MAR 15, 2018 11:18 AM PDT

Algorithm Predicts Glioma Survival Better Than Specialists

WRITTEN BY: Kara Marker

For people newly diagnosed with glioma, a lethal brain cancer, the most they can hope for is an accurate diagnosis, so doctors can choose the best treatment plan, and a careful prognosis, so they can plan for their future. New technology from Emory University provides an option to produce both.

Pathology specimen of a glioma of the midline. Credit: Jensflorian

Glioma is characterized by any tumor that develops from the supportive tissue of the brain, called glia, which regulates neuron function. Symptoms and treatment depend on the exact type of glial cell that is affected by cancer, and the exact cause of glioma is unknown. Doctors do know that those diagnosed with glioma often die within two years of diagnosis, but some people survive for more than a decade. How can doctors distinguish between the two groups so glioma patients know how to plan for their future?

Existing options for glioma diagnosis and prognosis include genomic tests and microscopic examinations of tissue samples. However, genetic testing cannot predict a patient’s future on its own, and microscopic exams are open to interpretation by different doctors.

"Genomics have significantly improved how we diagnose and treat gliomas, but microscopic examination remains subjective,” explained lead scientist Daniel J. Brat, MD, PhD. “There are large opportunities for more systematic and clinically meaningful data extraction using computational approaches.”

The opportunity seized by Emory scientists focused on artificial intelligence (AI) software designed to predict which glioma patients will survive longer than a couple of years. The program is based on tissue biopsies. And so far, the software has been more accurate than predictions made by glioma specialists.

Microscopic images of brain tumor tissue samples and a process called “deep-learning” were used to program software to act as glioma specialists, looking for visual clues that indicate a patient’s odds of survival. Researchers primed the software with both images and genomic data.

After testing the software, its predictions of how long glioma patients survived following their diagnoses was more accurate than predictions made by human pathologists. Over time, the software “learns to recognize many of the same structures and patterns in the tissues that pathologists use when performing exams.”

Scientists want to see this program making predictions for doctors seeing glioma patients. This could greatly enhance decision making about treatments and future planning. Researchers are also looking for new opportunities to further test the program’s ability to improve outcomes for patients newly diagnosed with glioma.

"What the pathologists do with a microscope is amazing. That an algorithm can learn a complex skill like this was an unexpected result,” said lead author Lee A.D. Cooper, PhD. “This is more evidence that AI will have a profound impact in medicine, and we may experience this sooner than expected."

The present study was published in the journal Proceedings of the National Academy of Sciences.

Sources: American Brain Tumor Association, Emory Health Sciences

About the Author
  • I am a scientific journalist and enthusiast, especially in the realm of biomedicine. I am passionate about conveying the truth in scientific phenomena and subsequently improving health and public awareness. Sometimes scientific research needs a translator to effectively communicate the scientific jargon present in significant findings. I plan to be that translating communicator, and I hope to decrease the spread of misrepresented scientific phenomena! Check out my science blog: ScienceKara.com.
You May Also Like
SEP 14, 2020
Clinical & Molecular DX
Cell Line Authentication Using STR Analysis
SEP 14, 2020
Cell Line Authentication Using STR Analysis
Imagine you’re studying colon cancer using a colon cell line model. After three painstaking years of research, you ...
OCT 17, 2020
Clinical & Molecular DX
Imaging Innovation Set to Ease the Pain of Osteoarthritis
OCT 17, 2020
Imaging Innovation Set to Ease the Pain of Osteoarthritis
In osteoarthritis, the joint cartilage that cushions bones begins to break down, causing debilitating pain and stiffness ...
OCT 29, 2020
Cannabis Sciences
Hemp 10 Years from Now
OCT 29, 2020
Hemp 10 Years from Now
The hemp industry has experienced major growth in recent years, largely due to legalization in many US states. Today, th ...
NOV 15, 2020
Neuroscience
Hearing Test Can Predict Autism in Newborns
NOV 15, 2020
Hearing Test Can Predict Autism in Newborns
For some time now, researchers have been aware that children and adults with autism tend to have different sensory syste ...
JAN 12, 2021
Clinical & Molecular DX
Portable Sequencer Ensures All the Cancer Cells Are Gone
JAN 12, 2021
Portable Sequencer Ensures All the Cancer Cells Are Gone
Surgeons remove a tumor from the abdominal cavity of a patient. But how can they be certain that all the cancer cells we ...
JAN 19, 2021
Cardiology
Looking to the Immune System for Help Diagnosing Carotid Stenosis
JAN 19, 2021
Looking to the Immune System for Help Diagnosing Carotid Stenosis
Everyone has seen a commercial about how bad fats can build up into a plaque into a blood vessel. This is called atheros ...
Loading Comments...