Diagnosis and prognosis of neuroendocrine tumours of the lung by means of high resolution image analysis

Neuroendocrine tumours (NET) of the lung are divided in subtypes with diffe rent malignant potential. The first is the benign or low-grade malignant ru mours, well-differentiated, called typical carcinoids (TC) and the second i s the high-grade malignant tumours, poorly differentiated of small (SCLC) o r large cell type (LCLC). Between these tumour types lies the well-differen tiated carcinoma with a lower grade of malignancy (WDNEC). In clinical rout ine it is very important with regard to prognosis to distinguish patients w ith low malignant potential from those with higher ones. In this study 32 c ases of SCLC, 13 of WDNEC and 14 of TC with a follow-up time up to 7 years were collected. Sections 4 mu m thick from paraffin embedded tissue were Fe ulgen stained. By means of high resolution image analysis 100 nuclei per ca se were randomly gathered to extract morphometric, densitometric and textur al quantitative features. To investigate the ploidy status of the tumour th e corrected DNA distribution was calculated. Stepwise linear discriminant a nalysis to differentiate the classes and Cox regression analysis for the su rvival time analysis were applied. Using chromatin textural and morphometri c features in two two-class discriminations, 11 of the 14 TC cases and 8 of the 13 WDNEC cases were correctly classified and 11/13 WDNEC cases and 28/ 32 SCLC cases, respectively. The WDNEC cases are more similar in chromatin structure to TC than to SCLC. For the survival analysis, only chromatin fea tures were selected to differentiate patients with better and worse prognos is independent of staging and tumour type.