{"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":"122 1","pages":""},"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
{"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":"31 1","pages":""},"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
{"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":"150 1","pages":""},"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
{"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":"1 1","pages":""},"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
{"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":"68 1","pages":""},"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
{"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":"132 1","pages":""},"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
{"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":"8 1","pages":""},"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
{"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":"59 1","pages":""},"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
{"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":"44 1","pages":""},"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}
{"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":"1 1","pages":""},"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}