Quantifying myelin content in brain tissue using color Spatial Light Interference Microscopy (cSLIM)

Abstract

Deficient myelination of the brain is associated with neurodevelopmental delays, particularly in high-risk infants, such as those born small in relation to their gestational age (SGA). New methods are needed to further study this condition. Here, we employ Color Spatial Light Interference Microscopy (cSLIM), which uses a brightfield objective and RGB camera to generate pathlength-maps with nanoscale sensitivity in conjunction with a regular brightfield image. Using tissue sections stained with Luxol Fast Blue, the myelin structures were segmented from a brightfield image. Using a binary mask, those portions were quantitatively analyzed in the corresponding phase maps. We first used the CLARITY method to remove tissue lipids and validate the sensitivity of cSLIM to lipid content. We then applied cSLIM to brain histology slices. These specimens are from a previous MRI study, which demonstrated that appropriate for gestational age (AGA) piglets have increased internal capsule myelination (ICM) compared to small for gestational age (SGA) piglets and that a hydrolyzed fat diet improved ICM in both. The identity of samples was blinded until after statistical analyses.

Fig 1. Schematic setup for cSLIM.

(A) The cSLIM module is attached to a phase contrast microscope and uses a brightfield objective with an RGB camera. (B) The four phase-shifted color interferograms, with the initial unshifted frame corresponding to a brightfield image. (C) Computed SLIM image.

Fig 2. High and low myelin.

(A) Picture of a slide of a piglet brain tissue with the internal capsule delineated in red. (B) A stitch of brightfield cSLIM images with selected single frames of high and low myelin regions (scale bars: 35 μm). (C) Histograms of the dry mass density values per quarter frame in one AGA tissue sample. (D) Histogram of the dry mass density values per quarter frame in one SGA tissue sample. Gaussian fitting is used to separate the high and low myelin regions.

Fig 3. Color SLM calibrations.

(A) Original SLIM image. (B) SLIM image obtained from different red, green, and blue SLM calibrations. (C) histograms of (A) and (B). (D) ‘RGB SLIM’ images composed of red, green, and blue SLIM images respectively.

Fig 4

Myelin segmentation process. (A) A brightfield image is first used to create a (B) binary mask specific to myelin, which is then multiplied by the (C) corresponding SLIM image. (D)The result is a phase map uniquely describing the myelin content of the image, with former cellular areas (encircled in red) deleted. (E) Plot of the cross section in (A). (F) Plot of the cross section in (C) and (G) its Fourier transform, which has a mean frequency of 0.36 μm^-1, corresponding to an average axonal width of 2.7 μm.

Fig 5. CLARITY results.

53 x 93 frame stitches of a mouse brain tissue (A) before and (B) after the clearing procedure. Dry mass density histograms of (C) the anterior commissure portions and (D) the corpus callosum structure. (* p<0.05).

Fig 6. Comparison of brightfield frames.

Single brightfield frames of high and low myelin areas in both appropriate for gestational age (AGA) and small for gestational age (SGA) samples. Scale bar: 35μm.

Fig 7. Dry mass comparisons.

(A) Difference in dry mass density per quarter frame of total AGA tissue with high myelin, (B) SGA with high myelin, (C) AGA with low myelin, (D) and SGA with low myelin. (* p<0.05, ** p<0.01).

Fig 8. Relationship between dry mass, area and intensity.

(A) Dry mass of myelin from 100 frames of 10 slides plotted against the area of the binary masks, (B) 3D plot of dry mass, area of the mask, and color intensity of the fibers, (C) difference between control and experimental slides in mask area, (D) and difference between control and experimental slides in color intensity (** p<0.01).