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Register a new userPolarized Helium to Image the Lung
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Authors
Mich`ele Leduc
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The main findings of the european PHIL project (Polarised Helium to Image the Lung) are reported. State of the art optical pumping techniques for polarising ^3He gas are described. MRI methodological improvements allow dynamical ventilation images with a good resolution, ultimately limited by gas diffusion. Diffusion imaging appears as a robust method of lung diagnosis. A discussion of the potential advantage of low field MRI is presented. Selected PHIL results for emphysema are given, with the perspectives that this joint work opens up for the future of respiratory medicine.
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We present NMR measurements of the diffusion of hyperpolarized helium-3 in the human lung performed at fields much lower than those of conventional MRI scanners. The measurements were made on standing subjects using homebuilt apparatus operating at 3 mT. Oxygen-limited transverse relaxation (T2 up to 15-35 s) could be measured in-vivo. Accurate global diffusion measurements have been performed in-vivo and in-vitro. 1D ADC mapping with high SNR demonstrates the real possibility of performing quality lung imaging at extremely low fields.
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images with 1.25 mm slice thickness is presented. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The results obtained on the collected database of lung CT scans are discussed.
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector computed-tomography (CT) images has been developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, consisting in a 3D dot-enhancement filter for nodule detection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The database used in this study consists of 17 low-dose CT scans reconstructed with thin slice thickness (~300 slices/scan). The preliminary results are shown in terms of the FROC analysis reporting a good sensitivity (85% range) for both internal and sub-pleural nodules at an acceptable level of false positive findings (1-9 FP/scan); the sensitivity value remains very high (75% range) even at 1-6 FP/scan
Optical pumping of He-3 produces large (hyper) nuclear-spin polarizations independent of the magnetic resonance imaging (MRI) field strength. This allows lung MRI to be performed at reduced fields with many associated benefits, such as lower tissue susceptibility gradients and decreased power absorption rates. Here we present results of 2D imaging as well as accurate 1D gas diffusion mapping of the human lung using He-3 at very low field (3 mT). Furthermore, measurements of transverse relaxation in zero applied gradient are shown to accurately track pulmonary oxygen partial pressure, opening the way for novel imaging sequences.
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