NeuroToxicology 56 (2016) 225–232

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NeuroToxicology

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Longitudinal diffusion tensor imaging of the rat brain after hexachlorophene exposure Jaivijay Ramua , Tetyana Konaka , Merle G. Paulea , Joseph P. Hanigb , Serguei Liachenkoa,* a b

Division of Neurotoxicology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States Center for Drug Evaluation and Research, Food and Drug Administration, White Oak, MD, United States

A R T I C L E I N F O

Article history: Received 10 March 2016 Received in revised form 17 August 2016 Accepted 17 August 2016 Available online 20 August 2016 Keywords: DTI Axial diffusivity Radial diffusivity Fractional anisotropy Hexachlorophene

A B S T R A C T

Longitudinal MRI employing diffusion tensor imaging and T2 mapping approaches has been applied to investigate the mechanisms of white matter damage caused by acute hexachlorophene neurotoxicity in rats in vivo. Male Sprague-Dawley rats were administered hexachlorophene orally once a day for five consecutive days at a dose of 30 mg/kg and were monitored in 7T MRI scanner at days 0 (baseline), 3, 6, 13, and 20 following the first hexachlorophene dose. Quantitative T2 maps as well as a number of diffusion tensor parameters (fractional anisotropy, radial and axial diffusivity, apparent diffusion coefficient, and trace) were calculated from corresponding MR images. T2, as well as all diffusion tensor derived parameters (except fractional anisotropy) showed significant changes during the course of neurotoxicity development. These changes peaked at 6 days after the first dose of hexachlorophene (one day after the last dose) and recovered to practically baseline levels at the end of observation (20 days from the first dose). While such changes in diffusivity and T2 relaxation clearly demonstrate myelin perturbations consistent with edema, the lack of changes of fractional anisotropy suggests that the structure of the myelin sheath was not disrupted significantly by hexachlorophene in this study. This is also confirmed by the rapid recovery of all observed MRI parameters after cessation of hexachlorophene exposure. ã 2016 Published by Elsevier B.V.

1. Introduction Hexachlorophene (HC), an organochlorine compound and a potent neuro-toxicant typically used to treat burns and prevent Staphylococcus aureus infection in infants (Alder et al., 1980; Heath et al., 2000) is known to cause alterations in white matter in the brain. It is still used as a prescription anti-infective topical preparation in the US. Although HC is typically administered externally, there have been reported instances of accidental ingestion of HC, due to its similar appearance to milk of magnesia, which have resulted in spongy degeneration of white matter (Kimbrough, 1973; Mullick, 1973). Several reports, including some dating back to the 70’s have described some of the toxic effects of

Abbreviations: AD, axial diffusivity; cc, Corpus Callosum; Comm, Commissures; DTI, diffusion tensor imaging; fim, Fimbria; HC, hexachlorophene; IC, Internal Capsule; FA, fraction anisotropy; RD, radial diffusivity. * Corresponding author at: NCTR/FDA, 3900 NCTR Rd, Jefferson, AR, 72079, United States. E-mail addresses: [email protected] (J. Ramu), [email protected] (T. Konak), [email protected] (M.G. Paule), [email protected] (J.P. Hanig), [email protected] (S. Liachenko). http://dx.doi.org/10.1016/j.neuro.2016.08.011 0161-813X/ã 2016 Published by Elsevier B.V.

HC (Lockhart, 1972; Kimbrough, 1973; Mullick, 1973; Shuman et al., 1974; Catalano, 1975; Shuman et al., 1975b, 1975a; Paul and Gordon, 1978; Tripier et al., 1981; Vorherr et al., 1988; Flanagan et al., 1995; Boyd et al., 2010; Kanno et al., 2012; Hanig et al., 2014; Itahashi et al., 2014), which include nausea, vomiting, diarrhea, dehydration, hypotension, irritability, weakness of lower extremities, and finally convulsions in human patients, and drowsiness with hyperactivity, hind limb paralysis accompanied with very high cerebrospinal fluid pressure in mice, rats, cats, and monkeys. Almost all clinical and non-clinical observations of HC toxicity were accompanied with brain edema and vacuolation of white matter, described as status spongiosis (Kimbrough, 1973; Mullick, 1973; Hanig et al., 1976). White matter changes caused by HC consistent with edema were also observed in vivo using MRI (Igisu and Kinoshita, 2007; Hanig et al., 2014). If human patients survive exposure to HC, the effects are reversible without noticeable longterm implications (Lockhart, 1972). In rats recovery from neurological effects occurs rather rapidly (days to weeks). Neuropathology and behavioral evidence takes longer to return to the normal state (Lockhart, 1972; Hanig et al., 1976; Hanig et al., 1977; Hanig et al., 1984). Overall there were 15 deaths reported in US (Lockhart, 1972; Kimbrough, 1973; Mullick, 1973; Culliford et al., 1974) and 39 in

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France (Martin-Bouyer et al., 1982), which were partially attributed to misuse of HC. The exact molecular mechanisms underlying HC toxicity are unknown. Scarce evidence suggests of its possible interference with liver and brain mitochondrial oxidative phosphorylation (Cammer and Moore, 1972), inhibition of myelin carbonic anhydrase (Cammer et al., 1976), and activation of lipid peroxidation in brain membranes (Rakhit and Hanig, 1984). On the cellular level the formation of spongiform lesions with vast vacuolation and splitting across the myelin sheath in white matter has been reported (Webster et al., 1974; Tripier et al., 1981). Behaviorally HC toxicity is manifested as motor dysfunction (hindlimb paralysis) and also problems with memory and cognition (Kimbrough, 1973). Despite the fact that HC is clearly known to cause significant white matter vacuolization, some recent studies have investigated potential beneficial effects of this compound, especially in the field of oncology where it is uses to inhibit b-Catenin degradation (Park et al., 2006; Miller et al., 2012; Zheng et al., 2012). However, there are insufficient data on the life cycle of the neurotoxic effects associated with HC to provide for its prudent use, clinically. Noninvasive MRI offers the unique opportunity for longitudinal investigations of the brain toxicity caused by HC, including changes in white matter. Diffusion Tensor Imaging (DTI) has been widely used to characterize white matter in vivo and to provide specific measures that can be related to, or correlated with, axonal damage (Assaf and Pasternak, 2008; Barrick et al., 2010; Amlien and Fjell, 2014). DTI utilizes the directional properties of water diffusion that is determined by the microstructure of the tissue under investigation. Brain white matter–as opposed to gray matter, is also characterized by higher anisotropy, which also depends on the compartmentalization (e.g. myelination) and direction of nerve fibers (Basser et al., 2000; Gulani et al., 2001; Beaulieu, 2002; Mori and Zhang, 2006; Alexander et al., 2007). DTI measurements provide specific scalar metrics including Fractional Anisotropy (FA), Trace, Axial Diffusivity (AD) and Radial Diffusivity (RD). FA provides information about the level of microstructural organization and Trace is highly sensitive to edema and demyelination. AD and RD correspond to the restricted diffusion of water parallel and perpendicular, respectively, to the orientation of the imaging plane, which, if oriented along or across the myelin sheath can provide specific information about changes in white matter (Gulani et al., 2001; Song et al., 2002; Schwartz et al., 2005). Information from the DTI scalars can be compiled to generate probabilistic paths of the fiber tracks based on the directionality of the main diffusion vector (Mori et al., 2002; Mori and van Zijl, 2002; Nucifora et al., 2007). A simpler approach – quantitative T2 mapping has been used in the past to study the toxic effects of HC (Kinoshita et al., 2000; Hanig et al., 2014). In the current study both DTI and T2 mapping have been employed to characterize the development of neurotoxic changes and subsequent recovery of white matter after HC exposure. 2. Materials and methods 2.1. Animal preparation The animal use protocol was approved by the National Center for Toxicological Research Institutional Animal Care and Use Committee. Adult male Sprague-Dawley rats (N = 15, 329  20 g) were either given HC (N = 10, 30 mg/kg) or pure vehicle (corn oil, N = 5, 1 ml/kg) orally (via gavage), once a day, for 5 consecutive days. Animals were kept under a typical 12/12 h day/night light cycle, watered and fed ad lib a standard rat chow diet and were single-housed in polypropylene cages outfitted with ventilatedtop isolators and natural wood chip bedding.

2.2. MRI MR imaging was performed using a 7 T Biospec Avance III MRI system (Bruker MRI, Billerica, MA) with a 12 cm ID gradient insert (600 mT/m). A four channel split-array rat brain RF coil (Rapid MR International, Columbus, OH) was used for receiving and a 72 mm birdcage RF coil (Bruker MRI, Billerica, MA) was used for transmitting the MRI signals. Animals were anesthetized with isoflurane (3% induction, 1–2% maintenance at 1 L/min in oxygen). Body temperature was kept at 37.3  0.6  C using a water-heated imaging cradle. For T2 relaxation mapping of the whole brain, a multi-slice, multi-echo spin echo sequence was used (image matrix 192  192  24, field of view = 3.84  3.84  2.4 cm, echo spacing = 15 ms, 16 echoes, repetition time = 6 s, number of averages = 1, total acquisition time  20 min). High-resolution anatomical reference images were acquired using a fast spin echo sequence with the following parameters: rare factor of 8, TR/TE of 9000/17.5 ms, image matrix of 192  192  56, field of view = 3.84  3.84  2.8 cm. DTI images were acquired with geometry identical to the anatomical images using a multi-shot 3D spin echo EPI sequence (number of shots 4) with TR/TE of 1000/41.73 ms, b factor of 1000 s/mm2, bandwidth of 250 kHz, 30 diffusion encoding directions, using the same geometry and matrix as the anatomical reference images. 2.3. T2 analysis T2 maps were calculated using voxel-by-voxel single-exponential fitting of image intensities and analyzed using an arbitrary threshold (Hanig et al., 2014; Liachenko et al., 2015). Voxels with T2 values equal to or less than 72 ms inclusive were designated as normal tissue and voxels with T2 values above 72 ms were designated as lesion tissue (Liachenko et al., 2015). Prior to thresholding, skull stripping of all T2 maps was performed to remove non-brain tissue from the images using semi-automated routines created in-house. 2.4. DTI analysis Diffusion weighted images were initially pre-processed for intra-subject motion correction using SPM8 software (Wellcome Department of Imaging Neurosceince, UCL, London). Semiautomated skull-stripping and 12-parameter affine transformation registration to a chosen subject (inter-subject) was performed using Medical Image Processing, Analysis and Visualization (MIPAV) software (mipav.cit.hin.gov). The co-registered images were then imported into DTI Studio software (Jiang et al., 2006) to calculate the DTI parameters such as FA, Trace, AD and RD. RGB*FA (FA modulated by the principal eigenvectors) was also generated by multiplying the FA image by the principal Eigen vector images. 2.5. T-Maps The registered FA, Trace, AD and RD maps were averaged based on time-points and a two-sample, two-tailed t-test (P < 0.05) was performed using SPM8 as described elsewhere (Ramu et al., 2008). T-tests were performed for unbiased determination of significant regions in the DTI scalars between the time-points. Maps of these significant differences were generated (t-maps). 2.6. ROI analysis The Region of Interest (ROI) analyses of the DTI scalars were performed using ImageJ software (http://imagej.nih.gov/ij/). Based on published literature, four major white matter structures including the internal capsule (IC), fimbria (Fim), genu of the

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Fig. 1. T2 maps of a representative animal obtained at various time points (days, shown below each map) after HC treatment. A single slice out of a 24 slice pack is shown. The color scale (on the right) relates to the actual T2 relaxation time (in milliseconds) for each voxel. Note the maximum T2 values in the white matter occurred at day 6. T2 maps of the control subjects (not shown) were not different from T2 maps at time 0.

corpus callosum (CC) and commissures (Comm – anterior & posterior combined) were assessed using the ROI analyses (Ramu et al., 2008; Rumple et al., 2013). ROIs were defined on a reference image (a chosen template image) and the same set was used to obtain the DTI scalar values from all the animals in the study. 2.7. Fiber tracking DTI Images were averaged and grouped based on time-points and fiber tracking was performed using a Fiber Assignment by Continuous Tracking (FACT) algorithm (Mori et al., 1999) using the DTI Studio (Jiang et al., 2006). The same set of ROIs used in the ROI analyses were used as seed points for the fibers. An FA threshold of 0.15 and an angle threshold of 700 were used to trace the fiber tracks based on termination criteria described by Mori et al. (Mori and van Zijl, 2002) originating from the CC, Comm, IC and Fim regions. Fiber tracking bundles were generated for the four locations at Day 0 and Day 6 for visual comparison and DTI scalar values for voxels aligned with the fiber tracks were also extracted. 2.8. Statistical analysis A one-way repeated measures ANOVA was used to analyze T2 changes. A two-way repeated measures ANOVA (one factor repetition) was performed on the ROI values for the DTI scalars. Post-hoc pairwise multiple comparisons between the groups were performed using the Holm-Sidak method. All statistical analysis was performed using SigmaPlot software (Systat Software, San Jose, CA).

Comm, IC and Fim) in which the ROIs were located. The intensity in the grayscale FA image indicates the FA values; white matter has higher FA values than gray matter. Figs. 5A-D are t-maps for coronal and axial images (shown in red) for FA (A), Trace (B), AD (C) and RD (D) respectively. The maps (colored areas) are superimposed on averaged corresponding DTI scalar images and represent significant (P < 0.05) group differences in the DTI scalar values at different time-points after HC administration. Bar graphs showing differences in the ROI analyses for four regions (IC, Fim, CC, Comm) are shown in Fig. 6. Significant differences in comparison with Day 0 values are indicated. While FA data did not show any significant differences over days, Trace, AD and RD data all showed clear decreases at Days 3, 6 and 13 gradually recovering to near Day 0 values by Day 20. Fig. 7 shows the fiber tracks generated for the same ROIs that were used in the analyses of the four regions represented in Fig. 6. The fiber tracks are color-coded based on the specific white matter tracks originating from voxels within the ROIs and are shown in three different (axial, coronal and sagittal) planes. The tracks shown do not encompass the entire bundles of white matter but only show those originating in each specific ROI. The comparison of the fiber bundles clearly demonstrates the location of the white matter changes along the major tracks from Day 0 to Day 6. The loss of tracks on day 6 does not necessarily mean the loss of connectivity, but rather reflects the inability of the tracking software to extract meaningful probabilistic information about those tracks in the HC-treated brain.

3. Results There were no statistical differences in body weight between treated and control groups of animals across all time points observed in this study. Fig. 1 shows the temporal changes in T2 maps after HC treatment over the course of the study in a single animal. Control rats treated with corn oil did not show any changes and were not included in the analysis. The lesion area as determined by changes in intensity of T2 signals were noticeable 3 days after the start of HC administration and reached a maximum at day 6, followed by almost complete recovery by day 20. Fig. 2 shows T2 lesion volumes as a function of days after the onset of treatment as determined using an arbitrary thresholding approach (Liachenko et al., 2015). The lesion volume was significantly larger on days 6 and 13 in comparison to Day 0 for the HC treated rats. Furthermore, the HC treated rats had significantly larger lesion volumes compared to control rats on days 6, 13, and 20. The temporal evolution of FA, AD and RD maps for a single representative subject is shown in Fig. 3. Fig. 4 shows the FA and color coded RGB*FA (FA modulated by the principal eigenvectors) maps averaged over 10 animals at baseline. These images also show the white matter locations (CC,

Fig. 2. Changes in volumes of ‘lesion’ tissue calculated using a thresholding method (see Methods section) in rats before (0 days) and after the start of saline (control, open circles) or hexachlorophene (HC, black circles) treatment. Data are means  standard deviations. * – statistically significantly different from time 0 within the same group (P < 0.05); # – statistically significant difference from control within the same time point (P < 0.05).

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Fig. 3. Longitudinal comparison of fractional anisotropy (FA), axial diffusivity (AD) and radial diffusivity (RD) maps in a representative animal prior to image co-registration. Qualitative differences in AD and RD in the corpus callosum area are evident starting at day 3 (arrows).

4. Discussion The aim of this study was to investigate the evolution and characteristics of white matter changes following HC exposure and DTI would seem to be the most appropriate methodology for this purpose. The dose of HC was chosen such that it would reliably produce MRI-detectable lesions in the brain while not drastically reducing survival rates based on our previous experience and published literature (Kinoshita et al., 2000; Hanig et al., 2014). To our knowledge, this report is the first attempting to non-invasively characterize HC-induced white matter lesions using diffusion

Fig. 4. Fractional anisotropy (FA) and color coded FA modulated by the principal eigenvectors (RGB*FA) maps averaged over 10 animals at baseline. The images also show the white matter locations (cc, comm, ic and fim) in which the regions of interest were located. Green represents the principal eigenvalue orientations of fibers that propagate from left to right, red represents those that propagate in the ventral-dorsal direction and blue represents rostral-caudal propagation. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

tensor MRI. The findings here provide valuable information pertaining to the differentiation of myelin and axonal changes in white matter. FA, AD and RD maps (Fig. 3) prior to registration clearly show HC-induced changes observed at Day 6 as well as the subsequent trend of the effect. These qualitative observations are consistent with the T2 mapping results. The registration, averaging and distortion correction procedures help to obtain statistical tmaps for various DTI metrics. The t-maps reveal the statistically significant differences seen in the DTI scalars under study. T2 maps clearly showed HC-induced lesions in the rat brain, reflecting the progression and regression of changes consistent with tissue edema. The location of these lesions suggests a predominant location in white matter. T2 acquisitions took only 20 min in comparison to the 70 min needed for the acquisition of DTI. In addition, DTI processing requires a correction for geometrical distortion (Zeng and Constable, 2002), several stages of image registration and averaging. The maximum lesion volume was observed at Day 6, which is consistent with previously published literature (Kinoshita et al., 2000). A limitation of the T2 metric is that it is not specific to the mechanism of toxicity. A host of changes including edema, vacuolization, ionic pump failure, neurochemical or even a simple change in temperature can affect T2 values in brain (Drayer et al., 1986; de Graaf et al., 2006; Kharatishvili et al., 2009; Hanig et al., 2014). The results of the t-maps are complimented by the ROI analyses, which also reveal the trend of declining values at days 3 and 6. Usually, a variety of factors contribute to changes in DTI scalars (see Table 1). Previous studies have shown clear correlations between AD and RD metrics to axonal integrity and myelination (Song et al., 2002; Thomalla et al., 2004; Nair et al., 2005; Feldman et al., 2010; Alexander et al., 2011; Feldman et al., 2012). AD is generally considered to be sensitive to white matter pathology and any axonal injury would result in a decrease in AD values (Alexander et al., 2011). RD values increase with de-myelination but they can also be influenced by changes in axon diameter or density. Since the RD values in our study decreased with time after HC exposure, this strongly suggests that the observed changes are associated with changes in axon density and not with significant demyelination. Trace metrics are highly sensitive to edema and the evidence of this is clearly apparent in current data. The FA metric is usually less specific to the type of macrocellular changes that occur

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Fig. 5. Axial and coronal slices of the averaged parametric maps for fractional anisotropy (A), trace (B), axial diffusivity (C), and radial diffusivity (D) with superimposed tmaps (colored) showing voxels with statistically significant (P < 0.05) group differences from the baseline (day 0) at different times after HC administration.

but it is very sensitive to microstructural changes: the differences seen at day 6 clearly relate to the impact of individual diffusivities on FA. It is possible that axonal changes might be the main contributors to the changes observed in FA. Decreasing RD values typically translate to denser axonal packing and there might not be

any associated de-myelination which, in turn, would result in minimal influence on FA. The ROI analyses did not detect significant differences in FA whereas the t-maps clearly identified specific areas of change. It is possible that the chosen ROIs did not exhibit statistically significant damage, or that the values might

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Fig. 6. Bar graphs showing the differences in the ROI analyses for four regions (ic, fim, cc, comm). *, # denote significant differences (p < 0.05) in comparison to Day 0. Data are means  standard errors of the means.

Fig. 7. Fiber tracks generated using the predefined ROIs (see Fig. 4) as seed points for the four studied regions. The fiber tracks are color-coded based on the specific white matter tracks originating from the voxels of the ROI and are shown in three different (axial, coronal and sagittal) planes. Note the lesser amount of fiber tracks shown at day 6 due to inability of the software to effectively calculate them after HC-induced white matter changes.

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have been affected by the partial volume averaging and, thus, higher standard deviations due to imperfect co-registration. Nevertheless, using two different methods helped to identify areas characterized by statistically significant damage. The fiber tracking results also provide further evidence of possible axonal damage and changes in cellular density as observed in the DTI scalars. Visual inspection of the resulting images allows for the clear observation of reduced anisotropy along the fiber path at Day 6 in comparison to Day 0. This reduced anisotropy does not necessarily mean that the nerve fibers are absent or severed: it is our understanding that increased diffusion reduces FA values and thereby inhibits the propagation of signal along the fiber tracts. Tract-based statistics have been used in the past to assess abnormalities in preterm infants (Anjari et al., 2007). Although the present results clearly capture lower-trending DTI scalars, our analyses might also benefit from the use of advanced DTI methodologies such as q-ball imaging (Tuch et al., 2002; Tuch, 2004; Wedeen et al., 2008) and probabilistic fiber tracking (Mori and van Zijl, 2002; Descoteaux et al., 2009) that can provide more accurate results at higher resolution. Histopathologic results reported earlier (Hanig et al., 2014) also show the axonal damage (status spongiosis and white matter vacuolation) seen in the MRI images and reductions in axial diffusivity values confirm the same. Similar changes in white matter are noted after exposure to some other neurotoxicants, like triethyltin (Winship, 1988; Aschner and Aschner, 1992), vigabatrin (Sills, 2003; Preece et al., 2004), cyclosporine A (Garcia-Escrig et al., 1994; Edwards et al., 1995; Pace et al., 1995), and acetyl-ethyl-tetramethyl-tetralin (Akasaki et al., 1990). While the white matter damage observed in the present study was expected after HC exposure, a fascinating trend towards reversal of pathology was also revealed for which the underlying mechanisms are not well understood and require further attention. Although DTI was shown to provide mechanistic information, the DTI imaging sequence requires a lot of post-processing steps and is not completely devoid of artifacts and/or distortion. Further imaging approaches using the techniques described here hold great promise for helping unravel the processes associated with the expression of some common white matter diseases: visualization of the reversal of possible axonal damage is particularly noteworthy. In the past, axonal sprouting following injury has been witnessed (Ramu et al., 2008), primarily in response to the administration of neurotrophins such as NT3 (Grill et al., 1997; Chen et al., 2006; Ramu et al., 2007) in injury models. This type of recovery seen in the current study within such a short time span raises some interesting questions as to what kind of mechanisms might be involved. Further histopathology studies might be important for answering some of the questions raised here where the feasibility of performing a longitudinal DTI study on HC treated animals was demonstrated. Conflict of interest None. Acknowledgements This work was supported by the National Center for Toxicological Research (NCTR) and Center for Drug Evaluation and Research (CDER), U.S. FDA [protocol number E07418]. This document has been reviewed in accordance with U.S. FDA policy and approved for publication. Approval does not signify that the contents necessarily reflect the position or opinions of the FDA nor does mention of trade names or commercial products constitute endorsement or recommendation for use. The findings

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