Fast and Automatic Quantification of Cardiac Perfusion MRI
نویسندگان
چکیده
Methods 75 datasets including 37 patients (25 after revasculated infarctions, 12 after radiation therapy in the treatment of Hodgkin’s disease) and 38 healthy volunteers were evaluated. 18 examinations were performed under adenosine induced stress. Perfusion series were acquired in a 1.5T scanner (Siemens) using an ECG-gated saturation recovery true-FISP sequence with the following parameters: Repetition time: 2.5 ms 2.6 ms, echo time: 1.1 ms, inversion time: 108 ms – 110 ms, flip angle: 48° 50°, field of view: 340 mm – 360 mm, slice thickness = 8mm. The contrast agent (CA) bolus was tracked by acquisition of 40 consecutive images over 40 heartbeats. All images were reconstructed to a 256 x 256 matrix. For quantification of myocardial blood flow the prebolus technique [1] with 1ml / 4 ml Gd-based CA was applied. The series were automatically motion corrected using the algorithm based on the technique proposed Adluru et al. [2]. This algorithm circumvents the problem of varying contrast by calculating a model image for each single original image. The original images were registered to the corresponding model images by minimizing the mean square difference between original and model through rigid transformation. This process was performed iteratively. The motion corrected images were segmented automatically using the software Developer Life (Definiens, Munich, Germany). One segmentation template for 8 myocardial sectors and two ROIs in the ventricles was determined and was applied to all motion corrected images. These signal intensity time courses have been evaluated using baselineand contamination correction [3]. For comparison all datasets were segmented manually to obtain the signal intensity time courses from 8 sectors in the myocardium and from the blood pools. The signal intensity time courses were evaluated the same way as the automatically obtained signal intensity time courses. For investigation of the interobserver variability 10 representative datasets were manually evaluated by two different observers.
منابع مشابه
An Efficient Framework for Accurate Arterial Input Selection in DSC-MRI of Glioma Brain Tumors
Introduction: Automatic arterial input function (AIF) selection has an essential role in quantification of cerebral perfusion parameters. The purpose of this study is to develop an optimal automatic method for AIF determination in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) of glioma brain tumors by using a new preprocessing method.Material and Methods: For this study, ...
متن کاملMyocardial perfusion SPECT: Perfusion quantification
Different software tools for quantification of myocardial perfusion SPECT (MPS) studies are routinely used. Several perfusion parameters can be computed automatically. Interpretation of the MPS should start with visual inspection of the rotating planar images, visual analysis of reconstructed SPECT slices and then quantitative analysis to confirm the visual impression. Quantification should be...
متن کاملSCALE PWI: A Pulse Sequence for Quantitative Cerebral Perfusion Imaging
INTRODUCTION Quantitative cerebral perfusion is a fundamental physiologic parameter that reflects the severity and progression of a broad range of pathologies including: cancer, stroke, Alzheimer’s Disease, and cerebrovascular occlusive disease. The “Bookend” technique [1,2] allows quantification of cerebral blood flow (CBF) and cerebral blood volume (CBV) with dynamic susceptibility contrast (...
متن کاملStress perfusion cardiac MRI with regadenoson and gadofoveset trisodium
Background Stress perfusion cardiac MRI (CMR) with a high relaxivity blood-pool contrast agent should allow for improved quantification of myocardial perfusion and myocardium blood volume in patients with coronary artery disease (CAD). In the current study, we sought to evaluate the diagnostic performance and image quality of stress perfusion CMR using the intravascular contrast agent gadofoves...
متن کاملDiffusion-weighted MRI for body imaging applications
Diffusion is the thermally induced motion of water molecules in biological tissues, called Brownian motion. Diffusion-weighted MRI (DWI) by means of apparent diffusion coefficient (ADC) calculation can be used for in vivo quantification of the combined effects of capillary perfusion and diffusion. With the advent of echoplanar imaging (EPI), DWI of the abdomen has become possible with fast imag...
متن کاملAutomatic Assessment of Cardiac Perfusion MRI
In this paper, a method based on Active Appearance Models (AAM) is applied for automatic registration of myocardial perfusion MRI. A semi-quantitative perfusion assessment of the registered image sequences is presented. This includes the formation of perfusion maps for three parameters; maximum up-slope, peak and time-to-peak.
متن کامل