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Fast-Tracking Pathology via Automated Image Analysis and High-Performance Computing: Application to Prostate Cancer Diagnostics

Final Report Summary - FAST-PATH (Fast-Tracking Pathology via Automated Image Analysis and High-Performance Computing: Application to Prostate Cancer Diagnostics)

Prostate cancer is the most common solid malignancy and the second leading cause of cancer death in men. With PSA screening being associated with over-treatment, the most significant clinical issue faced by the clinician and patient is discriminating between potentially lethal tumours needing immediate treatment and indolent cancer suitable for active surveillance. Gleeson grading currently represents the best marker of aggressiveness of this morphologically complex disease but demands increasing numbers of needle core biopsies to confirm diagnosis, which impacts on patients as well as increasing healthcare costs. By examining the morphological features of the tumour and novel biomarkers, we aimed to develop techniques that could more easily and accurately distinguish between aggressive and indolent prostate cancer. This would enable clinicians to personalise each patient’s care, thus yielding better outcomes for patients and reducing the economic burden of unnecessary treatment.

FAST-PATH (www.fastpathproject.com) was a collaborative effort undertaken by 6 partners across 3 EU countries. This pan-European project, with a total budget of €1.9 million, encouraged cooperation between key academic and industrial partners, centred on the intersectorial training of 14 experienced researchers who were recruited by FAST-PATH partners and seconded between institutions.

The central aim of the FAST-PATH programme was to address fundamental issues in prostate diagnostics through the use of novel tissue imaging technologies. Computer-based tissue imaging was utilised to support the high-throughput diagnostic analysis of prostate core biopsies. Newly discovered prostate cancer biomarkers were tested and validated by companion imaging algorithms that were developed to validate their efficacy and to ensure objectivity and reliability in diagnostic practice.

The FAST–PATH project produced exploitable foreground, including substantial improvements and refinements to OncoMark’s proprietary digital image analysis software IHC-MARK. OncoMark, an Irish SME based in Dublin, have optimised the IHC-MARK software to identify and quantify prostate cancer biomarkers expressed in the nucleus, membrane and cytoplasm of cells. PathXL, a UK SME based in Belfast, have developed and commercialised a web-based product called TissueMark, which allows pathologists and molecular pathology researchers to automate tumour mark-up and incorporate digital pathology into routine assessment of tissue samples. TissueMark won the 2014 Frost & Sullivan European Award for New Product Innovation.

Over the four year course of the FAST-PATH project, 13 experienced researchers were recruited by or seconded between the academic institutions and the SMEs. The transfer of knowledge between the institutions has yielded 14 scientific papers in peer-reviewed journals, one book chapter and 2 PhD dissertations to date. The training received by each fellow in these centres for excellence has greatly improved their experience and their career prospects, in addition to their contribution to advancement in the prostate cancer research field.