Flow cytometry immunophenotyping (FCI) of fine needle aspirates (FNAs) of lymph nodes.

ABSTRACT

Flow cytometry immunophenotyping (FCI) has an important role in the clinic work-up of fine needle aspirates (FNAs) of lymph nodes. Its standardization has been defined by proposed analytical protocols and procedures used to assure proper analytical results also in those non-routine samples. In Institute of Clinical Chemistry, "Merkur" University Hospital, FCI is accredited method according to laboratory accreditation standard ISO 15189. According to this laboratory accreditation standard, participation in external quality assessment (EQA) programs is a prerequisite for assuring integrity and quality of the entire laboratory process. A critical analysis of our institutional experience in the feasibility of FCI of the material obtained by FNA of lymph nodes with suspected lymphoma represented the purpose of the study. During an eight-year period in Institute of Clinical Chemistry, "Merkur" University Hospital, a total of 1295 FNA analysis was done, 245 of them with a possible diagnosis of B-cell Non-Hodgkin lymphomas (B-NHL) formed the basis of the study. Lymphocytes were isolated on density gradient according to Boyum et al. The average feasibility of FNAs for FCI analysis was 86% (ranged 78-93%). An acceptable total cell number in FNAs for FCI analysis (4257) was established. In total population of respondents statistical significances in expressions of cellular antigens CD3, CD5, CD22, CD23, CD19 and CD5 on B-cells (CD5+CD19+) between patient's with final diagnosis of benign, reactive lymphoid proliferations and patient's with diagnosis of B-NHL were found. EQA results analysis showed that all results were either inside target values (X +/- 1SD) or inside accepted values (X +/- 2SD). Compatibility of the restriction of immunoglobulins light chains determinated by FCI and cytomorphology diagnosis depends on the choice of criterion values of the light chains ratio which determine the monoclonality. According to the matrix of shares of all classified data of retained neural network, ranges of diagnostic sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and prevalency of 82%, 72%, 93%, 48%, and 72% were produced. As a conclusion, FCI is a reliable methodology for phenotyping FNAs of lymph nodes with suspected B-NHLs detecting their clonality easily.