5 Ways Artificial Intelligence Is Transforming Digital Pathology
– As the digital pathology market grows, facilities that rely on digital pathology will start using artificial intelligence (AI) to assist. AI could help health professionals cope with the gigantic quantities of data
– Discover why healthcare facilities increasingly realize that AI could help achieve significant impacts with digital pathology.
Thanks to approvals from the Food and Drug Administration (FDA) for applications such as primary disease diagnosis, digital pathology is rapidly becoming the new standard of care.
However, this advancement creates challenges that artificial intelligence could help solve.
Digital pathology enables capturing pathology information, such as whole slide images (WSI), and working with it digitally using a specialized scanner. Acquiring, studying and managing data in this way allows sharing between parties on a computer or mobile device.
According to experts, the global digital pathology market was worth $689.2 million in 2018. It’s also expected to grow at a rate of 11.7% each year between 2018 and 2026.
Why Does Digital Pathology Need Artificial Intelligence?
As the digital pathology market grows, facilities that rely on digital pathology will start using artificial intelligence (AI) to assist. AI could help health professionals cope with the gigantic quantities of data that digital pathology images create.
“The shift from traditional patient care to digital pathology continues beyond virtual microscopy, or even radiology PACS (picture archiving and communication system) solutions,” says David Dimond, Chief Innovation Officer Global Healthcare & Life Sciences at Dell Technologies. “This entails very specialized technology solutions that pull information from a wide range of disparate healthcare and research databases – inside and outside individual facilities. The pathology workflow and patient experience is very different as the pathology patient gives biomaterial which is more than just an image as leveraged in radiology.”
“For example,” he says, “due to the pure volume in size of slides leveraged in digital pathology (2-3GB per image), they must be processed using an updated digital workflow, which requires unprecedented scale. The slides are then scanned and imported into a software program, which uses machine learning to spot subtle patterns and provide detailed information to the pathologist.”
“This convergence of advanced imaging, automation, and powerful analytics like natural language processing (NLP), machine learning, and artificial intelligence (AI) in healthcare and life sciences organizations are bringing together the tools needed for scientists and clinicians to unlock medical breakthroughs at a pace like never before,” says Dimond.
He continues: “Determining how to integrate AI technology into workflows is a first step to change how pathologists work on a day-to-day basis – and many organizations are implementing the traditional and digital workflows in parallel in order to optimize the benefits of modernizing their pathology departments.”
Digital pathology could potentially improve the quality and speed of patient care forever. One of the benefits is a pathologist can look at a whole slide at once, then choose to zoom in on areas of interest. In contrast, a conventional microscope does not allow for looking at an entire tissue sample. Such fragmented views can cause even the most experienced pathologists to miss things.
Moreover, digital pathology allows looking at several images side by side. This option could be particularly useful when looking at multiple pictures of tumors over time, for example. These benefits transfer to patients by helping them receive the correct diagnoses sooner. Also, since digital pathology facilitates information sharing, it’s easier for clinicians to get other opinions from colleagues.
