Feature | Breast Imaging | May 28, 2020 | By January Lopez, M.D.

The Exciting Future of AI and Mammography - and Physicians

AI has the potential to help radiologists improve the efficiency and effectiveness of breast cancer imaging

AI has the potential to help radiologists improve the efficiency and effectiveness of breast cancer imaging

Getty Images

January Lopez, M.D.

January Lopez, M.D.

Headlines around the world the past several months declared that artificial intelligence (AI) is better at detecting breast cancer than human radiologists. Can artificial intelligence really read my own mammogram better than me? That would be intriguing, if it were true. 

In fact, there are no studies to date proving that AI technology reads mammograms more accurately than radiologists in the real-world setting, but what the groundbreaking study1 in the journal Nature did show was that AI could detect breast cancer more accurately than radiologists in a selected set of mammograms, particularly when those sets of mammograms are enriched with lots of breast cancer cases. 

The Promise of AI

Although there is much more research to be done, it grows clearer by the day that AI has great promise in improving breast cancer care. But as we venture out into the expanse of AI technology, it is critical we proceed with caution. Recall the headlines from March 2018 of the Uber fully autonomous car that killed a woman crossing the street in Tempe, Ariz. The car’s AI-based software was unable to identify her as a person crossing the street and struck her at around 40 MPH, according to the Associated Press. Then there was the meme that went viral on social media in 2016 depicting rows and columns of photos of Chihuahuas and blueberry muffins, which so cleverly illustrated the limitations of AI algorithms in correctly identifying some of those images so unmistakably identifiable by any human. Along those same lines, the recent article in Nature also found in its reader study that although AI was able to identify some cancers missed by the study radiologists, at least one cancer that was identified by all six radiologists was missed by the AI system.

So, where do we go from here? AI is good. Radiologists are good. But AI and radiologists are better together. I am seeing that potential firsthand as a principle investigator in an unpublished study Hoag is conducting in collaboration with Therapixel, a company that is not related to the Nature study, specializing in AI for medical imaging. The results of the study fully support this concept of augmented intelligence whereby the best results are obtained when radiologists harness the power of AI to optimize the accuracy and performance of mammographic screening for breast cancer.

AI’s Future in Mammography

Do I believe AI will become better at reading mammograms than me? I don’t know, but I sure hope so. Do I believe AI will make me obsolete? Not in my lifetime. Even if AI reaches its full potential, there are some cancers (i.e. “invisible cancers”) that it will miss simply due to the nature of mammography and other imaging techniques. Diagnosing breast cancer isn’t easy, and it certainly isn’t as simple as interpreting a mammogram. AI can’t lay hands on a person’s body or conduct a meaningful clinical interview that could reveal changes in skin, palpable lumps or discharge that turn out to be indicators of cancer. AI can’t perform breast biopsies or aspirations, and it cannot engage in a complex discussion about a woman’s individual values. Most importantly, AI cannot provide women with compassion and empathy.

I have heard AI described in medicine as analogous to the autopilot function on planes. While autopilot could potentially fly and land a plane on its own, would anyone be willing to board a plane without a human pilot? The same is true for patient care. AI will best be utilized in concert with radiologists who can shape the way it is used, develop standards and identify the technology’s limitations.

Instead of framing the story as “robot versus radiologist,” I believe patients are better served by discussing the powerful potential of putting AI and radiologists together. “AI has the potential to help radiologists improve the efficiency and effectiveness of breast cancer imaging” is not a scintillating headline. But it is a thrilling concept, and it’s one that I am excited to explore.

 

January Lopez, M.D., is a fellowship trained breast imaging specialist, board-certified diagnostic radiologist and Director of Breast Imaging at Hoag Breast Centers.

 

Reference:

1. McKinney, S.M., Sieniek, M., Godbole, V. et al. International evaluation of an AI system for breast cancer screening. Nature 577, 89–94 (2020). https://doi.org/10.1038/s41586-019-1799-6

 

Related Women's Health Content:

Leveraging Artificial Intelligence to Enhance the Radiologist and Patient Experience

Artificial Intelligence to Improve the Precision of Mammograms

Related Content

#SiemensHealthineers #Varian #Siemens The transformative combination accelerates the company’s impact on #global #healthcare and establishes a strong partner for #customers and #patients along the entire #cancer care continuum and for many of the most threatening #diseases
News | Radiology Business | April 15, 2021
April 15, 2021 — Siemens Healthineers AG an
Comparisons of high definition and standard definition infrared imaging for digital histopathology. Image courtesy of the Beckman Institute

Comparisons of high definition and standard definition infrared imaging for digital histopathology. Image courtesy of the Beckman Institute

News | Breast Imaging | April 14, 2021
April 14, 2021 — Detecting and analyzing breast cancer
A doctor reading #CXR scans using #SenseCare-Chest #DR Pro #diagnostic #software.

A doctor reading CXR scans using SenseCare-Chest DR Pro diagnostic software.

News | Artificial Intelligence | April 14, 2021
April 14, 2021 — SenseTime, a world-leading...
The U.S. Food and Drug Administration (#FDA) authorized marketing of #Medtronic's #GIGenius, the first device that uses #artificialintelligence (#AI) based on #machinelearning to assist #clinicians in detecting #lesions (such as #polyps or suspected tumors) in the #colon in real time during a c#olonoscopy.

The GI Genius intelligent endoscopy module works in real-time, automatically identifying and marking (with a green box) abnormalities consistent with colorectal polyps, including small flat polyps.

News | Artificial Intelligence | April 12, 2021
A 37-year-old woman developed a new, palpable left supraclavicular lymphadenopathy lump five days after her first dose of the Moderna COVID-19 vaccine in the left arm. On the day of vaccination, the patient was asymptomatic. This is an example of how the vaccine can mimic cancer and swollen lymph nodes. Image used with permission of RSNA.

A 37-year-old woman developed a new, palpable left supraclavicular lymphadenopathy lump five days after her first dose of the Moderna COVID-19 vaccine in the left arm. On the day of vaccination, the patient was asymptomatic. This is an example of how the vaccine can mimic cancer and swollen lymph nodes. Read more about this case study. Image used with permission of RSNA.

Feature | Coronavirus (COVID-19) | April 09, 2021 | By Dave Fornell, Editor
While the mass COVID-19 vaccinat
3-D mammography reduces the number of breast cancer cases diagnosed in the period between routine screenings, when compared with traditional mammography, according to a large study from Lund University in Sweden. The results are published in the journal Radiology.

Getty Images

News | Breast Imaging | April 09, 2021
April 9, 2021 — 3-D mammography reduces the number of breast cancer cases diagnosed in the period between routine scr
Varian announced it is collaborating with Google Cloud to build an advanced artificial intelligence (AI) based diagnostic platform to aid in the fight against cancer. Varian and Google Cloud AI embarked on a deployment journey, using Neural Architecture Search (NAS) technology via Google Cloud AI Platform, to create AI models for organ segmentation — a crucial and labor-intensive step in radiation oncology that can be a bottleneck in the cancer treatment clinical workflow.
News | Artificial Intelligence | April 08, 2021
April 8, 2021 — Varian announced it is collaborating with Google...
Mobidiag Oy, a privately held, commercial-stage Finnish-French developer of innovative molecular diagnostic tests and instrumentation, announced today that it has signed a definitive agreement to be acquired by Hologic, Inc., a global leader in women's health, for an enterprise value of approximately $795 million.  This includes a cash payment of approximately $714 million for Mobidiag’s equity, and net debt of approximately $81 million.
News | Women's Health | April 08, 2021
April 8, 2021 — Mobidiag Oy, a privately held, commercial-stage F
Brain tumors edged out by artificial intelligence: VBrain applies auto-contouring to the three most common types of brain tumors: brain metastasis, meningioma and acoustic neuroma.

Brain tumors edged out by artificial intelligence: VBrain applies auto-contouring to the three most common types of brain tumors: brain metastasis, meningioma and acoustic neuroma.

News | Artificial Intelligence | April 07, 2021
April 7, 2021 — Vysioneer, a leader in a...