An algorithmic approach to diagnose haematolymphoid neoplasms in effusion by combining morphology,...

There are limited studies of cytology diagnosis of haematopoietic and lymphoid tumours in serosal effusion except for occasional case reports. We would like to demonstrate an algorithmic approach for accurate diagnosis, especially in patients without previous history.

We reviewed 36 cases of lymphoma diagnosed in serosal effusion following an algorithmic approach. Suspected tumour cells were classified into small, intermediate and large sizes and two characteristic forms of plasmacytoid and Reed Sternberg-like on smears (step 1), followed by utilising panels of immunohistochemical markers and Epstein-Barr encoding region in situ hybridisation on cell blocks (step 2). A panel of CD3, CD20 and Ki-67 formed the basic workup, followed by pertinent batteries of immunostaining. Molecular tests were applied in 22 selected cases by fluorescence in situ hybridisation (step 3).

There were 15 diffuse large B-cell lymphomas; 12 plasma cell myelomas; two mantle cell lymphomas; one anaplastic large cell lymphoma ALK +; one small lymphocytic lymphoma; one plasmablastic lymphoma; one peripheral T-cell lymphoma, not otherwise specified, one extranodal NK/T-cell lymphoma, nasal type and two T-cell lymphoblastic lymphomas. 14 cases with previous history had complete concordance in immunophenotype between cytology and histology. Another 14 cases were primarily diagnosed in patients with initial symptom of effusion based on immunophenotyping and cytogenetic test in selected cases. Eight cases were diagnosed based on morphology alone.

An algorithmic approach based on morphology and immunohistochemistry is the key to making an accurate diagnosis of haematopoietic and lymphoid tumours in effusion. A molecular test is also important for confirmation and prognostic prediction. We reviewed 36 haematolymphoid neoplasms diagnosed in effusion including 14 cases primarily diagnosed in patients without previous history following an algorithmic approach by combining morphology, immunohistochemistry and molecular cytogenetics.