Optical Projection Tomography Imaging Offers New Approach for Breast Cancer Research

The team, led by Prof. Deirdre Meldrum, senior scientist and director of the Arizona State University (ASU) Center for Biosignatures Discovery Automation at Biodesign (Tempe, USA), has assessed normal, benign, and malignant cells, using the first research Cell-CT, developed by VisionGate, Inc. (Phoenix, AZ, USA)--a customized instrument capable of imaging cells in precise three-dimensional (3D) with true isotropic resolution. The technology allows the examination of subtle cellular details inaccessible with more conventional forms of microscopy that are inherently 2D.

The group’s findings appeared January 5, 2012, in the journal PLoS ONE. The 3D movie images of cells observed in the study reveal numerous characteristic traces of their condition as normal or aberrant. Prof. Meldrum commented, “There are numerous quantitative morphological parameters that are indicative of disease and may be used as biosignatures for disease staging and diagnosis. For example, a cancerous cell typically has an enlarged nucleus, nuclear invaginations, chromosome mutations, and unique nuclear shape changes.”

Currently, the definitive clinical diagnosis of breast cancer malignancy relies on careful examination of the nuclear structure of cells that have been prepared by histological staining and subjected to bright field microscopy. According to Vivek Nandakumar, lead author of the current study, pathologists qualitatively examine cell features including nuclear size, shape, nucleus-to-cytoplasm ratio, and the texture of cell chromatin. However, these observations do not involve quantitative measurements that would promote a more accurate analysis.

Prof. Meldrum agreed, as to the failings of conventional pathology. As director of the Microscale Life Sciences Center, she has devoted much of her career to the close study of cell heterogeneity, and the manner in which individual cells can go awry as they transition to diseased states. “In our analysis of live single cells we can quantify significant variation from cell to cell under the same conditions,” said Prof. Meldrum.

The scientists utilized Cell-CT to examine 150 cells in each of three specific categories: normal, benign fibrocystic and malignant breast epithelial. Controversy remains as to whether breast fibrosis, which may result from hormonal alterations, is a normal condition or an early indication of malignancy. The condition occurs when ligaments, scars, supportive tissue or other fibrous tissue become more prominent in the breast than fatty tissue.

Cell-CT is a new type of microscope, able to image cells in three-dimensions, using a technique called optical projection tomography. Cell-CT operates similar to a normal CT scanner, though it uses visible photons of light, instead of X-rays. Cells prepared for observation are not placed on slides, but are instead suspended in gel and injected through a microcapillary tube that permits multiple imaging in 360°.

The scanning process produces hundreds of thin slices through the cell. These sections, or tomographs, are reassembled through computer software, forming a detailed 3D image. Movies of cells seen in rotation brightly reveal shape asymmetries, a particularly useful tool for disease diagnosis.

The three cell types examined in the study fell into four distinct nuclear shape categories. Category 1 cell nuclei were slender, with marked concavity. Category 2 cells had a slight concavity and were bulky. Based on these shapes, the first two categories are termed mushroom cap morphology. (The category 2 mushroom cap morphology was the most common nuclear form seen in all three cell types.) Category 3 nuclei were mostly convex in shape, whereas category 4 nuclei were irregular and distorted in shape.

Significantly, cells taken from the cancerous cell line showed the largest fraction of irregular, category 4 and category 2 nuclei and the smallest fraction of nuclei with a category 3 convex shape. The malignant cells also displayed the greatest shape heterogeneity within category 4. The fibrocystic cell sample contained the largest portion of category 3 and the lowest portion of category 1 nuclei. The largest overall shape heterogeneity with respect to the four shape categories occurred in the normal cells.

Cell and nuclear volume were observed to increase as one travels from normal to fibrocystic to malignant cells, though fibrocystic cells had, on average, the largest nucleus-to-cytoplasm volume. Textural differences among cells and arrangement of chromatin were also observed. In all, the scientists computed 42 distinct 3D morphologic and textural descriptors of cellular and nuclear structure. Cell-CT technology is able to resolve cell features down to less than one half micron.

Study coauthor Roger Johnson, research laboratory manager at the Center for Biosignatures Discovery Automation, emphasized that the subtle nuclear differences seen, especially for the cancerous cells, would likely have been missed had the samples been examined with conventional 2D imagery. As a result, the architecture imaged with Cell-CT supersedes the existing nuclear grades established for cancer diagnosis using a microscope.

Although much progress has been made in determining the transformation of cells from normal to diseased states, patient outcomes for many forms of cancer remain discouragingly poor. Many believe a new paradigm for investigating such cancers will need to be established, and the field has drawn interested researches from diverse disciplines. Dr. Paul Davies, another coauthor of the current study is a physicist and cosmologist in ASU’s College of Liberal Arts and Sciences and part of a new US National Cancer Institute-funded consortium, focused on studying the physical science of cancer. “We expect that insights and methods drawn from physical science will lead to radical new ideas for understanding and tackling cancer,” said Dr. Davies.

These findings provide new clues into the variations of nuclear structure that often signal cell malignancy. The unparalleled structural details produced by Cell-CT have the potential to improve dramatically 3D nuclear morphometry, leading to a sensitive and specific nuclear grade classification for breast cancer diagnosis.

Related Links:
Arizona State University Center for Biosignatures Discovery Automation at Biodesign
VisionGate