Name: how to measure cortical folding from mr images: a step-by-step tutorial to compute local gyrification index
Uploaded: 2012-01-02T13:00:00
Description: Watch this Scientific Journal Video about How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index at JoVE.com

This research was supported by the National Center of Competence in Research (NCCR) "SYNAPSY - The Synaptic Bases of Mental Diseases" financed by the Swiss National Science Foundation (n&deg; 51AU40_125759). Development of the local Gyrification Index was supported by grants from the Swiss National Research Fund to Dr. Marie Schaer (323500-111165) and to Dr. Stephan Eliez (3200-063135.00/1, 3232-063134.00/1, PP0033-102864 and 32473B-121996) and by the Center for Biomedical Imaging (CIBM) of the Geneva-Lausanne Universities and the EPFL, as well as the foundations Leenaards and Louis-Jeantet. Support for the development of FreeSurfer software was provided in part by the National Center for Research Resources (P41-RR14075, and the NCRR BIRN Morphometric Project BIRN002, U24 RR021382), the National Institute for Biomedical Imaging and Bioengineering (R01 EB001550, R01EB006758), the National Institute for Neurological Disorders and Stroke (R01 NS052585-01) as well as the Mental Illness and Neuroscience Discovery (MIND) Institute, and is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Additional support was provided by The Autism &amp; Dyslexia Project funded by the Ellison Medical Foundation.

1. Реконструкция 3D корковой поверхности Это первая часть протокола используется стандартный трубопровод FreeSurfer, как описано в вики ( <a href="http://surfer.nmr.mgh.harvard.edu/fswiki">http://surfer.nmr.mgh.harvard.edu/fswiki</a> ). Обратите внимание, что команды подробно описаны здесь описать один из способов д...

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Протокол выше описано, как для измерения местных Индекс Gyrification на основе мозговой Т1-взвешенной МРТ и проведения статистических сопоставлений группы. Наш метод был специально разработан для локализации раннего нарушения в корковых процесс расширения и, как таковая, представляют особ?...

Материал: Unix или Mac рабочей станции с процессором 2 ГГц и выше и как минимум 4 Гб оперативной памяти, с FreeSurfer установлен ( <a href="http://surfer.nmr.mgh.harvard.edu/fswiki">http://surfer.nmr.mgh.harvard.edu/fswiki</a> , желательно последнюю версию, но не старше чем версия 4.0.3). Для вычисления индекса местных Gyrification, MATLAB также требуется ( <a href="http://www.mathworks.ch/">http://www.mathworks.com/</a> ) вместе с Image Processing Toolbox. Данные: образец хорошего качества (с высоким разрешением, высокой контрастности) церебральной МРТ Т1-взвешенных данных. Ваша группа испытуемых должны быть предпочтительно по возрасту и полу. Учитывая нормальное между индивидуальной изменчивости в коре головного морфология, число испытуемых в каждой группе должно быть достаточно, чтобы идентифицировать существующее различие группы (больше - лучше). Разумный минимальный размер выборки будет около 20 человекв группе (хотя вы, вероятно, может пойти на меньше, если интенсивность изменений велик и если в группе плотно подобраны для пола и возраста). <table border="1"><tbody><tr><td> Наименование оборудования </td><td> Компания </td><td> Номер по каталогу </td><td> Комментарии </td></tr><tr><td> FreeSurfer </td><td> Martinos Центра биомедицинской визуализации, MGH </td><td></td><td> Версия новее, чем 4.0.3 </td></tr><tr><td> Matlab </td><td> Mathworks </td><td></td><td> Image Processing Toolbox </td></tr></tbody></table>

how to measure cortical folding from mr images: a step-by-step tutorial to compute local gyrification index

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name local Gyrification Index (lGI1), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6, our method was specifically designed to identify early defects of cortical development.
In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer Software (<a href="http://surfer.nmr.mgh.harvard.edu/">http://surfer.nmr.mgh.harvard.edu/</a>, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the lGI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.

Watch this Scientific Journal Video about How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index at JoVE.com

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Измерение gyrification (корковой складывающиеся) в любом возрасте представляет собой окно в раннем развитии мозга. Таким образом, мы ранее разработали алгоритм для измерения местных gyrification в тысячах точек по полушарии<sup&gt; 1</sup&gt;. В этой статье мы подробно вычисления этого локального индекса gyrification.

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Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will ...

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