Radiologists and AI-powered health informatics: Leading the way in screening

Radiologists and AI-powered health informatics: Leading the way in screening

Sham Sokka, chief operating and technology officer of DeepHealth, discusses why he is excited about this year’s ECR congress in Vienna.

What are you most excited about for ECR this year?

Vienna is such a beautiful city and I’m so excited to be here at The European Congress of Radiology (ECR 2024) again this year.

Sham Sokka, chief operating and technology officer of DeepHealth, discusses why he is excited about this year’s ECR congress in Vienna.

What are you most excited about for ECR this year?

Vienna is such a beautiful city and I’m so excited to be here at The European Congress of Radiology (ECR 2024) again this year.

At DeepHealth, this represents an exciting time – to showcase our pioneering offering, present new data, and meet and network with experts in the field of screening and radiology. I always relish the opportunity to talk to our customers from around the world.

Everything we do at DeepHealth is about empowering radiologists and healthcare professionals, not just in the detection and diagnosis of diseases but across the whole care continuum. So ECR is a really important time for us to get out and interact with our customers.

Can you tell us a little more about DeepHealth?

Yes, of course. DeepHealth is one of the leading providers in healthcare radiology informatics.

Our technology is used in over 300 radiology departments and imaging centers around the world. To date, over 15 million exams have been impacted by DeepHealth solutions, resulting in more than two million AI-informed clinical decisions.

We are developing a unique ‘one system’ approach, designed to optimize the healthcare pathway, support radiology departments and imaging centers with a comprehensive solution for medical imaging, and include operational solutions and end-to-end services across the clinical care continuum.

Our technology and software are proven to increase performance, from protocol development and scan interpretation to workflow efficiency and patient management.

What is DeepHealth doing this year at ECR?

It’s going to be a busy few days. We have our symposium entitled Radiologists and AI-powered Health Informatics: Leading the way in Screening in which Professor Marie Pierre-Revel from the University of Paris, France will present the CASCADE study. The study evaluated the effectiveness of various thoracic CT exam reading modalities in lung cancer, including the integration of AI. Additionally, Dr. Sam Hare, CEO of Heart Lung Health and a consultant radiologist at the Royal Free London NHS Foundation Trust, will discuss the outcomes of the lung screening program in the UK using DeepHealth’s AI. DeepHealth’s Saige Lung offers a suite of CE-marked solutions, harnessing AI to enhance lung nodule assessment and reporting.

In addition, I’m excited that Maurits Engbersen, Clinical Manager, DeepHealth will be presenting the results of an independent study that investigated the effect of CAD on agreements in incidental lung nodule management recommendations between the reporting radiologist and an expert peer reviewer.

And, of course, we have our interactive demonstrations of DeepHealth technology at our dedicated booth on the exhibition floor. So, we’re looking forward to demonstrating what the suite of DeepHealth products can do for our customers.

Tell us a little more about Saige Breast and the data being discussed at your symposium.

This new data, which has just been published in Radiology: Artificial Intelligence, demonstrates the power of our diagnostic tool, Saige Breast, to improve breast lesion detection in radiologists of all levels of expertise.1

In a nutshell, the data shows that every radiologist involved in the study improved their interpretation performance when using Saige Breast, but most importantly, general radiologists can achieve specialist-level performance when using the tool.

Saige Breast has been trained on over 10,000 scans and has now been employed in over a million mammograms. Over 400 cases of breast cancer lesions have been identified, and all ages and races have benefitted from cancer lesion detection.

I understand that you have a new partnership that is being announced at ECR.

That’s correct. In addition to our existing partnerships with eRAD BB, Bayer Calantic, and Cryanic, amongst others, we are excited to announce a new strategic partnership also with Incepto to expand access to AI-powered medical imaging across Europe.

Our partnerships cover areas such as distribution, marketing, servicing, sales, and deployment for DeepHealth technology, including its unique operating system and breast, lung, and prostate cancer tools, and leverage our partners’ expertise in localization, customization, and service.

Our new partnership will enable even more radiology teams across Europe to have access to our technology, including our lung cancer detection tool used in over 90% of screening sites in the UK’s Targeted Lung Health Checks (TLHC) program.

And what are your plans for the rest of the year?

We have a really busy year ahead of us. I’m looking forward to continue engaging with customers and partners at HIMSS in Florida in a few weeks. Watch this space!

DeepHealth presence at ECR:

  • The satellite symposium “Radiologists and AI-powered Health Informatics: Leading the Way in Screening” will take place on Thursday, February 29 from 9:30 to 10:30 CET in room ACV-M1. It will also be streamed live on ESR Connect.
  • The research presentation session “Pulmonary Nodules and Lung Cancer Screening” focused on chest will take place on Saturday, March 2 from 16:00 to 17:30 CET in room RPS 2014. Within the session, Maurits Engbersen, Clinical Manager, DeepHealth, will present the results of a study that investigated the effect of CAD on agreements in management recommendations between the reporting radiologist and an expert peer reviewer.
  • Interactive demonstrations of DeepHealth technology at a dedicated booth on the exhibition floor (Booth no. AI – 13 – Expo X1 – AI area) 

The comments and observations expressed are those of the author and do not necessarily reflect the opinions of AuntMinnie.com.

  1. Kim, Jiye G et al. Impact of a Categorical AI System for Digital Breast Tomosynthesis on Breast Cancer Interpretation by Both General Radiologists and Breast Imaging Specialists. Radiology: Artificial Intelligence. 2024. e230137

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