Quantification of myocardial blood flow with cardiovascular magnetic resonance throughout the cardiac cycle

BACKGROUND: Myocardial blood flow (MBF) varies throughout the cardiac cycle in response to phasic changes in myocardial tension. The aim of this study was to determine if quantitative myocardial perfusion imaging with cardiovascular magnetic resonance (CMR) can accurately track physiological variations in MBF throughout the cardiac cycle. METHODS: 30 healthy volunteers underwent a single stress/rest perfusion CMR study with data acquisition at 5 different time points in the cardiac cycle (early-systole, mid-systole, end-systole, early-diastole and end-diastole). MBF was estimated on a per-subject basis by Fermi-constrained deconvolution. Interval variations in MBF between successive time points were expressed as percentage change. Maximal cyclic variation (MCV) was calculated as the percentage difference between maximum and minimum MBF values in a cardiac cycle. RESULTS: At stress, there was significant variation in MBF across the cardiac cycle with successive reductions in MBF from end-diastole to early-, mid- and end-systole, and an increase from early- to end-diastole (end-diastole: 4.50 ± 0.91 vs. early-systole: 4.03 ± 0.76 vs. mid-systole: 3.68 ± 0.67 vs. end-systole 3.31 ± 0.70 vs. early-diastole: 4.11 ± 0.83 ml/g/min; all p values <0.0001). In all cases, the maximum and minimum stress MBF values occurred at end-diastole and end-systole respectively (mean MCV = 26 ± 5%). There was a strong negative correlation between MCV and peak heart rate at stress (r = -0.88, p < 0.001). The largest interval variation in stress MBF occurred between end-systole and early-diastole (24 ± 9% increase). At rest, there was no significant cyclic variation in MBF (end-diastole: 1.24 ± 0.19 vs. early-systole: 1.28 ± 0.17 vs.mid-systole: 1.28 ± 0.17 vs. end-systole: 1.27 ± 0.19 vs. early-diastole: 1.29 ± 0.19 ml/g/min; p = 0.71). CONCLUSION: Quantitative perfusion CMR can be used to non-invasively assess cyclic variations in MBF throughout the cardiac cycle. In this study, estimates of stress MBF followed the expected physiological trend, peaking at end-diastole and falling steadily through to end-systole. This technique may be useful in future pathophysiological studies of coronary blood flow and microvascular function

Quantitative three-dimensional cardiovascular magnetic resonance myocardial perfusion imaging in systole and diastole

BACKGROUND: Two-dimensional (2D) perfusion cardiovascular magnetic resonance (CMR) remains limited by a lack of complete myocardial coverage. Three-dimensional (3D) perfusion CMR addresses this limitation and has recently been shown to be clinically feasible. However, the feasibility and potential clinical utility of quantitative 3D perfusion measurements, as already shown with 2D-perfusion CMR and positron emission tomography, has yet to be evaluated. The influence of systolic or diastolic acquisition on myocardial blood flow (MBF) estimates, diagnostic accuracy and image quality is also unknown for 3D-perfusion CMR. The purpose of this study was to establish the feasibility of quantitative 3D-perfusion CMR for the detection of coronary artery disease (CAD) and to compare systolic and diastolic estimates of MBF. METHODS: Thirty-five patients underwent 3D-perfusion CMR with data acquired at both end-systole and mid-diastole. MBF and myocardial perfusion reserve (MPR) were estimated on a per patient and per territory basis by Fermi-constrained deconvolution. Significant CAD was defined as stenosis ≥70% on quantitative coronary angiography. RESULTS: Twenty patients had significant CAD (involving 38 out of 105 territories). Stress MBF and MPR had a high diagnostic accuracy for the detection of CAD in both systole (area under curve [AUC]: 0.95 and 0.92, respectively) and diastole (AUC: 0.95 and 0.94). There were no significant differences in the AUCs between systole and diastole (p values >0.05). At stress, diastolic MBF estimates were significantly greater than systolic estimates (no CAD: 3.21 ± 0.50 vs. 2.75 ± 0.42 ml/g/min, p 0.05). Image quality was higher in systole than diastole (median score 3 vs. 2, p = 0.002). CONCLUSIONS: Quantitative 3D-perfusion CMR is feasible. Estimates of MBF are significantly different for systole and diastole at stress but diagnostic accuracy to detect CAD is high for both cardiac phases. Better image quality suggests that systolic data acquisition may be preferable

Multimodal phantoms for clinical PET/MRI

Phantoms are commonly used throughout medical imaging and medical physics for a multitude of applications, the designs of which vary between modalities and clinical or research requirements. Within positron emission tomography (PET) and nuclear medicine, phantoms have a well-established role in the validation of imaging protocols so as to reduce the administration of radioisotope to volunteers. Similarly, phantoms are used within magnetic resonance imaging (MRI) to perform quality assurance on clinical scanners, and gel-based phantoms have a longstanding use within the MRI research community as tissue equivalent phantoms. In recent years, combined PET/MRI scanners for simultaneous acquisition have entered both research and clinical use. This review explores the designs and applications of phantom work within the field of simultaneous acquisition PET/MRI as published over the period of a decade. Common themes in the design, manufacture and materials used within phantoms are identified and the solutions they provided to research in PET/MRI are summarised. Finally, the challenges remaining in creating multimodal phantoms for use with simultaneous acquisition PET/MRI are discussed. No phantoms currently exist commercially that have been designed and optimised for simultaneous PET/MRI acquisition. Subsequently, commercially available PET and nuclear medicine phantoms are often utilised, with CT-based attenuation maps substituted for MR-based attenuation maps due to the lack of MR visibility in phantom housing. Tissue equivalent and anthropomorphic phantoms are often developed by research groups in-house and provide customisable alternatives to overcome barriers such as MR-based attenuation correction, or to address specific areas of study such as motion correction. Further work to characterise materials and manufacture methods used in phantom design would facilitate the ability to reproduce phantoms across sites

ESR Statement on the Validation of Imaging Biomarkers

Medical imaging capable of generating imaging biomarkers, specifically radiology and nuclear medicine image acquisition and analysis processes, differs from frequently used comparators like blood or urine biomarkers. This difference arises from the sample acquisition methodology. While different analysis methodologies and equipment provide slightly different results in any analytical domain, unlike blood or urine analysis where the samples are obtained by simple extraction or excretion, in radiology the acquisition of the sample is heterogeneous by design, since complex equipment from different vendors is used. Therefore, with this additional degree of freedom in medical imaging, there is still risk of persistent heterogeneity of image quality through time, due to different technological implementations across vendors and protocols used in different centres. Quantitative imaging biomarkers have yet to demonstrate an impact on clinical practice due to this lack of comprehensive standardisation in terms of technical aspects of image acquisition, analysis algorithms, processes and clinical validation. The aim is establishing a standard methodology based on metrology for the validation of image acquisition and analysis methods used in the extraction of biomarkers and radiomics data. The appropriate implementation of the guidelines herein proposed by radiology departments, research institutes and industry will allow for a significant reduction in inter-vendor & inter-centre variability in imaging biomarkers and determine the measurement error obtained, enabling them to be used in imaging-based criteria for diagnosis, prognosis or treatment response, ultimately improving clinical workflows and patient care. The validation of developed analytical methods must be based on a technical performance validation and clinical validation

Mathematics and Medicine: How mathematics, modelling and simulations can lead to better diagnosis and treatments

Starting with the discovery of X-rays by Röntgen in 1895, the progress in medical imaging has been extraordinary and immensely beneficial to diagnosis and therapy. Parallel to the increase of imaging accuracy, there is the quest of moving from qualitative to quantitative analysis and patient-tailored therapy. Mathematics, modelling and simulations are increasing their importance as tools in this quest. In this paper we give an overview of relations between mathematical modelling and imaging and focus particularly on the estimation of perfusion in the brain. In the forward model, the brain is treated as a porous medium and a two compartment model (arterial/venous) is used. Motivated by the similarity with techniques in reservoir modelling, we propose an ensemble Kalman filter to perform the parameter estimation and apply the method to a simple example as an illustrative example.acceptedVersio

Current status in spatiotemporal analysis of contrast‐based perfusion MRI

In perfusion MRI, image voxels form a spatially organized network of systems, all exchanging indicator with their immediate neighbors. Yet the current paradigm for perfusion MRI analysis treats all voxels or regions-of-interest as isolated systems supplied by a single global source. This simplification not only leads to long-recognized systematic errors but also fails to leverage the embedded spatial structure within the data. Since the early 2000s, a variety of models and implementations have been proposed to analyze systems with between-voxel interactions. In general, this leads to large and connected numerical inverse problems that are intractible with conventional computational methods. With recent advances in machine learning, however, these approaches are becoming practically feasible, opening up the way for a paradigm shift in the approach to perfusion MRI. This paper seeks to review the work in spatiotemporal modelling of perfusion MRI using a coherent, harmonized nomenclature and notation, with clear physical definitions and assumptions. The aim is to introduce clarity in the state-of-the-art of this promising new approach to perfusion MRI, and help to identify gaps of knowledge and priorities for future research

Ex vivo gadoxetate relaxivities in rat liver tissue and blood at five magnetic field strengths from 1.41 to 7 T

Quantitative mapping of gadoxetate uptake and excretion rates in liver cells has shown potential to significantly improve the management of chronic liver disease and liver cancer. Unfortunately, technical and clinical validation of the technique is currently hampered by the lack of data on gadoxetate relaxivity. The aim of this study was to fill this gap by measuring gadoxetate relaxivity in liver tissue, which approximates hepatocytes, in blood, urine and bile at magnetic field strengths of 1.41, 1.5, 3, 4.7 and 7 T. Measurements were performed ex vivo in 44 female Mrp2 knockout rats and 30 female wild‐type rats who had received an intravenous bolus of either 10, 25 or 40 μmol/kg gadoxetate. T1 was measured at 37 ± 3°C on NMR instruments (1.41 and 3 T), small‐animal MRI (4.7 and 7 T) and clinical MRI (1.5 and 3 T). Gadolinium concentration was measured with optical emission spectrometry or mass spectrometry. The impact on measurements of gadoxetate rate constants was determined by generalizing pharmacokinetic models to tissues with different relaxivities. Relaxivity values (L mmol−1 s−1) showed the expected dependency on tissue/biofluid type and field strength, ranging from 15.0 ± 0.9 (1.41) to 6.0 ± 0.3 (7) T in liver tissue, from 7.5 ± 0.2 (1.41) to 6.2 ± 0.3 (7) T in blood, from 5.6 ± 0.1 (1.41) to 4.5 ± 0.1 (7) T in urine and from 5.6 ± 0.4 (1.41) to 4.3 ± 0.6 (7) T in bile. Failing to correct for the relaxivity difference between liver tissue and blood overestimates intracellular uptake rates by a factor of 2.0 at 1.41 T, 1.8 at 1.5 T, 1.5 at 3 T and 1.2 at 4.7 T. The relaxivity values derived in this study can be used retrospectively and prospectively to remove a well‐known bias in gadoxetate rate constants. This will promote the clinical translation of MR‐based liver function assessment by enabling direct validation against reference methods and a more effective translation between in vitro findings, animal models and patient studies

Cardiotoxicity and myocardial hypoperfusion associated with anti‐vascular endothelial growth factor therapies: prospective cardiac magnetic resonance imaging in patients with cancer

No abstract available

Comparison of Correction Techniques for the Spill in Effect in Emission Tomography

In positron emission tomography (PET) imaging, accurate clinical assessment is often affected by the partial volume effect (PVE) leading to overestimation (spill-in) or underestimation (spill-out) of activity in various small regions. The spill-in correction, in particular, can be very challenging when the target region is close to a hot background region. Therefore, this study evaluates and compares the performance of various recently developed spill-in correction techniques, namely: background correction (BC), local projection (LP), and hybrid kernelized (HKEM) methods. We used a simulated digital phantom and 18F-NaF PET data of three patients with abdominal aortic aneurysms (AAA) acquired with Siemens Biograph mMRTM and mCTTM scanners respectively. Region of Interest (ROI) analysis was performed and the extracted SUVmean, SUVmax and target-to-background ratio (TBR) scores were compared. Results showed substantial spill-in effects from hot regions to targeted regions, which are more prominent in small structures. The phantom experiment demonstrated the feasibility of spill-in correction with all methods. For the patient data, large differences in SUVmean, SUVmax and TBRmax scores were observed between the ROIs drawn over the entire aneurysm and ROIs excluding some regions close to the bone. Overall, BC yielded the best performance in spill-in correction in both phantom and patient studies

DCE-MRI for Early Prediction of Response in Hepatocellular Carcinoma after TACE and Sorafenib Therapy: A Pilot Study

Objective: Dynamic contrast-enhanced MRI (DCE-MRI) can measure the changes in tumor blood flow, vascular permeability and interstitial and intravascular volume. The objective was to evaluate the efficacy of DCE-MRI in prediction of Barcelona Clinic Liver Cancer (BCLC) staging B or C hepatocellular carcinoma (HCC) response after treatment with transcatheter arterial chemoembolization (TACE) followed by sorafenib therapy. Methods: Sorafenib was administered four days after TACE of BCLC staging B or C HCC in 11 patients (21 lesions). DCE-MRI was performed with Gd-EOB-DTPA contrast before TACE and three and 10 days after TACE. DCE-MRI acquisitions were taken pre-contrast, hepatic arterial-dominant phase and 60, 120, 180, 240, 330, 420, 510 and 600 seconds post-contrast. Distribution volume of contrast agent (DV) and transfer constant Ktrans were calculated. Patients were grouped by mRECIST after one month or more post-TACE into responders (complete response, partial response) and non-responders (stable disease, progressive disease). Results: DV was reduced in responders at three and 10 days post-TACE (p = 0.008 and p = 0.008 respectively). DV fell in non-responders at three days (p = 0.025) but was not significantly changed from pre-TACE values after sorafenib. Sensitivity and specificity for DV 10 days post-TACE were 88% and 77% respectively. Conclusion: DV may be a useful biomarker for early prediction of therapeutic outcome in intermediate HCC