjak, Gian Marco Melito, Katrin Ellermann, Thomas-Peter Fries","doi":"arxiv-2409.08635","DOIUrl":"https://doi.org/arxiv-2409.08635","url":null,"abstract":"The effects of the aortic geometry on its mechanics and blood flow, and\u0000subsequently on aortic pathologies, remain largely unexplored. The main\u0000obstacle lies in obtaining patient-specific aorta models, an extremely\u0000difficult procedure in terms of ethics and availability, segmentation, mesh\u0000generation, and all of the accompanying processes. Contrastingly, idealized\u0000models are easy to build but do not faithfully represent patient-specific\u0000variability. Additionally, a unified aortic parametrization in clinic and\u0000engineering has not yet been achieved. To bridge this gap, we introduce a new\u0000set of statistical parameters to generate synthetic models of the aorta. The\u0000parameters possess geometric significance and fall within physiological ranges,\u0000effectively bridging the disciplines of clinical medicine and engineering.\u0000Smoothly blended realistic representations are recovered with convolution\u0000surfaces. These enable high-quality visualization and biological appearance,\u0000whereas the structured mesh generation paves the way for numerical simulations.\u0000The only requirement of the approach is one patient-specific aorta model and\u0000the statistical data for parameter values obtained from the literature. The\u0000output of this work is SynthAorta, a dataset of ready-to-use synthetic,\u0000physiological aorta models, each containing a centerline, surface\u0000representation, and a structured hexahedral finite element mesh. The meshes are\u0000structured and fully consistent between different cases, making them imminently\u0000suitable for reduced order modeling and machine learning approaches.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259839","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}
Zitong Yu, Md Ashequr Rahman, Craig K. Abbey, Richard Laforest, Nancy A. Obuchowski, Barry A. Siegel, Abhinav K. Jha
Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by SPECT, typically requires the availability of a separate X-ray CT component, leading to additional radiation dose, higher costs, and potentially inaccurate diagnosis due to SPECT/CT misalignment. To address these issues, we developed a method for cardiac SPECT AC using deep learning and emission scatter-window photons without a separate transmission scan (CTLESS). In this method, an estimated attenuation map reconstructed from scatter-energy window projections is segmented into different regions using a multi-channel input multi-decoder network trained on CT scans. Pre-defined attenuation coefficients are assigned to these regions, yielding the attenuation map used for AC. We objectively evaluated this method in a retrospective study with anonymized clinical SPECT/CT stress MPI images on the clinical task of detecting defects with an anthropomorphic model observer. CTLESS yielded statistically non-inferior performance compared to a CT-based AC (CTAC) method and significantly outperformed a non-AC (NAC) method on this clinical task. Similar results were observed in stratified analyses with different sexes, defect extents and severities. The method was observed to generalize across two SPECT scanners, each with a different camera. In addition, CTLESS yielded similar performance as CTAC and outperformed NAC method on the metrics of root mean squared error and structural similarity index measure. Moreover, as we reduced the training dataset size, CTLESS yielded relatively stable AUC values and generally outperformed another DL-based AC method that directly estimated the attenuation coefficient within each voxel. These results demonstrate the capability of the CTLESS method for transmission-less AC in SPECT and motivate further clinical evaluation.
衰减补偿（AC）虽然有利于通过 SPECT 进行心肌灌注成像（MPI）的视觉解读任务，但通常需要使用单独的 X 射线 CT 组件，从而导致额外的辐射剂量、更高的成本，并可能因 SPECT/CT 错位而造成诊断不准确。为了解决这些问题，我们开发了一种使用深度学习和发射散射窗光子的心脏 SPECT AC 方法，无需单独的透射扫描（CTLESS）。在这种方法中，利用在 CT 扫描上训练的多通道输入多解码网络，将从散射能量窗投影重建的估计衰减图分割成不同的区域。将预先确定的衰减系数分配给这些区域，从而得到用于 AC 的衰减图。在一项回顾性研究中，我们使用匿名的临床SPECT/CT应力MPI图像，对该方法进行了客观评估，该方法的临床任务是检测具有厌形模型观察者的缺陷。与基于 CT 的 AC（CTAC）方法相比，CTLESS 在该临床任务中的表现在统计学上并不逊色，而且明显优于非 AC（NAC）方法。在对不同性别、缺陷范围和严重程度进行分层分析时，也观察到了类似的结果。据观察，该方法适用于两台 SPECT 扫描仪，每台扫描仪都配有不同的摄像头。此外，CTLESS 的性能与 CTAC 相似，在均方根误差和结构相似性指数测量指标上优于 NAC 方法。此外，随着训练数据集规模的缩小，CTLESS 的 AUC 值相对稳定，总体上优于另一种直接估计每个体素内衰减系数的基于 DL 的 AC 方法。这些结果证明了CTLESS方法在SPECT中进行无透射交流的能力，并促使我们进行进一步的临床评估。
{"title":"CTLESS: A scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT","authors":"Zitong Yu, Md Ashequr Rahman, Craig K. Abbey, Richard Laforest, Nancy A. Obuchowski, Barry A. Siegel, Abhinav K. Jha","doi":"arxiv-2409.07761","DOIUrl":"https://doi.org/arxiv-2409.07761","url":null,"abstract":"Attenuation compensation (AC), while being beneficial for\u0000visual-interpretation tasks in myocardial perfusion imaging (MPI) by SPECT,\u0000typically requires the availability of a separate X-ray CT component, leading\u0000to additional radiation dose, higher costs, and potentially inaccurate\u0000diagnosis due to SPECT/CT misalignment. To address these issues, we developed a\u0000method for cardiac SPECT AC using deep learning and emission scatter-window\u0000photons without a separate transmission scan (CTLESS). In this method, an\u0000estimated attenuation map reconstructed from scatter-energy window projections\u0000is segmented into different regions using a multi-channel input multi-decoder\u0000network trained on CT scans. Pre-defined attenuation coefficients are assigned\u0000to these regions, yielding the attenuation map used for AC. We objectively\u0000evaluated this method in a retrospective study with anonymized clinical\u0000SPECT/CT stress MPI images on the clinical task of detecting defects with an\u0000anthropomorphic model observer. CTLESS yielded statistically non-inferior\u0000performance compared to a CT-based AC (CTAC) method and significantly\u0000outperformed a non-AC (NAC) method on this clinical task. Similar results were\u0000observed in stratified analyses with different sexes, defect extents and\u0000severities. The method was observed to generalize across two SPECT scanners,\u0000each with a different camera. In addition, CTLESS yielded similar performance\u0000as CTAC and outperformed NAC method on the metrics of root mean squared error\u0000and structural similarity index measure. Moreover, as we reduced the training\u0000dataset size, CTLESS yielded relatively stable AUC values and generally\u0000outperformed another DL-based AC method that directly estimated the attenuation\u0000coefficient within each voxel. These results demonstrate the capability of the\u0000CTLESS method for transmission-less AC in SPECT and motivate further clinical\u0000evaluation.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176593","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}
Hannah Scholten, Tobias Wech, Istvan Homolya, Herbert Köstler
Purpose: Introducing "compensated variable-prephasing" (CVP), a phantom-based method for gradient waveform measurements. The technique is based on the "variable-prephasing" (VP) method, but takes into account the effects of all gradients involved in the measurement. Methods: We conducted measurements of a trapezoidal test gradient, and of an EPI readout gradient train with three approaches: VP, CVP, and "fully compensated variable-prephasing" (FCVP). We compared them to one another and to predictions based on the gradient system transfer function. Furthermore, we used the measured and predicted EPI gradients for trajectory corrections in phantom images on a 7T scanner. Results: The VP gradient measurements are confounded by lingering oscillations of the prephasing gradients, which are compensated in the CVP and FCVP measurements. FCVP is vulnerable to a sign asymmetry in the gradient chain. However, the trajectories determined by all three methods resulted in comparably high EPI image quality. Conclusion: We present a new approach allowing for phantom-based gradient waveform measurements with high precision, which can be useful for trajectory corrections in non-Cartesian or single-shot imaging techniques. In our experimental setup, the proposed "compensated variable-prephasing" method provided the most reliable gradient measurements of the different techniques we compared.
{"title":"Phantom-based gradient waveform measurements with compensated variable-prephasing: Description and application to EPI at 7T","authors":"Hannah Scholten, Tobias Wech, Istvan Homolya, Herbert Köstler","doi":"arxiv-2409.07203","DOIUrl":"https://doi.org/arxiv-2409.07203","url":null,"abstract":"Purpose: Introducing \"compensated variable-prephasing\" (CVP), a phantom-based\u0000method for gradient waveform measurements. The technique is based on the\u0000\"variable-prephasing\" (VP) method, but takes into account the effects of all\u0000gradients involved in the measurement. Methods: We conducted measurements of a trapezoidal test gradient, and of an\u0000EPI readout gradient train with three approaches: VP, CVP, and \"fully\u0000compensated variable-prephasing\" (FCVP). We compared them to one another and to\u0000predictions based on the gradient system transfer function. Furthermore, we\u0000used the measured and predicted EPI gradients for trajectory corrections in\u0000phantom images on a 7T scanner. Results: The VP gradient measurements are confounded by lingering\u0000oscillations of the prephasing gradients, which are compensated in the CVP and\u0000FCVP measurements. FCVP is vulnerable to a sign asymmetry in the gradient\u0000chain. However, the trajectories determined by all three methods resulted in\u0000comparably high EPI image quality. Conclusion: We present a new approach allowing for phantom-based gradient\u0000waveform measurements with high precision, which can be useful for trajectory\u0000corrections in non-Cartesian or single-shot imaging techniques. In our\u0000experimental setup, the proposed \"compensated variable-prephasing\" method\u0000provided the most reliable gradient measurements of the different techniques we\u0000compared.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176562","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}
Purpose: To develop and compare normal tissue complication probability (NTCP) models for recurrent brain metastases (BMs) treated with repeat single-fraction stereotactic radiosurgery (SRS), considering time-dependent discounted prior dose. Methods: We developed three NTCP models of BMs treated with GammaKnife-based SRS. The maximum dose to 0.2cc (D0.2cc) of each lesion-specific brain and one-year radionecrosis was fitted using a logistic model with equivalent-dose conversions in 2 Gy (EQD2). The M0 and M1-retreat modeled radionecrosis risk following SRS to 1029 non-recurrent lesions (patients=262) and 2nd SRS to 149 recurrent lesions (patients=87). The M1-combo model accounted for 2nd SRS and time-dependent discounted 1st SRS dose for recurrent lesions estimated by a modified Gompertzian function. Results: All three models fitted the data well (Chi-2 = 0.039-0.089 and p = 0.999-1.000). The fitted EQD250 was ~103 Gy for M0, ~88 Gy for M1-retreat, and ~165 Gy for M1-combo. The fitted EQD2_50 exhibited a progressively flatter dose-response curve across the three models, with values of 1.2 Gy for M0, 0.6 Gy for M1-retreat, and 0.4 Gy for M1-combo. For the brain D0.2cc of 29Gy and 19Gy, the steepest to shallowest dose-response or largest change in NTCP, i.e., NTCP29Gy - NTCP19Gy was observed in M1-retreat (0.16), M0 (0.14) and M1-combo (0.06). Conclusions: The model-fitted parameters predict that recurrent BMs have a lower threshold dose tolerance and a more gradual dose response for the 2nd SRS than non-recurrent BMs. This gradual dose-response becomes even more apparent when considering the time-dependent discounted 1st SRS as a cumulative 2nd SRS. Tailoring SRS retreatment protocols based on NTCP modeling can potentially enhance therapeutic efficacy.
{"title":"Does time to retreatment matter? An NTCP model to predict radionecrosis after repeat SRS for recurrent brain metastases incorporating time-dependent discounted dose","authors":"Manju Sharma, Issam El Naqa, Penny K Sneed","doi":"arxiv-2409.07647","DOIUrl":"https://doi.org/arxiv-2409.07647","url":null,"abstract":"Purpose: To develop and compare normal tissue complication probability (NTCP)\u0000models for recurrent brain metastases (BMs) treated with repeat single-fraction\u0000stereotactic radiosurgery (SRS), considering time-dependent discounted prior\u0000dose. Methods: We developed three NTCP models of BMs treated with\u0000GammaKnife-based SRS. The maximum dose to 0.2cc (D0.2cc) of each\u0000lesion-specific brain and one-year radionecrosis was fitted using a logistic\u0000model with equivalent-dose conversions in 2 Gy (EQD2). The M0 and M1-retreat\u0000modeled radionecrosis risk following SRS to 1029 non-recurrent lesions\u0000(patients=262) and 2nd SRS to 149 recurrent lesions (patients=87). The M1-combo\u0000model accounted for 2nd SRS and time-dependent discounted 1st SRS dose for\u0000recurrent lesions estimated by a modified Gompertzian function. Results: All\u0000three models fitted the data well (Chi-2 = 0.039-0.089 and p = 0.999-1.000).\u0000The fitted EQD250 was ~103 Gy for M0, ~88 Gy for M1-retreat, and ~165 Gy for\u0000M1-combo. The fitted EQD2_50 exhibited a progressively flatter dose-response\u0000curve across the three models, with values of 1.2 Gy for M0, 0.6 Gy for\u0000M1-retreat, and 0.4 Gy for M1-combo. For the brain D0.2cc of 29Gy and 19Gy, the\u0000steepest to shallowest dose-response or largest change in NTCP, i.e., NTCP29Gy\u0000- NTCP19Gy was observed in M1-retreat (0.16), M0 (0.14) and M1-combo (0.06).\u0000Conclusions: The model-fitted parameters predict that recurrent BMs have a\u0000lower threshold dose tolerance and a more gradual dose response for the 2nd SRS\u0000than non-recurrent BMs. This gradual dose-response becomes even more apparent\u0000when considering the time-dependent discounted 1st SRS as a cumulative 2nd SRS.\u0000Tailoring SRS retreatment protocols based on NTCP modeling can potentially\u0000enhance therapeutic efficacy.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227573","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}
Arunima Dev T V, Anagha P. K, Midhun C. V, M. M Musthafa, Vafiya Thaslim T. T, Shaima Akbar, Swapna B, Nicemon Thomas, Antony Joseph, S. Ganesan
The capability of standard Geant4 PhysicsLists to address the fragmentation of $^{12}$C$-^{12}$C was assessed through a comparative analysis with experimental cross sections reported by Divay et al. and Dudouet et al. The standard PhysicsLists were found to be inadequate in explaining the fragmentation systematics. To address this limitation, the breakup component of fragmentation was systematically integrated into the standard PhysicsList, which successfully replicated the differential and double differential cross sections for $alpha$ production. This breakup component was modeled using fresco CDCC-CRC calculations. This novel physics process was then incorporated into the Geant4 framework, facilitating the calculation of dose distributions in water and tissue. The application of this method demonstrated a precise reproduction of the dose deposited at the Bragg peak region, corroborating the experimental data from Liedner et al., thereby enhancing the accurate visibility of dose tailing.
{"title":"Unraveling the Effects of Cluster Transfer-Induced Breakups on $^{12}$C Fragmentation in Hadron Therapy","authors":"Arunima Dev T V, Anagha P. K, Midhun C. V, M. M Musthafa, Vafiya Thaslim T. T, Shaima Akbar, Swapna B, Nicemon Thomas, Antony Joseph, S. Ganesan","doi":"arxiv-2409.07090","DOIUrl":"https://doi.org/arxiv-2409.07090","url":null,"abstract":"The capability of standard Geant4 PhysicsLists to address the fragmentation\u0000of $^{12}$C$-^{12}$C was assessed through a comparative analysis with\u0000experimental cross sections reported by Divay et al. and Dudouet et al. The\u0000standard PhysicsLists were found to be inadequate in explaining the\u0000fragmentation systematics. To address this limitation, the breakup component of\u0000fragmentation was systematically integrated into the standard PhysicsList,\u0000which successfully replicated the differential and double differential cross\u0000sections for $alpha$ production. This breakup component was modeled using\u0000fresco CDCC-CRC calculations. This novel physics process was then incorporated\u0000into the Geant4 framework, facilitating the calculation of dose distributions\u0000in water and tissue. The application of this method demonstrated a precise\u0000reproduction of the dose deposited at the Bragg peak region, corroborating the\u0000experimental data from Liedner et al., thereby enhancing the accurate\u0000visibility of dose tailing.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176594","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}
Rohan Amare, Danielle Stolley, Steve Parrish, Megan Jacobsen, Rick Layman, Chimamanda Santos, Beatrice Riviere, Natalie Fowlkes, David Fuentes, Erik Cressman
Objective: Innovative therapies such as thermoembolization are expected to play an important role in improvising care for patients with diseases such as hepatocellular carcinoma. Thermoembolization is a minimally invasive strategy that combines thermal ablation and embolization in a single procedure. This approach exploits an exothermic chemical reaction that occurs when an acid chloride is delivered via an endovascular route. However, comprehension of the complexities of the biophysics of thermoembolization is challenging. Mathematical models can aid in understanding such complex processes and assisting clinicians in making informed decisions. In this study, we used a Hagen Poiseuille 1D blood flow model to predict the mass transport and possible embolization locations in a porcine hepatic artery. Method: The 1D flow model was used on in vivo embolization imaging data of three pigs. The hydrolysis time constant of acid chloride chemical reaction was optimized for each pig, and LOOCV method was used to test the model's predictive ability. Conclusion: This basic model provided a balanced accuracy rate of 66.8% for identifying the possible locations of embolization in the hepatic artery. Use of the model provides an initial understanding of the vascular transport phenomena that are predicted to occur as a result of thermoembolization.
{"title":"1D Thermoembolization Model Using CT Imaging Data for Porcine Liver","authors":"Rohan Amare, Danielle Stolley, Steve Parrish, Megan Jacobsen, Rick Layman, Chimamanda Santos, Beatrice Riviere, Natalie Fowlkes, David Fuentes, Erik Cressman","doi":"arxiv-2409.06811","DOIUrl":"https://doi.org/arxiv-2409.06811","url":null,"abstract":"Objective: Innovative therapies such as thermoembolization are expected to\u0000play an important role in improvising care for patients with diseases such as\u0000hepatocellular carcinoma. Thermoembolization is a minimally invasive strategy\u0000that combines thermal ablation and embolization in a single procedure. This\u0000approach exploits an exothermic chemical reaction that occurs when an acid\u0000chloride is delivered via an endovascular route. However, comprehension of the\u0000complexities of the biophysics of thermoembolization is challenging.\u0000Mathematical models can aid in understanding such complex processes and\u0000assisting clinicians in making informed decisions. In this study, we used a\u0000Hagen Poiseuille 1D blood flow model to predict the mass transport and possible\u0000embolization locations in a porcine hepatic artery. Method: The 1D flow model was used on in vivo embolization imaging data of\u0000three pigs. The hydrolysis time constant of acid chloride chemical reaction was\u0000optimized for each pig, and LOOCV method was used to test the model's\u0000predictive ability. Conclusion: This basic model provided a balanced accuracy rate of 66.8% for\u0000identifying the possible locations of embolization in the hepatic artery. Use\u0000of the model provides an initial understanding of the vascular transport\u0000phenomena that are predicted to occur as a result of thermoembolization.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176596","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}
Xiaoxi Liu, Ying-Chieh Lai., Di Cui, Shiang-Cheng Kung, Meyeon Park, Laszik Zoltan, Peder E. Z. Larson, Zhen J. Wang
BACKGROUND: Kidney transplant is the treatment of choice for patients with end-stage renal disease. Early detection of allograft injury is important to delay or prevent irreversible damage. PURPOSE: To investigate the feasibility of hyperpolarized (HP) [1-13C]pyruvate MRI for assessing kidney allograft metabolism. SUBJECTS: 6 participants (mean age, 45.2 +- 12.4 years, 2 females) scheduled for kidney allograft biopsy and 5 patients (mean age, 59.6 +- 10.4 years, 2 females) with renal cell carcinoma (RCC). ASSESSMENT: Five of the six kidney allograft participants underwent biopsy after MRI. Estimated glomerular filtration rate (eGFR) and urine protein-to-creatine ratio (uPCR) were collected within 4 weeks of MRI. Kidney metabolism was quantified from HP [1-13C]pyruvate MRI using the lactate-to-pyruvate ratio in allograft kidneys and non-tumor bearing kidneys from RCC patients. RESULTS: Biopsy was performed a mean of 9 days (range 5-19 days) after HP [1-13C]pyruvate MRI. Three biopsies were normal, one showed low-grade fibrosis and one showed moderate microvascular inflammation. All had stable functioning allografts with eGFR > 60 mL/min/1.73 m2 and normal uPCR. One participant who did not undergo biopsy had reduced eGFR of 49 mL/min/1.73 m2 and elevated uPCR. The mean lactate-to-pyruvate ratio was 0.373 in participants with normal findings (n = 3) and 0.552 in participants with abnormal findings (n = 2). The lactate-to-pyruvate ratio was highest (0.847) in the participant with reduced eGFR and elevated uPRC. Native non-tumor bearing kidneys had a mean lactate-to-pyruvate ratio of 0.309. DATA CONCLUSION: Stable allografts with normal findings at biopsy showed lactate-to-pyruvate ratios similar to native non-tumor bearing kidneys, whereas allografts with abnormal findings showed higher lactate-to-pyruvate ratios.
{"title":"Initial Experience of Metabolic Imaging with Hyperpolarized [1-13C]pyruvate MRI in Kidney Transplant Patients","authors":"Xiaoxi Liu, Ying-Chieh Lai., Di Cui, Shiang-Cheng Kung, Meyeon Park, Laszik Zoltan, Peder E. Z. Larson, Zhen J. Wang","doi":"arxiv-2409.06664","DOIUrl":"https://doi.org/arxiv-2409.06664","url":null,"abstract":"BACKGROUND: Kidney transplant is the treatment of choice for patients with\u0000end-stage renal disease. Early detection of allograft injury is important to\u0000delay or prevent irreversible damage. PURPOSE: To investigate the feasibility\u0000of hyperpolarized (HP) [1-13C]pyruvate MRI for assessing kidney allograft\u0000metabolism. SUBJECTS: 6 participants (mean age, 45.2 +- 12.4 years, 2 females)\u0000scheduled for kidney allograft biopsy and 5 patients (mean age, 59.6 +- 10.4\u0000years, 2 females) with renal cell carcinoma (RCC). ASSESSMENT: Five of the six\u0000kidney allograft participants underwent biopsy after MRI. Estimated glomerular\u0000filtration rate (eGFR) and urine protein-to-creatine ratio (uPCR) were\u0000collected within 4 weeks of MRI. Kidney metabolism was quantified from HP\u0000[1-13C]pyruvate MRI using the lactate-to-pyruvate ratio in allograft kidneys\u0000and non-tumor bearing kidneys from RCC patients. RESULTS: Biopsy was performed\u0000a mean of 9 days (range 5-19 days) after HP [1-13C]pyruvate MRI. Three biopsies\u0000were normal, one showed low-grade fibrosis and one showed moderate\u0000microvascular inflammation. All had stable functioning allografts with eGFR >\u000060 mL/min/1.73 m2 and normal uPCR. One participant who did not undergo biopsy\u0000had reduced eGFR of 49 mL/min/1.73 m2 and elevated uPCR. The mean\u0000lactate-to-pyruvate ratio was 0.373 in participants with normal findings (n =\u00003) and 0.552 in participants with abnormal findings (n = 2). The\u0000lactate-to-pyruvate ratio was highest (0.847) in the participant with reduced\u0000eGFR and elevated uPRC. Native non-tumor bearing kidneys had a mean\u0000lactate-to-pyruvate ratio of 0.309. DATA CONCLUSION: Stable allografts with\u0000normal findings at biopsy showed lactate-to-pyruvate ratios similar to native\u0000non-tumor bearing kidneys, whereas allografts with abnormal findings showed\u0000higher lactate-to-pyruvate ratios.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176595","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 extends the Lucas-Washburn theory through non-equilibrium thermodynamic analysis to examine fluid absorption in medical foams used for hemorrhage control. As a universal model for capillary flow in porous media, the theory demonstrated strong agreement with experimental results, confirming its semi-quantitative accuracy. Minor deviations, likely due to material heterogeneity, were observed and explained, enhancing the theory's applicability to real-world conditions. Our findings underscore the universality of the Lucas-Washburn framework and provide valuable insights for optimizing the design of medical foams, ultimately contributing to more effective bleeding control solutions in clinical applications.
{"title":"Water Absorption Dynamics in Medical Foam: Empirical Validation of the Lucas-Washburn Model","authors":"Weihua Mu, Lina Cao","doi":"arxiv-2409.06265","DOIUrl":"https://doi.org/arxiv-2409.06265","url":null,"abstract":"This study extends the Lucas-Washburn theory through non-equilibrium\u0000thermodynamic analysis to examine fluid absorption in medical foams used for\u0000hemorrhage control. As a universal model for capillary flow in porous media,\u0000the theory demonstrated strong agreement with experimental results, confirming\u0000its semi-quantitative accuracy. Minor deviations, likely due to material\u0000heterogeneity, were observed and explained, enhancing the theory's\u0000applicability to real-world conditions. Our findings underscore the\u0000universality of the Lucas-Washburn framework and provide valuable insights for\u0000optimizing the design of medical foams, ultimately contributing to more\u0000effective bleeding control solutions in clinical applications.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176597","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}
Dolors Serra, Pau Romero, Paula Franco, Ignacio Bernat, Miguel Lozano, Ignacio Garcia-Fernandez, David Soto, Antonio Berruezo, Oscar Camara, Rafael Sebastian
This study presents a novel methodology for stratifying post-myocardial infarction patients at risk of ventricular arrhythmias using patient-specific 3D cardiac models derived from late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) images. The method integrates imaging and computational simulation with a simplified cellular automaton model, Arrhythmic3D, enabling rapid and accurate VA risk assessment in clinical timeframes. Applied to 51 patients, the model generated thousands of personalized simulations to evaluate arrhythmia inducibility and predict VA risk. Key findings include the identification of slow conduction channels (SCCs) within scar tissue as critical to reentrant arrhythmias and the localization of high-risk zones for potential intervention. The Arrhythmic Risk Score (ARRISK), developed from simulation results, demonstrated strong concordance with clinical outcomes and outperformed traditional imaging-based risk stratification. The methodology is fully automated, requiring minimal user intervention, and offers a promising tool for improving precision medicine in cardiac care by enhancing patient-specific arrhythmia risk assessment and guiding treatment strategies.
这项研究提出了一种新方法，利用从晚期钆增强心血管磁共振（LGE-CMR）图像中提取的患者特异性三维心脏模型，对心肌梗塞后患者的室性心律失常风险进行分层。该方法将成像和计算模拟与简化的细胞自动机模型 Arrhythmic3D 相结合，能够在临床时间内快速准确地评估 VA 风险。该模型应用于 51 名患者，生成了数千个个性化模拟，用于评估心律失常诱发性和预测 VA 风险。主要发现包括确定瘢痕组织内的慢传导通道（SCC）对再发性心律失常至关重要，以及定位潜在干预的高风险区。根据模拟结果开发的心律失常风险评分（ARRISK）与临床结果非常吻合，而且优于传统的基于成像的风险分层。该方法是全自动的，只需极少的用户干预，通过加强特定患者的心律失常风险评估和指导治疗策略，为改善心脏护理的精准医疗提供了一种前景广阔的工具。
{"title":"Unsupervised stratification of patients with myocardial infarction based on imaging and in-silico biomarkers","authors":"Dolors Serra, Pau Romero, Paula Franco, Ignacio Bernat, Miguel Lozano, Ignacio Garcia-Fernandez, David Soto, Antonio Berruezo, Oscar Camara, Rafael Sebastian","doi":"arxiv-2409.06526","DOIUrl":"https://doi.org/arxiv-2409.06526","url":null,"abstract":"This study presents a novel methodology for stratifying post-myocardial\u0000infarction patients at risk of ventricular arrhythmias using patient-specific\u00003D cardiac models derived from late gadolinium enhancement cardiovascular\u0000magnetic resonance (LGE-CMR) images. The method integrates imaging and\u0000computational simulation with a simplified cellular automaton model,\u0000Arrhythmic3D, enabling rapid and accurate VA risk assessment in clinical\u0000timeframes. Applied to 51 patients, the model generated thousands of\u0000personalized simulations to evaluate arrhythmia inducibility and predict VA\u0000risk. Key findings include the identification of slow conduction channels\u0000(SCCs) within scar tissue as critical to reentrant arrhythmias and the\u0000localization of high-risk zones for potential intervention. The Arrhythmic Risk\u0000Score (ARRISK), developed from simulation results, demonstrated strong\u0000concordance with clinical outcomes and outperformed traditional imaging-based\u0000risk stratification. The methodology is fully automated, requiring minimal user\u0000intervention, and offers a promising tool for improving precision medicine in\u0000cardiac care by enhancing patient-specific arrhythmia risk assessment and\u0000guiding treatment strategies.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176598","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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