Development and optimization of tools for the study of human brain anatomical connectivity using high angular resolution diffusion MRI

Project Type: FONDECYT Initiation #11121644
Position: Principal Researcher
Award Year: 2012. Ending Year: 2015.

Descripción

This project sought to develop and optimize tools for the study and analysis of brain connectivity, using Difussion Magnetic Resonance Imaging (dMRI) data.

The studies are based on High Angular Resolution Difussion Imaging (HARDI) images.

These present very high quality, due to the advancement of acquisition technologies, as well as the acquisition itself (long duration, dedicated to research) and the performed post-processing, which seek to provide a solid base for the study of the healthy adult human brain.

The main results of this project contemplate:

  • The analysis of the reproducibility of short association fascicles of the brain, using data clustering tools and cortical parcellations.

  • The optimization of an algorithm for the segmentation of brain fibers, achieving times that allow an interactive segmentation (Principal Researcher: Professor Miguel Figueroa T.).

  • The development of a tool for the optimized visualization and manipulation of brain tracts.

Other interesting results are:

  • Development of a tool for the optimized visualization of tracts for Android devices (iFiber).

  • Creation of an atlas of short brain fascicles.

  • Development of algorithms for the comparison of brain tracts, between subjects and between hemispheres.

Undergraduate Theses related to the project

Student Thesis Defense Date
Ignacio Osorio W. Electronic Civil Engineering Thesis: “Software for the Interactive Visualization and Extraction of Brain Fibers” December 31st, 2015.
Danilo Bonometti B. Electronic Civil Engineering Thesis: “Visualization of Brain Fibers” April 1st, 2015.
Daniel Seguel B. Biomedical Civil Engineering Thesis: “Automatic Algorithm for the Segmentation of Short Association Fibers of the Human Brain” March 17th, 2015.
Claudio Román G. Biomedical Civil Engineering Thesis: “Short Brain Fibers Clustering Calculated from Difussion Magnetic Resonance Imaging Images” January 16th, 2015.
Miguel Guevara O. Biomedical Civil Engineering Thesis: “Algorithm for the Automatic Segmentation of Short Brain Fibers of the Fronto-Parietal Region and the Insular Cortex” January 16th, 2015.
Pablo L. Silva P. Biomedical Civil Engineering Thesis: “Parcellation of the Brain Cortex Based on the Anatomical Connectivity” May 29th, 2014.
Eduardo Venegas A. Electronic Civil Engineering Thesis: “Development of a software for the interactive manipulation of brain fibers” July 18th, 2014.
Nicole A. Labra A. Biomedical Civil Engineering Thesis: “Optimization of Algorithm for the Classification of White Matter Fibers based on the Brain Fascicles Atlas” April 30th, 2013.
Edison Pardo R. Electronic Civil Engineering Thesis: “Study of the Variability of the Connections of Short Association of the Human Brain” April 4th, 2013.
Gabriel E. Varela M. Biomedical Civil Engineering Thesis: “Calculation of Diffusion Tensor Indices from the Westin Algorithm” April 4th, 2013.

Postgraduate Theses related to the project

Student Thesis Defense Date
Claudio Román G. Master of Engineering Sciences w/m in Electrical Engineering.
“Segmentation of brain short brain fibers based on hierarchical Clustering from HARDI database”		 November 30th, 2016.
Miguel Guevara O. Master of Engineering Sciences w/m in Electrical Engineering.
“Parcellation of the brain cortex based on fiber atlas calculated from tractography”		 January 30th, 2016.
Nicole Labra A. Master of Engineering Sciences w/m in Electrical Engineering, (co-director)
“Quick segmentation of white substance brain fibers”		 January 28th, 2015.

Publications

2208, 2021

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

Schilling KG, Rheault F, Petit L, Hansen CB, Nath V, Yeh FC, Girard G, Barakovic M, Rafael-Patino J, Yu T, Fischi-Gomez E, Pizzolato M, Ocampo-Pineda M, Schiavi S, Canales-Rodríguez EJ, Daducci A, Granziera C, Innocenti G, Thiran JP, Mancini L, Wastling S, Cocozza S, Petracca M, Pontillo G, Mancini M, Vos SB, Vakharia VN, Duncan JS, Melero H, Manzanedo L, Sanz-Morales E, Peña-Melián Á, Calamante F, Attyé A, Cabeen RP, Korobova L, Toga AW, Vijayakumari AA, Parker D, Verma R, Radwan A, Sunaert S, Emsell L, De Luca A, Leemans A, Bajada CJ, Haroon H, Azadbakht H, Chamberland M, Genc S, Tax CMW, Yeh PH, Srikanchana R, Mcknight CD, Yang JY, Chen J, Kelly CE, Yeh CH, Cochereau J, Maller JJ, Welton T, Almairac F, Seunarine KK, Clark CA, Zhang F, Makris N, Golby A, Rathi Y, O'Donnell LJ, Xia Y, Aydogan DB, Shi Y, Fernandes FG, Raemaekers M, Warrington S, Michielse S, Ramírez-Manzanares A, Concha L, Aranda R, Meraz MR, Lerma-Usabiaga G, Roitman L, Fekonja LS, Calarco N, Joseph M, Nakua H, Voineskos AN, Karan P, Grenier G, Legarreta JH, Adluru N, Nair VA, Prabhakaran V, Alexander AL, Kamagata K, Saito Y, Uchida W, Andica C, Abe M, Bayrak RG, Wheeler-Kingshott CAMG, D'Angelo E, Palesi F, Savini G, Rolandi N, Guevara P, Houenou J, López-López N, Mangin JF, Poupon C, Román C, Vázquez A, Maffei C, Arantes M, Andrade JP, Silva SM, Calhoun VD, Caverzasi E, Sacco S, Lauricella M, Pestilli F, Bullock D, Zhan Y, Brignoni-Perez E, Lebel C, Reynolds JE, Nestrasil I, Labounek R, Lenglet C, Paulson A, Aulicka S, Heilbronner SR, Heuer K, Chandio BQ, Guaje J, Tang W, Garyfallidis E, Raja R, Anderson AW, Landman BA, Descoteaux M. Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset? Neuroimage. 243, p118502, 2021. DOI: https://doi.org/10.1016/j.neuroimage.2021.118502

2907, 2021

ABrainVis: an android brain image visualization tool

I. Osorio, M. Guevara, D. Bonometti, D. Carrasco, M. Descoteaux, C. Poupon, JF. Mangin, C. Hernández C, P. Guevara. ABrainVis: an android brain image visualization tool. Biomed Eng Online, 20:72, 2021. DOI: https://doi.org/10.1186/s12938-021-00909-0  

2207, 2021

Opinion piece on first gender equality policy in science and technology

Opinion piece written by professor Pamela Guevara, published in El Mostrador newspaper and in RevistaEI magazine, about the first gender equality policy in science and technology: "A greater participation of women and further positioning of their leading role in sciences and technology can contribute to girls and young women to feel secure and motivated to project themselves in CTCI (Science, Technology, Knowledge, and Innovation) areas". Read the full column in the following sites (only in Spanish): El Mostrador newspaper y RevistaEI magazine.

2705, 2021

Professor Guevara joins the Group of Principal Investigators at AC3E

Starting May 2021, Dr. Pamela Guevara is a Principal Researcher at the Advanced Center for Electrical and Electronic Engineering (AC3E), in charge of the Biomedical Systems research line. Regarding the achievement, the professor commented: “It is an honour to be part of a group of prominent researchers that contribute to excellence research in different areas, and who form a very pleasant group of people. It is a great challenge to continue generating quality research, lead our research lines and empowering ourselves of this new position in benefit of the Center, creating initiatives to improve the synergy and productivity”. Along with professor Guevara, Dr. Margarita Norambuena also joins the Group of Principal Investigators at AC3E, in charge of the Electrical Systems research line. This is the first time that the AC3E has two female principal investigators, which represents a very important milestone that highlights the ever-growing leading role of women in science and engineering. On this, the director of the center, Dr. Matías Zañartu, stated: “Our new female principal investigators will be an important reference, from their leadership positions in a research center such as the AC3E, and a role model for all  female students. They will have a leading role in helping us to break the paradigm that electrical and electronic engineering is just for men”. Read the full article at the following link (in Spanish).

2502, 2021

Investigating Superficial White Matter Integrity in Early MS Using Machine Learning

Buyukturkoglu Korhan, Valentina Fuentealba, Christopher Vergara, Ceren Tozlu, Jacob B. Dahan, Britta E. Carroll, Carlos Guevara Oliva, Amy Kuceyeski, James F. Sumowski, Ranganatha Sitaram, Pamela Guevara. Investigating Superficial White Matter Integrity in Early MS Using Machine Learning. ACTRIMS FORUM 2021, USA, Virtual event, 2021. DOI: not available yet.

News

2018-11-10T18:32:47-03:00

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