Peter is Head of the Pathology Bioimaging and Informatics Laboratory within the Centre for Cancer Research and Cell Biology at Queen’s University Belfast. He is also Founder of and VP for Research and Development with PathXL Ltd, a global company specializing in digital pathology software for tumor analysis and biomarker discovery.
For the past 25 years, he has been leading research on digital pathology, computer vision and tissue bioimaging in diagnostic and molecular cancer pathology for the high throughput quantitative analysis identification of novel tissue and cell biomarkers markers. Being a pioneer of early techniques in tissue measurement, image analysis, pathology informatics and tissue biomarker discovery, he has been published in over 150 peer reviewed publications in some of the worlds leading journals.
Peter established the digital pathology laboratory at Queens University Belfast with a full range of whole slide scanning technology, specialized imaging techniques and associated image analysis software, which is now embedded within the wider Molecular Pathology Laboratory program. He also heads up a team of software developers in image analysis and pathology informatics, focused on developing new tools for automated tissue microarray analysis and clinogenomic data integration for biomarker discovery including high performance tissue imaging for biomarker discovery in prostate cancer.
As informatics lead for the Northern Ireland Biobank (NIB), a major initiative aimed at the prospective collection of high quality cancer tissue samples for translational research in cancer, he oversees the informatics to support tissue collection, tracking, storage and retrieval of tissue samples and integration of clinical, pathological and epidemiological data. He is also external informatics adviser to two national biobanks in Italy and South Africa. He has sat on MRC Panel of Experts, the Pathological Society Committee, Journal of Pathology Editorial Board and the International Society for Cellular Oncology.
As founder of PathXL Ltd (www.pathxl.com), Professor Hamilton has led the company through venture capital investment to a point where it now has an experienced senior management team, with sales across the world and an advanced portfolio of sophisticated digital pathology solutions for education, research and clinical practice. Recently, PathXL Ltd has been developing novel approaches to tumor imaging, cancer cell recognition, biomarker analysis and data integration aimed at supporting modern pathology in translational personalized medicine. PathXL has won the Frost and Sullivan Enabling Technology Award and the European New Product Innovation Award with its TissueMark™ platform for the automated identification and measurement of tumor tissue for molecular evaluation of solid tumors. PathXL is rapidly expanding its software products through Xplore™ to support the integration of digital pathology with big data integration. In addition to PathXL, he also sits on the board of a number of other Queen’s University spin-out biotechnology companies. Professor Hamilton has successfully married an outstanding academic career with a thriving digital pathology business, with the goal of translating innovative academic research into industry.
Title: Next generation Imaging and Computer Vision in Pathology: pipedream or reality?
Automated image analysis has had a long history but continues to grow with massive improvements in algorithms, speed, performance, and with emerging opportunities for high throughput tissue biomarker analysis and automated decision support for primary diagnostics. Of particular importance is the development of computer vision and image analysis for H&E stained samples. This talk will outline recent advances in automated tissue analysis for biomarker discovery and diagnostics and how adoption of digital pathology will drive the demand for quantitative imaging and decision support.
As an example, PathXL have developed TissueMark for the automated identification and analysis of tumour in lung, colon, breast and prostate cancer digital H&E slides. The conventional pathological estimation of % tumour nuclei in H&E samples shows gross variation between pathologists, undermining the quality of next generation sequencing, molecular testing and patient therapy and potential of false negative diagnoses. TissueMark uses a combination of pattern recognition, glandular analysis and nuclear segmentation to identify premaligant and invasive cancer patterns in H&E stained tissues and use this to assess tumour cell numbers and annotate samples for nucleic acid extraction and molecular profiling. Benchmark data was generated to validate TissueMark technology and showed concordance of automated data with manual counts, accelerating tumour markup and improving sample quality assessment. This represents an example of how automated imaging of tissue samples can be of immense value in quantitative tumour analysis for molecular diagnostics, thereby improving reliability in discovery and diagnostics.
This together with other examples in pathology research and practice will demonstrate that next generation tissue imaging technology in digital pathology could radically change how pathology is practiced.