Background: Factors that can predict the presence and number of noncalcified coronary plaques (NCP) in Japanese patients with zero coronary artery calcium scores (CACS) essentially remain undefined. Methods and Result...Background: Factors that can predict the presence and number of noncalcified coronary plaques (NCP) in Japanese patients with zero coronary artery calcium scores (CACS) essentially remain undefined. Methods and Results: We assessed independent predictors of the presence and number of segments with NCP in 111 Japanese patients with zero CACS who underwent 64-slice multi-detector computed tomography at our hospital. Thirty five patients (32%) had NCP, and 24 patients (22%) had ≥ 2 NCPs. Multiple logistic regression analysis revealed that significant predictors for the presence of NCP were age (odds ratio [OR]: 1.06, 95% confidence interval [CI] 1.01 - 1.11, p = 0.021), male (OR: 3.61, 95% CI 1.40 - 9.35, p = 0.008) and diabetes mellitus (OR: 3.10, 95% CI 1.02 - 9.45, p = 0.046), and those for the presence of ≥ 2 NCPs were age (OR: 1.08, 95% CI 1.02 - 1.15, p = 0.007) and a current smoking habit (OR: 5.09, 95% CI 1.00 - 25.74, p = 0.049). Multiple linear regression analysis identified advanced age, male gender and diabetes mellitus as independent predictors of the number of NCPs. A novel score calculated from the above four predictors showed moderate accuracy for a diagnosis of NCP and ≥ 2 NCPs, with areas under receiver operating curves of 0.738 and 0.736, respectively. Conclusions: Male Japanese patients with zero CACS, advanced age, diabetes mellitus and a current smoking habit might have NCPs.展开更多
Corona Virus Disease 2019(COVID-19) has affected millions of people worldwide and caused more than6.3 million deaths(World Health Organization, June 2022). Increased attempts have been made to develop deep learning me...Corona Virus Disease 2019(COVID-19) has affected millions of people worldwide and caused more than6.3 million deaths(World Health Organization, June 2022). Increased attempts have been made to develop deep learning methods to diagnose COVID-19 based on computed tomography(CT) lung images. It is a challenge to reproduce and obtain the CT lung data, because it is not publicly available. This paper introduces a new generalized framework to segment and classify CT images and determine whether a patient is tested positive or negative for COVID-19 based on lung CT images. In this work, many different strategies are explored for the classification task.ResNet50 and VGG16 models are applied to classify CT lung images into COVID-19 positive or negative. Also,VGG16 and ReNet50 combined with U-Net, which is one of the most used architectures in deep learning for image segmentation, are employed to segment CT lung images before the classifying process to increase system performance. Moreover, the image size dependent normalization technique(ISDNT) and Wiener filter are utilized as the preprocessing techniques to enhance images and noise suppression. Additionally, transfer learning and data augmentation techniques are performed to solve the problem of COVID-19 CT lung images deficiency, therefore the over-fitting of deep models can be avoided. The proposed frameworks, which comprised of end-to-end, VGG16,ResNet50, and U-Net with VGG16 or ResNet50, are applied on the dataset that is sourced from COVID-19 lung CT images in Kaggle. The classification results show that using the preprocessed CT lung images as the input for U-Net hybrid with ResNet50 achieves the best performance. The proposed classification model achieves the 98.98%accuracy(ACC), 98.87% area under the ROC curve(AUC), 98.89% sensitivity(Se), 97.99 % precision(Pr), 97.88%F-score, and 1.8974-seconds computational time.展开更多
AIM to observe the effect of targeted therapy with 64-slice spiral computed tomography (CT) combined with cryoablation for liver cancer. METHODS A total of 124 patients ( 142 tumors) were enrolled into this study. Acc...AIM to observe the effect of targeted therapy with 64-slice spiral computed tomography (CT) combined with cryoablation for liver cancer. METHODS A total of 124 patients ( 142 tumors) were enrolled into this study. According to the use of dual-slice spiral CT or 64-slice spiral CT as a guide technology, patients were divided into two groups: dual-slice group (n = 56, 65 tumors) and 64-slice group (n = 8, 77 tumors). All patients were accepted and received targeted therapy by an argon-helium superconducting surgery system. The guided scan times of the two groups was recorded and compared. In the two groups, the lesion ice coverage in diameter of >= 3 cm and < 3 cm were recorded, and freezing effective rate was compared. Hepatic perfusion values [ hepatic artery perfusion (HAP), portal vein perfusion (PVP), and the hepatic arterial perfusion index (HAPI)] of tumor tissues, adjacent tissues and normal liver tissues at preoperative and postoperative four weeks in the two groups were compared. Local tumor changes were recorded and efficiency was compared at four weeks post-operation. Adverse events were recorded and compared between the two groups, including fever, pain, frostbite, nausea, vomiting, pleural effusion and abdominal bleeding. RESULTS Guided scan times in the dual-slice group was longer than that in the 64-slice group (t = 11.445, P = 0.000). The freezing effective rate for tumors < 3 cm in diameter in the dual-slice group (81.58%) was lower than that in the 64-slice group (92.86%) (chi(2) = 5.707, P = 0.017). The HAP and HAPI of tumor tissues were lower at four weeks post-treatment than at pretreatment in both groups (all P < 0.05), and those in the 64-slice group were lower than that in the dual-slice group ( all P < 0.05). HAP and PVP were lower and HAPI was higher in tumor adjacent tissues at post-treatment than at pre-treatment ( all P < 0.05). Furthermore, the treatment effect and therapeutic efficacy in the dual-slice group were lower than the 64-slice group at four weeks post-treatment (all P < 0.05). Moreover, pleural effusion and intraperitoneal hemorrhage occurred in patients in the dual-slice group, while no complications occurred in the 64-slice group (all P < 0.05). CONCLUSION 64-slice spiral CT applied with cryoablation in targeted therapy for liver cancer can achieve a safe and effective freezing treatment, so it is worth being used.展开更多
文摘Background: Factors that can predict the presence and number of noncalcified coronary plaques (NCP) in Japanese patients with zero coronary artery calcium scores (CACS) essentially remain undefined. Methods and Results: We assessed independent predictors of the presence and number of segments with NCP in 111 Japanese patients with zero CACS who underwent 64-slice multi-detector computed tomography at our hospital. Thirty five patients (32%) had NCP, and 24 patients (22%) had ≥ 2 NCPs. Multiple logistic regression analysis revealed that significant predictors for the presence of NCP were age (odds ratio [OR]: 1.06, 95% confidence interval [CI] 1.01 - 1.11, p = 0.021), male (OR: 3.61, 95% CI 1.40 - 9.35, p = 0.008) and diabetes mellitus (OR: 3.10, 95% CI 1.02 - 9.45, p = 0.046), and those for the presence of ≥ 2 NCPs were age (OR: 1.08, 95% CI 1.02 - 1.15, p = 0.007) and a current smoking habit (OR: 5.09, 95% CI 1.00 - 25.74, p = 0.049). Multiple linear regression analysis identified advanced age, male gender and diabetes mellitus as independent predictors of the number of NCPs. A novel score calculated from the above four predictors showed moderate accuracy for a diagnosis of NCP and ≥ 2 NCPs, with areas under receiver operating curves of 0.738 and 0.736, respectively. Conclusions: Male Japanese patients with zero CACS, advanced age, diabetes mellitus and a current smoking habit might have NCPs.
文摘Corona Virus Disease 2019(COVID-19) has affected millions of people worldwide and caused more than6.3 million deaths(World Health Organization, June 2022). Increased attempts have been made to develop deep learning methods to diagnose COVID-19 based on computed tomography(CT) lung images. It is a challenge to reproduce and obtain the CT lung data, because it is not publicly available. This paper introduces a new generalized framework to segment and classify CT images and determine whether a patient is tested positive or negative for COVID-19 based on lung CT images. In this work, many different strategies are explored for the classification task.ResNet50 and VGG16 models are applied to classify CT lung images into COVID-19 positive or negative. Also,VGG16 and ReNet50 combined with U-Net, which is one of the most used architectures in deep learning for image segmentation, are employed to segment CT lung images before the classifying process to increase system performance. Moreover, the image size dependent normalization technique(ISDNT) and Wiener filter are utilized as the preprocessing techniques to enhance images and noise suppression. Additionally, transfer learning and data augmentation techniques are performed to solve the problem of COVID-19 CT lung images deficiency, therefore the over-fitting of deep models can be avoided. The proposed frameworks, which comprised of end-to-end, VGG16,ResNet50, and U-Net with VGG16 or ResNet50, are applied on the dataset that is sourced from COVID-19 lung CT images in Kaggle. The classification results show that using the preprocessed CT lung images as the input for U-Net hybrid with ResNet50 achieves the best performance. The proposed classification model achieves the 98.98%accuracy(ACC), 98.87% area under the ROC curve(AUC), 98.89% sensitivity(Se), 97.99 % precision(Pr), 97.88%F-score, and 1.8974-seconds computational time.
基金Supported by Hebei Province Health Department of Scientific Research fund project,No.20110157
文摘AIM to observe the effect of targeted therapy with 64-slice spiral computed tomography (CT) combined with cryoablation for liver cancer. METHODS A total of 124 patients ( 142 tumors) were enrolled into this study. According to the use of dual-slice spiral CT or 64-slice spiral CT as a guide technology, patients were divided into two groups: dual-slice group (n = 56, 65 tumors) and 64-slice group (n = 8, 77 tumors). All patients were accepted and received targeted therapy by an argon-helium superconducting surgery system. The guided scan times of the two groups was recorded and compared. In the two groups, the lesion ice coverage in diameter of >= 3 cm and < 3 cm were recorded, and freezing effective rate was compared. Hepatic perfusion values [ hepatic artery perfusion (HAP), portal vein perfusion (PVP), and the hepatic arterial perfusion index (HAPI)] of tumor tissues, adjacent tissues and normal liver tissues at preoperative and postoperative four weeks in the two groups were compared. Local tumor changes were recorded and efficiency was compared at four weeks post-operation. Adverse events were recorded and compared between the two groups, including fever, pain, frostbite, nausea, vomiting, pleural effusion and abdominal bleeding. RESULTS Guided scan times in the dual-slice group was longer than that in the 64-slice group (t = 11.445, P = 0.000). The freezing effective rate for tumors < 3 cm in diameter in the dual-slice group (81.58%) was lower than that in the 64-slice group (92.86%) (chi(2) = 5.707, P = 0.017). The HAP and HAPI of tumor tissues were lower at four weeks post-treatment than at pretreatment in both groups (all P < 0.05), and those in the 64-slice group were lower than that in the dual-slice group ( all P < 0.05). HAP and PVP were lower and HAPI was higher in tumor adjacent tissues at post-treatment than at pre-treatment ( all P < 0.05). Furthermore, the treatment effect and therapeutic efficacy in the dual-slice group were lower than the 64-slice group at four weeks post-treatment (all P < 0.05). Moreover, pleural effusion and intraperitoneal hemorrhage occurred in patients in the dual-slice group, while no complications occurred in the 64-slice group (all P < 0.05). CONCLUSION 64-slice spiral CT applied with cryoablation in targeted therapy for liver cancer can achieve a safe and effective freezing treatment, so it is worth being used.
