JNS-13815; No of Pages 7 Journal of the Neurological Sciences xxx (2015) xxx–xxx

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Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study Pei-Chin Chen a, Meng-Hsiang Chen a, Hsiu-Ling Chen a,b, Cheng-Hsien Lu c, Kun-Hsien Chou d,e, Re-Wen Wu f, Nai-Wen Tsai c, Ching-Po Lin d,e, Shau-Hsuan Li g, Yi-Wen Chen a, Yu-Fan Cheng a, Wei-Che Lin a,⁎ a

Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taiwan Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taiwan d Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan e Brain Research Center, National Yang-Ming University, Taipei, Taiwan f Department of Orthopedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taiwan g Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taiwan b c

a r t i c l e

i n f o

Article history: Received 17 February 2015 Received in revised form 18 May 2015 Accepted 20 May 2015 Available online xxxx Keywords: Carbon monoxide intoxication Corpus callosum Delayed encephalopathy Diffusion tensor image Magnetic resonance imaging White matter

a b s t r a c t Purpose: To evaluate the correlation between microstructural damage in the corpus callosum (CC) and the cognitive performance of patients with or without delayed encephalopathy (DE) after carbon monoxide (CO) intoxication in the chronic stage. Methods: Diffusion tensor imaging (DTI) was performed more than 6 months after CO intoxication for 10 patients with DE and 10 patients without DE recruited from out-patient clinics, as well as for 15 normal controls (NCs). Using a probabilistic tractography method to parcel the CC based on fiber projections to cortical connectivity patterns, the DTI indices were calculated in the CC subregions and further correlated with cognitive performance. Results: The DE group exhibited significantly lower fractional anisotropy (FA) and higher radial diffusivity (RD) values in the prefrontal, premotor, primary motor, primary sensory, parietal, and occipital CC subregions than did the NCs. The DE group also exhibited significantly lower FA values in the prefrontal and premotor subregions than did the non-DE group. Lower FA and higher RD values in the CC subregions were associated with poorer scores on the symbol search test. Conclusions: CO intoxication may cause lower FA and higher RD in the CC subregions, with subsequent cognitive impairment. This finding suggests that selective CC damage after CO intoxication is more profound in patients with DE. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Carbon monoxide (CO) intoxication is the most commonly occurring form of lethal gas intoxication, and can also result in extensive brain injury and subsequent cognitive impairment in non-lethal cases [1]. After CO intoxication, two common types of clinical presentation may develop: (1) acute consciousness deterioration which occurs immediately Abbreviations: CO, carbon monoxide; DE, delayed encephalopathy; WM, white matter; CC, corpus callosum; DTI, diffusion tensor imaging; FA, fractional anisotropy; AD, axial diffusivity; RD, radial diffusivity; NC, normal control; NP, neuropsychological. ⁎ Corresponding author at: Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, 123 Ta-Pei Road, Niao-Sung, Kaohsiung 83305, Taiwan. Tel.: +886 7 7317123x3027; fax: +886 7 7317123x2523. E-mail addresses: [email protected] (P.-C. Chen), [email protected] (M.-H. Chen), [email protected] (H.-L. Chen), [email protected] (C.-H. Lu), [email protected] (K.-H. Chou), [email protected] (R.-W. Wu), [email protected] (N.-W. Tsai), [email protected] (C.-P. Lin), [email protected] (S.-H. Li), [email protected] (Y.-W. Chen), [email protected] (Y.-F. Cheng), [email protected] (W.-C. Lin).

after CO exposure, and (2) delayed encephalopathy (DE), which occurs in approximately 0.06–40% of survivors after CO intoxication and presents with rapid neurologic deterioration and a broad spectrum of neuropsychiatric symptoms after a lucid interval [2]. The latter syndrome is clinically characterized by a recurrence of neurologic or psychiatric symptoms that include dementia, disorientation, Parkinsonism, psychiatric syndrome, and akinetic mutism or apallic states [3]. Evidence has shown that lesions in the white matter (WM) of the brain, especially the peri-ventricular WM and centrum semiovale, occur as a result of CO intoxication and that these lesions might contribute to DE. Such lesions have been associated with diffuse demyelination of the cerebral WM [4–7], including the corpus callosum (CC) [5–7]. Damage to different portions of CC fibers may contribute to distinct behavioral and cognitive symptoms. However, little is known about how microstructure damage to the CC occurs after CO intoxication. In addition, there is a paucity of information regarding the nature of the damage to different portions of fibers in the CC after CO intoxication, both in patients with and without DE.

http://dx.doi.org/10.1016/j.jns.2015.05.030 0022-510X/© 2015 Elsevier B.V. All rights reserved.

Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030

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P.-C. Chen et al. / Journal of the Neurological Sciences xxx (2015) xxx–xxx

2. Materials and methods

demographic and clinical data are listed in Table 1. All of the subjects underwent MRI studies and neuro-psychological tests in the chronic stage (for the CO intoxication subjects) or, in the case of the NCs, at the time of enrollment. A clear history of acute CO intoxication was defined as an episode of past exposure to burning charcoal or gas in an enclosed space and/or an elevated COHb level [11]. Those with a history of neurologic or psychiatric illness, developmental disorders, or head injuries that could affect the results of the neuropsychiatric or neuroimaging surveys, as well as those who used medication for unrelated conditions, were excluded. The enrolled CO patients either sought first aid at our hospital's emergency room during the acute CO intoxication and received follow-up treatment at our out-patient clinic (n = 15) or sought first aid at another hospital's emergency room and then visited our out-patient clinic following the development of new symptoms after the acute CO intoxication (n = 5). All of them awoke within 24 h of their acute CO intoxication episode and underwent hyperbaric oxygen therapy for several days. During the acute stage, all of the patients underwent conventional MRI. The CO intoxicated patients were determined to belong to one of two subgroups based on the presence or absence in their disease course of delayed encephalopathy (DE), which is characterized clinically by recurring neurologic or psychiatric symptoms punctuated by temporary asymptomatic periods (lucid intervals) of varying durations [6]. For our 20 patients, there were 10 patients in the non-DE group and 10 patients in the DE group according to the above definition. Chang Gung Memorial Hospital's Institutional Review Committee on Human Research approved the study, and all the participants provided written informed consent.

2.1. Participants

2.2. Neuropsychological (NP) testing

Using cross-sectional data from 2008 to 2010, patients with CO intoxication in the chronic stage (which was defined as the follow-up period occurring more than 6 months after the acute CO intoxication episode) who were treated at Kaohsiung Chang Gung Memorial Hospital were evaluated as candidates for the present study via chart review, telephone interview, or in-person clinical interview. Initially, twenty-five patients with CO intoxication were found to fully fit the criteria. Finally, twenty patients with CO intoxication in the chronic phase (N6 months) were enrolled in the study (four of the aforementioned patients were not willing to participate, and one patient was excluded due to an imaging artifact). For comparison, fifteen age- and sex-matched normal controls (NCs) were also recruited. The subjects'

All the subjects underwent neuropsychological testing and MR imaging on the same day. The neuropsychological testing included the Wechsler Adult Intelligence Scale. The Wechsler Adult Intelligence Scale, a family of tests created by David Wechsler to measure cognitive domains that contribute to intelligence, is commonly used to assess a wide range of cognitive abilities and impairments [12]. This study used the full scale intelligence quotient measure from the Taiwanese version of the Wechsler Adult Intelligence Scale — III [13,14], which was based on the combined verbal comprehension index, perceptual organization index, working memory index, and processing speed index scores [15]. All of the participants finished the picture completion and matrix reasoning tasks, the sub-tests that comprise the perceptual

Recently, non-invasive MRI techniques, such as diffusion tensor imaging (DTI), have been shown to be capable of providing information about the white matter pathways in the human brain by detecting the water molecular diffusion in the local microstructure at a given voxel [8]. Among the DTI indices, the MD (average diffusion coefficient, [(λ1 + λ2 + λ3) / 3]) is viewed as a measurement of isotropic diffusion in the context of free movement of water. Axial diffusivity (AD) (which is the principal diffusion component and is denoted mathematically as λ1) is the diffusion coefficient along the direction of maximal “apparent” diffusion. The second and third eigenvalues in the DTI can be averaged and presented as radial diffusivity (RD) (which is the transverse diffusion component and is denoted mathematically as [(λ2 + λ3) / 2]). Lastly, the fractional anisotropy (FA) representing the integrity of white matter fibers is the relative ratio of the axial to radial diffusivities [9,10]. However, there have only been a limited number of neuro-imaging studies that have focused on the condition of the CC and its correlation with cognitive declines in CO patients through the use of multiple diffusion indices. In the present study, we measured all the aforementioned diffusivity indices to comprehensively explore the different types of diffusion characteristics in the CC in patients with CO. The parcellation of the CC was estimated by probability tractography, with the CC being divided into seven subregions based on projections to specific cortical areas. Our goal was to investigate the subregional callosal damage in patients with and without DE after CO intoxication. Microstructure differences in the CC subregions and cognitive performance were determined for all the patient subjects.

Table 1 Demographic and clinical characteristics of the DE, non-DE, and normal control groups. Patients with chronic COI

Definition Number of cases Gender (n = male/female) Age (years) Duration of follow-up (months) COHb% during the acute stage WAIS Picture completion Digit symbol Symbol search Matrix reasoning Digit span

Normal control

F or X2

P value

DE group

Non-DE group

With DE 10 7/3 40.4 (9.0) 23.1 (17.54) 15.88 (8.92)

Without DE 10 7/3 39.4 (9.1) 29.9 (12.2) 11.58 (13.34)

Healthy control 15 8/7 39.33 (9.36) – –

– 1.020 0.046 2.359 1.716

– 0.601 0.955 0.328 0.529

13.14 (6.31) 59 (16.67)§ 21.57 (14.81)§ 11.71 (4.42) 22.4 (3.9)§

13.8 (3.77) 65.6 (20.1) # 28.3 (6.94) 14 (4.62) 20.44 (4.1) #

11.53 (1.77) 12.33 (2.32) 36.2 (8.39) 15.73 (5.89) 13.07 (2.74)

1.185 55.365 5.796 1.433 20.975

0.32 b0.001 b0.001 0.255 b0.001

Data are presented as mean (standard deviation). Boldfaced P-values indicate significant differences (P b 0.05) in appropriate statistical tests. Results of post-hoc ANCOVA test in neuropsychological tests were corrected for multiple comparisons using Tukey's correction (adjusted for age and sex). Abbreviations: WAIS, Wechsler Adult Intelligence Scale; DE, delayed encephalopathy. # P b 0.05 in post-hoc comparison with normal control and non-DE groups. § P b 0.05 in post-hoc comparison with normal control and DE groups.

Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030

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organization index, as well as the digit symbol and symbol search tasks, which comprise the processing speed index.

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the diffusion-weighted images were spatially normalized into the Montreal Neurological Institute standard space. The final voxel size of each image was 2 mm3.

2.3. Data acquisition All MRI scans were acquired on a 3 T MRI system (Signa; GE Medical Systems) equipped with an eight-channel head coil. DTI was acquired using a single shot spin-echo echo-planar imaging sequence (TR/TE = 15,800/77.4 ms; 55 slices; NEX = 6; matrix size = 256 × 256; field of view = 256 × 256 mm; slice thickness = 2.5 mm without gaping; voxel size = 1 × 1 × 2.5 mm). The diffusion images gradient encoding schemes include 13 non-collinear directions with a b-value of 1000 s/mm2 and a non-diffusion weighted image volume (b-value = 0 s/mm2). The T1-weighted structure images were acquired using the threedimensional fast spoiled gradient recalled echo sequence (TR/TE/TI = 9.4/3.8/450 ms; flip angle = 20°; 110 slices; NEX = 1; matrix size = 512 × 512; field of view = 240 × 240 mm; slice thickness = 1.3 mm; voxel size = 0.47 × 0.47 × 1.3 mm). All the images were acquired parallel to the anterior–posterior commissure line. The total scanning time for this protocol was 21 min for each participant. 2.4. Data pre-processing All image pre-processing and analyses were performed with the FSL V4.1 (Functional Magnetic Resonance Imaging of the Brain's Software Library, Oxford, UK; http://www.fmrib.ox.au.uk/fsl) [16]. To reduce eddy current distortions and motion artifacts, each diffusion-weighted image was registered to the non-diffusion weighted image by an affine registration approach that was supplied in FMRIB's Linear Image Registration Tool. We then used the Brain Extraction Tool to strip the skull from the non-diffusion weighted image and from the corresponding T1-weighted image of each participant to remove non-brain tissue and background noise from the images, ensuring the accuracy of cross-modality image registration [17,18]. 2.5. Data analysis All image data analyses and parcellations of the CC were performed as previously described in detail [18]. 2.5.1. Standard space identification and cross modality image registration For group comparison, the Montreal Neurological Institute space was used as the standard template space in the present study. We used a two-stage registration approach to determine the transformation matrix for registering the DTI dataset from the native space to the Montreal Neurological Institute space for each subject [19]. First, the transformation matrix was determined by registering the nondiffusion weighted image to a high-resolution T1 image with a 6 degrees of freedom affine registration approach by using FMRIB's Linear Image Registration Tool. Then the transformation matrix was determined by transferring the structural T1 image to the Montreal Neurological Institute T1 standard template with a nonlinear registration approach by using FMRIB's Non-Linear Image Registration Tool in the linear and non-linear registration procedures. These two transformation matrices were concatenated into a final transformation matrix to transform the images from the native diffusion space to the standard space, a process which helped to avoid possible artifacts due to multiple interpolations of the image registration. The inverse final transformation matrix was also calculated. 2.5.2. DTI analysis The diffusion tensor model was fitted in each voxel using FMRIB's Diffusion Toolbox, which provided a voxel-wise calculation of the FA, AD, and RD values. By using the two-stage registration approach mentioned above, all these diffusion indices inherently registered to

2.5.3. Parcellation of the CC A probabilistic tractography was performed to parcellate the entire three-dimensional human CC into different subregions based on connection profiles according to previous detailed literature [18,20,21]. The probability distribution function of the principal fiber direction was calculated in each voxel using a Bayesian approach involving the use of sampling techniques for crossing fibers (BEDPOSTX; part of FSL). After modeling the local diffusion signal in each voxel, the probability distribution of global connectivity between a pair of seed and target regions was also estimated using repeated sampling 5000 times at each voxel in the seed region with a curvature threshold of 0.2 and a step length of 0.5 mm. A spatial probability distribution of the fiber pathway from the seed to the target region was thus measured. The seed mask for the entire CC for each subject was derived from the atlas based on the diffusion tensor maps obtained from the International Consortium of Brain Mapping [22]. We combined the genu, body, and splenium labels from the atlas, which are available in the FSL atlas tool. Fig. 1 illustrates the seven cortical regions and the resulting seven subregions of the CC. To determine the target masks of the fiber tractography, the cortical probability image (HarvardOxford-cortmaxprob-thr25–2 mm, provided by the Harvard–Oxford Cortical Structural Atlas) was used to parcellate the whole cortex into seven cortical regions, namely, the prefrontal, the premotor and supplementary motor, the primary motor, the primary sensory, the parietal, the occipital, and the temporal cortices. The definitions used for the seven cortical regions followed those given by previous studies [18,23,24], and detailed definitions of the regions are listed in Supplementary Table A. After probabilistic tracking, the number of samples that passed through each cortical target region was recorded and a probability of the connection from the seed region to each cortical region was calculated as a proportion of the total number of samples (5000 samples). Hard segmentation of the entire CC was performed by classification of the seed region according to the highest probability of connection to the corresponding cortical target regions. All tractography and hard segmentation calculation were performed in the native space of the subject dataset, and the resulting maps were warped into the Montreal Neurological Institute space using the previous two-stage registration approach.

2.6. Statistical analysis 2.6.1. Analysis of demographic data for the different groups The Statistics Package for Social Science, Version 13.0 (SPSS Inc., Chicago; IL USA), was used to perform all of the demographic analyses. The demographic data, including age and sex, were compared among the study groups by using the analysis of variance and Pearson's chi-square tests. An analysis of covariance model with age and sex as the covariates was used to determine the differences in the scores for the NP tests among the three groups. Post-hoc tests with Bonferroni correction were performed for multiple comparisons. The threshold for statistical significance for all the variables was set at P b 0.05.

2.6.2. Analysis of group comparisons regarding the CC subregions Statistical comparisons of the CC subregions in terms of the different diffusivity indices were performed among the three groups, with the analysis of covariance model adjusting for the age and sex of each participant. Post-hoc tests with Bonferroni correction were performed for multiple comparisons.

Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030

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Fig. 1. Three-dimensional surface reconstruction of the seven cortical target masks including the prefrontal cortex (red), premotor area cortex (orange), primary motor cortex (yellow), primary sensory cortex (green), parietal cortex (blue), occipital cortex (light blue), and temporal cortex (pink) (a), the CC topography of each subject was established using a connectivitybased parcellation approach with a hard segmentation method (b). The data illustrated in this figure were obtained from 1 NC subject, 1 DE subject, and 1 non-DE subject. The color of each CC subdivision corresponds to its connection profile for the different cortical areas. From the CC topography, the proportions of CC parcellation revealed no significant differences among the three groups. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

2.6.3. Correlation between NP test scores and subregional diffusivity indices of the CC To determine the correlations between the NP testing scores and the diffusion indices for the subregions of the CC in the patient subjects (including both the DE and non-DE groups), Pearson's skipped correlation analysis [25] was performed on data after removing bivariate outliers. The significance threshold was set to a P-value of less than 0.05.

3. Results 3.1. Clinical characteristics and NP performance There were no significant differences among the three groups in terms of age (P = 0.955) or sex (P = 0.601). The mean interval between the initial CO exposure and the date of the MRI study and NP testing was 29.9 ± 12.2 months (range: 6–45 months) in the non-DE group and 23.1 ± 17.54 months (range: 6–51 months) in the DE group. Patients without DE (n = 10, non-DE group) underwent treatment during the acute stage of CO intoxication. Eight patients suffered an initial loss of consciousness and subsequently recovered after treatment. None of these non-DE subjects exhibited neurologic or psychiatric symptoms during the later follow-up period. In contrast, the patients with DE (n = 10, DE group) all presented delayed neuropsychiatric sequelae during the follow-up period. Half of the patients with DE (n = 5) underwent acute treatment at another hospital; therefore, their clinical histories with regard to the acute stage were unclear. The other DE patients (n = 5) suffered an initial loss of consciousness from which they then recovered after treatment in the acute stage. Symptoms of DE (n = 10) included consciousness change (n = 3), Parkinsonism (n = 2), dystonia (n = 3), insomnia (n = 1), and gait disturbance (n = 1). The patients with DE had gradually recovered from the symptoms, but most of them still exhibited some neuropsychiatric disorders during the chronic stage. Fifteen of the total 20 CO intoxication patients underwent conventional MRI during the acute stage, with the results including unremarkable findings (total = 8; DE = 3, non-DE = 5), globus pallidus signal change (DE = 6), and WM lesions (DE = 4). Three patients presented with concomitant globus pallidus and WM change. According to post-hoc analysis of the NP test values, the DE and nonDE groups performed significantly worse than the NC group on the digit symbol and digit span tests (P b 0.001). For the symbol search test, there

was only a statistically significant difference between the DE and NC groups. 3.2. Group comparisons of the DTI indices in the CC subregions The mean values of the subregional DTI indices for the DE, non-DE, and NC groups are presented in Table 2. Compared to the NC subjects, the DE group subjects had lower FA and higher RD values in the prefrontal, premotor, primary motor, primary sensory, parietal, and occipital CC subregions. Compared to the non-DE group, the DE group presented with lower FA values in the prefrontal and premotor subregions and a higher mean RD value in the prefrontal subregion. 3.3. Correlations between the DTI indices in the CC subregions and the NP test scores We found significant correlations between the NP test scores and the DTI indices in the CC subregions, as detailed in Fig. 2. Poorer symbol search test scores were positively correlated with higher FA values in the prefrontal, primary sensory, and parietal subregions, and negatively correlated with lower RD values in the primary sensory subregion. 4. Discussion To date, the relationship between the severity of CC damage and altered cognitive function in DE and non-DE patients after CO intoxication has not been fully studied. We successfully and accurately subdivided the entire three-dimensional CC into functional subgroups by parcellating them according to individual cortical trajectories to different cortical areas. The in vivo DTI study showed that callosal damage had developed extensively over several subregions of the CC in the DE group. Furthermore, the altered fiber integrity of the subregional CC fibers connected to the corresponding cortical functional areas correlated well with the scores on the neuropsychological tests. Neuronal injury after global brain anoxia or ischemia might result in Wallerian degeneration in WM [26]. Nevertheless, nerve fiber damage might also be the direct effect of hypoxic–ischemic injury and is probably independent of the neuronal injury [26]. A parameter derived from the directional diffusivities of DTI has been validated as a useful marker to evaluate white matter integrity as well as the conditions of the myelin and axons [27]. An alteration in AD indicates axonal damage in the

Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030

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Table 2 Mean values of DTI indices in CC subregions of the DE, non-DE, and normal control groups. CC subdivision

Prefrontal

Premotor

Primary motor

Primary sensory

Parietal

Occipital

Temporal

FA NC Non-DE DE F value P value

0.56 ± 0.03 0.54 ± 0.03 0.44 ± 0.09a,b 13.84 b0.001

0.57 ± 0.04 0.53 ± 0.05 0.44 ± 0.09a,b 11.51 b0.001

0.55 ± 0.04 0.50 ± 0.03 0.45 ± 0.08b 7.877 0.002

0.58 ± 0.04 0.52 ± 0.07 0.46 ± 0.07b 4.61 0.018

0.59 ± 0.04 0.56 ± 0.05 0.49 ± 0.1b 3.914 0.031

0.64 ± 0.03 0.59 ± 0.05 0.52 ± 0.06b 5.49 0.01

0.59 ± 0.04 0.59 ± 0.07 0.58 ± 0.08 0.131 0.871

AD NC Non-DE DE F value P value

1560 ± 65 1607 ± 64 1631 ± 245 0.939 0.403

1462 ± 45 1500 ± 94 1509 ± 196 0.828 0.447

1685 ± 86 1714 ± 109 1722 ± 153 0.304 0.74

1792 ± 90 1893 ± 150 1847 ± 280 1.062 0.359

1494 ± 69 1497 ± 43 1494 ± 149 0.001 0.998

1734 ± 79 1811 ± 120 1859 ± 200 2.852 0.074

1908 ± 147 1907 ± 173 1853 ± 241 0.27 0.765

RD NC Non-DE DE F value P value

600 ± 76 662 ± 63 818 ± 216a,b 7.417 0.003

524 ± 65 612 ± 54 733 ± 185b 10.051 b0.001

686 ± 82 788 ± 82 857 ± 155b 6.733 0.004

681 ± 86 864 ± 173 885 ± 301b 3.955 0.03

523 ± 54 574 ± 92 624 ± 120b 3.405 0.047

589 ± 79 724 ± 130 798 ± 260b 5.47 0.01

803 ± 209 788 ± 199 768 ± 181 0.132 0.877

CC volume (cm3) NC Non-DE DE F value P value

16.1 ± 1.1 16.1 ± 0.98 16.4 ± 2.6 0.163 0.85

4.9 ± 0.56 4.67 ± 0.74 4.75 ± 0.69 0.286 0.75

1.59 ± 0.36 1.36 ± 0.36 1.17 ± 0.46 3.268 0.051

1.2 ± 0.24 1.17 ± 0.27 0.82 ± 0.4b 3.768 0.034

6.59 ± 1.14 6.53 ± 0.83 6.89 ± 0.88 0.372 0.693

5.67 ± 1.24 5.87 ± 1.13 5.64 ± 1.12 0.106 0.9

3.46 ± 1.4 3.32 ± 0.9 3.47 ± 1.2 0.046 0.956

ANCOVA analyses were applied to estimate statistical differences among the three study groups (adjusted for age, sex, and CC volume). Results of post-hoc test were corrected for multiple comparisons using Bonferroni correction (P b 0.05). The unit of the diffusivity values (AD and RD) is 10−6 mm2/s. The DTI indices are presented as means ± standard deviation. Abbreviations: DE, delayed encephalopathy; CC, corpus callosum; FA, fractional anisotropy; AD, axial diffusivity; RD, radial diffusivity; NC, normal control. a P b 0.05 in post-hoc test with DE and non-DE groups. b P b 0.05 in post-hoc test with NC and DE groups.

fibers, whereas an alteration in RD suggests demyelination with a disruption of myelin integrity [28,29]. For the DE group, the decreased FA, increased RD, and unchanged AD values in the prefrontal, premotor, primary motor, primary sensory, parietal, and occipital subregions suggest that fiber myelin damage may be an important component in the development of DE [7]. However, the variable clinical course noted in our study and references suggests different individual vulnerabilities to CO intoxication, whether directly or indirectly. Special caution should thus be taken before drawing any conclusions regarding which processes occur in the WM after CO intoxication. This CC parcellation study provided a highly objective method for clarifying significant CC damage in different subregions in patients after CO intoxication. Previous evidence has indicated that generalized CC atrophy might occur in patients with CO intoxication [5]. In addition, extensive frontal, parietal, basal ganglia, and hippocampus damages have been observed in DE patients as compared to non-DE patients [30]. However, little is known about the differences between DE and non-DE groups in terms of the WM integrity in the subregions of the CC. Compared with non-DE patients and NCs, patients with DE displayed more myelin damage in several subregions of the CC in the chronic stage, even after controlling for the volume of the CC. Our results indicating that temporal CC subregions in patients with DE were less affected were also consistent with previous findings showing that less injury occurs in the temporal lobes [7]. However, the fibers in the temporal lobes constitute only a small component of the CC parcellation in the present study and thus might not be able to represent the integrity of the temporal lobes completely. Another explanation for the anterior–posterior gradient distribution of the CC damage is the special myelination difference along the whole structure, with small diameter fibers being located anteriorly and large fibers being located more posteriorly [31]. These different microenvironments of the CC might cause the different degrees of damage that occurred from CO intoxication in our subjects and thus help to explain our findings. In addition, damage to deep WM structures, such

as the centrum semiovale, which contains abundant projection fibers connecting to the frontal and parietal cortices, has been emphasized as being highly correlated with the presentation of chronic symptoms after CO intoxication [32]. Although the pathogenesis of DE after CO intoxication is likely multi-factorial, anterior circulation seems more vulnerable to damage in DE. Results of diffusion-weighted images in patients with CO intoxication have been found to vary substantially depending on the timing of the examination [32]. By using DTI, the early detection of lower FA at 2 weeks after CO poisoning can predict the presence of DE [32], while lower FA in the centrum semiovale might be observed to continue until 3 months after the poisoning [33]. The initial decreased FA and increased RD values might deteriorate with progressive changes at 10 months, without any improvement in cognitive functioning [11]. Our assessment results for patients with and without DE at 30 months and 24 months after intoxication showing low FA and high RD values in the CC further supplement the data of previous studies by adding a level of chronological detail to the relationship between WM damage and clinical disease status. Based on a variety of previous histological and image findings, it can be concluded that our findings of CC damage using a probabilistic tractography method which can depict fibers connecting to specific regions in the cerebral cortex in the current study do not contradict the findings of previous studies suggesting that damage to WM between the CC and cerebral cortex is responsible for chronic symptoms. In previous studies, a wide range of cognitive sequelae after CO poisoning, including poor mental processing speed and poor working memory, were found to be evident [3,34,35]. In this study, in comparisons with non-DE patients, relatively worse cognition scores for the symbol search task were found in DE patients at 2.5 years after CO poisoning. Although our results were limited to a small sample of patients who had been affected by CO intoxication, and thus might overlook the issue of selection bias, they tend to suggest that WM damage in DE could persist and even remain irreversible long after the

Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030

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Fig. 2. Scatterplots showing the correlations between the NP test scores and the DTI indices of the CC subregions in the patient groups.

intoxication event. The symbol search test of the Wechsler Adult Intelligence Scale has previously been used to measure the processing speed of patients, and this speed has been found to be related to lesions in areas of the middle frontal gyrus, postcentral gyrus, and inferior parietal gyrus [36]. In this study, an association between slower processing speeds in symbol search testing and lower FA and higher RD values further supported the pathophysiological finding of WM damage in the CO intoxication. These results provided evidence that cognitive performance was affected after CO intoxication and that these effects persisted in particular patients, in addition to indicating accompanying CC subregion damage in functionally relevant cortical areas. Although this study offers valuable insights into the involvement of the corpus callosum in CO intoxication issues, it nevertheless has some limitations. First, our sample size was too small for definite conclusions relating to DE and non-DE patients. Patients without DE were difficult to contact and often rejected invitations to join the non-invasive research because they have little concern about following up on results in the chronic stage. Therefore, the number of patients in the non-DE group was the same as the number of patients in the DE group, even though DE occurs relatively rarely, with an approximate incidence of only 10% among all CO-intoxicated patients [3]. Second, the treatments provided for CO-intoxicated patients vary, including, for example, whether they receive hyperbaric oxygen therapy or not. Moreover, the initial laboratory data were not thoroughly collected for every subject in the emergency room. Therefore, initial disease severity could not be compared

to long-term outcomes to define a clearer relationship. Rather, we have only provided indirect evidence of the relationship between the integrity of the CC microstructures and cognitive performance in this cross-sectional study design. The prospective trajectory of the CC network changes would provide more direct information regarding the temporal correlation between the development of DE and the corresponding connecting CC fibers. Finally, the signal-to-noise ratio (SNR) is an important factor in DTI index calculations and tensor orientation estimations [37]. A recent review suggested that the SNR needs to be considered when setting the protocol for DTI-based studies [38]. Although the current DTI datasets were suboptimal in terms of the number of diffusion-encoding directions, the SNR of CC calculated according to previous suggestion was sufficiently high to produce reliable DTI-related measurements [37,39]. Conflicts of interest On behalf of all the authors, we declare that all human and animal studies have been approved by the Chang Gung Memorial Hospital ethics committee and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. We further declare that all the patients gave informed consent prior to inclusion in this study. We also declare that we do not have any actual or potential conflicts of interest, including any financial, personal, or other relationships with other people or

Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030

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Please cite this article as: P.-C. Chen, et al., Callosal damage and cognitive deficits in chronic carbon monoxide intoxication: A diffusion tensor imaging study, J Neurol Sci (2015), http://dx.doi.org/10.1016/j.jns.2015.05.030