Lauren M. Zuromski, Jacob Durtschi, Aimal Aziz, Jeffrey Chumley, Mark Dewey, Paul English, Muir Morrison, Keith Simmon, Blaine Whipple, Brendan O'Fallon, David P. Ng
Machine-learning (ML) models in flow cytometry have the potential to reduce error rates, increase reproducibility, and boost the efficiency of clinical labs. While numerous ML models for flow cytometry data have been proposed, few studies have described the clinical deployment of such models. Realizing the potential gains of ML models in clinical labs requires not only an accurate model, but infrastructure for automated inference, error detection, analytics and monitoring, and structured data extraction. Here, we describe an ML model for detection of Acute Myeloid Leukemia (AML), along with the infrastructure supporting clinical implementation. Our infrastructure leverages the resilience and scalability of the cloud for model inference, a Kubernetes-based workflow system that provides model reproducibility and resource management, and a system for extracting structured diagnoses from full-text reports. We also describe our model monitoring and visualization platform, an essential element for ensuring continued model accuracy. Finally, we present a post-deployment analysis of impacts on turn-around time and compare production accuracy to the original validation statistics.
流式细胞仪中的机器学习（ML）模型具有降低错误率、提高可重复性和提高临床实验室效率的潜力。虽然针对流式细胞仪数据提出了许多 ML 模型，但很少有研究描述了此类模型的临床应用。要在临床实验室中实现 ML 模型的潜在收益，不仅需要准确的模型，还需要用于自动推理、错误检测、分析和监控以及结构化数据提取的基础设施。在此，我们介绍了一种用于检测急性髓性白血病（AML）的 ML 模型，以及支持临床实施的基础设施。我们的基础设施利用云的弹性和可扩展性进行模型推理，利用基于 Kubernetes 的工作流系统提供模型的可重复性和资源管理，并利用系统从全文报告中提取结构化诊断结果。我们还介绍了我们的模型监控和可视化平台，这是确保模型持续准确性的重要因素。最后，我们介绍了部署后对周转时间影响的分析，并将生产准确性与最初的验证统计数据进行了比较。
{"title":"Clinical Validation of a Real-Time Machine Learning-based System for the Detection of Acute Myeloid Leukemia by Flow Cytometry","authors":"Lauren M. Zuromski, Jacob Durtschi, Aimal Aziz, Jeffrey Chumley, Mark Dewey, Paul English, Muir Morrison, Keith Simmon, Blaine Whipple, Brendan O'Fallon, David P. Ng","doi":"arxiv-2409.11350","DOIUrl":"https://doi.org/arxiv-2409.11350","url":null,"abstract":"Machine-learning (ML) models in flow cytometry have the potential to reduce\u0000error rates, increase reproducibility, and boost the efficiency of clinical\u0000labs. While numerous ML models for flow cytometry data have been proposed, few\u0000studies have described the clinical deployment of such models. Realizing the\u0000potential gains of ML models in clinical labs requires not only an accurate\u0000model, but infrastructure for automated inference, error detection, analytics\u0000and monitoring, and structured data extraction. Here, we describe an ML model\u0000for detection of Acute Myeloid Leukemia (AML), along with the infrastructure\u0000supporting clinical implementation. Our infrastructure leverages the resilience\u0000and scalability of the cloud for model inference, a Kubernetes-based workflow\u0000system that provides model reproducibility and resource management, and a\u0000system for extracting structured diagnoses from full-text reports. We also\u0000describe our model monitoring and visualization platform, an essential element\u0000for ensuring continued model accuracy. Finally, we present a post-deployment\u0000analysis of impacts on turn-around time and compare production accuracy to the\u0000original validation statistics.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266667","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}
The complexity of gene regulatory networks in multicellular organisms makes interpretable low-dimensional models highly desirable. An attractive geometric picture, attributed to Waddington, visualizes the differentiation of a cell into diverse functional types as gradient flow on a dynamic potential landscape, but it is unclear under what biological constraints this metaphor is mathematically precise. Here, we show that growth-maximizing regulatory strategies that guide a single cell to a target distribution of cell types are described by time-dependent potential landscapes, under certain generic growth-control tradeoffs. Our analysis leads to a sharp bound on the time it takes for a population to grow to a target distribution of a certain size. We show how the framework can be used to compute Waddington-like epigenetic landscapes and growth curves in an illustrative model of growth and differentiation. The theory suggests a conceptual link between nonequilibrium thermodynamics and cellular decision-making during development.
{"title":"Dynamic landscapes and statistical limits on growth during cell fate specification","authors":"Gautam Reddy","doi":"arxiv-2409.09548","DOIUrl":"https://doi.org/arxiv-2409.09548","url":null,"abstract":"The complexity of gene regulatory networks in multicellular organisms makes\u0000interpretable low-dimensional models highly desirable. An attractive geometric\u0000picture, attributed to Waddington, visualizes the differentiation of a cell\u0000into diverse functional types as gradient flow on a dynamic potential\u0000landscape, but it is unclear under what biological constraints this metaphor is\u0000mathematically precise. Here, we show that growth-maximizing regulatory\u0000strategies that guide a single cell to a target distribution of cell types are\u0000described by time-dependent potential landscapes, under certain generic\u0000growth-control tradeoffs. Our analysis leads to a sharp bound on the time it\u0000takes for a population to grow to a target distribution of a certain size. We\u0000show how the framework can be used to compute Waddington-like epigenetic\u0000landscapes and growth curves in an illustrative model of growth and\u0000differentiation. The theory suggests a conceptual link between nonequilibrium\u0000thermodynamics and cellular decision-making during development.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266668","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}
When cell sheets fold during development, their apical or basal surfaces constrict and cell shapes approach the geometric singularity in which these surfaces vanish. Here, we reveal the mechanical consequences of this geometric singularity for tissue folding in a minimal vertex model of an epithelial monolayer. In simulations of the buckling of the epithelium under compression and numerical solutions of the corresponding continuum model, we discover an "unbuckling" bifurcation: At large compression, the buckling amplitude can decrease with increasing compression. By asymptotic solution of the continuum equations, we reveal that this bifurcation comes with a large stiffening of the epithelium. Our results thus provide the mechanical basis for absorption of compressive stresses by tissue folds such as the cephalic furrow during germband extension in Drosophila.
{"title":"(Un)buckling mechanics of epithelial monolayers under compression","authors":"Chandraniva Guha Ray, Pierre A. Haas","doi":"arxiv-2409.07928","DOIUrl":"https://doi.org/arxiv-2409.07928","url":null,"abstract":"When cell sheets fold during development, their apical or basal surfaces\u0000constrict and cell shapes approach the geometric singularity in which these\u0000surfaces vanish. Here, we reveal the mechanical consequences of this geometric\u0000singularity for tissue folding in a minimal vertex model of an epithelial\u0000monolayer. In simulations of the buckling of the epithelium under compression\u0000and numerical solutions of the corresponding continuum model, we discover an\u0000\"unbuckling\" bifurcation: At large compression, the buckling amplitude can\u0000decrease with increasing compression. By asymptotic solution of the continuum\u0000equations, we reveal that this bifurcation comes with a large stiffening of the\u0000epithelium. Our results thus provide the mechanical basis for absorption of\u0000compressive stresses by tissue folds such as the cephalic furrow during\u0000germband extension in Drosophila.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183336","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}
Yuri G. Vilela, Artur C. Fassoni, Armando G. M. Neves
Adaptive therapy is a promising paradigm for treating cancers, that exploits competitive interactions between drug-sensitive and drug-resistant cells, thereby avoiding or delaying treatment failure due to evolution of drug resistance within the tumor. Previous studies have shown the mathematical possibility of building cyclic schemes of drug administration which restore tumor composition to its exact initial value in deterministic models. However, algorithms for cycle design, the conditions on which such algorithms are certain to work, as well as conditions for cycle stability remain elusive. Here, we state biologically motivated hypotheses that guarantee existence of such cycles in two deterministic classes of mathematical models already considered in the literature: Lotka-Volterra and adjusted replicator dynamics. We stress that not only existence of cyclic schemes, but also stability of such cycles is a relevant feature for applications in real clinical scenarios. We also analyze stochastic versions of the above deterministic models, a necessary step if we want to take into account that real tumors are composed by a finite population of cells subject to randomness, a relevant feature in the context of low tumor burden. We argue that the stability of the deterministic cycles is also relevant for the stochastic version of the models. In fact, Dua, Ma and Newton [Cancers (2021)] and Park and Newton [Phys. Rev. E (2023)] observed breakdown of deterministic cycles in a stochastic model (Moran process) for a tumor. Our findings indicate that the breakdown phenomenon is not due to stochasticity itself, but to the deterministic instability inherent in the cycles of the referenced papers. We then illustrate how stable deterministic cycles avoid for very large times the breakdown of cyclic treatments in stochastic tumor models.
适应性疗法是治疗癌症的一种有前途的模式，它利用药物敏感细胞和耐药细胞之间的竞争性相互作用，从而避免或延缓因肿瘤内耐药性演变而导致的治疗失败。以往的研究表明，在数学上可以建立循环给药方案，在确定性模型中将肿瘤成分恢复到精确的初始值。然而，循环设计的算法、这种算法确定有效的条件以及循环稳定性的条件仍然难以捉摸。在这里，我们提出了以生物学为动机的假设，以保证在文献中已经考虑过的两类确定性数学模型中存在这种循环：我们强调，不仅循环方案存在，而且这种循环的稳定性也是实际临床应用的一个相关特征。我们还分析了上述确定性模型的随机版本，如果我们想考虑到真实肿瘤是由受随机性影响的有限细胞群组成，这是一个必要的步骤。我们认为，确定性循环的稳定性也与随机模型有关。事实上，Dua、Ma 和 Newton [Cancers (2021)]以及 Park 和 Newton [Phys. Rev. E (2023)]在肿瘤的随机模型（莫伦过程）中观察到了确定性循环的崩溃。我们的研究结果表明，这种崩溃现象不是由于随机性本身，而是由于参考文献中的循环所固有的确定性不稳定性。然后，我们说明了稳定的确定性循环如何在很大程度上避免随机肿瘤模型循环处理的崩溃。
{"title":"On the design and stability of cancer adaptive therapy cycles: deterministic and stochastic models","authors":"Yuri G. Vilela, Artur C. Fassoni, Armando G. M. Neves","doi":"arxiv-2409.06867","DOIUrl":"https://doi.org/arxiv-2409.06867","url":null,"abstract":"Adaptive therapy is a promising paradigm for treating cancers, that exploits\u0000competitive interactions between drug-sensitive and drug-resistant cells,\u0000thereby avoiding or delaying treatment failure due to evolution of drug\u0000resistance within the tumor. Previous studies have shown the mathematical\u0000possibility of building cyclic schemes of drug administration which restore\u0000tumor composition to its exact initial value in deterministic models. However,\u0000algorithms for cycle design, the conditions on which such algorithms are\u0000certain to work, as well as conditions for cycle stability remain elusive.\u0000Here, we state biologically motivated hypotheses that guarantee existence of\u0000such cycles in two deterministic classes of mathematical models already\u0000considered in the literature: Lotka-Volterra and adjusted replicator dynamics.\u0000We stress that not only existence of cyclic schemes, but also stability of such\u0000cycles is a relevant feature for applications in real clinical scenarios. We\u0000also analyze stochastic versions of the above deterministic models, a necessary\u0000step if we want to take into account that real tumors are composed by a finite\u0000population of cells subject to randomness, a relevant feature in the context of\u0000low tumor burden. We argue that the stability of the deterministic cycles is\u0000also relevant for the stochastic version of the models. In fact, Dua, Ma and\u0000Newton [Cancers (2021)] and Park and Newton [Phys. Rev. E (2023)] observed\u0000breakdown of deterministic cycles in a stochastic model (Moran process) for a\u0000tumor. Our findings indicate that the breakdown phenomenon is not due to\u0000stochasticity itself, but to the deterministic instability inherent in the\u0000cycles of the referenced papers. We then illustrate how stable deterministic\u0000cycles avoid for very large times the breakdown of cyclic treatments in\u0000stochastic tumor models.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"152 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183335","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}
Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schonlieb, Sarah A. Teichmann
Celcomen leverages a mathematical causality framework to disentangle intra- and inter- cellular gene regulation programs in spatial transcriptomics and single-cell data through a generative graph neural network. It can learn gene-gene interactions, as well as generate post-perturbation counterfactual spatial transcriptomics, thereby offering access to experimentally inaccessible samples. We validated its disentanglement, identifiability, and counterfactual prediction capabilities through simulations and in clinically relevant human glioblastoma, human fetal spleen, and mouse lung cancer samples. Celcomen provides the means to model disease and therapy induced changes allowing for new insights into single-cell spatially resolved tissue responses relevant to human health.
{"title":"Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling","authors":"Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schonlieb, Sarah A. Teichmann","doi":"arxiv-2409.05804","DOIUrl":"https://doi.org/arxiv-2409.05804","url":null,"abstract":"Celcomen leverages a mathematical causality framework to disentangle intra-\u0000and inter- cellular gene regulation programs in spatial transcriptomics and\u0000single-cell data through a generative graph neural network. It can learn\u0000gene-gene interactions, as well as generate post-perturbation counterfactual\u0000spatial transcriptomics, thereby offering access to experimentally inaccessible\u0000samples. We validated its disentanglement, identifiability, and counterfactual\u0000prediction capabilities through simulations and in clinically relevant human\u0000glioblastoma, human fetal spleen, and mouse lung cancer samples. Celcomen\u0000provides the means to model disease and therapy induced changes allowing for\u0000new insights into single-cell spatially resolved tissue responses relevant to\u0000human health.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183349","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}
Ornamental fish have various positive effects in human life. Due to the effect and importance of aesthetics and artificial reproduction of these fish, which may be enclosed in aquarium environments and come in contact with cigarette smoke, the effects of tobacco smoke on the gonad tissue of goldfish were investigated. For this purpose, 60 goldfish randomly (weight 100gr) divided in 3 groups and were released in tanks containing 10 liters of water (temperature: 20, hardness: 14 ppt, pH: 7/8). After adaptation, in treatment 1, 1gr of tobacco was heated daily with a direct flame, and the resulting smoke was collected and injected into water with an air pump, in treatment 2, this process was done twice a day. After 3 months, fish gonads tissue were sampled and histopathological slides were investigated. The results showed that in the treatment 2, there were early and immature oocytes in the ovarian tissue in comparison to other groups. Also, in the testes of fish of treatment 2, the reduction of spermatozoids and the higher number of spermatogonia were observed. In the treatment 3, these changes were more. A significant difference between the groups in both female and male was observed at the sexual maturation stages (P<0.001). Based on this study, the dissolution of tobacco smoke can have a negative effect on the process of sexual reproduction and fish exposed to more smoke are more likely to be sterile, and these changes were observed in both males and female.
{"title":"Histopathological study on goldfish (Carassius auratus) gonads exposed to tobacco smoke","authors":"Ali Parsakhanghah","doi":"arxiv-2409.05175","DOIUrl":"https://doi.org/arxiv-2409.05175","url":null,"abstract":"Ornamental fish have various positive effects in human life. Due to the\u0000effect and importance of aesthetics and artificial reproduction of these fish,\u0000which may be enclosed in aquarium environments and come in contact with\u0000cigarette smoke, the effects of tobacco smoke on the gonad tissue of goldfish\u0000were investigated. For this purpose, 60 goldfish randomly (weight 100gr)\u0000divided in 3 groups and were released in tanks containing 10 liters of water\u0000(temperature: 20, hardness: 14 ppt, pH: 7/8). After adaptation, in treatment 1,\u00001gr of tobacco was heated daily with a direct flame, and the resulting smoke\u0000was collected and injected into water with an air pump, in treatment 2, this\u0000process was done twice a day. After 3 months, fish gonads tissue were sampled\u0000and histopathological slides were investigated. The results showed that in the\u0000treatment 2, there were early and immature oocytes in the ovarian tissue in\u0000comparison to other groups. Also, in the testes of fish of treatment 2, the\u0000reduction of spermatozoids and the higher number of spermatogonia were\u0000observed. In the treatment 3, these changes were more. A significant difference\u0000between the groups in both female and male was observed at the sexual\u0000maturation stages (P<0.001). Based on this study, the dissolution of tobacco\u0000smoke can have a negative effect on the process of sexual reproduction and fish\u0000exposed to more smoke are more likely to be sterile, and these changes were\u0000observed in both males and female.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183339","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}
Deep learning models have shown promise in histopathology image analysis, but their opaque decision-making process poses challenges in high-risk medical scenarios. Here we introduce HIPPO, an explainable AI method that interrogates attention-based multiple instance learning (ABMIL) models in computational pathology by generating counterfactual examples through tissue patch modifications in whole slide images. Applying HIPPO to ABMIL models trained to detect breast cancer metastasis reveals that they may overlook small tumors and can be misled by non-tumor tissue, while attention maps$unicode{x2014}$widely used for interpretation$unicode{x2014}$often highlight regions that do not directly influence predictions. By interpreting ABMIL models trained on a prognostic prediction task, HIPPO identified tissue areas with stronger prognostic effects than high-attention regions, which sometimes showed counterintuitive influences on risk scores. These findings demonstrate HIPPO's capacity for comprehensive model evaluation, bias detection, and quantitative hypothesis testing. HIPPO greatly expands the capabilities of explainable AI tools to assess the trustworthy and reliable development, deployment, and regulation of weakly-supervised models in computational pathology.
{"title":"Explainable AI for computational pathology identifies model limitations and tissue biomarkers","authors":"Jakub R. Kaczmarzyk, Joel H. Saltz, Peter K. Koo","doi":"arxiv-2409.03080","DOIUrl":"https://doi.org/arxiv-2409.03080","url":null,"abstract":"Deep learning models have shown promise in histopathology image analysis, but\u0000their opaque decision-making process poses challenges in high-risk medical\u0000scenarios. Here we introduce HIPPO, an explainable AI method that interrogates\u0000attention-based multiple instance learning (ABMIL) models in computational\u0000pathology by generating counterfactual examples through tissue patch\u0000modifications in whole slide images. Applying HIPPO to ABMIL models trained to\u0000detect breast cancer metastasis reveals that they may overlook small tumors and\u0000can be misled by non-tumor tissue, while attention maps$unicode{x2014}$widely\u0000used for interpretation$unicode{x2014}$often highlight regions that do not\u0000directly influence predictions. By interpreting ABMIL models trained on a\u0000prognostic prediction task, HIPPO identified tissue areas with stronger\u0000prognostic effects than high-attention regions, which sometimes showed\u0000counterintuitive influences on risk scores. These findings demonstrate HIPPO's\u0000capacity for comprehensive model evaluation, bias detection, and quantitative\u0000hypothesis testing. HIPPO greatly expands the capabilities of explainable AI\u0000tools to assess the trustworthy and reliable development, deployment, and\u0000regulation of weakly-supervised models in computational pathology.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183350","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 numerous studies on cerebral arterial blood flow, there has not yet been a comprehensive description of hemodynamics in patients undergoing debranching thoracic endovascular aortic repair (dTEVAR), a promising surgical option for aortic arch aneurysms. A phase delay of the flow rate in the left vertebral artery (LVA) in patients after dTEVAR compared to those before was experimentally observed, while the phase in the right vertebral artery (RVA) remained almost the same before and after surgery. Since this surgical intervention included stent graft implantation and extra-anatomical bypass, it was expected that the intracranial hemodynamic changes due to dTEVAR were coupled with fluid flow and pulse waves in cerebral arteries. To clarify this issue, A one-dimensional model (1D) was used to numerically investigate the relative contribution (i.e., local vessel stiffness and flow path changes) of the VA flow rate to the phase difference. The numerical results demonstrated a phase delay of flow rate in the LVA but not the RVA in postoperative patients undergoing dTEVAR relative to preoperative patients. The results further showed that the primary factor affecting the phase delay of the flow rate in the LVA after surgery compared to that before was the bypass, i.e., alteration of flow path, rather than stent grafting, i.e., the change in local vessel stiffness. The numerical results provide insights into hemodynamics in postoperative patients undergoing dTEVAR, as well as knowledge about therapeutic decisions.
{"title":"Phase changes of the flow rate in the vertebral artery caused by debranching thoracic endovascular aortic repair: effects of flow path and local vessel stiffness on vertebral arterial pulsation","authors":"Naoki Takeishia, Li Jialongb, Naoto Yokoyamac, Hisashi Tanakad, Takasumi Gotoe, Shigeo Wada","doi":"arxiv-2409.02476","DOIUrl":"https://doi.org/arxiv-2409.02476","url":null,"abstract":"Despite numerous studies on cerebral arterial blood flow, there has not yet\u0000been a comprehensive description of hemodynamics in patients undergoing\u0000debranching thoracic endovascular aortic repair (dTEVAR), a promising surgical\u0000option for aortic arch aneurysms. A phase delay of the flow rate in the left\u0000vertebral artery (LVA) in patients after dTEVAR compared to those before was\u0000experimentally observed, while the phase in the right vertebral artery (RVA)\u0000remained almost the same before and after surgery. Since this surgical\u0000intervention included stent graft implantation and extra-anatomical bypass, it\u0000was expected that the intracranial hemodynamic changes due to dTEVAR were\u0000coupled with fluid flow and pulse waves in cerebral arteries. To clarify this\u0000issue, A one-dimensional model (1D) was used to numerically investigate the\u0000relative contribution (i.e., local vessel stiffness and flow path changes) of\u0000the VA flow rate to the phase difference. The numerical results demonstrated a\u0000phase delay of flow rate in the LVA but not the RVA in postoperative patients\u0000undergoing dTEVAR relative to preoperative patients. The results further showed\u0000that the primary factor affecting the phase delay of the flow rate in the LVA\u0000after surgery compared to that before was the bypass, i.e., alteration of flow\u0000path, rather than stent grafting, i.e., the change in local vessel stiffness.\u0000The numerical results provide insights into hemodynamics in postoperative\u0000patients undergoing dTEVAR, as well as knowledge about therapeutic decisions.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"388 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183351","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}
Jixin Hou, Zhengwang Wu, Xianyan Chen, Dajiang Zhu, Tianming Liu, Gang Li, Xianqiao Wang
The surface morphology of the developing mammalian brain is crucial for understanding brain function and dysfunction. Computational modeling offers valuable insights into the underlying mechanisms for early brain folding. While previous studies generally assume uniform growth, recent findings indicate significant regional variations in brain tissue growth. However, the role of these variations in cortical development remains unclear. In this study, we explored how regional cortical growth affects brain folding patterns. We first developed growth models for typical cortical regions using ML-assisted symbolic regression, based on longitudinal data from over 1,000 infant MRI scans that captured cortical surface area and thickness during perinatal and postnatal brains development. These models were subsequently integrated into computational software to simulate cortical development with anatomically realistic geometric models. We quantified the resulting folding patterns using metrics such as mean curvature, sulcal depth, and gyrification index. Our results demonstrate that regional growth models generate complex brain folding patterns that more closely match actual brains structures, both quantitatively and qualitatively, compared to uniform growth models. Growth magnitude plays a dominant role in shaping folding patterns, while growth trajectory has a minor influence. Moreover, multi-region models better capture the intricacies of brain folding than single-region models. Our results underscore the necessity and importance of incorporating regional growth heterogeneity into brain folding simulations, which could enhance early diagnosis and treatment of cortical malformations and neurodevelopmental disorders such as epilepsy and autism.
发育中哺乳动物大脑的表面形态对于了解大脑功能和功能障碍至关重要。计算建模为早期大脑折叠的内在机制提供了宝贵的见解。以往的研究通常假定大脑是均匀生长的，但最近的研究结果表明，大脑组织的生长存在明显的区域性差异。然而，这些变化在大脑皮层发育中的作用仍不清楚。在这项研究中，我们探讨了区域性皮质生长如何影响大脑褶皱模式。我们首先利用 ML 辅助符号回归，基于 1000 多例婴儿核磁共振扫描的纵向数据，建立了典型皮质区域的生长模型，这些数据捕捉了围产期和出生后大脑发育过程中皮质的表面积和厚度。这些模型随后被整合到计算软件中，以解剖学上真实的几何模型模拟大脑皮层的发育过程。我们使用平均曲率、沟深度和回旋指数等指标对由此产生的褶皱模式进行了量化。我们的研究结果表明，与均匀生长模型相比，区域生长模型产生的复杂大脑褶皱模式在数量和质量上都更接近实际大脑结构。生长幅度在塑造褶皱模式中起主要作用，而生长轨迹的影响较小。此外，与单区域模型相比，多区域模型能更好地捕捉大脑折叠的复杂性。我们的研究结果凸显了将区域生长异质性纳入大脑折叠模拟的必要性和重要性，这可以提高对皮层畸形和神经发育疾病（如癫痫和自闭症）的早期诊断和治疗。
{"title":"Role of Data-driven Regional Growth Model in Shaping Brain Folding Patterns","authors":"Jixin Hou, Zhengwang Wu, Xianyan Chen, Dajiang Zhu, Tianming Liu, Gang Li, Xianqiao Wang","doi":"arxiv-2408.17334","DOIUrl":"https://doi.org/arxiv-2408.17334","url":null,"abstract":"The surface morphology of the developing mammalian brain is crucial for\u0000understanding brain function and dysfunction. Computational modeling offers\u0000valuable insights into the underlying mechanisms for early brain folding. While\u0000previous studies generally assume uniform growth, recent findings indicate\u0000significant regional variations in brain tissue growth. However, the role of\u0000these variations in cortical development remains unclear. In this study, we\u0000explored how regional cortical growth affects brain folding patterns. We first\u0000developed growth models for typical cortical regions using ML-assisted symbolic\u0000regression, based on longitudinal data from over 1,000 infant MRI scans that\u0000captured cortical surface area and thickness during perinatal and postnatal\u0000brains development. These models were subsequently integrated into\u0000computational software to simulate cortical development with anatomically\u0000realistic geometric models. We quantified the resulting folding patterns using\u0000metrics such as mean curvature, sulcal depth, and gyrification index. Our\u0000results demonstrate that regional growth models generate complex brain folding\u0000patterns that more closely match actual brains structures, both quantitatively\u0000and qualitatively, compared to uniform growth models. Growth magnitude plays a\u0000dominant role in shaping folding patterns, while growth trajectory has a minor\u0000influence. Moreover, multi-region models better capture the intricacies of\u0000brain folding than single-region models. Our results underscore the necessity\u0000and importance of incorporating regional growth heterogeneity into brain\u0000folding simulations, which could enhance early diagnosis and treatment of\u0000cortical malformations and neurodevelopmental disorders such as epilepsy and\u0000autism.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183352","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}
Significance: Cerebral blood flow (CBF) imaging is crucial for diagnosing cerebrovascular diseases. However, existing large neuroimaging techniques with high cost, low sampling rate, and poor mobility make them unsuitable for continuous and longitudinal CBF monitoring at the bedside. Aim: This study aimed to develop a low-cost, portable, programmable scanning diffuse speckle contrast imaging (PS-DSCI) technology for fast, high-density, and depth-sensitive imaging of CBF in rodents. Approach: The PS-DSCI employed a programmable digital micromirror device (DMD) for remote line-shape laser (785 nm) scanning on tissue surface and synchronized a 2D camera for capturing boundary diffuse laser speckle contrasts. New algorithms were developed to address deformations of line-shape scanning, thus minimizing CBF reconstruction artifacts. The PS-DSCI was examined in head-simulating phantoms and adult mice. Results: The PS-DSCI enables resolving Intralipid particle flow contrasts at different tissue depths. In vivo experiments in adult mice demonstrated the capability of PS-DSCI to image global/regional CBF variations induced by 8% CO2 inhalation and transient carotid artery ligations. Conclusions: Compared to conventional point scanning, the line scanning in PS-DSCI significantly increases spatiotemporal resolution. The high sampling rate of PS-DSCI is crucial for capturing rapid CBF changes while high spatial resolution is important for visualizing brain vasculature.
{"title":"Programmable scanning diffuse speckle contrast imaging of cerebral blood flow","authors":"Faezeh Akbari, Xuhui Liu, Fatemeh Hamedi, Mehrana Mohtasebi, Lei Chen, Guoqiang Yu","doi":"arxiv-2408.12715","DOIUrl":"https://doi.org/arxiv-2408.12715","url":null,"abstract":"Significance: Cerebral blood flow (CBF) imaging is crucial for diagnosing\u0000cerebrovascular diseases. However, existing large neuroimaging techniques with\u0000high cost, low sampling rate, and poor mobility make them unsuitable for\u0000continuous and longitudinal CBF monitoring at the bedside. Aim: This study\u0000aimed to develop a low-cost, portable, programmable scanning diffuse speckle\u0000contrast imaging (PS-DSCI) technology for fast, high-density, and\u0000depth-sensitive imaging of CBF in rodents. Approach: The PS-DSCI employed a\u0000programmable digital micromirror device (DMD) for remote line-shape laser (785\u0000nm) scanning on tissue surface and synchronized a 2D camera for capturing\u0000boundary diffuse laser speckle contrasts. New algorithms were developed to\u0000address deformations of line-shape scanning, thus minimizing CBF reconstruction\u0000artifacts. The PS-DSCI was examined in head-simulating phantoms and adult mice.\u0000Results: The PS-DSCI enables resolving Intralipid particle flow contrasts at\u0000different tissue depths. In vivo experiments in adult mice demonstrated the\u0000capability of PS-DSCI to image global/regional CBF variations induced by 8% CO2\u0000inhalation and transient carotid artery ligations. Conclusions: Compared to\u0000conventional point scanning, the line scanning in PS-DSCI significantly\u0000increases spatiotemporal resolution. The high sampling rate of PS-DSCI is\u0000crucial for capturing rapid CBF changes while high spatial resolution is\u0000important for visualizing brain vasculature.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183353","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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