Machines See the Future for Patients Diagnosed with Brain Tumors

For patients diagnosed with glioma, a deadly form of brain tumor, the future can be very uncertain. While gliomas are often fatal within two years of diagnosis, some patients can survive for 10 years or more. Predicting the course of a patient's disease at diagnosis is critical in selecting the right therapy and in helping patients and their families to plan their lives.

Researchers at Emory and Northwestern Universities recently developed artificial intelligence (AI) software that can predict the survival of patients diagnosed with glioma by examining data from tissue biopsies. The approach, described in Proceedings of the National Academy of Sciences, is more accurate than the predictions of doctors who undergo years of highly-specialized training for the same purpose.

Doctors currently use a combination of genomic tests and microscopic examination of tissues to predict how a patient's disease will behave clinically or respond to therapy. While genomic testing is reliable, these tests do not completely explain patient outcomes, and so microscopic examination is used to further refine prognosis. Microscopic examination, however, is very subjective, with different pathologists often providing different interpretations of the same case. These interpretations can impact critical decisions like whether a patient enrolls in an experimental clinical trial or receives radiation therapy as part of their treatment.

"Genomics have significantly improved how we diagnose and treat gliomas, but microscopic examination remains subjective. There are large opportunities for more systematic and clinically meaningful data extraction using computational approaches," says Daniel J. Brat, MD, PhD, the lead neuropathologist on the study, who began developing the software while at Emory University and the Winship Cancer Institute. Brat currently is chair of pathology at Northwestern University Feinberg School of Medicine.

The researchers used an approach called deep-learning to train the software to learn visual patterns associated with patient survival using microscopic images of brain tumor tissue samples. The breakthrough resulted from combining this advanced technology with more conventional methods that statisticians use to analyze patient outcomes. When the software was trained using both images and genomic data, its predictions of how long patients survive beyond diagnosis were more accurate than those of human pathologists. The study used public data produced by the National Cancer Institute's Cancer Genome Atlas project to develop and evaluate the algorithm.

"The eventual goal is to use this software to provide doctors with more accurate and consistent information. We want to identify patients where treatment can extend life," says Lee A.D. Cooper, PhD, the study's lead author, a professor of biomedical informatics at Emory University School of Medicine and member of the Winship Cancer Institute. "What the pathologists do with a microscope is amazing. That an algorithm can learn a complex skill like this was an unexpected result. This is more evidence that AI will have a profound impact in medicine, and we may experience this sooner than expected."

The researchers also demonstrated that the software learns to recognize many of the same structures and patterns in the tissues that pathologists use when performing their examinations. "Validation remains a barrier to using these algorithms in patient care. Being able to explain why an algorithm works is an important step towards clinical implementation."

The researchers are looking forward to future studies to evaluate whether the software can be used to improve outcomes for newly diagnosed patients.

Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, Lee AD Cooper.
Predicting cancer outcomes from histology and genomics using convolutional networks.
PNAS March 12, 2018. 201717139. doi: 10.1073/pnas.1717139115.

Most Popular Now

MSD is Looking for a Digital Health Solu…

MSD Lebanon is looking for an external partner to co-create a digital solution that helps oncologists to stay updated with relevant clinical content about cancer. The solution should consider several...

Brain-Computer Interface Enables People …

Tablets and other mobile computing devices are part of everyday life, but using them can be difficult for people with paralysis. New research from the BrainGate consortium shows that a...

Diagnosing a Heart Attack at 10,000 Mete…

A passenger suddenly has chest pain on board. The crew asks for a doctor; when present, this is not always a cardiologist. The pilot has to decide if a flight...

Medical Experts Once Again Were "Sp…

12 - 15 November 2018, Düsseldorf, Germany. Once again, decision makers of the international healthcare industry were "spoiled for choice" when it came to the themes at the world’s largest medical...

GenePlanet Presents its Innovative Healt…

GenePlanet, the Swiss-backed biotech company present in more than 30 countries worldwide, is attending MEDICA, the leading international trade fair for the medical sector that takes place in Düsseldorf, Germany...

AI-Pathway Companion from Siemens Health…

At the Congress of the Radiological Society of North America (RSNA 2018) in Chicago, USA, Siemens Healthineers is presenting AI-Pathway Companion* for the first time. It is a clinical decision...

Philips Latest 'Future Health Index' Rep…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, announced publication of the latest Future Health Index (FHI) report. 'Telehealth: delivering value across institutional and geographical borders...

AI System may Accelerate Search for Canc…

Searching through the mountains of published cancer research could be made easier for scientists, thanks to a new AI system. The system, called LION LBD and developed by computer scientists...

AOK Counts on the Orchestra eHealth Suit…

The AOK community builds a digital health network for its insurants and thus takes on a pioneering task among German health insurances. Through the digital health network its 25 million...

New China and US Studies Back Use of Pul…

Fast and easy blood pressure monitoring could soon be at your fingertips - literally - thanks to new University of British Columbia research that showed blood pressure (BP) can be...

Australian Health Region Boosts Patient …

Patients and clinicians will benefit from easy access to critical real-time patient information at the bedside after Australian population health services provider ACT Health signed a further contract with Patientrack's...