Xin Zhang, Jixiong Xie, Ting Su, Jiongtao Zhu, Han Cui, Yuhang Tan, Dongmei Xia, Hairong Zheng, Dong Liang, Yongshuai Ge
Background: Recently, the popularity of dual-layer flat-panel detector (DL-FPD) based dual-energy cone-beam CT (DE-CBCT) imaging has been increasing. However, the image quality of DE-CBCT remains constrained by the Compton scattered X-ray photons. Purpose: The objective of this study is to develop an energy-modulated scatter correction method for DL-FPD based CBCT imaging. Methods: The DLFPD can measure primary and Compton scattered X-ray photons having dfferent energies: X-ray photons with lower energies are predominantly captured by the top detector layer, while X-ray photons with higher energies are primarily collected by the bottom detector layer. Afterwards, the scattered X-ray signals acquired on both detector layers can be analytically retrieved via a simple model along with several pre-calibrated parameters. Both Monte Carlo simulations and phantom experiments are performed to verify this energy-modulated scatter correction method utilizing DL-FPD. Results: Results demonstrate that the proposed energy-modulated scatter correction method can signficantly reduce the shading artifacts of both low-energy and high-energy CBCT images acquired from DL-FPD. On average, the image non-uniformity is reduce by over 77% in the low-energy CBCT image and by over 66% in the high-energy CBCT image. Moreover, the accuracy of the decomposed multi-material results is also substantially improved. Conclusion: In the future, Compton scattered X-ray signals can be easily corrected for CBCT systems using DL-FPDs.
背景：近来，基于双层平板探测器（DL-FPD）的双能量锥束 CT（DE-CBCT）成像技术日益普及，但 DE-CBCT 的成像质量仍然受到康普顿散射 X 射线光子的制约。目的：本研究旨在为基于 DL-FPD 的 CBCT 成像开发一种能量调制散射校正方法。方法：DLFPD 可以测量不同能量的原生 X 射线光子和康普顿散射 X 射线光子：能量较低的 X 射线光子主要被顶部探测器层捕获，而能量较高的 X 射线光子主要被底部探测器层捕获。之后，可以通过一个简单的模型和几个预先校准的参数，分析检索在两个探测器层上获得的散射 X 射线信号。为了验证这种利用 DL-FPD 的能量调制散射校正方法，我们进行了蒙特卡洛模拟和幻影实验。结果：结果表明，所提出的能量调制散射校正方法可以显著减少从 DL-FPD 采集的低能量和高能量 CBCT 图像的阴影伪影。平均而言，低能量 CBCT 图像的不均匀性降低了 77% 以上，高能量 CBCT 图像的不均匀性降低了 66% 以上。此外，多材料分解结果的准确性也大幅提高。结论未来，使用 DL-FPD 的 CBCT 系统可以轻松校正康普顿散射 X 射线信号。
{"title":"CBCT scatter correction with dual-layer flat-panel detector","authors":"Xin Zhang, Jixiong Xie, Ting Su, Jiongtao Zhu, Han Cui, Yuhang Tan, Dongmei Xia, Hairong Zheng, Dong Liang, Yongshuai Ge","doi":"arxiv-2408.04943","DOIUrl":"https://doi.org/arxiv-2408.04943","url":null,"abstract":"Background: Recently, the popularity of dual-layer flat-panel detector\u0000(DL-FPD) based dual-energy cone-beam CT (DE-CBCT) imaging has been increasing.\u0000However, the image quality of DE-CBCT remains constrained by the Compton\u0000scattered X-ray photons. Purpose: The objective of this study is to develop an energy-modulated\u0000scatter correction method for DL-FPD based CBCT imaging. Methods: The DLFPD can measure primary and Compton scattered X-ray photons\u0000having dfferent energies: X-ray photons with lower energies are predominantly\u0000captured by the top detector layer, while X-ray photons with higher energies\u0000are primarily collected by the bottom detector layer. Afterwards, the scattered\u0000X-ray signals acquired on both detector layers can be analytically retrieved\u0000via a simple model along with several pre-calibrated parameters. Both Monte\u0000Carlo simulations and phantom experiments are performed to verify this\u0000energy-modulated scatter correction method utilizing DL-FPD. Results: Results demonstrate that the proposed energy-modulated scatter\u0000correction method can signficantly reduce the shading artifacts of both\u0000low-energy and high-energy CBCT images acquired from DL-FPD. On average, the\u0000image non-uniformity is reduce by over 77% in the low-energy CBCT image and by\u0000over 66% in the high-energy CBCT image. Moreover, the accuracy of the\u0000decomposed multi-material results is also substantially improved. Conclusion: In the future, Compton scattered X-ray signals can be easily\u0000corrected for CBCT systems using DL-FPDs.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937670","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}
Given rising numbers of bilateral cochlear implant (CI) users, predominantly children, there is a clinical need for efficient and reliable tests that can objectively evaluate binaural hearing. These tests are crucial for guiding the setup of bilateral CIs to optimise delivery of binaural cues. Our primary goal is to introduce a clinical electroencephalogram (EEG) procedure to assess binaural hearing function at various stages within the auditory pathway. Previous research demonstrated that bilateral CI users significantly decrease in ability to discriminate interaural time differences when pulse rates exceed 300 pulses per second. Our paradigm utilizes different pulse rates to objectively explore the limits. A notable challenge with this EEG procedure is the interference induced by CI electrical stimulus artefacts. Despite this obstacle, the potential benefits of CI stimulation artefacts often go unnoticed. This paper outlines positive applications of the frequently criticized CI artefacts for optimizing the experiment setup.
鉴于双侧人工耳蜗（CI）用户的数量不断增加，临床上需要能客观评估双耳听力的高效可靠的测试。这些测试对于指导双侧人工耳蜗的设置以优化双耳线索的传递至关重要。我们的主要目标是引入一种临床脑电图（EEG）程序，在听觉通路的不同阶段评估双耳听力功能。以前的研究表明，当脉冲频率超过每秒 300 个脉冲时，双侧 CI 用户分辨耳间时差的能力会显著下降。我们的范例利用不同的脉冲频率来客观地探索极限。这种 EEG 程序面临的一个显著挑战是 CI 电刺激伪影的干扰。尽管存在这一障碍，但 CI 刺激伪影的潜在益处却经常被忽视。本文概述了经常受到批评的 CI 伪影在优化实验设置方面的积极应用。
{"title":"Exploring the Impact of Cochlear Implant Stimulation Artefacts in EEG Recordings: Unveiling Potential Benefits","authors":"Hongmei Hu, Ben Williges, Deborah Vickers","doi":"arxiv-2408.04429","DOIUrl":"https://doi.org/arxiv-2408.04429","url":null,"abstract":"Given rising numbers of bilateral cochlear implant (CI) users, predominantly\u0000children, there is a clinical need for efficient and reliable tests that can\u0000objectively evaluate binaural hearing. These tests are crucial for guiding the\u0000setup of bilateral CIs to optimise delivery of binaural cues. Our primary goal\u0000is to introduce a clinical electroencephalogram (EEG) procedure to assess\u0000binaural hearing function at various stages within the auditory pathway.\u0000Previous research demonstrated that bilateral CI users significantly decrease\u0000in ability to discriminate interaural time differences when pulse rates exceed\u0000300 pulses per second. Our paradigm utilizes different pulse rates to\u0000objectively explore the limits. A notable challenge with this EEG procedure is\u0000the interference induced by CI electrical stimulus artefacts. Despite this\u0000obstacle, the potential benefits of CI stimulation artefacts often go\u0000unnoticed. This paper outlines positive applications of the frequently\u0000criticized CI artefacts for optimizing the experiment setup.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937812","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}
Despite advancements in lung cancer therapy, the prognosis for advanced or metastatic patients remains poor, yet many patients eventually develop resistance to standard treatments leading to disease progression and poor survival. Here, we described a combination of CAP and nanoparticles (ZrO2 NPs (zirconium oxide nanoparticle) and 3Y-TZP NPs (3% mol Yttria Tetragonal Zirconia Polycrystal Nanoparticle)) for lung cancer therapy. We found that ZrO2 NPs caused obvious damage to the inside of the lung cancer cells. CAP and ZrO2 NPs mainly affected the mitochondria function, leading to a decrease in mitochondrial membrane potential and ATP levels, and causing endoplasmic reticulum stress and cell nucleus internal DNA damage, etc. CAP combined with ZrO2 NPs (CAP@ZrO2) induced lung cancer cell apoptosis by activating the TGF-b{eta} pathway. CAP@ZrO2 offers a new therapy for the clinical treatment of lung cancer.
尽管肺癌治疗取得了进展，但晚期或转移性患者的预后仍然很差，许多患者最终会对标准治疗产生抗药性，导致疾病进展和生存率低下。在此，我们介绍了一种结合 CAP 和纳米粒子（ZrO2 NPs（氧化锆纳米粒子）和 3Y-TZP NPs（3% mol Yttria TetragonalZirconia Polycrystal Nanoparticle））的肺癌治疗方法。我们发现 ZrO2NPs 对肺癌细胞内部造成了明显的损伤。CAP 和 ZrO2NPs 主要影响线粒体功能，导致线粒体膜电位和 ATP 水平下降，引起内质网应激和细胞核内部 DNA 损伤等。CAP与ZrO2 NPs（CAP@ZrO2）通过激活TGF-b{eta}途径诱导肺癌细胞凋亡。CAP@ZrO2为临床治疗肺癌提供了一种新疗法。
{"title":"Cold plasma with zirconia nanoparticles for lung cancer via TGF-b{eta} signaling pathway","authors":"Yueye Huang, Rui Zhang, Xiao Chen, Fei Cao, Qiujie Fang, Qingnan Xu, Shicong Huang, Yufan Wang, Guojun Chen, Zhitong Chen","doi":"arxiv-2408.11838","DOIUrl":"https://doi.org/arxiv-2408.11838","url":null,"abstract":"Despite advancements in lung cancer therapy, the prognosis for advanced or\u0000metastatic patients remains poor, yet many patients eventually develop\u0000resistance to standard treatments leading to disease progression and poor\u0000survival. Here, we described a combination of CAP and nanoparticles (ZrO2 NPs\u0000(zirconium oxide nanoparticle) and 3Y-TZP NPs (3% mol Yttria Tetragonal\u0000Zirconia Polycrystal Nanoparticle)) for lung cancer therapy. We found that ZrO2\u0000NPs caused obvious damage to the inside of the lung cancer cells. CAP and ZrO2\u0000NPs mainly affected the mitochondria function, leading to a decrease in\u0000mitochondrial membrane potential and ATP levels, and causing endoplasmic\u0000reticulum stress and cell nucleus internal DNA damage, etc. CAP combined with\u0000ZrO2 NPs (CAP@ZrO2) induced lung cancer cell apoptosis by activating the\u0000TGF-b{eta} pathway. CAP@ZrO2 offers a new therapy for the clinical treatment\u0000of lung cancer.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223423","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}
Image generative AI has garnered significant attention in recent years. In particular, the diffusion model, a core component of recent generative AI, produces high-quality images with rich diversity. In this study, we propose a novel CT reconstruction method by combining the denoising diffusion probabilistic model with iterative CT reconstruction. In sharp contrast to previous studies, we optimize the fidelity loss of CT reconstruction with respect to the latent variable of the diffusion model, instead of the image and model parameters. To suppress anatomical structure changes produced by the diffusion model, we shallow the diffusion and reverse processes, and fix a set of added noises in the reverse process to make it deterministic during inference. We demonstrate the effectiveness of the proposed method through sparse view CT reconstruction of 1/10 view projection data. Despite the simplicity of the implementation, the proposed method shows the capability of reconstructing high-quality images while preserving the patient's anatomical structure, and outperforms existing methods including iterative reconstruction, iterative reconstruction with total variation, and the diffusion model alone in terms of quantitative indices such as SSIM and PSNR. We also explore further sparse view CT using 1/20 view projection data with the same trained diffusion model. As the number of iterations increases, image quality improvement comparable to that of 1/10 sparse view CT reconstruction is achieved. In principle, the proposed method can be widely applied not only to CT but also to other imaging modalities such as MRI, PET, and SPECT.
{"title":"Iterative CT Reconstruction via Latent Variable Optimization of Shallow Diffusion Models","authors":"Sho Ozaki, Shizuo Kaji, Toshikazu Imae, Kanabu Nawa, Hideomi Yamashita, Keiichi Nakagawa","doi":"arxiv-2408.03156","DOIUrl":"https://doi.org/arxiv-2408.03156","url":null,"abstract":"Image generative AI has garnered significant attention in recent years. In\u0000particular, the diffusion model, a core component of recent generative AI,\u0000produces high-quality images with rich diversity. In this study, we propose a\u0000novel CT reconstruction method by combining the denoising diffusion\u0000probabilistic model with iterative CT reconstruction. In sharp contrast to\u0000previous studies, we optimize the fidelity loss of CT reconstruction with\u0000respect to the latent variable of the diffusion model, instead of the image and\u0000model parameters. To suppress anatomical structure changes produced by the\u0000diffusion model, we shallow the diffusion and reverse processes, and fix a set\u0000of added noises in the reverse process to make it deterministic during\u0000inference. We demonstrate the effectiveness of the proposed method through\u0000sparse view CT reconstruction of 1/10 view projection data. Despite the\u0000simplicity of the implementation, the proposed method shows the capability of\u0000reconstructing high-quality images while preserving the patient's anatomical\u0000structure, and outperforms existing methods including iterative reconstruction,\u0000iterative reconstruction with total variation, and the diffusion model alone in\u0000terms of quantitative indices such as SSIM and PSNR. We also explore further\u0000sparse view CT using 1/20 view projection data with the same trained diffusion\u0000model. As the number of iterations increases, image quality improvement\u0000comparable to that of 1/10 sparse view CT reconstruction is achieved. In\u0000principle, the proposed method can be widely applied not only to CT but also to\u0000other imaging modalities such as MRI, PET, and SPECT.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937814","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}
Personalized federated learning (PFL) for surgical instrument segmentation (SIS) is a promising approach. It enables multiple clinical sites to collaboratively train a series of models in privacy, with each model tailored to the individual distribution of each site. Existing PFL methods rarely consider the personalization of multi-headed self-attention, and do not account for appearance diversity and instrument shape similarity, both inherent in surgical scenes. We thus propose PFedSIS, a novel PFL method with visual trait priors for SIS, incorporating global-personalized disentanglement (GPD), appearance-regulation personalized enhancement (APE), and shape-similarity global enhancement (SGE), to boost SIS performance in each site. GPD represents the first attempt at head-wise assignment for multi-headed self-attention personalization. To preserve the unique appearance representation of each site and gradually leverage the inter-site difference, APE introduces appearance regulation and provides customized layer-wise aggregation solutions via hypernetworks for each site's personalized parameters. The mutual shape information of instruments is maintained and shared via SGE, which enhances the cross-style shape consistency on the image level and computes the shape-similarity contribution of each site on the prediction level for updating the global parameters. PFedSIS outperforms state-of-the-art methods with +1.51% Dice, +2.11% IoU, -2.79 ASSD, -15.55 HD95 performance gains. The corresponding code and models will be released at https://github.com/wzjialang/PFedSIS.
{"title":"Personalizing Federated Instrument Segmentation with Visual Trait Priors in Robotic Surgery","authors":"Jialang Xu, Jiacheng Wang, Lequan Yu, Danail Stoyanov, Yueming Jin, Evangelos B. Mazomenos","doi":"arxiv-2408.03208","DOIUrl":"https://doi.org/arxiv-2408.03208","url":null,"abstract":"Personalized federated learning (PFL) for surgical instrument segmentation\u0000(SIS) is a promising approach. It enables multiple clinical sites to\u0000collaboratively train a series of models in privacy, with each model tailored\u0000to the individual distribution of each site. Existing PFL methods rarely\u0000consider the personalization of multi-headed self-attention, and do not account\u0000for appearance diversity and instrument shape similarity, both inherent in\u0000surgical scenes. We thus propose PFedSIS, a novel PFL method with visual trait\u0000priors for SIS, incorporating global-personalized disentanglement (GPD),\u0000appearance-regulation personalized enhancement (APE), and shape-similarity\u0000global enhancement (SGE), to boost SIS performance in each site. GPD represents\u0000the first attempt at head-wise assignment for multi-headed self-attention\u0000personalization. To preserve the unique appearance representation of each site\u0000and gradually leverage the inter-site difference, APE introduces appearance\u0000regulation and provides customized layer-wise aggregation solutions via\u0000hypernetworks for each site's personalized parameters. The mutual shape\u0000information of instruments is maintained and shared via SGE, which enhances the\u0000cross-style shape consistency on the image level and computes the\u0000shape-similarity contribution of each site on the prediction level for updating\u0000the global parameters. PFedSIS outperforms state-of-the-art methods with +1.51%\u0000Dice, +2.11% IoU, -2.79 ASSD, -15.55 HD95 performance gains. The corresponding\u0000code and models will be released at https://github.com/wzjialang/PFedSIS.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937813","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}
Matthew. J. King, Timon. S. Gutleb, B. E. Treeby, B. T. Cox
We summarise and implement a numerical method for evaluating a numerical method for modelling the frequency dependent power-law absorption within ultrasound using the first order linear wave equations with a loss taking the form of a fractional time derivative. The (Caputo) fractional time derivative requires the full problem history which is contained within an iterative procedure with the resulting numerical method requiring a static memory at across all time steps without loss of accuracy. The Spatial domain is treated by the Fourier k-space method, with derivatives on a uniform grid. Numerically comparisons are made against a model for the same power-law absorption with loss described by the fractional- Laplacian operator. One advantage of the fractional time derivative over the Fractional Laplacian is the local treatment of the power-law, allowing for a spatially varying frequency power-law.
我们总结并实施了一种数值方法，用于评估利用一阶线性波方程模拟超声波内随频率变化的幂律吸收的数值方法，其损失采用分数时间导数形式。卡普托）分数时间导数要求在迭代过程中包含完整的问题历史，由此产生的数值方法要求在不损失精度的情况下在所有时间步长上都有静态记忆。空间域采用傅里叶 k 空间方法处理，在统一网格上进行导数计算。在数值上，与分数拉普拉斯算子描述的相同幂律吸收损失模型进行了比较。与分数拉普拉斯算子相比，分数时间导数的一个优点是对幂律进行了局部处理，允许使用空间变化的频率幂律。
{"title":"Modelling power-law ultrasound absorption using a time-fractional, static memory, Fourier pseudo-spectral method","authors":"Matthew. J. King, Timon. S. Gutleb, B. E. Treeby, B. T. Cox","doi":"arxiv-2408.02541","DOIUrl":"https://doi.org/arxiv-2408.02541","url":null,"abstract":"We summarise and implement a numerical method for evaluating a numerical\u0000method for modelling the frequency dependent power-law absorption within\u0000ultrasound using the first order linear wave equations with a loss taking the\u0000form of a fractional time derivative. The (Caputo) fractional time derivative\u0000requires the full problem history which is contained within an iterative\u0000procedure with the resulting numerical method requiring a static memory at\u0000across all time steps without loss of accuracy. The Spatial domain is treated\u0000by the Fourier k-space method, with derivatives on a uniform grid. Numerically\u0000comparisons are made against a model for the same power-law absorption with\u0000loss described by the fractional- Laplacian operator. One advantage of the\u0000fractional time derivative over the Fractional Laplacian is the local treatment\u0000of the power-law, allowing for a spatially varying frequency power-law.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937815","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}
A unique sample independent 3D self calibration methodology is tested on a unique optical coherence tomography and multi-spectral scanning laser ophthalmoscope (OCT-SLO) hybrid system. Operators visual cognition is replaced by computer vision using the proposed novel fully automatic AI-driven system design. Sample specific automatic contrast adjustment of the beam is achieved on the pre-instructed region of interest. The AI model deduces infrared, fluorescence, and visual spectrum optical alignment by estimating pre-instructed features quantitatively. The tested approach, however, is flexible enough to utilize any apt AI model. Relative comparison with classical signal-to-noise-driven automation is shown to be 200 percent inferior and 130 percent slower than the AI-driven approach. The best spatial resolution of the system is found to be (a) 2.41 microns in glass bead eye phantom, 0.76 with STD 0.46 microns in the mouse retina in the axial direction, and (b) better than 228 line pair per millimeter (lp per mm) or 2 microns for all three spectrums, i.e., 488 nm, 840 nm, and 520 to 550 nm emission in coronal, frontal or x-y plane. Intelligent automation reduces the possibility of developing cold cataracts (especially in mouse imaging) and patient-associated discomfort due to delay during manual alignment by facilitating easy handling for swift ocular imaging and better accuracy. The automatic novel tabletop compact system provides true functional 3D images in three different spectrums for dynamic sample profiles. This is especially useful for photodynamic imaging treatment.
{"title":"Self-calibrating Intelligent OCT-SLO SystemMayank Goswami","authors":"Mayank Goswami","doi":"arxiv-2408.02703","DOIUrl":"https://doi.org/arxiv-2408.02703","url":null,"abstract":"A unique sample independent 3D self calibration methodology is tested on a\u0000unique optical coherence tomography and multi-spectral scanning laser\u0000ophthalmoscope (OCT-SLO) hybrid system. Operators visual cognition is replaced\u0000by computer vision using the proposed novel fully automatic AI-driven system\u0000design. Sample specific automatic contrast adjustment of the beam is achieved\u0000on the pre-instructed region of interest. The AI model deduces infrared,\u0000fluorescence, and visual spectrum optical alignment by estimating\u0000pre-instructed features quantitatively. The tested approach, however, is\u0000flexible enough to utilize any apt AI model. Relative comparison with classical\u0000signal-to-noise-driven automation is shown to be 200 percent inferior and 130\u0000percent slower than the AI-driven approach. The best spatial resolution of the\u0000system is found to be (a) 2.41 microns in glass bead eye phantom, 0.76 with STD\u00000.46 microns in the mouse retina in the axial direction, and (b) better than\u0000228 line pair per millimeter (lp per mm) or 2 microns for all three spectrums,\u0000i.e., 488 nm, 840 nm, and 520 to 550 nm emission in coronal, frontal or x-y\u0000plane. Intelligent automation reduces the possibility of developing cold\u0000cataracts (especially in mouse imaging) and patient-associated discomfort due\u0000to delay during manual alignment by facilitating easy handling for swift ocular\u0000imaging and better accuracy. The automatic novel tabletop compact system\u0000provides true functional 3D images in three different spectrums for dynamic\u0000sample profiles. This is especially useful for photodynamic imaging treatment.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937847","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}
Diwei Shi, Sisi Li, Fan Liu, Xiaoyu Jiang, Lei Wu, Li Chen, Quanshui Zheng, Haihua Bao, Hua Guo, Junzhong Xu
Early assessment of tumor therapeutic response is an important topic in precision medicine to optimize personalized treatment regimens and reduce unnecessary toxicity, cost, and delay. Although diffusion MRI (dMRI) has shown potential to address this need, its predictive accuracy is limited, likely due to its unspecific sensitivity to overall pathological changes. In this work, we propose a new quantitative dMRI-based method dubbed EXCHANGE (MRI of water Exchange, Confined and Hindered diffusion under Arbitrary Gradient waveform Encodings) for simultaneous mapping of cell size, cell density, and transcytolemmal water exchange. Such rich microstructural information comprehensively evaluates tumor pathologies at the cellular level. Validations using numerical simulations and in vitro cell experiments confirmed that the EXCHANGE method can accurately estimate mean cell size, density, and water exchange rate constants. The results from in vivo animal experiments show the potential of EXCHANGE for monitoring tumor treatment response. Finally, the EXCHANGE method was implemented in breast cancer patients with neoadjuvant chemotherapy, demonstrating its feasibility in assessing tumor therapeutic response in clinics. In summary, a new, quantitative dMRI-based EXCHANGE method was proposed to comprehensively characterize tumor microstructural properties at the cellular level, suggesting a unique means to monitor tumor treatment response in clinical practice.
{"title":"Comprehensive characterization of tumor therapeutic response with simultaneous mapping cell size, density, and transcytolemmal water exchange","authors":"Diwei Shi, Sisi Li, Fan Liu, Xiaoyu Jiang, Lei Wu, Li Chen, Quanshui Zheng, Haihua Bao, Hua Guo, Junzhong Xu","doi":"arxiv-2408.01918","DOIUrl":"https://doi.org/arxiv-2408.01918","url":null,"abstract":"Early assessment of tumor therapeutic response is an important topic in\u0000precision medicine to optimize personalized treatment regimens and reduce\u0000unnecessary toxicity, cost, and delay. Although diffusion MRI (dMRI) has shown\u0000potential to address this need, its predictive accuracy is limited, likely due\u0000to its unspecific sensitivity to overall pathological changes. In this work, we\u0000propose a new quantitative dMRI-based method dubbed EXCHANGE (MRI of water\u0000Exchange, Confined and Hindered diffusion under Arbitrary Gradient waveform\u0000Encodings) for simultaneous mapping of cell size, cell density, and\u0000transcytolemmal water exchange. Such rich microstructural information\u0000comprehensively evaluates tumor pathologies at the cellular level. Validations\u0000using numerical simulations and in vitro cell experiments confirmed that the\u0000EXCHANGE method can accurately estimate mean cell size, density, and water\u0000exchange rate constants. The results from in vivo animal experiments show the\u0000potential of EXCHANGE for monitoring tumor treatment response. Finally, the\u0000EXCHANGE method was implemented in breast cancer patients with neoadjuvant\u0000chemotherapy, demonstrating its feasibility in assessing tumor therapeutic\u0000response in clinics. In summary, a new, quantitative dMRI-based EXCHANGE method\u0000was proposed to comprehensively characterize tumor microstructural properties\u0000at the cellular level, suggesting a unique means to monitor tumor treatment\u0000response in clinical practice.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937665","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}
Saisneha Koppaka, David Doan, Wei Cai, Wendy Gu, Sindy K. Y. Tang
Cutting soft materials on the microscale has emerging applications in single-cell studies, tissue microdissection for organoid culture, drug screens, and other analyses. However, the cutting process is complex and remains incompletely understood. Furthermore, precise control over blade geometries, such as the blade tip radius, has been difficult to achieve. In this work, we use the Nanoscribe 3D printer to precisely fabricate micro-blades (i.e., blades <1 mm in length) and blade grid geometries. This fabrication method enables a systematic study of the effect of blade geometry on the indentation cutting of paraffin wax, a common tissue-embedding material. First, we print straight micro-blades with tip radius ranging from ~100 nm to 10 um. The micro-blades are mounted in a custom nanoindentation setup to measure the cutting energy during indentation cutting of paraffin. Cutting energy, measured as the difference in dissipated energy between the first and second loading cycles, decreases as blade tip radius decreases, until ~357 nm when the cutting energy plateaus despite further decrease in tip radius. Second, we expand our method to blades printed in unconventional configurations, including parallel blade structures and blades arranged in a square grid. Under the conditions tested, the cutting energy scales approximately linearly with the total length of the blades comprising the blade structure. The experimental platform described can be extended to investigate other blade geometries and guide the design of microscale cutting of soft materials.
在微尺度上切割软材料在单细胞研究、用于类器官培养的组织显微切割、药物筛选和其他分析中有着新兴的应用。然而，切割过程十分复杂，人们对它的了解还很不够。此外，刀片几何形状（如刀尖半径）的精确控制一直难以实现。在这项工作中，我们使用 Nanoscribe 3D 打印机精确制造微型刀片（即长度小于 1 毫米的刀片）和刀片网格几何形状。通过这种制造方法，我们可以系统地研究刀片几何形状对石蜡（一种常见的组织包埋材料）压痕切割的影响。首先，我们打印出尖端半径在 ~100 nm 到 10 um 之间的直微型刀片。将微型刀片安装在定制的纳米压痕装置中，测量石蜡压痕切割时的切割能量。切割能量是以第一和第二个加载周期之间耗散能量的差值来测量的，随着刀尖半径的减小而减小，直到 ~357 nm 时，尽管刀尖半径进一步减小，切割能量仍然下降。其次，我们将方法扩展到以非常规配置打印的刀片，包括平行刀片结构和以方形网格排列的刀片。在测试条件下，切割能量与构成刀片结构的刀片总长度大致呈线性关系。所述实验平台可扩展用于研究其他刀片几何形状，并指导软材料的微尺度切割设计。
{"title":"Characterization of 3D printed micro-blades for cutting tissue-embedding material","authors":"Saisneha Koppaka, David Doan, Wei Cai, Wendy Gu, Sindy K. Y. Tang","doi":"arxiv-2408.03155","DOIUrl":"https://doi.org/arxiv-2408.03155","url":null,"abstract":"Cutting soft materials on the microscale has emerging applications in\u0000single-cell studies, tissue microdissection for organoid culture, drug screens,\u0000and other analyses. However, the cutting process is complex and remains\u0000incompletely understood. Furthermore, precise control over blade geometries,\u0000such as the blade tip radius, has been difficult to achieve. In this work, we\u0000use the Nanoscribe 3D printer to precisely fabricate micro-blades (i.e., blades\u0000<1 mm in length) and blade grid geometries. This fabrication method enables a\u0000systematic study of the effect of blade geometry on the indentation cutting of\u0000paraffin wax, a common tissue-embedding material. First, we print straight\u0000micro-blades with tip radius ranging from ~100 nm to 10 um. The micro-blades\u0000are mounted in a custom nanoindentation setup to measure the cutting energy\u0000during indentation cutting of paraffin. Cutting energy, measured as the\u0000difference in dissipated energy between the first and second loading cycles,\u0000decreases as blade tip radius decreases, until ~357 nm when the cutting energy\u0000plateaus despite further decrease in tip radius. Second, we expand our method\u0000to blades printed in unconventional configurations, including parallel blade\u0000structures and blades arranged in a square grid. Under the conditions tested,\u0000the cutting energy scales approximately linearly with the total length of the\u0000blades comprising the blade structure. The experimental platform described can\u0000be extended to investigate other blade geometries and guide the design of\u0000microscale cutting of soft materials.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937669","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}
Renato Bellotti, Nicola Bizzocchi, Antony J. Lomax, Andreas Adelmann, Damien C. Weber, Jan Hrbacek
Purpose: Beam angle selection is critical in proton therapy treatment planning, yet automated approaches remain underexplored. This study presents and evaluates GAMBAS, a novel, fast machine learning model for automatic beam angle selection. Methods: The model extracts a predefined set of anatomical features from a patient's CT and structure contours. Using these features, it identifies the most similar patient from a training database and suggests that patient's beam arrangement. A retrospective study with 19 patients was conducted, comparing this model's suggestions to human planners' choices and randomly selected beam arrangements from the training dataset. An expert treatment planner evaluated the plans on quality (scale 1-5), ranked them, and guessed the method used. Results: The number of acceptable (score 4 or 5) plans was comparable between human-chosen 17 (89%) and model-selected 16(84%) beam arrangements. The fully automatic treatment planning took between 4 - 7 min (mean 5 min). Conclusion: The model produces beam arrangements of comparable quality to those chosen by human planners, demonstrating its potential as a fast tool for quality assurance and patient selection, although it is not yet ready for clinical use.
{"title":"GAMBAS -- Fast Beam Arrangement Selection for Proton Therapy using a Nearest Neighbour Model","authors":"Renato Bellotti, Nicola Bizzocchi, Antony J. Lomax, Andreas Adelmann, Damien C. Weber, Jan Hrbacek","doi":"arxiv-2408.01206","DOIUrl":"https://doi.org/arxiv-2408.01206","url":null,"abstract":"Purpose: Beam angle selection is critical in proton therapy treatment\u0000planning, yet automated approaches remain underexplored. This study presents\u0000and evaluates GAMBAS, a novel, fast machine learning model for automatic beam\u0000angle selection. Methods: The model extracts a predefined set of anatomical features from a\u0000patient's CT and structure contours. Using these features, it identifies the\u0000most similar patient from a training database and suggests that patient's beam\u0000arrangement. A retrospective study with 19 patients was conducted, comparing\u0000this model's suggestions to human planners' choices and randomly selected beam\u0000arrangements from the training dataset. An expert treatment planner evaluated\u0000the plans on quality (scale 1-5), ranked them, and guessed the method used. Results: The number of acceptable (score 4 or 5) plans was comparable between\u0000human-chosen 17 (89%) and model-selected 16(84%) beam arrangements. The fully\u0000automatic treatment planning took between 4 - 7 min (mean 5 min). Conclusion: The model produces beam arrangements of comparable quality to\u0000those chosen by human planners, demonstrating its potential as a fast tool for\u0000quality assurance and patient selection, although it is not yet ready for\u0000clinical use.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937667","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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