Toggle Main Menu Toggle Search

Open Access padlockePrints

Image analysis can be used to detect spatial changes in the histopathology of pancreatic tumours

Lookup NU author(s): Dr Andrew SimsORCiD, Dr Mark Bennett, Dr Alan Murray

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

Pancreatic cancer is frequently associated with intense growth of fibrous tissue at the periphery of tumours, but the histopathological quantification of this stromal reaction has not yet been used as a prognostic factor because of the difficulty of obtaining quantitative measures using manual methods. Manual histological grading is a poor indicator of outcome in this type of cancer and there is a clinical need to establish a more sensitive indicator. Recent pancreatic tumour biology research has focused upon the stromal reaction and there is an indication that its histopathological quantification may lead to a new prognostic indicator. Histological samples from 21 cases of pancreatic carcinoma were stained using the sirius red, light-green method. Multiple images from the centre and periphery of each tumour were automatically segmented using colour cluster analysis to subdivide each image into representative colours. These were classified manually as stroma, cell cytoplasm or lumen in order to measure the area of each component in each image. Measured areas were analysed to determine whether the technique could detect spatial differences in the area of each tissue component over all samples, and within individual samples. Over all 21 cases, the area of stromal tissue at the periphery of the tumours exceeded that at the centre by an average of 10.0 percentage points (P < 0.001). Within individual tumours, the algorithm was able to detect significantly more stroma (P < 0.05) at the periphery than the centre in 11 cases, whilst none of the remaining cases had significantly more stromal tissue at the centre than the periphery. The results demonstrate that semi-automated analysis can be used to detect spatial differences in the area of fibrous tissue in routinely stained sections of pancreatic cancer.


Publication metadata

Author(s): Sims AJ, Bennett MK, Murray A

Publication type: Article

Publication status: Published

Journal: Physics in Medicine and Biology

Year: 2003

Volume: 48

Issue: 13

Pages: N183-N191

ISSN (print): 0031-9155

ISSN (electronic):

Publisher: Institute of Physics Publishing Ltd.

URL: http://dx.doi.org/10.1088/0031-9155/48/13/401

DOI: 10.1088/0031-9155/48/13/401


Altmetrics

Altmetrics provided by Altmetric


Share