Image-based Automated Counting of Plasma Cells and Marrow Cellularity in Core Marrow Biopsies

Clinical Center

Investigators

Abstract

Plasma cells (PC) are normally responsible for manufacturing large amounts of antibodies. When PC become cancerous they accumulate in the bone marrow, where they interfere with the production of normal blood cells and destroy bone. The most aggressive form of PC cancers is called Multiple Myeloma, which constitutes 1% of all cancers. One of the most valuable procedures used in the diagnosis of these cancers and determination of tumor load is a bone marrow examination. This procedure consists of obtaining aspirates and bone biopsies where pathologists examine microscopic preparations and estimate the number of PC present. This number is currently a required criterion for diagnosis of PC cancers and also evaluation of response to therapy. However, current microscopic methods for the enumeration of PC lack precision. The counts in the aspirates are affected by blood contamination and estimations based on bone tissue preparations are somewhat subjective and at best semi-quantitative. Also, the total marrow cellularity, which is valuable in assessing numerous hematologic conditions, is evaluated semi-quantitatively. To facilitate these counts and improve accuracy and precision, we developed digital image-based software to perform a rapid quantitation of PC and marrow cellularity in bone marrow biopsies. The initial evaluation of this software provided excellent results and we are performing additional testing to further validating it. A similar approach used for PC could be extended to the analysis of other cell types such as leukemic cells, lymphocytes, or cells of other lineages. Although the testing and validations of the current software version demonstrated very good results, there are limitations with the program that preclude its universal use. For example, the software produces acceptable results as long as it is used with images obtained with a single microscope and a single camera. If either of these is changed, the software coding needs to be changed accordingly, a process that is not practical. Also, the application process is rather slow. For these reasons, the software language and algorithm are currently being modified not only to make the program flexible enough to accommodate different resolutions and other imaging conditions (colors, intensities, etc.) but also to make the software application faster and more efficient in order to make it more practical than the existing version.