Abstract
A method and approach were developed for fully automated measurements of immunostained lymphocytes in tissue sections by means of digital color microscopy and patent pending advanced cell analysis. The validation data for population statistic measurements of immunostained lymphocytes in tissue sections using tissue cytometry is presented. Segmentation of a 512 x 474 RGB image and display of statistical results table took 12 to 15 seconds using in-house developed algorithms. We used a panel of 7 antibodies for validation on 14 cases of mantle cell lymphoma giving percentage positive, total lymphocytes, density staining. An average of 2027 image frames with 810,800 cell objects were evaluated. Antibodies to CD3, CD4, CD8, Bcl-1, Ki-67, CD20, CD5 were subjected to virtual flow cytometry on tissue. The results of tissue cytometry were compared with manual counts of expert observers and with the results of flow cytometry immunophenotyping of the same specimen. The correlation coefficient and 95 % confidence interval by linear regression analysis yielded a high concordance between manual human results (M), flow cytometry results(FC), and tissue cytometry (TC) results per antibody, (r =0.9365 manual vs TC, r =0.9537 FC vs TC). We noted a lower CD8 tumor infiltrating lymphocytes in blastic form than in non-blastic form of mantle cell and a higher Ki67 in the latter subtype than in the former. These results suggest the technology of tissue cytometry could be a clinically valid surrogate for both manual and flow cytometry analysis when only tissue immunohistochemistry is available for diagnosis and prognosis. The application for cancer diagnosis, monitoring, and prognosis is for objective counting of immunostained cells in tissues with percentage results. These results could be also be used in standardization of cut off percentage used in diagnosis; for exemplary tool for leukemic blasts(CD34) >20% for acute leukemia, for determining automated 30 % cut off for positivity for prognostic markers in diffuse large B-cell lymphoma for bcl-2, bcl-6, mum-1, and CD10.
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