Original article

Brain Fascicles Volumetry in Healthy Population

José Fernando Hernández1 Leonardo Bello-Dávila1 Sergio Francisco Ramírez1 Jorge Marin1 Jorge Rudas2 Edgar G. Ordóñez-Rubiano1 Jenny Vicuña Vanegas1

1 Hospital Universitario Infantil de San José, Bogotá, Colombia 2 Department of Sciences, National University of Colombia, Bogotá, Colombia.

Abstract Objective The advent of has facilitated the study of , as it is a noninvasive technique based on the well-known magnetic resonance imaging (MRI). This has allowed great discoveries as regards brain fascicles involved in cognitive functions. However, the assessment continues to be subjective and depends on the evaluator’s experience and training. For this reason, its applicability to clinical practice has been limited. In this respect, it is advisable to set standard parameters of cerebral white matter volumes in the healthy population through an electronic, reproducible tool so that it can be applied in patients. Materials and Methods The study was conducted in ten neurologically healthy subjects. Diffusion-weighted images were acquired for each subject and the results were visualized using the FiberNavigator tool (http://scilus.github.io/ fibernavigator). Finally, this same tool was used to purify the fascicles under study and perform the fiber count. Results Volumetric values of the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF) and cingulate fasciculus (CF) were obtained. No statistically significant differences were found in the number of fibers that make up the cerebral fascicles. Discussion The results obtained about the anatomy and directionality of fibers in brain fascicles in this study are con- sistent with all other reports published to date, and no differences have been found as regards their organization and trajectory. Conclusion Although these results cannot be used as reference values for their application in patients with neurological conditions, we are providing information that was unavailable to date with this specific equipment and reproducibility among different users and software.

Keywords anisotropy, cognition, diffusion tensor imaging, diffusion tractography, white matter

Introduction sential supporting diagnostic tool for neuroradiology.4 These evaluations led to identify that the integrity of white matter is Recent research has described different tracts that associate associated with the preservation of cognitive activities.5 multiple cortical regions, which is the basis of human cogni- Tractography is a noninvasive study that allows an assess- tion.1 This has led investigators to focus their studies on the ment of the integrity of long tracts. Thus, it became useful analysis of the underlying phenomena of white matter, con- in neurosurgery for surgical planning and for reducing post- sidering that subcortical networks are not accurately known. operative sequels, with gliomas and the corticospinal tract Advances in magnetic resonance imaging (MRI) have led to being most frequently evaluated.6,7 Publications on DTI make a better understanding of the structure and function of the reference to neurological conditions involving some kind of brain, enabling the isolation of tracts involved in cognitive abnormality in white matter tracts. This is the case of tem- processes.2 Since the advent of Diffusing Tensor Imaging poral lobe epilepsy, where decreased fractional anisotropy (DTI), the usefulness of this technique in neuroradiology has (FA) of the superior longitudinal fasciculus (SLF) has been ob- not been questioned, as it represents the vector sum of water served, and of Alzheimer’s disease, where FA is decreased in molecules, providing a graphic directionality of axons, repre- the right uncinate fasciculus (UF) as compared to the left.8,9 sented in colors as in the anisotropy map.3 Thus, tractography Nevertheless, the tractography assessment is usually subjec- is the 3D representation of DTI, which allows visualization tive and dependent on the training of the clinical personnel of the subcortical cerebral trajectory and has become an es- involved. In addition, it is often the case that no normality

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parameters (tract volumes, lengths, etc.) are available, which and the tractography was generated using a deterministic are required as benchmarks for comparison in population fiber tracking algorithm based on EuDX on a tensor field. studies. Based on the above, there is a need to standardize values in the healthy population. For this reason, we pres- Visualization ent the volumetric analysis of the most important cerebral The FiberNavigator tool was used for visualization and man- fascicles involved in cognitive functions in healthy subjects. ual parcellation of each tract.10 Location of the regions of interest (ROIs) was based on the atlas by Wakana et al.11 Fiber counting was performed using the FiberNavigator ellipsoid Materials and methods and cuboid tool, which ensures counting the highest number of white matter fibers that make up the fascicle. The study was conducted in 10 subjects aged 18 to 51 years old The average tract volume and FA was determined by calculat- (seven men and three women) who were neurologically healthy ing the arithmetic mean, which is the sum of all values of the (normal Montreal Cognitive Assessment [MoCA] test results) tract in each hemisphere divided by the number of subjects. and had no symptoms or history of disease. All subjects un- The statistical analysis was performed by a nonparametric derwent a brain MRI with tractography, which was reported as test for two independent samples. Specifically, the Mann- normal and read by a neuroradiologist trained in this technique. Whitney U test was used, with a level of confidence of at least 5%. This test does not consider any a priori assump- Image acquisition tion regarding the distribution or nature of data. Research A complete MRI study was performed on a 1.5 Tesla scan- was performed in compliance with international guidelines ner (Signa Excite HDXT, GE Healthcare, Milwaukee, WI, USA) related to recommendations for research involving human with a head coil. For each subject, the following sequences subjects stated in the Declaration of Helsinki (latest version, were obtained: 1) T1-weighted sequence; 2) axial T-2 weight- Brazil 2013) and the Belmont Report. Accordingly, all patients ed sequence; 3) diffusion-weighted sequence (DWI). Each signed an informed consent approved by the ethics commit- T1-weighted structural image has 140 slices (1 mm thickness tee of the University Foundation of Health Sciences. and no gap between slices, 320 x 192 matrix, TR = 650 ms, TE = 22 ms, FOV = 22) and acquisition time = 2 min and 35 seconds, covering the entire brain volume. T2-weighted Results structural images contain 22 slices (6 mm thickness with a slice gap of 1 mm, matrix = 320 x 256, TR = 6000 ms, TE = Isolation of 100 white matter tracts was achieved in 10 97.44 ms, FOV = 24) and acquisition time = 1 min and 20 healthy subjects by DWI. The FA and a volumetric value were seconds, covering the entire brain volume. Each DWI has 30 obtained for the following cerebral fascicles in each hemi- slices (2 mm thickness, with no gap between slices, matrix = sphere: superior longitudinal fasciculus (SLF), inferior lon- 128 x 128, TR = 1000, TE = 102.3 ms, flip angle = 90) with gitudinal fasciculus (ILF), inferior fronto-occipital fasciculus 24 directions with echo-planar imaging (EPI) and acquisition (IFOF), uncinate fasciculus (UF) and cingulate fasciculus (CF). time = 6 min, covering the entire brain volume. As regards FA values reported in Table 1, there were no inter- hemispheric tract differences above 0.03, and differences in Preprocessing mean values did not exceed this threshold either; therefore, Initially, DWI sequences were adjusted to remove artifacts no statistically significant differences were found. from acquisition and standardize measurements, by applying Tractography allowed counting of each of the fibers that the following sequence of steps: manual alignment between make up the tract; thus, the volume of the cerebral fascicle DWI and T1, reslice of DWI sequences to obtain isometric under study could be obtained, in addition to a mean value voxels, co-registration between diffusion and structural im- reported in Table 2. Such mean values showed great inter- age, Eddy-current correction (https://fsl.fmrib.ox.ac.uk/fsl/ hemispheric volumetric differences in the same fascicle (for fslwiki/eddy), brain extraction and denoising using the non- example: RIFOF: 526 and LIFOF: 575), but in the statistical local-means algorithm (http://nipy.org/dipy/examples_built/ analysis of results, no statistically significant differences were denoise_nlmeans.html). found, neither in volume nor in FA. In this respect, it should be highlighted that although some fascicles showed great Postprocessing differences in the arithmetic mean (mean value of each tract) After preprocessing and in order to compute the tractogra- reported in Table 2, this value is not appropriate to record sta- phy derived from DWI, the diffusion tensor model was esti- tistically significant volumetric differences, as this statistical mated, the AF and mean diffusivity maps were generated, measurement is affected by extreme values of distribution.

96 Rev. Argent. Radiol. 2019;83(3): 95-101 José Fernando Hernández et al.

Table 1: Fractional anisotropy of brain fascicles

Subject Gender RSLF LSLF RILF LILF RIFOF LIFOF RUF LUF RCF LCF

1 M 0.43 0.48 0.51 0.51 0.43 0.4 0.47 0.47 0.47 0.45 2 F 0.59 0.62 0.51 0.49 0.48 0.45 0.45 0.46 0.41 0.38 3 M 0.43 0.45 0.54 0.54 0.48 0.46 0.48 0.49 0.41 0.38 4 F 0.43 0.42 0.49 0.49 0.46 0.45 0.31 0.33 0.41 0.42 5 F 0.41 0.42 0.52 0.52 0.45 0.43 0.51 0.52 0.46 0.42 6 M 0.48 0.48 0.41 0.39 0.34 0.31 0.41 0.41 0.45 0.44 7 M 0.51 0.52 0.52 0.51 0.44 0.47 0.45 0.48 0.5 0.48 8 M 0.48 0.45 0.52 0.52 0.44 0.42 0.52 0.54 0.42 0.44 9 M 0.51 0.53 0.47 0.47 0.44 0.46 0.52 0.53 0.43 0.45 10 M 0.46 0.48 0.49 0.51 0.48 0.48 0.51 0.51 0.45 0.42

Abbreviations: F, female; LCF, left cingulate fasciculus; LIFOF, left inferior fronto-occipital fasciculus; LILF, left inferior longitudinal fasciculus; LSLF, left superior longitudinal fasciculus; LUF, left uncinate fasciculus; M, male; RCF, right cingulate fasciculus; RIFOF, right inferior fronto- occipital fasciculus; RILF, right inferior longitudinal fasciculus; RSLF, right superior longitudinal fasciculus; RUF, right uncinate fasciculus.

Table 2: Brain fascicles fiber count

Subject Gender RSLF LSLF RILF LILF RIFOF LIFOF RUF LUF RCF LCF

1 M 597 538 1144 1169 520 617 314 216 625 570 2 F 557 568 905 936 512 610 296 244 425 510 3 M 562 575 921 934 472 574 333 293 510 580 4 F 520 533 935 944 580 623 244 350 530 564 5 F 542 567 980 995 543 577 288 296 435 467 6 M 556 570 1055 1050 412 464 306 318 607 416 7 M 532 551 907 922 580 645 276 252 623 645 8 M 556 580 1009 940 474 511 303 230 895 970 9 M 524 518 895 975 592 571 329 353 656 687 10 M 588 560 966 990 579 564 316 322 613 640 Average 553.40 556 971.7 985.5 526.4 575.6 300.5 287.4 591.9 604.9

Superior longitudinal fasciculus Table 3: Statistical differences by Mann-Whitney test As regards the anatomical distribution of this tract, its fibers run towards the inferior , passing through the pa- Tract count rietal lobe and ending in the superior . In the RSLF – LSLF - > p=0.311522465419 RILF – LILF - > p = 0.21367765694890384 anterior frontal region, the SLF converges with the UF and the RIFOF – LIFOF - > p = 0.0928556402224 IFOF, which makes isolation of its fibers difficult in this area; RUF – LUF - > p = 0.338677972903 therefore, the seed point was placed in a more posterior lo- RCF – LCF - > p = 0.469860183474 cation in its frontal trajectory. Using the anisotropy map on a coronal slice as a reference to determine the directionality of Fractional Anisotropy RSLF – LSLF - > p= 0.337225774999 fibers, the SLF was seeded using a two-ROI approach. Figure RILF – LILF - > p = 0.423562261019 1 shows a sagittal view of this fasciculus for an improved RIFOF – LIFOF - > p = 0.310067765958 visualization of its trajectory. RUF – LUF - > p = 0.271762914193 RCF – LCF - > p = 0.270685104777

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Fig. 1 Left SLF on a FA map in sagittal view. With the cuboid Fig. 2 Left ILF on a FA map in sagittal view. With the cuboid technique, a two-ROI approach was used for seeding, with technique, a two-ROI approach was used for seeding, with the first ROI being placed in the frontal region and the sec- the first ROI being placed in the temporal region and the sec- ond one in the temporal region. ond one in the occipital region.

Fig. 3 Left IFOF on a FA map in sagittal view. With the cuboid Fig. 4 Right UF on a FA map in sagittal view. With the ellipsoid technique, a two-ROI approach was used for seeding, with technique, a two-ROI approach was used for seeding, with the first ROI being placed in the inferior frontal region and the the first ROI being placed in the inferior frontal region and the second one in the occipital region. second one in the superior temporal region.

Inferior longitudinal fasciculus Fronto-occipital fasciculus This association tract has two portions: a surface portion and These white matter fibers connect the occipital lobe to the a deep portion connecting the anterior pole of the temporal frontal lobe, running from the pole of the occipital cortex lobe with the cortical termination of the occipital lobe, where through the temporal lobe to end in the orbitofrontal and it blends with fibers of the IFOF. Identification of this fascicle frontopolar areas. This fasciculus was isolated on an anisot- was achieved by seeding using a two-ROI approach on a sag- ropy map with axial slice using a two-ROI approach for seed- ittal slice, displayed on a fractional anisotropy map that al- ing. Figure 3 provides full visualization of fiber tract direction lows visualization of white matter fibers trajectories (Fig. 2). on a sagittal slice.

98 Rev. Argent. Radiol. 2019;83(3): 95-101 José Fernando Hernández et al.

in a healthy population, which implies a thorough knowledge of DTI neuroanatomy to be able to reproduce the study by this technique, as well as an optimal knowledge of the electronic tool used. Subjects older than 65 were not included in our sample because aging has been associated with a cognitive decline due to changes in the cerebral white matter.14,15 No right or left hemispheric dominance of white matter was identified from a structural viewpoint, beyond the functional dominance related to specialized areas of the cortex in the left hemisphere --already reported in the literature--, since the statistical analysis of findings impedes such an assertion. However, in the language connectome study in which eight white matter fascicles were quantified in 20 healthy male subjects, a leftward asymmetry in volume was found for the arcuate fascicle, IFOF and middle longitudinal fascicle, in ad- dition to extensive cortical connections, which may imply that they are not exclusively involved in language processing, but Fig. 5 Right CF on a FA map in sagittal view. With the cuboid support other cognitive skills.16 Conversely, the study con- technique, a two-ROI approach was used for seeding in the 17 frontal region. ducted by Thiebaut et al. in 40 healthy subjects, reported statistically significant rightward asymmetry for the arcuate fascicle and the IFOF. These inconsistent results may be due to differences in the equipment and techniques used for trac- Uncinate fasciculus tography and, for this reason, no conclusion can be drawn as The fibers of the uncinate fasciculus, so named because of regards gender (male-female) differences, although Thiebaut its hook shape and also known as frontotemporal fasciculus, et al confirmed in their study a greater leftward asymmetry connect in a bidirectional manner the anterior pole of the su- for the arcuate fascicle in men. In addition, using the DTI perior temporal lobe to the orbitofrontal area. Two ROIs were technique, higher fractional anisotropy has been found in placed on coronal planes on an anisotropy map and isolation men, especially in the SLF and ILF.18 of the UF is depicted in Figure 4, but on a sagittal plane, so Hence, so far tractography cannot be considered as a fully that the hook shape can be seen. reliable method for the evaluation of white matter, consider- ing the heterogeneity of pathologies, inter-individual differ- Cingulate fasciculus ences and the new tractography algorithms that may provide Being part of the , this fascicle has U-shaped some advantage over the previous ones, as in the case of Al- and projection fibers. The former follow the course of the zheimer’s disease, where diagnostic accuracy varies in a single whole cingulate gyrus forming an arch, connecting areas of subject by applying nine tractography algorithms.19, 20 the prefrontal lobe to the parahippocampal area, reaching Based on the above, there are two limitations to this study. The the uncus of the temporal lobe. The U fibers extend from the first is the small sample size, which does not allow us to make subcallosal area and connect the frontal, parietal, occipital assertions about volumetric differences related to gender, age and temporal lobes. The two ROIs for this fascicle were ob- or other demographic characteristics. However, we highlight tained on a sagittal slice of the anisotropy map (Fig. 5). the difficulty of performing tractography in healthy subjects, considering the healthcare system needs and limitations, which do not allow large investments in the healthy population. Discussion Furthermore, the manual placement of seed points does not ensure inclusion of 100% of the white matter fibers that The results obtained about the anatomy and fiber direction of make up the fascicle. However, using the ellipsoid and cuboid the brain fascicles in this study are in agreement with all other glyphing technique of the FiberNavigator tool, the maximum reports published to date, and no differences were found as number of fibers could be obtained and, more importantly, regards their organization and trajectory.12,13 The five fascicles with the selected ROIs neither the trajectory nor the symme- evaluated in this study were selected because they are the try of the tract were lost. most widely studied and involved in cognitive functions. We In addition, no tool was available in this study for visualization emphasize the fact of being able to isolate 100 tracts manually of cortical terminations of each fascicle evaluated so that a

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