The Lantern Vol. 52, No. 2, Spring 1986

• The Cartoonist • Balance • Haiku • Moment of Truth • There Was a Man • Mad Song / Cassandra\u27s Song • Part I - The Descent • Political Thought • Beast • Questions Yet Unanswered • Aphrodite: A Lover\u27s Lament • The Most Limber Boy • Style And • Thoughts From My Confusion • Andy • Momma Wake Up • In The Suburbs • Tommy • When the Phone Rings • There\u27s Something Soothing • Starting Over • A Day in the Life of a Flower • Pretension • It Seems Like So Long Ago • I Walk Along • Insignificant Man • Variations on a Latin Theme • The Riddle • Roll the Dice - Its Your Turn • This Is Your Day • One Night Stand • Make My Day • You Really Can\u27t Expect • Medusa • Don\u27t Think • Broken Chain • Life...A Hammock? • To My Friend • Ode On a Grecian Keghttps://digitalcommons.ursinus.edu/lantern/1128/thumbnail.jp

Automated quantification reveals hyperglycemia inhibits endothelial angiogenic function.

Diabetes Mellitus (DM) has reached epidemic levels globally. A contributing factor to the development of DM is high blood glucose (hyperglycemia). One complication associated with DM is a decreased angiogenesis. The Matrigel tube formation assay (TFA) is the most widely utilized in vitro assay designed to assess angiogenic factors and conditions. In spite of the widespread use of Matrigel TFAs, quantification is labor-intensive and subjective, often limiting experiential design and interpretation of results. This study describes the development and validation of an open source software tool for high throughput, morphometric analysis of TFA images and the validation of an in vitro hyperglycemic model of DM.Endothelial cells mimic angiogenesis when placed onto a Matrigel coated surface by forming tube-like structures. The goal of this study was to develop an open-source software algorithm requiring minimal user input (Pipeline v1.3) to automatically quantify tubular metrics from TFA images. Using Pipeline, the ability of endothelial cells to form tubes was assessed after culture in normal or high glucose for 1 or 2 weeks. A significant decrease in the total tube length and number of branch points was found when comparing groups treated with high glucose for 2 weeks versus normal glucose or 1 week of high glucose.Using Pipeline, it was determined that hyperglycemia inhibits formation of endothelial tubes in vitro. Analysis using Pipeline was more accurate and significantly faster than manual analysis. The Pipeline algorithm was shown to have additional applications, such as detection of retinal vasculature

Pipeline analysis was demonstrated through evaluating the effects of simulated-hyperglycemia on RMVEC tube formation <i>in vitro</i>.

<p>RMVECs were cultured in normal glucose (5.6 mM) or high glucose (25 mM) for 1–2 weeks. Cells were then isolated and 20,000 RMVECs were incubated at 37°C for 24 and 48 hours on Matrigel in a four-well chamber. Two week exposure to high glucose significantly decreased both (A) total tube length and (B) the number of nodal branch points detected and (C) total tube area (p<0.05). (D) Representative input/output images from each condition.</p

Comparison of Operator Required to Complete Total Length Analysis.

<p>Time required to complete the analysis by manually tracing or by Pipeline (all times in minutes). In the present study (data displayed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094599#pone-0094599-g007" target="_blank"><b>Figure 7</b></a>) it took each operator approximately 240 minutes to complete the analysis by manually tracing tube-like structures. Completing the same analysis in Pipeline took approximately 7 minutes to set up the analysis and 10 minutes to examine the output images to verify an accurate result. When re-analyzing the data from Chu et al, it took only 1 minute to set up the analysis in Pipeline and 5 minutes to verify an accurate result as opposed to 180 minutes to complete the analysis through manual tracing.</p

Comparison of Manual Quantification in Liu et

<p>Liu analyzed the number of branchpoints and relative tube length by manually tracing structures in ImageJ. After analyzing the same raw data in Pipeline, the same trends were observed when analyzing (A) branchpoints and (B) tube length. In both panels, statistical significance was maintained. When comparing manual tracing to Pipeline quantification, both metrics were found to be highly correlated. (C) Branchpoint analysis correlation: R² = 0.902 and (D) length analysis correlation: R² = 0.961.</p

Pipeline graphical user interface components are as follows: (A) Opening Panel, allows user to select imaging processing mode.

<p>(B) Single Processing mode, allows user to manipulate and optimize (7) analysis parameters for a single image. Analysis parameters can then be used in Batch Analysis mode to process an entire group of images. (C) Batch Analysis processing mode, allows a user to select multiple images for analysis with a set of parameters optimized within the single processing mode. In Batch Analysis mode, the 6 images generated in the single processing mode can be exported as TIFFs to separate folders.</p

The overall analysis algorithm flowchart for Pipeline is displayed above.

<p>TIFF files are imported, converted to a grayscale image, edges are detected using the “Canny” method, and a binary mask called ‘tube edges’ is created. The mask is then skeletonized forming an additional binary mask called the ‘skeleton image’. The total tubular area, length, thickness, and number of branchpoints is then calculated from these two images.</p