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.

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.

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.

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.

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.

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.

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.

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.

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.

Combination of diffusion-weighted imaging and arterial spin labeling at 3.0 T for the clinical staging of nasopharyngeal carcinoma.

PURPOSE: To probe the utility of diffusion-weighted imaging (DWI) and 3D arterial spin labeling (ASL) in assessing the clinical stage of nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: This prospective study included sixty-five newly diagnosed NPC patients who underwent DWI and 3D ASL scans on a 3.0-T magnetic resonance imaging (MRI) system. The apparent diffusion coefficient (ADC) and the tumor blood flow (TBF) of NPC were measured. Tumors were classified as low or high T, N and American Joint Committee on Cancer (AJCC) stages. Student's t-test was used to evaluate the differences between tumors with low and high clinical stages. Pearson correlation analyses were performed to determine the correlation between MRI parameters and clinical stages. Receiver operating characteristic (ROC) curves were then used to evaluate diagnostic capability. RESULTS: High T stage (T3/4) NPC showed significantly lower ADCmin (P = 0.000) and higher TBFmax (P = 0.003) and TBFmean (P = 0.008) values than low T stage (T1/2) NPC. High N stage (N2/3) NPC showed significantly lower ADCmin values (P = 0.023) than low N stage (N0/1) NPC. High AJCC stage (III/IV) NPC showed significantly lower ADCmin (P = 0.000) and higher TBFmax (P = 0.005) and TBFmean (P = 0.011) values than low AJCC stage (I/II) NPC. ADCmin values showed moderate negative correlations with T stage (r = -0.512, P = 0.000), N stage (r = -0.281, P = 0.023), and AJCC stage (r = -0.494, P = 0.000). TBFmax values showed moderate positive correlations with T stage (r = 0.369, P = 0.003) and AJCC stage (r = 0.346, P = 0.005). Compared with ADCmin and TBFmax alone, the combination of ADCmin and TBFmax improved the accuracy from 72.3% and 75.4% to 78.5%, respectively, for T staging, as well as from 72.3% and 69.2% to 83.1% for AJCC staging. CONCLUSIONS: ADCmin and TBFmax values in patients with NPC could help evaluate clinical stages. ADCmin and TBFmax values combined could clearly improve the accuracy in the assessment of AJCC stage.

Optimization of CT windowing for diagnosing invasiveness of adenocarcinoma presenting as sub-solid nodules.

PURPOSE: To evaluate the optimal window setting to diagnose the invasiveness of lung adenocarcinoma in sub-solid nodules (SSNs). METHODS: We retrospectively included 437 SSNs and randomly divided them 3:1 into a training group (327) and a testing group (110). The presence of a solid component was regarded as indicator of invasiveness. At fixed window level (WL) of 35 Hounsfield Units (HU), two readers adjusted the window width (WW) in the training group and recorded once a solid component appeared or disappeared on CT images acquired at 120 kVp. The optimal WW cut-off value to differentiate between invasive and pre-invasive lesions, based on the receiver operating characteristic (ROC) curve, was defined as "core" WW. The diagnostic performances of the mediastinal window setting (WW/WL, 350/35 HU) and core window setting were then compared in the testing group. RESULTS: Of the 437 SSNs, 88 were pre-invasive [17 atypical adenomatous hyperplasia (AAH) and 71 adenocarcinoma in situ (AIS)], 349 were invasive [233 minimally invasive adenocarcinoma (MIA), 116 invasive adenocarcinoma (IA)]. In training group, the core WW of 1175 HU was the optimal cut-off to detect solid components of SSNs (AUC:0.79). In testing group, the sensitivity, specificity, positive, negative predictive value, and diagnostic accuracy for SSN invasiveness were 49.4%, 90.5%, 95.7%, 29.7%, and 57.3% for mediastinal window setting, and 87.6%, 76.2%, 91.6%, 76.2%, and 85.5% for core window setting. CONCLUSION: At 120 kVp, core window setting (WW/WL, 1175/35 HU) outperformed the traditional mediastinal window setting to diagnose the invasiveness of SSNs.

A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary Adenocarcinoma.

OBJECTIVES: To develop an imaging reporting system for the classification of 3 adenocarcinoma subtypes of computed tomography (CT)-detected subsolid pulmonary nodules (SSNs) in clinical patients. METHODS: Between November 2011 and October 2017, 437 pathologically confirmed SSNs were retrospectively identified. SSNs were randomly divided 2:1 into a training group (291 cases) and a testing group (146 cases). CT-imaging characteristics were analyzed using multinomial univariable and multivariable logistic regression analysis to identify discriminating factors for the 3 adenocarcinoma subtypes (pre-invasive lesions, minimally invasive adenocarcinoma, and invasive adenocarcinoma). These factors were used to develop a classification and regression tree model. Finally, an SSN Imaging Reporting System (SSN-IRS) was constructed based on the optimized classification model. For validation, the classification performance was evaluated in the testing group. RESULTS: Of the CT-derived characteristics of SSNs, qualitative density (nonsolid or part-solid), core (non-core or core), semantic features (pleural indentation, vacuole sign, vascular invasion), and diameter of solid component (≤6 mm or >6 mm), were the most important factors for the SSN-IRS. The total sensitivity, specificity, and diagnostic accuracy of the SSN-IRS was 89.0% (95% confidence interval [CI], 84.8%-92.4%), 74.6% (95% CI, 70.8%-78.1%), and 79.4% (95% CI, 76.5%-82.0%) in the training group and 84.9% (95% CI, 78.1%-90.3%), 68.5% (95% CI, 62.8%-73.8%), and 74.0% (95% CI, 69.6%-78.0%) in the testing group, respectively. CONCLUSIONS: The SSN-IRS can classify 3 adenocarcinoma subtypes using CT-based characteristics of subsolid pulmonary nodules. This classification tool can help clinicians to make follow-up recommendations or decisions for surgery in clinical patients with SSNs.

Clinical characteristics and work-up of small to intermediate-sized pulmonary nodules in a Chinese dedicated cancer hospital.

Objectives: To evaluate the characteristics and work-up of small to intermediate-sized pulmonary nodules in a Chinese dedicated cancer hospital. Methods: Patients with pulmonary nodules 4-25 mm in diameter detected via computed tomography (CT) in 2013 were consecutively included. The analysis was restricted to patients with a histological nodule diagnosis or a 2-year follow-up period without nodule growth confirming benign disease. Patient information was collected from hospital records. Results: Among the 314 nodules examined in 299 patients, 212 (67.5%) nodules in 206 (68.9%) patients were malignant. Compared to benign nodules, malignant nodules were larger (18.0 mm vs. 12.5 mm, P < 0.001), more often partly solid (16.0% vs. 4.7%, P < 0.001) and more often spiculated (72.2% vs. 41.2%, P < 0.001), with higher density in contrast-enhanced CT (67.0 HU vs. 57.5 HU, P = 0.015). Final diagnosis was based on surgery in 232 out of 314 (73.9%) nodules, 166 of which were identified as malignant [30 (18.1%) stage III or IV] and 66 as benign. In 36 nodules (11.5%), diagnosis was confirmed by biopsy and the remainder verified based on stability of nodule size at follow-up imaging (n = 46, 14.6%). Among 65 nodules subjected to gene (EGFR) mutation analyses, 28 (43.1%) cases (EGFR19 n = 13; EGFR21 n = 15) were identified as EGFR mutant and 37 (56.9%) as EGFR wild-type. Prior to surgery, the majority of patients [n = 194 (83.6%)] received a contrast-enhanced CT scan for staging of both malignant [n = 140 (84.3%)] and benign [n = 54 (81.8%)] nodules. Usage of positron emission tomography (PET)-CT was relatively uncommon [n = 38 (16.4%)]. Conclusions: CT-derived nodule assessment assists in diagnosis of small to intermediate- sized malignant pulmonary nodules. Currently, contrast-enhanced CT is commonly used as the sole diagnostic confirmation technique for pre-surgical staging, often resulting in surgery for late-stage disease and unnecessary surgery in cases of benign nodules.

Comparison of Veterans Affairs, Mayo, Brock classification models and radiologist diagnosis for classifying the malignancy of pulmonary nodules in Chinese clinical population.

BACKGROUND: Several classification models based on Western population have been developed to help clinicians to classify the malignancy probability of pulmonary nodules. However, the diagnostic performance of these Western models in Chinese population is unknown. This paper aimed to compare the diagnostic performance of radiologist evaluation of malignancy probability and three classification models (Mayo Clinic, Veterans Affairs, and Brock University) in Chinese clinical pulmonology patients. METHODS: This single-center retrospective study included clinical patients from Tianjin Medical University Cancer Institute and Hospital with new, CT-detected pulmonary nodules in 2013. Patients with a nodule with diameter of 4-25 mm, and histological diagnosis or 2-year follow-up were included. Analysis of area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and threshold of decision analysis was used to evaluate the diagnostic performance of radiologist diagnosis and the three classification models, with histological diagnosis or 2-year follow-up as the reference. RESULTS: In total, 277 patients (286 nodules) were included. Two hundred and seven of 286 nodules (72.4%) in 203 patients were malignant. AUC of the Mayo model (0.77; 95% CI: 0.72-0.82) and Brock model (0.77; 95% CI: 0.72-0.82) were similar to radiologist diagnosis (0.78; 95% CI: 0.73-0.83; P=0.68, P=0.71, respectively). The diagnostic performance of the VA model (AUC: 0.66) was significantly lower than that of radiologist diagnosis (P=0.003). A three-class classifying threshold analysis and DCA showed that the radiologist evaluation had higher discriminatory power for malignancy than the three classification models. CONCLUSIONS: In a cohort of Chinese clinical pulmonology patients, radiologist evaluation of lung nodule malignancy probability demonstrated higher diagnostic performance than Mayo, Brock, and VA classification models. To optimize nodule diagnosis and management, a new model with more radiological characteristics could be valuable.

Methods of computed tomography screening and management of lung cancer in Tianjin: design of a population-based cohort study.

OBJECTIVE: European lung cancer screening studies using computed tomography (CT) have shown that a management protocol based on measuring lung nodule volume and volume doubling time (VDT) is more specific for early lung cancer detection than a diameter-based protocol. However, whether this also applies to a Chinese population is unclear. The aim of this study is to compare the diagnostic performance of a volume-based protocol with a diameter-based protocol for lung cancer detection and optimize the nodule management criteria for a Chinese population. METHODS: This study has a population-based, prospective cohort design and includes 4000 participants from the Hexi district of Tianjin, China. Participants will undergo low-dose chest CT at baseline and after 1 year. Initially, detected lung nodules will be evaluated for diameter and managed according to a routine diameter-based protocol (Clinical Practice Guideline in Oncology for Lung Cancer Screening, Version 2.2018). Subsequently, lung nodules will be evaluated for volume and management will be simulated according to a volume-based protocol and VDT (a European lung nodule management protocol). Participants will be followed up for 4 years to evaluate lung cancer incidence and mortality. The primary outcome is the diagnostic performance of the European volume-based protocol compared to diameter-based management regarding lung nodules detected using low-dose CT. RESULTS: The diagnostic performance of volume- and diameter-based management for lung nodules in a Chinese population will be estimated and compared. CONCLUSIONS: Through the study, we expect to improve the management of lung nodules and early detection of lung cancer in Chinese populations.