[Low-dose helical CT projection data restoration using noise estimation].

OBJECTIVE: To build a helical CT projection data restoration model at random low-dose levels. METHODS: We used a noise estimation module to achieve noise estimation and obtained a low-dose projection noise variance map, which was used to guide projection data recovery by the projection data restoration module. A filtering back-projection algorithm (FBP) was finally used to reconstruct the images. The 3D wavelet group residual dense network (3DWGRDN) was adopted to build the network architecture of the noise estimation and projection data restoration module using asymmetric loss and total variational regularization. For validation of the model, 1/10 and 1/15 of normal dose helical CT images were restored using the proposed model and 3 other restoration models (IRLNet, REDCNN and MWResNet), and the results were visually and quantitatively compared. RESULTS: Quantitative comparisons of the restored images showed that the proposed helical CT projection data restoration model increased the structural similarity index by 5.79% to 17.46% compared with the other restoration algorithms (P < 0.05). The image quality scores of the proposed method rated by clinical radiologists ranged from 7.19% to 17.38%, significantly higher than the other restoration algorithms (P < 0.05). CONCLUSION: The proposed method can effectively suppress noises and reduce artifacts in the projection data at different low-dose levels while preserving the integrity of the edges and fine details of the reconstructed CT images.

Low-dose helical CT projection data restoration using noise estimation / 南方医科大学学报

OBJECTIVE@#To build a helical CT projection data restoration model at random low-dose levels.@*METHODS@#We used a noise estimation module to achieve noise estimation and obtained a low-dose projection noise variance map, which was used to guide projection data recovery by the projection data restoration module. A filtering back-projection algorithm (FBP) was finally used to reconstruct the images. The 3D wavelet group residual dense network (3DWGRDN) was adopted to build the network architecture of the noise estimation and projection data restoration module using asymmetric loss and total variational regularization. For validation of the model, 1/10 and 1/15 of normal dose helical CT images were restored using the proposed model and 3 other restoration models (IRLNet, REDCNN and MWResNet), and the results were visually and quantitatively compared.@*RESULTS@#Quantitative comparisons of the restored images showed that the proposed helical CT projection data restoration model increased the structural similarity index by 5.79% to 17.46% compared with the other restoration algorithms (P < 0.05). The image quality scores of the proposed method rated by clinical radiologists ranged from 7.19% to 17.38%, significantly higher than the other restoration algorithms (P < 0.05).@*CONCLUSION@#The proposed method can effectively suppress noises and reduce artifacts in the projection data at different low-dose levels while preserving the integrity of the edges and fine details of the reconstructed CT images.

[Progress of Lung Cancer Screening with Low Dose Helical Computed Tomography].

Lung cancer which represents characteristics of a heavy disease burden, a large proportion of advanced lung cancer and a low five-year survival rate is a threat to human health. It is essential to implement population-based lung cancer screening to improve early detection and early treatment. The National Lung Screening Trial (NLST) demonstrated that screening with low dose helical computed tomography (LDCT) may decrease lung cancer mortality, which brings hope for the early diagnosis and treatment of lung cancer. In recent years, great progresses have been made on research of lung cancer screening with LDCT. However, whether LDCT could be applied to large population-based lung cancer screening projects is still under debate. In this paper, we review the recent progresses on history of lung cancer screening with LDCT, selection of high-risk individuals, management of pulmonary nodules, performance of screening, acceptance of LDCT and cost-effectiveness.
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Initial Results from Mobile Low-Dose Computerized Tomographic Lung Cancer Screening Unit: Improved Outcomes for Underserved Populations.

INTRODUCTION: The National Lung Screening Trial (NLST) demonstrated that screening high-risk patients with low-dose computed tomography (CT) of the chest reduces lung cancer mortality compared with screening with chest x-ray. Uninsured and Medicaid patients usually lack access to this hospital-based screening test because of geographic and socioeconomic factors. We hypothesized that a mobile screening unit would improve access and confer the benefits demonstrated by the NLST to this underserved group, which is most at risk of lung cancer deaths. PATIENTS AND METHODS: We created a mobile unit by building a Samsung BodyTom portable 32-slice low-dose CT scanner into a 35-foot coach; it delivers high-quality images for both soft tissue and bone and includes a waiting area and high-speed wireless internet connection for fast image transfer. The unit was extensively tested to show robustness and stability of mobile equipment. This project was designed to screen uninsured and underinsured patients, otherwise with eligibility criteria identical to that of the National Lung Screening Trial, with the only difference being exclusion of patients eligible for Medicare (which provides financial coverage for CT-based lung cancer screening). RESULTS: We screened 550 patients (20% black, 3% Hispanic, 70% rural) with a male-to-female ratio of 1.1:1, median age 61 years (range, 55-64), and found 12 lung cancers at initial screen (2.2%), including 6 at stage I-II (58% of total lung cancers early stage) and 38 Lung-RADS 4 (highly suspicious) lesions that are being followed closely. Incidental findings included nonlung cancers and coronary artery disease. DISCUSSION: In this initial pilot study, using the first mobile low-dose whole body CT screening unit in the U.S., the initial cancer detection rate is comparable to that reported in the NLST, despite excluding patients over the age of 64 years who have Medicare coverage, but with marked improvement of screening rates specifically in underserved sociodemographic, racial, and ethnic groups and with better outcomes than conventionally found in the underserved and at lower cost per case. IMPLICATIONS FOR PRACTICE: This study shows clearly that a mobile low-dose CT scanning unit allows effective lung cancer screening for underserved populations, such as impoverished African Americans, Hispanics, Native Americans, or isolated rural groups, and has a pick-up rate of 1% for early stage disease. If confirmed in a planned randomized trial, this will be policy changing, as these groups usually present with advanced disease; this approach will produce better survival data at lower cost per case.

Progress of Lung Cancer Screening with Low Dose Helical Computed Tomography / 中国肺癌杂志

Lung cancer which represents characteristics of a heavy disease burden, a large proportion of advanced lung cancer and a low five-year survival rate is a threat to human health. It is essential to implement population-based lung cancer screening to improve early detection and early treatment. The National Lung Screening Trial (NLST) demonstrated that screening with low dose helical computed tomography (LDCT) may decrease lung cancer mortality, which brings hope for the early diagnosis and treatment of lung cancer. In recent years, great progresses have been made on research of lung cancer screening with LDCT. However, whether LDCT could be applied to large population-based lung cancer screening projects is still under debate. In this paper, we review the recent progresses on history of lung cancer screening with LDCT, selection of high-risk individuals, management of pulmonary nodules, performance of screening, acceptance of LDCT and cost-effectiveness.
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From focal pulmonary pure ground-glass opacity nodule detected by low-dose computed tomography into invasive lung adenocarcinoma: A growth pattern analysis in the elderly.

BACKGROUND: Elderly patients are under-represented in studies of pure ground-glass opacity (pGGO) nodules; thus, this study analyzed the growth pattern and clinical outcomes of pGGO nodules in the elderly in order to help make treatment decisions. METHODS: We retrospectively reviewed patients aged over 60 years with screening-detected and pathologically confirmed growing focal pGGO nodules. RESULTS: During the study period, 858 subjects had undergone at least three low-dose computed tomography scans in our center. Twenty patients were treated for growing focal pGGO nodules. The median age at detection was 66 years (range: 60-80). The median time to an increase of at least 2 mm was 348 days (range: 98-1527) and to develop a solid portion, 1141 days (range: 480-3010). Seven patients had surgery for increased nodule size, four had surgery immediately after the solid portion appeared, and nine were treated after a median follow-up of 1153 days (range: 240-2342) since the solid portion developed. The median size of the solid component was 8 mm (2-13) before surgery. No recurrence was observed after a median follow-up of 41 months. Pathology revealed adenocarcinoma in situ in five patients, and minimally invasive or invasive adenocarcinoma in the remainder. The appearance of a solid portion was significantly associated with invasive adenocarcinoma compared to increased size alone (100% vs. 44.4%; P = 0.005). CONCLUSIONS: pGGO nodules had an indolent growth pattern and good prognosis in our patient sample, even after the appearance of a solid portion. Therefore, minimally invasive surgery after the development of a solid component may be an option for the elderly.

The Case for Lung Cancer Screening: What Nurses Need to Know.

BACKGROUND: Lung cancer screening with low-dose helical computed tomography (LDCT) can improve high-risk individuals' chances of being diagnosed at an earlier stage and increase survival. OBJECTIVES: The aims of this article are to present the risk factors associated with the development of lung cancer, identify patients at high risk for lung cancer qualifying for LDCT screening, and understand the importance of early lung cancer detection through the use of LDCT screening. METHODS: PubMed and CINAHL® databases were searched with key words lung cancer screening to identify full-text academic articles from 2004-2014. This resulted in 529 articles from PubMed and 195 from CINAHL. PubMed offered suggestions for additional relevant journal articles. The National Comprehensive Cancer Network guidelines also provided substantial evidence-based information. FINDINGS: Nurses need to provide support, education, and resources for patients undergoing lung cancer screening.