A Non-Invasive Method for

Measuring Contractility

in Cardiocytes

David Torres and Paul Paolini

AP0911

09

A Non-Invasive Method for Measuring Contractilityin Cardiocytes

Torres Barba, David 1,2

1San Diego State University2Computational Science Research Center∗Corresponding author: 5500 Campanile Drive, San Diego, CA 92182

Abstract: We are developing a non-invasive procedure for measuring contractileresponses of both adult and neonatal mam-malian cardiocytes. This method can be em-ployed to quantify pharmacological effects ofdrugs on myocytes. Methods for quantifyingneonatal cell contraction reported in the lit-erature have required the use of elaborateequipment such as a proximity detector oran atomic force microscope (to measure theincrease in cell elevation as a cardiocyte con-tracts), and typically interfere with simulta-neous optical recording of cell signals. Suchcontraction quantification methods are ex-pensive due to the equipment needed. Ourapproach to contractile measurement is be-ing developed with the goal to be a practicaland relatively inexpensive method.

Our approach uses two different imageprocessing procedures that allow us to pro-duce contractility records of both adult andneonatal cardiocytes. In our first procedurewe analyze neonatal myocytes. Contractioncurves generated from neonatal cells withour new method exhibit a very similar pro-file and time course to those produced bymore sophisticated and expensive methods[11, 15].

Our second image processing procedureis an application that allows measurementof the adult cardiocytes area in each frame.Application of our two dimensional quan-tification technique to the study of adultcardiocytes produces contraction vs. timerecords virtually identical in time course andshape to records obtained from traditionalone dimensional, cell boundary tracking pro-cedures [12].

The contractility graphs created by thetwo image processing procedures are consis-tent with the expected results and graphs re-sulting from past studies performed on my-ocytes [10]. This new non-invasive approachto contractile quantification will be useful in

the analysis of the myocyte contractile dy-namics in the presence of drugs.

Keywords: Contractility, Myocyte, ImageAnalysis

1 Introduction

Isolated adult and neonatal cardiocytes frommammalian heart are widely used in cardio-vascular cell biology research. The study ofcardiocyte contractility can help unveil fun-damental processes underlying heart func-tion in health and disease. Many positiveand negative inotropic factors modulate thecontractile behavior of cardiocytes. Due tothe high number of studies and the unlim-ited research possibilities with cardiocytes,we decided it would be useful to develop anon-invasive working protocol that could al-low for the quantification of the contractilityexhibited by both neonatal and adult car-diocytes. The image processing method forneonatal myocytes could be applied to thestudy of the effects of the extracellular ma-trix (ECM) on developing myocytes. TheECM has been shown to play a crucial role inthe sarcomere development in neonatal my-ocytes [1, 7]. Currently our laboratory hasone protocol for measuring adult cell con-tractility a one dimensional cell boundaryvideo tracking method but no equivalentmethod for quantifying neonatal cell con-tractility [12].

We were previously able to use only theintracellular calcium transient signal ampli-tude or integral to measure neonatal cell con-tractile potential. The application of the cellboundary video tracking method and the useof cellular force measurements using single-spaced polymeric microstructures to detectamplitude of contraction and beating ratein neonatal cardiocytes have been reportedin the literature [2, 9, 14, 17], but have been

found to be erratic and unreliable in our lab-oratory studies. The availability of a proto-col for measuring both neonatal and adultcardiocyte contractions would allow a con-sistent method to characterize inotropic ef-fects of drugs on both cell types, and couldopen the door to a new line of research inthe world of cardiovascular biology.

2 Contractility and MyocyteMechanics

Contractility is the intrinsic ability of heartmuscle to generate force and to shorten. At

the molecular level the contractile processoriginates from the changing concentrationsof Ca2+ ions in the myocardial cytosol. Cal-cium ions enter through the calcium chan-nel that opens in response to the wave ofdepolarization that travels along the sar-colemma. These Ca2+ ions trigger the re-lease of more calcium from the sarcoplas-mic reticulum (SR) and thereby initiate acontraction-relaxation cycle [6, 5, 3]. Figure1 shows a schematic of the cytosol and ex-tracellular space, depicting the exchange ofCa2+, Na+, K+, and Cl− ions that leads tothe contraction of the myocyte.

Fig. 1: Parts of the ultra-structure of a myocyte: The A-band, the I-band, theZ-lines, the sarcoplasmic reticulum, the transevers tubular system (T-tubule), and the mitochondria. (Original image from [4].)

3 Previous Work

Given the need that exists in cardiovascularresearch to analyze the aspect of contractil-ity and force development in myocytes, sev-eral methods have been developed. All thesemethods require the use of expensive equip-ment and sophisticated techniques to per-form the desired analysis.

One of the first efforts to measure con-traction or shortening was performed withthe assistance of a video based device thewas able to capture the extent and rate oflength shortening of isolated cardiac my-ocytes [16]. Even though several methodswere published prior to this method, this wasthe first technique to specialize on contract-ing cardiac cells. The video based method

uses two tracking points at each end of themyocyte to track edge displacement as themyocyte contracts. The distance betweenthe two edges is measured using edge detec-tion while a record of the data is stored ina file. The method produces satisfactory re-sults and has been an approved and widelyused method for measuring contractile re-sponses of adult myocytes for almost twentyyears.

The need for measuring different aspectsof a myocyte has led some researchers to ex-plore techniques such as scanning ion con-ductance microscopy [15]. This techniqueuses a distance modulated protocol for scan-ning ion conductance microscopy to providea distance control mechanisms to image con-tracting myocytes. This technique combined

with laser confocal microscopy measures my-ocyte height and local calcium concentrationduring contractility.

In the last two decades soft materialshave been explored by researchers in cell bi-ology as a means to measure force develop-ment and tracking movement of cells. My-ocytes have not been an exception in the ap-plication of this emerging science. Materialssuch as polydimethylsiloxane (PDMS) andpolyacrylamide (PAM), have been widely ex-plored in an effort to measure different as-pects of cell mechanics during contraction.In 1980, Harris et al used soft silicone rubberto qualitatively measure cellular force [9]. Inthe last two decades, methods such as thisone have evolved into robust and complextechniques that offer extensive cellular forcedevelopment analysis. Despite the signifi-cant advances in such approaches,

...they are limited by extensivecomputation for force calibrationdue to a continuous substrate de-formation [17].

In 2005, Zhao et al, created a PDMS mi-croship to measure cellular force and studysubcellular mechanics [12, 17]. The chip con-sisted of micrometer scale polymeric pillarson a plain substrate. This chip was fabri-cated using a flexible polymer microfrabri-cation technique to create polymeric mi-crostructures of various aspect ratios, whichallows for the measurement of a range offorces at the subcellular level. This was anattempt to avoid the common problems thatresult from the application of polymeric pil-lars, as often they are too far apart or closeto one another and force measurement accu-racy is compromised.

Similar studies have been done with mi-cropatterned substrates to measure force de-velopment, cell motion and the creation offocal adhesion points. Such approach wasdeveloped with the intent to be a real-time,high resolution measurement of force appliedby cells at single adhesion points by combin-ing micropatterned substrates and fluores-cence imaging. This method poses the sameproblems exhibited by the other methods byusing expensive equipment and requiring ro-bust and complex methodologies.

4 Materials and Methods

4.1 Cell Preparation

Following isolation using enzyme retrogradeperfusion in the isolated heart, cardiocyteswere plated to trap fibroblasts and avoidtheir presence in microscope images. Cellsremained in the incubator in this state forapproximately two hours. Cardiocytes werere-plated to trap any extra fibroblasts re-maining in the cell suspension. Cells re-mained in this state for another hour. Cellswere finally transferred to plates with 10%fetal bovine serum (FBS) solution in whichthey were to remain for the rest of the pro-cedure. The 10% FBS solution was changedas necessary throughout the analysis in orderto keep cells properly oxygenated and imagesfree of unwanted objects such as death cells.Forty-eight hours later the cardiocyte’s con-tractile machinery is developed enough to beready for video recording. Plated cells wereelectrically paced at 0.33 Hz for 3 msec du-ration.

4.2 Microscopy and DataAcquisition

The analysis in this study assumed that thevolume of any given cardiocyte remains con-stant as it contracts. The magnitude of vol-ume changes accompanying muscle cell con-traction are known to be only a few mil-lionths of the resting volume [4]. The car-diocytes were observed using a Nikon phasecontrast microscope (Model ELWD). Out-put of a Cohu CCD camera (Model 2122-1000) mounted on the microscope was digi-tized by a frame grabber card. Images wererecorded using Windows Movie Maker soft-ware at a frequency of 30 frames per sec-ond. Video frames were fed into Matlab forbatch processing using various Image Pro-cessing Toolbox functions.

5 Image Analysis

5.1 Image Processing of AdultMyocyte Sequence

The analysis of the adult myocyte video se-quence was done via the application of Mat-labs Image Analysis Toolbox and its built-in functions. The analysis required the cre-ation of a script that allowed an automatic

application of a series of image enhancementand quantification functions for each framein the contraction sequence. The scriptloaded the image sequence into Matlab andprocessed the images one by one with eachof the Matlab built-in functions listed in thescript.

The first Matlab Image Analysis tool ap-plied by the script was the imclose function.This function prepared the image for the restof the analysis by performing a morphologi-cal closing on the grayscale image. The op-eration performed a dilation followed by anerosion, which tends to smooth the contoursof objects and generally joins narrow breaks,fills long thin gulfs and fills the holes smallerthan the structuring element [8]. The result-ing image was subtracted from the originalimage depicting the adult myocyte as a wayto increase contrast between myocyte andbackground and to aid in the edge detectionprocess. Figure 2 shows the morphologicallyclosed image containing an adult myocyteafter being processed by the imclose func-tion (top-left) and the resulting image whenthe morphologically closed image was sub-tracted from the original image (top-right).

The next step in the adult image process-ing sequence, was the creation of binary im-ages. In order to create a binary image, the

Matlab command im2bw was applied; thiscommand creates a binary (black and white)image by applying a threshold value. Thethreshold value was used as a break pointto depict pixels with values higher than thethreshold as white pixels and pixels with val-ues lower than the threshold as black pixels,thus creating a binary image. In figure 2we can see the image after (bottom-left) theim2bw command was applied.

The next step in the process was the re-moval of spurious optical background, leav-ing only a binary outline of the myocyte.Then the adult myocyte image was itselfcleared of any trace of cell inclusions, leav-ing nothing but the cell outline in the im-age; ready for area measurements. In fig-ure 2 we can see the binary image containingthe adult myocyte and optical background(bottom-left), and finally the cell outlineready for area measurements (bottom-right).

The script proceeded to repeat the imageprocessing with all the images in the contrac-tion sequence. The area of the adult myoctyewas determined for each individual frame.Finally, a graph depicting myocyte area vs.time was created. Figure 3 shows the finaloutput of the script applied in Matlab witha sequence of 30 images.

5.2 Image Processing ofNeonatal Myocyte Sequence

The analysis of the neonatal myocyte con-traction was also performed via the applica-tion of the functions in the Matlabs ImageAnalysis Toolbox. The analysis required thecreation of a script that asked the user thename of the sequence of images to be ana-lyzed and the number of images in the se-quence. The script loaded the images intoMatlab and processed the images one by onewith each of the Matlab built-in functionslisted in the script.

The first built-in Matlab Image Analy-sis function used was the imadjust function.This function prepared the image for the restof the analysis by decreasing the dynamicrange possible for the pixels in the image.The Matlab function imadjust is an inten-sity transformation function for gray scale

images. The function maps the intensity val-ues in the image in question to new values inan output image. The function takes valuesbetween low in and high in and maps themto values between low out and high out. Allthe values below low in and above high inare removed. There exists a gamma param-eter which determines the shape of the curvethat depicts the way in which intensity val-ues are mapped. In the case of the appli-cation to this project the gamma parameterwas set to a value of 1, such that intensityvalues are mapped linearly [8].

The next step in the analysis process wasthe creation of a binary image that will un-cover the inclusions resulting from the con-tractile mechanisms in the center of the my-ocytes. In order to create this binary im-age, the Matlab command im2bw was used.This command creates binary images usinga threshold value as explained in the adult

Fig. 2: 4 Steps of the Adult analysis process. Top-left shows the adult myocyteimage after the application of the morphological closing procedure. Top-right, shows the adult myocyte after the subtraction of the morphologicalyclosed image. Bottom left shows the binary image of the adult myocyte.Bottom right shows the adult myocyte after the elimination of the un-wanted objects

myocyte processing section of this report.The script then commanded the user to

select a region of interest (ROI) where theinclusion area changes were to be quanti-fied. Changes in these objects (correspond-ing to dark inclusions within the myocyte)with time were interpreted as an expressionof contractile response of the neonatal car-diocyte. The script proceeded to repeat theprocess with all the images in the sequence.The total area of the inclusions was deter-

mined for each individual image. The in-dividual values are stored in a data array.Finally, a graph depicting inclusion area vs.time was created. Figure 4 shows a sam-ple of an image enhanced for processing, abinary image showing the region of interestand the corresponding contraction record.In figure 5 we can see the final output ofthe script run in Matlab of two different se-quences of neonatal contractions.

Repeatability was an issue as soon as ourfirst non-invasive procedure for measuringcontractile responses was developed. In or-der to see whether we could produce consis-tent results on the same cell, we recorded acell throughout multiple contractions. Theimage sequences were analyzed using theneonatal image processing procedure. The

results showed satisfactory results, since wewere able obtain a contraction record of thefive consecutive contractions (see figure 6).Figure 7, shows the five consecutive contrac-tions overlaid in the same graph, includingan average of the contractile behavior of themyocyte.

Fig. 3: (A) Adult myoctye image taken using inverted phase contrast microscopy.(B) Outline of adult myocyte. (C) Image overlap (A) and (B) to showaccuracy of cell outline. (D) Contraction record of adult myocyte.

6 Discussion

Neonatal myocytes represent a challengewhen trying to obtain a functional responsethat can be compared with measurementsof cell shortening vs. time (or cell force vs.time) from adult myocytes. Adult cardiaccells have a well defined cylindrical morphol-ogy, and contractility can be measured bymeasuring the cells shortening (or the short-ening of individual sarcomeres within thecell, the engines of shortening and force de-velopment). Our laboratory measures adultcardiac myocyte responses with a one di-mensional video-based edge detection circuitprocessing video images of the shorteningcell [12].

Cell perimeter and cell outline changesrecorded in adult cardiocytes using the newtechnique consistently decreased during con-traction with a pattern similar to shorten-ing vs. time curves recorded by tracking cellboundaries, and appeared to provide a re-liable measure of contraction. The advan-tage offered by the new method is that it isa more inclusive method that takes into ac-count the entire cell geometry rather thanjust the overall edge-to-edge length.

We originally hypothesized that a changein a neonatal cells perimeter and area couldbe detected by image analysis, with the un-

derstanding that contraction was likely ac-companied by a retraction of the cells bound-aries and a slight increase in its elevation.Such changes in elevation were recorded byShevchuk in 2006, using the atomic force mi-croscope, or AFM [15]. The signal gener-ated by the new neonatal method producescontraction vs. time graphs are very simi-lar in behavior to those of the adult cardio-cytes. Our study has been successful in prov-ing that a usable contractility signal can beobtained from neonatal myocytes based onthe application of image analysis. We havegreat expectations for the research capabili-ties that the creation of these two procedurescan provide.

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Fig. 4: (A) Original image showing Neonatal Myocyte. (B) Image enhanced for process-ing. (C) Binary image of Neonatal Myocyte after image processing, showing cellinclusions and region of interest. (D) Contraction Record of Neonatal Myocyte.

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Fig. 5: Neonatal Myocyte Images after being processed. (A,C) Contractionrecord of neonatal myocyte. (B,D) Image of Neonatal Myocyte takenusing inverted phase contrast microscopy.

Fig. 6: Multiple Contraction Record of Neonatal Myocyte. Record of 5 Consecutive Con-tractions Exhibited by a Neonatal Myocyte.

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Fig. 7: Record of 5 Contractions and Average. All Contractions were exhibited by theSame Neonatal Myocyte in a Consecutive Fashion.