弥散张量纤维成像检测大脑半球弓形束曲率

doi:10.3969/j.issn.1673-5374.2013.03.006

摘要/Abstract

摘要：

由于弓形束连接大脑布洛卡区和韦尼克区，因此研究失语症患者弓形束解剖定位和计量信息对于该病的治疗有重要意义。我们应用弥散张量纤维束成像检测12例健康人双侧大脑半球弓形束水平和垂直屈曲率。健康人右侧大脑半球直接和间接弓形束水平屈曲率分别是121.13 ± 5.89和25.99 ± 3.01；左侧大脑半球直接和间接弓形束水平屈曲率分别是121.83 ± 5.33和27.40 ± 2.96。健康人右侧大脑半球直接和间接弓形束垂直屈曲率分别是43.97 ± 7.98和30.15 ± 3.82；左侧大脑半球直接和间接弓形束垂直屈曲率分别是39.39 ± 4.42和24.08 ± 4.34。实验为弓形束疾病患者特殊神经通路的定位和定量评估提供了重要数据。

关键词: 神经再生, 神经影像, 临床实践, 弥散张量纤维束成像, 弥散张量成像, 弓形束, 直接屈曲率, 间接屈曲率, 解剖定位, 定量信息, 失语症, 布洛卡区, 韦尼克区, 弓形纤维, 基金资助文章, 图片文章

Abstract:

Because Broca’s area and Wernicke’s area in the brain are connected by the arcuate fasciculus, understanding the anatomical location and morphometry of the arcuate fasciculus can help in the treatment of patients with aphasia. We measured the horizontal and vertical curvature ranges of the arcuate fasciculus in both hemispheres in 12 healthy subjects using diffusion tensor tractography. In the right hemisphere, the direct curvature range and indirect curvature range values of the arcuate fasciculus horizontal part were 121.13 ± 5.89 and 25.99 ± 3.01 degrees, respectively, and in the left hemisphere, the values were 121.83 ± 5.33 and 27.40 ± 2.96 degrees, respectively. In the right hemisphere, the direct curvature range and indirect curvature range values of the arcuate fasciculus vertical part were 43.97 ± 7.98 and 30.15 ± 3.82 degrees, respectively, and in the left hemisphere, the values were 39.39 ± 4.42 and 24.08 ± 4.34 degrees, respectively. We believe that the measured curvature ranges are important data for localization and quantitative assessment of specific neuronal pathways in patients presenting with arcuate fasciculus abnormalities.

Key words: neural regeneration, neuroimaging, clinical practice, diffusion tensor tractography, diffusion tensor imaging, arcuate fasciculus, direct curvature range, indirect curvature range, anatomical location, quantitative information, aphasia, Broca’s area, Wernicke’s area, arched fiber, grant-supported paper, photographs-containing paper, neuroregeneration

. 弥散张量纤维成像检测大脑半球弓形束曲率[J]. 中国神经再生研究(英文版), 2013, 8(3): 244-250.

Dong Hoon Lee, Cheol Pyo Hong, Yong Hyun Kwon, Yoon Tae Hwang, Joong Hwi Kim, Ji Won Park. Curvature range measurements of the arcuate fasciculus using diffusion tensor tractography[J]. Neural Regeneration Research, 2013, 8(3): 244-250.

参考文献

[1] Bernal B, Ardila A. The role of the arcuate fasciculus in conduction aphasia. Brain. 2009;132:2309-2316.http://brain.oxfordjournals.org/content/132/9/2309.abstract

[2] Glasser MF, Rilling JK. DTI tractography of the human brain's language pathways. Cereb Cortex. 2008;18:2471-2482.http://cercor.oxfordjournals.org/content/18/11/2471.long

[3] Catani M, Jones DK, ffytche DH. Perisylvian language networks of the human brain. Ann Neurol. 2005;57:8-16.http://dx.doi.org/10.1002/ana.20319

[4]   Hagmann P, Cammoun L, Martuzzi R, et al. Hand preference and sex shape the architecture of language networks. Hum Brain Mapp. 2006;27:828-835.http://onlinelibrary.wiley.com/doi/10.1002/hbm.20224/abstract

[5]   Nucifora PG, Verma R, Mlehem ER, et al. Leftward asymmetry in relative fiber density of the arcuate fasciculus. Neuroreport. 2005;16:791-794.http://meta.wkhealth.com/pt/pt-core/template-journal/lwwgateway/media/landingpage.htm?issn=0959-4965&volume=16&issue=8&spage=791

[6] Hong JH, Kim SH, Ahn SH, et al. The anatomical location of the arcuate fasciculus in the human brain: a diffusion tensor tractography study. Brain Res Bull. 2009;80:52-55.http://www.sciencedirect.com/science/article/pii/S0361923009001439

[7] Diehl B, Piao Z, Tkach J, et al. Cortical stimulation for language mapping in focal epilepsy: correlations with tractography of the arcuate fasciculus. Epilepsia. 2010;51:639-646.http://dx.doi.org/10.1111/j.1528-1167.2009.02421.x

[8] Duffau H, Capelle L, Sichez N, et al. Intraoperative mapping of the subcortical language pathways using direct stimulations. An anatomo-functional study. Brain. 2002;125:199-214.http://brain.oxfordjournals.org/content/125/1/199.long

[9] Duffau H, Gatignol P, Denvil D, et al. The articulatory loop: study of the subcortical connectivity by electrostimulation. Neuroreport. 2003;14:2005-2008.http://pt.wkhealth.com/pt/re/lwwgateway/landingpage.htm;jsessionid=Q8NHCslnjlwYy1zlbvjJQSptslHcGD2YKvM6RQHnnc6LjnkJpLzS!458665271!181195629!8091!-1?issn=0959-4965&volume=14&issue=15&spage=2005

[10]   Kim SH, Lee DG, You H, et al. The clinical application of the arcuate fasciculus for stroke patients with aphasia: a diffusion tensor tractography study. NeuroRehabilitation. 2011;29:305-310.http://pt.wkhealth.com/pt/re/lwwgateway/landingpage.htm;jsessionid=Q7QJhpZGZq7pw2DdlMl761QHhPZPMh4yn3c5PPJDJlPnQ1YdHpXQ!458665271!181195629!8091!-1?issn=0959-4965&volume=14&issue=15&spage=2005

[11]   Matsumoto R, Nair DR, LaPresto E, et al. Functional connectivity in the human language system: a cortico-cortical evoked potential study. Brain. 2004;127:2316-2330.http://brain.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=15269116

[12] Selnes OA, van Zijl PC, Barker PB, et al. MR diffusion tensor imaging documented arcuate fasciculus lesion in a patient with normal repetition performance. Aphasiology. 2002;16:897-902.http://www.tandfonline.com/doi/abs/10.1080/02687030244000374#preview

[13] Powell HW, Parker GJ, Alexander DC, et al. Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. NeuroImage. 2006;32:388-399.http://linkinghub.elsevier.com/retrieve/pii/S1053-8119(06)00176-5

[14] Vernooij MW, Smits M, Wielopolski PA, et al. Fiber density asymmetry of the arcuate fasciculus in relation to functional hemispheric language lateralization in both right- and left-handed healthy subjects: a combined fMRI and DTI study. NeuroImage. 2007;35:1064-1076.http://www.sciencedirect.com/science/article/pii/S1053811906012134

[15]   Makris N, Kennedy DN, McInerney S, et al. Segmentation of subcomponents within the superior longitudinal fascicle in humans: a quantitative, in vivo, DT-MRI study. Cereb Cortex. 2005;15(6):854-869. http://cercor.oxfordjournals.org/content/15/6/854.long

[16]   Jeong JW, Sundaram SK, Kumar A, et al. Aberrant diffusion and geometric properties in the left arcuate fasciculus of developmentally delayed children: a diffusion tensor imaging study. Am J Neuroradiol. 2011;32:323-330.http://www.ajnr.org/content/32/2/323.long

[17]   Mori S, Crain BJ, Chacko VP, et al. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol. 1999;45:265-269.http://www.ncbi.nlm.nih.gov/pubmed/9989633

[18] Zhang W, Li X, Zhang J, et al. Landmark-referenced voxel-based analysis of diffusion tensor images of the brainstem white matter tracts: application in patients with middle cerebral artery stroke. NeuroImage. 2009;44:906-913.http://www.sciencedirect.com/science/article/pii/S1053811908009853

[19] Mori S, van Zijl PC. Fiber tracking: principles and strategies - a technical review. NMR Biomed. 2002;15:468-480.http://dx.doi.org/10.1002/nbm.781

[20] Jiang H, van Zijl PC, Kim J, et al. DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Programs Biomed. 2006;81:106-116.http://linkinghub.elsevier.com/retrieve/pii/S0169-2607(05)00234-8

[21] Blumenfeld-Katzir T, Pasternak O, Dagan M, et al. Diffusion MRI of structural brain plasticity induced by a learning and memory task. PLoS One. 2011;6:e20678.http://dx.plos.org/10.1371/journal.pone.0020678

[22] Leergaard TB, White NS, de Crespigny A, et al. Quantitative histological validation of diffusion MRI fiber orientation distributions in the rat brain. PLoS One. 2010;5:e8595.http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0008595

[23] Razek AA. Diffusion-weighted magnetic resonance imaging of head and neck. J Comput Assist Tomogr. 2010;34:808-815.http://pt.wkhealth.com/pt/re/lwwgateway/landingpage.htm;jsessionid=Q7ZN6MzpvvS2b53TDhn7wp9nQyyLNT8MGTp6y2ytLBsK2R3tmKXS!-1375816324!181195628!8091!-1?issn=0363-8715&volume=34&issue=6&spage=808

[24]   Hong JH, Son SM, Jang SH. Identification of spinothalamic tract and its related thalamocorical fibers in human brain. Neurosci Lett. 2010;468:102-105.http://linkinghub.elsevier.com/retrieve/pii/S0304-3940(09)01420-7

[25]   Assaf Y, Pasternak O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. J Mol Neurosci. 2008;34:51-61.http://dx.doi.org/10.1007/s12031-007-0029-0

[26]   Jiang S, Liu M, Han T, et al. Diffusion tensor imaging with multiple diffusion-weighted gradient directions. Neural Regen Res. 2011;6:66-71.http://linkinghub.elsevier.com/retrieve/pii/S1090-7807(98)91673-1

[27]   Kunimatsu A, Aoki S, Masutani Y, et al. The optimal trackability threshold of fractional anisotropy for diffusion tensor tractography of the corticospinal tract. Magn Reson Med Sci. 2004;3:11-17.https://www.jstage.jst.go.jp/article/mrms/3/1/3_1_11/_article

[28]   Kwon HG, Jang SH. Excellent recovery of aphasia in a patient with complete injury of the arcuate fasciculus in the dominant hemisphere. NeuroRehabilitation. 2011;29:401-404.http://iospress.metapress.com/content/9031r775x1842351/?genre=article&issn=1053-8135&volume=29&issue=4&spage=401

[29]   Jellison BJ, Field AS, Medow J, et al. Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am J Neuroradiol. 2004;25:356-369.http://www.ajnr.org/content/25/3/356.long

[30]   Stieltjes B, Kaufmann WE, van Zijl PC, et al. Diffusion tensor imaging and axonal tracking in the human brainstem. Neuroimage. 2001;14:723-735.http://www.sciencedirect.com/science/article/pii/S1053811901908614

[31]   Wakana S, Jiang H, Nagae-Poetscher LM, et al. Fiber tract-based atlas of human white matter anatomy. Radiology. 2004;230:77-87.http://radiology.rsna.org/content/230/1/77.long

[32]   Beaulieu C. The basis of anisotropic water diffusion in the nervous system: a technical review. NMR Biomed. 2002;15:435-455.http://onlinelibrary.wiley.com/doi/10.1002/nbm.782/abstract

[33]   Conturo TE, Lori NF, Cull TS, et al. Tracking neuronal fiber pathways in the living human brain. Proc Natl Acad Sci USA. 1999;96:10422-10427.http://www.pnas.org/content/96/18/10422.long

[34]   Poupon C, Clark CA, Frouin V, et al. Regularization of diffusion-based direction maps for the tracking of brain white matter fascicules. Neuroimage. 2000;12:184-195.http://www.sciencedirect.com/science/article/pii/S1053811900906074

[35]   Jones DK, Simmons A, Williams SC, et al. Non-invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI. Mag Reson Med. 1999;42:37-41.http://dx.doi.org/10.1002/(SICI)1522-2594(199907)42:1%3C37::AID-MRM7%3E3.0.CO;2-O

[36]   Upadhyay J, Hallock K, Ducros M, et al. Diffusion tensor spectroscopy and imaging of the arcuate fasciculus, Neuroimage. 2008;39:1-9.http://www.sciencedirect.com/science/article/pii/S1053811907007756

[37] Kwon HG, Byun WM, Ahn SH, et al. The anatomical characteristics of the stria terminalis in the human brain: a diffusion tensor tractography study. Neurosci Lett. 2011;500:99-102.http://www.sciencedirect.com/science/article/pii/S0304394011009074

[38] Yang HS, Kwon HG, Hong JH, et al. The rubrospinal tract in the human brain: diffusion tensor imaging study. Neurosci Lett. 2011;504:45-48.http://linkinghub.elsevier.com/retrieve/pii/S0304-3940(11)01249-3

[39]   Catani M, Mesulam M. The arcuate fasciculus and the disconnection theme in language and aphasia: history and current state. Cortex. 2008;44:953-961.http://linkinghub.elsevier.com/retrieve/pii/S0010-9452(08)00111-1

[40]   Parker GJ, Luzzi S, Alexander DC, et al. Lateralization of ventral and dorsal auditory-language pathways in the human brain. Neuroimage. 2005;24:656-666.http://linkinghub.elsevier.com/retrieve/pii/S1053-8119(04)00510-5

[41]   Hayashi Y, Kinoshita M, Nakada M, et al. Correlation between language function and the left arcuate fasciculus detected by diffusion tensor imaging tractography after brain tumor surgery. J Neurosurg. 2012;117(5):839-843. http://thejns.org/doi/abs/10.3171/2012.8.JNS12348?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed&

[42]   Matsumoto R, Okada T, Mikuni N, et al. Hemispheric asymmetry of the arcuate fasciculus: a preliminary diffusion tensor tractography study in patients with unilateral language dominance defined by Wada test. J Neurol. 2008;255:1703-1711.http://link.springer.com/article/10.1007%2Fs00415-008-0005-9

[43]   Zhang Y, Wang C, Zhao X, et al. Diffusion tensor imaging depicting damage to the arcuate fasciculus in patients with conduction aphasia: a study of the Wernicke-Geschwind model. Neurol Res. 2010;32:775-778.http://www.ingentaconnect.com/content/maney/nres/2010/00000032/00000007/art00017?token=00581b0b7829316ef536e58654624317b6f3b4741217a6b3b707b5e4e26634a492f2530332976e9a55a95a60

[44]   Song X, Dornbos D 3rd, Lai Z, et al. Diffusion tensor imaging and diffusion tensor imaging-fibre tractograph depict the mechanisms of Broca-like and Wernicke-like conduction aphasia. Neurol Res. 2011;33:529-535.http://www.ingentaconnect.com/content/maney/nres/2011/00000033/00000005/art00013?token=005619bb589b2e9c8383a4b3b25703a2b462473384d352063662a726e2d2954496f642f466fb77aa2d5a78

[45]   Hosomi A, Nagakane Y, Yamada K, et al. Assessment of arcuate fasciculus with diffusion-tensor tractography may predict the prognosis of aphasia in patients with left middle cerebral artery infarcts. Neuroradiology. 2009;51:549-555.http://dx.doi.org/10.1007/s00234-009-0534-7

[46]   Breier JI, Hasan KM, Zhang W, et al. Language dysfunction after stroke and damage to white matter tracts evaluated using diffusion tensor imaging. Am J Neuroradiol. 2008;29:483-487.http://www.ajnr.org/content/29/3/483.long

[47]   Catani M, Mesulam M. The arcuate fasciculus and the disconnection theme in language and aphasia: history and current state. Cortex. 2008;44:953-961.http://linkinghub.elsevier.com/retrieve/pii/S0010-9452(08)00111-1

[48]   Rasmussen T, Milner B. Clinical and surgical studies of the cerebral speech areas in man. In: Zulch KJ, Creutzfeldt O, Galbraith GC, eds. Cerebral Localization. Berlin: Springer-Verlag. 1975.http://link.springer.com/chapter/10.1007%2F978-3-642-66204-1_19

[49] Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia. 1971;9:97-113.http://www.ncbi.nlm.nih.gov/pubmed/5146491

[50] Pruessmann KP, Weiger M, Scheidegger MB, et al. SENSE: sensitivity encoding for fast MRI. Mag Reson Med. 1999;42:952-962.http://dx.doi.org/10.1002/(SICI)1522-2594(199911)42:5%3C952::AID-MRM16%3E3.0.CO;2-S

[51] Bammer R, Keeling SL, Augustin M, et al. Improved diffusion-weighted single-shot echo-planar imaging (EPI) in stroke using sensitivity encoding (SENSE). Mag Reson Med. 2001;46:548-554.http://dx.doi.org/10.1002/mrm.1226

[52] Kuhl CK, Gieseke J, von Falkenhausen M, et al. Sensitivity encoding for diffusion-weighted MR imaging at 3.0 T: intraindividual comparative study. Radiology. 2005;234:517-526.http://radiology.rsnajnls.org/cgi/pmidlookup?view=long&pmid=15671005

[53] Huang H, Ceritoglu C, Li X, et al. Correction of B0 susceptibility induced distortion in diffusion-weighted images using large-deformation diffeomorphic metric mapping. Mag Reson Imaging. 2008;26:1294-1302.http://www.mrijournal.com/article/S0730-725X(08)00131-8/abstract

[54]   Lee WN, Larrat B, Pernot M, et al. Ultrasound elastic tensor imaging: comparison with MR diffusion tensor imaging in the myocardium. Phys Med Biol. 2012;57:5075-5095.http://iopscience.iop.org/0031-9155/57/16/5075/

[55]   Descoteaux M, Deriche R, Knosche TR, et al. Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Trans Med Imaging. 2009;28:269-286.http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4601462

[56]   Seizeur R, Wiest-Daessle N, Prima S, et al. Corticospinal tractography with morphological, functional and diffusion tensor MRI: a comparative study of four deterministic algorithms used in clinical routine. Surg Radiol Anat. 2012;34:709-719.http://link.springer.com/article/10.1007%2Fs00276-012-0951-x

[57]   Lebel C, Benner T, Beauliey C. Six is enough? Comparison of diffusion parameters measured using six or more diffusion-encoding gradients directions with deterministic tractography. Magn Reson Med. 2012;68:474-483.http://onlinelibrary.wiley.com/doi/10.1002/mrm.23254/abstract

[58]   Mori S, Kaufmann WE, Davatzikos C, et al. Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking. Magn Reson Med. 2002;47:215-223.http://dx.doi.org/10.1002/mrm.10074

[59]   Lazar M, Weinstein DM, Tsuruda JS, et al. White matter tractography using diffusion tensor deflection. Hum Brain Mapp. 2003;18:306-321.http://dx.doi.org/10.1002/hbm.10102

引言

材料方法

Design

Neuroimaging, observational study.

Time and setting

All experiments were performed at the Department of Physical Medicine and Rehabilitation, Yeungnam University Hospital, Republic of Korea in June 2008.

Subjects

Twelve healthy subjects, nine males and three females, aged 39 ± 4.13 (range 26–50) years were recruited by volunteers advertising at the Yeungnam University Hospital. They had no previous history of neurological or physical disease. Subjects were restricted to right-handed individuals, and handedness was determined using the Edinburg Handedness Inventory^[49]. All subjects understood the purpose of the study and provided written, informed consent prior to participation. The institutional review board of the Yeungnam University Hospital approved the study protocol.

Methods

Diffusion tensor imaging data acquisition

Diffusion tensor imaging data were obtained using a 1.5 T MR scanner (Gyroscan Intera, Philips Healthcare, Best, Netherlands) with a six-channel phased array sensitivity encoding (SENSE) head coil. Each diffusion tensor imaging dataset was acquired with two diffusion- sensitizing gradients based on the single-shot spin echo echo-planar imaging pulse sequence. The imaging parameters were as follows: field of view = 221 mm × 221 mm, repetition time/echo time = 10 726/75 ms, matrix = 128 × 128, slice thickness = 2.3 mm, and SENSE factor = 2. Diffusion weighting was applied along 32 distinct directions with a b-value of 1 000 s/mm². We obtained 63–67 contiguous transverse slices covering the entire brain parallel to the anterior and posterior commissure lines with no slice gap^[6].

The diffusion tensor imaging datasets were transferred to a personal computer running a Windows platform, and image distortion corrections were performed prior to image processing. Image distortion was caused by susceptibility artifacts due to the use of the echo-planar imaging technique and eddy currents due to diffusion gradient changes in diffusion-weighted images. The susceptibility artifacts were reduced using parallel imaging because a reduction of the phase-encoding steps translated directly into a reduced echo train length that reduces phase error in single-shot echo-planar imaging^[50-53]. Therefore, we used the SENSE parallel imaging technique with a phased array coil to reduce susceptibility artifacts. The effects of eddy currents and small bulk motion of the head were corrected with 12-mode linear affine registration using each subject’s non-diffusion-weighted image (b-value = 0 s/mm²) as a template for all diffusion-weighted images^[52-53].

Diffusion tensor imaging data analysis

The diffusion tensor imaging datasets were processed using MedINRIA 1.9.0 software (Asclepios Research Team, Sophia Antipolis, France), which consisted of fiber assignment by the continuous tracking algorithm and calculation of the diffusion tensor values using a deterministic method^[54-57]. The six elements of the diffusion tensor were calculated for each voxel and diagonalized. Three eigenvalues and eigenvectors were obtained, and the largest eigenvalue was used as an indicator of fiber orientation. The seed region of interest (ROI) was manually drawn in the posterior parietal portion of the superior longitudinal fascicle, and the target ROI was manually drawn in the posterior temporal lobe using a color-coded fractional anisotropy (FA) map^{[14, 58-59]}. The color-coded FA map showed the directions of the fiber pathways with three colors (red: left-right direction; green: anterior-posterior direction; and blue: superior-inferior direction). The seed ROI was located in the green part, and the target ROI was located in the blue part of the color-coded FA map^{[6, 58-59]}. Tracking was stopped at voxels with FA values that were lower than the threshold or if the angle between two eigenvectors to be connected by the tracking was greater than the threshold. In this study, tracking was terminated when a voxel had an FA value lower than the threshold of 0.2 or a trajectory angle lower than the threshold of 70 degrees.

Curvature range measurements of the arcuate fasciculus

We separately measured the curvature range of the horizontal arcuate fasciculus and the vertical arcuate fasciculus. The arcuate fasciculus curvature range was analyzed in both hemispheres. The ImageJ program (Wayne Rasband, NIH, Bethesda, MD, USA) was used for these analyses.

The arcuate fasciculus horizontal part was examined on transverse images to describe the mediolateral curvature range. We measured two angles, the direct and indirect mediolateral curvatures at the corona radiata level (Figure 1).

The line labeled “1” was parallel to the anterior-posterior direction of the horizontal arcuate fasciculus, and the line labeled “2” was parallel to the arcuate fasciculus, which was directly curved toward the lateral direction. The angles between 1 and 2 determined the DCR. The ICR was defined as the angle between 1 and 3, which is a line connecting the most posterior and most lateral points of the arcuate fasciculus horizontal part.

The arcuate fasciculus vertical part was examined on coronal images to describe the mediolateral curvature range. We applied the same method used for the arcuate fasciculus horizontal part measurements (Figure 1).The DCR was defined by the angle between “1”, which is the line parallel to the arcuate fasciculus in the superior- posterior direction, and “2”, which is the line along the arcuate fasciculus curvature direction. The ICR was determined by the angle between 1 and 3, which is a line connecting the most superior and most lateral points of the arcuate fasciculus vertical part.