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Biomedical subjects

Georgios Sakas

Publications and source records attributed to Georgios Sakas.

6 recordsLinked to original sources
PubMed2006

Advantages and limitations of prospective head motion compensation for MRI using an optical motion tracking device.

RATIONALE AND OBJECTIVES: Subject motion appears to be a limiting factor in numerous magnetic resonance (MR) imaging (MRI) applications. In particular, head tremor, which often accompanies stroke, may render certain high-resolution two- (2D) and three-dimensional (3D) techniques inapplicable. The reason for that is head movement during acquisition. The study objective is to achieve a method able to compensate for complete motion during data acquisition. The method should be usable for every sequence and easily implemented on different MR scanners. MATERIALS AND METHODS: The possibility of interfacing the MR scanner with an external optical motion-tracking system capable of determining the object's position with submillimeter accuracy and an update rate of 60 Hz is shown. Movement information on the object position (head) is used to compensate for motion in real time by updating the field of view (FOV) by recalculating the gradients and radiofrequency parameter of the MR scanner during acquisition of k-space data, based on tracking data. RESULTS: Results of rotation phantom, in vivo experiments, and implementation of three different MRI sequences, 2D spin echo, 3D gradient echo, and echo planar imaging, are presented. Finally, the proposed method is compared with the prospective motion correction software available on the scanner software. CONCLUSION: A prospective motion correction method that works in real time only by updating the FOV of the MR scanner is presented. Results show the feasibility of using an external optical motion-tracking system to compensate for strong and fast subject motion during acquisition.

Algorithms↗
PubMed2006

Integrated telemedicine applications and services for oncological positron emission tomography.

TENPET (Trans European Network for Positron Emission Tomography) aims to evaluate the provision of integrated teleconsultation and intelligent computer supported cooperative work services for clinical positron emission tomography (PET) in Europe at its current stage, as it is a multi-centre project financially supported by the European Commission (Information Society, eTEN Program). It addresses technological challenges by linking PET centres and developing supporting services that permit remote consultation between professionals in the field. The technological platform (CE-marked) runs on Win2000/NT/XP systems and incorporates advanced techniques for image visualization, analysis and fusion, as well as for interactive communication and message handling for off-line communications. Four PET Centres from Spain, France and Germany participate to the pilot system trials. The performance evaluation of the system is carried out via log files and user-filled questionnaires on the frequency of the teleconsultations, their duration and efficacy, quality of the images received, user satisfaction, as well as on privacy, ethical and security issues. TENPET promotes the co-operation and improved communication between PET practitioners that are miles away from their peers or on mobile units, offering options for second opinion and training and permitting physicians to remotely consult patient data if they are away from their centre. It is expected that TENPET will have a significant impact in the development of new skills by PET professionals and will support the establishment of peripheral PET units. To our knowledge, TENPET is the first telemedicine service specifically designed for oncological PET. This report presents the technical innovations incorporated in the TENPET platform and the initial pilot studies at real and diverse clinical environments in the field of oncology.

Artificial Intelligence↗
PubMed2005

Accuracy of biopsy needle navigation using the Medarpa system--computed tomography reality superimposed on the site of intervention.

The aim of this work was to determine the accuracy of a new navigational system, Medarpa, with a transparent display superimposing computed tomography (CT) reality on the site of intervention. Medarpa uses an optical and an electromagnetic tracking system which allows tracking of instruments, the radiologist and the transparent display. The display superimposes a CT view of a phantom chest on a phantom chest model, in real time. In group A, needle positioning was performed using the Medarpa system. Three targets (diameter 1.5 mm) located inside the phantom were punctured. In group B, the same targets were used to perform standard CT-guided puncturing using the single-slice technique. The same needles were used in both groups (15 G, 15 cm). A total of 42 punctures were performed in each group. Post puncture, CT scans were made to verify needle tip positions. The mean deviation from the needle tip to the targets was 6.65+/-1.61 mm for group A (range 3.54-9.51 mm) and 7.05+/-1.33 mm for group B (range 4.10-9.45 mm). No significant difference was found between group A and group B for any target (p>0.05). No significant difference was found between the targets of the same group (p>0.05). The accuracy in needle puncturing using the augmented reality system, Medarpa, matches the accuracy achieved by CT-guided puncturing technique.

Biopsy, Needle↗
PubMed2005

Prospective head motion compensation for MRI by updating the gradients and radio frequency during data acquisition.

Subject motion appears to be a limiting factor in numerous magnetic resonance imaging (MRI) applications. For head imaging the subject's ability to maintain the same head position for a considerable period of time places restrictions on the total acquisition time. For healthy individuals this time typically does not exceed 10 minutes and may be considerably reduced in case of pathology. In particular, head tremor, which often accompanies stroke, may render certain high-resolution 2D and 3D techniques inapplicable. Several navigator techniques have been proposed to circumvent the subject motion problem. The most suitable for head imaging appears to be the orbital or spherical navigator methods. Navigators, however, not only lengthen the measurement because of the time required for acquisition of the position information, but also require additional excitation radio frequency (RF) pulses to be incorporated into the sequence timing, which disturbs the steady state. Here we demonstrate the possibility of interfacing the MR scanner with an external optical motion tracking system, capable of determining the object's position with sub-millimeter accuracy and an update rate of 60Hz. The movement information on the object position (head) is used to compensate the motion in real time. This is done by updating the field of view (FOV) by recalculating the gradients and the RF-parameter of the MRI tomograph during the acquisition of k-space data based on the tracking data. Results of rotation phantom, in vivo experiments and the implementation in two different MRI sequences are presented.

Artifacts↗
PubMed2004

The compensation of head motion artifacts using an infrared tracking system and a new algorithm for fMRI.

We aim to provide a next generation Magnetic Resonance Imaging (MRI) technology with an integrated solution for reducing motion artifacts in brain imaging applications. New developments in the field of MRI are revolutionizing the diagnostic capabilities e.g. of functional (fMRI) of the technique. Unfortunately, motion artifacts are eminent problems in cerebral MRI images, especially in difficult patient populations (e.g. chronic pain, children, neonates). Patient motion artifacts are present in 2D sequences, but are extremely detrimental in multi-slice 3D sequences often employed in fMRI. The problem of motion compensation in MRI technology deals with: Identification of the source as well as pattern of motion. Obtaining a mathematical model of motion that can be used to identify and then compensate the motion effects. Optimizing the image acquisition sequence in order to minimize, or even eliminate, the effect of motion. We propose a method to obtain a quantitative measure of the movement of the head between different data acquisition points in both MRI, and functional MRI examination.

Algorithms↗