Patient-specific modelling

特定于患者的建模
  • 文章类型: Journal Article
    目的:在数字牙科中越来越需要在颌面部(DMF)计算机断层扫描(CT)或锥形束计算机断层扫描(CBCT)扫描上分割解剖结构。这项研究的主要目的是提出和评估一种名为DentalSegmentator的新型开源工具,用于在DMFCT和CBCT扫描中对五个解剖结构进行全自动分割:上颌骨/上颅骨,下颌骨,上牙,下牙,和下颌管。
    方法:使用470例CT和CBCT扫描的回顾性样本作为训练/验证集。通过比较专家提供的分割和两个固定测试数据集中的自动分割来评估工具的性能和通用性:在正颌手术之前获得的133个CT和CBCT扫描的内部数据集以及从5个机构的常规检查中随机抽样的123个CBCT扫描的外部数据集。
    结果:内部测试数据集(n=133)中的平均总体结果是92.2±6.3%的Dice相似性系数(DSC)和98.2±2.2%的归一化表面距离(NSD)。外部测试数据集(n=123)的平均总体结果是94.2±7.4%的DSC和98.4±3.6%的NSD。
    结论:从这个高度多样化的数据集获得的结果表明,该工具可以为DMFCT和CBCT扫描提供全自动和强大的多类别分割。为鼓励临床部署DentalSegmentator,预训练的nnU-Net模型已与3D切片器软件的扩展一起公开可用。
    结论:DentalSegmentator开源3D切片器扩展提供了一个免费的,健壮,和易于使用的方法从CT和CBCT扫描获得患者特定的三维模型。这些模型在数字牙科工作流程中用于各种目的,比如可视化,治疗计划,干预,和后续行动。
    OBJECTIVE: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evaluate a novel open source tool called DentalSegmentator for fully automatic segmentation of five anatomical structures on DMF CT and CBCT scans: maxilla/upper skull, mandible, upper teeth, lower teeth, and the mandibular canal.
    METHODS: A retrospective sample of 470 CT and CBCT scans was used as a training/validation set. The performance and generalizability of the tool was evaluated by comparing segmentations provided by experts and automatic segmentations in two hold-out test datasets: an internal dataset of 133 CT and CBCT scans acquired before orthognathic surgery and an external dataset of 123 CBCT scans randomly sampled from routine examinations in 5 institutions.
    RESULTS: The mean overall results in the internal test dataset (n = 133) were a Dice similarity coefficient (DSC) of 92.2 ± 6.3 % and a normalised surface distance (NSD) of 98.2 ± 2.2 %. The mean overall results on the external test dataset (n = 123) were a DSC of 94.2 ± 7.4 % and a NSD of 98.4 ± 3.6 %.
    CONCLUSIONS: The results obtained from this highly diverse dataset demonstrate that this tool can provide fully automatic and robust multiclass segmentation for DMF CT and CBCT scans. To encourage the clinical deployment of DentalSegmentator, the pre-trained nnU-Net model has been made publicly available along with an extension for the 3D Slicer software.
    CONCLUSIONS: DentalSegmentator open source 3D Slicer extension provides a free, robust, and easy-to-use approach to obtaining patient-specific three-dimensional models from CT and CBCT scans. These models serve various purposes in a digital dentistry workflow, such as visualization, treatment planning, intervention, and follow-up.
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  • 文章类型: Journal Article
    在过去的几十年中,心脏电生理学的计算模型已经逐渐成熟,现在正在个性化,以提供针对患者的治疗指导,以改善次优的治疗结果。这些个性化电生理模型的预测功能有望提供最佳治疗计划,由于依赖于基于人群或平均患者的方法,目前在临床上受到限制。个性化电生理模型的生成需要一系列步骤,其中一系列激活映射,已经提出了校准方法和治疗模拟管道。然而,可能构成临床相关的硅片治疗的最佳方法仍在研究中,并面临局限性,例如电解剖数据记录的不确定性,在临床时间表内生成和校准模型,并要求验证或基准恢复的组织参数。本文旨在报告心脏计算模型个性化的技术,重点是基于电解剖标测数据校准心脏组织电导率。
    Computational models of cardiac electrophysiology have gradually matured during the past few decades and are now being personalised to provide patient-specific therapy guidance for improving suboptimal treatment outcomes. The predictive features of these personalised electrophysiology models hold the promise of providing optimal treatment planning, which is currently limited in the clinic owing to reliance on a population-based or average patient approach. The generation of a personalised electrophysiology model entails a sequence of steps for which a range of activation mapping, calibration methods and therapy simulation pipelines have been suggested. However, the optimal methods that can potentially constitute a clinically relevant in silico treatment are still being investigated and face limitations, such as uncertainty of electroanatomical data recordings, generation and calibration of models within clinical timelines and requirements to validate or benchmark the recovered tissue parameters. This paper is aimed at reporting techniques on the personalisation of cardiac computational models, with a focus on calibrating cardiac tissue conductivity based on electroanatomical mapping data.
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  • 文章类型: Journal Article
    目的:确定将受益于心脏再同步治疗(CRT)的心力衰竭(HF)患者仍然具有挑战性。我们评估了患者心脏数字孪生(DT)中的虚拟起搏是否可用于预测CRT后左心室(LV)反向重构的程度。
    结果:回顾性纳入45例接受CRT的宽QRS波(≥130ms)和左心室射血分数降低(≤35%)的HF患者。在CRT植入前(基线)和后6个月进行超声心动图检查,以获得LV体积和18段纵向应变。通过根据每位患者的基线测量值个性化CircAdapt模型,使用先前开发的算法生成45个DT。从每个DT,基线间隔到外侧心肌功差异(MWLW-S,DT)和左心室收缩压上升的最大速率(dP/dtmax,DT)得出。然后使用患者特定的房室延迟和导线位置模拟双心室起搏。虚拟起搏引起的变化ΔMWLW-S,DT和ΔdP/dtmax,在6个月的随访中,DT与真实世界的LV收缩末期容积变化(ΔLVESV)相关。DT的基线MWLW-S,DT和虚拟起搏诱导的ΔMWLW-S,DT与真实患者的反向重塑ΔLVESV均显着相关(分别为r=-0.60,P<0.001和r=0.62,P<0.001),而ΔdP/dtmax之间的相关性,DT和ΔLVESV明显较弱(r=-0.34,P=0.02)。
    结论:我们的结果表明,通过DT中的虚拟起搏减少间隔到横向的工作不平衡可以预测真实世界的CRT后LV反向重塑。这种DT方法可以证明是选择用于CRT的HF患者的额外工具,并且有可能在优化CRT递送方面提供有价值的见解。
    OBJECTIVE: Identifying heart failure (HF) patients who will benefit from cardiac resynchronization therapy (CRT) remains challenging. We evaluated whether virtual pacing in a digital twin (DT) of the patient\'s heart could be used to predict the degree of left ventricular (LV) reverse remodelling post-CRT.
    RESULTS: Forty-five HF patients with wide QRS complex (≥130 ms) and reduced LV ejection fraction (≤35%) receiving CRT were retrospectively enrolled. Echocardiography was performed before (baseline) and 6 months after CRT implantation to obtain LV volumes and 18-segment longitudinal strain. A previously developed algorithm was used to generate 45 DTs by personalizing the CircAdapt model to each patient\'s baseline measurements. From each DT, baseline septal-to-lateral myocardial work difference (MWLW-S,DT) and maximum rate of LV systolic pressure rise (dP/dtmax,DT) were derived. Biventricular pacing was then simulated using patient-specific atrioventricular delay and lead location. Virtual pacing-induced changes ΔMWLW-S,DT and ΔdP/dtmax,DT were correlated with real-world LV end-systolic volume change at 6-month follow-up (ΔLVESV). The DT\'s baseline MWLW-S,DT and virtual pacing-induced ΔMWLW-S,DT were both significantly associated with the real patient\'s reverse remodelling ΔLVESV (r = -0.60, P < 0.001 and r = 0.62, P < 0.001, respectively), while correlation between ΔdP/dtmax,DT and ΔLVESV was considerably weaker (r = -0.34, P = 0.02).
    CONCLUSIONS: Our results suggest that the reduction of septal-to-lateral work imbalance by virtual pacing in the DT can predict real-world post-CRT LV reverse remodelling. This DT approach could prove to be an additional tool in selecting HF patients for CRT and has the potential to provide valuable insights in optimization of CRT delivery.
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  • 文章类型: Journal Article
    人工智能(AI)的变革力量正在重塑医学的各个领域。最近的进展,在计算进步的催化下,在妇产科(OBGYN)中看到了人工智能技术的相应采用。我们在三个重点领域探索人工智能的用途和潜力:妊娠并发症的预测建模,基于深度学习的图像解释,用于精确诊断,和大型语言模型启用智能医疗助手。我们还为道德实施提供建议,AI的治理,并促进对人工智能可解释性的研究,对于负责任的AI集成和部署至关重要。AI有望在OBGYN实现个性化医疗保健的革命性时代。
    The transformative power of artificial intelligence (AI) is reshaping diverse domains of medicine. Recent progress, catalyzed by computing advancements, has seen commensurate adoption of AI technologies within obstetrics and gynaecology. We explore the use and potential of AI in three focus areas: predictive modelling for pregnancy complications, Deep learning-based image interpretation for precise diagnoses, and large language models enabling intelligent health care assistants. We also provide recommendations for the ethical implementation, governance of AI, and promote research into AI explainability, which are crucial for responsible AI integration and deployment. AI promises a revolutionary era of personalized health care in obstetrics and gynaecology.
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  • 文章类型: Journal Article
    数据驱动,降序建模在解决与计算和实验血液动力学模型相关的挑战方面显示出了希望。在这项工作中,我们专注于使用降阶模型(ROM)来重建患者特定解剖主动脉中的速度场,目的是将从稳健正确正交分解(RPOD)获得的ROM与从传统正确正交分解(POD)获得的ROM进行比较。POD和RPOD应用于体外,通过粒子图像测速法获取的血液动力学数据,并将分解的流量与从相同几何形状和流量条件下的计算流体动力学(CFD)数据得出的流量进行比较。在这项工作中,PIV和CFD结果可作为临床血液动力学数据的替代,例如MR、有助于证明ROMS在实际临床场景中的潜在用途。使用不同数量的POD模式重建流量,并将整个心动周期获得的流量特征与原始全阶模型(FOM)进行比较。稳健主成分分析(RPCA)RPOD的第一步,已被发现可以提高PIV数据的质量,允许POD以类似于没有测量噪声的数值数据的两种模式捕获流的大部分动能。重建误差沿着心动周期而不同,其中舒张血流需要更多模式以进行准确重建。总的来说,模式1-10足以表示流场。结果表明,前几个POD模式描述了表征这种主动脉夹层血流的相干结构,这表明有可能在低维空间中表示主动脉血流的宏观行为;从而大大简化了问题,并允许计算效率更高的流量模拟或基于机器学习的流量预测,这可以为将此类模型转换为临床铺平道路。
    Data driven, reduced order modelling has shown promise in tackling the challenges associated with computational and experimental haemodynamic models. In this work, we focus on the use of Reduced Order Models (ROMs) to reconstruct velocity fields in a patient-specific dissected aorta, with the objective being to compare the ROMs obtained from Robust Proper Orthogonal Decomposition (RPOD) to those obtained from the traditional Proper Orthogonal Decomposition (POD). POD and RPOD are applied to in vitro, haemodynamic data acquired by Particle Image Velocimetry and compare the decomposed flows to those derived from Computational Fluid Dynamics (CFD) data for the same geometry and flow conditions. In this work, PIV and CFD results act as surrogates for clinical haemodynamic data e.g. MR, helping to demonstrate the potential use of ROMS in real clinical scenarios. The flow is reconstructed using different numbers of POD modes and the flow features obtained throughout the cardiac cycle are compared to the original Full Order Models (FOMs). Robust Principal Component Analysis (RPCA), the first step of RPOD, has been found to enhance the quality of PIV data, allowing POD to capture most of the kinetic energy of the flow in just two modes similar to the numerical data that are free from measurement noise. The reconstruction errors differ along the cardiac cycle with diastolic flows requiring more modes for accurate reconstruction. In general, modes 1-10 are found sufficient to represent the flow field. The results demonstrate that the coherent structures that characterise this aortic dissection flow are described by the first few POD modes suggesting that it is possible to represent the macroscale behaviour of aortic flow in a low-dimensional space; thus significantly simplifying the problem, and allowing for more computationally efficient flow simulations or machine learning based flow predictions that can pave the way for translation of such models to the clinic.
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  • 文章类型: Journal Article
    这项工作提出了一个开源软件管道,用于创建具有纤维取向和纤维蛋白FAULTosis图的患者特定左心房模型。适用于电生理学模拟,并量化模型创建的观察者内部和观察者之间的可重复性。半自动管道以对比增强磁共振血管造影作为输入,和晚期钆增强(LGE)对比磁共振(CMR)。从一组50个CMR数据集中为五个操作员分配了20个案例,以创建总共100个模型来评估操作员之间和内部的变异性。每个输出模型包括:(1)在肺静脉和二尖瓣处开放的标记表面网格,(2)从扩散张量MRI(DTMRI)人类图谱映射的纤维取向,(3)从LGE-CMR扫描中提取的纤维化图,(4)模拟局部激活时间(LAT)和相位奇异性(PS)映射。通过比较输出网格形状的一致性来评估我们管道的可重复性,左心房中的纤维化分布,和纤维取向。通过比较总激活时间,在LAT图中评估了模拟输出的可重复性。和平均传导速度(CV)。将PS图与结构相似性指数度量(SSIM)进行比较。用户总共处理了60个病例,用于处理了60个病例,用于处理了40个病例。我们的工作流程允许在16.72±12.25分钟内创建单个模型。相似性是用形状来衡量的,沿相同方向取向的纤维百分比,和用于纤维化计算的类内相关系数(ICC)。形状仅在用户选择二尖瓣和肺静脉从口到远端的长度方面存在明显差异;纤维化一致性很高,ICC为0.909(内部)和0.999(内部);纤维取向一致性高,分别为60.63%(内部)和71.77%(内部)。LAT表现出良好的协议,其中,对于内部,总激活时间的绝对差的中位数±IQR为2.02±2.45ms,和1.37±2.45ms内。此外,平均CV差异的平均值±SD为-0.00404±0.0155m/s,内部为0.0021±0.0115m/s。最后,PS图在内部和内部的SSIM中显示出适度的一致性,其中,内部和内部的平均±sdSSIM分别为0.648±0.21和0.608±0.15。虽然我们在模型中发现了显著的差异,作为用户输入的结果,我们的测试表明,由操作员之间和内部变异性引起的不确定性与估计纤维引起的不确定性相当,和分割工具的图像分辨率精度。
    This work presents an open-source software pipeline to create patient-specific left atrial models with fibre orientations and a fibrDEFAULTosis map, suitable for electrophysiology simulations, and quantifies the intra and inter observer reproducibility of the model creation. The semi-automatic pipeline takes as input a contrast enhanced magnetic resonance angiogram, and a late gadolinium enhanced (LGE) contrast magnetic resonance (CMR). Five operators were allocated 20 cases each from a set of 50 CMR datasets to create a total of 100 models to evaluate inter and intra-operator variability. Each output model consisted of: (1) a labelled surface mesh open at the pulmonary veins and mitral valve, (2) fibre orientations mapped from a diffusion tensor MRI (DTMRI) human atlas, (3) fibrosis map extracted from the LGE-CMR scan, and (4) simulation of local activation time (LAT) and phase singularity (PS) mapping. Reproducibility in our pipeline was evaluated by comparing agreement in shape of the output meshes, fibrosis distribution in the left atrial body, and fibre orientations. Reproducibility in simulations outputs was evaluated in the LAT maps by comparing the total activation times, and the mean conduction velocity (CV). PS maps were compared with the structural similarity index measure (SSIM). The users processed in total 60 cases for inter and 40 cases for intra-operator variability. Our workflow allows a single model to be created in 16.72 ± 12.25 min. Similarity was measured with shape, percentage of fibres oriented in the same direction, and intra-class correlation coefficient (ICC) for the fibrosis calculation. Shape differed noticeably only with users\' selection of the mitral valve and the length of the pulmonary veins from the ostia to the distal end; fibrosis agreement was high, with ICC of 0.909 (inter) and 0.999 (intra); fibre orientation agreement was high with 60.63% (inter) and 71.77% (intra). The LAT showed good agreement, where the median ± IQR of the absolute difference of the total activation times was 2.02 ± 2.45 ms for inter, and 1.37 ± 2.45 ms for intra. Also, the average ± sd of the mean CV difference was -0.00404 ± 0.0155 m/s for inter, and 0.0021 ± 0.0115 m/s for intra. Finally, the PS maps showed a moderately good agreement in SSIM for inter and intra, where the mean ± sd SSIM for inter and intra were 0.648 ± 0.21 and 0.608 ± 0.15, respectively. Although we found notable differences in the models, as a consequence of user input, our tests show that the uncertainty caused by both inter and intra-operator variability is comparable with uncertainty due to estimated fibres, and image resolution accuracy of segmentation tools.
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  • 文章类型: Published Erratum
    [这修正了文章DOI:10.3389/fphys.202.1042537。].
    [This corrects the article DOI: 10.3389/fphys.2022.1042537.].
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  • 文章类型: Journal Article
    Simulations of cardiac electrophysiology and mechanics have been reported to be sensitive to the microstructural anisotropy of the myocardium. Consequently, a personalized representation of cardiac microstructure is a crucial component of accurate, personalized cardiac biomechanical models. In-vivo cardiac Diffusion Tensor Imaging (cDTI) is a non-invasive magnetic resonance imaging technique capable of probing the heart\'s microstructure. Being a rather novel technique, issues such as low resolution, signal-to noise ratio, and spatial coverage are currently limiting factors. We outline four interpolation techniques with varying degrees of data fidelity, different amounts of smoothing strength, and varying representation error to bridge the gap between the sparse in-vivo data and the model, requiring a 3D representation of microstructure across the myocardium. We provide a workflow to incorporate in-vivo myofiber orientation into a left ventricular model and demonstrate that personalized modelling based on fiber orientations from in-vivo cDTI data is feasible. The interpolation error is correlated with a trend in personalized parameters and simulated physiological parameters, strains, and ventricular twist. This trend in simulation results is consistent across material parameter settings and therefore corresponds to a bias introduced by the interpolation method. This study suggests that using a tensor interpolation approach to personalize microstructure with in-vivo cDTI data, reduces the fiber uncertainty and thereby the bias in the simulation results.
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  • 文章类型: Journal Article
    目的:抗心动过速起搏(ATP)是无痛终止室性心动过速(VT)的可靠电疗法。然而,ATP通常是无效的,特别是对于快速VT。可以通过更靠近驱动VT的凹入电路的优化递送来增强功效。这项研究的目的是比较ATP功效的不同位置相对于折返回路,和进一步优化ATP通过减少失败,通过重新启动。
    结果:在7个梗死猪心室计算模型的队列中诱导了73个持续VT,主要由单个折返途径主导。比较了从折返回路(隔膜)和三个远端位置(左心室外侧/后部)的三个位置递送的爆裂ATP的功效。使用重新启动发作来开发一种算法,该算法利用连续感测的电描记图形态之间的相关性来自动截断ATP脉冲传递。与快速VT相比,抗心动过速起搏在缓慢终止时更有效(65vs.46%,P=0.000039)。对慢速VT的单独分析显示,与近端位置相比,从远端递送时的疗效明显更高(远端72%,近端59%),快速VT被逆转(远端41%,近端51%)。应用我们的早期终止检测算法(ETDA)在79%的重新引发病例中准确检测到VT终止,改善近端递送的总体功效,关键峡部(CI)内部的递送总体上最有效。
    结论:在折返回路附近的抗心动过速起搏递送在终止快速VT时更有效,但VT不那么慢,由于频繁的重新启动。衰减重新开始,通过ETDA,增加所有VT在CI内的递送功效。
    Anti-tachycardia pacing (ATP) is a reliable electrotherapy to painlessly terminate ventricular tachycardia (VT). However, ATP is often ineffective, particularly for fast VTs. The efficacy may be enhanced by optimized delivery closer to the re-entrant circuit driving the VT. This study aims to compare ATP efficacy for different delivery locations with respect to the re-entrant circuit, and further optimize ATP by minimizing failure through re-initiation.
    Seventy-three sustained VTs were induced in a cohort of seven infarcted porcine ventricular computational models, largely dominated by a single re-entrant pathway. The efficacy of burst ATP delivered from three locations proximal to the re-entrant circuit (septum) and three distal locations (lateral/posterior left ventricle) was compared. Re-initiation episodes were used to develop an algorithm utilizing correlations between successive sensed electrogram morphologies to automatically truncate ATP pulse delivery. Anti-tachycardia pacing was more efficacious at terminating slow compared with fast VTs (65 vs. 46%, P = 0.000039). A separate analysis of slow VTs showed that the efficacy was significantly higher when delivered from distal compared with proximal locations (distal 72%, proximal 59%), being reversed for fast VTs (distal 41%, proximal 51%). Application of our early termination detection algorithm (ETDA) accurately detected VT termination in 79% of re-initiated cases, improving the overall efficacy for proximal delivery with delivery inside the critical isthmus (CI) itself being overall most effective.
    Anti-tachycardia pacing delivery proximal to the re-entrant circuit is more effective at terminating fast VTs, but less so slow VTs, due to frequent re-initiation. Attenuating re-initiation, through ETDA, increases the efficacy of delivery within the CI for all VTs.
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  • 文章类型: Journal Article
    在对牙齿及其支撑结构的生物力学行为有了更好的了解之后,在过去的50年中,牙科实践在很大程度上得到了发展。以及成像和生物材料领域的发展。然而,许多患者仍然遇到治疗失败;这与评估每个临床情况的生物力学方面的复杂性质有关,如闭塞和根解剖。并行,锥束计算机断层成像技术的出现使牙本质学领域的研究人员以及临床医生能够使用图像处理和有限元技术以足够的精度收集和建模患者数据。这些发展产生了一种新的精准医学概念,该概念提出了单独评估解剖学和生物力学特征并相应地调整治疗方案。虽然这种方法已经应用于颌面外科,它在牙科中的实施仍然受到限制。然而,人工智能的最新发展使得可以自动化费力的建模任务的几个部分,使这种用户辅助决策支持工具更接近临床医生和研究人员。因此,本叙述性综述旨在介绍和讨论当前研究牙科患者特定模型的文献,其最先进的应用程序,和研究视角。
    The dental practice has largely evolved in the last 50 years following a better understanding of the biomechanical behaviour of teeth and its supporting structures, as well as developments in the fields of imaging and biomaterials. However, many patients still encounter treatment failures; this is related to the complex nature of evaluating the biomechanical aspects of each clinical situation due to the numerous patient-specific parameters, such as occlusion and root anatomy. In parallel, the advent of cone beam computed tomography enabled researchers in the field of odontology as well as clinicians to gather and model patient data with sufficient accuracy using image processing and finite element technologies. These developments gave rise to a new precision medicine concept that proposes to individually assess anatomical and biomechanical characteristics and adapt treatment options accordingly. While this approach is already applied in maxillofacial surgery, its implementation in dentistry is still restricted. However, recent advancements in artificial intelligence make it possible to automate several parts of the laborious modelling task, bringing such user-assisted decision-support tools closer to both clinicians and researchers. Therefore, the present narrative review aimed to present and discuss the current literature investigating patient-specific modelling in dentistry, its state-of-the-art applications, and research perspectives.
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