Automated image analysis of a glomerular injury marker desmin in spontaneously diabetic Torii rats treated with losartan

Diabetic nephropathy is a major complication in diabetes and a leading cause of end-stage renal failure. Glomerular podocytes are functionally and structurally injured early in diabetic nephropathy. A non-obese type 2 diabetes model, the spontaneously diabetic Torii (SDT) rat, is of increasing preclinical interest because of its pathophysiological similarities to human type 2 diabetic complications including diabetic nephropathy. However, podocyte injury in SDT rat glomeruli and the effect of angiotensin II receptor blocker treatment in the early stage have not been reported in detail. Therefore, we have evaluated early stages of glomerular podocyte damage and the beneficial effect of early treatment with losartan in SDT rats using desmin as a sensitive podocyte injury marker. Moreover, we have developed an automated, computational glomerulus recognition method and illustrated its specific application for quantitatively studying glomerular desmin immunoreactivity. This state-of-the-art method enabled automatic recognition and quantification of glomerular desmin-positive areas, eliminating the need to laboriously trace glomerulus borders by hand. The image analysis method not only enabled assessment of a large number of glomeruli, but also clearly demonstrated that glomerular injury was more severe in the juxtamedullary region than in the superficial cortex region. This applied not only in SDT rat diabetic nephropathy but also in puromycin aminonucleoside-induced nephropathy, which was also studied. The proposed glomerulus image analysis method combined with desmin immunohistochemistry should facilitate evaluations in preclinical drug efficacy studies as well as elucidation of the pathophysiology of diabetic nephropathy.

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Automated image analysis method for oil-release test of lipid-based materials

MethodsX ◽

10.1016/j.mex.2021.101447 ◽

2021 ◽

pp. 101447

Author(s):

Fabio Valoppi ◽

Petri Lassila ◽

Ari Salmi ◽

Edward Haeggström

Keyword(s):

Image Analysis ◽

Automated Image Analysis ◽

Analysis Method ◽

Image Analysis Method ◽

Release Test

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Proof of Concept for an Automated Image Analysis Method to Quantify Rat Bone Marrow Hematopoietic Lineages on H&E Sections

Toxicologic Pathology ◽

10.1177/0192623318766458 ◽

2018 ◽

Vol 46 (3) ◽

pp. 336-347 ◽

Cited By ~ 2

Author(s):

Cleopatra Kozlowski ◽

Aaron Fullerton ◽

Gary Cain ◽

Paula Katavolos ◽

Joseph Bravo ◽

...

Keyword(s):

Bone Marrow ◽

Image Analysis ◽

Cell Density ◽

Bone Marrow Cell ◽

Marrow Cell ◽

Automated Image Analysis ◽

Computer Algorithm ◽

Analysis Method ◽

Image Analysis Method ◽

Rat Bone

The bone marrow is an important site for assessment of the hematopoietic toxicity of new drug candidates. Here, we extended our previous work, where we developed a computer algorithm to automatically quantitate overall bone marrow cell density by analyzing digitized images of standard hematoxylin and eosin (H&E) slides of rat bone marrow and further evaluated the capability to quantify myeloid: erythroid + lymphoid (M:EL) ratio and megakaryocyte cell density. We tested the algorithm in a toxicity study, where rats were dosed with two molecules known to affect bone marrow composition, monomethyl auristatin E, and a Bcl-xL inhibitor. The image analysis method detected significant changes in M:EL and megakaryocyte number that were either not found or semiquantitatively described by manual microscopic observation of the same slides. The image analysis results were consistent with other more established but time-consuming methods that measure changes in bone marrow cell composition: smear cytology, flow cytometry, and microscopic assessment. Our work demonstrates the feasibility of a rapid and more quantitative assessment of changes in bone marrow cell lineage composition using a computer algorithm compared to microscopic examination of H&E-stained bone marrow sections.

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Toluidine blue staining of murine mast cells and quantitation by a novel, automated image analysis method using whole slide skin images

Journal of Histotechnology ◽

10.1080/01478885.2021.1915934 ◽

2021 ◽

pp. 1-6

Author(s):

Nivethitha Raja ◽

Sangmesh Naikodi ◽

Arunprasath Govindarajan ◽

Kamalavenkatesh Palanisamy

Keyword(s):

Image Analysis ◽

Mast Cells ◽

Toluidine Blue ◽

Automated Image Analysis ◽

Blue Staining ◽

Analysis Method ◽

Image Analysis Method ◽

Toluidine Blue Staining

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Erratum

Toxicologic Pathology ◽

10.1177/0192623318794946 ◽

2018 ◽

Vol 46 (6) ◽

pp. 722-722

Keyword(s):

Bone Marrow ◽

Image Analysis ◽

Automated Image Analysis ◽

Proof Of Concept ◽

Analysis Method ◽

Image Analysis Method ◽

Bone Marrow Cellularity ◽

Marrow Cellularity ◽

Rat Bone

Kozlowski, C., Brumm, J., and Cain, G. (2018). An Automated Image Analysis Method to Quantify Veterinary Bone Marrow Cellularity on H&E Sections. Tox Path46, 324–335. (Original DOI: 10.1177/0192623318766457). Kozlowski, C., Fullerton, A., Cain, G., Katavolos, P., Bravo, J., and Tarrant, J. M. (2018). Proof of Concept for an Automated Image Analysis Method to Quantify Rat Bone Marrow Hematopoietic Lineages on H&E Sections. Tox Path46, 336–347. (Oringinal DOI: 10.1177/0192623318766458). In the print issue and initial version of the online issue, the figures for Kozlowski, Brumm, and Cain were mistakenly placed into Kozlowski, Fullerton, et al., and vice versa. The online versions of both articles have been updated to display the appropriate figures.

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