Uncertainty and bias in contrast concentration measurements using spoiled gradient echo pulse sequences

Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation

OBJECTIVES

Dynamic contrast-enhanced MR images can be analyzed through the application of a wide range of kinetic models. This process is prone to variability and a lack of standardization that can affect the measured metrics. There is a need for customized digital reference objects (DROs) for the validation of DCE-MRI software packages that undertake kinetic model analysis. DROs are currently available only for a small subset of the kinetic models commonly applied to DCE-MRI data. This work aimed to address this gap.

METHODS

Code was written in the MATLAB programming environment to generate customizable DROs. This modular code allows the insertion of a plug-in to describe the kinetic model to be tested. We input our generated DROs into three commercial and open-source analysis packages and assessed the agreement of kinetic model parameter values output with the 'ground-truth' values used in the DRO generation.

RESULTS

For the five kinetic models tested, the concordance correlation coefficient values were >98%, indicating excellent agreement of the results with 'ground-truth'.

CONCLUSIONS

Testing our DROs on three independent software packages produced concordant results, strongly suggesting our DRO generation code is correct. This implies that our DROs can be used to validate other third party software for the kinetic model analysis of DCE-MRI data.

ADVANCES IN KNOWLEDGE

This work extends published work of others to allow customized generation of test objects for any applied kinetic model and allows the incorporation of B1 mapping into the DRO for application at higher field strengths.

GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging

The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories. GRASPnet operates in the image-time space and does not use explicit data consistency to minimize the reconstruction time. Three different network architectures were developed: (1) GRASPnet-2D: 2D convolutional kernels (x,y) and coil and contrast dimensions collapsed into a single combined dimension; (2) GRASPnet-3D: 3D kernels (x,y,t); and (3) GRASPnet-2D + time: two 3D kernels to first exploit spatial correlations (x,y,1) followed by temporal correlations (1,1,t). The networks were trained using iterative GRASP reconstruction as the reference. Free-breathing 3D abdominal imaging with contrast injection was performed on 33 patients with liver lesions using a T1-weighted golden-angle stack-of-stars pulse sequence. Ten datasets were used for testing. The three GRASPnet architectures were compared with iterative GRASP results using quantitative and qualitative analysis, including impressions from two body radiologists. The three GRASPnet techniques reduced the reconstruction time to about 13 s with similar results with respect to iterative GRASP. Among the GRASPnet techniques, GRASPnet-2D + time compared favorably in the quantitative analysis. Spatiotemporal deep learning enables reconstruction of dynamic 4D contrast-enhanced images in a few seconds, which would facilitate translation to clinical practice of compressed sensing methods that are currently limited by long reconstruction times.

Comparison of DCE-MRI parametric mapping using MP2RAGE and variable flip angle T1 mapping

Quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) measures the rate of transfer of contrast agent from the vascular space to the tissue space by fitting signal-time data to pharmacokinetic models. However, these models are very sensitive to errors in T₁ mapping. Accurate T₁ mapping is necessary for high quality quantitative DCE-MRI studies. This study compares magnetization prepared rapid (two) gradient echo sequence (MP2RAGE) T₁-mapping accuracy to the conventional variable flip angle (VFA) approach, and also determines the effect of the new T₁-mapping method on the K^trans parameter. VFA and MP2RAGE T₁ values were compared to the gold standard inverse recovery (IR) method in phantom over manually drawn ROIs. In vivo, ROIs were manually drawn over prostate and prostatic lesions. Average T₁ values over ROIs were compared and K^trans maps for each method were calculated via the extended Tofts model. VFA-T₁ maps overestimated T₁ values by up to 50% compared to gold standard IR T₁ values in phantom. MP2RAGE differed by up to 9%. MP2RAGE-T₁ and K^trans values were significantly different from VFA values over prostatic lesions (p < 0.05). K^trans was consistently underestimated using VFA compared to MP2RAGE (p < 0.05). MP2RAGE T₁ maps are shown to be more accurate, leading to more reliable pharmacokinetic modeling. This can potentially lead to better lesion characterization and improve clinical outcomes.

Endothelial cell death after ionizing radiation does not impair vascular structure in mouse tumor models

The effect of radiation therapy on tumor vasculature has long been a subject of debate. Increased oxygenation and perfusion have been documented during radiation therapy. Conversely, apoptosis of endothelial cells in irradiated tumors has been proposed as a major contributor to tumor control. To examine these contradictions, we use multiphoton microscopy in two murine tumor models: MC38, a highly vascularized, and B16F10, a moderately vascularized model, grown in transgenic mice with tdTomato-labeled endothelium before and after a single (15 Gy) or fractionated (5 × 3 Gy) dose of radiation. Unexpectedly, even these high doses lead to little structural change of the perfused vasculature. Conversely, non-perfused vessels and blind ends are substantially impaired after radiation accompanied by apoptosis and reduced proliferation of their endothelium. RNAseq analysis of tumor endothelial cells confirms the modification of gene expression in apoptotic and cell cycle regulation pathways after irradiation. Therefore, we conclude that apoptosis of tumor endothelial cells after radiation does not impair vascular structure.

Longitudinal Correlations Between Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced (DCE) MRI During Radiotherapy in Prostate Cancer Patients

Purpose

Intravoxel incoherent motion (IVIM) is a promising technique that can acquire perfusion information without the use of contrast agent, contrary to the more established dynamic contrast-enhanced (DCE) technique. This is of interest for treatment response monitoring, where patients can be imaged on each treatment fraction. In this study, longitudinal correlations between IVIM- and DCE parameters were assessed in prostate cancer patients receiving radiation treatment.

Materials and Methods

20 prostate cancer patients were treated on a 1.5 T MR-linac with 20 x 3 or 3.1 Gy. Weekly IVIM and DCE scans were acquired. Tumors, the peripheral zone (PZ), and the transition zone (TZ) were delineated on a T₂-weighted scan acquired on the first fraction. IVIM and DCE scans were registered to this scan and the delineations were propagated. Median values from these delineations were used for further analysis. The IVIM parameters D, f, D^* and the product fD^* were calculated. The Tofts model was used to calculate the DCE parameters K^trans, k_ep and v_e. Pearson correlations were calculated for the IVIM and DCE parameters on values from the first fraction for each region of interest (ROI). For longitudinal analysis, the repeated measures correlation coefficient was used to determine correlations between IVIM and DCE parameters in each ROI.

Results

When averaging over patients, an increase during treatment in all IVIM and DCE parameters was observed in all ROIs, except for D in the PZ and TZ. No significant Pearson correlations were found between any pair of IVIM and DCE parameters measured on the first fraction. Significant but low longitudinal correlations were found for some combinations of IVIM and DCE parameters in the PZ and TZ, while no significant longitudinal correlations were found in the tumor. Notably in the TZ, for both f and fD^*, significant longitudinal correlations with all DCE parameters were found.

Conclusions

The increase in IVIM- and DCE parameters when averaging over patients indicates a measurable response to radiation treatment with both techniques. Although low, significant longitudinal correlations were found which suggests that IVIM could potentially be used as an alternative to DCE for treatment response monitoring.

Gadolinium Retention in the Brain of Mother and Pup Mouse: Effect of Pregnancy and Repeated Administration of Gadolinium‐Based Contrast Agents

Background

The association of repeated administration of gadolinium‐based contrast agents (GBCAs) with the gadolinium (Gd) retention in the brains of mother and fetus remains unclear.

Purpose

To investigate the effects of pregnancy and repeated administration of GBCAs on Gd retention in the brains of mother and pup mice.

Study type

Cross‐sectional cohort toxicity study.

Animal Model

From gestational days 16–19, pregnant (n = 48) BALB/c mice.

Field Strength

A 9.4 T and fast spin echo sequence.

Assessment

Half of the mother mice (n = 24) were killed at postnatal day 1 (P1) for inductively coupled plasma mass spectrometry (ICP‐MS) and transmission electron microscopy (TEM). Besides the ICP‐MS and TEM, four pups were randomly selected from each mother and killed at P1 for ultraperformance liquid chromatography mass spectrometry (UPLC‐MS) and Nissl staining.

Statistical Tests

One‐way analysis of variance and unpaired t‐test.

Results

In the group of gadodiamide, retention of Gd in the brains of pregnant mice was significantly lower than that of nonpregnant mice in the area of the deep cerebellar nuclei (DCN) (10.35 ± 2.16 nmol/g vs. 18.74 ± 3.65 nmol/g). Retention of Gd in the DCN of pups whose mothers were administered gadoterate meglumine was significantly lower than that of pups whose mothers were administered gadodiamide (0.21 ± 0.09 nmol/g vs. 6.15 ± 3.21 nmol/g) at P1. In mice treated with gadodiamide, most of the retained Gd in the brain tissue was insoluble (19.5% ± 9.5% of the recovered amount corresponded to the intact complex in the DCN).

Data Conclusion

In different brain areas of the mother and pup mice, the retention of Gd after gadoterate meglumine administration was lower than that of gadodiamide and gadopentetate dimeglumine administration, and almost all the detected Gd in pups' brains was intact soluble GBCAs.

Evidence Level

1

Technical Efficacy

Stage 2

Radiomic combination of spatial and temporal features extracted from DCE-MRI for prostate cancer detection. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:3153-3156. [PMID: 34891910 DOI: 10.1109/embc46164.2021.9630015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Multi-parametric MRI is part of the standard prostate cancer (PCa) diagnostic protocol. Recent imaging guidelines (PI-RADS v2) downgraded the value of Dynamic Contrast-Enhanced (DCE)-MRI in the diagnosis of PCa. A purely qualitative analysis of the DCE-MRI time series, as it is generally done by radiologists, might indeed overlook information on the microvascular architecture and function. In this study, we investigate the discriminative power of quantitative imaging features derived from texture and pharmacokinetic analysis of DCE-MRI. In 605 regions of interest (benign and malignant tissue) delineated in 80 patients, we found through independent cross-validation that a subset of quantitative spatial and temporal features extracted from DCE-MRI and incorporated in machine learning classifiers obtains a good diagnostic performance (AUC = 0.80-0.86) in distinguishing malignant from benign regions.Clinical Relevance- These findings highlight the underlying potential of quantitative DCE-derived radiomic features in identifying PCa by MRI.

Quantitative Imaging of Blood-Brain Barrier Permeability Following Repetitive Mild Head Impacts

This was an exploratory study designed to evaluate the feasibility of a recently established imaging modality, quantitative ultrashort time-to-echo contrast enhanced (QUTE-CE), to follow the early pathology and vulnerability of the blood brain barrier in response to single and repetitive mild head impacts. A closed-head, momentum exchange model was used to produce three consecutive mild head impacts aimed at the forebrain separated by 24 h each. Animals were measured at baseline and within 1 h of impact. Anatomical images were collected to assess the extent of structural damage. QUTE-CE biomarkers for BBB permeability were calculated on 420,000 voxels in the brain and were registered to a bilateral 3D brain atlas providing site-specific information on 118 anatomical regions. Blood brain barrier permeability was confirmed by extravasation of labeled dextran. All head impacts occurred in the absence of any structural brain damage. A single mild head impact had measurable effects on blood brain barrier permeability and was more significant after the second and third impacts. Affected regions included the prefrontal ctx, basal ganglia, hippocampus, amygdala, and brainstem. Our findings support the concerns raised by the healthcare community regarding mild head injuries in participants in organized contact sports and military personnel in basic training and combat.

DCE-MRI quantitative transport mapping for noninvasively detecting hypoxia inducible factor-1α, epidermal growth factor receptor overexpression, and Ki-67 in nasopharyngeal carcinoma patients

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has the potential to noninvasively detect expression of hypoxia inducible factor-1-alpha (HIF-1α), epidermal growth factor receptor (EGFR), and Ki-67 in nasopharyngeal carcinoma (NPC) by quantitatively measuring tumor blood flow, vascularity, and permeability.

PURPOSE

We aim to explore the utility of DCE-MRI in detecting HIF-1α, EGFR, and Ki-67 expression levels using traditional Kety's/Tofts' modeling and quantitative transport mapping (QTM).

MATERIALS AND METHODS

Eighty-nine NPC patients underwent DCE-MRI before treatment were enrolled. DCE-MRI was processed to generate the following kinetic parameters: |u| and D from the QTM model, tumor blood flow (TBF) from Kety's model, and K^trans, V_e, and K_ep from Tofts' model. Pretreatment levels of HIF-1α, EGFR, and Ki-67 were assessed by immunohistochemistry and classified into low and high expression groups.

RESULTS

|u| (p < 0.001) and TBF (p = 0.015) values were significantly higher in the HIF-1α high-expression group compared to low-expression group. Only K^trans (p = 0.016) was significantly higher in the EGFR high-expression group. Only |u| (p < 0.001) values were significantly higher in the Ki-67 high-expression group compared to low-expression group. Multiple linear regression analyses showed that |u| independently correlated with HIF-1α and Ki-67 expression, and K^trans independently correlated with EGFR. The areas under the ROC curves of |u| for HIF-1α and Ki-67, and K^trans for EGFR were 0.83, 0.74, and 0.70, respectively.

CONCLUSION

|u| and K^trans derived from DCE-MRI may be considered as noninvasive imaging markers for detecting hypoxia and proliferation in NPC patients.

Dynamic contrast enhanced magnetic resonance imaging: A review of its application in the assessment of placental function

It is important to develop a better understanding of placental insufficiency given its role in common maternofetal complications such as preeclampsia and fetal growth restriction. Functional magnetic resonance imaging offers unprecedented techniques for exploring the placenta under both normal and pathological physiological conditions. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is an established and very robust method to investigate the microcirculatory parameters of an organ and more specifically its perfusion. It is currently a gold standard in the physiological and circulatory evaluation of an organ. Its application to the human placenta could enable to access many microcirculatory parameters relevant to the placental function such as organ blood flow, fractional blood volume, and permeability surface area, by the acquisition of serial images, before, during, and after administration of an intravenous contrast agent. Widely used in animal models with gadolinium-based contrast agents, its application to the human placenta could be possible if the safety of contrast agents in pregnancy is established or they are confirmed to not cross the placenta.

Tumour irradiation combined with vascular-targeted photodynamic therapy enhances antitumour effects in pre-clinical prostate cancer

BACKGROUND

There is a need to improve the treatment of prostate cancer (PCa) and reduce treatment side effects. Vascular-targeted photodynamic therapy (VTP) is a focal therapy for low-risk low-volume localised PCa, which rapidly disrupts targeted tumour vessels. There is interest in expanding the use of VTP to higher-risk disease. Tumour vasculature is characterised by vessel immaturity, increased permeability, aberrant branching and inefficient flow. FRT alters the tumour microenvironment and promotes transient 'vascular normalisation'. We hypothesised that multimodality therapy combining fractionated radiotherapy (FRT) and VTP could improve PCa tumour control compared against monotherapy with FRT or VTP.

METHODS

We investigated whether sequential delivery of FRT followed by VTP 7 days later improves flank TRAMP-C1 PCa tumour allograft control compared to monotherapy with FRT or VTP.

RESULTS

FRT induced 'vascular normalisation' changes in PCa flank tumour allografts, improving vascular function as demonstrated using dynamic contrast-enhanced magnetic resonance imaging. FRT followed by VTP significantly delayed tumour growth in flank PCa allograft pre-clinical models, compared with monotherapy with FRT or VTP, and improved overall survival.

CONCLUSION

Combining FRT and VTP may be a promising multimodal approach in PCa therapy. This provides proof-of-concept for this multimodality treatment to inform early phase clinical trials.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats

Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (K_m,u) of gadoxetate was 106 μM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.

Robust arterial input function surrogate measurement from the superior sagittal sinus complex signal for fast dynamic contrast-enhanced MRI in the brain

PURPOSE

Accurately estimating the arterial input function for dynamic contrast-enhanced MRI is challenging. An arterial input function is typically determined from signal magnitude changes related to a contrast agent, often leading to underestimation of peak concentrations. Alternatively, signal phase recovers the accurate peak concentration for straight vessels but suffers from high noise. A recent method proposed to fit the signal in the complex plane by combining the advantages of the previous 2 methods. The purpose of this work is to refine this complex-based method to determine the venous output function (VOF), an arterial input function surrogate, from the superior sagittal sinus.

METHODS

We propose a state-of-the-art complex-based method that includes direct compensation for blood inflow and signal phase correction accounting for the curvature of the superior sagittal sinus, generally assumed collinear with B₀ . We compared the magnitude-, phase-, and complex-based VOF determination methods against various simulated biases as well as for 29 brain metastases patients.

RESULTS

Angulation of the superior sagittal sinus relative to B₀ varied widely within patients, and its effect on the signal phase caused an underestimation of peak concentrations of up to 65%. Correction significantly increased the VOF peak concentration for the phase- and complex-based VOFs in the cohort. The phase-based method recovered accurate peak concentrations but lacked precision in the tail of the VOF. Our complex-based VOF completely recovered the effect of inflow and resulted in a high-peak concentration with limited noise.

CONCLUSION

The new complex-based method resulted in high-quality VOF robust against superior sagittal sinus curvature and variations in patient positioning.

Ferumoxytol-enhanced ultrashort TE MRA and quantitative morphometry of the human kidney vasculature

PURPOSE

To evaluate the feasibility of Quantitative Ultrashort-Time-to-Echo Contrast-Enhanced (QUTE-CE) MRA using ferumoxytol as a contrast agent for abdominal angiography in the kidney.

METHODS

Four subjects underwent ferumoxytol-enhanced MRA with the 3D UTE Spiral VIBE WIP sequence at 3 T. Image quality metrics were quantified, specifically the blood Signal-to-Noise Ratio (SNR), blood-tissue Contrast-to-Noise Ratio (CNR) and Intraluminal Signal Heterogeneity (ISH) from both the aorta and inferior vena cava (IVC). Morphometric analysis of the vessels was performed using manual approach and semi-automatic approach using Vascular Modeling ToolKit (VMTK). Image quality and branching order were compared between QUTE-CE MRA and the Gadolinium (Gd) CEMRA reference image.

RESULTS

QUTE-CE MRA provides a bright blood snapshot that delineates arteries and veins equally in the same scan. The maximum SNR and CNR values were 3,282 ± 1,218 and 1,295 ± 580, respectively - significantly higher than available literature values using other CEMRA techniques. QUTE-CE MRA had lower ISH and depicted higher vessel branching order (7th vs 3rd) within the kidney compared to a standard dynamic clinical Gd CEMRA scan. Morphometric analysis yielded quantitative results for the total kidney volume, total cyst volume and for diameters of the branching arterial network down to the 7^th branch. Vessel curvature was significantly increased (p < 0.001) in the presence of a renal cyst compared to equivalent vessels in normal kidney regions.

CONCLUSION

QUTE-CE MRA is feasible for kidney angiography, providing greater detail of kidney vasculature, enabling quantitative morphometric analysis of the abdominal and intra-renal vessels and yielding metrics relevant to vascular diseases while using a contrast agent ferumoxytol that is safe for CKD patients.

Clinical Study of Ultrasonic Extreme Velocity Imaging Pulse Wave Technique in Carotid Elasticity in Patients with Type II Diabetes Mellitus

In this study, extreme velocity ultrasonic imaging pulse wave technology was used to detect the main indices of atherosclerosis such as carotid intima-media thickness (IMT) and carotid elasticity, and biochemical indices such as glycated hemoglobin, blood glucose and blood lipids in one hundred twenty 18–60-year-old patients with type II diabetes mellitus (T2DM) and 120 healthy controls. We analyzed the correlations between carotid elasticity, carotid IMT, and a range of biochemical indices. The results indicated that when the carotid IMT in young and middle-aged patients with T2DM was within the normal range (0.56±0.03 mm), the carotid artery elasticity was abnormal [Pulse wave propagation velocity (PWV)-BS = 7.69± 1.26 m/s; PWV-ES = 8.34±1.51 m/s; P < 0.05]. Additionally, PWV-BS was positively correlated with age, course of the disease, glycated hemoglobin (HbA1c), and fasting blood glucose (FBG) (r = 0.297, 0.377, 0.369, 0.382), and PWV-ES was positively correlated with age, course of the disease, HbA1c, and FBG (r = 0.318, 0.386, 0.392, 0.339). This finding provides a basis for extreme velocity ultrasonic imaging pulse wave technology to become a new method for the early screening of atherosclerosis in patients with T2DM; this is important for timely clinical intervention in patients with T2DM.

MRI Mapping of Renal T1: Basic Concept

In renal MRI, measurement of the T₁ relaxation time of water molecules may provide a valuable biomarker for a variety of pathological conditions. Due to its sensitivity to the tissue microenvironment, T₁ has gained substantial interest for noninvasive imaging of renal pathology, including inflammation and fibrosis. In this chapter, we will discuss the basic concept of T₁ mapping and different T₁ measurement techniques and we will provide an overview of emerging preclinical applications of T₁ for imaging of kidney disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Impact of aerobic exercise on cognitive function in patients with schizophrenia during daily nursing: A protocol for systematic review and meta-analysis

OBJECTIVES

To assess the effect of aerobic exercise (AE) on cognition function in people with schizophrenia (SZ) during daily nursing.

METHODS

The literature search will be conducted via PubMed, Embase, Cochrane Library, and Web of Science. Weighted mean difference (WMD) or standardized mean difference (SMD) and 95% confidence intervals (CIs) will be adopted to calculate the association between AE and cognitive function in patients with SZ. Publication bias will be performed by Begg test. When there is publication bias, "cut-and-fill method" will be adopted to adjust publication bias. Sensitivity analysis will be used to test the stability of the result. When the heterogeneity is large (I2 ≥ 50%), meta regression will be used to explore the source of inter-study heterogeneity. When the heterogeneity is large (I2 ≥ 50%) and the results are statistically significant (P < .05), age, sex, duration of disease, duration of intervention, amount of exercise per week, improvement of cardiopulmonary health, and other factors will be sub-analyzed.

CONCLUSION

This meta-analysis will evaluate the impact of aerobic exercise on cognitive function in patients with SZ during daily nursing on the basis of existing evidence.

OSF REGISTRATION NUMBER

10.17605/OSF.IO/C8ABX.

Bayesian non-linear regression with spatial priors for noise reduction and error estimation in quantitative MRI with an application in T1 estimation

PURPOSE

To develop a method that can reduce and estimate uncertainty in quantitative MR parameter maps without the need for hand-tuning of any hyperparameters.

METHODS

We present an estimation method where uncertainties are reduced by incorporating information on spatial correlations between neighbouring voxels. The method is based on a Bayesian hierarchical non-linear regression model, where the parameters of interest are sampled, using Markov chain Monte Carlo (MCMC), from a high-dimensional posterior distribution with a spatial prior. The degree to which the prior affects the model is determined by an automatic hyperparameter search using an information criterion and is, therefore, free from manual user-dependent tuning. The samples obtained further provide a convenient means to obtain uncertainties in both voxels and regions. The developed method was evaluated on T ₁ estimations based on the variable flip angle method.

RESULTS

The proposed method delivers noise-reduced T ₁ parameter maps with associated error estimates by combining MCMC sampling, the widely applicable information criterion, and total variation-based denoising. The proposed method results in an overall decrease in estimation error when compared to conventional voxel-wise maximum likelihood estimation. However, this comes with an increased bias in some regions, predominately at tissue interfaces, as well as an increase in computational time.

CONCLUSIONS

This study provides a method that generates more precise estimates compared to the conventional method, without incorporating user subjectivity, and with the added benefit of uncertainty estimation.

Whole-heart, ungated, free-breathing, cardiac-phase-resolved myocardial perfusion MRI by using Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state (CRIMP)

PURPOSE

To develop a whole-heart, free-breathing, non-electrocardiograph (ECG)-gated, cardiac-phase-resolved myocardial perfusion MRI framework (CRIMP; Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state) and test its quantification feasibility.

METHODS

CRIMP used interleaved radial simultaneous multi-slice (SMS) slice groups to cover the whole heart in 9 or 12 short-axis slices. The sequence continuously acquired data without magnetization preparation, ECG gating or breath-holding, and captured multiple cardiac phases. Images were reconstructed by a motion-compensated patch-based locally low-rank reconstruction. Bloch simulations were performed to study the signal-to-noise ratio/contrast-to-noise ratio (SNR/CNR) for CRIMP and to study the steady-state signal under motion. Seven patients were scanned with CRIMP at stress and rest to develop the sequence. One human and two dogs were scanned at rest with a dual-bolus method to test the quantification feasibility of CRIMP. The dual-bolus scans were performed using both CRIMP and an ungated radial SMS saturation recovery (SMS-SR) sequence with injection dose = 0.075 mmol/kg to compare the sequences in terms of SNR, cardiac phase resolution and quantitative myocardial blood flow (MBF).

RESULTS

Perfusion images with multiple cardiac phases in all image slices with a temporal resolution of 72 ms/frame were obtained. Simulations and in-vivo acquisitions showed CRIMP kept the inner slices in steady-state regardless of motion. CRIMP outperformed SMS-SR in slice coverage (9 over 6), SNR (mean 20% improvement), and provided cardiac phase resolution. CRIMP and SMS-SR sequences provided comparable MBF values (rest systolic CRIMP = 0.58 ± 0.07, SMS-SR = 0.61 ± 0.16).

CONCLUSION

CRIMP allows for whole-heart, cardiac-phase-resolved myocardial perfusion images without ECG-gating or breath-holding. The sequence can provide MBF if an accurate arterial input function is obtained separately.

Phantom Validation of DCE-MRI Magnitude and Phase-Based Vascular Input Function Measurements

Accurate, patient-specific measurement of arterial input functions (AIF) may improve model-based analysis of vascular permeability. This study investigated factors affecting AIF measurements from magnetic resonance imaging (MRI) magnitude (AIF_MAGN) and phase (AIF_PHA) signals, and compared them against computed tomography (CT) (AIF_CT), under controlled conditions relevant to clinical protocols using a multimodality flow phantom. The flow phantom was applied at flip angles of 20° and 30°, flow rates (3-7.5 mL/s), and peak bolus concentrations (0.5-10 mM), for in-plane and through-plane flow. Spatial 3D-FLASH signal and variable flip angle T1 profiles were measured to investigate in-flow and radiofrequency-related biases, and magnitude- and phase-derived Gd-DTPA concentrations were compared. MRI AIF performance was tested against AIF_CT via Pearson correlation analysis. AIF_MAGN was sensitive to imaging orientation, spatial location, flip angle, and flow rate, and it grossly underestimated AIF_CT peak concentrations. Conversion to Gd-DTPA concentration using T1 taken at the same orientation and flow rate as the dynamic contrast-enhanced acquisition improved AIF_MAGN accuracy; yet, AIF_MAGN metrics remained variable and significantly reduced from AIF_CT at concentrations above 2.5 mM. AIF_PHA performed equivalently within 1 mM to AIF_CT across all tested conditions. AIF_PHA, but not AIF_MAGN, reported equivalent measurements to AIF_CT across the range of tested conditions. AIF_PHA showed superior robustness.

Tracer kinetic models as temporal constraints during brain tumor DCE-MRI reconstruction

Purpose

To apply tracer kinetic models as temporal constraints during reconstruction of under‐sampled brain tumor dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI).

Methods

A library of concentration vs time profiles is simulated for a range of physiological kinetic parameters. The library is reduced to a dictionary of temporal bases, where each profile is approximated by a sparse linear combination of the bases. Image reconstruction is formulated as estimation of concentration profiles and sparse model coefficients with a fixed sparsity level. Simulations are performed to evaluate modeling error, and error statistics in kinetic parameter estimation in presence of noise. Retrospective under‐sampling experiments are performed on a brain tumor DCE digital reference object (DRO), and 12 brain tumor in‐vivo 3T datasets. The performances of the proposed under‐sampled reconstruction scheme and an existing compressed sensing‐based temporal finite‐difference (tFD) under‐sampled reconstruction were compared against the fully sampled inverse Fourier Transform‐based reconstruction.

Results

Simulations demonstrate that sparsity levels of 2 and 3 model the library profiles from the Patlak and extended Tofts‐Kety (ETK) models, respectively. Noise sensitivity analysis showed equivalent kinetic parameter estimation error statistics from noisy concentration profiles, and model approximated profiles. DRO‐based experiments showed good fidelity in recovery of kinetic maps from 20‐fold under‐sampled data. In‐vivo experiments demonstrated reduced bias and uncertainty in kinetic mapping with the proposed approach compared to tFD at under‐sampled reduction factors >= 20.

Conclusions

Tracer kinetic models can be applied as temporal constraints during brain tumor DCE‐MRI reconstruction. The proposed under‐sampled scheme resulted in model parameter estimates less biased with respect to conventional fully sampled DCE MRI reconstructions and parameter estimation. The approach is flexible, can use nonlinear kinetic models, and does not require tuning of regularization parameters.

Nanomedicine - advantages for their use in rheumatoid arthritis theranostics

Rheumatoid arthritis (RA) is an autoimmune disease accompanies with synovial inflammation and progressive bone destruction. Currently, anti-rheumatic drugs need high dose and frequent use for a long-term, which lead to serious side effect and low patient compliance. To overcome above problems and improve clinical efficacy, nano-technology with targeting ability, sustained release and so forth, has been proposed on RA treatment and already achieved success in RA animal models. In this review, authors summarize and illustrate representative nanomedicine targeting to RA states, which is achieved either through passive or active targeting with high affinity to the receptors that are over-expressed in macrophages or angiogenesis. In particular, authors highlight the new strategies to promote the efficacy of nanoscale treatments through phototherapy and the addition of contrast elements for theranostic application. The described advances may pave the way to better understanding and designing the novel nanomedicine and multifunctional nano-system on efficient RA treatment.

A Comparative Study of Two-Compartment Exchange Models for Dynamic Contrast-Enhanced MRI in Characterizing Uterine Cervical Carcinoma

A variety of tracer kinetic methods have been employed to assess tumor angiogenesis. The Standard two-Compartment model (SC) used in cervix carcinoma was less frequent, and Adiabatic Approximation to the Tissue Homogeneity (AATH) and Distributed Parameter (DP) model are lacking. This study compares two-compartment exchange models (2CXM) (AATH, SC, and DP) for determining dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in cervical cancer, with the aim of investigating the potential of various parameters derived from 2CXM for tumor diagnosis and exploring the possible relationship between these parameters in patients with cervix cancer. Parameters (tissue blood flow, F_p; tissue blood volume, V_p; interstitial volume, V_e; and vascular permeability, PS) for regions of interest (ROI) of cervix lesions and normal cervix tissue were estimated by AATH, SC, and DP models in 36 patients with cervix cancer and 17 healthy subjects. All parameters showed significant differences between lesions and normal tissue with a P value less than 0.05, except for PS from the AATH model, F_p from the SC model, and V_p from the DP model. Parameter V_e from the AATH model had the largest AUC (r = 0.85). Parameters F_p and V_p from SC and DP models and V_e and PS from AATH and DP models were highly correlated, respectively, (r > 0.8) in cervix lesions. Cervix cancer was found to have a very unusual microcirculation pattern, with over-growth of cancer cells but without evident development of angiogenesis. V_e has the best performance in identifying cervix cancer. Most physiological parameters derived from AATH, SC, and DP models are linearly correlated in cervix cancer.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

Impact of (k,t) sampling on DCE MRI tracer kinetic parameter estimation in digital reference objects

Purpose

To evaluate the impact of (k,t) data sampling on the variance of tracer‐kinetic parameter (TK) estimation in high‐resolution whole‐brain dynamic contrast enhanced magnetic resonance imaging (DCE‐MRI) using digital reference objects. We study this in the context of TK model constraints, and in the absence of other constraints.

Methods

Three anatomically and physiologically realistic brain‐tumor digital reference objects were generated. Data sampling strategies included uniform and variable density; zone‐based, lattice, pseudo‐random, and pseudo‐radial; with 50‐time frames and 4‐fold to 25‐fold undersampling. In all cases, we assume a fully sampled first time frame, and prior knowledge of the arterial input function. TK parameters were estimated by indirect estimation (i.e., image‐time‐series reconstruction followed by model fitting), and direct estimation from the under‐sampled data. We evaluated methods based on the Cramér‐Rao bound and Monte‐Carlo simulations, over the range of signal‐to‐noise ratio (SNR) seen in clinical brain DCE‐MRI.

Results

Lattice‐based sampling provided the lowest SDs, followed by pseudo‐random, pseudo‐radial, and zone‐based. This ranking was consistent for the Patlak and extended Tofts model. Pseudo‐random sampling resulted in 19% higher averaged SD compared to lattice‐based sampling. Zone‐based sampling resulted in substantially higher SD at undersampling factors above 10. CRB analysis showed only a small difference between uniform and variable density for both lattice‐based and pseudo‐random sampling up to undersampling factors of 25.

Conclusion

Lattice sampling provided the lowest SDs, although the differences between sampling schemes were not substantial at low undersampling factors. The differences between lattice‐based and pseudo‐random sampling strategies with both uniform and variable density were within the range of error induced by other sources, at up to 25‐fold undersampling.

Spatially regularized estimation of the tissue homogeneity model parameters in DCE-MRI using proximal minimization

PURPOSE

The Tofts and the extended Tofts models are the pharmacokinetic models commonly used in dynamic contrast-enhanced MRI (DCE-MRI) perfusion analysis, although they do not provide two important biological markers, namely, the plasma flow and the permeability-surface area product. Estimates of such markers are possible using advanced pharmacokinetic models describing the vascular distribution phase, such as the tissue homogeneity model. However, the disadvantage of the advanced models lies in biased and uncertain estimates, especially when the estimates are computed voxelwise. The goal of this work is to improve the reliability of the estimates by including information from neighboring voxels.

THEORY AND METHODS

Information from the neighboring voxels is incorporated in the estimation process through spatial regularization in the form of total variation. The spatial regularization is applied on five maps of perfusion parameters estimated using the tissue homogeneity model. Since the total variation is not differentiable, two proximal techniques of convex optimization are used to solve the problem numerically.

RESULTS

The proposed algorithm helps to reduce noise in the estimated perfusion-parameter maps together with improving accuracy of the estimates. These conclusions are proved using a numerical phantom. In addition, experiments on real data show improved spatial consistency and readability of perfusion maps without considerable lowering of the quality of fit.

CONCLUSION

The reliability of the DCE-MRI perfusion analysis using the tissue homogeneity model can be improved by employing spatial regularization. The proposed utilization of modern optimization techniques implies only slightly higher computational costs compared to the standard approach without spatial regularization.

Feasibility and accuracy of quantitative imaging on a 1.5 T MR-linear accelerator

PURPOSE

Systems for magnetic resonance (MR-) guided radiotherapy enable daily MR imaging of cancer patients during treatment, which is of interest for treatment response monitoring and biomarker discovery using quantitative MRI (qMRI). Here, the performance of a 1.5 T MR-linac regarding qMRI was assessed on phantoms. Additionally, we show the feasibility of qMRI in a prostate cancer patient on this system for the first time.

MATERIALS AND METHODS

Four 1.5 T MR-linac systems from four institutes were included in this study. T₁ and T₂ relaxation times, and apparent diffusion coefficient (ADC) maps, as well as dynamic contrast enhanced (DCE) images were acquired. Bland-Altman statistics were used, and accuracy, repeatability, and reproducibility were determined.

RESULTS

Median accuracy for T₁ ranged over the four systems from 2.7 to 14.3%, for T₂ from 10.4 to 14.1%, and for ADC from 1.9 to 2.7%. For DCE images, the accuracy ranged from 12.8 to 35.8% for a gadolinium concentration of 0.5 mM and deteriorated for higher concentrations. Median short-term repeatability for T₁ ranged from 0.6 to 5.1%, for T₂ from 0.4 to 1.2%, and for ADC from 1.3 to 2.2%. DCE acquisitions showed a coefficient of variation of 0.1-0.6% in the signal intensity. Long-term repeatability was 1.8% for T₁, 1.4% for T₂, 1.7% for ADC, and 17.9% for DCE. Reproducibility was 11.2% for T₁, 2.9% for T₂, 2.2% for ADC, and 18.4% for DCE.

CONCLUSION

These results indicate that qMRI on the Unity MR-linac is feasible, accurate, and repeatable which is promising for treatment response monitoring and treatment plan adaptation based on daily qMRI.

Improved repeatability of dynamic contrast-enhanced MRI using the complex MRI signal to derive arterial input functions: a test-retest study in prostate cancer patients

Purpose

The arterial input function (AIF) is a major source of uncertainty in tracer kinetic (TK) analysis of dynamic contrast‐enhanced (DCE)‐MRI data. The aim of this study was to investigate the repeatability of AIFs extracted from the complex signal and of the resulting TK parameters in prostate cancer patients.

Methods

Twenty‐two patients with biopsy‐proven prostate cancer underwent a 3T MRI exam twice. DCE‐MRI data were acquired with a 3D spoiled gradient echo sequence. AIFs were extracted from the magnitude of the signal (AIF_MAGN), phase (AIF_PHASE), and complex signal (AIF_COMPLEX). The Tofts model was applied to extract K^trans, k_ep and v_e. Repeatability of AIF curve characteristics and TK parameters was assessed with the within‐subject coefficient of variation (wCV).

Results

The wCV for peak height and full width at half maximum for AIF_COMPLEX (7% and 8%) indicated an improved repeatability compared to AIF_MAGN (12% and 12%) and AIF_PHASE (12% and 7%). This translated in lower wCV values for K^trans (11%) with AIF_COMPLEX in comparison to AIF_MAGN (24%) and AIF_PHASE (15%). For k_ep, the wCV was 16% with AIF_MAGN, 13% with AIF_PHASE, and 13% with AIF_COMPLEX.

Conclusion

Repeatability of AIF_PHASE and AIF_COMPLEX is higher than for AIF_MAGN, resulting in a better repeatability of TK parameters. Thus, use of either AIF_PHASE or AIF_COMPLEX improves the robustness of quantitative analysis of DCE‐MRI in prostate cancer.

Signal amplification method for miR-205 assay through combining graphene oxide with duplex-specific nuclease

Since microRNA-205 (miR-205) is a predictive biomarker for anti-radiation of nasopharyngeal carcinoma (NPC), quantitative detection of miR-205 is important for developing personalized strategies for the treatment of NPC. In this investigation, based on the graphene oxide sensor and duplex specific nuclease (DSN) for fluorescence signal amplification, a highly sensitive detection method for miR-205 was designed. A target-recycling mechanism is employed, where a single miR-205 target triggers the cleavage of many DNA signal probes. The method shows the ability to analyze miR-205 in solution, and it can detect miR-205 at concentrations as low as 132 pmol L⁻¹ with a linear range of 5–40 nmol L⁻¹. Furthermore, the method is specific in that it distinguishes between a target miRNA and a sequence with single base, double base and three base mismatches, as well as other miRNAs. Considering simplicity and excellent sensitivity/specificity, it is promising for applications in radioresistance studies as well as the early clinical diagnosis of NPC.

A signal amplified method for detecting a biomarker of radiation-resistant nasopharyngeal carcinoma using graphene oxide and duplex-specific nuclease was constructed.

Quantitative Gd-DOTA-based aerosol deposition mapping in the lungs of asthmatic rats using 3D UTE-MRI

Asthma is a chronic respiratory disease, commonly treated with inhaled therapy. Better understanding of the mechanisms of aerosol deposition is required to improve inhaled drug delivery. Three-dimensional ultrashort echo time (UTE) MRI acquisitions at 1.5 T were combined with spontaneous nose-only inhalation of aerosolized gadolinium (Gd) to map the aerosol deposition and to characterize signal enhancement in asthmatic rat lungs. The rats were sensitized to ovalbumin (OVA) to develop asthmatic models and challenged before imaging by nebulization of OVA to trigger asthmatic symptoms. The negative controls were not sensitized or challenged by nebulization of saline. The animal lungs were imaged before and after administration of Gd-based aerosol in freely breathing rats, by using a T₁ -weighted 3D UTE sequence. A contrast-enhanced quantitative analysis was performed to assess regional concentration. OVA-sensitized rats had lower signal enhancement and lower deposited aerosol concentration. Their enhancement dynamics showed large inter-subject variability. The signal intensity was homogeneously enhanced for controls while OVA-sensitized rats showed heterogeneous enhancement. Contrast-enhanced 3D UTE was applied with aerosolized Gd to efficiently measure spatially resolved deposition in asthmatic lungs. The small administered dose (around 1 μmol/kg body weight) and the use of standard clinical MRI suggest a potential application for the exploration of asthma.

In vitro pharmacokinetic phantom for two-compartment modeling in DCE-MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an established minimally-invasive method for assessment of extravascular leakage, hemodynamics, and tissue viability. However, differences in acquisition protocols, variety of pharmacokinetic models, and uncertainty on physical sources of MR signal hamper the reliability and widespread use of DCE-MRI in clinical practice. Measurements performed in a controlled in vitro setup could be used as a basis for standardization of the acquisition procedure, as well as objective evaluation and comparison of pharmacokinetic models. In this paper, we present a novel flow phantom that mimics a two-compartmental (blood plasma and extravascular extracellular space/EES) vascular bed, enabling systemic validation of acquisition protocols. The phantom consisted of a hemodialysis filter with two compartments, separated by hollow fiber membranes. The aim of this phantom was to vary the extravasation rate by adjusting the flow in the two compartments. Contrast agent transport kinetics within the phantom was interpreted using two-compartmental pharmacokinetic models. Boluses of gadolinium-based contrast-agent were injected in a tube network connected to the hollow fiber phantom; time-intensity curves (TICs) were obtained from image series, acquired using a T1-weighted DCE-MRI sequence. Under the assumption of a linear dilution system, the TICs obtained from the input and output of the system were then analyzed by a system identification approach to estimate the trans-membrane extravasation rates in different flow conditions. To this end, model-based deconvolution was employed to determine (identify) the impulse response of the investigated dilution system. The flow rates in the EES compartment significantly and consistently influenced the estimated extravasation rates, in line with the expected trends based on simulation results. The proposed phantom can therefore be used to model a two-compartmental vascular bed and can be employed to test and optimize DCE-MRI acquisition sequences in order to determine a standardized acquisition procedure leading to consistent quantification results.

Computational fluid dynamics with imaging of cleared tissue and of in vivo perfusion predicts drug uptake and treatment responses in tumours

Understanding the uptake of a drug by diseased tissue, and the drug's subsequent spatiotemporal distribution, are central factors in the development of effective targeted therapies. However, the interaction between the pathophysiology of diseased tissue and individual therapeutic agents can be complex, and can vary across tissue types and across subjects. Here, we show that the combination of mathematical modelling, high-resolution optical imaging of intact and optically cleared tumour tissue from animal models, and in vivo imaging of vascular perfusion predicts the heterogeneous uptake, by large tissue samples, of specific therapeutic agents, as well as their spatiotemporal distribution. In particular, by using murine models of colorectal cancer and glioma, we report and validate predictions of steady-state blood flow and intravascular and interstitial fluid pressure in tumours, of the spatially heterogeneous uptake of chelated gadolinium by tumours, and of the effect of a vascular disrupting agent on tumour vasculature.

Impact of contrast agent injection duration on dynamic contrast-enhanced MRI quantification in prostate cancer

The volume transfer constant K^trans , which describes the leakage of contrast agent (CA) from vasculature into tissue, is the most commonly reported quantitative parameter for dynamic contrast-enhanced (DCE-) MRI. However, the variation in reported K^trans values between studies from different institutes is large. One of the primary sources of uncertainty is quantification of the arterial input function (AIF). The aim of this study is to determine the influence of the CA injection duration on the AIF and tracer kinetic analysis (TKA) parameters (i.e. K^trans , k_ep and v_e ). Thirty-one patients with prostate cancer received two DCE-MRI examinations with an injection duration of 5 s in the first examination and a prolonged injection duration in the second examination, varying between 7.5 s and 30 s. The DCE examination was carried out on a 3.0 T MRI scanner using a transversal T₁ -weighted 3D spoiled gradient echo sequence (300 s duration, dynamic scan time of 2.5 s). Data of 29 of the 31 were further analysed. AIFs were determined from the phase signal in the left and right femoral arteries. K^trans , k_ep and v_e were estimated with the standard Tofts model for regions of healthy peripheral zone and tumour tissue. We observed a significantly smaller peak height and increased width in the AIF for injection durations of 15 s and longer. However, we did not find significant differences in K^trans , k_ep or v_e for the studied injection durations. The study demonstrates that the TKA parameters K^trans , k_ep and v_e , measured in the prostate, do not show a significant change as a function of injection duration.

Accuracy and precision of quantitative DCE-MRI parameters: How should one estimate contrast concentration?

INTRODUCTION

Pharmacokinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) data are sensitive to acquisition and post-processing techniques, which makes it difficult to compare results obtained using different methods. In particular, one of the most important factors affecting estimation of model parameters is how to convert MRI signal intensities to contrast agent concentration. The purpose of our study was to quantitatively compare a linear signal-to-concentration conversion (LC) as an approximation and a non-linear conversion (NLC) based on the MRI signal equation, in terms of the accuracy and precision of the pharmacokinetic parameters in T₁-weighted DCE-MRI.

MATERIALS AND METHODS

Numerical simulation studies were conducted to compare LC and NLC in terms of the accuracy and precision in contrast kinetic parameter estimation, and to evaluate their dependency on flip angle (FA), pre-contrast T₁ (T₁₀) and arterial input function (AIF). In addition, the effect of the conversion method on the diagnostic accuracy was evaluated with 36 breast lesions (19 benign and 17 malignant).

RESULTS

The transfer rate (K^trans) estimated using LC and measured AIF (mAIF) were up to 38% higher than the true K^trans values, while the LC K^trans estimates with the presumed AIF (pAIF) were up to 7% lower than the true K^trans values, when FA = 45°. When using a small FA, such as 12°, the LC K^trans with pAIF had least sensitivity to the error in T₁₀ compared to the K^trans estimated using LC with mAIF, and NLC with pAIF or mAIF. The breast DCE-MRI study showed that both LC and NLC K^trans were significantly different (p < 0.05) between the malignant and benign lesions. The effect size between benign and malignant values as measured by Cohen's d was 1.06 for LC K^trans and 1.02 for NLC K^trans.

CONCLUSION

The present study results show that, when precontrast T₁ measurement is not available and a low FA is used for DCE-MRI, the uncertainty in the contrast kinetic parameter estimation can be reduced by using the LC method with pAIF, without compromising the diagnostic accuracy.

Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI

In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T₁, T₂ and T₂^∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T₁, T₂ and T₂^∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.

Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCE-MRI: Results from a multicenter phantom study

PURPOSE

To determine the in vitro accuracy, test-retest repeatability, and interplatform reproducibility of T₁ quantification protocols used for dynamic contrast-enhanced MRI at 1.5 and 3 T.

METHODS

A T₁ phantom with 14 samples was imaged at eight centers with a common inversion-recovery spin-echo (IR-SE) protocol and a variable flip angle (VFA) protocol using seven flip angles, as well as site-specific protocols (VFA with different flip angles, variable repetition time, proton density, and Look-Locker inversion recovery). Factors influencing the accuracy (deviation from reference NMR T₁ measurements) and repeatability were assessed using general linear mixed models. Interplatform reproducibility was assessed using coefficients of variation.

RESULTS

For the common IR-SE protocol, accuracy (median error across platforms = 1.4-5.5%) was influenced predominantly by T₁ sample (P < 10^-6 ), whereas test-retest repeatability (median error = 0.2-8.3%) was influenced by the scanner (P < 10^-6 ). For the common VFA protocol, accuracy (median error = 5.7-32.2%) was influenced by field strength (P = 0.006), whereas repeatability (median error = 0.7-25.8%) was influenced by the scanner (P < 0.0001). Interplatform reproducibility with the common VFA was lower at 3 T than 1.5 T (P = 0.004), and lower than that of the common IR-SE protocol (coefficient of variation 1.5T: VFA/IR-SE = 11.13%/8.21%, P = 0.028; 3 T: VFA/IR-SE = 22.87%/5.46%, P = 0.001). Among the site-specific protocols, Look-Locker inversion recovery and VFA (2-3 flip angles) protocols showed the best accuracy and repeatability (errors < 15%).

CONCLUSIONS

The VFA protocols with 2 to 3 flip angles optimized for different applications achieved acceptable balance of extensive spatial coverage, accuracy, and repeatability in T₁ quantification (errors < 15%). Further optimization in terms of flip-angle choice for each tissue application, and the use of B₁ correction, are needed to improve the robustness of VFA protocols for T₁ mapping. Magn Reson Med 79:2564-2575, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Noninvasive prediction of portal pressure with MR elastography and DCE-MRI of the liver and spleen: Preliminary results

BACKGROUND

Portal hypertension (PH), defined by hepatic venous pressure gradient (HVPG) ≥5 mmHg and clinically significant PH, defined by HVPG ≥10 mmHg, are complications of chronic liver disease.

PURPOSE

To assess the diagnostic performance of MR elastography (MRE) and dynamic contrast-enhanced MRI (DCE-MRI) of the liver and spleen for the prediction of PH and clinically significant PH, in comparison with a qualitative PH imaging scoring system.

STUDY TYPE

IRB-approved prospective study.

POPULATION

In all, 34 patients with chronic liver disease who underwent HVPG measurement.

FIELD STRENGTH/SEQUENCE

1.5/3T examination including 2D-GRE MRE (n = 33) and DCE-MRI of the liver/spleen (n = 28).

ASSESSMENT

Liver and spleen stiffness were calculated from elastogram maps. DCE-MRI was analyzed using model-free parameters and pharmacokinetic modeling. Two observers calculated qualitative PH imaging scores based on routine images.

STATISTICAL TESTS

Imaging parameters were correlated with HVPG. Receiver operating characteristic (ROC) analysis was performed for prediction of PH and clinically significant PH.

RESULTS

There were significant correlations between DCE-MRI parameters (liver time-to-peak, r = 0.517 / P = 0.006, liver distribution volume, r = 0.494 / P = 0.009, liver upslope, r = -0.567 / P = 0.002), liver stiffness (r = 0.478 / P = 0.016), PH imaging score (r = 0.441 / P = 0.009), and HVPG. ROC analysis provided significant area under the ROC (AUROCs) for PH (liver upslope 0.765, liver stiffness 0.809, spleen volume/diameter 0.746-0.731, PH imaging score 0.756) and for clinically significant PH (liver and spleen perfusion parameters 0.733-0.776, liver stiffness 0.742, PH imaging score 0.742). The ratio of liver stiffness to liver upslope had the highest AUROC for diagnosing PH (0.903) and clinically significant PH (0.785).

DATA CONCLUSION

These preliminary results suggest that the combination of liver stiffness and perfusion metrics provide excellent accuracy for diagnosing PH, and fair accuracy for clinically significant PH. Combined MRE and DCE-MRI outperformed qualitative imaging scores for prediction of PH.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1091-1103.

Novel Detection of Placental Insufficiency by Magnetic Resonance Imaging in the Nonhuman Primate

The placenta is a vital organ necessary for healthy fetal development. Placental insufficiency creates an in utero environment where the fetus is at risk of insufficient oxygen or nutrient exchange. This is primarily caused by impairment of either maternal or fetal circulation or vascular thrombosis such as placental infarction. As a result of placental dysfunction, affected fetuses may be growth restricted, neurologically impaired, and at risk of increased morbidity and mortality. In a cohort of 4 pregnant Rhesus macaques, we describe antenatal detection of naturally occurring intrauterine growth restriction (IUGR) and aberrant fetal neurodevelopment in 1 animal. Abnormal growth parameters were detected by Doppler ultrasound, and vascular insufficiency in the intervillous space was characterized by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Furthermore, placental oxygen reserve was shown to be reduced compared to control animals by measurements of placental water T2*. To characterize the effects of IUGR on fetal brain development, T2 and diffusion anisotropy images of the fetal brain were acquired in utero. Reduced brain volume and cerebral cortical surface area were apparent macroscopically. Microstructural abnormalities within the developing white matter and cerebral cortex were also observed through analysis of water diffusion anisotropy. After delivery by cesarean section, pathological examination confirmed placental insufficiency with hypoxia. These findings exemplify how DCE-MRI and T2*-based measurements of blood oxygenation within the placenta can provide noninvasive imaging methods for assessing in vivo placental health to potentially identify pregnancies affected by placental insufficiency and abnormal fetal neurodevelopment prior to the onset of fetal and neonatal distress.

Estimating the arterial input function from dynamic contrast-enhanced MRI data with compensation for flow enhancement (I): Theory, method, and phantom experiments

BACKGROUND

The arterial input function (AIF) represents the time-dependent arterial contrast agent (CA) concentration that is used in pharmacokinetic modeling.

PURPOSE

To develop a novel method for estimating the AIF from dynamic contrast-enhanced (DCE-) MRI data, while compensating for flow enhancement.

STUDY TYPE

Signal simulation and phantom measurements.

PHANTOM MODEL

Time-intensity curves (TICs) were simulated for different numbers of excitation pulses modeling flow effects. A phantom experiment was performed in which a solution (without CA) was passed through a straight tube, at constant flow velocity.

FIELD STRENGTH/SEQUENCE

Dynamic fast spoiled gradient echo (FSPGRs) at 3T MRI, both in the simulations and in the phantom experiment. TICs were generated for a duration of 373 seconds and sampled at intervals of 1.247 seconds (300 timepoints).

ASSESSMENT

The proposed method first estimates the number of pulses that spins have received, and then uses this knowledge to accurately estimate the CA concentration.

STATISTICAL TESTS

The difference between the median of the estimated number of pulses and the true value was determined, as well as the interquartile range (IQR) of the estimations. The estimated CA concentrations were evaluated in the same way. The estimated number of pulses was also used to calculate flow velocity.

RESULTS

The difference between the median estimated and reference number of pulses varied from -0.005 to -1.371 (corresponding IQRs: 0.853 and 48.377) at true values of 10 and 180 pulses, respectively. The difference between the median estimated CA concentration and the reference value varied from -0.00015 to 0.00306 mmol/L (corresponding IQRs: 0.01989 and 1.51013 mmol/L) at true values of 0.5 and 8.0 mmol/l, respectively, at an intermediate value of 100 pulses. The estimated flow velocities in the phantom were within 10% of the reference value.

DATA CONCLUSION

The proposed method accurately corrects the MRI signal affected by the inflow effect.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1190-1196.

Quantitative vascular neuroimaging of the rat brain using superparamagnetic nanoparticles: New insights on vascular organization and brain function

A method called Quantitative Ultra-Short Time-to-Echo Contrast Enhanced (QUTE-CE) Magnetic Resonance Imaging (MRI) which utilizes superparamagnetic iron oxide nanoparticles (SPIONs) as a contrast agent to yield positive contrast angiograms with high clarity and definition is applied to the whole live rat brain. QUTE-CE MRI intensity data are particularly well suited for measuring quantitative cerebral blood volume (qCBV). A global map of qCBV in the awake resting-state with unprecedented detail was created via application of a 3D MRI rat brain atlas with 173 segmented and annotated brain areas. From this map we identified two distributed, integrated neural circuits showing the highest capillary densities in the brain. One is the neural circuitry involved with the primary senses of smell, hearing and vision and the other is the neural circuitry of memory. Under isoflurane anesthesia, these same circuits showed significant decreases in qCBV suggesting a role in consciousness. Neural circuits in the brainstem associated with the reticular activating system and the maintenance of respiration, body temperature and cardiovascular function showed an increase in qCBV with anesthesia. During awake CO2 challenge, 84 regions showed significant increases relative to an awake baseline state. This CO2 response provides a measure of cerebral vascular reactivity and regional perfusion reserve with the highest response measured in the somatosensory cortex. These results demonstrate the utility of QUTE-CE MRI for qCBV analysis and offer a new perspective on brain function and vascular organization.

MRI measurements of Blood-Brain Barrier function in dementia: A review of recent studies

Blood-brain barrier (BBB) separates the systemic circulation and the brain, regulating transport of most molecules to protect the brain microenvironment. Multiple structural and functional components preserve the integrity of the BBB. Several imaging modalities are available to study disruption of the BBB. However, the subtle changes in BBB leakage that occurs in vascular cognitive impairment and Alzheimer's disease have been less well studied. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is the most widely adopted non-invasive imaging technique for evaluating BBB breakdown. It is used as a significant marker for a wide variety of diseases with large permeability leaks, such as brain tumors and multiple sclerosis, to more subtle disruption in chronic vascular disease and dementia. DCE-MRI analysis of BBB includes both model-free parameters and quantitative parameters using pharmacokinetic modelling. We review MRI studies of BBB breakdown in dementia. The challenges in measuring subtle BBB changes and the state of the art techniques are initially examined. Subsequently, a systematic review comparing methodologies from recent in-vivo MRI studies is presented. Various factors related to subtle BBB permeability measurement such as DCE-MRI acquisition parameters, arterial input assessment, T₁ mapping and data analysis methods are reviewed with the focus on finding the optimal technique. Finally, the reported BBB permeability values in dementia are compared across different studies and across various brain regions. We conclude that reliable measurement of low-level BBB permeability across sites remains a difficult problem and a standardization of the methodology for both data acquisition and quantitative analysis is required. This article is part of the Special Issue entitled 'Cerebral Ischemia'.

Semi-parametric arterial input functions for quantitative dynamic contrast enhanced magnetic resonance imaging in mice

OBJECTIVE

An extension of single- and multi-channel blind deconvolution is presented to improve the estimation of the arterial input function (AIF) in quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI).

METHODS

The Lucy-Richardson expectation-maximization algorithm is used to obtain estimates of the AIF and the tissue residue function (TRF). In the first part of the algorithm, nonparametric estimates of the AIF and TRF are obtained. In the second part, the decaying part of the AIF is approximated by three decaying exponential functions with the same delay, giving an almost noise free semi-parametric AIF. Simultaneously, the TRF is approximated using the adiabatic approximation of the Johnson-Wilson (aaJW) pharmacokinetic model.

RESULTS

In simulations and tests on real data, use of this AIF gave perfusion values close to those obtained with the corresponding previously published nonparametric AIF, and are more noise robust.

CONCLUSION

When used subsequently in voxelwise perfusion analysis, these semi-parametric AIFs should give more correct perfusion analysis maps less affected by recording noise than the corresponding nonparametric AIFs, and AIFs obtained from arteries.

SIGNIFICANCE

This paper presents a method to increase the noise robustness in the estimation of the perfusion parameter values in DCE-MRI.

TumourMetrics: a comprehensive clinical solution for the standardization of DCE-MRI analysis in research and routine use

Background

A reliable analysis methodology is needed to provide valuable imaging biomarkers for clinical trials, with particular regards to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) application using pharmacokinetic (PK) model analysis. In order to address this scientific challenge, we provided a comprehensive analysis solution that could overcome the impediments to clinical research and routine use.

Methods

TumourMetrics has been designed to meet the Quantitative Imaging Biomarkers Alliance (QIBA) v.1.0 profile. The quality performance was assessed using the QIBA test data and our customizable numeric phantom. The analysis workflow is made customizable to facilitate standardization of optimized protocol across centers.

Results

Our quantification workflow estimated the PK model parameters accurately. The method is robust, almost fully automatic and allows a direct integration of the results into the diagnostic workflow.

Conclusions

The analysis is easy-to-use and accessible for routine implementation of DCE-MRI into clinical practice.

A Multi-Institutional Comparison of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameter Calculations

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides quantitative metrics (e.g. K^trans, v_e) via pharmacokinetic models. We tested inter-algorithm variability in these quantitative metrics with 11 published DCE-MRI algorithms, all implementing Tofts-Kermode or extended Tofts pharmacokinetic models. Digital reference objects (DROs) with known K^trans and v_e values were used to assess performance at varying noise levels. Additionally, DCE-MRI data from 15 head and neck squamous cell carcinoma patients over 3 time-points during chemoradiotherapy were used to ascertain K^trans and v_e kinetic trends across algorithms. Algorithms performed well (less than 3% average error) when no noise was present in the DRO. With noise, 87% of K^trans and 84% of v_e algorithm-DRO combinations were generally in the correct order. Low Krippendorff’s alpha values showed that algorithms could not consistently classify patients as above or below the median for a given algorithm at each time point or for differences in values between time points. A majority of the algorithms produced a significant Spearman correlation in v_e of the primary gross tumor volume with time. Algorithmic differences in K^trans and v_e values over time indicate limitations in combining/comparing data from distinct DCE-MRI model implementations. Careful cross-algorithm quality-assurance must be utilized as DCE-MRI results may not be interpretable using differing software.