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Using Artificial Intelligence to Detect Cervical Cancer

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Doctor reviewing cell phone
Credit: gettyimages/Dean Mitchell

My last post highlighted the use of artificial intelligence (AI) to create an algorithm capable of detecting 10 different kinds of irregular heart rhythms. But that’s just one of the many potential medical uses of AI. In this post, I’ll tell you how NIH researchers are pairing AI analysis with smartphone cameras to help more women avoid cervical cancer.

In work described in the Journal of the National Cancer Institute [1], researchers used a high-performance computer to analyze thousands of cervical photographs, obtained more than 20 years ago from volunteers in a cancer screening study. The computer learned to recognize specific patterns associated with pre-cancerous and cancerous changes of the cervix, and that information was used to develop an algorithm for reliably detecting such changes in the collection of images. In fact, the AI-generated algorithm outperformed human expert reviewers and all standard screening tests in detecting pre-cancerous changes.

Nearly all cervical cancers are caused by the human papillomavirus (HPV). Cervical cancer screening—first with Pap smears and now also using HPV testing—have greatly reduced deaths from cervical cancer. But this cancer still claims the lives of more than 4,000 U.S. women each year, with higher frequency among women who are black or older [2]. Around the world, more than a quarter-million women die of this preventable disease, mostly in poor and remote areas [3].

These troubling numbers have kept researchers on the lookout for low cost, but easy-to-use, tools that could be highly effective at detecting HPV infections most likely to advance to cervical cancer. Such tools would also need to work well in areas with limited resources for sample preparation and lab analysis. That’s what led to this collaboration involving researchers from NIH’s National Cancer Institute (NCI) and Global Good, Bellevue, WA, which is an Intellectual Ventures collaboration with Bill Gates to invent life-changing technologies for the developing world.

Global Good researchers contacted NCI experts hoping to apply AI to a large dataset of cervical images. The NCI experts suggested an 18-year cervical cancer screening study in Costa Rica. The NCI-supported project, completed in the 1990s, generated nearly 60,000 cervical images, later digitized by NIH’s National Library of Medicine and stored away safely.

The researchers agreed that all these images, obtained in a highly standardized way, would serve as perfect training material for a computer to develop a detection algorithm for cervical cancer. This type of AI, called machine learning, involves feeding tens of thousands of images into a computer equipped with one or more high-powered graphics processing units (GPUs), similar to something you’d find in an Xbox or PlayStation. The GPUs allow the computer to crunch large sets of visual data in the images and devise a set of rules, or algorithms, that allow it to learn to “see” physical features.

Here’s how they did it. First, the researchers got the computer to create a convolutional neural network. That’s a fancy way of saying that they trained it to read images, filter out the millions of non-essential bytes, and retain the few hundred bytes in the photo that make it uniquely identifiable. They fed 1.28 million color images covering hundreds of common objects into the computer to create layers of processing ability that, like the human visual system, can distinguish objects and their qualities.

Once the convolutional neural network was formed, the researchers took the next big step: training the system to see the physical properties of a healthy cervix, a cervix with worrisome cellular changes, or a cervix with pre-cancer. That’s where the thousands of cervical images from the Costa Rican screening trial literally entered the picture.

When all these layers of processing ability were formed, the researchers had created the “automated visual evaluation” algorithm. It went on to identify with remarkable accuracy the images associated with the Costa Rican study’s 241 known precancers and 38 known cancers. The algorithm’s few minor hiccups came mainly from suboptimal images with faded colors or slightly blurred focus.

These minor glitches have the researchers now working hard to optimize the process, including determining how health workers can capture good quality photos of the cervix with a smartphone during a routine pelvic exam and how to outfit smartphones with the necessary software to analyze cervical photos quickly in real-world settings. The goal is to enable health workers to use a smartphone or similar device to provide women with cervical screening and treatment during a single visit.

In fact, the researchers are already field testing their AI-inspired approach on smartphones in the United States and abroad. If all goes well, this low-cost, mobile approach could provide a valuable new tool to help reduce the burden of cervical cancer among underserved populations.

The day that cervical cancer no longer steals the lives of hundreds of thousands of women a year worldwide will be a joyful moment for cancer researchers, as well as a major victory for women’s health.

References:

[1] An observational study of Deep Learning and automated evaluation of cervical images for cancer screening. Hu L, Bell D, Antani S, Xue Z, Yu K, Horning MP, Gachuhi N, Wilson B, Jaiswal MS, Befano B, Long LR, Herrero R, Einstein MH, Burk RD, Demarco M, Gage JC, Rodriguez AC, Wentzensen N, Schiffman M. J Natl Cancer Inst. 2019 Jan 10. [Epub ahead of print]

[2] “Study: Death Rate from Cervical Cancer Higher Than Thought,” American Cancer Society, Jan. 25, 2017.

[3] “World Cancer Day,” World Health Organization, Feb. 2, 2017.

Links:

Cervical Cancer (National Cancer Institute/NIH)

Global Good (Intellectual Ventures, Bellevue, WA)

NIH Support: National Cancer Institute; National Library of Medicine


Standing With a Remarkable Young Man

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Francis Collins and Andrew Lee

It was a pleasure to participate in presenting Andrew Lee with the Charles A. Sanders, M.D., Partnership Award at the annual fall board dinner of the Foundation for the National Institutes of Health (FNIH). The dinner was held on October 24 in Bethesda, MD. The 22-year-old Lee uses his passion for cars to travel the country to raise awareness and funds for rare kidney cancer research in children and young adults. In just over two years, Lee has turned his Driven to Cure, Inc. into an active grassroots movement that has made generous donations to help advance cutting-edge kidney cancer research conducted by the National Cancer Institute at the NIH Clinical Center. The Charles A. Sanders, M.D., Partnership Award is named for the former chairman of the FNIH Board of Directors. Credit: FNIH


Fighting Cancer with Natural Killer Cells

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GIF of immune cells attacking

Credit: Michele Ardolino, University of Ottawa, and Brian Weist, Gilead Sciences, Foster City, CA

Cancer immunotherapies, which enlist a patient’s own immune system to attack and shrink developing tumors, have come a long way in recent years, leading in some instances to dramatic cures of widely disseminated cancers. But, as this video highlights, new insights from immunology are still being revealed that may provide even greater therapeutic potential.

Our immune system comes equipped with all kinds of specialized cells, including the infection-controlling Natural Killer (NK) cells. The video shows an army of NK cells (green) attacking a tumor in a mouse (blood vessels, blue) treated with a well-established type of cancer immunotherapy known as a checkpoint inhibitor. What makes the video so interesting is that researchers didn’t think checkpoint inhibitors could activate NK cells.


The Cancer Genome Atlas Symposium 2018

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An Aspirin a Day for Older People Doesn’t Prolong Healthy Lifespan

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Hands holding a pill and a glass of water

Credit: iStock/thodonal

Many older people who’ve survived a heart attack or stroke take low-dose aspirin every day to help prevent further cardiovascular problems [1]. There is compelling evidence that this works. But should perfectly healthy older folks follow suit?

Most of us would have guessed “yes”—but the answer appears to be “no” when you consider the latest scientific evidence.  Recently, a large, international study of older people without a history of cardiovascular disease found that those who took a low-dose aspirin daily over more than 4 years weren’t any healthier than those who didn’t. What’s more, there were some unexpected indications that low-dose aspirin might even boost the risk of death.


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