#Astronomical algorithms 1998 pdf manual#

We describe three algorithms developed for oestrogen receptor (ER), B-cell lymphoma protein 2 (BCL2) and human epidermal growth factor receptor 2 (HER2) representing examples of nuclear, cytoplasmic and membranous staining patterns, respectively. We therefore investigated the adaptation of algorithms used in astronomy to immunostained microscopic images of breast cancer in order to produce comparable measures of protein expression ( Walton et al, 2010). Driven by the large volume of data, image analysis in the field of astronomy has matured into a sophisticated, robust discipline. However, these efforts are seriously limited by the bottleneck of manually assessing immunostains for tens of proteins across thousands of cases and the pathologist’s ability to discriminate between small staining differences on this scale.Īstronomers have long been faced with the problem of automatically deriving objective, reproducible and continuous information from complex telescopic images of the sky.

In addition, TMAs and IHC have enabled the investigation of high-dimensional relationships between proteins expressed in cancers in a manner analogous to expression profiling using cDNA microarrays ( Callagy et al, 2003 Makretsov et al, 2004 Abd El-Rehim et al, 2005 Jacquemier et al, 2005 Ali et al, 2011).

#Astronomical algorithms 1998 pdf manual#

However, this process continues to rely heavily on manual assessment of staining resulting in laboriously acquired semi-quantitative readouts of protein expression. The coupling of IHC and tissue microarray (TMA) technology has enabled researchers to screen for candidate biomarkers in large study cohorts including clinical trials. The advantages of IHC, which include preserved tissue morphology, quick turnaround time and ability to assay small amounts of tissue such as core biopsies, have established it as the principal ancillary study in diagnostic pathology. Immunohistochemistry (IHC) is the most widely used method for the assessment of protein expression in tissues in both the clinical and research setting. The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology.

Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to ‘positive’ or ‘negative’ categories with agreement rates of up to 96%. Results:Īll continuous automated scores showed good correlation with their corresponding ordinal manual scores. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists. We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress. High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry.