Context: The proliferation marker Ki67 is an important diagnostic and prognostic aid in surgical pathology. However, manual quantification in a counting frame to accurately establish the proliferation rate (Ki67 index) is cumbersome and time-consuming. Instead, digital image analysis of Ki67/MART1 double stains may provide fast and novel index computations for entire tumor sections.
View Article and Find Full Text PDFThe dramatic increase in computer processing power in combination with the availability of high-quality digital cameras during the last 10 years has fertilized the grounds for quantitative microscopy based on digital image analysis. With the present introduction of robust scanners for whole slide imaging in both research and routine, the benefits of automation and objectivity in the analysis of tissue sections will be even more obvious. For in situ studies of signal transduction, the combination of tissue microarrays, immunohistochemistry, digital imaging, and quantitative image analysis will be central operations.
View Article and Find Full Text PDFObjective: The aim of this study was to assess the impact of oral hormone therapy (HT) on breast density in postmenopausal women and to compare the use of computer-based automated approaches for the assessment of breast density with reference to traditional methods.
Methods: Low-dose oral estrogen (1 mg) continuously combined with drospirenone (2 mg) was administered to postmenopausal women for up to 2 years (26 treatment cycles, 28 d/cycle) in a randomized, placebo-controlled trial. This post hoc analysis assessed the changes in breast density measured from digitized images by two radiologist-based approaches (Breast Imaging Reporting and Data System score and interactive threshold) and one computer-based technique (heterogeneity examination of radiographs).
Unlabelled: The aim of this study was to investigate whether transdermal low-dose estradiol treatment induces changes in mammographic density or heterogeneity compared with raloxifene, whether if these changes relate to changes in bone formation/resorption markers, and whether these findings indicate elevation of breast cancer risk by treatment.
Methods: Digitized mammograms of 2 x 135 completers of a 2-year, randomized trial formed the base of the present analysis. Active treatments were transdermal estradiol releasing 0.
We investigate the possibility to develop methodologies for assessing effect specific structural changes of the breast tissue using a general statistical machine learning framework. We present an approach of obtaining objective mammographic pattern measures quantifying a specific biological effect, such as hormone replacement therapy (HRT). We compare results using this approach to using standard density measures.
View Article and Find Full Text PDFMed Image Comput Comput Assist Interv
January 2008
A methodology is introduced for the automated assessment of structural changes of breast tissue in mammograms. It employs a generic machine learning framework and provides objective breast density measures quantifying the specific biological effects of interest. In several illustrative experiments on data from a clinical trial, it is shown that the proposed method can quantify effects caused by hormone replacement therapy (HRT) at least as good as standard methods.
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