Virtual non-contrast series of photon-counting detector computed tomography angiography for aortic valve calcium scoring.
Franka RischEva HarmelKatharina RippelBastian WeinPhilip W RaakeEvaldas GirdauskasSébastien ElvingerTamer OwaisChristian Scheurig-MuenklerThomas J KrönckeFlorian SchwarzFranziska BraunJosua A DeckerPublished in: The international journal of cardiovascular imaging (2024)
The aim of our study was to evaluate two different virtual non-contrast (VNC) algorithms applied to photon counting detector (PCD)-CT data in terms of noise, effectiveness of contrast media subtraction and aortic valve calcium (AVC) scoring compared to reference true non-contrast (TNC)-based results. Consecutive patients underwent TAVR planning examination comprising a TNC scan, followed by a CTA of the heart. VNC series were reconstructed using a conventional (VNC conv ) and a calcium-preserving (VNC pc ) algorithm. Noise was analyzed by means of the standard deviation of CT-values within the left ventricle. To assess the effectiveness of contrast media removal, heart volumes were segmented and the proportion of their histograms > 130HU was taken. AVC was measured by Agatston and volume score. 41 patients were included. Comparable noise levels to TNC were achieved with all VNC reconstructions. Contrast media was effectively virtually removed (proportions > 130HU from 81% to < 1%). Median calcium scores derived from VNC conv underestimated TNC-based scores (up to 74%). Results with smallest absolute difference to TNC were obtained with VNC pc reconstructions (0.4 mm, Br36, QIR 4), but with persistent significant underestimation (median 29%). Both VNC algorithms showed near-perfect (r²>0.9) correlation with TNC. Thin-slice VNC reconstructions provide equivalent noise levels to standard thick-slice TNC series and effective virtual removal of iodinated contrast. AVC scoring was feasible on both VNC series, showing near-perfect correlation, but with significant underestimation. VNC pc with 0.4 mm slices and Br36 kernel at QIR 4 gave the most comparable results and, with further advances, could be a promising replacement for additional TNC.
Keyphrases
- aortic valve
- image quality
- magnetic resonance
- contrast enhanced
- transcatheter aortic valve replacement
- aortic stenosis
- ejection fraction
- end stage renal disease
- computed tomography
- transcatheter aortic valve implantation
- machine learning
- aortic valve replacement
- air pollution
- magnetic resonance imaging
- dual energy
- randomized controlled trial
- chronic kidney disease
- newly diagnosed
- deep learning
- prognostic factors
- peritoneal dialysis
- pulmonary hypertension
- mitral valve
- atrial fibrillation
- coronary artery disease
- artificial intelligence
- monte carlo
- positron emission tomography
- big data