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Indica Labs Announces Collaboration With The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics


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Indica Labs and The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) have announced an agreement to collaborate on the development of an AI-based digital pathology solution for the detection of cancer within lymph nodes from colorectal surgery cases. The primary aim of the innovative research project is to develop a tool which in the future may improve the efficiency of pathology teams within the National Health Service Greater Glasgow and Clyde (NHSGGC) reporting colorectal cancer cases and the detection of metastatic cancer in lymph nodes.


Funded by a combination of Innovate UK and industrial partners, and based in Scotland, and supported by the West of Scotland Innovation Hub, iCAIRD is one of the largest healthcare AI research portfolios in the UK. A collaboration of 30 partners from across the NHS, industry, academia and technology, the programme is currently delivering 35 ground-breaking AI projects across radiology and pathology, having grown from just 10 projects at the outset in 2019. The mission of iCAIRD is to establish a world-class centre of excellence for implementation of artificial intelligence in digital diagnostics.


Anonymised H&E slides from NHS Greater Glasgow and Clyde’s digital pathology archive will be used to train, validate and test the algorithm, which is being developed collaboratively by iCAIRD and Indica Labs. The resulting algorithm will report negative and positive lymph node status and will be compared to pathologist reports. Furthermore, positively involved lymph nodes will be categorized into metastases, micro-metastases, and individual tumor cells.


Dr. Gareth Bryson, Consultant Pathologist at NHSGGC and Clinical Director for Laboratory Medicine of iCAIRD commented on the potential value this tool will bring to the NHS: "Our belief is that AI powered decision support tools, such as the one we are working on, may help to support pathologists by improving the process’ efficiency, while simultaneously increasing sensitivity in detecting small metastasis – which will direct patient therapy. Colorectal cancer resections are one of the most common cancer resection specimens and a disproportionate amount of pathologist’s time is utilised in screening lymph nodes."


Indica Labs, based in Albuquerque, New Mexico, offers a suite of digital pathology image analysis solutions including HALO AI™, and HALO AP®; both of which will be utilized by Indica Labs and iCAIRD partners for the development of AI-based pathology solutions and their evaluation in an NHS digital pathology workflow.


HALO AI uses deep learning neural networks to classify and quantify clinically significant tissue patterns and cell populations. HALO AP is a CE-IVD certified software platform for digital anatomic pathology labs that can operate as a standalone case and image management system or can be fully integrated within LIS or HIS solutions. HALO AP supports a full range of tissue-based workflows, including AI-assisted assays, quantitative analytics, synoptic reporting, tumor boards, and secondary consults. In addition to HALO AI and HALO AP, Indica Labs recently received a CE-IVD mark for HALO Prostate AI, a deep learning-based screening tool designed to assist pathologists in identifying and grading prostate cancer in core needle biopsies that is deployed using HALO AP.


"The team at Indica Labs is excited to collaborate with iCAIRD on the development and deployment of a state-of-the-art AI tool that aims to improve diagnostic accuracy, turnaround times, and laboratory efficiency for the benefit of both pathologists and colorectal cancer patients," commented Steven Hashagen, CEO Indica Labs.


HALO AP will be evaluated within simulated digital workflows at the pathology department in NHS GGC, using iCAIRD’s research environment to demonstrate interoperability with clinical systems. HALO AP will be used as a platform to deliver the new colorectal cancer algorithm. Through this collaboration, diagnostic accuracy and efficiency will be compared between existing fully digital workflows and one that applies AI through HALO AP.

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