RetFM-J, an ImageJ-based module for automated counting and quantifying features of nuclei in retinal whole-mounts

Hedberg-Buenz, Adam; Christopher, Mark; Lewis, Carly; Meyer, Kacie J.; Rudd, Danielle S.; Dutca, Laura M.; Wang, Kai; Garvin, Mona K.; Scheetz, Todd E.; Abràmoff, Michael D.; Harper, Matthew M.; Anderson, Michael G.

doi:10.1016/j.exer.2015.07.020

Cited by 25 publications

(31 citation statements)

References 14 publications

(14 reference statements)

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“…Likewise, microgliosis could cause increases specific to disease stage in some categories (Bosco, Steele et al 2011, Liu, Li et al 2012). Third, although performance of RetFM-J is robust with regard to retinas stained in different batches (Hedberg-Buenz, Christopher et al 2015), the same has not yet been stringently tested for RetFM-Class. In an attempt to minimize this potential confounder, the current training set for RetFM-Class purposefully included samples from multiple histologic batches.…”

Section: Discussionmentioning

confidence: 99%

“…Retinas were collected for whole-mount preparations as previously described (Hedberg-Buenz, Christopher et al 2015), with attention to keeping times for staining, mounting, and documentation as uniform as possible, and keeping experimental and control samples evenly dispersed between histologic batches. Whole-mounted retinas stained with H&E were scanned at 40x magnification with a digital whole-slide scanner (ScanScope CS, Aperio, Vista, CA).…”

Section: Methodsmentioning

confidence: 99%

“…Stained whole-mount retinal preparations were imaged by light microscopy and images were subjected to analysis using RetFM-J as previously described (Hedberg-Buenz, Christopher et al 2015). Quantitative measurements of 41 features relating to morphology and stain appearance (Supplemental Table 1) were computed for each extracted nucleus, so that further processing and classification could be performed.…”

Section: Methodsmentioning

confidence: 99%

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Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Hedberg-Buenz

Christopher

Lewis

et al. 2016

Experimental Eye Research

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The inner surface of the retina contains a complex mixture of neurons, glia, and vasculature, including retinal ganglion cells (RGCs), the final output neurons of the retina and primary neurons that are damaged in several blinding diseases. The goal of the current work was two-fold: to assess the feasibility of using computer-assisted detection of nuclei and random forest classification to automate the quantification of RGCs in hematoxylin/eosin (H&E)-stained retinal whole-mounts; and if possible, to use the approach to examine how nuclear size influences disease susceptibility among RGC populations. To achieve this, data from RetFM-J, a semi-automated ImageJ-based module that detects, counts, and collects quantitative data on nuclei of H&E-stained whole-mounted retinas, were used in conjunction with a manually curated set of images to train a random forest classifier. To test performance, computer-derived outputs were compared to previously published features of several well-characterized mouse models of ophthalmic disease and their controls: normal C57BL/6J mice; Jun-sufficient and Jun-deficient mice subjected to controlled optic nerve crush (CONC); and DBA/2J mice with naturally occurring glaucoma. The result of these efforts was development of RetFM-Class, a command-line-based tool that uses data output from RetFM-J to perform random forest classification of cell type. Comparative testing revealed that manual and automated classifications by RetFM-Class correlated well, with 83.2% classification accuracy for RGCs. Automated characterization of C57BL/6J retinas predicted 54,642 RGCs per normal retina, and identified a 48.3% Jun-dependent loss of cells at 35 days post CONC and a 71.2% loss of RGCs among 16-month-old DBA/2J mice with glaucoma. Output from automated analyses was used to compare nuclear area among large numbers of RGCs from DBA/2J mice (n=127,361). In aged DBA/2J mice with glaucoma, RetFM-Class detected a decrease in median and mean nucleus size of cells classified into the RGC category, as did an independent confirmation study using manual measurements of nuclear area demarcated by BRN3A-immunoreactivity. In conclusion, we have demonstrated that histology-based random forest classification is feasible and can be utilized to study RGCs in a high-throughput fashion. Despite having some limitations, this approach demonstrated a significant association between the size of the RGC nucleus and the DBA/2J form of glaucoma.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Hedberg-Buenz

Christopher

Lewis

et al. 2016

Experimental Eye Research

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“…To quantitate cell numbers, images were analyzed by threshold-based automatic particle counting. 28 To calculate the percentile of nerve coverage in each cornea, images were adjusted with a threshold, analyzed as particle (show mask), then analyzed by percentage area.…”

Section: Whole Mount Confocal Microscopymentioning

confidence: 99%

Targeting Imbalance between IL-1β and IL-1 Receptor Antagonist Ameliorates Delayed Epithelium Wound Healing in Diabetic Mouse Corneas

Yan

Gao

Sun

et al. 2016

The American Journal of Pathology

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fanxq@sh163. net.Patients with diabetes mellitus often develop corneal complications and delayed wound healing. How diabetes might alter acute inflammatory responses to tissue injury, leading to delayed wound healing, remains mostly elusive. Using a streptozotocin-induced type I diabetes mellitus mice and corneal epithelium-debridement wound model, we discovered that although wounding induced marked expression of IL-1b and the secreted form of IL-1 receptor antagonist (sIL-1Ra), diabetes suppressed the expressions of sIL-1Ra but not IL-1b in healing epithelia and both in whole cornea. In normoglycemic mice, IL-1b or sIL-1Ra blockade delayed wound healing and influenced each other's expression. In diabetic mice, in addition to delayed reepithelization, diabetes weakened phosphatidylinositol 3-kinaseeAkt signaling, caused cell apoptosis, diminished cell proliferation, suppressed neutrophil and natural killer cell infiltrations, and impaired sensory nerve reinnervation in healing mouse corneas. Local administration of recombinant IL-1Ra partially, but significantly, reversed these pathological changes in the diabetic corneas. CXCL10 was a downstream chemokine of IL-1beIL-1Ra, and exogenous CXCL10 alleviated delayed wound healing in the diabetic, but attenuated it in the normal corneas. In conclusion, the suppressed early innate/inflammatory responses instigated by the imbalance between IL-1b and IL-1Ra is an underlying cause for delayed wound healing in the diabetic corneas. Local application of IL-1Ra accelerates reepithelialization and may be used to treat chronic corneal and potential skin wounds of diabetic patients. (Am J Pathol 2016 http://dx

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“…Para evaluar el grado de activación glial se ha empleado un sistema de gradación basado en la extensión de la inmunoexpresión de la GFAP a lo largo del citoplasma y prolongaciones de las células de Müller 91 en concreto: Grado 1: inmunoexpresión en los pies de las células de Müller a nivel de la GCL.Grado 2: inmunoexpresión en los pies de las células de Müller a nivel de la GCL y algunas prolongaciones que alcanzan la IPL.Grado 3: inmunoexpresión en los pies de las células de Müller a nivel de la GCL y prolongaciones hasta la INL.Grado 4: inmunoexpresión en los pies de las células de Müller a nivel de la GCL y prolongaciones hasta la ONL.Se realizó una descripción de la inmunoexpresión de la Tubulina beta III en las muestras de NR frescas, en los controles de 3 días y en las NR cocultivadas con MSV y se cuantificó la proporción de la intensidad de la Tubulina beta III dividida entre la intensidad del DAPI con el programa ImageJ a partir de 5 imágenes por muestra obtenidas con una magnificación de 20x y fue expresada en unidades arbitrarias (A.U). Además, se cuantificó el número de núcleos teñidos con DAPI en cada una de las capas retinianas y el número de núcleos NeuN positivos correspondientes a las células ganglionares de la retina con el programa ImageJ y el plugin RetFM-J (ImageJ-based module for automated counting and quantifying features of nuclei in retinal whole-mounts)92 a partir de 12 imágenes por muestra obtenidas con una magnificación de 20x. Al mismo tiempo, se cuantificaron de forma manual los núcleos TUNEL positivos en cada una de las capas retinianas.…”

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Evaluación preclínica de la seguridad y la eficacia de la terapia con células madre mesenquimales para su utilización en un ensayo clínico en pacientes con neuropatía óptica isquémica anterior no arterítica

Velandia¹,

Cecilia²

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RetFM-J, an ImageJ-based module for automated counting and quantifying features of nuclei in retinal whole-mounts

Cited by 25 publications

References 14 publications

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Targeting Imbalance between IL-1β and IL-1 Receptor Antagonist Ameliorates Delayed Epithelium Wound Healing in Diabetic Mouse Corneas

Evaluación preclínica de la seguridad y la eficacia de la terapia con células madre mesenquimales para su utilización en un ensayo clínico en pacientes con neuropatía óptica isquémica anterior no arterítica

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