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In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Noise reduction and motion elimination in low-dose 4D myocardial computed tomography perfusion (CTP): preliminary
Steffen Lukas1, Sarah Feger1, Matthias Rief1
1Department of Radiology, Charité Medical School, Charitéplatz 1, 10117, Berlin, Germany.
Insights
The novel ASTRA4D algorithm significantly reduces noise and improves image quality in four-dimensional computed tomography perfusion (4D CTP) for better detection of myocardial ischemia.
Area of Science:
- Medical Imaging
- Cardiovascular Imaging
- Image Processing
Background:
- Dynamic contrast-enhanced computed tomography perfusion (CTP) is crucial for diagnosing coronary artery disease.
- Low-dose CTP is challenged by motion artifacts and spatiotemporal noise, impacting diagnostic accuracy.
- Existing methods struggle to effectively address both motion and noise simultaneously.
Purpose of the Study:
- To introduce and validate a novel four-dimensional (4D) algorithm, ASTRA4D, for simultaneous motion elimination and noise reduction in low-dose myocardial CTP.
- To enhance the spatiotemporal resolution and image quality of dynamic CTP sequences.
- To improve the sensitivity and specificity of detecting myocardial perfusion deficits.
Main Methods:
- A new deformable image registration method, ASTRA4D, was developed using principal component analysis (PCA) of temporally smoothed time-attenuation curves.
- The algorithm was applied to dynamic contrast-enhanced 320-row CTP data from 30 patients with suspected coronary artery disease.
- Quantitative (noise, SNR, deformation) and qualitative (motion, contrast, sharpness) metrics were assessed and compared to a benchmark PCA method.
- Diagnostic accuracy for myocardial perfusion deficits was evaluated against magnetic resonance myocardial perfusion imaging (MR-MPI).
Main Results:
- ASTRA4D successfully registered images in all patients, significantly reducing temporal noise by 83% and spatial noise by 34% compared to PCA.
- Signal-to-noise ratio (SNR) improved by 47%, and subjective image quality scores for motion, contrast, and sharpness were significantly enhanced.
- Per-segment sensitivity for detecting perfusion deficits increased to 91% with ASTRA4D, compared to 52% with PCA (p < 0.001).
- Specificity remained high at 96% for ASTRA4D versus 98% for PCA.
Conclusions:
- The ASTRA4D algorithm effectively eliminates motion artifacts and reduces spatiotemporal noise in low-dose 4D CTP.
- ASTRA4D significantly improves CTP image quality and enhances the detection of myocardial ischemia.
- The algorithm demonstrates excellent concordance with MRI for identifying perfusion deficits, improving diagnostic confidence.
Objectives:
To propose and evaluate a four-dimensional (4D) algorithm for joint motion elimination and spatiotemporal noise reduction in low-dose dynamic myocardial computed tomography perfusion (CTP).
Methods:
Thirty patients with suspected or confirmed coronary artery disease were prospectively included and underwent dynamic contrast-enhanced 320-row CTP. A novel deformable image registration method based on the principal component analysis (PCA) of the ante hoc temporally smoothed voxel-wise time-attenuation curves (ASTRA4D) is presented. Quantitative (standard deviation, signal-to-noise ratio (SNR), temporal variation, volumetric deformation) and qualitative (motion, contrast, contour sharpness [1, poor; 5, excellent]) measures of CTP quality were assessed for the original and motion-compensated sequences (without and with temporal filtering, PCA/ASTRA4D). Following myocardial perfusion deficit detection by two readers, diagnostic accuracy was evaluated using magnetic resonance myocardial perfusion imaging (MR-MPI) as the reference standard in 15 patients.
Results:
Registration using ASTRA4D was successful in all 30 patients and resulted in comparison with the benchmark PCA in significantly (p < 0.001) reduced noise over time (- 83%, 178.5 vs 29.9) and spatially (- 34%, 21.4 vs 14.1) as well as improved SNR (+ 47%, 3.6 vs 5.3) and subjective image quality (motion, contrast, contour sharpness [+ 1.0, + 1.0, + 0.5]). ASTRA4D had significantly improved per-segment sensitivity of 91% (58/64) and similar specificity of 96% (429/446) compared with PCA (52%, 33/64; 98%, 435/446; p = 0.011) in the visual detection of perfusion deficits.
Conclusions:
The ASTRA4D registration algorithm improved the spatiotemporal noise profile and CTP sequence image quality, resulting in significantly improved sensitivity of 4D CTP in the detection of myocardial ischemia.
Key Points:
• ASTRA4D combines local temporal regression and deformable image registration. • Quantitative and qualitative measures of CTP quality are improved compared to PCA. • Improved spatiotemporal differentiation of ischemic regions leads to an excellent perfusion deficit concordance of ASTRA4D with MRI.
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