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Application of Sholl Analysis to Quantify Changes in Growth and Development in Rat Mammary Gland Whole Mounts

Stanko JP, Easterling MR, Fenton SE
Reprod Toxicol (2015), DOI: https://doi.org/10.1016/j.reprotox.2014.11.004 PMID: 25463529


Publication


Abstract

Studies that utilize the rodent mammary gland (MG) as an endpoint for assessing the developmental toxicity of chemical exposures typically employ either basic dimensional measurements or developmental scoring of morphological characteristics as a means to quantify MG development. There are numerous means by which to report these developmental changes, leading to inconsistent translation across laboratories. The Sholl analysis is a method historically used for quantifying neuronal dendritic patterns. The present study describes the use of the Sholl analysis to quantify MG branching characteristics. Using this method, we were able to detect significant differences in branching density in MG of peripubertal female Sprague Dawley rats that had been exposed to vehicle or a potent estrogen. These data suggest the Sholl analysis can be an effective tool for quantitatively measuring an important characteristic of MG development and for examining associations between MG growth and density and adverse effects in the breast.

Figures


Figure 1. Mammary scoring criteria

Examples of criteria considered when evaluating mammary gland ductal outgrowth. Image shown is a mammary gland whole mount from a PND25 Charles River Sprague Dawley rat. LN = lymph node, MEA = mammary epithelial area, MG4 = 4th inguinal mammary gland, MG5 = 5th inguinal mammary gland, TEB = terminal end bud.

Figure 2. Physical similarities

Physical similarities between a neuron and rodent mammary gland. A) Pyramidal cortical neuron of adult male rat. Scale bar is 50 µm. B) A mammary gland from a female PND25 CRSD rat. C) A mammary gland from a female PND21 CD-1 mouse. Although branching is more complex in the mammary gland, particularly in the rat, the basic tree-like structure is maintained. Scale bars in B and C are 1 mm.

Figure 3. Image processing

Stepwise ImageJ processing of mammary gland whole mount image. A) Original whole mount image. B) Binary thresholded image. C) Skeletonized image. D) Overlay of skeletonized image onto original whole mount image demonstrating accuracy of ImageJ processing. E) Analyzed image painted as a heat map according to the Sholl profile. An enlargement of Figure 3D is provided in Figure 4 to show detail.

Figure 4. Overlay

Enlargement of Figure 3D showing the detail of a skeletonized image overlayed onto the original whole mount image.

Figure 5. Mammary glands

Mammary glands from PND 21 NCTRSD rats. A) MG4 from vehicle rat, B) MG4 from rat treated with 5 µg EE/kg BW. Images are representative of group means for mammary gland physical parameters and Sholl analysis. Scale bars are 1 mm.

Figure 6. Sholl profiles

Sholl profiles for NCTRSD rats. Profiles were derived from images in Figure 5 and are representative of group means. A) Linear plot of N vs. distance and B) semi-log plot of log(N/mm2) vs. distance for vehicle-treated NCTRSD rat. C) Linear plot of N vs. distance and D) semi-log plot of log(N/mm2) vs. distance for EE-treated NCTRSD rat. Parameters indicated are data for the individual animal.

Tables


Table 1. Mammary epithelial parameters

Values are means ± SEM; Long. Growth: longitudinal growth determined as the distance from base of attachment of the epithelial tree to most distal edge of the epithelium; MEA: mammary epithelial area determined as the area enclosed by a line traced around the perimeter of the glandular epithelium; CV: coefficient of variation.
****p < 0.0001 by t-test.

Table 2. Sholl analysis parameters

Values are means ± SEM; Sum N: total intersections in MEA; N/mm2: intersections/MEA less the area occupied by the lymph node; k: Sholl regression coefficient; CV: coefficient of variation.
*p < 0.05.
**p < 0.01.
***p < 0.001 by t-test.

Supplemental Materials


Supplemental Figure 3

Supplemental Table 2

Supplemental Application 3

Open Source Software


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