Insect kinin mimics act as potential control agents for aphids: Structural modifications of Trp4.

Insect kinins are endogenous, biologically active peptides with various physiological functions. The use of insect kinins in plant protection is being evaluated by many groups. Some kinins have been chosen as lead compounds for pest control. We previously reported an insect kinin mimic IV-3 that had insecticidal activity. And by introducing a strong electron withdrawing group (-CF3 ) on the benzene ring (Phe2 ), we discovered a compound, L7 , with better activity than lead IV-3. In this work, taking L7 as the lead compound, we designed and synthesized 13 compounds to evaluate the influence of position 4 (Trp4 ) of insect kinin on insecticidal activity, by replacing the H atom on tryptophan with -CH3 and -Cl or substituting the indole ring of tryptophan with the benzene, naphthalene, pyridine, imidazole, cyclohexane, and alkyl carboxamides. The aphid bioassay results showed that the compounds M1 , M3 , and M5 were more active than the positive control, pymetrozine. Especially, replacing the side chain by an indole ring with 4-Cl substitution (M1 , LC50 = 0.0029 mmol/L) increased the aphicidal activity. The structure-activity relationships (SARs) indicated that the side chain benzene ring at this position may be important to the aphicidal activity. In addition, the toxicity prediction by Toxtree, and the toxicity experiments on Apis mellifera suggested that M1 was no toxicity risk on a non-target organism. It could be used as a selective and bee-friendly insecticide to control aphids.

Ct-defined emphysema prevalence in a Chinese and Dutch general population.

PURPOSE: We determine and compare the prevalence, subtypes, severity, and risk factors for emphysema assessed by low-dose CT(LDCT) in Chinese and Dutch general populations. METHODS: This cross-sectional study included LDCT scans of 1143 participants between May and October 2017 from a Chinese Cohort study and 1200 participants with same age range and different smoking status between May and October 2019 from a Dutch population-based study. An experienced radiologist visually assessed the scans for emphysema presence (≥trace), subtype, and severity. Logistic regression analyses, overall and stratified by smoking status, were performed and adjusted for fume exposure, demographic and smoking data. RESULTS: The Chinese population had a comparable proportion of women to the Dutch population (54.9 % vs 58.9 %), was older (61.7 ± 6.3 vs 59.8 ± 8.1), included more never smokers (66.4 % vs 38.3 %), had a higher emphysema prevalence ([58.8 % vs 39.7 %], adjusted odds ratio, aOR = 2.06, 95 %CI = 1.68-2.53), and more often had centrilobular emphysema (54.8 % vs 32.8 %, p < 0.001), but no differences in emphysema severity. After stratification, only in never smokers an increased odds of emphysema was observed in the Chinese compared to the Dutch (aOR = 2.55, 95 %CI = 1.95-3.35). Never smokers in both populations shared older age (aOR = 1.59, 95 %CI = 1.25-2.02 vs 1.26, 95 %CI = 0.97-1.64) and male sex (aOR = 1.50, 95 %CI = 1.02-2.22 vs 1.93, 95 %CI = 1.26-2.96) as risk factors for emphysema. CONCLUSIONS: Only never smokers had a higher prevalence of mainly centrilobular emphysema in the Chinese general population compared to the Dutch after adjusting for confounders, indicating that factors other than smoking, age and sex contribute to presence of CT-defined emphysema.

Volumetric computed tomography screening for lung cancer: three rounds of the NELSON trial.

Several medical associations recommended lung cancer screening by low-dose computed tomography scanning for high-risk groups. Counselling of the candidates on the potential harms and benefits and their lung cancer risk is a prerequisite for screening. In the NELSON trial, screenings are considered positive for (part) solid lung nodules with a volume >500 mm3 and for (part) solid or nonsolid nodules with a volume-doubling time <400 days. For this study, the performance of the NELSON strategy in three screening rounds was evaluated and risk calculations were made for a follow-up period of 5.5 years. 458 (6%) of the 7582 participants screened had a positive screen result and 200 (2.6%) were diagnosed with lung cancer. The positive screenings had a predictive value of 40.6% and only 1.2% of all scan results were false-positive. In a period of 5.5 years, the risk of screen-detected lung cancer strongly depends on the result of the first scan: 1.0% after a negative baseline result, 5.7% after an indeterminate baseline and 48.3% after a positive baseline. The screening strategy yielded few positive and false-positive scans with a reasonable positive predictive value. The 5.5-year lung cancer risk calculations aid clinicians in counselling candidates for lung cancer screening with low-dose computed tomography.

Sensitivity and accuracy of volumetry of pulmonary nodules on low-dose 16- and 64-row multi-detector CT: an anthropomorphic phantom study.

OBJECTIVE: To assess the sensitivity of detection and accuracy of volumetry by manual and semi-automated quantification of artificial pulmonary nodules in an anthropomorphic thoracic phantom on low-dose CT. METHODS: Fifteen artificial spherical nodules (diameter 3, 5, 8, 10 and 12 mm; CT densities -800, -630 and +100 HU) were randomly placed inside an anthropomorphic thoracic phantom. The phantom was examined on 16- and 64-row multidetector CT with a low-dose protocol. Two independent blinded observers screened for pulmonary nodules. Nodule diameter was measured manually, and volume calculated. For solid nodules (+100 HU), diameter and volume were also evaluated by semi-automated software. Differences in observed volumes between the manual and semi-automated method were evaluated by a t-test. RESULTS: Sensitivity was 100 % for all nodules of >5 mm and larger, 60-80 % for solid and 0-20 % for non-solid 3-mm nodules. No false-positive nodules but high inter-observer reliability and inter-technique correlation were found. Volume was underestimated manually by 24.1 ± 14.0 % for nodules of any density, and 26.4 ± 15.5 % for solid nodules, compared with 7.6 ± 8.5 % (P < 0.01) semi-automatically. CONCLUSION: In an anthropomorphic phantom study, the sensitivity of detection is 100 % for nodules of >5 mm in diameter. Semi-automated volumetry yielded more accurate nodule volumes than manual measurements.

Modality-Attention Promotes the Neural Effects of Precise Timing Prediction in Early Sensory Processing.

Precise timing prediction (TP) enables the brain to accurately predict the occurrence of upcoming events in millisecond timescale, which is fundamental for adaptive behaviors. The neural effect of the TP within a single sensory modality has been widely studied. However, less is known about how precise TP works when the brain is concurrently faced with multimodality sensory inputs. Modality attention (MA) is a crucial cognitive function for dealing with the overwhelming information induced by multimodality sensory inputs. Therefore, it is necessary to investigate whether and how the MA influences the neural effects of the precise TP. This study designed a visual-auditory temporal discrimination task, in which the MA was allocated to visual or auditory modality, and the TP was manipulated into no timing prediction (NTP), matched timing prediction (MTP), and violated timing prediction (VTP) conditions. Behavioral and electroencephalogram (EEG) data were recorded from 27 subjects, event-related potentials (ERP), time-frequency distributions of inter-trial coherence (ITC), and event-related spectral perturbation (ERSP) were analyzed. In the visual modality, precise TP led to N1 amplitude and 200-400 ms theta ITC variations. Such variations only emerged when the MA was attended. In auditory modality, the MTP had the largest P2 amplitude and delta ITC than other TP conditions when the MA was attended, whereas the distinctions disappeared when the MA was unattended. The results suggest that the MA promoted the neural effects of the precise TP in early sensory processing, which provides more neural evidence for better understanding the interactions between the TP and MA.

SKDCPM algorithm can improve the single-trial decoding performance of very similar error-related potentials.

Error related potential (ErrP) is an effective control signal for the brain-computer interface (BCI). Current ErrP decoding methods can only distinguish right and wrong mental states. However, in real scenarios, error conditions often contain more detailed information, such as the degree of error, which would induce very similar ErrPs. Distinguishing such ErrPs effectively is of vital importance to provide more detailed information for optimizing BCIs. Hereto, a major challenge is the EEG differences of very similar ErrPs are very small. Thus, it is necessary to develop new efficient method for decoding very similar ErrPs. This study newly proposed an algorithm named shrinkage discriminant canonical pattern matching (SKDCPM), and compared its decoding results with the linear discriminant analysis (LDA), shrinkage LDA (SKLDA), stepwise LDA (SWLDA), Bayesian LDA (BLDA) and the DCPM, which were algorithms commonly used for ErrP decoding. A data set of 18 subjects was built, it had four conditions, i.e., right (0°), errors with varying degrees, i.e., 45°, 90°, 180° deviation from the predicted direction. As a result, the SKDCPM had high balanced accuracy (BACC) in right-wrong classification (0° vs. others). More importantly, it achieved a grand averaged BACC of 69.54% with the highest up to 74.25%, which outperformed all the other algorithms in very similar ErrPs decoding (45° vs. 90° vs. 180°) significantly. This study could provide new decoding methods for developing the ErrP-based BCI system.

Temporal prediction changes motor-related EEG phase synchronization and network centrality in alpha and beta band.

Much neurophysiological evidence revealed motor system is involved in temporal prediction. However, It remains unknown how temporal prediction influences motor-related neural representations. Thus, more neural evidence is needed to understand better how temporal prediction influences the motor. This study designed a rhythmic finger-tap task and formed three temporal prediction conditions, i.e., 1000ms temporal prediction, 1500ms temporal prediction, and no temporal prediction. Behavioral and EEG data from 24 healthy subjects were recorded. The weighted phase lag index was calculated to measure the degree of phase synchronization. Eigenvector centrality and betweenness centrality were used to measure brain connectivity. Behavioral results showed that tap-visual asynchronies were decreased when temporal prediction existed. Phase synchronization results showed, compared to no temporal prediction, the alpha-band phase synchronization between the frontal and central area was reduced in 1000ms temporal prediction, and the beta-band phase synchronization between the frontal and parietal area was decreased in 1500ms temporal prediction. As to the brain connectivity, compared to no temporal prediction condition, the eigenvector centrality of the left frontal in 1500ms temporal prediction was decreased in the alpha band, and the betweenness centrality of the right temporal in 1000ms temporal prediction was reduced in the alpha-band. These results can provide new neural evidence for a better understanding of temporal prediction and motor interactions.

Rhythmic temporal prediction enhances neural representations of movement intention for brain-computer interface.

Objective.Detecting movement intention is a typical use of brain-computer interfaces (BCI). However, as an endogenous electroencephalography (EEG) feature, the neural representation of movement is insufficient for improving motor-based BCI. This study aimed to develop a new movement augmentation BCI encoding paradigm by incorporating the cognitive function of rhythmic temporal prediction, and test the feasibility of this new paradigm in optimizing detections of movement intention.Methods.A visual-motion synchronization task was designed with two movement intentions (left vs. right) and three rhythmic temporal prediction conditions (1000 ms vs. 1500 ms vs. no temporal prediction). Behavioural and EEG data of 24 healthy participants were recorded. Event-related potentials (ERPs), event-related spectral perturbation induced by left- and right-finger movements, the common spatial pattern (CSP) and support vector machine, Riemann tangent space algorithm and logistic regression were used and compared across the three temporal prediction conditions, aiming to test the impact of temporal prediction on movement detection.Results.Behavioural results showed significantly smaller deviation time for 1000 ms and 1500 ms conditions. ERP analyses revealed 1000 ms and 1500 ms conditions led to rhythmic oscillations with a time lag in contralateral and ipsilateral areas of movement. Compared with no temporal prediction, 1000 ms condition exhibited greater beta event-related desynchronization (ERD) lateralization in motor area (P< 0.001) and larger beta ERD in frontal area (P< 0.001). 1000 ms condition achieved an averaged left-right decoding accuracy of 89.71% using CSP and 97.30% using Riemann tangent space, both significantly higher than no temporal prediction. Moreover, movement and temporal information can be decoded simultaneously, achieving 88.51% four-classification accuracy.Significance.The results not only confirm the effectiveness of rhythmic temporal prediction in enhancing detection ability of motor-based BCI, but also highlight the dual encodings of movement and temporal information within a single BCI paradigm, which is promising to expand the range of intentions that can be decoded by the BCI.

Management of lung nodules detected by volume CT scanning.

BACKGROUND: The use of multidetector computed tomography (CT) in lung-cancer screening trials involving subjects with an increased risk of lung cancer has highlighted the problem for the clinician of deciding on the best course of action when noncalcified pulmonary nodules are detected by CT. METHODS: A total of 7557 participants underwent CT screening in years 1, 2, and 4 of a randomized trial of lung-cancer screening. We used software to evaluate a noncalcified nodule according to its volume or volume-doubling time. Growth was defined as an increase in volume of at least 25% between two scans. The first-round screening test was considered to be negative if the volume of a nodule was less than 50 mm(3), if it was 50 to 500 mm(3) but had not grown by the time of the 3-month follow-up CT, or if, in the case of those that had grown, the volume-doubling time was 400 days or more. RESULTS: In the first and second rounds of screening, 2.6% and 1.8% of the participants, respectively, had a positive test result. In round one, the sensitivity of the screen was 94.6% (95% confidence interval [CI], 86.5 to 98.0) and the negative predictive value 99.9% (95% CI, 99.9 to 100.0). In the 7361 subjects with a negative screening result in round one, 20 lung cancers were detected after 2 years of follow-up. CONCLUSIONS: Among subjects at high risk for lung cancer who were screened in three rounds of CT scanning and in whom noncalcified pulmonary nodules were evaluated according to volume and volume-doubling time, the chances of finding lung cancer 1 and 2 years after a negative first-round test were 1 in 1000 and 3 in 1000, respectively. (Current Controlled Trials number, ISRCTN63545820.)

No benefit for consensus double reading at baseline screening for lung cancer with the use of semiautomated volumetry software.

PURPOSE: To retrospectively evaluate the performance of consensus double reading compared with single reading at baseline screening of a lung cancer computed tomography (CT) screening trial. MATERIALS AND METHODS: The study was approved by the Dutch Minister of Health and ethical committees. Written informed consent was obtained from all participants. The benefit of consensus double reading was expressed by the percentage change in cancer detection rate, recall rate, number of additional nodules detected, and change in sensitivity and specificity in 7557 participants. The reference standard was a retrospective analysis of the serial CT scans performed in participants diagnosed with lung cancer during a 2-year period after baseline. Semiautomated volumetric software was used for nodule evaluation. McNemar tests were performed to test statistical significance. In addition, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated and 95% confidence intervals (CIs) constructed. RESULTS: Seventy-four cases of lung cancer were qualified as detectable at baseline. Compared with single reading, consensus double reading did not increase the cancer detection rate (2.7%; 95% CI: -1.0%, 6.4%; P = .50) or change the recall rate (20.6% vs 20.8%, P = .28), but led to the detection of 19.0% (1635 of 8623; 95% CI: 18.0%, 19.9%, P < .01) more nodules. The sensitivity, specificity, PPV, and NPV were 95.9% (71 of 74), 80.2% (6001 of 7483), 4.6% (71 of 1553) and 99.9% (6001 of 6004) for single reading and 98.6% (73 of 74), 80.0% (1497 of 7483), 4.6% (73 of 1570), and 99.9% (5986 of 5987) for consensus double reading, respectively. CONCLUSION: There is no statistically significant benefit for consensus double reading at baseline screening for lung cancer with the use of a nodule management strategy based solely on semiautomated volumetry.

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume.

OBJECTIVE: To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmonary nodules on low-dose computed tomography (CT) by nodule volume. METHODS: A total of 400 low-dose chest CT examinations were randomly selected from the NELSON lung cancer screening trial. CTs were evaluated by two independent readers and processed by CAD. A total of 1,667 findings marked by readers and/or CAD were evaluated by a consensus panel of expert chest radiologists. Performance was evaluated by calculating sensitivity of pulmonary nodule detection and number of false positives, by nodule characteristics and volume. RESULTS: According to the screening protocol, 90.9 % of the findings could be excluded from further evaluation, 49.2 % being small nodules (less than 50 mm(3)). Excluding small nodules reduced false-positive detections by CAD from 3.7 to 1.9 per examination. Of 151 findings that needed further evaluation, 33 (21.9 %) were detected by CAD only, one of them being diagnosed as lung cancer the following year. The sensitivity of nodule detection was 78.1 % for double reading and 96.7 % for CAD. A total of 69.7 % of nodules undetected by readers were attached nodules of which 78.3 % were vessel-attached. CONCLUSIONS: CAD is valuable in lung cancer screening to improve sensitivity of pulmonary nodule detection beyond double reading, at a low false-positive rate when excluding small nodules. KEY POINTS: • Computer-aided detection (CAD) has known advantages for computed tomography (CT). • Combined CAD/nodule size cut-off parameters assist CT lung cancer screening. • This combination improves the sensitivity of pulmonary nodule detection by CT. • It increases the positive predictive value for cancer detection.

A novel bee-friendly peptidomimetic insecticide: Synthesis, aphicidal activity and 3D-QSAR study of insect kinin analogs at Phe2 modification.

BACKGROUND: As one of the most abundant and destructive pests in agriculture, aphids cause significant damage to crops due to their sap-taking and as virus vectors. Chemical insecticides are the most effective method to control aphids, but they bring insecticide resistance problems and harm nontarget organisms, especially bees, therefore the search for novel eco-friendly aphid control agents with low bee toxicity is urgent. Insect kinins are a class of small neuropeptides that control important functions in insects. In our previous study, we found insect kinin analog IV-3 has good aphicidal activity and the location of the aromatic ring on the side chain of Phe2 is the key to the formation of the ß-turn resulting in the biological activity of insect kinin analogs. However, there are few studies on insect kinin Phe2 substitution and modification, and its structure-activity relationship is still unclear. RESULTS: In this project, 44 insect kinin analogs with the Phe2 modification, replacing it with different natural or unnatural amino acids, were designed and synthesized based on the lead IV-3 to explore the role of the Phe2 residues. Bioassays with soybean aphids of Aphis glycines indicated that nine analogs have better aphicidal activity than the lead IV-3. In particular, compound L25 exhibits excellent aphicidal activity (LC50  = 0.0047 mmol L-1 ) and has low toxicity to bees. Furthermore, a reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) was established to produce a helpful clue that introducing hydrophobic groups away from the backbone chain is beneficial to improve aphicidal activity. CONCLUSION: The residue Phe2 of insect kinin analogs is the key position and has a significant impact on the activity. L25 has a high toxicity for aphids, while a low toxicity to bees, and therefore can be considered as a lead compound to develop new biosafe aphid control agents. Finally, we provide a useful 3D-QSAR model as theoretical guidance for further structural optimization. © 2022 Society of Chemical Industry.

Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program.

OBJECTIVE: To evaluate the performance of a deep learning-based computer-aided detection (DL-CAD) system in a Chinese low-dose CT (LDCT) lung cancer screening program. MATERIALS AND METHODS: One-hundred-and-eighty individuals with a lung nodule on their baseline LDCT lung cancer screening scan were randomly mixed with screenees without nodules in a 1:1 ratio (total: 360 individuals). All scans were assessed by double reading and subsequently processed by an academic DL-CAD system. The findings of double reading and the DL-CAD system were then evaluated by two senior radiologists to derive the reference standard. The detection performance was evaluated by the Free Response Operating Characteristic curve, sensitivity and false-positive (FP) rate. The senior radiologists categorized nodules according to nodule diameter, type (solid, part-solid, non-solid) and Lung-RADS. RESULTS: The reference standard consisted of 262 nodules ≥ 4 mm in 196 individuals; 359 findings were considered false positives. The DL-CAD system achieved a sensitivity of 90.1% with 1.0 FP/scan for detection of lung nodules regardless of size or type, whereas double reading had a sensitivity of 76.0% with 0.04 FP/scan (P = 0.001). The sensitivity for detection of nodules ≥ 4 - ≤ 6 mm was significantly higher with DL-CAD than with double reading (86.3% vs. 58.9% respectively; P = 0.001). Sixty-three nodules were only identified by the DL-CAD system, and 27 nodules only found by double reading. The DL-CAD system reached similar performance compared to double reading in Lung-RADS 3 (94.3% vs. 90.0%, P = 0.549) and Lung-RADS 4 nodules (100.0% vs. 97.0%, P = 1.000), but showed a higher sensitivity in Lung-RADS 2 (86.2% vs. 65.4%, P < 0.001). CONCLUSIONS: The DL-CAD system can accurately detect pulmonary nodules on LDCT, with an acceptable false-positive rate of 1 nodule per scan and has higher detection performance than double reading. This DL-CAD system may assist radiologists in nodule detection in LDCT lung cancer screening.

Atomic cerium modulated palladium nanoclusters exsolved ferrite catalysts for lean methane conversion.

The active and stable palladium (Pd) based catalysts for CH4 conversion are of great environmental and industrial significance. Herein, we employed N2 as an optimal activation agent to develop a Pd nanocluster exsolved Ce-incorporated perovskite ferrite catalyst toward lean methane oxidation. Replacing the traditional initiator of H2, the N2 was found as an effective driving force to selectively touch off the surface exsolution of Pd nanocluster from perovskite framework without deteriorating the overall material robustness. The catalyst showed an outstanding T50 (temperature of 50% conversion) plummeting down to 350°C, outperforming the pristine and H2-activated counterparts. Further, the combined theoretical and experimental results also deciphered the crucial role that the atomically dispersed Ce ions played in both construction of active sites and CH4 conversion. The isolated Ce located at the A-site of perovskite framework facilitated the thermodynamic and kinetics of the Pd exsolution process, lowering its formation temperature and promoting its quantity. Moreover, the incorporation of Ce lowered the energy barrier for cleavage of C─H bond, and was dedicated to the preservation of highly reactive PdOx moieties during stability measurement. This work successfully ventures uncharted territory of in situ exsolution to provide a new design thinking for a highly performed catalytic interface.

Minimized thermal expansion mismatch of cobalt-based perovskite air electrodes for solid oxide cells.

The mismatch of thermal expansion coefficients (TECs) between cobalt-containing perovskite air electrodes and electrolytes is a great challenge for the development of thermo-mechanically durable solid oxide cells (SOCs). In this work, we propose a facile design principle to directly grow highly dispersed Co reactive sites onto ion-conducting scaffolds and confine the dimension of active centres within nanoscale. As a representative, the Co-socketed BaCe0.7Zr0.2Y0.1O3-δ perovskite (denoted as R-BCZY-Co) was constructed via a consecutive sol-gel and in situ exsolution approach. Combined XRD, H2-TPR, SEM and TEM results confirm the emergence of Co nanoparticles on a BCZY matrix without the segregation of a secondary Co-rich phase. The symmetric half-cell measurement suggests that R-BCZY-Co air electrode with the optimal Co content of 10 mol% exhibits a 7-fold promoted oxygen activation performance with a polarization resistance of ∼0.17 Ω cm2 at 750 °C. The TEC mismatch between fabricated R-BCZY-Co electrodes and BCZY electrolytes is minimized down to only ∼11.4%, which is significantly lower than that of other representative counterparts. Moreover, the detailed XPS result proves that the architecture of exsolved Co on BCZY possesses a higher concentration of surface oxygen vacancy, which further benefits the kinetics of ion diffusion and oxygen absorption.

Using arterial spin labeling blood flow and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma from lymphoid hyperplasia.

ABSTRACT: To investigate the feasibility of arterial spin labeling (ASL) blood flow (BF) and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPLH).Sixty-three stage T1 NPC patients and benign NPLH patients underwent ASL on a 3.0-T magnetic resonance imaging system. BF histogram parameters were derived automatically, including the mean, median, maximum, minimum, kurtosis, skewness, and variance. Absolute values were obtained for skewness and kurtosis (absolute value of skewness [AVS] and absolute value of kurtosis [AVK], respectively). The Mann-Whitney U test, receiver operating characteristic curve, and multiple logistic regression models were used for statistical analysis.The mean, maximum, and variance of ASL BF values were significantly higher in early-stage NPC than in NPLH (all P < 0.0001), while the median and AVK values of early-stage NPC were also significantly higher than those of NPLH (all P < 0.001). No significant difference was found between the minimum and AVS values in early-stage NPC compared with NPLH (P = 0.125 and P = 0.084, respectively). The area under the curve (AUC) of the maximum was significantly higher than those of the mean and median (P < 0.05). The AUC of variance was significantly higher than those of the other parameters (all P < 0.05). Multivariate analysis showed that variance was the only independent predictor of outcome (P < 0.05).ASL BF and its histogram analysis could distinguish early-stage NPC from NPLH, and the variance value was a unique independent predictor.

A contrast-enhanced-CT-based classification tree model for classifying malignancy of solid lung tumors in a Chinese clinical population.

BACKGROUND: To develop and validate a contrast-enhanced CT based classification tree model for classifying solid lung tumors in clinical patients into malignant or benign. METHODS: Between January 2015 and October 2017, 827 pathologically confirmed solid lung tumors (487 malignant, 340 benign; median size, 27.0 mm, IQR 18.0-39.0 mm) from 827 patients from a dedicated Chinese cancer hospital were identified. Nodules were divided randomly into two groups, a training group (575 cases) and a testing group (252 cases). CT characteristics were collected by two radiologists, and analyzed using a classification and regression tree (CART) model. For validation, we used the decision analysis threshold to evaluate the classification performance of the CART model and radiologist's diagnosis (benign; malignant) in the testing group. RESULTS: Three out of 19 characteristics [margin (smooth; slightly lobulated/lobulated/spiculated), and shape (round/oval; irregular), subjective enhancement (no/uniform enhancement; heterogeneous enhancement)] were automatically generated by the CART model for classifying solid lung tumors. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the CART model is 98.5%, 58.1%, 80.6%, 98.6%, 79.8%, and 90.4%, 54.7%, 82.4% 98.5%, 74.2% for the radiologist's diagnosis by using three-threshold decision analysis. CONCLUSIONS: Tumor margin and shape, and subjective tumor enhancement were the most important CT characteristics in the CART model for classifying solid lung tumors as malignant. The CART model had higher discriminatory power than radiologist's diagnosis. The CART model could help radiologists making recommendations regarding follow-up or surgery in clinical patients with a solid lung tumor.

Community-based lung cancer screening by low-dose computed tomography in China: First round results and a meta-analysis.

OBJECTIVE: To evaluate the efficiency of low-dose computed tomography (LDCT) screening for lung cancer in China by analyzing the baseline results of a community-based screening study accompanied with a meta-analysis. METHODS: A first round of community-based lung cancer screening with LDCT was conducted in Tianjin, China, and a systematic literature search was performed to identify LDCT screening and registry-based clinical studies for lung cancer in China. Baseline results in the community-based screening study were described by participant risk level and the lung cancer detection rate was compared with the pooled rate among the screening studies. The percentage of patients per stage was compared between the community-based study and screening and clinical studies. RESULTS: In the community-based study, 5523 participants (43.6% men) underwent LDCT. The lung cancer detection rate was 0.5% (high-risk, 1.2%; low-risk, 0.4%), with stage I disease present in 70.0% (high-risk, 50.0%; low-risk, 83.3%), and the adenocarcinoma present in 84.4% (high-risk, 61.5%; low-risk, 100%). Among all screen-detected lung cancer, women accounted for 8.3% and 66.7% in the high- and low-risk group, respectively. In the screening studies from mainland China, the lung cancer detection rate 0.6% (95 %CI: 0.3%-0.9%) for high-risk populations. The proportions with carcinoma in situ and stage I disease in the screening and clinical studies were 76.4% (95 %CI: 66.3%-85.3%) and 15.2% (95 %CI: 11.8%-18.9%), respectively. CONCLUSIONS: The stage shift of lung cancer due to screening suggests a potential effectiveness of LDCT screening in China. Nearly 70% of screen-detected lung cancers in low-risk populations are identified in women.

Volumetric measurement of pulmonary nodules at low-dose chest CT: effect of reconstruction setting on measurement variability.

OBJECTIVE: To assess volumetric measurement variability in pulmonary nodules detected at low-dose chest CT with three reconstruction settings. METHODS: The volume of 200 solid pulmonary nodules was measured three times using commercially available semi-automated software of low-dose chest CT data-sets reconstructed with 1 mm section thickness and a soft kernel (A), 2 mm and a soft kernel (B), and 2 mm and a sharp kernel (C), respectively. Repeatability coefficients of the three measurements within each setting were calculated by the Bland and Altman method. A three-level model was applied to test the impact of reconstruction setting on the measured volume. RESULTS: The repeatability coefficients were 8.9, 22.5 and 37.5% for settings A, B and C. Three-level analysis showed that settings A and C yielded a 1.29 times higher estimate of nodule volume compared with setting B (P = 0.03). The significant interaction among setting, nodule location and morphology demonstrated that the effect of the reconstruction setting was different for different types of nodules. Low-dose CT reconstructed with 1 mm section thickness and a soft kernel provided the most repeatable volume measurement. CONCLUSION: A wide, nodule-type-dependent range of agreement between volume measurements with different reconstruction settings suggests strict consistency is required for serial CT studies.

Nasopharyngeal carcinoma perfusion MRI: Comparison of arterial spin labeling and dynamic contrast-enhanced MRI.

To investigate the feasibility of 3D arterial spin labeling (ASL) as an alternative to dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the qualitative and quantitative evaluation of nasopharyngeal carcinoma (NPC) perfusion.Fifty-two newly diagnosed NPC patients underwent 3D ASL and DCE-MRI scans on a 3.0-T MRI system. The visual qualitative evaluation of the NPC perfusion level was scored from 0 to 3 (0 = no contrast to normal peripheral soft tissue, 3 = pronounced contrast to normal peripheral soft tissue). The visual evaluation of the NPC outline was scored from 0 to 2 (0 = very vague outline, 2 = clear outline). Comparisons of the ASL-derived blood flow (BF) with the DCE-MRI-derived positive enhancement integral, maximum slope of increase, maximum slope of decrease, and time to peak (TTP) were conducted between NPC and non-NPC areas with independent samples t-tests. The diagnostic performance of these parameters was assessed by receiver operating characteristic curve analysis. The correlations between ASL BF and DCE parameters were assessed by Spearman correlation analysis.There was no difference in the visual scores of the NPC perfusion level between the 2 perfusion methods (P= .963). ASL had a lower visual score for describing the outline of NPC than DCE-MRI (P < .001). The ASL and DCE parameters of the NPC areas were significantly different from those of the non-NPC areas (P < .001). The ASL BF showed the largest area under the receiver operating characteristic curve (AUC) of 0.936 for identifying NPC. When all NPC and non-NPC areas were taken into account, significant correlations were observed between the ASL BF and the DCE parameters positive enhancement integral (r = 0.503, P < .001), maximum slope of increase (r = 0.616, P < .001), maximum slope of decrease (r = 0.380, P < .001), and TTP (r = -0.601, P < .001).3D ASL could reveal the hyperperfusion of NPC in a qualitative and quantitative manner without using contrast agent. Additionally, the ASL BF correlated significantly with the semiquantitative DCE-MRI parameters.