Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma

Magnetic Resonance Materials in Physics, Biology and Medicine - Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI....     

Acute impairment of rat renal function by l-NAME as measured using dynamic MRI

OBJECTIVE: To assess the feasibility of utilizing dynamic contrast enhanced (DCE)-MRI for depicting the effects of N (G)-nitro-L: -arginine methylester (L: -NAME), a nitric oxide synthase (NOS) inhibitor, on glomerular filtration rate (GFR) in rats. Since Gd-DTPA is mainly cleared through the kidneys, a first-order kinetic model was used to estimate GFR based on a clearance index (k ( cl )) that describes the tracer transport rate from the renal cortex to the outer medulla. MATERIALS AND METHODS: Normotensive Sprague-Dawley rats were infused with either vehicle (0.9% NaCl) or one of three doses of L: -NAME (1, 3 or 10 mg/kg) for 30 min prior to imaging. In a separate set of animals, systolic blood pressure (SBP) was measured for all treatment groups. RESULTS: L: -NAME caused a significant increase in SBP at all doses when compared to pre-dose values and at the two highest doses, post-infusion, when compared to vehicle. Administration of L: -NAME also led to dose-dependent changes in the rate of Gd-DTPA uptake and tracer concentrations reached in selected regions of the kidney. The k ( cl ) measurements indicated a significant impairment of GFR following NOS blockade at the highest dose of L: -NAME. CONCLUSION: DCE-MRI method detected changes in GFR in response to NO inhibition with L: -NAME. This non-invasive technique could be used in longitudinal studies in preclinical and clinical settings offering a rapid assessment of single-kidney function.     

Simultaneous dynamic T1 and T2* measurement for AIF assessment combined with DCE MRI in a mouse tumor model

A double-delay SR-MGE-SNAP sequence allowing simultaneous T1 and T2* measurement was developed for integrating arterial input function (AIF) measurement into DCE MRI. Implemented on a 4.7-T animal MR system, this technique was applied to mice with colorectal tumor xenografts. AIF, measured in the mouse heart, was modeled by a bi-exponential function, whereas tumor K(trans) and v(e) parameter maps were obtained from analysis with a two- compartment model using an individually measured AIF. AIF analysis of T2*-corrected data yielded A1 = 9.2 +/- 4.3 kg/l, A(2) = 4.2 +/- 0.8 kg/l, m1 = 2.3 +/- 1.1 min(-1), and m2 = 0.05 +/- 0.02 min(-1). The mean initial plasma concentration C ( p )(t = 0) = 8.0 +/- 2.7 mM was compatible with estimated 8.6 mM. Without T2*-correction distribution phase parameters A1, m1, and C(p)(t = 0) were underestimated. In tumors, neglect of T2* effects yielded mean K(trans) values which were reduced by 14% (P < 0.05), whereas v(e) showed only a slight non-significant reduction. Simultaneous measurement of DeltaR1 and DeltaR2* studied in highly and poorly vascularized and (pre-)necrotic tumor regions revealed complementary behavior of both parameters with respect to vascular properties. In conclusion, the presented measurement technique is a promising tool for dynamic MRI applications studied in animal models at high field strengths and/or with CA of high relaxivities, as it combines classical DCE MRI integrating AIF assessment with dynamic T2* measurement.     

Motion-compensated data decomposition algorithm to accelerate dynamic cardiac MRI

Objectives

In dynamic cardiac magnetic resonance imaging (MRI), the spatiotemporal resolution is often limited by low imaging speed. Compressed sensing (CS) theory can be applied to improve imaging speed and spatiotemporal resolution. The combination of compressed sensing and low-rank matrix completion represents an attractive means to further increase imaging speed. By extending prior work, a Motion-Compensated Data Decomposition (MCDD) algorithm is proposed to improve the performance of CS for accelerated dynamic cardiac MRI.

Materials and methods

The process of MCDD can be described as follows: first, we decompose the dynamic images into a low-rank (L) and a sparse component (S). The L component includes periodic motion in the background, since it is highly correlated among frames, and the S component corresponds to respiratory motion. A motion-estimation/motion-compensation (ME-MC) algorithm is then applied to the low-rank component to reconstruct a cardiac motion compensated dynamic cardiac MRI.

Results

With validations on the numerical phantom and in vivo cardiac MRI data, we demonstrate the utility of the proposed scheme in significantly improving compressed sensing reconstructions by minimizing motion artifacts. The proposed method achieves higher PSNR and lower MSE and HFEN for medium to high acceleration factors.

Conclusion

The proposed method is observed to yield reconstructions with minimal spatiotemporal blurring and motion artifacts in comparison to the existing state-of-the-art methods.

     

Operator dependency of arterial input function in dynamic contrast-enhanced MRI

Objective

To investigate the effect of inter-operator variability in arterial input function (AIF) definition on kinetic parameter estimates (KPEs) from dynamic contrast-enhanced (DCE) MRI in patients with high-grade gliomas.

Methods

The study included 118 DCE series from 23 patients. AIFs were measured by three domain experts (DEs), and a population AIF (pop-AIF) was constructed from the measured AIFs. The DE-AIFs, pop-AIF and AUC-normalized DE-AIFs were used for pharmacokinetic analysis with the extended Tofts model. AIF-dependence of KPEs was assessed by intraclass correlation coefficient (ICC) analysis, and the impact on relative longitudinal change in K^trans was assessed by Fleiss’ kappa (κ).

Results

There was a moderate to substantial agreement (ICC 0.51–0.76) between KPEs when using DE-AIFs, while AUC-normalized AIFs yielded ICC 0.77–0.95 for K^trans, k_ep and v_e and ICC 0.70 for v_p. Inclusion of the pop-AIF did not reduce agreement. Agreement in relative longitudinal change in K^trans was moderate (κ = 0.591) using DE-AIFs, while AUC-normalized AIFs gave substantial (κ = 0.809) agreement.

Discussion

AUC-normalized AIFs can reduce the variation in kinetic parameter results originating from operator input. The pop-AIF presented in this work may be applied in absence of a satisfactory measurement.

     

Effects of bolus injection duration on perfusion estimates in dynamic CT and dynamic susceptibility contrast MRI

Estimates of cerebral blood flow (CBF) and tissue mean transit time (MTT) have been shown to differ between dynamic CT perfusion (CTP) and dynamic susceptibility contrast MRI (DSC-MRI). This study investigates whether these discrepancies regarding CBF and MTT between CTP and DSC-MRI can be attributed to the different injection durations of these techniques. Five subjects were scanned using CTP and DSC-MRI. Region-wise estimates of CBF, MTT, and cerebral blood volume (CBV) were derived based on oscillatory index regularized singular value decomposition. A parametric model that reproduced the shape of measured time curves and characteristics of resulting perfusion parameter estimates was developed and used to simulate data with injection durations typical for CTP and DSC-MRI for a clinically relevant set of perfusion scenarios and noise levels. In simulations, estimates of CBF/MTT showed larger negative/positive bias and increasing variability for CTP when compared to DSC-MRI, especially for high CBF levels. While noise also affected estimates, at clinically relevant levels, the injection duration effect was larger. There are several methodological differences between CTP and DSC-MRI. The results of this study suggest that the injection duration is among those that can explain differences in estimates of CBF and MTT between these bolus tracking techniques.

     

Assessment of neovascular permeability in a pancreatic tumor model using dynamic contrast-enhanced (DCE) MRI with contrast agents of different molecular weights

Object  

We evaluated the relationship of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-derived pharmacokinetic parameters and contrast agents with different molecular weights (MW) in a pancreatic tumor mouse model.     

Enhancing breast tumor detection with near-field imaging

This article outlines the main features of active, passive, and hybrid systems under investigation for breast cancer detection. Our main focus is on active microwave systems, in particular microwave tomography and confocal microwave imaging     

基于动态独立分量分析算法的谐波检测

介绍了一种基于峭度的非高斯极大的动态独立分量分析算法,并将其引入到谐波检测中.该算法在非高斯极大ICA算法的基础上,利用动态的递推关系公式计算得到当前的峭度值,并将峭度的非高斯极大作为独立性判据,从而实现谐波信号的盲分离.为了更好地逼近真实信号,对分离后的信号进行幅值修正,最终完成谐波的检测.仿真实验结果表明了该算法的正确性和可行性.     

磁悬浮式体外凝血功能动态检测传感器

针对传统体外凝血动态检测传感器弹性支撑易疲劳而引起传感器精度降低的关键问题,设计一种基于磁悬浮方式的体外凝血检测新型传感器。根据体外凝血检测传感器工作原理及结构特点,建立传感器内部磁悬浮空间状态数学模型,通过不同相位角的排布对传感器内部结构进行电磁结构仿真,采用有限元数值分析法对相位角与磁感应强度的关系进行分析,优化分析结果并搭建实验测试装置。利用本装置对传感器进行参数标定,验证传感器磁悬浮排布结构设计结果,并通过与标准粘度溶液配套测试与进口仪器进行数据比对。结果表明,本文设计的磁悬浮式体外凝血功能动态检测传感器相位角在20°时产生的内部磁感应强度为1.46e·10;Wb/m,与仿真数据基本吻合,此时传感器的振幅为2.03μm,振动频率为150 Hz,测试数据重复性与相关性分别为0.003、0.994,经过计算传感器精度为0.002 MPa·s。本文设计的凝血功能动态检测传感器精度可以满足体外凝血检测的要求,为改善产品性能方面提供核心技术保障,在提升临床凝血快速检测技术中发挥重要的作用。     

动态场景下的快速目标检测算法

提出了一种动态场景下的目标快速检测算法,基于特征点SURF算法,采用旋转参数模型,结合最小二乘法求解全局运动参数进行运动补偿,最后使用帧差法获得运动目标.采用ORSA的方法去除外点的影响;SURF算法不能满足实时性的需要,针对这一点,提出基于运动预测的特征点匹配算法,提高了匹配的速度和准确率;采用基于残差图像块的更新策...     

基于动态独立分量分析算法的谐波检测

介绍了一种基于峭度的非高斯极大的动态独立分量分析算法,并将其引入到谐波检测中。该算法在非高斯极大ICA算法的基础上,利用动态的递推关系公式计算得到当前的峭度值,并将峭度的非高斯极大作为独立性判据,从而实现谐波信号的盲分离。为了更好地逼近真实信号,对分离后的信号进行幅值修正,最终完成谐波的检测。仿真实验结果表明了该算法的正确性和可行性。     

Precision analysis of kinetic modelling estimates in dynamic contrast enhanced MRI

Object  

Dynamic contrast enhanced MRI and pharmacokinetic modelling provide a powerful tool for tumour diagnosis and treatment evaluation. However, several studies show low reproducibility of the technique and poor precision of the transendothelial transfer constant K ^trans. This work proposes a theoretical framework describing how finite signal-noise-ratio (SNR) in the MR images is propagated throughout the measurement protocol to uncertainty on the kinetic parameter estimates.     

基于谱分解动态散射成像的细胞无标记检测与分类方法

细胞成像及检测技术在医学研究及临床诊断领域具有重要的研究意义和应用价值,而无标记与高通量检测尤其具有挑 战。 本研究基于动态散射理论的细胞成像方法,搭建了动态散射成像系统,提出了基于谱分解的动态信号提取算法,结合机器 学习算法实现了无标记、高通量的细胞分类。 采用血细胞、EG7-OVA 肿瘤细胞、A549 肺癌肿瘤细胞进行实验验证,结果表明本 文提出的方法对血细胞与肿瘤细胞识别准确率可达 98%以上,对于血细胞、EG7-OVA 细胞和 A549 细胞之间的三分类识别率约 为 91%。 本文实现的细胞检测和分类方法具有临床应用前景。     

Absolute cerebral blood flow measured by dynamic susceptibility contrast MRI: a direct comparison with Xe-133 SPECT

Absolute regional cerebral blood flow (CBF) was measured in ten healthy volunteers, using both dynamic susceptibility-contrast (DSC) magnetic resonance imaging (MRI) and Xe-133 SPECT within-4 h. After i.v. injection of Gd-DTPA-BMA (0.3 mmol/kg b.w.), the bolus was monitored with a Simultaneous Dual FLASH pulse sequence (1.5 s image), providing one slice through brain tissue and a second slice through the carotid artery. ConcentrationC(t)x − (1 TE) ln[S(t)/S(0)] was related to CBF asC(t)=CBF [AIF(t)⊗R(t)], where AIF is the arterial input function andR(t) is the residue function. A singular-value-decomposition-based deconvolution technique was used for retrieval ofR(t). Absolute CBF was given by Zierler’s area-to-height relation and the central volume principle. For elimination of large vessels (ELV), all MRI-based CBF values exceeding 2.5 times the mean CBF value of the slice were excluded. A correction for partial-volume effects (CPVE) in the artery used for AIF monitoring was based on registration of signal in a phantom with tubes of various diameters (1.5–6.5 mm), providing an individual concentration correction factor applied to AIF data registered in vivo. In the Xe-133 SPECT investigation, 3000–4000 MBq of Xe-133 was administered intravenously, and CBF was calculated using the Kanno-Lassen algorithm. When ELV and CPVE were applied. DSC-MRI showed average CBF values from the entire slice of 43±10 ml/(min 100 g) (small-artery AIF) and 48±17 ml (min 100 g) (carotid-artery AIF) (mean±S.D.,n=10). The corresponding Xe-133-SPECT-based CBF was 33±6 ml (min 100 g) (n=10). The relationships of CBF(MRI) versus CBF(SPECT) showed good linear correlation (r=0.74–0.83).     

Absolute cerebral blood flow measured by dynamic susceptibility contrast MRI: a direct comparison with Xe-133 SPECT

Absolute regional cerebral blood flow (CBF) was measured in ten healthy volunteers, using both dynamic susceptibility-contrast (DSC) magnetic resonance imaging (MRI) and Xe-133 SPECT within 4 h. After i.v. injection of Gd-DTPA-BMA (0.3 mmol/kg b.w.), the bolus was monitored with a Simultaneous Dual FLASH pulse sequence (1.5 s/image), providing one slice through brain tissue and a second slice through the carotid artery. Concentration C(t) is proportional to -(1/TE) ln[S(t)/S(0)] was related to CBF as C(t) = CBF [AIF(t) x R(t)], where AIF is the arterial input function and R(t) is the residue function. A singular-value-decomposition-based deconvolution technique was used for retrieval of R(t). Absolute CBF was given by Zierler's area-to-height relation and the central volume principle. For elimination of large vessels (ELV), all MRI-based CBF values exceeding 2.5 times the mean CBF value of the slice were excluded. A correction for partial-volume effects (CPVE) in the artery used for AIF monitoring was based on registration of signal in a phantom with tubes of various diameters (1.5-6.5 mm), providing an individual concentration correction factor applied to AIF data registered in vivo. In the Xe-133 SPECT investigation, 3,000-4,000 MBq of Xe-133 was administered intravenously, and CBF was calculated using the Kanno Lassen algorithm. When ELV and CPVE were applied, DSC-MRI showed average CBF values from the entire slice of 43 +/- 10 ml/(min 100 g) (small-artery AIF) and 48 +/- 17 ml/(min 100 g) (carotid-artery AIF) (mean +/- S.D., n = 10). The corresponding Xe-133-SPECT-based CBF was 33 +/- 6 ml/(min 100 g) (n = 10). The relationships of CBF(MRI) versus CBF(SPECT) showed good linear correlation (r = 0.74-0.83).     

A novel framework for evaluating the image accuracy of dynamic MRI and the application on accelerated breast DCE MRI

Objective

To develop a novel framework for evaluating the accuracy of quantitative analysis on dynamic contrast-enhanced (DCE) MRI with a specific combination of imaging technique, scanning parameters, and scanner and software performance and to test this framework with breast DCE MRI with Time-resolved angiography WIth Stochastic Trajectories (TWIST).

Materials and methods

Realistic breast tumor phantoms were 3D printed as cavities and filled with solutions of MR contrast agent. Full k-space raw data of individual tumor phantoms and a uniform background phantom were acquired. DCE raw data were simulated by sorting the raw data according to TWIST view order and scaling the raw data according to the enhancement based on pharmaco-kinetic (PK) models. The measured spatial and temporal characteristics from the images reconstructed using the scanner software were compared with the original PK model (ground truth).

Results

Images could be reconstructed using the manufacturer’s platform with the modified ‘raw data.’ Compared with the ‘ground truth,’ the RMS error in all images was <10% in most cases. With increasing view-sharing acceleration, the error of the initial uptake slope decreased while the error of peak enhancement increased. Deviations of PK parameters varied with the type of enhancement.

Conclusion

A new framework has been developed and tested to more realistically evaluate the quantitative measurement errors caused by a combination of the imaging technique, parameters and scanner and software performance in DCE-MRI.

     

考虑补偿策略的动态电压恢复器补偿量检测方法

电压补偿量的检测是影响动态电压恢复器(DVR)实时性和补偿精度的关键环节。为了进一步提高DVR的补偿性能,针对用户对补偿策略选取的不同,通过引入目标电压函数,提出改进d-q变换法对电压补偿量进行检测。该方法考虑到电压相位跳变、衰减直流分量、谐波和三相不对称等复杂情况的存在,可以对系统电压跌落的起止时刻、跌落幅值和相位跳变角实时检测,并结合补偿策略直接检测出需要的电压补偿量。通过仿真分析对所提方法的正确性及应用于DVR中的有效性进行了验证。     

基于遗传算法的机器人动态视觉检测系统

建立了一种基于二自由度机器人视觉伺服系统,该系统通过实时监控和跟踪运动目标,实现对运动目标的相对距离和瞬时速度的动态检测。本系统为双目视觉系统,采用遗传算法进行特征点匹配,利用其随机搜索的特点,更快更好地找到全局最优值,从而得到较高匹配精度的点。最后通过三维重建和建立速度模型,实现了对机器人动平台运动参数的动态检测,并给出测量精度及改进方法。此方法还适用于多自由度并联机器人和空间复杂运动的检测。     

动态条件下电能表性能检测方法研究*

随着电能表工作环境的不断变化,电能表动态检测方法显得越来越重要。基于电能表测试和检定的基本原理,剖析电能表动态测试的独特之处以及所存在的关键问题,进而提出有效的动态测试方法,为后续动态测试方案的实现奠定理论基础,进一步推动了电能表动态特性测试及检定的标准化和规范化,为彻底摸清电能表动态误差特性、提高其动态误差性能提供了技术指导方向。