Degeneration of white matter and gray matter revealed by diffusion tensor imaging and pathological mechanism after spinal cord injury in canine

Abstract

Aim: Exploration of the mechanism of spinal cord degeneration may be the key to treatment of spinal cord injury (SCI). This study aimed to investigate the degeneration of white matter and gray matter and pathological mechanism in canine after SCI.

Methods: Diffusion tensor imaging (DTI) was performed on canine models with normal (n = 5) and injured (n = 7) spinal cords using a 3.0T MRI scanner at precontusion and 3 hours, 24 hours, 6 weeks, and 12 weeks postcontusion. The tissue sections were stained using H&E and immunohistochemistry.

Results: For white matter, fractional anisotropy (FA) values significantly decreased in lesion epicenter, caudal segment 1 cm away from epicenter, and caudal segment 2 cm away from epicenter (P = 0.003, P = 0.004, and P = 0.013, respectively) after SCI. Apparent diffusion coefficient (ADC) values were initially decreased and then increased in lesion epicenter and caudal segment 1 cm away from epicenter (P < 0.001 and P = 0.010, respectively). There are no significant changes in FA and ADC values in rostral segments (P > 0.05). For gray matter, ADC values decreased initially and then increased in lesion epicenter (P < 0.001), and overall trend decreased in caudal segment 1 cm away from epicenter (P = 0.039). FA values did not change significantly (P > 0.05). Pathological examination confirmed the dynamic changes of DTI parameters.

Conclusion: Diffusion tensor imaging is more sensitive to degeneration of white matter than gray matter, and the white matter degeneration may be not symmetrical which meant the caudal degradation appeared to be more severe than the rostral one.

Keywords: canine model; diffusion tensor imaging; gray matter; pathological degeneration; spinal cord injury; white matter.

Figure 1

Typical example of seven region of interests (ROIs) of normal and SCI groups (A,B). The segmentation example of white matter and gray matter (C,D). The typical DTI images (E,F,G,H)

Figure 2

Comparison of DTI parameters between control and SCI group at all time points of seven sites along the white matter as analyzed by two‐way ANOVA. The histogram below was the control group (N = 5), and the above histogram was the SCI group (N = 7). An error probability of 0.05 (P) was used as the significance level. All parameters are represented as mean ± standard deviation (SD).**P < 0.001, *P < 0.05, S1‐S7, site1‐site7

Figure 3

Comparison of DTI parameters between control and SCI group at all time points of seven sites along the gray matter as analyzed by two‐way ANOVA. The histogram below was the control group (N = 5), and the histogram above was the SCI group (N = 7). An error probability of 0.05 (P) was used as the significance level. All parameters are represented as mean ± standard deviation (SD).**P < 0.001, *P < 0.05, S1‐S7, site1‐site7

Figure 4

Representation of HE and immunohistochemistry staining in control and SCI groups. A, The shape becomes irregular and the boundaries become unclear. B, Amorphous cavity formation and spreads to the white matter. C, The scar formed at the posterior horn of gray matter, and the boundary had a deformity. D,E,F, The axons of the white matter fiber bundle were degenerated and became messy. G,H,I, The darker reactive glial scar almost occupied most of the spinal cord area in the epicenter. At the rostral and caudal levels, the reactive glial cells proliferated and went beyond the gray matter area. Based on the figures from Liu et al14

Figure 5

Representative histogram profile and score of a cytoplasmic stained image using IHC Profiler. A, Profiling of DAB and hematoxylin‐stained cytoplasmic image sample. The histogram profile corresponds to the pixel intensity value vs corresponding number counts of pixel intensity. The log given below the hematoxylin‐stained image shows the accurate percentage of the pixels present in each zone of pixel intensity and the respective computed score. B, The quantitative analysis results of scarring. The high positive and positive scores are calculated. Both scores are represented as mean ± standard deviation (SD). **P < 0.001, *P < 0.05, N = 5

Figure 6

The pathological mechanism simulation of SCI. A, An oval injury area was formed at the injury site in acute stage after SCI, axons were injured and fractured, ruptured blood vessels led to hematoma formation, and inflammatory cytokines were released and infiltrated at the site of injury. These in turn caused intracellular and extracellular homeostasis imbalance and edema, the pressure increased, and then the damaged axons were demyelinated and led to cell death. B, Molecular mechanism simulation of cellular metabolism after ischemia and edema in acute stage after contusion. C, Injury response affected normal spinal cord tissue anterograde and retrograde, resulting in degenerative responses in normal tissues. Over time, the edema, hematoma, and inflammatory cytokines were absorbed and discharged. A cystic cavity was gradually formed, and the reactive glial scar with covered edge was formed. Small amounts of axons and myelin sheaths were repaired, but most of the neural circuits could not be recovered. Based on the figures from Ahuja et al39 and Tyler et al40