Utah-based Novarad is working with Texas firm Ikonopedia to enhance clinical excellence with a complete breast care platform. And Radiology Imaging Associates has launched a breast cancer detection programme using artificial intelligence.

Novarad’s NovaMG Pro platform uses Ikonopedia’s cloud-based breast imaging reporting system, and Novarad’s viewing and image management technology.

Ikonopedia provides a structured reporting tool for breast reporting. Using metrics alerts and reporting, Ikonopedia lowers the amount of wrong patient reports and incorrect laterality. With QA notifications, shortcuts and automation, Ikonopedia’s breast reporting tool tracks every finding to a complete resolution to improve patient care and save lives.

Novarad’s user-friendly viewer includes data integration, hanging protocols, a single-click workflow, built-in safety checks to ensure a complete viewing, AI, report distribution, and the ability to read other radiology studies without requiring the doctor to change seats or log into a different system. It is a complete system that can be configured in minutes rather than days, and it integrates with every EMR.

One out of eight women will be diagnosed with breast cancer in their lifetime. Ikonopedia and Novarad seek to improve the quality of care for all women by ensuring the safe and efficient practice of breast imaging.

“The entire Ikonopedia team is excited about partnering with Novarad, who matches our commitment to core values of patient safety and physician efficiency,” said Emily Crane, CEO of Ikonopedia. “We know this collaboration will save lives, increase identification of high-risk patients, and provide physicians with the best tools available.”

Florida-based Radiology Imaging Associates, a division of RadNet, has started implementing its enhanced breast cancer detection (EBCD) service, which works with a patient’s annual breast screening regimen.

Patients can receive a screening mammography service including the application of Saige-Dx FDA-cleared artificial intelligence (AI) technology powered by DeepHealth, an additional AI-driven review applied to certain suspicious exams and findings, an in-depth personalised lifetime risk assessment for breast cancer, and a dedicated support line for questions about certain aspects of the patient’s reports.

EBCD presents an improved level of accuracy in breast cancer detection, empowering women to take greater control of their health.

“AI is dramatically improving our detection capability and overall quality,” said Howard Berger, CEO of RadNet.

Gregory Sorensen, founder of DeepHealth and president of RadNet’s AI division, added: “Saige-Dx is a sophisticated, AI deep-learning algorithm that has been trained on more data than any one radiologist would see in a lifetime. Saige-Dx’s pivotal study showed that radiologists who used Saige-Dx improved their performance, something no other mammography AI tool has demonstrated. Saige-Dx analyses each mammogram in detail and, if suspicious findings are present, the AI identifies the lesion in the exam for the radiologist and categorises the level of suspicion.”

And Jacqueline Holt, director of breast imaging at RadNet, said: “In medicine, the ability to see and detect disease with more certainty is a game-changer, driving better patient outcomes. We are using AI to detect breast cancers that the human eye might not notice. In my experience, the addition of these proven, FDA-cleared algorithms has allowed us to detect hundreds of cancers that otherwise would not have been found at the time of screening.”

In the past, many breast screening mammography patients have described a desire for more information about the reports and follow-ups they receive after their annual mammogram, including their lifetime risk of developing breast cancer. While a breast density score, required in 38 US states, is one factor in a patient’s lifetime risk for breast cancer, multiple factors can increase risk.

The EBCD service addresses questions about breast cancer risk by providing a personalised report and a specialist to call when patients have questions about their lifetime risk of breast cancer. Depending on the patient’s risk level, their referring physician might recommend a customised screening protocol.

The EBCD service was created for women who want more accurate and informative mammograms.

“The EBCD service is one of the most exciting and important endeavours the company has pursued for our patients and staff,” said Berger. “It serves as another example of how RadNet continues to lead radiology forward.”

RadNet has a network of 349 owned and/or operated outpatient imaging centres. Its markets include California, Maryland, Delaware, New Jersey, New York, Florida and Arizona. Together with affiliated radiologists, including full-time and per diem employees and technicians, RadNet has approximately 9000 employees.

DeepHealth uses machine learning to distil lifetimes of insights from medical experts into software to assist physicians.