Radiomics – seeing deeper into CCT plaque? Radiomics-based precision phenotyping of coronary plaque morphology improved prediction (c-statistic 0.7 to 0.74) of #cvMI by #YesCCT over & above clinical factors & plaque burden in the SCOT-HEART trial. jacc.org/doi/10.1016/j.jcmg.…#JACCIMG
Dr Andrew Lin (@DrAndrewLin) from @MonashUni showing that inflammation inhibits local adipogenesis in pericoronary adipose tissue (PCAT) and this can be detected by AI-driven🤖algorithms on #YesCCT as an increase in CT attenuation of PCAT which improves prognosis #SCCT2023
Our paper now out in @CircImaging. Machine learning integration of quantitative plaque features from #YesCCT predicts ischemia by invasive FFR and ⬇️myocardial blood flow by PET. A multicenter collaboration with data from NXT & PACIFIC trials.
@damini_dey@Doc_Tiger@Heart_SCCT
Delighted to receive Postdoctoral Fellowship funding. Thanks to @heartfoundation for supporting our research using coronary CT and AI to better understand the effects of statins on plaques.
@MonashUni @VicHeartInst @ProfSNicholls
We're excited to announce our 2022 research funding portfolio! The Heart Foundation will be supporting 59 research projects, investing a total of $13.25 million into fighting the no.1 cause of death in Australia - heart disease. Read more about the projects and recipients 👇
Key message from #SCCT2022: Substantial growth of Cardiac CT around the globe!
Fueled by innovations, scientific data, guidelines, and more...
👇trends in England, publications, @Heart_SCCT membership
After a very successful first volume, with @damini_dey and @DrAndrewLin we are inviting everyone to consider submitting their radiomic research in CVD to @FrontCVMedicine 🧪♥️🩺(IF: 6.050)
Delighted to place 2nd in YIA Clinical Investigations at #ACC22. Congratulations to all awardees on the outstanding science & innovation @ACCinTouch
Thank you @damini_dey for the mentorship and our superb team @nipunmanral@Piotr_JSlomka @MarcDweck @imagingmedsci @ProfSNicholls
Our work on an AI system for rapid plaque measurements and stenosis estimation from coronary CTA, with prognostic value and potential for future workflow implementation now published:
thelancet.com/journals/landi…
An AI-based tool can rapidly and accurately measure plaque volume and stenosis severity from coronary CTA images in patients w/ stable chest pain, according to new data. It also has the potential to better predict future MIs.
tctmd.com/news/deep-learning…@damini_dey@toddvillinesmd