4 research outputs found
Generative adversarial networks improve interior computed tomography angiography reconstruction
Abstract
In interior computed tomography (CT), the x-ray beam is collimated to a limited field-of-view (FOV) (e.g. the volume of the heart) to decrease exposure to adjacent organs, but the resulting image has a severe truncation artifact when reconstructed with traditional filtered back-projection (FBP) type algorithms. In some examinations, such as cardiac or dentomaxillofacial imaging, interior CT could be used to achieve further dose reductions. In this work, we describe a deep learning (DL) method to obtain artifact-free images from interior CT angiography. Our method employs the Pix2Pix generative adversarial network (GAN) in a two-stage process: (1) An extended sinogram is computed from a truncated sinogram with one GAN model, and (2) the FBP reconstruction obtained from that extended sinogram is used as an input to another GAN model that improves the quality of the interior reconstruction. Our double GAN (DGAN) model was trained with 10 000 truncated sinograms simulated from real computed tomography angiography slice images. Truncated sinograms (input) were used with original slice images (target) in training to yield an improved reconstruction (output). DGAN performance was compared with the adaptive de-truncation method, total variation regularization, and two reference DL methods: FBPConvNet, and U-Net-based sinogram extension (ES-UNet). Our DGAN method and ES-UNet yielded the best root-mean-squared error (RMSE) (0.03 ± 0.01), and structural similarity index (SSIM) (0.92 ± 0.02) values, and reference DL methods also yielded good results. Furthermore, we performed an extended FOV analysis by increasing the reconstruction area by 10% and 20%. In both cases, the DGAN approach yielded best results at RMSE (0.03 ± 0.01 and 0.04 ± 0.01 for the 10% and 20% cases, respectively), peak signal-to-noise ratio (PSNR) (30.5 ± 2.6 dB and 28.6 ± 2.6 dB), and SSIM (0.90 ± 0.02 and 0.87 ± 0.02). In conclusion, our method was able to not only reconstruct the interior region with improved image quality, but also extend the reconstructed FOV by 20%
Plaque histology and myocardial disease in sudden coronary death:the Fingesture study
Abstract
Aims: At least 50% of deaths due to coronary artery disease (CAD) are sudden cardiac deaths (SCDs), but the role of acute plaque complications on the incidence of sudden death in CAD is somewhat unclear. The present study aimed to investigate plaque histology and concomitant myocardial disease in sudden coronary death.
Methods and results: The study population is derived from the Fingesture study, which has collected data from 5869 consecutive autopsy-verified SCD victims in Northern Finland (population ≈600 000) between 1998 and 2017. In this substudy, histological examination of culprit lesions was performed in 600 SCD victims whose death was due to CAD. Determination of the cause of death was based on the combination of medical records, police reports, and autopsy data. Plaque histology was classified as either (i) plaque rupture or erosion, (ii) intraplaque haemorrhage, or (iii) stable plaque. The mean age of the study subjects was 64.9 ± 11.2 years, and 82% were male. Twenty-four per cent had plaque rupture or plaque erosion, 24% had an intraplaque haemorrhage, and 52% had a stable plaque. Myocardial hypertrophy was present in 78% and myocardial fibrosis in 93% of victims. The presence of myocardial hypertrophy or fibrosis was not associated with specific plaque histology.
Conclusions: Less than half of sudden deaths due to CAD had evidence of acute plaque complication, an observation which is contrary to historical perceptions. The prevalence of concomitant myocardial disease was high and independent of associated plaque morphology
Heme oxygenase-1 repeat polymorphism in septic acute kidney injury
Abstract
Acute kidney injury (AKI) is a syndrome that frequently affects the critically ill. Recently, an increased number of dinucleotide repeats in the HMOX1 gene were reported to associate with development of AKI in cardiac surgery. We aimed to test the replicability of this finding in a Finnish cohort of critically ill septic patients. This multicenter study was part of the national FINNAKI study. We genotyped 300 patients with severe AKI (KDIGO 2 or 3) and 353 controls without AKI (KDIGO 0) for the guanine–thymine (GTn) repeat in the promoter region of the HMOX1 gene. The allele calling was based on the number of repeats, the cut off being 27 repeats in the S–L (short to long) classification, and 27 and 34 repeats for the S–M–L₂ (short to medium to very long) classification. The plasma concentrations of heme oxygenase-1 (HO-1) enzyme were measured on admission. The allele distribution in our patients was similar to that published previously, with peaks at 23 and 30 repeats. The S-allele increases AKI risk. An adjusted OR was 1.30 for each S-allele in an additive genetic model (95% CI 1.01–1.66; p = 0.041). Alleles with a repeat number greater than 34 were significantly associated with lower HO-1 concentration (p<0.001). In septic patients, we report an association between a short repeat in HMOX1 and AKI risk