Apr 2, 2021 — 4 min read
As a medical AI company, we value in building clinical evidence. We have published lots of studies featuring the performance of our AI solutions in major peer-reviewed journals.
We have also been closely working with physicians and researchers around the world to conduct trials on the clinical outcomes of AI. These trials aim to assess the benefits of using it in real-world clinical settings and to gain insight into how it could be best adopted into routine practice.
Dr. Fredrik Strand, MD PhD, from the Karolinska University Hospital in Sweden, is one of the leading researchers who has demonstrated the potential value of AI in breast cancer screening.
In his recent retrospective study published in JAMA Oncology, he demonstrated that AI algorithms differed in performance to detect breast cancers on mammograms and that Lunit algorithm outperformed the others. He also showed that Lunit AI when combined with the first-reader radiologist detected more breast cancers in the double-reading environment.
Interview with Dr. Fredrik Strand, MD PhD, from the Karolinska University Hospital in Sweden
To evaluate the sufficient diagnostic performance of Lunit AI solution as an independent reader, Dr. Strand has set out a prospective clinical trial in a true screening population.
Below is an email interview with him that will give you a glimpse into his prospective research.
We’d like to hear about your prospective clinical trial that starts in March of 2021.
Dr. Strand: The program is called “ScreenTrust” and consists of two studies: “ScreenTrust CAD” and “ScreenTrust MRI”.
The first one, ScreenTrust CAD, is a clinical trial of AI as an independent reader of screening mammograms, aiming to examine to what extent AI can replace or assist radiologists in screening.
The second one, ScreenTrust MRI, is a clinical trial of AI as selection mechanism to invite women for supplemental MRI after a normal screening mammogram, aiming to examine to what extent AI together with MRI can help identify cancer that did not show up on mammography.
Is it going to be the first prospective study that evaluates the performance of an AI algorithm combined with radiologists in a true screening population?
Dr. Strand: As far as I know, both trials are the first clinical trials within full population-based study populations. However, I would expect that similar ones are being planned since AI seems to hold so much potential in this field.
What is the main difference between your research and other AI research?
Dr. Strand: We have a multidisciplinary group consisting of breast radiologists, biostatisticians and computer scientists. We combine networks that were academically developed with networks that were commercially developed.
The Swedish screening program is well-established and it is easy to follow the participants over time, thanks to regional and national registries. Our approach to clinical trials have a clear practical focus, since I am working part-time as a breast radiologist and part-time as a researcher.
Did you have any difficulty planning and preparing for the trial?
Dr. Strand: It took slightly longer than expected to get the two hospitals onboard, but everyone was very enthusiastic from the start.
Do you expect to get the results you are looking for? Are you confident in the performance of AI?
Dr. Strand: We have our beliefs based on retrospective studies, but in a prospective clinical setting, there is also important interaction between AI and humans that does not show up in retrospective studies.
I am confident that AI can play an important role, as there are now a large number of retrospective studies supporting that. However, I also think that the studies will show that there are still opportunities to improve the role of AI and how to combine AI with human assessments.
When are we going to be able to see your interim results?
Dr. Strand: It will probably take 1,5 to 2 years from the start (the CAD project expected to be slightly quicker than the MRI project), so that would mean sometime during 2023.
How would the results of your study be applied to the European breast screening environment?
Dr. Strand: We have to wait and analyse the results of course. If AI proves to work as expected, we could see a change from double-reading by human readers to the first combination of AI and one human reader, and later perhaps some cases can be read by AI alone.
Using AI to better manage COVID-19
Lunit to unveil data-driven imaging biomarker at RSNA 2016
Lunit INSIGHT: The First-ever, Real-time Imaging AI Analytics on the Web
Cognitive biases and augmented intelligence in radiology
Uncertainty and Deep Learning
Lunit Returns to RSNA with Real-time Imaging Platform, Featuring Cloud-based A
Lunit Unveils “Lunit INSIGHT,” A New Real-time Imaging AI Platform on the Web at RSNA 2017
Lunit INSIGHT: Q&A with Brandon B. Suh, Chief Medical Officer at Lunit
Lunit Opens “Lunit INSIGHT for Mammography” for Public Access
Lunit Brings its Newest AI Solution for Mammography to RSNA 2018
Lunit Partners with Fujifilm and Salud Digna to Provide Medical AI Solution in Mexico
Lunit announces new members in its advisory board: Dr. Eliot Siegel, Dr. Linda Moy, and Dr. Khan Siddiqui
Lunit to Showcase AI Solution for Breast Cancer at SBI 2019
Lunit Receives Korea MFDS Approval for its AI Solution for Breast Cancer, Lunit INSIGHT MMG
Lunit Gets Korea MFDS Approval for its AI Solution for Chest X-ray, Lunit INSIGHT CXR 2
Lunit at RSNA 2019
Lunit Announces its First CE Mark for AI-Powered Chest X-ray Analysis Software, Lunit INSIGHT CXR
Lunit AI software clinically installed in global sites—to be presented at RSNA 2019
AI-assisted Radiologists Can Detect More Breast Cancer with Reduced False-positive Recall
Lunit INSIGHT MMG, an AI Solution for Breast Cancer Detection, Now CE Certified
Lunit at ECR 2020: Providing Virtual Exhibition and Online Presentations
Emergent Connect Partners with Lunit to Provide Cloud Based AI Solutions
AI Analysis Can Improve Lung Cancer Detection on Chest Radiographs
AI has Added Value in Insurance Underwriting Process, Recent Pilot Project Between Lunit and Cathay Financial Innovation Lab Reveals
RSNA 2020--Lunit Collaborates with Global Giants in Presenting its AI Solution at Virtual Booths of GE Healthcare, FujiFilm, and Sectra
AI Proves Its Value in Assistance for Emergency Cases-- With Higher Accuracy and Timely Reporting Time of Chest Radiographs
Lunit Expands Collaboration with GE Healthcare to Advance AI Adoption across Healthcare Industry
AI Can Offer Fast and Reliable Examination to Triage COVID-19 Patients-- A Multicenter Retrospective Study Reveals
Recent Studies Reveal High Performance of Lunit AI in Breast Cancer Detection
South Korean Medical AI Provider and PACS Leader Enters Indonesian Market, to Help COVID-19 Screening and Diagnosis
What do medical studies say about AI for COVID-19 management?
What do the medical journals say about AI-powered mammography?
Research Using Lunit Demo Website
Lunit Presents AI-powered Pathologic Classification of Immune Phenotype that Predicts Response to Immunotherapy at USCAP 2021
What do the medical journals say about AI-powered chest x-ray interpretation?
Join our webinar with Dr. Fredrik Strand
AACR 2021 - Lunit Presents Abstracts Demonstrating the Potential of its AI Biomarker in Cancer Treatment