Automated nuclear image morphometry on fine needle aspiration smears of malignant round cell tumors

To analyze nuclear image morphometry in fine needle aspiration cytology smears of different groups of malignant round cell tumors (MRCTs) to evaluate its diagnostic role.

In this study there were 55 cases of MRCT, consisting of 18 Ewing's sarcoma (EW), 10 neuroblastoma (NB), 5 non-Hodgkin's lymphoma (NHL), 6 rhabdomyosarcoma (RMS), 4 peripheral neuroectodermal tumor (PNET), 8 Wilm's tumor (WT), 2 retinoblastoma (RB) and 2 undifferentiated round cell tumor (URCT). A Leica image cytometer with Quantimet 600 software (Leica, Cambridge, U.K) was used to measure nuclear area, nuclear diameter, nuclear perimeter, nuclear convex perimeter (CP), nuclear roundness and nuclear convex area on hematoxylin and eosin-stained cytologic smears. At least 100 cells were studied in each case.

The RB group of tumors showed the highest mean nuclear area (NA), convex area (CA), CP, diameter (D), perimeter (P) and roundness (R). RMS had the highest mean CA, and URCT had the highest mean roundness. ANOVA was performed on the tumors and showed significant differences for all the variables in all the groups (P < .000). All the morphometric data (except roundness) were significantly different in RMS versus all other MRCTs except RB. Similarly, morphometric data on WT were also significantly different from that on NHL. Most of the morphometric data (except CA and R) showed significant differences between RB and all other MRCTs except RMS. PNET, EW and NB could not be differentiated with those variables.

RMS and RB could successfully be differentiated from all other MRCTs with the help of morphometry. It was not possible to differentiate RMS and RB by image cytometry (ICM) since the ICM data overlapped in those two groups. It was possible to differentiate WT and NHL with ICM. Nuclear ICM was not significantly different in the NB, PNET and ES groups, and probably ICM would not be very helpful to differentiate these groups of MRCT.