Biomedical subjects

Ion P I Pappas

Publications and source records attributed to Ion P I Pappas.

3 recordsLinked to original sources

PubMed2005

Improved targeting device and computer navigation for accurate placement of brachytherapy needles.

Successful treatment of skull base tumors with interstitial brachytherapy requires high targeting accuracy for the brachytherapy needles to avoid harming vital anatomical structures. To enable safe placement of the needles in this area, we developed an image-based planning and navigation system for brachytherapy, which includes a custom-made mechanical positioning arm that allows rough and fine adjustment of the needle position. The fine-adjustment mechanism consists of an XYZ microstage at the base of the arm and a needle holder with two fine-adjustable inclinations. The rotation axes of the inclinations cross at the tip of the needle so that the inclinational adjustments do not interfere with the translational adjustments. A vacuum cushion and a noninvasive fixation frame are used for the head immobilization. To avoid mechanical bending of the needles due to the weight of attached tracking markers, which would be detrimental for targeting accuracy, only a single LED marker on the tail of the needle is used. An experimental phantom-based targeting study with this setup demonstrated that a positioning accuracy of 1.4 mm (rms) can be achieved. The study showed that the proposed setup allows brachytherapy needles to be easily aligned and inserted with high targeting accuracy according to a preliminary plan. The achievable accuracy is higher than if the needles are inserted manually. The proposed system can be linked to a standard afterloader and standard dosimetry planning module. The associated additional effort is reasonable for the clinical practice and therefore the proposed procedure provides a promising tool for the safe treatment of tumors in the skull base area.

Bone Neoplasms↗

PubMed2005

Automatic method to assess local CT-MR imaging registration accuracy on images of the head.

BACKGROUND AND PURPOSE: Precise registration of CT and MR images is crucial in many clinical cases for proper diagnosis, decision making or navigation in surgical interventions. Various algorithms can be used to register CT and MR datasets, but prior to clinical use the result must be validated. To evaluate the registration result by visual inspection is tiring and time-consuming. We propose a new automatic registration assessment method, which provides the user a color-coded fused representation of the CT and MR images, and indicates the location and extent of poor registration accuracy. METHODS: The method for local assessment of CT-MR registration is based on segmentation of bone structures in the CT and MR images, followed by a voxel correspondence analysis. The result is represented as a color-coded overlay. The algorithm was tested on simulated and real datasets with different levels of noise and intensity non-uniformity. RESULTS: Based on tests on simulated MR imaging data, it was found that the algorithm was robust for noise levels up to 7% and intensity non-uniformities up to 20% of the full intensity scale. Due to the inability to distinguish clearly between bone and cerebro-spinal fluids in the MR image (T1-weighted), the algorithm was found to be optimistic in the sense that a number of voxels are classified as well-registered although they should not. However, nearly all voxels classified as misregistered are correctly classified. CONCLUSION: The proposed algorithm offers a new way to automatically assess the CT-MR image registration accuracy locally in all the areas of the volume that contain bone and to represent the result with a user-friendly, intuitive color-coded overlay on the fused dataset.

Algorithms↗

PubMed2002

Transcutaneous functional electrical stimulator "Compex Motion".

Research groups in the field of functional electrical stimulation (FES) are often confronted with the fact that existing and commercially available FES stimulators do not provide sufficient flexibility and cannot be used to perform different FES tasks. The lack of flexibility of the commercial systems until now forced various FES research teams to develop their own stimulators. This paper presents a newly developed firmware and graphical programming software for the commercial Compex 2 stimulator which enhances the versatility and capabilities of the stimulator from a medical and therapeutic device to a neuroprosthesis and research tool. The new stimulator, called Compex Motion, can now be used to develop various custom-made neuroprostheses, neurological assessment devices, muscle exercise systems, and experimental setups for physiological studies. It can be programmed to generate any arbitrary stimulation sequence that can be controlled or regulated by various external sensors, sensory systems, or laboratory equipment. By interconnecting two or more Compex Motion stimulators, the number of stimulation channels can be increased to multiples of four channels, 8, 12, 16, 20, and so forth. The stimulation sequences and the control strategies are programmed and stored on exchangeable credit card-sized memory chip cards. The stimulator has four biphasic current-regulated stimulation channels and two general purpose analog input channels that can be configured to measure the output voltage of a variety of sensors such as goniometers, inclinometers, gyroscopes, or electromyographic (EMG) sensors. For real-time EMG control of the stimulation patterns, an EMG processing algorithm with software stimulation artifact blanking was implemented. The Compex Motion stimulator is manufactured by the Swiss company Compex SA and is currently undergoing clinical trials.

Electric Stimulation Therapy↗