White matter tract involvement in alien hand syndrome following stroke: diffusion tensor imaging study

doi:10.21203/rs.3.rs-4715836/v1

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White matter tract involvement in alien hand syndrome following stroke: diffusion tensor imaging study

https://doi.org/10.21203/rs.3.rs-4715836/v1

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Alien Hand Syndrome (AHS) disrupts hand control, often attributed to corpus callosum (CC) damage, which connects the two brain hemispheres. AHS can also result from damage to the medial frontal cortex, parietal lobe, or thalamus, but its precise causes remain unclear. This study aimed to identify the white matter tracts associated with AHS development using the automated reconstruction of 42 tracts from diffusion tensor imaging (DTI).

We included three female AHS patients with anterior cerebral arterial (ACA) infarctions. Additionally, we enrolled 20 age-matched control subjects and six patients with ACA infarctions but without AHS symptoms (N-AHS group) for comparison. DTI was conducted in AHS, N-AHS, and control groups. Fractional anisotropy (FA) and volume values were extracted from the DTI datasets of participants using TRActs Constrained by UnderLying Anatomy (TRACULA) technique.

The AHS group showed lower FA values of the CC body (parietal and temporal section), right arcuate fasciculus, corticospinal tract, extreme capsule, inferior longitudinal fasciculus, and superior longitudinal fasciculus than the control group. However, these tracts exhibited no significant difference between N-AHS and control groups. Similarly, the volume value in the genu of CC in the AHS group was lower than controls, but not in other tracts.

Our results suggest that the extensive CC lesion, especially in the posterior parietal and temporal section of CC body, is associated with the development of AHS. These results shed light on the neural mechanisms involved in AHS and underscore the significance of considering various white matter tracts beyond CC for understanding this syndrome.

Alien hand syndrome

Stroke

Diffusion tensor imaging

White matter tracts

Alien hand syndrome (AHS) is a rare yet intriguing neurological disorder in which an individual experiences involuntary movement in their own hands with a sense of loss of limb ownership, resulting from brain injury (Hassan & Josephs, 2016; Park et al., 2012; Sarva et al., 2014). In 1908, Goldstein first described the concept of AHS with the case of a 57-year-old woman who perceived her left hand as having a will of its own. An autopsy conducted later revealed strokes in the right cerebral hemisphere and the corpus callosum (CC).(Goldstein, 1908) In the 1990s, Goldberg introduced the term "alien hand" to describe the condition of two patients (Goldberg & Bloom, 1990). These individuals demonstrated uncontrolled grasping with their right hand and impulsive groping movements of the limb against their will, even while under visual observation, yet they recognized the limb as their own.(Goldberg & Bloom, 1990) Stroke lesions were identified in the left medial frontal cortex and callosal areas.(Goldberg & Bloom, 1990) Subsequently, the phrase "alien hand" has been widely adopted in scholarly literature. This condition is characterized by noticeable involuntary movements and a perception that the affected limb is estranged or possesses its own volition.

There are numerous theories of the pathomechanisms of AHS, but one of them is the interhemispheric disconnection theory, which is closely associated with CC.(Hassan & Josephs, 2016) Common causes include midline tumors, callosotomy, callosal demyelination, and strokes within the anterior cerebral artery (ACA) area.(Feinberg et al., 1992; Graff-Radford et al., 2013; Hassan & Josephs, 2016) Strokes after ACA infarcts often lead to contralateral leg paralysis and temporary aphasia, which are followed by the development of AHS.(Chan & Ross, 1997; Feinberg et al., 1992) However, damage to the corpus callosum does not always lead to AHS. Previous research indicates that strokes affecting only the corpus callosum are rare, with cases typically involving a combination of callosal and posterior variant AHS.(Yuan et al., 2011) In a significant study of 100 cases involving strokes in the anterior cerebral artery (affecting CC, cingulate gyrus, or supplementary motor area), alien limb phenomena were observed in 10% of the cases.(Hassan & Josephs, 2016) There was not a specific infarct location determining the occurrence of AHS.(Kang & Kim, 2008) These findings indicate that AHS development requires additional white matter disconnection between regions involved in motor execution and inhibitory control, in addition to damage to the CC. Therefore, analyzing a wide variety of white matter tracts will aid in understanding the pathomechanisms of AHS.

A key technique commonly used in the reconstruction of white matter tracts is diffusion tensor imaging (DTI). There are numerous methods for reconstructing white matter tracts from DTI data, allowing for the generation of structural connectivity in the human brain.(Jellison et al., 2004; Kreilkamp et al., 2017; Mori et al., 2009) The most commonly used techniques involve manual tractography, which necessitates a skilled researcher to delineate individual tract bundles by identifying known anatomical characteristics.(Kreilkamp et al., 2017) Employing these methods, previous studies have documented substantial changes in DTI scalar measurements.(Kreilkamp et al., 2017) However, a major practical limitation of manual tractography techniques is the availability of trained personnel, leading to inconsistencies and inaccuracies, as well as the time-intensive process involved in taking measurements.(Kreilkamp et al., 2017) The advantages to the advancement of automated morphometric methods could potentially bypass several limitations inherent to manual tractography techniques.(Yendiki et al., 2011)

The aim of this study was to determine which white matter tracts damage is associated with the development of AHS after stroke using DTI.

Participants

We collected data on AHS patients from the prospective database of STroke Outcome Prediction (STOP) of Korea University Hospital. This database integrates clinical evaluation, neurophysiological and neuroimaging data for prediction of functional outcome, such as motor, cognition and language etc., in stroke patients. The STOP database was officially registered with the Clinical Research Information Service under Registration Number KCT0005909. We reviewed the medical records of 610 who had taken DTI at the early subacute phase between January 2016 to February 2023. Three female patients with AHS, having suffered from ischemic infarction within the ACA territory, were included in the study as AHS group (Fig. 1). These patients represented particular symptoms such as involuntary hand movements, grasping difficulty, and compulsive manipulations in the affected limb, with corresponding lesions observed in CC on brain MRI (Fig. 2)

Furthermore, the 6 patients who had ACA territory infarction affecting the CC but exhibited no symptoms of AHS (N-AHS group) were recruited for comparative analysis between AHS and N-AHS group. In addition, we collected neuroimaging data of 20 healthy age-matched control subjects (control group). The recruitment criteria included being right-handed and having no history of neurological disorders.

This research received approval from the Institutional Review Board of Korea University Anam Hospital (IRB No. 2022AN0116) and was conducted adhering to the principles outlined in the Declaration of Helsinki. All patients provided written informed consent and agreed to participate in the study.

Clinical and demographic data

We collected demographic and clinical data within one month following stroke onset including the National Institute of Health Stroke Scale (NIHSS), Korean version of the Mini-Mental State Exam (K-MMSE), Fugl-Meyer Assessment (FMA), Manual Function Test (MFT), and Modified Barthel Index (MBI). Additionally, all patients in both the AHS group and the non-AHS (N-AHS) group underwent MRI diffusion tensor imaging (DTI) in the early subacute stage of stroke, approximately within 1 month of onset.

MRI acquisition protocol

Study participants were imaged using a sophisticated 3.0 Tesla MR scanner (Magnetom Prisma, Siemens Medical Solutions, Erlangen, Germany), outfitted with an advanced 64-channel head and neck coil. Imaging involved the acquisition of a coronal 3D T1-weighted magnetization prepared rapid gradient echo (MPRAGE) sequence, oriented perpendicular to the longitudinal axis of the anterior commissure-posterior commissure line in the midsagittal plane. The imaging parameters were as follows: slice thickness was maintained at 1.0 mm with no interslice gap; 384 slices were acquired; repetition time (TR) and echo time (TE) were set at 2300 milliseconds and 2.26 milliseconds, respectively; the flip angle was 9 degrees; the number of signal averages was set to 1; the matrix resolution was 256 × 256; and the field of view (FOV) was 256 mm × 256 mm. For the acquisition of diffusion tensor imaging (DTI) data, a single-shot spin-echo planar imaging sequence was employed with these specifications: 64 diffusion gradient directions; matrix size of 112 × 112; FOV of 224 × 224 mm²; slice thickness of 2.0 mm; isotropic voxel size of 2.0 × 2.0 × 2.0 mm³; echo time of 55 milliseconds; repetition time of 6100 milliseconds; a b-value of 1000 s/mm²; and a flip angle of 90 degrees. Anatomical and diffusion tensor imaging data were converted from DICOM to NIfTI-1 (nii.gz) format using dcm2niix of MRIcroGL (http://www.nitrc.org/projects/mricrogl).

White matter tracts extraction

Diffusion tensor imaging data undergo processing using the TRACULA (TRActs Constrained by UnderLying Anatomy) pipeline within FreeSurfer 7.4.1 (http://surfer.nmr.mgh.harvard.edu) for white matter tract integrity analysis and reconstruction..(Fischl, 2012) Pre-tractography adjustments include corrections for subject motion, EPI distortions, and eddy current effects using the eddy correct utilities within the FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki).(Graham et al., 2016; Jenkinson et al., 2012) Non-brain tissues are excised using the Brain Extraction Tool (BET). The tensor model is then applied to the adjusted DTI data to produce fractional anisotropy (FA) maps from eigenvalues via the DTIFIT tool. The ball and stick model are employed to estimate diffusion probabilities using BedpostX pipeline of FSL. The TRACULA pipeline automatically reconstructs forty-two major white matter tracts collaborated with previously segmented subthalamic nuclei (Maffei et al., 2021), and the DTI metrics such as fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values for each tract are extracted for subsequent analysis (Fig. 2).

Statistical analyses

The Kruskal-Wallis test was performed to compare the continuous variables such as age, education duration (years), and K-MMSE across three groups: the AHS group, N-AHS group, and control group. Sex and stroke side as a categorical variable was compared across the groups using the chi-square test. Additionally, handedness was not statistically compared separately as all enrolled participants were right-handed. Other demographic and clinical variables such as the duration from onset to MRI imaging (days), NIHSS, FMA (total and upper extremity), MFT and MBI were evaluated only among stroke patients (AHS and N-AHS groups). Thus, we used the Mann-Whitney test to analyze differences between the two groups in these measures. The Kruskal-Wallis test was used to compare DTI parameters of various white matter tracts assessed by TRACULA among the three groups. A significance level of p < 0.05 was established.

Clinical and demographic data

The AHS and the N-AHS group underwent MRI DTI in the early subacute stage of stroke, approximately within 1 month of onset (mean days = 26.0, 32.7, respectively) (Table 1). The AHS group showed significant lower K-MMSE scores compared to the control group, 21.33 ± 2.31, 29.05 ± 1.05 points, respectively (p = 0.030). There was statistically significantly more right brain damage in AHS group than in the N-AHS group (p = 0.033). There was no significant difference between the groups in terms of age, sex, education years, initial NIHSS, FMA, MFT and MBI scores.

Table 1

Comparison of demographic and clinical variables according to study groups
Variables	AHS (n = 3)	N-AHS (n = 6)	Control (n = 20)	p value	Pairwise comparison
Age (years)	66.00 (2.00)	56.00 (15.375)	63.30 (4.054)	0.342	NS
Onset to MRI	26.00 (17.059)	32.67 (23.001)	-	0.714	NS
Sex (Male/Female)	0/3	2/4	10/10	0.236	NS
Handedness (R/L)	3/0	6/0	20/0	-	-
Education (years)	9.0 (3.00)	12.0 (4.899)	14.15 (4.258)	0.127	NS
Stroke side (R/L/B)	2/0/1	1/5/0	-	0.034*	-
Initial NIHSS	3.33 (1.528)	7.83 (5.981)	-	0.167	NS
Fugl-Meyer Assessment (total, 100)	41.67 (18.903)	58.00 (38.121)	-	0.548	NS
Fugl-Meyer Assessment (upper, 66)	28.33 (9.074)	45.50 (31.088)	-	0.548	NS
K-MMSE	21.33 (2.309)^†	20.33 (14.264)	29.05 (1.050) ^†	0.033*	0.030^†
MFT (32)	16.00 (14.177)	18.67 (14.583)	-	0.548	NS
MBI (100)	36.67 (29.535)	43.67 (28.542)	-	0.905	NS
R, right; L, left; B, bilateral; AHS, alien hand syndrome group; N-AHS, group of patients with stroke but no AHS symptoms; MRI, Magnetic Resonance Imaging; K-MMSE, Korean version of Mini-Mental Status Examination; MFT, Manual Function Test; MBI, Modified Barthel Index; NIHSS, National Institute of Health Stroke Scale, NS, not significant
*p-value < 0.05, in the statistical analysis in any Mann–Whitney, Chi square, or Kruskal–Wallis test.
^†p-value < 0.05, between AHS vs. control group, and ^δ between N-AHS vs. control group.
^¶ P-value between two groups was calculated with pairwise t-test, rather than Kruskal–Wallis analysis

Whole-tract diffusion metric analysis

The FA values of whole white matter tracts reconstructed by TRACULA in 3 groups are presented in Table 2. The FA values of 42 white matter tracts showed no significant difference between the AHS group and N-AHS group. In the CC, the AHS group showed lower FA values only in the parietal and temporal sections of body of the CC than the control group (p < 0.05). However, there were no statistically significant differences in these tracts between the N-AHS and control groups. The FA values of the rostrum, genu and the premotor and central sections of body of the CC, the bilateral dorsal cingulum bundle (dCB), the bilateral frontal aslant tract (FAT) and the bilateral superior longitudinal fasciculus (SLF) showed significant decreased values between the AHS and control groups, as well as between the N-AHS and control groups.

Table 2

Comparison of fraction anisotropy values of white matter tracts according to study groups
FA values of white matter tracts	AHS^†	N-AHS^δ	Control^†δ	p value	Pairwise comparison
AC	0.379 (0.0338)	0.381 (0.0382)	0.400 (0.0361)	0.745	NS
CC – rostrum	0.431 (0.0599)	0.460 (0.0686)	0.551 (0.0401)	0.002*	0.027^†, 0.014^δ
CC – genu	0.398 (0.0969)	0.431 (0.0796)	0.587 (0.0413)	0.001*	0.022^†, 0.004^δ
CC – body – prefrontal	0.349 (0.0459)	0.392 (0.0533)	-	0.381	NS
CC – body – premotor	0.351 (0.0498)	0.417 (0.0815)	0.592 (0.0341)	< 0.001*	0.007^†, 0.003^δ
CC – body – central	0.417 (0.0559)	0.453 (0.0612)	0.569 (0.0263)	< 0.001*	0.011^†, 0.003^δ
CC – body – parietal	0.483 (0.0389)	0.547 (0.0349)	0.582 (0.0251)	0.003*	0.010^†
CC – body – temporal	0.487 (0.0371)	0.498 (0.0716)	0.551 (0.0242)	0.010*	0.039^†
CC – splenium	0.580 (0.0814)	0.640 (0.0229)	0.641 (0.0517)	0.232	NS
MCP	0.450 (0.0224)	0.478 (0.0268)	0.466 (0.0234)	0.369	NS
AF (L)	0.410 (0.0162)	0.397 (0.0254)	-	0.548	NS
AF (R)	0.366 (0.0295)	0.419 (0.0176)	0.434 (0.0270)	0.014*	0.012^†
AR (L)	0.453 (0.0308)	0.466 (0.0254)	0.481 (0.0251)	0.178	NS
AR (R)	0.421 (0.0570)	0.473 (0.0499)	0.487 (0.0146)	0.119	NS
ATR (L)	0.448 (0.0632)	0.403 (0.0809)	0.481 (0.0328)	0.052	NS
ATR (R)	0.432 (0.0804)	0.458 (0.0443)	0.506 (0.0371)	0.062	NS
CB – dorsal (L)	0.385 (0.0585)	0.396 (0.0692)	0.546 (0.0308)	< 0.001*	0.012^†, 0.001^δ
CB – dorsal (R)	0.378 (0.0613)	0.442 (0.0194)	0.515 (0.0320)	< 0.001*	0.004^†, 0.002^δ
CB – ventral (L)	0.465 (0.0308)	0.498 (0.0518)	0.458 (0.0299)	0.129	NS
CB – ventral (R)	0.443 (0.0317)	0.489 (0.0338)	0.473 (0.0350)	0.229	NS
CST (L)	0.497 (0.0293)	0.478 (0.0560)	0.537 (0.0204)	0.006*	0.018^δ
CST (R)	0.496 (0.0111)	0.526 (0.0198)	0.536 (0.0223)	0.023*	0.021^†
EMC (L)	0.468 (0.0245)	0.423 (0.0800)	0.495 (0.0262)	0.010*	0.014^δ
EMC (R)	0.437 (0.0357)	0.467 (0.0297)	0.495 (0.0207)	0.011*	0.046^†
FAT (L)	0.413 (0.0374)	0.365 (0.1028)	0.480 (0.0222)	0.002*	0.047^†, 0.009^δ
FAT (R)	0.347 (0.0738)	0.430 (0.0234)	0.478 (0.0273)	0.001*	0.005^†, 0.023^δ
Fornix (L)	0.451 (0.0172)	0.423 (0.0979)	0.478 (0.0614)	0.068	NS
Fornix (R)	0.438 (0.232)	0.422 (0.0827)	0.494 (0.0229)	0.004*	0.031^†, 0.031^δ
ILF (L)	0.480 (0.0353)	0.493 (0.0368)	0.510 (0.0304)	0.494	NS
ILF (R)	0.446 (0.0265)	0.498 (0.0185)	0.515 (0.0293)	0.014*	0.004^†
MLF (L)	0.462 (0.0343)	0.459 (0.0248)	0.500 (0.0254)	0.007*	0.013^δ
MLF (R)	0.437 (0.0380)	0.492 (0.0365)	0.494 (0.0320)	0.083	NS
OR (L)	0.488 (0.0428)	0.471 (0.0126)	0.506 (0.0246)	0.014*	0.011^δ
OR (R)	0.457 (0.0488)	0.498 (0.0166)	0.505 (0.0334)	0.079	NS
SLF I (L)	0.415 (0.0407)	0.387 (0.0810)	0.504 (0.0309)	0.001*	0.046^†, 0.002^δ
SLF I (R)	0.384 (0.0865)	0.455 (0.0253)	0.511 (0.0326)	0.001*	0.007^†, 0.015^δ
SLF II (L)	0.361 (0.0212)	0.340 (0.0394)	0.396 (0.0227)	0.002*	0.004^δ
SLF II (R)	0.357 (0.0245)	0.381 (0.0176)	0.404 (0.0310)	0.026*	0.049^†
SLF III (L)	0.399 (0.0194)	0.367 (0.0559)	0.434 (0.0230)	0.004*	0.007^δ
SLF III (R)	0.372 (0.0114)	0.405 (0.0200)	0.419 (0.0206)	0.010*	0.013^†
UF (L)	0.452 (0.0192)	0.411 (0.0788)	0.475 (0.0237)	0.012*	0.019^δ
UF (R)	0.428 (0.0440)	0.456 (0.0120)	0.486 (0.0215)	0.003*	0.044^†, 0.021^δ
R, right; L, left; B, bilateral; AHS, alien hand syndrome group; N-AHS, group of patients with stroke but no AHS symptoms; FA, fraction anisotropy; AC, anterior commissure; CC, corpus callosum; MCP, middle cerebellar peduncle; AC, arcuate fasciculus; AR, acoustic radiation; ATR, anterior thalamic radiation; CB, cingulum bundle; CST, corticospinal tract; EMC, extreme capsule; FAT, frontal aslant tract; ILF, inferior longitudinal fasciculus; MLF, middle longitudinal fasciculus; OR, optic radiation; SLF, superior longitudinal fasciculus; UF, uncinate fasciculus; NS, not significant
*p-value < 0.05, in the statistical analysis in Mann–Whitney or Kruskal–Wallis test.
^†p-value < 0.05, between AHS vs. control group, and ^δ between N-AHS vs. control group.

In addition, the volume value in the genu of CC in the AHS group was lower than the control group (p = 0.04), but there was no significant difference in other tracts between the AHS and control groups (Table 3). The N-AHS group showed lower the volume values of the CC body (premotor section) (p = 0.024). We additionally analyzed the values of MD, AD, and RD (Table S1, S2, S3).

Table 3

Comparison of volume values of white matter tracts according to study groups
Volume values of white matter tracts	AHS	N-AHS	Control	p value	Pairwise comparison
AC	1410.67 (322.97)	1429.33 (301.04)	1514.45 (584.37)	0.961	NS
CC – rostrum	1676.00 (542.88)	1884.50 (689.25)	2053.95 (501.16)	0.328	NS
CC – genu	709.00 (950.05)	2311.33 (1227.02)	2398.95 (603.91)	0.047*	0.040^†
CC – body – prefrontal	4365.67 (1497.11)	3291.67 (1330.07)	-	0.714	NS
CC – body – premotor	10723.67 (9894.65)	3240.17 (2085.89)	6007.05 (4762.58)	0.027*	0.024^δ
CC – body – central	4297.00 (1547.02)	4333.50 (829.01)	5514.05 (3203.05)	0.584	NS
CC – body – parietal	6250.33 (410.16)	5214.33 (645.40)	6238.75 (1066.65)	0.044*	NS
CC – body – temporal	11863.33 (1464.30)	9221.50 (5065.46)	13300.60 (2262.69)	0.101	NS
CC – splenium	4022.67 (652.55)	3356.67 (595.69)	4423.45 (1604.48)	0.152	NS
MCP	5263.67 (1103.82)	5400.50 (1525.21)	6567.90 (1454.30)	0.077	NS
AF (L)	6043.00 (1297.59)	4837.83 (1291.67)	-	0.439	NS
AF (R)	4866.67 (685.43)	5147.50 (1538.51)	5889.90 (3643.61)	0.924	NS
AR (L)	886.67 (133.50)	524.33 (217.70)	788.45 (310.38)	0.024*	0.048^√
AR (R)	705.00 (153.63)	630.67 (178.73)	705.25 (181.53)	0.668	NS
ATR (L)	743.00 (259.67)	871.33 (387.50)	926.30 (229.33)	0.508	NS
ATR (R)	1142.67 (549.60)	1843.33 (2625.21)	823.45 (249.49)	0.496	NS
CB – dorsal (L)	2575.33 (528.03)	2166.83 (638.13)	2412.30 (536.78)	0.708	NS
CB – dorsal (R)	2702.33 (848.56)	2427.83 (667.69)	2855.90 (463.07)	0.322	NS
CB – ventral (L)	836.33 (32.81)	671.00 (169.71)	718.70 (262.01)	0.392	NS
CB – ventral (R)	1267.33 (803.76)	762.50 (305.96)	744.20 (264.29)	0.516	NS
CST (L)	3673.00 (794.14)	2841.50 (758.10)	3004.05 (758.46)	0.257	NS
CST (R)	3781.00 (121.50)	3250.00 (705.47)	3553.95 (611.01)	0.294	NS
EMC (L)	1624.67 (517.28)	1733.83 (1029.29)	1744.05 (327.26)	0.583	NS
EMC (R)	1607.00 (155.79)	1631.83 (290.61)	1807.20 (260.46)	0.308	NS
FAT (L)	1890.33 (283.48)	3457.33 (3361.76)	2782.05 (1627.20)	0.337	NS
FAT (R)	2571.33 (543.96)	2290.00 (910.10)	2281.05 (620.56)	0.604	NS
Fornix (L)	1553.67 (536.31)	1501.67 (870.61)	1890.60 (713.24)	0.128	NS
Fornix (R)	1878.67 (453.23)	1417.50 (723.93)	2174.15 (466.14)	0.037*	0.034^δ
ILF (L)	2772.00 (276.86)	2386.17 (648.48)	2968.95 (584.01)	0.089	NS
ILF (R)	2642.33 (86.43)	2502.83 (245.31)	2675.25 (550.95)	0.689	NS
MLF (L)	2543.67 (495.15)	2206.50 (286.25)	2339.70 (749.42)	0.701	NS
MLF (R)	1516.67 (521.57)	2090.00 (811.16)	2074.90 (689.07)	0.358	NS
OR (L)	2151.33 (347.23)	1849.83 (819.65)	2264.70 (539.68)	0.164	NS
OR (R)	1889.00 (675.62)	1863.83 (269.27)	1765.40 (563.83)	0.821	NS
SLF I (L)	3561.33 (411.33)	3312.83 (1157.83)	3289.25 (658.50)	0.742	NS
SLF I (R)	3050.33 (674.85)	3064.50 (722.65)	3160.85 (621.07)	0.889	NS
SLF II (L)	3643.33 (2692.64)	3978.17 (1506.02)	4994.45 (966.69)	0.256	NS
SLF II (R)	3574.33 (481.84)	3598.00 (887.90)	3873.90 (791.84)	0.640	NS
SLF III (L)	3355.67 (633.82)	3189.17 (771.88)	4863.35 (3351.19)	0.062	NS
SLF III (R)	3479.67 (144.42)	3465.67 (1282.05)	4334.40 (3478.67)	0.901	NS
UF (L)	1729.67 (204.61)	1549.17 (379.08)	1916.80 (406.57)	0.140	NS
UF (R)	2005.67 (564.03)	1737.17 (274.65)	2092.20 (248.99)	0.069	NS
R, right; L, left; B, bilateral; AHS, alien hand syndrome group; N-AHS, group of patients with stroke but no AHS symptoms; FA, fraction anisotropy; AC, anterior commissure; CC, corpus callosum; MCP, middle cerebellar peduncle; AC, arcuate fasciculus; AR, acoustic radiation; ATR, anterior thalamic radiation; CB, cingulum bundle; CST, corticospinal tract; EMC, extreme capsule; FAT, frontal aslant tract; ILF, inferior longitudinal fasciculus; MLF, middle longitudinal fasciculus; OR, optic radiation; SLF, superior longitudinal fasciculus; UF, uncinate fasciculus; NS, not significant
*p-value < 0.05, in the statistical analysis in Mann–Whitney or Kruskal–Wallis test.
^†p-value < 0.05, between AHS vs. control group, ^δ between N-AHS vs. control group, and ^√between AHS vs. N-AHS.

This study aimed to identify the white matter tracts contributing to the development of AHS in the patients with ischemic stroke. Our results suggest that damage to most of sections of CC, especially in the parietal and temporal section of the body of CC is associated with development of AHS after stroke.

In this study, we enrolled patients with corpus callosum lesions resulting from ACA territory stroke. CC consists of the primary commissural fibers connecting both cerebral hemispheres and plays a crucial role in the interhemispheric transfer of information.(Goldstein et al., 2024) Damage to the CC is a key factor in the development of AHS, which is a common neurological manifestation of callosal disconnection syndrome .(Chan & Ross, 1997; Hassan & Josephs, 2016; Jang et al., 2013a; Molko et al., 2002) Hassan et al proposed 3 types of AHS: frontal, callosal and posterior.(Hassan & Josephs, 2016) Among these, the anterior variant AHS, which includes the frontal and callosal variant, is associated with CC. Frontal AHS, affecting the dominant hand, is typically caused by a lesion in the dominant medial frontal lobe, the supplementary motor area, or the anterior portion of the CC. Callosal AHS, primarily caused by lesions in the CC, is characterized by intermanual conflict affecting the non-dominant (interhemispheric disconnection theory).(Feinberg et al., 1992; Goldberg & Bloom, 1990) Previous DTI study reported decreased FA value of the CC in a AHS patient (Jang et al., 2013a; Jang et al., 2013b; Sugawara et al., 2023), and our results also revealed decreased FA values in the CC, similar to previous findings. Thus, a lesion in the CC appears to be a necessary condition for the development of AHS.

In our study, the FA vale of the posterior portions of the CC body, specifically the parietal and temporal section, only AHS group was significantly lower than that in the control group. This result suggests that these two sections of the CC may play a more critical role in the manifestation of AHS during callosal disconnection syndrome. Previous studies on patients with CC lesions have documented a high variability in callosal disconnection syndrome, dependent on the location and extent of CC damage in each case.(Jang et al., 2013a) Previous studies reported that the lesions in the posterior part of the CC were linked with various symptoms, including tactile anomia, agraphia, somatosensory deficits, alexia, neglect, visual anomia, and impairment of visual recognition. (Koch et al., 2011) These symptoms, characterized by strong feelings of estrangement from the affected limb and parietal sensory deficits, significantly influence the manifestation of AHS features.(Hassan & Josephs, 2016)

In patients without AHS, the parietal and temporal sections of the CC body may serve as compensatory fibers for interhemispheric connections following damage to the anterior CC. In a case study with AHS after hemorrhage of CC, the patient’s AHS resolved after 7 weeks. Tractography revealed disrupted callosal fibers and unusual neural connections through temporal lobe fibers, suggesting compensatory mechanisms for recovery following damage to the CC fibers.(Jang et al., 2013b)

Neuroimaging and clinical studies implicated the supplementary motor area (SMA), pre-SMA, and their network connections in the development of the anterior variant of AHS.(Hassan & Josephs, 2016) The SMA, located on the mesial surface of the frontal lobe, is renowned for its role in motor planning, initiation, and even inhibition.(Hassan & Josephs, 2016) And the FAT is a white matter tract that connects the SMA and pre-SMA to the inferior frontal gyrus, which has also been identified as an emerging locus for motor inhibitory control in several studies.(Dick et al., 2019; Hampshire et al., 2010) SLF I originates from the superior parietal lobe and terminates within the SMA and premotor areas in the frontal lobe, playing a crucial role in proprioception and motor movement.(Schmahmann et al., 2008) The SLF II, which plays a role in visual-spatial awareness and attention, originates from the posterolateral parietal lobe.(Schmahmann et al., 2008) It extends through the postcentral, precentral, and middle frontal gyri, terminating within the dorsolateral prefrontal cortex.(Schmahmann et al., 2008) And the SLF III originates from the supramarginal gyrus and extends towards the ILF, terminating within the dorsal prefrontal cortex.(Schmahmann et al., 2008) This bundle is instrumental in processing somatosensory input and facilitating fine movements of the hand.(Schmahmann et al., 2008) These findings underscore that damage to the FAT and SLF can lead to a loss of inhibitory control over motor execution, contributing to the development of AHS. However, the FA values of FAT and SLF showed a significant difference from the control, with no difference between AHS and N-AHS groups. While the functions of the FAT and SLF are not yet completely understood, the causal relationship between damage to these tracts and the occurrence of AHS warrants further analysis in future studies.

The interpretation of studies on AHS is currently limited by the small number of subjects. However, none of the previously reported studies have analyzed all white matter tracts using DTI for studying AHS. Therefore, our results will provide additional insights regarding the neural pathways associated with AHS, and its underlying neural mechanisms.

This study suggests that the extensive CC lesion, especially in the posterior parietal and temporal of CC body, is associated with the development of AHS. These results shed light on the neural mechanisms involved in AHS and underscore the significance of considering various white matter tracts beyond CC for understanding this syndrome.

Acknowledgements

The authors would like to express our gratitude to all the participants and colleagues of the Department of Rehabilitation Medicine at Korea University Anam Hospital for their valuable support in this research.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government. (No. 2022R1A2B5B02001673)

Conflicts of interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics approval

This research was approved by the Institutional Review Board of Korea University Anam Hospital (IRB No. 2022AN0116) and was conducted in accordance with the principles stated in the Declaration of Helsinki.

Consent to participate

All patients signed a written agreement and consented to participate in the study.

Consent for publication

All authors agreed to submit the paper for publication.

Author contributions

- Jihee Park: Data Collection, Statistical analysis, Investigation, Interpretation of results, Writing - Original Draft

- Sekwang Lee: Investigation, Writing – Review & Editing

- Woo-Suk Tae: Resources, Software, Visualization, Writing - Original Draft

- Sung-Bom Pyun: Conceptualization, Methodology, Funding Acquisition, Project Administration, Resources, Supervision, Interpretation of results, Writing – Review & Editing

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No competing interests reported.

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White matter tract involvement in alien hand syndrome following stroke: diffusion tensor imaging study

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