Dual-energy CT-based radiomics in predicting EGFR mutation status non-invasively in lung adenocarcinoma.

Objectives: Patients with epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma (LUAD) can benefit from individualized targeted therapy. This study aims to develop, compare, analyse prediction models based on dual-energy spectral computed tomography (DESCT) and CT-based radiomic features to non-invasively predict EGFR mutation status in LUAD. Materials and methods: Patients with LUAD (n = 175), including 111 patients with and 64 patients without EGFR mutations, were enrolled in the current study. All patients were randomly divided into a training dataset (122 cases) and validation dataset (53 cases) at a ratio of 7:3. After extracting CT-based radiomic, DESCT and clinical features, we built seven prediction models and a nomogram of the best prediction. Receiver operating characteristic (ROC) curves and the mean area under the curve (AUC) values were used for comparisons among the models to obtain the best prediction model for predicting EGFR mutations. Results: The best distinguishing ability is the combined model incorporating radiomic, DESCT and clinical features for predicting the EGFR mutation status with an AUC of 0.86 (95 % CI: 0.79-0.92) in the training group and an AUC value of 0.83 (95 % CI: 0.73, 0.96) in the validation group. Conclusions: Our study provides a predictive nomogram non-invasively with a combination of CT-based radiomic, DESCT and clinical features, which can provide image-based biological information for targeted therapy of LUAD with EGFR mutations.

Micronodular thymoma with lymphoid stroma: Contrast-enhanced CT features with histopathological correlation in 10 patients.

Objectives: This study aimed to evaluate and summarize the contrast-enhanced computed tomography (CECT) imaging features of micronodular thymoma with lymphoid stroma (MTWLS) based on all MTWLS patients at our institution and was the first imaging study of MTWLS worldwide. Methods: This retrospective study included 10 MTWLS patients who underwent CECT between April 2012 and November 2021. We collected and analyzed the CECT imaging features, including the location, size, shape, tumor density, classification, and CT value of the solid component. Descriptive statistical analysis was performed using the SPSS software (version 26.0; IBM). Results: Ten patients (five males [50%], five females [50%]; median age, 61.4 years; range, 54-72 years) underwent CECT. Of the 10 cases, one case was purely cystic, seven cases were cystic-solid, and two cases were purely solid. Six cases were round/oval in shape, and four cases were irregularly shaped. Excluding a purely cystic tumor with an unmeasurable degree of enhancement, two cases showed moderate enhancement, and seven cases showed significant enhancement. Among the solid or cystic-solid cases, the mean CT value of the measurable solid component on the enhanced scan was 93.9 HU. Nine masses were located adjacent to the mediastinal pleura, pericardium, or large vessels. Additionally, there were no malignant tumor signs in any patient, including penetration of the mediastinal pleura or involvement of the pericardium, pleural effusion, elevation of the diaphragm, or direct vascular invasion. Conclusion: MTWLS demonstrates certain features on CECT, such as a high rate of cystic change, significant solid component enhancement, and no malignant, invasive imaging features. These CECT features are helpful for diagnosing MTWLS.

[Comparative analysis of chemical compositions of fruits of Perilla frutescens var. arguta and P. frutescens var. frutescens by pre-column derivatization with GC-MS].

The present study compared the appearance and chemical composition of fruits of Perilla frutescens var. arguta(PFA) and P. frutescens var. frutescens(PFF). VHX-6000 3 D depth of field synthesis technology was applied for the appearance observation. The metabolites were qualitatively and quantitatively analyzed by pre-column derivatization combined with gas chromatography-mass spectrometry(GC-MS). Finally, cluster analysis(CA), principal component analysis(PCA), and orthogonal partial least-squares discriminant analysis(OPLS-DA) were applied for exploring the differences in their chemical compositions. The results indicated that the size and color of PFA and PFF fruits were different. PFF fruits were significantly larger than PFA fruits. The surface color of PFA fruits was brown, while PFF fruits were in multiple colors, such as white, grayish-white, and brown. Amino acids, saccharides, organic acids, fatty acids, and phenolic acids were identified in PFA and PFF fruits. The results of CA, PCA, and OPLS-DA indicated significant differences in the content of components between PFA and PFF fruits. Three metabolites, including D-glucose, rosmarinic acid, and D-fructose, which were significantly higher in PFA fruits than in PFF fruits, were screened out as differential metabolites. Considering the regulation on the content of rosmarinic acid in Perillae Fructus in the Chinese Pharmacopoeia(2020 edition), the medicinal value of PFA fruits is higher than that of PFF. In conclusion, there are differences in appearance and chemical composition between PFA fruits and PFF fruits. These results are expected to provide fundamental data for specifying plant source and quality control of Perillae Fructus.

Proposing a deep learning-based method for improving the diagnostic certainty of pulmonary nodules in CT scan of chest.

OBJECTIVE: To compare the performance of a deep learning (DL)-based method for diagnosing pulmonary nodules compared with radiologists' diagnostic approach in computed tomography (CT) of the chest. MATERIALS AND METHODS: A total of 150 pathologically confirmed pulmonary nodules (60% malignant) assessed and reported by radiologists were included. CT images were processed by the proposed DL-based method to generate the probability of malignancy (0-100%), and the nodules were divided into the groups of benign (0-39.9%), indeterminate (40.0-59.9%), and malignant (60.0-100%). Taking the pathological results as the gold standard, we compared the diagnostic performance of the proposed DL-based method with the radiologists' diagnostic approach using the McNemar-Bowker test. RESULTS: There was a statistically significant difference between the diagnosis results of the proposed DL-based method and the radiologists' diagnostic approach (p < 0.001). Moreover, there was no statistically significant difference in the composition of the diagnosis results between the proposed DL-based method and the radiologists' diagnostic approach (all p > 0.05). The difference in diagnostic accuracy between the proposed DL-based method (70%) and radiologists' diagnostic performance (64%) was not statistically significant (p = 0.243). CONCLUSIONS: The proposed DL-based method achieved an accuracy comparable with the radiologists' diagnostic approach in clinical practice. Furthermore, its advantage in improving diagnostic certainty may raise the radiologists' confidence in diagnosing pulmonary nodules and may help clinical management. Therefore, the proposed DL-based method showed great potential in a certain clinical application. KEY POINTS: • Deep learning-based method for diagnosing the pulmonary nodules in computed tomography provides a higher diagnostic certainty.

Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation.

OBJECTIVE: To explore the natural history of pulmonary subsolid nodules (SSNs) with different pathological types by deep learning-assisted nodule segmentation. METHODS: Between June 2012 and June 2019, 95 resected SSNs with preoperative long-term follow-up were enrolled in this retrospective study. SSN detection and segmentation were performed on preoperative follow-up CTs using the deep learning-based Dr. Wise system. SSNs were categorized into invasive adenocarcinoma (IAC, n = 47) and non-IAC (n = 48) groups; according to the interval change during the preoperative follow-up, SSNs were divided into growth (n = 68), nongrowth (n = 22), and new emergence (n = 5) groups. We analyzed the cumulative percentages and pattern of SSN growth and identified significant factors for IAC diagnosis and SSN growth. RESULTS: The mean preoperative follow-up was 42.1 ± 17.0 months. More SSNs showed growth or new emergence in the IAC than in the non-IAC group (89.4% vs. 64.6%, p = 0.009). Volume doubling time was non-significantly shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days, p = 0.077). Median mass doubling time was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). Lobulated sign (p = 0.002) and SSN mass (p = 0.004) were significant factors for differentiating IACs. IACs showed significantly higher cumulative growth percentages than non-IACs in the first 70 months of follow-up. The growth pattern of SSNs may conform to the exponential model. The initial volume (p = 0.042) was a predictor for SSN growth. CONCLUSIONS: IACs appearing as SSNs showed an indolent course. The mean growth rate was larger for IACs than for non-IACs. SSNs with larger initial volume are more likely to grow. KEY POINTS: • Invasive adenocarcinomas (IACs) appearing as subsolid nodules (SSNs), with a mean volume doubling time (VDT) of 1436.0 ± 1188.2 days and median mass doubling time (MDT) of 821.7 days, showed an indolent course. • The VDT was shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days), but the difference was not significant (p = 0.077). The median MDT was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). • SSNs with lobulated sign and larger mass (> 390.5 mg) may very likely be IACs. SSNs with larger initial volume are more likely to grow.

Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning-assisted nodule segmentation.

OBJECTIVE: To investigate the natural history of persistent pulmonary pure ground-glass nodules (pGGNs) with deep learning-assisted nodule segmentation. METHODS: Between January 2007 and October 2018, 110 pGGNs from 110 patients with 573 follow-up CT scans were included in this retrospective study. pGGN automatic segmentation was performed on initial and all follow-up CT scans using the Dr. Wise system based on convolution neural networks. Subsequently, pGGN diameter, density, volume, mass, volume doubling time (VDT), and mass doubling time (MDT) were calculated automatically. Enrolled pGGNs were categorized into growth, 52 (47.3%), and non-growth, 58 (52.7%), groups according to volume growth. Kaplan-Meier analyses with the log-rank test and Cox proportional hazards regression analysis were conducted to analyze the cumulative percentages of pGGN growth and identify risk factors for growth. RESULTS: The mean follow-up period of the enrolled pGGNs was 48.7 ± 23.8 months. The median VDT of the 52 pGGNs having grown was 1448 (range, 339-8640) days, and their median MDT was 1332 (range, 290-38,912) days. The 12-month, 24.7-month, and 60.8-month cumulative percentages of pGGN growth were 10%, 25.5%, and 51.1%, respectively, and they significantly differed among the initial diameter, volume, and mass subgroups (all p < 0.001). The growth pattern of pGGNs may conform to the exponential model. Lobulated sign (p = 0.044), initial mean diameter (p < 0.001), volume (p = 0.003), and mass (p = 0.023) predicted pGGN growth. CONCLUSIONS: Persistent pGGNs showed an indolent course. Deep learning can assist in accurately elucidating the natural history of pGGNs. pGGNs with lobulated sign and larger initial diameter, volume, and mass are more likely to grow. KEY POINTS: • The pure ground-glass nodule (pGGN) segmentation accuracy of the Dr. Wise system based on convolution neural networks (CNNs) was 96.5% (573/594). • The median volume doubling time (VDT) of 52 pure ground-glass nodules (pGGNs) having grown was 1448 days (range, 339-8640 days), and their median mass doubling time (MDT) was 1332 days (range, 290-38,912 days). The mean time to growth in volume was 854 ± 675 days (range, 116-2856 days). • The 12-month, 24.7-month, and 60.8-month cumulative percentages of pGGN growth were 10%, 25.5%, and 51.1%, respectively, and they significantly differed among the initial diameter, volume, and mass subgroups (all p values < 0.001). The growth pattern of pure ground-glass nodules may conform to exponential model.

Dual-energy spectral CT characteristics in surgically resected lung adenocarcinoma: comparison between Kirsten rat sarcoma viral oncogene mutations and epidermal growth factor receptor mutations.

BACKGROUND: Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) are the two most frequent and well-known oncogene of lung adenocarcinoma. The purpose of this study is to compare the characteristics measured with dual-energy spectral computed tomography (DESCT) in lung adenocarcinoma patients who have KRAS and EGFR gene mutations. METHODS: Patients with surgically resected lung adenocarcinoma (n = 72) were enrolled, including 12 patients with KRAS mutations and 60 patients with EGFR mutations. DESCT quantitative parameters, including the CT number at 70 keV, the slopes of the spectral attenuation curves (slope λ HU), normalized iodine concentration (NIC), normalized water concentration (NWC), and effective atomic number (effective Z), were analyzed. A multiple logistic regression model was applied to discriminate clinical and DESCT characteristics between the types of mutations. RESULTS: The KRAS mutation was more common in people who smoked than the EGFR mutation. Nodule type differed significantly between the KRAS and EGFR groups (P = 0.035), and all KRAS mutation adenocarcinomas were solid nodules. Most DESCT quantitative parameters differed significantly between solid nodules and subsolid nodules. CT number at 70 keV, slope λ HU, NIC, and effective Z differed significantly between the KRAS and EGFR groups (P = 0.006, 0.017, 0.013 and 0.010) with solid lung adenocarcinoma. Multivariate logistic analysis of DESCT and clinical features indicated that besides smoking history, the CT value at 70 keV (OR = 0.938, P = 0.009) was significant independent factor that could be used to differentiate KRAS and EGFR mutations in solid lung adenocarcinoma. CONCLUSIONS: DESCT would be a potential tool to differentiate lung adenocarcinoma patients with a KRAS mutation from those with an EGFR mutation.

Quantitative features of dual-energy spectral computed tomography for solid lung adenocarcinoma with EGFR and KRAS mutations, and ALK rearrangement: a preliminary study.

BACKGROUND: The present work aimed to evaluate radio-genomic associations of quantitative parameters obtained by dual-energy spectral computed tomography (DESCT) for solid lung adenocarcinoma with epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations, as well as anaplastic lymphoma kinase (ALK) rearrangement. METHODS: Ninety-six cases of solid lung cancer were selected and assessed for EGFR and KRAS mutations, and ALK rearrangement. Then, they underwent chest DESCT, and quantitative parameters, including water concentration (WC), iodine concentration (IC), CT value at 70 keV, effective atomic number (Effective-Z) and spectral Hounsfield unit curve slope (λHU slope) were measured. Finally, the associations of quantitative radiological features with various gene alterations were evaluated. RESULTS: The positive rates were 51.0% (49/96) for EGFR, 13.5% (13/96) for KRAS and 16.7% (16/96) for ALK. In univariate analysis, EGFR mutation was associated with smoking status, CT value at 70 keV, IC, Effective-Z, and λHU slope; KRAS mutation was associated with CT value at 70 keV, IC, Effective-Z, and λHU slope, and ALK rearrangement was correlated with age and WC. In multivariate analysis, smoking status (OR =2.924, P=0.019) and CT value at 70 keV (OR =1.036, P=0.006) were significantly associated with EGFR mutation; Effective-Z and age were significantly associated with KRAS mutation (OR =0.047, P=0.032) and ALK rearrangement (OR =0.933, P=0.008), respectively. CONCLUSIONS: Quantitative analysis of DESCT could help detect solid lung adenocarcinoma harboring EGFR or KRAS mutation, or ALK rearrangement.

Identification of epidermal growth factor receptor mutations in pulmonary adenocarcinoma using dual-energy spectral computed tomography.

OBJECTIVES: To explore the role of dual-energy spectral computed tomography (DESCT) quantitative characteristics for the identification of epidermal growth factor receptor (EGFR) mutation status in a cohort of East Asian patients with pulmonary adenocarcinoma. MATERIALS AND METHODS: Patients with lung adenocarcinoma who underwent both DESCT chest examination and EGFR test were retrospectively selected from our institution's database. The DESCT visual morphological features and quantitative parameters, including the CT number at 70 keV, normalized iodine concentration (NIC), normalized water concentration, and slopes of the spectral attenuation curves (slope λ HU [Hounsfield unit]), were evaluated or calculated. The patients were divided into two groups: the EGFR mutation group and EGFR wild-type group. Statistical analyses were performed to identify the DESCT quantitative parameters for diagnosis of EGFR mutation status. RESULTS: EGFR mutations were detected in 66 (55.0%) of the 120 enrolled patients. The univariate analysis revealed that sex, smoking history, CT texture, NIC, and slope λ HU were significantly associated with EGFR mutation status (p = 0.037, 0.001, 0.047, 0.010, and 0.018, respectively). The multivariate logistic analysis revealed that smoking history (odds ratio [OR] = 3.23, p = 0.005) and NIC (OR = 58.026, p = 0.049) were the two significant predictive factors associated with EGFR mutations. Based on this analysis, the smoking history and NIC were combined to determine the predictive value for EGFR mutations with the area under the curve of 0.702. CONCLUSIONS: NIC may be a potential quantitative DESCT parameter for predicting EGFR mutations in patients with pulmonary adenocarcinoma. KEY POINTS: • DESCT can provide multiple quantitative image parameters compared to conventional CT. • Identification of the radio-genomic relation between DESCT and EGFR status can help to define molecular subcategories of lung adenocarcinoma, which is valuable for personalized clinical targeted therapy. • NIC may be a potential DESCT quantitative parameter for predicting EGFR mutations in pulmonary adenocarcinoma.

Marine phytoplankton motility sensor integrated into a microfluidic chip for high-throughput pollutant toxicity assessment.

A microfluidic chip was designed to assess the toxicity of pollutants in a high-throughput way by using marine phytoplankton motility as a sensor signal. In this chip, multiple gradient generators (CGGs) with diffusible chambers enable large scale of dose-response bioassays to be performed in a simple way. Two mobile marine phytoplankton cells were confined on-chip and stimulated by 8 concentrations (generated by CGG) of Hg, Pb, Cu and phenol singly, as well as Cu and phenol jointly. CASA system was used to characterize motility by motile percentage (%MOT), curvilinear velocity (VCL), average path velocity (VAP) and straight line velocity (VSL). In all cases, dose-dependent inhibitions of motility were observed. In the present system, only 2h was needed to predict EC50. Thus, the developed microfluidic chip device was proved to be useful as a rapid/simple and high-throughput test method in marine pollution toxicity assessment.

[Genetic screening and analysis of suppressors of asa1-1 (soa) defective in jasmonate-mediated lateral root formation in Arabidopsis].

It has been shown that jasmonate modulates the lateral root development through crosstalk with auxin in Arabidopsis thaliana. Exogenous application of jasmonate stimulates lateral root formation in wild type but inhibits lateral root formation in asa1-1. Our previous work has demonstrated that the lateral root formation defect of asa1-1 is co-related with jasmonte effect on PIN2 protein levels. To further elucidate the molecular mechanisms underlying jasmonate-mediated reduction of plasma membrane (PM)-resident PIN2 abundance, we have conducted a genetic screen to identify suppressors of asa1-1 (soa), which showed lateral root formation in the presence of jasmonate. Here, we described the basic characterization of soa563 and soa856. We showed that both soa563 and soa856 displayed restored lateral root formation in response to exogenous jasmonate. In addition, jasmonate-induced PIN2:GFP reduction was blocked in these two mutants. Our on-going effort to identify genes defined by these mutants promise to shed new light on the understanding of the molecular mechanisms controlling jasmonate-mediated regulation of PIN2 protein trafficking and turnover.

Cytotoxicity, apoptosis-inducing effects and structure-activity relationships of four natural xanthones from Gentianopsis paludosa Ma in HepG2 and HL-60 cells.

Four xanthones were isolated from Gentianopsis paludosa Ma and were identified by modern spectroscopic methods. Cytotoxicity of the four xanthones was tested on HepG2 cells and HL-60 cells by sulphorhodamine B (SRB) assay. Clonogenic survival assay, trypan blue exclusion method, AO/EB staining and DNA fragmentation assay were conducted to investigate the effect on growth inhibition and apoptosis in the two cell lines in vitro. At the same time, structure-activity relationships (SARs) of the xanthones were investigated. The results showed that the xanthones had significant cytotoxicity and inhibition of proliferation in both HepG2 cells and HL-60 cells, and could induce apoptosis in these two cell lines. SARs indicated that the methoxy group had more cytotoxic contribution than the hydroxyl group at site C-8 in the structural scaffold of xanthone. The glycosidea at site C-1 may aggravate the stereospecific blockade of compound 4 and reduced its cytotoxic activity.

Anti-proliferation, cell cycle arrest and apoptosis induced by a natural xanthone from Gentianopsis paludosa Ma, in human promyelocytic leukemia cell line HL-60 cells.

1-hydroxy-3,7,8-trimethoxyxanthone (xanthone 1) was isolated from Gentianopsis paludosa Ma and identified by MS and NMR in our laboratory. In this study, the results showed that xanthone 1 is a potent inducer of anti-proliferation and apoptosis in HL-60 cells. When the cells treated with lower concentrations of xanthone 1 (12.4-74.4microM), significant proliferation inhibition was detected by cell viability assay and morphological analyses, and conspicuous G1 and G2/M cell cycle arrest were observed by flow cytometric (FCM) analysis. However, when the cells treated with higher doses of xanthone 1 (82.7-330.8microM), significant apoptosis was observed by double sequential AO/EB staining, DNA fragmentation assay and FCM analysis. In addition, conspicuous DNA damage was detected by comet assay. In short, all the results showed that xanthone 1 had a significant cytotoxic effect and could induce proliferation inhibition and apoptosis in HL-60 cells in a time- and dose-dependent manner. It was possible that xanthone 1 could induce DNA damage in HL-60 cells, which resulted in G1 phase arrest at the lower concentrations and G2/M phase arrest at the higher concentrations, thus inhibiting the cell proliferation, and irreparable DNA damage at the higher concentrations might be responsible for the occurrence of apoptosis.