Laboratory for Optical and Computational Instrumentation

Madison, WI, United States

Laboratory for Optical and Computational Instrumentation

Madison, WI, United States
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Hiner M.C.,Laboratory for Optical and Computational Instrumentation | Rueden C.T.,Laboratory for Optical and Computational Instrumentation | Eliceiri K.W.,Laboratory for Optical and Computational Instrumentation | Eliceiri K.W.,Morgridge Institute for Research
Bioinformatics | Year: 2017

ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks. © 2017 The Author.


Wegner K.A.,University of Wisconsin - Madison | Keikhosravi A.,Laboratory for Optical and Computational Instrumentation | Eliceiri K.W.,Laboratory for Optical and Computational Instrumentation | Eliceiri K.W.,Morgridge Institute for Research | And 2 more authors.
Journal of Histochemistry and Cytochemistry | Year: 2017

The low cost and simplicity of picrosirius red (PSR) staining have driven its popularity for collagen detection in tissue sections. We extended the versatility of this method by using fluorescent imaging to detect the PSR signal and applying automated quantification tools. We also developed the first PSR protocol that is fully compatible with multiplex immunostaining, making it possible to test whether collagen structure differs across immunohistochemically labeled regions of the tissue landscape. We compared our imaging method with two gold standards in collagen imaging, linear polarized light microscopy and second harmonic generation imaging, and found that it is at least as sensitive and robust to changes in sample orientation. As proof of principle, we used a genetic approach to overexpress beta catenin in a patchy subset of mouse prostate epithelial cells distinguished only by immunolabeling. We showed that collagen fiber length is significantly greater near beta catenin overexpressing cells than near control cells. Our fluorescent PSR imaging method is sensitive, reproducible, and offers a new way to guide region of interest selection for quantifying collagen in tissue sections. © 2017, © The Author(s) 2017.


Gehler S.,Augustana College at Rock Island | Ponik S.M.,University of Wisconsin - Madison | Ponik S.M.,Laboratory for Optical and Computational Instrumentation | Riching K.M.,Laboratory for Optical and Computational Instrumentation | And 3 more authors.
Critical Reviews in Eukaryotic Gene Expression | Year: 2013

Cell transformation and tumor progression involve a common set of acquired capabilities, including increased proliferation, failure of cell death, self-sufficiency in growth, angiogenesis, and tumor cell invasion and metastasis. The stromal environment consists of many cell types and various extracellular matrix (ECM) proteins that support normal tissue maintenance and which have been implicated in tumor progression. Both the chemical and mechanical properties of the ECM have been shown to influence normal and malignant cell behavior. For instance, mesenchymal stem cells differentiate into specific lineages that are dependent on matrix stiffness, while tumor cells undergo changes in cell behavior and gene expression in response to matrix stiffness. ECM remodeling is implicated in tumor progression and can result in increased deposition of stromal ECM, enhanced contraction of ECM fibrils, and altered collagen alignment and ECM stiffness. Tumor cells respond to changes in ECM remodeling through altered intracellular signaling and cell cycle control that lead to enhanced proliferation, loss of normal tissue architecture, and local tumor cell migration and invasion. This review focuses on the bi-directional interplay between the mechanical properties of the ECM and integrin-mediated signal transduction events in an effort to elucidate cell behaviors during tumor progression. © 2013 Begell House, Inc.


Li C.,University of Wisconsin - Madison | Hall G.,University of Wisconsin - Madison | Hall G.,Laboratory for Optical and Computational Instrumentation | Zeng X.,University of Wisconsin - Madison | And 5 more authors.
Applied Physics Letters | Year: 2011

We demonstrate three-dimensional (3D) surface profiling of the water-oil interface in a tunable liquid microlens using a Shack-Hartmann wave front sensor. The principles and the optical setup for achieving 3D surface measurements are presented and a hydrogel-actuated liquid lens was measured at different focal lengths. The 3D surface profiles are then used to study the optical properties of the liquid lens. Our method of 3D surface profiling could foster the improvement of liquid lens design and fabrication, including surface treatment and aberration reduction. © 2011 American Institute of Physics.


Ajeti V.,University of Wisconsin - Madison | Ajeti V.,Laboratory for Optical and Computational Instrumentation | Lien C.-H.,University of Wisconsin - Madison | Chen S.-J.,National Cheng Kung University | And 12 more authors.
Optics Express | Year: 2013

Multiphoton excited photochemistry is a powerful 3D fabrication tool that produces sub-micron feature sizes. Here we exploit the freeform nature of the process to create models of the extracellular matrix (ECM) of several tissues, where the design blueprint is derived directly from high resolution optical microscopy images (e.g. fluorescence and Second Harmonic Generation). To achieve this goal, we implemented a new form of instrument control, termed modulated raster scanning, where rapid laser shuttering (10 MHz) is used to directly map the greyscale image data to the resulting protein concentration in the fabricated scaffold. Fidelity in terms of area coverage and relative concentration relative to the image data is 95%. We compare the results to an STL approach, and find the new scheme provides significantly improved performance. We suggest the method will enable a variety of cell-matrix studies in cancer biology and also provide insight into generating scaffolds for tissue engineering. ©2013 Optical Society of America.


Ittmann M.,Baylor College of Medicine | Ittmann M.,Michael bakey Veterans Affairs Medical Center | Huang J.,University of California at Los Angeles | Radaelli E.,University of Milan | And 15 more authors.
Cancer Research | Year: 2013

Animal models, particularly mouse models, play a central role in the study of the etiology, prevention, and treatment of human prostate cancer. While tissue culture models are extremely useful in understanding the biology of prostate cancer, they cannot recapitulate the complex cellular interactions within the tumor microenvironment that play a key role in cancer initiation and progression. The National Cancer Institute (NCI) Mouse Models of Human Cancers Consortium convened a group of human and veterinary pathologists to review the current animal models of prostate cancer and make recommendations about the pathologic analysis of these models. More than 40 different models with 439 samples were reviewed, including genetically engineered mouse models, xenograft, rat, and canine models. Numerous relevant models have been developed over the past 15 years, and each approach has strengths and weaknesses. Analysis of multiple genetically engineered models has shown that reactive stroma formation is present in all the models developing invasive carcinomas. In addition, numerous models with multiple genetic alterations display aggressive phenotypes characterized by sarcomatoid carcinomas and metastases, which is presumably a histologic manifestation of epithelial-mesenchymal transition. The significant progress in development of improved models of prostate cancer has already accelerated our understanding of thecomplex biology of prostate cancer andpromises to enhance developmentof new approaches to prevention, detection, and treatment of this common malignancy. Cancer Res; 73(9); 2718-36. © 2013 AACR.


Freeman B.T.,University of Minnesota | Ogle B.M.,Laboratory for Optical and Computational Instrumentation | Ogle B.M.,University of Minnesota | Ogle B.M.,University of Wisconsin - Madison
Stem Cells Translational Medicine | Year: 2015

Evidence suggests that transplanted mesenchymal stem cells (MSCs) can aid recovery of damaged myocardium caused by myocardial infarction. One possible mechanism for MSC-mediated recovery is reprogramming after cell fusion between transplanted MSCs and recipient cardiac cells. We used a Cre/LoxP-based luciferase reporter system coupled to biophotonic imaging to detect fusion of transplanted human pluripotent stem cell-derived MSCs to cells of organs of living mice. Human MSCs, with transient expression of a viral fusogen, were delivered to the murine heart via a collagen patch. At 2 days and 1 week later, living mice were probed for bioluminescence indicative of cell fusion. Cell fusion was detected at the site of delivery (heart) and in distal tissues (i.e., stomach, small intestine, liver). Fusion was confirmed at the cellular scale via fluorescence in situ hybridization for human-specific and mouse-specific centromeres. Human cells in organs distal to the heart were typically located near the vasculature, suggesting MSCs and perhaps MSC fusion products have the ability to migrate via the circulatory system to distal organs and engraft with local cells. The present study reveals previously unknown migratory patterns of delivered human MSCs and associated fusion products in the healthy murine heart. The study also sets the stage for follow-on studies to determine the functional effects of cell fusion ina model of myocardial damage or disease. © AlphaMed Press 2015.


PubMed | Morgridge Institute for Research, University of Wisconsin - Madison and Laboratory for Optical and Computational Instrumentation
Type: Journal Article | Journal: Journal of pathology informatics | Year: 2014

Mortality in cancer patients is directly attributable to the ability of cancer cells to metastasize to distant sites from the primary tumor. This migration of tumor cells begins with a remodeling of the local tumor microenvironment, including changes to the extracellular matrix and the recruitment of stromal cells, both of which facilitate invasion of tumor cells into the bloodstream. In breast cancer, it has been proposed that the alignment of collagen fibers surrounding tumor epithelial cells can serve as a quantitative image-based biomarker for survival of invasive ductal carcinoma patients. Specific types of collagen alignment have been identified for their prognostic value and now these tumor associated collagen signatures (TACS) are central to several clinical specimen imaging trials. Here, we implement the semi-automated acquisition and analysis of this TACS candidate biomarker and demonstrate a protocol that will allow consistent scoring to be performed throughout large patient cohorts.Using large field of view high resolution microscopy techniques, image processing and supervised learning methods, we are able to quantify and score features of collagen fiber alignment with respect to adjacent tumor-stromal boundaries.Our semi-automated technique produced scores that have statistically significant correlation with scores generated by a panel of three human observers. In addition, our system generated classification scores that accurately predicted survival in a cohort of 196 breast cancer patients. Feature rank analysis reveals that TACS positive fibers are more well-aligned with each other, are of generally lower density, and terminate within or near groups of epithelial cells at larger angles of interaction.These results demonstrate the utility of a supervised learning protocol for streamlining the analysis of collagen alignment with respect to tumor stromal boundaries.


PubMed | Laboratory for Optical and Computational Instrumentation
Type: | Journal: Bioinformatics (Oxford, England) | Year: 2016

ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks.Freely available extension to ImageJ2 (http://imagej.net/Downloads). Installation and use instructions available at http://imagej.net/MATLAB_Scripting. Tested with ImageJ 2.0.0-rc-54, Java 1.8.0_66 and MATLAB R2015b.eliceiri@wisc.eduSupplementary information: Supplementary data are available at Bioinformatics online.


News Article | October 25, 2016
Site: www.medicalnewstoday.com

A study in the current journal Oncotarget provides the first evidence linking a disturbance of the most common protein in the body with a poor outcome in pancreatic cancer. The study reinforces growing evidence that collagen, which forms fibrous networks in skin, tendons and muscles, is intimately involved in several cancers, says the paper's corresponding author, Kevin Eliceiri, director of the Laboratory for Optical and Computational Instrumentation (LOCI) at the University of Wisconsin-Madison. For the study, the Wisconsin researchers examined surgical tissues from 114 pancreatic cancer patients and identified a particular rearrangement of collagen fibers surrounding the tumor as a "biomarker" of early death. A similar rearrangement of collagen has also been found in breast cancer, head, neck, esophageal and colorectal cancers. "Collagen is the most abundant protein in the body," says Eliceiri. "It's a beautiful molecule - wavy, with a fibrous nature. Without it we would be a sack of nothing. With this little molecule, the specific fiber organization really matters to metastasis." The images were created using an automated laser scanning microscope developed at LOCI that shines a laser at tumor specimens mounted on microscope slides. The laser's bright, rapid pulses interact with the collagen fibers, which glow and reveal exquisite details of their structure and relationship to nearby fibers. The new study tested how collagen formation might affect metastasis, Eliceiri says. "We did not know anything about survival when we measured the alignment of the collagen in tumors from 114 pancreatic cancer patients. When we looked at the clinical records, we found that the tumors with highly aligned collagen fibers had the worst survival. To our knowledge, this is the first time this technique was used for prognostic purposes in pancreatic cancer." First author Cole Drifka, a biomedical engineering postdoctoral researcher, conceived and performed the study under the supervision of Eliceiri and W. John Kao, a professor of pharmacy. "The powerful tissue resource used in this study was made possible by generous financial donations from Teresa's Foundation for Pancreatic Cancer and the Tim and Mary Ann McKenzie Chair of Surgical Oncology Professorship," says Drifka. "Above all, it was made possible by the selfless tissue donations by UW Health patients. The new tissue collection represents a blossoming institutional focus on pancreatic cancer and is now available to all campus researchers seeking to comprehend this challenging disease." Finding and fighting metastases is a focus in cancer treatment, Eliceiri explains. "The original tumor seldom kills; poor prognosis is usually due to metastases as they spread to new tissues and organs." The LOCI lab specializes in developing new imaging techniques for living things, with a special interest in studying cells in their microenvironment rather than in isolation. In the case of several major tumor types, the collagen matrix plays a critical role, Eliceiri says. For reasons yet to be determined, he adds, "cancer progression seems to be associated with the reorientation of the direction of the collagen. The tumor starts with collagen wrapped around it, but when it's time to metastasize, the collagen fiber changes it alignment." If alignment matters to metastasis, "We want to know what causes the alignment shift, because then maybe we could block that change," Eliceiri says. For example, if a signaling molecule initiates the realignment, it could be a target for drugs. Collagen, a structural protein often involved in scarring and wound healing, is emerging as an important factor in a number of other diseases, Eliceiri says. "Collagen may be harmful or protective, but in every disease where collagen is present, it's part of the disease process." More than a dozen labs at UW-Madison are working on various aspects of collagen. For example, Patricia Keely, professor and chair of cell and regenerative biology who studies the matrix surrounding cells, is exploring its link to breast cancer. Paul Campagnola, a professor of biomedical engineering, is exploring its link in ovarian and lung cancer. Sharon Weber, a co-author on the Oncotarget paper and a professor of surgery, concentrates on pancreatic cancer. Understanding collagen's role in cancer could have several uses, Weber says. "Prognosis, which is our focus in this paper, is one. Can we identify some signature in the pattern of collagen that will help us understand which patients are going to do well and which are not? Might collagen patterns also help us sort out which patients should undergo surgery? The patterns of collagen in cancer might also be used to ascertain the effectiveness of chemotherapy or radiation so that we can utilize those toxic treatments in those patients who will benefit most." In cancer, Weber says, knowledge is power. "It would be amazing if we could use these differences in collagen patterns to help discover new therapeutic targets for this devastating disease." Article: Highly aligned stromal collagen is a negative prognostic factor following pancreatic ductal adenocarcinoma resection, Cole R. Drifka, Agnes G. Loeffler, Kara Mathewson, Adib Keikhosravi, Jens C. Eickhoff, Yuming Liu, Sharon M. Weber, W. John Kao, Kevin W. Eliceiri, Oncotarget, doi: 10.18632/oncotarget.12772, published 20 October 2016.

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