Image restoration of motion artifacts in cardiac arteries and vessels based on a generative adversarial network.

Background: When the heart rate of a patient exceeds the physical limits of a scanning device, even retrospective electrocardiography (ECG) gating technology cannot correct motion artifacts. The purpose of this study was to use deep learning methods to correct motion artifacts in coronary computed tomography angiography (CCTA) images acquired with retrospective ECG gating. Methods: To correct motion artifacts in CCTA images, we used a cycle Wasserstein generative adversarial network with a gradient penalty (WGAN-GP) to synthesize CCTA images without motion artifacts, and applied objective image indicators and clinical quantitative scores to evaluate the images. The objective image indicators included peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and normalized mean square error (NMSE). For clinical quantitative scoring, we randomly selected 50 sets of images from the test data set as the scoring data set. We invited 2 radiologists from Zhongnan Hospital of Wuhan University to score the composite images. Results: In the test images, the PSNR, SSIM, NMSE and clinical quantitative score were 24.96±1.54, 0.769±0.055, 0.031±0.023, and 4.12±0.61, respectively. The images synthesized by cycle WGAN-GP performed better on objective image indicators and clinical quantitative scores than those synthesized by cycle least squares generative adversarial network (LSGAN), UNet, WGAN, and cycle WGAN. Conclusions: Our proposed method can effectively correct the motion artifacts of coronary arteries in CCTA images and performs better than other methods. According to the performance of the clinical score, correction of images by this method does not affect the clinical diagnosis.

Classification and quantification of double superior vena cava evaluated by computed tomography imaging.

BACKGROUND: A double superior vena cava (DSVC) may cause technical difficulties in some cardiovascular procedures. However, no quantitative data exist to describe the morphological features of this anomaly. METHODS: From January 2015 to January 2019, the data of 128 consecutive patients diagnosed with DSVC on computed tomography (CT) images were retrospectively analyzed. We proposed an easy and rational method for DSVC classification based on the presence or absence of the left brachiocephalic vein (LBCV), the presence or absence of an anastomotic vein bridging the bilateral superior vena cava (SVC), and the drainage pattern of the left superior vena cava (LSVC). The following classifications were established: type I, LBVC absent, LSVC drainage into the right atrium via the coronary sinus; type II, LBCV present, LSVC drainage into the right atrium via the coronary sinus; type III, LBCV absent, LSVC drainage into the right atrium via the anastomosis; type IV, LBCV present, LSVC drainage into the right atrium via the anastomosis. The length, diameter, and area of the bilateral SVC and the coronary sinus were carefully measured across the 4 types. RESULTS: Type I was the most frequently occurring type (66 of 128, 51.6%), followed by type II (43 of 128, 33.6%), then type III (15 of 128, 11.7%), and type IV (4 of 128, 3.1%). The LSVC was significantly longer than the right SVC (RSVC) in all 4 types, and the diameters of the LSVC were significantly larger in types without the LBCV (i.e., types I and III) (P<0.0001 for all). Additionally, the diameter of the coronary sinus in types I and II was triple that in types III and IV (P<0.0001), which was thought to be due to increased venous blood reflux through the coronary sinus. CONCLUSIONS: The anatomical features of DSVC can be satisfactorily depicted on CT. The quantitative measurement of this anomaly by the reporting radiologists could assist clinicians to minimize the procedure-associated risks.

Assessing patent foramen ovale on coronary computed tomographic angiography: a comparison with transesophageal echocardiography.

PURPOSE: This study was undertaken to determine if coronary computed tomographic angiography (CCTA) can help to assess patent foramen ovale (PFO) with high accuracy and reproducibility when compared to transesophageal echocardiography (TEE). MATERIALS AND METHODS: In total, 75 suspected PFO cases (31 men, 44 women; mean age, 45 ± 9 years) were evaluated by coronary CTA and TEE. PFO tunnel length (TL) and the opening diameter of the left atrial entrance (ODLAE) and right atrial entrance (ODRAE), as well as contrast shunt (if present due to PFO), were measured by both modalities. RESULTS: PFO was detected in 68 patients with TEE. The sensitivity for the detection of PFO with CCTA was 85.3%; specificity, 71.4%; positive predictive value, 96.7%; and negative predictive value, 33.3%. Both modalities demonstrated good agreement in measuring TL and ODLAE of PFO. However, the ODRAE of TEE was different from that of CCTA (1.14 ± 0.4 mm and 1.45 ± 0.5 mm, respectively, p = 0.04). The intra-observer and inter-observer variability and agreement for TL, ODRAE, and ODLAE of PFO were excellent between the two measurements. CONCLUSION: CCTA provided a method for detection of PFO with high accuracy and reproducibility compared with TEE. Therefore, CCTA is a practical and efficient alternative to TEE for PFO diagnosis.

Correcting motion artifacts in coronary computed tomography angiography images using a dual-zone cycle generative adversarial network.

BACKGROUND: Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality to detect and diagnose coronary artery disease. Due to the limitations of equipment and the patient's physiological condition, some CCTA images collected by 64-slice spiral computed tomography (CT) have motion artifacts in the right coronary artery, left circumflex coronary artery and other positions. OBJECTIVE: To perform coronary artery motion artifact correction on clinical CCTA images collected by Siemens 64-slice spiral CT and evaluate the artifact correction method. METHODS: We propose a novel method based on the generative adversarial network (GAN) to correct artifacts of CCTA clinical images. We use CCTA clinical images collected by 64-slice spiral CT as the original dataset. Pairs of regions of interest (ROIs) cropped from original dataset or images with and without motion artifacts are used to train the dual-zone GAN. When predicting the CCTA images, the network inputs only the clinical images with motion artifacts. RESULTS: Experiments show that this network effectively corrects CCTA motion artifacts. Regardless of ROIs or images, the peak signal to noise ratio (PSNR), structural similarity (SSIM), mean square error (MSE) and mean absolute error (MAE) of the generated images are greatly improved compared to those of the input data. In addition, based on scores from physicians, the average score for the coronary artery artifact correction of the output images is higher. CONCLUSIONS: This study demonstrates that the dual-zone GAN has the excellent ability to correct motion artifacts in the coronary arteries and maintain the overall characteristics of CCTA clinical images.

CT features of coronavirus disease 2019 (COVID-19) in the original district of this disease (Wuhan): a pictorial review.

On December 31, 2019, the Wuhan Health Commission reported the discovery of an "unexplained" pneumonia for the first time; the pathogen was confirmed as novel coronavirus pneumonia (2019-nCoV) on January 7, 2020. As one of the important examination methods for the Corona Virus Disease 2019 (COVID-19), Computed Tomography (CT) examination plays an important role in the clinical discovery of suspected cases, diagnosis, and treatment review. This paper reviews the published papers in order to offer help in early clinical screening, disease diagnosis, disease severity determination and post-treatment review.

A fatal outcome from SARS-CoV-2 infection: One case report of a young man with multiple organ damage.

The coronavirus disease 2019 (COVID-19) first emerged in Wuhan, China on December 2019 and has become a severe public health issue worldwide. A 36-year-old man was presented to the hospital staff with a fever that had already persisted for a three-day period, general weakness and diarrhea. He had no chronic diseases and was tested positive for COVID-19 with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid. During his hospitalization, several abnormal indicators appeared in his laboratory tests, which implied systemic inflammation and multiple organ damage. A series of chest radiographs monitored the dynamic process of lung lesions, which could predict the clinical changes of the patient. His condition deteriorated rapidly, resulting in death due to acute respiratory distress syndrome (ARDS) on hospital day 13. The case indicates that inflammatory response may appear in people infected with SARS-CoV-2 and may lead to multiple organ damage (especially pancreatic damage). When a COVID-19 patient is entering into the critical stage, their condition could rapidly deteriorate.

The Endophytic Fungus Phomopsis liquidambari Increases Nodulation and N2 Fixation in Arachis hypogaea by Enhancing Hydrogen Peroxide and Nitric Oxide Signalling.

The continuous cropping obstacles in monoculture fields are a major production constraint for peanuts. Application of the endophytic fungus Phomopsis liquidambari has increased peanut yields, and nodulation and N2 fixation increases have been considered as important factors for P. liquidambari infection-improved peanut yield. However, the mechanisms involved in this process remain unknown. This work showed that compared with only Bradyrhizobium inoculation, co-inoculation with P. liquidambari significantly elevated endogenous H2O2 and NO levels in peanut roots. Pre-treatment of seedlings with specific scavengers of H2O2 (CAT) and NO (cPTIO) blocked P. liquidambari-induced nodulation and N2 fixation. CAT not only suppressed the P. liquidambari-induced nodulation and N2 fixation, but also suppressed the enhanced H2O2 and NO generation. Nevertheless, the cPTIO did not significantly inhibit the induced H2O2 biosynthesis, implying that H2O2 acted upstream of NO production. These results were confirmed by observations that exogenous H2O2 and sodium nitroprusside (SNP) reversed the inhibition of P. liquidambari-increased nodulation and N2 fixation by the specific scavengers. The transcriptional activities of the symbiosis-related genes SymRK and CCaMK of peanut-Bradyrhizobium interactions also increased significantly in response to P. liquidambari, H2O2 and SNP treatments. The pot experiment further confirmed that the P. liquidambari infection-enhanced H2O2 and NO signalling pathways were significantly related to the increase in peanut nodulation and N2 fixation. This is the first report that endophytic fungus P. liquidambari can increase peanut-Bradyrhizobium interactions via enhanced H2O2/NO-dependent signalling crosstalk, which is conducive to the alleviation of continuous cropping obstacles via an increase in nodulation and N2 fixation.