ABSTRACT
The purpose of this study was to improve the prognostic value of tumour histopathology image analysis methodology by image preprocessing. Key image qualities were modified including contrast, sharpness and brightness. The texture information was subsequently extracted from images of haematoxylin/eosin-stained tumour tissue sections by GLCM, monofractal and multifractal algorithms without any analytical limitation to predefined structures. Images were derived from patient groups with invasive breast carcinoma (BC, 93 patients) and inflammatory breast carcinoma (IBC, 51 patients). The prognostic performance was indeed significantly enhanced by preprocessing with the average AUCs of individual texture features improving from 0.68 ± 0.05 for original to 0.78 ± 0.01 for preprocessed images in the BC group and 0.75 ± 0.01 to 0.80 ± 0.02 in the IBC group. Image preprocessing also improved the prognostic independence of texture features as indicated by multivariate analysis. Surprisingly, the tonal histogram compression by the nonnormalisation preprocessing has prognostically outperformed the tested contrast normalisation algorithms. Generally, features without prognostic value showed higher susceptibility to prognostic enhancement by preprocessing whereas IDM texture feature was exceptionally susceptible. The obtained results are suggestive of the existence of distinct texture prognostic clues in the two examined types of breast cancer. The obtained enhancement of prognostic performance is essential for the anticipated clinical use of this method as a simple and cost-effective prognosticator of cancer outcome.
Subject(s)
Breast Neoplasms/pathology , Histocytochemistry/methods , Image Processing, Computer-Assisted/methods , Microscopy/methods , Specimen Handling/methods , Algorithms , Female , Humans , Neoplasm Grading/methods , PrognosisABSTRACT
PURPOSE: To evaluate the influence of molecular biomarkers (estrogen receptor - ER, progesterone receptor - PR, and human epidermal growth factor receptor2 - HER2) and pathological parameters on metastasis free interval (MFI) in adjuvantly tamoxifen-treated breast cancer patients, during different follow up periods (0-2.5 years, 2.5-5 years and 5-12 years). METHODS: The study included 113 postmenopausal breast cancer patients with known pathological parameters. Steroid receptors were determined by ligand-binding assay and HER2 amplification status by chromogenic in situ hybridization (CISH). RESULTS: During the first 2.5 years of therapy patients with ER <5 fmol/mg, PR <5 fmol/mg or pT2 (≥2cm) tumors had higher probability of distant metastasis. For the period between 2.5-5 years, analysis of MFI according to pathological parameters and molecular biomarkers, separately, did not show any statistically significant difference. Patients with pT≥2 cm and HER2 amplification had much greater chance of developing distant metastasis when compared to other phenotypes (HER2-negative/pT1, HER2-negative/pT2 and HER2-positive/pT1). Patiens with ER ≥160 fmol/mg and PR ≥45 fmol/mg had good prognosis after 5 years of tamoxifen therapy. CONCLUSION: Our study indicates that there is a change of influence of the analyzed pathological parameters on MFI, depending on different follow up periods. Steroid receptor status, tumor size and HER2 status (alone or in combination) are significant parameters for the course of disease of postmenopausal ER-positive breast cancer patients, but during different periods of follow up.
Subject(s)
Antineoplastic Agents, Hormonal/therapeutic use , Biomarkers, Tumor/analysis , Breast Neoplasms/chemistry , Breast Neoplasms/drug therapy , Neoplasms, Hormone-Dependent/chemistry , Neoplasms, Hormone-Dependent/drug therapy , Tamoxifen/therapeutic use , Adult , Aged , Aged, 80 and over , Biomarkers, Tumor/genetics , Breast Neoplasms/genetics , Breast Neoplasms/pathology , Chemotherapy, Adjuvant , Disease-Free Survival , Female , Humans , Kaplan-Meier Estimate , Middle Aged , Neoplasms, Hormone-Dependent/pathology , Postmenopause , Receptor, ErbB-2/genetics , Receptors, Estrogen/analysis , Receptors, Progesterone/analysis , Risk Factors , Time Factors , Treatment Outcome , Tumor BurdenABSTRACT
We have developed a novel microarray approach for differential screening using probes labelled with two different radioelements. The complementary DNAs from the reverse transcription of mRNAs from two different biological samples were labelled with radioelements of significantly different energies (3H and 35S or 33P). Radioactive images corresponding to the expressed genes were acquired with a MicroImager, a real time, high resolution digital autoradiography system. An algorithm was used to process the data such that the initially acquired radioactive image was filtered into two subimages, each representative of the hybridisation result specific for one probe. The simultaneous screening of gene expression in two different biological samples requires <100 ng mRNA without any amplification. In such conditions, the technique is sensitive enough to directly quantify the amount of mRNA even when present in small amounts: 10(7) molecules in the probe as assessed with an added control sequence and 2 x 10(5) molecules with an endogenous tyrosine hydroxylase mRNA. This novel technique of double radioactive labelling on a microarray is thus suitable for the comparison of gene expression in two different biological samples available in only small quantities. Consequently, it has great potential for various biological fields, such as neuroscience.
