title: Quantitative Image Analysis of Epithelial and Stromal Area in Histological Sections of Colorectal Cancer: An Emerging Diagnostic Tool.
abstract: In colorectal cancer (CRC), an increase in the stromal (S) area with the reduction of the epithelial (E) parts has been suggested as an indication of tumor progression. Therefore, an automated image method capable of discriminating E and S areas would allow an improved diagnosis. Immunofluorescence staining was performed on paraffin-embedded sections from colorectal tumors (16 samples from patients with liver metastasis and 18 without). Noncancerous tumor adjacent mucosa (n = 5) and normal mucosa (n = 4) were taken as controls. Epithelial cells were identified by an anti-keratin 8 (K8) antibody. Large tissue areas (5-63 mm(2)/slide) including tumor center, tumor front, and adjacent mucosa were scanned using an automated microscopy system (TissueFAXS). With our newly developed algorithms, we showed that there is more K8-immunoreactive E in the tumor center than in tumor adjacent and normal mucosa. Comparing patients with and without metastasis, the E/S ratio decreased by 20% in the tumor center and by 40% at tumor front in metastatic samples. The reduction of E might be due to a more aggressive phenotype in metastasis patients. The novel software allowed a detailed morphometric analysis of cancer tissue compartments as tools for objective quantitative measurements, reduced analysis time, and increased reproducibility of the data.
authors.affiliation: Department of Pathophysiology and Allergy Research, Medical University of Vienna, 1090 Vienna, Austria ; TissueGnostics GmbH, 1020 Vienna, Austria.
authors.forename: R
authors.initials: R
authors.lastname: Rogojanu
authors.affiliation: Department of Pathophysiology and Allergy Research, Medical University of Vienna, 1090 Vienna, Austria.
authors.forename: T
authors.initials: T
authors.lastname: Thalhammer
authors.affiliation: Department of Pathophysiology and Allergy Research, Medical University of Vienna, 1090 Vienna, Austria.
authors.forename: U
authors.initials: U
authors.lastname: Thiem
authors.affiliation: Department of Pathophysiology and Allergy Research, Medical University of Vienna, 1090 Vienna, Austria.
authors.forename: A
authors.initials: A
authors.lastname: Heindl
authors.affiliation: Clinical Institute of Pathology, Medical University of Vienna, 1090 Vienna, Austria.
authors.forename: I
authors.initials: I
authors.lastname: Mesteri
authors.affiliation: Seewald Solutions, 4616 Weisskirchen/Traun, Austria.
authors.forename: A
authors.initials: A
authors.lastname: Seewald
authors.affiliation: Department of Clinical Pharmacy and Diagnostics, University of Vienna, 1090 Vienna, Austria.
authors.forename: W
authors.initials: W
authors.lastname: Jäger
authors.affiliation: Faculty of Automatic Control and Computer Engineering, "Gheorghe Asachi" Technical University of Iasi, 700050 Iasi, Romania.
authors.forename: C
authors.initials: C
authors.lastname: Smochina
authors.affiliation: Department of Pathophysiology and Allergy Research, Medical University of Vienna, 1090 Vienna, Austria.
authors.forename: I
authors.initials: I
authors.lastname: Ellinger
authors.affiliation: Department of Pathophysiology and Allergy Research, Medical University of Vienna, 1090 Vienna, Austria.
authors.forename: G
authors.initials: G
authors.lastname: Bises
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D015179:Colorectal Neoplasms / Q000473:pathology*; D003238:Connective Tissue / Q000473:pathology*; D004847:Epithelial Cells / Q000473:pathology*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008113:Liver Neoplasms / Q000473:pathology* / Q000556:secondary*; D008297:Male; D008853:Microscopy / Q000379:methods; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity