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Desmoplasia measured by computer assisted image analysis: an independent prognostic marker in colorectal carcinoma

¹ Department of Pathology, Dokuz Eylül University School of Medicine, Inciralt, Izmir 35340, Turkey
² Department of General Surgery, Dokuz Eylül University School of Medicine
³ Department of Biomedical Engineering, Dokuz Eylül University School of Medicine

Correspondence to:
Dr S Sarioglu
Dokuz Eylül University School of Medicine, Department of Pathology, Inciralt, Izmir 35340, Turkey; sulen.sarioglu{at}deu.edu.tr Aims: The assessment of desmoplasia by traditional semiquantitative methods does not provide reliable prognostic data. The aim of this study was to quantify desmoplasia by computerised image analysis in primary colorectal carcinomas and to investigate its ability to predict overall survival.

Methods: In total, 112 colorectal adenocarcinomas, with a median follow up of 66 months, were studied. The representative tumour sections were stained by the van Gieson method, which stains collagen rich stroma red. For quantitative histochemical measurement, digital images were analysed by a computerised image analysis program to calculate the percentage of red stained tissue area. The percentage of desmoplasia (PD) was related to conventional clinicopathological prognostic factors and overall survival.

Results: The mean (SD) PD was 4.85 (3.37). PD was found to be significantly associated with lymph vessel and venous invasion. By Kaplan–Meier analysis, PD was associated with survival—patients with PD > 4 had a shorter survival than those with PD 4. In multivariate analysis, tumour stage, distant metastasis, and PD emerged as independent prognostic factors.

Conclusion: Desmoplasia measured by image analysis seems to be a significant prognostic indicator in patients with colorectal carcinoma and the improved method described in this study would be useful for routine prognostication.

Abbreviations: CV, coefficient of variation; PD, percentage of desmoplasia

Keywords: desmoplasia; colorectal carcinoma; prognosis; quantitative histochemistry; image analysis

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