Interventional device developer Medtronic has received the CE Mark for its cardiac resynchronization therapy defibrillators for 3-tesla MRI scans.
The full line of defibrillators -- also labeled for 1.5-tesla scanners -- is now available in Europe to help treat heart failure and reduce the risk of sudden cardiac arrest in patients with Claria MRI Quad CRT-D SureScan, Amplia MRI Quad CRT-D SureScan, and Compia MRI Quad CRT-D SureScan systems. All three defibrillators are approved for MRI scans without positioning restrictions. The Claria defibrillator is not approved for sale in the U.S.
The Claria MRI CRT-D features the EffectivCRT Diagnostic and the EffectivCRT during atrial fibrillation (AF) algorithm, which automatically adjusts pacing rates -- without adversely affecting the average heart rate -- to tailor the therapy to individual patients.
The Claria MRI and Amplia MRI CRT-Ds also feature the Medtronic-exclusive AdaptivCRT algorithm, which improves cardiac resynchronization therapy response rate and reduces risk of atrial fibrillation. They also enable multiple point pacing, which can stimulate two sites on the left ventricle (lower chamber) simultaneously.
Additional features available in all three devices include the following:
- Attain Perfoma MRI SureScan quadripolar leads: Attain Perfoma left ventricular leads include short bipolar spacing to reduce phrenic nerve stimulation occurrence; steroid on all electrodes; and three shapes for varying patient anatomies.
- VectorExpress technology: An automated in-office test that reduces lead programing to two minutes and reveals clinically actionable information to help physicians select optimal pacing configurations for each patient.
In addition to the full line of cardiac resynchronization therapy defibrillators, Medtronic MR-conditional cardiac rhythm and heart failure devices and leads previously approved for 1.5 tesla are now approved for full-body scans in both 1.5- and 3-tesla MRI systems in Europe. These include Advisa MRI and Ensura MRI pacemakers, Micra transcatheter pacing system, Reveal XT and Reveal LINQ insertable cardiac monitors, and Evera MRI and Visia AF MRI implantable cardioverter defibrillators.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
