© 2002 The Royal Microscopical Society Journal of Microscopy, Vol. 205, Pt 2 February 2002, pp. 125–135 Received 4 January 2001; accepted 7 September 2001 Blackwell Science Ltd A method for quantifying cell size from differential interference contrast images: validation and application to osmotically stressed chondrocytes L. G. ALEXOPOULOS*‡, G. R. ERICKSON*† & F. GUILAK*†‡ *Orthopaedic Research Laboratories, Department of Surgery, Box 3093, Duke University Medical Center, Durham, NC 27710, U.S.A. †Department of Biomedical Engineering, Duke University, Box 90281, 136 Hudson Hall, Durham, NC 27708-0281, U.S.A. ‡Department of Mechanical Engineering & Materials Science, Duke University, Box 90300, 144 Hudson Hall, Durham, NC 27708-0300, U.S.A. Key words. Cell measuring, chondrocytes, differential interference contrast (DIC), dynamic programming, edge detection, edge linking, image analysis, image processing, morphology, morphometry, osmotic stress, volume regulation. Summary An automatic image analysis method was developed to deter- mine the shape and size of spheroidal cells from a time series of differential interference contrast (DIC) images. The program incorporates an edge detection algorithm and dynamic pro- gramming for edge linking. To assess the accuracy and work- ing range of the method, results from DIC images of different focal planes and resolutions were compared to confocal images in which the cell membrane was fluorescently labelled. The results indicate that a 1-μm focal drift from the in-focus plane can lead to an overestimation of cell volume up to 14.1%, mostly due to shadowing effects of DIC microscopy. DIC images allow for accurate measurements when the focal plane lies in a zone slightly above the centre of a spherical cell. In this range the method performs with 1.9% overall volume error without taking into account the error introduced by the representation of the cell as a sphere. As a test case, the method was applied to quantify volume changes due to acute changes of osmotic stress. Introduction Under normal physiological conditions, cells are exposed to varying mechanical and physicochemical stresses that result in active and passive changes in cell volume and morphology. In articular cartilage, for example, chondrocyte phenotypic expression and metabolic activity are strongly influenced by changes in cell shape and volume secondary to mechanical and chemical (e.g. osmotic) stresses (Guilak et al., 1997). In this respect, the accurate measurement of cell shape and size is an important step in the interpretation of structure–function relationships in cells. A first step in determining cell shape and size from digital microscopy images is identification of the cell boundaries, and several different techniques have been adapted for quantitat- ive analysis of cell morphology. However, by necessity, such methods are only applicable to a specific model system. For example, three-dimensional (3-D) volume images recorded by confocal or dual-photon microscopy may be well-suited for studying cell morphology in situ, but can be limited in certain cases due to the need for fluorescence imaging and the length of the time needed to acquire 3-D stacks of images(Guilak, 1994; Guilak et al., 1995; Errington et al., 1997; Errington & White, 1999; Kubinova et al., 1999). In studying isolated cells, 2-D images are often recorded via video or scanning micro- scopy using a variety of contrast techniques. Differential inter- ference contrast (DIC) is a technique that is often used to increase image contrast in plated cells. However, quantitative determination of the cell border in DIC images is a non-trivial task owing to the differences in image contrast along the cell boundary. Reports in the literature show a variety of 2-D image processing algorithms for quantitative cell morphometry (Inoue & Spring, 1997; Sabri et al., 1997). Young & Gray (1997) developed an algorithm based on thresholding and gradient- follow methods. This method requires manual thresholding and identification of the boundary, which may introduce bias Correspondence: Farshid Guilak, PhD, Orthopaedic Research Laboratories, Duke University Medical Center, 375 MSR Bldg., Research Dr, Box 3093, Durham, NC 27710, U.S.A. Tel.: +1 919 684 2521; fax: +1 919 681 8490; e-mail: guilak@duke.edu Received 4 January 2001; accepted 7 September 2001