Purpose: To identify the predominant source of the $T_1$ variability described in the literature, which ranges from 0.6 - 1.1 s for brain white matter at 3 T. Methods: 25 $T_1$-mapping methods from the literature were simulated with a mono-exponential and magnetization-transfer (MT) models, each followed by mono-exponential fitting. A single set of model parameters was assumed for the simulation of all methods, and these parameters were estimated by fitting the simulation-based to the corresponding literature $T_1$ values of white matter at 3 T. Results: Mono-exponential simulations suggest good inter-method reproducibility and fail to explain the highly variable $T_1$ estimates in the literature. In contrast, MT simulations suggest that a mono-exponential fit results in a variable $T_1$ and explain up to 62% of the literature's variability. Conclusion: The results suggest that a mono-exponential model does not adequately describe longitudinal relaxation in biological tissue. Therefore, $T_1$ in biological tissue should be considered only a semi-quantitative metric that is inherently contingent upon the imaging methodology; and comparisons between different $T_1$-mapping methods and the use of simplistic spin systems - such as doped-water phantoms - for validation should be viewed with caution.
{"title":"Magnetization transfer explains most of the $T_1$ variability in the MRI literature","authors":"Jakob Assländer","doi":"arxiv-2409.05318","DOIUrl":"https://doi.org/arxiv-2409.05318","url":null,"abstract":"Purpose: To identify the predominant source of the $T_1$ variability\u0000described in the literature, which ranges from 0.6 - 1.1 s for brain white\u0000matter at 3 T. Methods: 25 $T_1$-mapping methods from the literature were simulated with a\u0000mono-exponential and magnetization-transfer (MT) models, each followed by\u0000mono-exponential fitting. A single set of model parameters was assumed for the\u0000simulation of all methods, and these parameters were estimated by fitting the\u0000simulation-based to the corresponding literature $T_1$ values of white matter\u0000at 3 T. Results: Mono-exponential simulations suggest good inter-method\u0000reproducibility and fail to explain the highly variable $T_1$ estimates in the\u0000literature. In contrast, MT simulations suggest that a mono-exponential fit\u0000results in a variable $T_1$ and explain up to 62% of the literature's\u0000variability. Conclusion: The results suggest that a mono-exponential model does not\u0000adequately describe longitudinal relaxation in biological tissue. Therefore,\u0000$T_1$ in biological tissue should be considered only a semi-quantitative metric\u0000that is inherently contingent upon the imaging methodology; and comparisons\u0000between different $T_1$-mapping methods and the use of simplistic spin systems\u0000- such as doped-water phantoms - for validation should be viewed with caution.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176602","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}
Yao Chen, Savannah M. Decker, Petr Bruza, David J. Gladstone, Lesley A. Jarvis, Brian W. Pogue, Kimberley S. Samkoe, Rongxiao Zhang
Accurate patient positioning is critical for precise radiotherapy dose delivery, as positioning errors can significantly affect treatment outcomes. This study introduces a novel method for tracking loco-regional tissue deformation through Cherenkov image analysis during fractionated breast cancer radiotherapy. The primary goal was to develop and test an algorithm for Cherenkov-based regional position accuracy quantification, specifically for loco-regional deformations, which lack ideal quantification methods in radiotherapy. Blood vessel detection and segmentation were developed in Cherenkov images using a tissue phantom with incremental movements, and later applied to images from fractionated whole breast radiotherapy in human patients (n=10). A combined rigid and non-rigid registration technique was used to detect inter- and intra-fractional positioning variations. This approach quantified positioning variations in two parts: a global shift from rigid registration and a two-dimensional variation map of loco-regional deformation from non-rigid registration. The methodology was validated using an anthropomorphic chest phantom experiment, where known treatment couch translations and respiratory motion were simulated to assess inter- and intra-fractional uncertainties, yielding an average accuracy of 0.83 mm for couch translations up to 20 mm. Analysis of clinical Cherenkov data from ten breast cancer patients showed an inter-fraction setup variation of 3.7 plus minus 2.4 mm relative to the first fraction and loco-regional deformations (95th percentile) of up to 3.3 plus minus 1.9 mm. This study presents a Cherenkov-based approach to quantify global and local positioning variations, demonstrating feasibility in addressing loco-regional deformations that conventional imaging techniques fail to capture.
{"title":"Cherenkov Imaged Bio-morphological Features Verify Patient Positioning with Deformable Tissue Translocation in Breast Radiotherapy","authors":"Yao Chen, Savannah M. Decker, Petr Bruza, David J. Gladstone, Lesley A. Jarvis, Brian W. Pogue, Kimberley S. Samkoe, Rongxiao Zhang","doi":"arxiv-2409.05680","DOIUrl":"https://doi.org/arxiv-2409.05680","url":null,"abstract":"Accurate patient positioning is critical for precise radiotherapy dose\u0000delivery, as positioning errors can significantly affect treatment outcomes.\u0000This study introduces a novel method for tracking loco-regional tissue\u0000deformation through Cherenkov image analysis during fractionated breast cancer\u0000radiotherapy. The primary goal was to develop and test an algorithm for\u0000Cherenkov-based regional position accuracy quantification, specifically for\u0000loco-regional deformations, which lack ideal quantification methods in\u0000radiotherapy. Blood vessel detection and segmentation were developed in\u0000Cherenkov images using a tissue phantom with incremental movements, and later\u0000applied to images from fractionated whole breast radiotherapy in human patients\u0000(n=10). A combined rigid and non-rigid registration technique was used to\u0000detect inter- and intra-fractional positioning variations. This approach\u0000quantified positioning variations in two parts: a global shift from rigid\u0000registration and a two-dimensional variation map of loco-regional deformation\u0000from non-rigid registration. The methodology was validated using an\u0000anthropomorphic chest phantom experiment, where known treatment couch\u0000translations and respiratory motion were simulated to assess inter- and\u0000intra-fractional uncertainties, yielding an average accuracy of 0.83 mm for\u0000couch translations up to 20 mm. Analysis of clinical Cherenkov data from ten\u0000breast cancer patients showed an inter-fraction setup variation of 3.7 plus\u0000minus 2.4 mm relative to the first fraction and loco-regional deformations\u0000(95th percentile) of up to 3.3 plus minus 1.9 mm. This study presents a\u0000Cherenkov-based approach to quantify global and local positioning variations,\u0000demonstrating feasibility in addressing loco-regional deformations that\u0000conventional imaging techniques fail to capture.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176600","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}
J. Lerendegui-Marco, J. Balibrea-Correa, P. Álvarez-Rodríguez, V. Babiano-Suárez, B. Gameiro, I. Ladarescu, C. Méndez-Malagón, C. Michelagnoli, I. Porras, M. Porras-Quesada, C. Ruiz-Ruiz, P. Torres-Sánchez, C. Domingo-Pardo
Dosimetry in BNCT poses significant challenges due to the indirect effect of neutrons interacting with elements within the body and uncertainties associated with the uptake of boron compounds used in clinical practice. Current treatment planning relies on unconventional estimates of boron tumor uptake derived from prior PET scans and thus, an online boron-uptake monitor would be highly convenient. This work presents the first pilot experiments carried out at ILL-Grenoble with the high-efficiency Compton camera i-TED, hereby aiming at demonstrating its applicability for BNCT dosimetry by introducing real-time measurement of the boron concentration and imaging capabilities of spatial dose distribution. In this experiment, we measured the $^{10}$B uptake of different cancer cells of tongue squamous cell carcinoma, malignant melanoma and glioblastoma treated with BPA (80~ppm of $^{10}$B). The samples were irradiated with the thermal neutron spectrum of ILL-Grenoble and the 478keV $gamma$-rays from the $^{7}$Li de-excitation after the neutron-boron reaction were registered both with the Compton imager and the high-sensitivity FIPPS HPGe array. These series of measurements allowed us to demonstrate the imaging capabilities of the Compton imaging device for this type of application, as well as to assess its sensitivity, which was found to be below 1 $mu$g of $^{10}$B.
由于中子与体内元素相互作用的间接效应以及临床实践中使用的硼化合物摄取量的不确定性，BNCT 的剂量测定面临着巨大挑战。目前的治疗计划依赖于从先前的 PET 扫描中得出的非传统的硼肿瘤摄取估计值，因此，在线硼摄取监测仪将非常方便。这项工作介绍了在ILL-格勒诺布尔利用高效康普顿相机i-TED进行的首次试点实验，旨在通过引入硼浓度的实时测量和空间剂量分布的成像功能，展示其在BNCT剂量测定中的适用性。在本实验中，我们测量了经双酚 A 处理（80~ppm 的^{10}$B）的舌鳞癌、恶性黑色素瘤和胶质母细胞瘤等不同癌细胞对^{10}$B 的吸收情况。用 ILL-Grenoble 的热中子能谱对样品进行辐照，并用康普顿成像仪和高灵敏度 FIPPS HPGearray 对中子-硼反应后^{7}$Li 去激发产生的 478keV $γ$射线进行登记。通过这一系列测量，我们展示了康普顿成像装置在这类应用中的成像能力，并评估了其灵敏度，发现其灵敏度低于 1 $m$g of$^{10}$B 。
{"title":"Real-Time Boron Concentration Measurement in BNCT Using Compton Imaging","authors":"J. Lerendegui-Marco, J. Balibrea-Correa, P. Álvarez-Rodríguez, V. Babiano-Suárez, B. Gameiro, I. Ladarescu, C. Méndez-Malagón, C. Michelagnoli, I. Porras, M. Porras-Quesada, C. Ruiz-Ruiz, P. Torres-Sánchez, C. Domingo-Pardo","doi":"arxiv-2409.05687","DOIUrl":"https://doi.org/arxiv-2409.05687","url":null,"abstract":"Dosimetry in BNCT poses significant challenges due to the indirect effect of\u0000neutrons interacting with elements within the body and uncertainties associated\u0000with the uptake of boron compounds used in clinical practice. Current treatment\u0000planning relies on unconventional estimates of boron tumor uptake derived from\u0000prior PET scans and thus, an online boron-uptake monitor would be highly\u0000convenient. This work presents the first pilot experiments carried out at\u0000ILL-Grenoble with the high-efficiency Compton camera i-TED, hereby aiming at\u0000demonstrating its applicability for BNCT dosimetry by introducing real-time\u0000measurement of the boron concentration and imaging capabilities of spatial dose\u0000distribution. In this experiment, we measured the $^{10}$B uptake of different\u0000cancer cells of tongue squamous cell carcinoma, malignant melanoma and\u0000glioblastoma treated with BPA (80~ppm of $^{10}$B). The samples were irradiated\u0000with the thermal neutron spectrum of ILL-Grenoble and the 478keV $gamma$-rays\u0000from the $^{7}$Li de-excitation after the neutron-boron reaction were\u0000registered both with the Compton imager and the high-sensitivity FIPPS HPGe\u0000array. These series of measurements allowed us to demonstrate the imaging\u0000capabilities of the Compton imaging device for this type of application, as\u0000well as to assess its sensitivity, which was found to be below 1 $mu$g of\u0000$^{10}$B.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176599","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}
Yuzhu Li, Nir Pillar, Tairan Liu, Guangdong Ma, Yuxuan Qi, Kevin de Haan, Yijie Zhang, Xilin Yang, Adrian J. Correa, Guangqian Xiao, Kuang-Yu Jen, Kenneth A. Iczkowski, Yulun Wu, William Dean Wallace, Aydogan Ozcan
Organ transplantation serves as the primary therapeutic strategy for end-stage organ failures. However, allograft rejection is a common complication of organ transplantation. Histological assessment is essential for the timely detection and diagnosis of transplant rejection and remains the gold standard. Nevertheless, the traditional histochemical staining process is time-consuming, costly, and labor-intensive. Here, we present a panel of virtual staining neural networks for lung and heart transplant biopsies, which digitally convert autofluorescence microscopic images of label-free tissue sections into their brightfield histologically stained counterparts, bypassing the traditional histochemical staining process. Specifically, we virtually generated Hematoxylin and Eosin (H&E), Masson's Trichrome (MT), and Elastic Verhoeff-Van Gieson (EVG) stains for label-free transplant lung tissue, along with H&E and MT stains for label-free transplant heart tissue. Subsequent blind evaluations conducted by three board-certified pathologists have confirmed that the virtual staining networks consistently produce high-quality histology images with high color uniformity, closely resembling their well-stained histochemical counterparts across various tissue features. The use of virtually stained images for the evaluation of transplant biopsies achieved comparable diagnostic outcomes to those obtained via traditional histochemical staining, with a concordance rate of 82.4% for lung samples and 91.7% for heart samples. Moreover, virtual staining models create multiple stains from the same autofluorescence input, eliminating structural mismatches observed between adjacent sections stained in the traditional workflow, while also saving tissue, expert time, and staining costs.
{"title":"Label-free evaluation of lung and heart transplant biopsies using virtual staining","authors":"Yuzhu Li, Nir Pillar, Tairan Liu, Guangdong Ma, Yuxuan Qi, Kevin de Haan, Yijie Zhang, Xilin Yang, Adrian J. Correa, Guangqian Xiao, Kuang-Yu Jen, Kenneth A. Iczkowski, Yulun Wu, William Dean Wallace, Aydogan Ozcan","doi":"arxiv-2409.05255","DOIUrl":"https://doi.org/arxiv-2409.05255","url":null,"abstract":"Organ transplantation serves as the primary therapeutic strategy for\u0000end-stage organ failures. However, allograft rejection is a common complication\u0000of organ transplantation. Histological assessment is essential for the timely\u0000detection and diagnosis of transplant rejection and remains the gold standard.\u0000Nevertheless, the traditional histochemical staining process is time-consuming,\u0000costly, and labor-intensive. Here, we present a panel of virtual staining\u0000neural networks for lung and heart transplant biopsies, which digitally convert\u0000autofluorescence microscopic images of label-free tissue sections into their\u0000brightfield histologically stained counterparts, bypassing the traditional\u0000histochemical staining process. Specifically, we virtually generated\u0000Hematoxylin and Eosin (H&E), Masson's Trichrome (MT), and Elastic Verhoeff-Van\u0000Gieson (EVG) stains for label-free transplant lung tissue, along with H&E and\u0000MT stains for label-free transplant heart tissue. Subsequent blind evaluations\u0000conducted by three board-certified pathologists have confirmed that the virtual\u0000staining networks consistently produce high-quality histology images with high\u0000color uniformity, closely resembling their well-stained histochemical\u0000counterparts across various tissue features. The use of virtually stained\u0000images for the evaluation of transplant biopsies achieved comparable diagnostic\u0000outcomes to those obtained via traditional histochemical staining, with a\u0000concordance rate of 82.4% for lung samples and 91.7% for heart samples.\u0000Moreover, virtual staining models create multiple stains from the same\u0000autofluorescence input, eliminating structural mismatches observed between\u0000adjacent sections stained in the traditional workflow, while also saving\u0000tissue, expert time, and staining costs.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176604","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}
José Gerardo Suárez-García, María Isabel Antonio-de la Rosa, Nora Coral Soriano-Becerril, Javier M. Hernández-López, Benito de Celis-Alonso
Novel brain biomarkers of obesity were sought by studying statistical measurements on fractional anisotropy (FA) images of different white matter (WM) tracts from subjects with specific demographic characteristics. Tract measurements were chosen that showed differences between two groups (normal weigh and overweight/obese) and that were correlated with their BMI. From these measurements, a simple and novel process was applied to select those that would allow the creation of models to quantify and classify the state of obesity of individuals. The biomarkers were created from the tract measurements used in the models. Some positive correlations were found between WM integrity and BMI, mainly in tracts involved in motor functions. From this result, neuroplasticity in motor tracts associated with obesity was hypothesized. Two models were built to quantify and classify obesity status, whose regression coefficients formed the novel proposed obesity-associated brain biomarkers. A process for the selection of tract measurements was proposed, such that models were built to determine the obesity status of subjects individually. From these models, novel brain biomarkers associated with obesity were created. These allow the generation of new knowledge and are intended to be a future tool in the clinical environment for the prevention and treatment of brain changes associated with obesity.
{"title":"Novel brain biomarkers of obesity based on statistical measurements of white matter tracts","authors":"José Gerardo Suárez-García, María Isabel Antonio-de la Rosa, Nora Coral Soriano-Becerril, Javier M. Hernández-López, Benito de Celis-Alonso","doi":"arxiv-2409.04680","DOIUrl":"https://doi.org/arxiv-2409.04680","url":null,"abstract":"Novel brain biomarkers of obesity were sought by studying statistical\u0000measurements on fractional anisotropy (FA) images of different white matter\u0000(WM) tracts from subjects with specific demographic characteristics. Tract\u0000measurements were chosen that showed differences between two groups (normal\u0000weigh and overweight/obese) and that were correlated with their BMI. From these\u0000measurements, a simple and novel process was applied to select those that would\u0000allow the creation of models to quantify and classify the state of obesity of\u0000individuals. The biomarkers were created from the tract measurements used in\u0000the models. Some positive correlations were found between WM integrity and BMI,\u0000mainly in tracts involved in motor functions. From this result, neuroplasticity\u0000in motor tracts associated with obesity was hypothesized. Two models were built\u0000to quantify and classify obesity status, whose regression coefficients formed\u0000the novel proposed obesity-associated brain biomarkers. A process for the\u0000selection of tract measurements was proposed, such that models were built to\u0000determine the obesity status of subjects individually. From these models, novel\u0000brain biomarkers associated with obesity were created. These allow the\u0000generation of new knowledge and are intended to be a future tool in the\u0000clinical environment for the prevention and treatment of brain changes\u0000associated with obesity.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176634","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}
Junbo Peng, Tonghe Wang, Richard L. J. Qiu, Chih-Wei Chang, Justin Roper, David S. Yu, Xiangyang Tang, Xiaofeng Yang
Background: Limited-angle (LA) dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations are hindered by the challenging image reconstruction from LA projections. While optimization-based and deep learning-based methods have been proposed for image reconstruction, their utilization is limited by the requirement for X-ray spectra measurement or paired datasets for model training. Purpose: This work aims to facilitate the clinical applications of fast and low-dose DECBCT by developing a practical solution for image reconstruction in LA-DECBCT. Methods: An inter-spectral structural similarity-based regularization was integrated into the iterative image reconstruction in LA-DECBCT. By enforcing the similarity between the DE images, LA artifacts were efficiently reduced in the reconstructed DECBCT images. The proposed method was evaluated using four physical phantoms and three digital phantoms, demonstrating its efficacy in quantitative DECBCT imaging. Results: In all the studies, the proposed method achieves accurate image reconstruction without visible residual artifacts from LA-DECBCT projection data. In the digital phantom study, the proposed method reduces the mean-absolute-error (MAE) from 419 to 14 HU for the High-energy CBCT and 591 to 20 HU for the low-energy CBCT. Conclusions: The proposed method achieves accurate image reconstruction without the need for X-ray spectra measurement for optimization or paired datasets for model training, showing great practical value in clinical implementations of LA-DECBCT.
背景：有限角度（LA）双能量（DE）锥束 CT（CBCT）被认为是在当前 CBCT 扫描仪上实现快速、低剂量 DE 成像而无需修改硬件的潜在解决方案。然而，LA 投影的图像重建难度很大，阻碍了其临床应用。虽然基于优化和深度学习的方法已被提出用于图像重建，但由于需要测量 X 射线光谱或配对数据集进行模型训练，这些方法的使用受到了限制。目的：这项工作旨在通过开发一种实用的LA-DECBCT 图像重建解决方案，促进快速、低剂量 DECBCT 的临床应用。方法：在 LA-DECBCT 的迭代图像重建中加入了基于光谱间结构相似性的正则化。通过加强 DE 图像之间的相似性，重建的 DECBCT 图像中的 LA 伪影得以有效减少。使用四个物理模型和三个数字模型对所提出的方法进行了评估，证明了该方法在定量 DECBCT 成像中的有效性。结果：在所有研究中，所提出的方法都能从 LA-DECBCT 投影数据中准确地重建图像，且无明显的残留伪影。在数字模型研究中，所提出的方法将高能量 CBCT 的主题误差（MAE）从 419 HU 降至 14 HU，将低能量 CBCT 的主题误差（MAE）从 591 HU 降至 20 HU。结论：该方法无需测量 X 射线光谱进行优化，也无需成对的数据集进行模型训练，即可实现精确的图像重建，在 LA-DECBCT 的临床应用中显示出巨大的实用价值。
{"title":"Optimization-Based Image Reconstruction Regularized with Inter-Spectral Structural Similarity for Limited-Angle Dual-Energy Cone-Beam CT","authors":"Junbo Peng, Tonghe Wang, Richard L. J. Qiu, Chih-Wei Chang, Justin Roper, David S. Yu, Xiangyang Tang, Xiaofeng Yang","doi":"arxiv-2409.04674","DOIUrl":"https://doi.org/arxiv-2409.04674","url":null,"abstract":"Background: Limited-angle (LA) dual-energy (DE) cone-beam CT (CBCT) is\u0000considered as a potential solution to achieve fast and low-dose DE imaging on\u0000current CBCT scanners without hardware modification. However, its clinical\u0000implementations are hindered by the challenging image reconstruction from LA\u0000projections. While optimization-based and deep learning-based methods have been\u0000proposed for image reconstruction, their utilization is limited by the\u0000requirement for X-ray spectra measurement or paired datasets for model\u0000training. Purpose: This work aims to facilitate the clinical applications of fast and\u0000low-dose DECBCT by developing a practical solution for image reconstruction in\u0000LA-DECBCT. Methods: An inter-spectral structural similarity-based regularization was\u0000integrated into the iterative image reconstruction in LA-DECBCT. By enforcing\u0000the similarity between the DE images, LA artifacts were efficiently reduced in\u0000the reconstructed DECBCT images. The proposed method was evaluated using four\u0000physical phantoms and three digital phantoms, demonstrating its efficacy in\u0000quantitative DECBCT imaging. Results: In all the studies, the proposed method achieves accurate image\u0000reconstruction without visible residual artifacts from LA-DECBCT projection\u0000data. In the digital phantom study, the proposed method reduces the\u0000mean-absolute-error (MAE) from 419 to 14 HU for the High-energy CBCT and 591 to\u000020 HU for the low-energy CBCT. Conclusions: The proposed method achieves accurate image reconstruction\u0000without the need for X-ray spectra measurement for optimization or paired\u0000datasets for model training, showing great practical value in clinical\u0000implementations of LA-DECBCT.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176603","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}
Hua-Chieh Shao, Tielige Mengke, Tinsu Pan, You Zhang
Real-time cone-beam computed tomography (CBCT) provides instantaneous visualization of patient anatomy for image guidance, motion tracking, and online treatment adaptation in radiotherapy. While many real-time imaging and motion tracking methods leveraged patient-specific prior information to alleviate under-sampling challenges and meet the temporal constraint (< 500 ms), the prior information can be outdated and introduce biases, thus compromising the imaging and motion tracking accuracy. To address this challenge, we developed a framework (DREME) for real-time CBCT imaging and motion estimation, without relying on patient-specific prior knowledge. DREME incorporates a deep learning-based real-time CBCT imaging and motion estimation method into a dynamic CBCT reconstruction framework. The reconstruction framework reconstructs a dynamic sequence of CBCTs in a data-driven manner from a standard pre-treatment scan, without utilizing patient-specific knowledge. Meanwhile, a convolutional neural network-based motion encoder is jointly trained during the reconstruction to learn motion-related features relevant for real-time motion estimation, based on a single arbitrarily-angled x-ray projection. DREME was tested on digital phantom simulation and real patient studies. DREME accurately solved 3D respiration-induced anatomic motion in real time (~1.5 ms inference time for each x-ray projection). In the digital phantom study, it achieved an average lung tumor center-of-mass localization error of 1.2$pm$0.9 mm (Mean$pm$SD). In the patient study, it achieved a real-time tumor localization accuracy of 1.8$pm$1.6 mm in the projection domain. DREME achieves CBCT and volumetric motion estimation in real time from a single x-ray projection at arbitrary angles, paving the way for future clinical applications in intra-fractional motion management.
{"title":"Real-time CBCT Imaging and Motion Tracking via a Single Arbitrarily-angled X-ray Projection by a Joint Dynamic Reconstruction and Motion Estimation (DREME) Framework (DREME) Framework","authors":"Hua-Chieh Shao, Tielige Mengke, Tinsu Pan, You Zhang","doi":"arxiv-2409.04614","DOIUrl":"https://doi.org/arxiv-2409.04614","url":null,"abstract":"Real-time cone-beam computed tomography (CBCT) provides instantaneous\u0000visualization of patient anatomy for image guidance, motion tracking, and\u0000online treatment adaptation in radiotherapy. While many real-time imaging and\u0000motion tracking methods leveraged patient-specific prior information to\u0000alleviate under-sampling challenges and meet the temporal constraint (< 500\u0000ms), the prior information can be outdated and introduce biases, thus\u0000compromising the imaging and motion tracking accuracy. To address this\u0000challenge, we developed a framework (DREME) for real-time CBCT imaging and\u0000motion estimation, without relying on patient-specific prior knowledge. DREME\u0000incorporates a deep learning-based real-time CBCT imaging and motion estimation\u0000method into a dynamic CBCT reconstruction framework. The reconstruction\u0000framework reconstructs a dynamic sequence of CBCTs in a data-driven manner from\u0000a standard pre-treatment scan, without utilizing patient-specific knowledge.\u0000Meanwhile, a convolutional neural network-based motion encoder is jointly\u0000trained during the reconstruction to learn motion-related features relevant for\u0000real-time motion estimation, based on a single arbitrarily-angled x-ray\u0000projection. DREME was tested on digital phantom simulation and real patient\u0000studies. DREME accurately solved 3D respiration-induced anatomic motion in real\u0000time (~1.5 ms inference time for each x-ray projection). In the digital phantom\u0000study, it achieved an average lung tumor center-of-mass localization error of\u00001.2$pm$0.9 mm (Mean$pm$SD). In the patient study, it achieved a real-time\u0000tumor localization accuracy of 1.8$pm$1.6 mm in the projection domain. DREME\u0000achieves CBCT and volumetric motion estimation in real time from a single x-ray\u0000projection at arbitrary angles, paving the way for future clinical applications\u0000in intra-fractional motion management.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176633","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}
Tanmay Mukherjee, Sunder Neelakantan, Kyle Myers, Carl Tong, Reza Avazmohammadi
Brightness mode (B-mode) ultrasound is a common imaging modality in the clinical assessment of several cardiovascular diseases. The utility of ultrasound-based functional indices such as the ejection fraction (EF) and stroke volume (SV) is widely described in diagnosing advanced-stage cardiovascular diseases. Additionally, structural indices obtained through the analysis of cardiac motion have been found to be important in the early-stage assessment of structural heart diseases, such as hypertrophic cardiomyopathy and myocardial infarction. Estimating heterogeneous variations in cardiac motion through B-mode ultrasound imaging is a crucial component of patient care. Despite the benefits of such imaging techniques, motion estimation algorithms are susceptible to variability between vendors due to the lack of benchmark motion quantities. In contrast, finite element (FE) simulations of cardiac biomechanics leverage well-established constitutive models of the myocardium to ensure reproducibility. In this study, we developed a methodology to create synthetic B-mode ultrasound images from FE simulations. The proposed methodology provides a detailed representation of displacements and strains under complex mouse-specific loading protocols of the LV. A comparison between the synthetic images and FE simulations revealed qualitative similarity in displacement patterns, thereby yielding benchmark quantities to improve the reproducibility of motion estimation algorithms. Thus, the study provides a methodology to create an extensive repository of images describing complex motion patterns to facilitate the enhanced reproducibility of cardiac motion analysis.
亮度模式（B 型）超声是临床评估多种心血管疾病的常用成像模式。射血分数（EF）和冲程容积（SV）等基于超声的功能指数在诊断晚期心血管疾病中的作用已被广泛描述。此外，通过分析心脏运动获得的结构指数在早期评估肥厚型心肌病和心肌梗塞等结构性心脏病时也非常重要。通过 B 型超声成像估计心脏运动的异质性变化是患者护理的重要组成部分。尽管这种成像技术好处多多，但由于缺乏基准运动量，运动估计算法很容易受到供应商之间差异的影响。与此相反，心脏生物力学的有限元（FE）模拟则利用成熟的心肌构成模型来确保可重复性。在这项研究中，我们开发了一种从有限元模拟中创建合成 B 型超声图像的方法。所提出的方法能详细呈现左心室在复杂的小鼠特定加载方案下的位移和应变。合成图像和 FE 模拟之间的比较显示了位移模式的定性相似性，从而为改进运动估计算法的可重复性提供了基准量。因此，该研究提供了一种方法来创建一个描述复杂运动模式的广泛图像库，以促进提高心脏运动分析的可重复性。
{"title":"Synthetic ultrasound images to benchmark echocardiography-based biomechanics","authors":"Tanmay Mukherjee, Sunder Neelakantan, Kyle Myers, Carl Tong, Reza Avazmohammadi","doi":"arxiv-2409.04577","DOIUrl":"https://doi.org/arxiv-2409.04577","url":null,"abstract":"Brightness mode (B-mode) ultrasound is a common imaging modality in the\u0000clinical assessment of several cardiovascular diseases. The utility of\u0000ultrasound-based functional indices such as the ejection fraction (EF) and\u0000stroke volume (SV) is widely described in diagnosing advanced-stage\u0000cardiovascular diseases. Additionally, structural indices obtained through the\u0000analysis of cardiac motion have been found to be important in the early-stage\u0000assessment of structural heart diseases, such as hypertrophic cardiomyopathy\u0000and myocardial infarction. Estimating heterogeneous variations in cardiac\u0000motion through B-mode ultrasound imaging is a crucial component of patient\u0000care. Despite the benefits of such imaging techniques, motion estimation\u0000algorithms are susceptible to variability between vendors due to the lack of\u0000benchmark motion quantities. In contrast, finite element (FE) simulations of\u0000cardiac biomechanics leverage well-established constitutive models of the\u0000myocardium to ensure reproducibility. In this study, we developed a methodology\u0000to create synthetic B-mode ultrasound images from FE simulations. The proposed\u0000methodology provides a detailed representation of displacements and strains\u0000under complex mouse-specific loading protocols of the LV. A comparison between\u0000the synthetic images and FE simulations revealed qualitative similarity in\u0000displacement patterns, thereby yielding benchmark quantities to improve the\u0000reproducibility of motion estimation algorithms. Thus, the study provides a\u0000methodology to create an extensive repository of images describing complex\u0000motion patterns to facilitate the enhanced reproducibility of cardiac motion\u0000analysis.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176632","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}
Zhanyue Zhao, Yiwei Jiang, Charles Bales, Yang Wang, Gregory Fischer
Intracorporeal needle-based therapeutic ultrasound (NBTU) offers a minimally invasive approach for the thermal ablation of malignant brain tumors, including both primary and metastatic cancers. NBTU utilizes a high-frequency alternating electric field to excite a piezoelectric transducer, generating acoustic waves that cause localized heating and tumor cell ablation, and it provides a more precise ablation by delivering lower acoustic power doses directly to targeted tumors while sparing surrounding healthy tissue. Building on our previous work, this study introduces a database for optimizing pre-operative surgical planning by simulating ablation effects in varied tissue environments and develops an extended simulation model incorporating various tumor types and sizes to evaluate thermal damage under trans-tissue conditions. A comprehensive database is created from these simulations, detailing critical parameters such as CEM43 isodose maps, temperature changes, thermal dose areas, and maximum ablation distances for four directional probes. This database serves as a valuable resource for future studies, aiding in complex trajectory planning and parameter optimization for NBTU procedures. Moreover, a novel probe selection method is proposed to enhance pre-surgical planning, providing a strategic approach to selecting probes that maximize therapeutic efficiency and minimize ablation time. By avoiding unnecessary thermal propagation and optimizing probe angles, this method has the potential to improve patient outcomes and streamline surgical procedures. Overall, the findings of this study contribute significantly to the field of NBTU, offering a robust framework for enhancing treatment precision and efficacy in clinical settings.
{"title":"Development of Advanced FEM Simulation Technology for Pre-Operative Surgical Planning","authors":"Zhanyue Zhao, Yiwei Jiang, Charles Bales, Yang Wang, Gregory Fischer","doi":"arxiv-2409.03990","DOIUrl":"https://doi.org/arxiv-2409.03990","url":null,"abstract":"Intracorporeal needle-based therapeutic ultrasound (NBTU) offers a minimally\u0000invasive approach for the thermal ablation of malignant brain tumors, including\u0000both primary and metastatic cancers. NBTU utilizes a high-frequency alternating\u0000electric field to excite a piezoelectric transducer, generating acoustic waves\u0000that cause localized heating and tumor cell ablation, and it provides a more\u0000precise ablation by delivering lower acoustic power doses directly to targeted\u0000tumors while sparing surrounding healthy tissue. Building on our previous work,\u0000this study introduces a database for optimizing pre-operative surgical planning\u0000by simulating ablation effects in varied tissue environments and develops an\u0000extended simulation model incorporating various tumor types and sizes to\u0000evaluate thermal damage under trans-tissue conditions. A comprehensive database\u0000is created from these simulations, detailing critical parameters such as CEM43\u0000isodose maps, temperature changes, thermal dose areas, and maximum ablation\u0000distances for four directional probes. This database serves as a valuable\u0000resource for future studies, aiding in complex trajectory planning and\u0000parameter optimization for NBTU procedures. Moreover, a novel probe selection\u0000method is proposed to enhance pre-surgical planning, providing a strategic\u0000approach to selecting probes that maximize therapeutic efficiency and minimize\u0000ablation time. By avoiding unnecessary thermal propagation and optimizing probe\u0000angles, this method has the potential to improve patient outcomes and\u0000streamline surgical procedures. Overall, the findings of this study contribute\u0000significantly to the field of NBTU, offering a robust framework for enhancing\u0000treatment precision and efficacy in clinical settings.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176636","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 review explores the synthesis, characterization, and therapeutic applications of zinc oxide nanoparticles (ZnO NPs) in the treatment of diabetes mellitus. The study delves into both chemical and green synthesis methods, comparing their impacts on nanoparticle properties. Key characterization techniques such as XRD, FTIR, UV-Vis spectroscopy, and SEM confirm the crystalline structure, optical properties, and morphology of the nanoparticles. ZnO NPs demonstrate significant biological activities, including antibacterial, anti-inflammatory, and antidiabetic effects. These nanoparticles show promise in improving glucose regulation, enhancing insulin sensitivity, and boosting glucose uptake in cells. Despite these benefits, the potential toxicity and long-term effects of ZnO NPs warrant further investigation. Future research should focus on optimizing synthesis methods and conducting comprehensive studies to fully exploit ZnO NPs' potential in diabetes management and other biomedical applications.
{"title":"The Current and Future Perspectives of Zinc Oxide Nanoparticles in the Treatment of Diabetes Mellitus","authors":"Iqra Yousaf","doi":"arxiv-2409.04486","DOIUrl":"https://doi.org/arxiv-2409.04486","url":null,"abstract":"This review explores the synthesis, characterization, and therapeutic\u0000applications of zinc oxide nanoparticles (ZnO NPs) in the treatment of diabetes\u0000mellitus. The study delves into both chemical and green synthesis methods,\u0000comparing their impacts on nanoparticle properties. Key characterization\u0000techniques such as XRD, FTIR, UV-Vis spectroscopy, and SEM confirm the\u0000crystalline structure, optical properties, and morphology of the nanoparticles.\u0000ZnO NPs demonstrate significant biological activities, including antibacterial,\u0000anti-inflammatory, and antidiabetic effects. These nanoparticles show promise\u0000in improving glucose regulation, enhancing insulin sensitivity, and boosting\u0000glucose uptake in cells. Despite these benefits, the potential toxicity and\u0000long-term effects of ZnO NPs warrant further investigation. Future research\u0000should focus on optimizing synthesis methods and conducting comprehensive\u0000studies to fully exploit ZnO NPs' potential in diabetes management and other\u0000biomedical applications.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227574","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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