The insufficiency of CT examination in early detection of central lung squamous cell carcinoma and squamous epithelial precancerous lesions

Abstract Background CT examination for lung cancer has been carried out for more than 20 years and great achievements have been made in the early detection of lung cancer. However, in the clinical work, a large number of advanced central lung squamous cell carcinoma are still detected through bronchoscopy. Meanwhile, a part of CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions are also accidentally detected through bronchoscopy. Methods This study retrospectively collects the medical records of patients in the bronchoscopy room of the Endoscopy Department of Zhejiang Cancer Hospital from January 2014 to December 2018. The inclusion criteria for patients includes: 1.Patient medical records completed, 2.Without history of lung cancer before the diagnosis and first pathological diagnosis of primary lung cancer, 3.Have the lung CT data of the same period, 4.Have the bronchoscopy records and related pathological diagnosis, 5.The patients undergoing radical surgical treatment must have a complete postoperative pathological diagnosis. Finally, a total of 10,851 patients with primary lung cancer are included in the study, including 7175 males and 3676 females, aged 22–98 years. Firstly, 130 patients with CT-occult lesions are extracted and their clinical features are analyzed. Then, 604 cases of single central squamous cell carcinoma and 3569 cases of peripheral adenocarcinoma are extracted and compares in postoperative tumor diameter and lymph node metastasis. Results 115 cases of CT-occult central lung squamous cell carcinoma and 15 cases of squamous epithelial precancerous lesions are found. In the total lung cancer, the proportion of CT-occult lesions is 130/10,851 (1.20%). Meanwhile, all these patients are middle-aged and elderly men with a history of heavy smoking. There are statistically significant differences in postoperative median tumor diameter (3.65 cm vs.1.70 cm, P < 0.0001) and lymph node metastasis rate (50.99% vs.13.06%, P < 0.0001) between 604 patients with operable single central lung squamous cell carcinoma and 3569 patients with operable peripheral lung adenocarcinoma. Of the 604 patients with squamous cell carcinoma, 96.52% (583/604) are male with a history of heavy smoking and aged 40–82 years with a median age of 64 years. Conclusions This study indicates that the current lung CT examination of lung cancer is indeed insufficiency for the early diagnosis of central squamous cell carcinoma and squamous epithelial precancerous lesions. Further bronchoscopy in middle-aged and elderly men with a history of heavy smoking can make up for the lack of routine lung CT examination

The predictive value of the change of the number of pixels under different CT value intervals in the CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions

Abstract Background Due to the fact that the CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions. (CT-occult CLSCC and SEPL) cannot be detected by lung CT screening, early and timely diagnosis of central lung cancer becomes very difficult, which directly affects the prognosis of patients. Methods We retrospectively review medical records of patients at the Zhejiang Cancer Hospital and enrolled 41 patients with the CT-occult CLSCC and SEPL and 48 patients without the CT-occult CLSCC and SEPL. We compare the clinical characteristics, imaging features and Changes in the number of pixels under different CT value intervals of patients with and without the CT-occult CLSCC and SEPL and we perform univariate and multivariate logistic regression analysis to explore independent factors for the CT-occult CLSCC and SEPL in the patients. Results We demonstrate that pack-years ≥ 20 (OR: 3.848, 95% CI: 1.086 ~ 13.633), the number of pixels change of CT value in interval [-850 ~ -750HU] (OR: 5.302, 95% CI: 1.122 ~ 25.057) and in interval [-900 ~ -850HU] (OR: 3.478, 95% CI: 1.167 ~ 10.365) are independently associated with the CT-occult CLSCC and SEPL in the patients. Ultimately, the logistic model obtained is statistically significant (p < 0.05) and an area under the ROC curve is 0.776 (95% CI: 0.682–0.870). The sensitivity of this model is 90.2% and the specificity is 52.1%. Conclusion The results of this study indicate that in the CT value range [-950 ~ -750HU], when the total number of lung pixels tend to increase towards the region with high CT value, the probability of the occurrence of CT-occult CLSCC and SEPL lesions also increases. Meanwhile, these results have guiding significance for the further study of radiomic

A Data Correction Algorithm for Low-Frequency Floating Car Data

The data collected by floating cars is an important source for lane-level map production. Compared with other data sources, this method is a low-cost but challenging way to generate high-accuracy maps. In this paper, we propose a data correction algorithm for low-frequency floating car data. First, we preprocess the trajectory data by an adaptive density optimizing method to remove the noise points with large mistakes. Then, we match the trajectory data with OpenStreetMap (OSM) using an efficient hierarchical map matching algorithm. Lastly, we correct the floating car data by an OSM-based physical attraction model. Experiments are conducted exploiting the data collected by thousands of taxies over one week in Wuhan City, China. The results show that the accuracy of the data is improved and the proposed algorithm is demonstrated to be practical and effective

HDM-RRT: A Fast HD-Map-Guided Motion Planning Algorithm for Autonomous Driving in the Campus Environment

On campus, the complexity of the environment and the lack of regulatory constraints make it difficult to model the environment, resulting in less efficient motion planning algorithms. To solve this problem, HD-Map-guided sampling-based motion planning is a feasible research direction. We proposed a motion planning algorithm for autonomous vehicles on campus, called HD-Map-guided rapidly-exploring random tree (HDM-RRT). In our algorithm, A collision risk map (CR-Map) that quantifies the collision risk coefficient on the road is combined with the Gaussian distribution for sampling to improve the efficiency of algorithm. Then, the node optimization strategy of the algorithm is deeply optimized through the prior information of the CR-Map to improve the convergence rate and solve the problem of poor stability in campus environments. Three experiments were designed to verify the efficiency and stability of our approach. The results show that the sampling efficiency of our algorithm is four times higher than that of the Gaussian distribution method. The average convergence rate of the proposed algorithm outperforms the RRT* algorithm and DT-RRT* algorithm. In terms of algorithm efficiency, the average computation time of the proposed algorithm is only 15.98 ms, which is much better than that of the three compared algorithms

Robust Lane-Detection Method for Low-Speed Environments

Vision-based lane-detection methods provide low-cost density information about roads for autonomous vehicles. In this paper, we propose a robust and efficient method to expand the application of these methods to cover low-speed environments. First, the reliable region near the vehicle is initialized and a series of rectangular detection regions are dynamically constructed along the road. Then, an improved symmetrical local threshold edge extraction is introduced to extract the edge points of the lane markings based on accurate marking width limitations. In order to meet real-time requirements, a novel Bresenham line voting space is proposed to improve the process of line segment detection. Combined with straight lines, polylines, and curves, the proposed geometric fitting method has the ability to adapt to various road shapes. Finally, different status vectors and Kalman filter transfer matrices are used to track the key points of the linear and nonlinear parts of the lane. The proposed method was tested on a public database and our autonomous platform. The experimental results show that the method is robust and efficient and can meet the real-time requirements of autonomous vehicles

Hydrodynamic performance and optimization of a pneumatic type spar buoy wave energy converter

In order to optimize the geometry of the spar buoy wave energy converter and improve its capture performance, numerical calculation and experimental research were carried out. The spar buoy oscillating water column wave energy technology can be regard as one of the pneumatic types oscillating single floating body. According to the study of the hydrodynamic characteristic and capture performance of the floater and the water column in the central pipe, the spar buoy mainly utilizes its heave motion to absorb wave energy. By comparing the numerical calculation results of the hydrodynamic performance and Capture Width Ratio (CWR) of five spar buoy models with different floater shapes, it is found that the flat-bottomed spar buoy has the best capture performance. The influence of the model's total mass on its capture performance was studied. The results show that an appropriate increase in the total mass increases the optimal response period and helps to improve the capture performance. The maximum CWR can reach 0.984. The research results show that the tail tube length has a minimal effect on the wave energy conversion characteristic, but the water column in the tube is greatly affected by its length

A Significant Inhibitory Effect on Advanced Glycation End Product Formation by Catechin as the Major Metabolite of Lotus Seedpod Oligomeric Procyanidins

Several lines of evidence suggested that B-type procyanidin oligomers from lotus seedpod (LSOPC) may effectively modulate the formation of advanced glycation end products (AGEs). In vivo, LSOPC is metabolized by intestinal flora to become various kinds of phenolic compounds that possess potent antioxidant activities. However, few reports of the absorption and metabolism of LSOPC have been revealed. In the present study, rats were orally administered with LSOPC at a dose of 300 mg/kg body weight. The metabolites of LSOPC in urine were elucidated by HPLC-MS/MS analysis 24 h post-administration. Eight major metabolites were significantly increased by the administration of 300 mg/kg of LSOPC (p &lt; 0.01). The anti-glycative activity of LSOPC and its metabolites were investigated. The results showed that LSOPC and catechin had greater anti-glycative activities than other metabolites, which were positively correlated to their carbonyl scavenging activities and antioxidant capacities

Graphene Quantum Dot-Mediated Atom-Layer Semiconductor Electrocatalyst for Hydrogen Evolution

Highlights The functional groups on graphene quantum dots (GQDs) for boosting the formation of MoS2 nanosheets via theoretical calculations were predicted. Near atom-layer-QD@SO3 with about 2 nm were synthesized using a functionalized GQD-induced in-situ bottom-up approach. Mechanistic insight on the role of functionalized GQDs was elaborated, namely, electron-withdrawing group functionalized GQDs facilitate the formation of nanosheet architectures of MoS2 compared to electron-donating group