Biomedical Image Technologies (BIT)

Research: Image-guided surgery & radiotherapy dosimetry

The aim is to contribute to surgery and radiotherapy planning, by means of image registration, image segmentation and Monte Carlo simulations.

Image processing techniques have been proposed to facilitate pre-surgical planning, intra-surgical decision making and intra-operative radiotherapy dosimetry.

Treatment Planning for Intraoperative Radiation Therapy

Intraoperative radiotherapy has the drawback that the computation of dosimetry cannot be done in advance, as the position of the tissues when applying the therapy cannot be accurately predicted.

To make feasible the therapy planning, we have worked in a fast method to compute radiation dose distribution with real images acquired during surgery. The method is based on a fast and customized Monte Carlo algorithm to compute dose distribution and has been integrated in radiance, GMV's treatment planning system.

Liver image-guided surgery

Essential parameters for liver surgery planning are the location of tumors, their position in relation to the vasculature and the volume of the remnant functional liver after the surgery. Automatic estimation of these parameters from preoperative CT or MRI studies aid surgeons to accurate plan hepatic surgery.

Image processing techniques (segmentation and registration) allows to obtain these parameters, combining information from both image modalities. In particular, we have proposed a new registration technique (organ-focused mutual information nonrigid multimodal registration) that is able to accurately combine liver anatomic CT with functional contrast-enhanced MRI.

Localization of epiloptogenic focus

The accurate localization of the epileptogenic focus in epileptic patients that do not respond to drug medication, is critical to guarantee success in surgery treatment. One technique commonly used for this localization is the subtraction of Ictal SPECT Co-registered to MRI (SISCOM). SISCOM involves the registration of ictal and inter-ictal SPECT, intensity normalization, subtraction and registration of the result to an anatomic MRI image

In collaboration with Hospital Clínic, we have developed a tool (FocusDet) to aid clinicians in the analysis of these images and to locate the epileptic focus. Its accuracy has been evaluated with Monte Carlo simulations

Collaborations

• Unidad de Medicina y Cirugía Experimental. Hospital G.U. Gregorio Marañón (Spain).
• Hospital Clínic de Barcelona.
• GMV Soluciones Globales Internet, S.A.U.

Some publications

(more can be found on the Publications page)

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• Goswami, S.S., Ortuño, J.E., Santos, A., Calvo, F.A., Pascau, J., Ledesma-Carbayo, M.J. "A New Workflow for Image-Guided Intraoperative Electron Radiotherapy Using Projection-Based Pose Tracking". IEEE Access, 8:137501-137516. 2020.
• Guerra, P., Udias, J.M., Herranz, E., Santos-Miranda, J., Herraiz, J., Valdivieso, M., Rodríguez, R., Calama, J., Pascau, J., Calvo, F., Illana, C., Ledesma-Carbayo, M.J., Santos, A. "Feasibility Assessment of the Interactive Use of a Monte Carlo Algorithm in Treatment Planning for Intraoperative Electron Radiation Therapy". Phys. Med. Biol., 59(23):7159-7179. 2014.
• Esteban, O., Wollny, G., Gorthi, S., Ledesma-Carbayo, M.J., Thiran, J.P., Santos, A., Bach-Cuadra, M. "MBIS: Multivariate Bayesian Image Segmentation". Comput. Meth. Programs Biomed., 115(2):76-94. 2014.
• Fernandez-de-Manuel, L., Wollny, G., Kybic, J., Jimenez-Carretero, D., Tellado, J.M., Ramon, E., Desco, M., Santos, A., Pascau, J., Ledesma-Carbayo, M.J. "Organ-Focused Mutual Information for Nonrigid Multimodal Registration of Liver CT and Gd-EOB-DTPA-enhanced MRI". Med. Image Anal., 18(1):22-35. 2014.
• Ortuño, J.E., Ledesma-Carbayo, M.J., Simões, R.V., Candiota, A.P., Arús, C., Santos, A. "DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data". BMC Bioinformatics, 14:316. 2013.
• Martí Fuster, B., Esteban, O., Planes, X., Aguiar, P., Crespo, C., Falcon, C., Wollny, G., Rubí Sureda, S., Setoain, X., Frangi, A.F., Ledesma, M.J., Santos, A., Pavía, J., Ros, D. "FocusDET, A New Toolbox for SISCOM Analysis. Evaluation of the Registration Accuracy Using Monte Carlo Simulation". Neuroinformatics, 11(1):77-89. 2013.
• Zöllner, F.G., Sance, R., Rogelj, P., Ledesma-Carbayo, M.J., Rørvik, J., Santos, A., Lundervold, A. "Assessment of 3D DCE-MRI of the kidneys using non-rigid image registration and segmentation of voxel time courses". Comput. Med. Imaging Graph., 33(3): 171-181. 2009.
• Pavlopoulos, S., Thireou, T., Kontaxakis, G., Santos, A. "Analysis and Interpretation of Dynamic FDG-PET Oncological Studies using Data Reduction Techniques". Biomed Eng Online, 6:36. 2007.
• Thireou, T., Pavlopoulos, S., Kontaxakis, Santos, A. "Blind Source Separation for the Computational Analysis of Dynamic Oncological PET Studies". Oncol Rep, 15: 1007-1012. 2006.
• Thireou, T., Strauss, L.G., Dimitrakopoulou-Strauss, A., Kontaxakis, G., Pavlopoulos, S., Santos, A. "Performance Evaluation of Principal Component Analysis in Dynamic FDG-PET Studies of Recurrent Colorectal Cancer". Comput. Med. Imaging Graph., 27(1): 43-51. 2003.