From the July 2019 issue of HealthCare Business News magazine
By Tory Waldron
Medical imaging saves millions of lives each year, helping doctors to detect and diagnose a wide range of diseases, from cancer and appendicitis to stroke and heart disease.
However, it can be challenging for imaging centers and radiology departments to develop efficient workflows, especially given the sheer volume of data passing through these organizations on a daily basis.
Currently, diagnostic mammography is the top U.S. radiology procedure by total volume: over 2.4 million procedures, according to Definitive Healthcare data. That’s over 2.4 million patient charts for U.S. radiologists to sift through and analyze on a yearly basis! In 2018, physicians reported more than 187,000 breast cancer diagnoses, making regular screenings an integral part of preventative health. And, with a combined 4 million procedures, chest x-rays also produce an overwhelming amount of data for radiologists to examine.
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With millions of patients and scans to review, it’s essential for imaging departments to be as efficient as possible. And, ultimately, this can be achieved through the power of technology.
1. Invest in new AI technologies
The first imperative for any radiologist is to prioritize the patients most in need of treatment, which often means sifting through piles of charts and data. However, this can become time-consuming; a high volume of patients and scans may delay any necessary treatments. AI technologies are working toward bridging this gap.
Artificial intelligence in the medical imaging market is estimated to rise from $21.48 billion in 2018 to a projected value of $264.85 billion by 2026, according to Data Bridge Market Research’s April 2019 report. Ultimately, AI has the potential to revolutionize the medical imaging industry by sifting through mountains of scans quickly and offering providers and patients life-changing insights into a variety of diseases, injuries, and conditions that may be hard to detect without the supplemental technology.
So what are some imaging-related AI technologies to keep your eye on? First and foremost, Google’s DeepMind AI technology can read 3D retinal OCT scans and diagnose ophthalmic conditions with 99 percent accuracy, alerting the technician to which patients require the most urgent care. ICAD’s “ProFound AI” solution is revolutionizing digital breast tomosynthesis (DBT) by allowing radiologists to view each breast tissue layer independently, which helps detect cancer earlier (by 8 percent) and reduces radiologists’ time spent reading each breast scan by more than 50 percent on average.