Id1 expression in CD4 T cells promotes differentiation and function of follicular helper T cells and upregulation of related functional molecules.

Although the roles of E proteins and inhibitors of DNA-binding (Id) in T follicular helper (TFH) and T follicular regulatory (TFR) cells have been previously reported, direct models demonstrating the impact of multiple E protein members have been lacking. To suppress all E proteins including E2A, HEB and E2-2, we overexpressed Id1 in CD4 cells using a CD4-Id1 mouse model, to observe any changes in TFH and TFR cell differentiation. Our objective was to gain better understanding of the roles that E proteins and Id molecules play in the differentiation of TFH and TFR cells. The CD4-Id1 transgenic (TG) mice that we constructed overexpressed Id1 in CD4 cells, inhibiting E protein function. Our results showed an increase in the proportion and absolute numbers of Treg, TFH and TFR cells in the spleen of TG mice. Additionally, the expression of surface characterisation molecules PD-1 and ICOS was significantly upregulated in TFH and TFR cells. The study also revealed a downregulation of the marginal zone B cell precursor and an increase in the activation and secretion of IgG1 in spleen B cells. Furthermore, the peripheral TFH cells of TG mice enhanced the function of assisting B cells. RNA sequencing results indicated that a variety of TFH-related functional molecules were upregulated in TFH cells of Id1 TG mice. In conclusion, E proteins play a crucial role in regulating TFH/TFR cell differentiation and function and suppressing E protein activity promotes germinal centre humoral immunity, which has important implications for immune regulation and treating related diseases.

VNN2-expressing circulating monocytes exhibit unique functional characteristics and are decreased in patients with primary Sjögren's syndrome.

OBJECTIVE: This study aims to elucidate the significance of VNN2 expression in peripheral blood monocytes and its clinical relevance in primary Sjögren's syndrome (pSS). METHODS: We investigated VNN2 expression by analyzing single-cell RNA sequencing (scRNA-seq) data from peripheral blood mononuclear cells. Flow cytometry was used to detect and compare VNN2 expression in total monocytes, classical monocytes (cMo), intermediate monocytes (iMo) and non-classical monocytes (ncMo). Additionally, we examined the expression of HLA, ICAM1, CD62L, ITGAM, S100A8, S100A9, CCR2, CCR6, CX3CR1 and CXCR3 in VNN2+ and VNN2- cells. We analyzed the correlation between VNN2 expression and clinical indicators and assessed the clinical utility of VNN2+ monocytes in pSS diagnosis using receiver operating characteristic curves. RESULTS: We observed high VNN2 expression in monocytes, with significantly higher levels in CD14++ monocytes compared to ncMo. VNN2+ monocytes exhibited decreased expression of HLA and CD62L and increased expression of ICAM1, ITGAM, S100A8, S100A9, CCR2, CCR6, CX3CR1 and CXCR3 compared to VNN2- monocytes. Although scRNA-seq data showed that VNN2 mRNA was upregulated, cell surface expression of VNN2 was decreased in monocytes from pSS patients compared to healthy controls. The reduced levels of VNN2+ monocyte subpopulations in pSS patients were negatively correlated with anti-ribosome antibody levels and positively correlated with complement 4 levels. Detection of VNN2 expression in monocytes can aid in the auxiliary diagnosis of pSS. CONCLUSION: Monocytes expressing cell surface VNN2 are significantly reduced in pSS patients. This suggests a potential role for VNN2 in pSS development and its potential use as a diagnostic marker for pSS.

Evaluation of Left Ventricular Flow Kinetic Energy by Four-Dimensional Blood Flow MRI in Nondialysis Chronic Kidney Disease Patients.

BACKGROUND: Chronic kidney disease (CKD) is associated with increased, and early cardiovascular disease risk. Changes in hemodynamics within the left ventricle (LV) respond to cardiac remodeling. The LV hemodynamics in nondialysis CKD patients are not clearly understood. PURPOSE: To use four-dimensional blood flow MRI (4D flow MRI) to explore changes in LV kinetic energy (KE) and the relationship between LV KE and LV remodeling in CKD patients. STUDY TYPE: Retrospective. POPULATION: 98 predialysis CKD patients (Stage 3: n = 21, stage 4: n = 21, and stage 5: n = 56) and 16 age- and sex-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady-state free precession (SSFP) cine sequence, 4D flow MRI with a fast field echo sequence, T1 mapping with a modified Look-Locker SSFP sequence, and T2 mapping with a gradient recalled and spin echo sequence. ASSESSMENT: Demographic characteristics (age, sex, height, weight, blood pressure, heart rate, aortic regurgitation, and mitral regurgitation) and laboratory data (eGFR, Creatinine, hemoglobin, ferritin, transferrin saturation, potassium, and carbon dioxide bonding capacity) were extracted from patient records. Myocardial T1, T2, LV ejection fraction, end diastolic volume (EDV), end systolic volume, LV flow components (direct flow, delayed ejection, retained inflow, and residual volume) and KE parameters (peak systolic, systolic, diastolic, peak E-wave, peak A-wave, E/A ratio, and global) were assessed. The KE parameters were normalized to EDV (KEiEDV). Parameters were compared between disease stage in CKD patients, and between CKD patients and healthy controls. STATISTICAL TESTS: Differences in clinical and imaging parameters between groups were compared using one-way ANOVA, Kruskal Walls and Mann-Whitney U tests, chi-square test, and Fisher's exact test. Pearson or Spearman's correlation coefficients and multiple linear regression analysis were used to compare the correlation between LV KE and other clinical and functional parameters. A P-value of <0.05 was considered significant. RESULTS: Compared with healthy controls, peak systolic (24.76 ± 5.40 µJ/mL vs. 31.86 ± 13.18 µJ/mL), systolic (11.62 ± 2.29 µJ/mL vs. 15.27 ± 5.10 µJ/mL), diastolic (7.95 ± 1.92 µJ/mL vs. 13.33 ± 5.15 µJ/mL), peak A-wave (15.95 ± 4.86 µJ/mL vs. 31.98 ± 14.51 µJ/mL), and global KEiEDV (9.40 ± 1.64 µJ/mL vs. 14.02 ± 4.14 µJ/mL) were significantly increased and the KEiEDV E/A ratio (1.16 ± 0.67 vs. 0.69 ± 0.53) was significantly decreased in CKD patients. As the CKD stage progressed, both diastolic KEiEDV (10.45 ± 4.30 µJ/mL vs. 12.28 ± 4.85 µJ/mL vs. 14.80 ± 5.06 µJ/mL) and peak E-wave KEiEDV (15.30 ± 7.06 µJ/mL vs. 14.69 ± 8.20 µJ/mL vs. 19.33 ± 8.29 µJ/mL) increased significantly. In multiple regression analysis, global KEiEDV (ß* = 0.505; ß* = 0.328), and proportion of direct flow (ß* = -0.376; ß* = -0.410) demonstrated an independent association with T1 and T2 times. DATA CONCLUSION: 4D flow MRI-derived LV KE parameters show altered LV adaptations in CKD patients and correlate independently with T1 and T2 mapping that may represent myocardial fibrosis and edema. TECHNICAL EFFICACY: Stage 3.

Predictive value of left atrial strain analysis in adverse clinical events in patients with hypertrophic cardiomyopathy: a CMR study.

BACKGROUND: A subset of patients with hypertrophic cardiomyopathy (HCM) will experience adverse clinical events such as heart failure (HF), cardiovascular death, and new-onset atrial fibrillation (AF). Current risk stratification methods are imperfect and limit the identification of patients at high risk for HCM. This study aimed to evaluate the role of cardiac magnetic resonance (CMR)-derived left atrial strain parameters in the occurrence of adverse clinical events in patients with HCM. METHODS: Left atrial (LA) structural, functional, and strain parameters were evaluated in 99 patients with HCM and compared with 89 age-, sex-, and BMI-matched control subjects. LA strain parameters were derived from CMR two- and four-chamber cine images by a semiautomatic method. LA strain parameters include global longitudinal strain (GLS) and global circumferential strain (GCS). The LA GLS includes reservoir strain (GLS reservoir), conduit strain (GLS conduit), and booster strain (GLS booster). Three LA GLS strain rate (SR) parameters were derived: SR reservoir, SR conduit, and SR booster. The primary endpoint was set as a composite of adverse clinical events, including SCD, new-onset or worsening to hospitalized HF, new-onset AF, thromboembolic events, and fatal ventricular arrhythmias. RESULTS: LA GLS, GLS SR and GCS were impaired in HCM patients compared to control subjects (all p < 0.001). After a mean follow-up of 37.94 ± 23.69 months, 18 HCM patients reached the primary endpoint. LA GLS, GLS SR, and GCS were significantly lower in HCM patients with adverse clinical events than in those without adverse clinical events (all p < 0.05). In stepwise multiple Cox regression analysis, LV SV, LA diameter, pre-contraction LAV (LAV pre-ac), passive LA ejection fraction (EF), and LA GLS booster were all independent determinants of adverse clinical events. LA GLS booster ≤ 8.9% was the strongest determinant (HR = 8.9 [95%CI (1.951, 40.933)], p = 0.005). Finally, LA GLS booster provided predictive adverse clinical events value (AUC = 0.86 [95%CI 0.77-0.98]) that exceeded traditional outcome predictors. CONCLUSION: LA strain assessment, a measure of LA function, provides additional predictive information for established predictors of HCM patients. LA GLS booster was independently associated with adverse clinical events in patients with HCM.

Pathological components and CT imaging analysis of the area adjacent pleura within the pure ground-glass nodules with pleural deformation in invasive lung adenocarcinoma.

BACKGROUND: Pleural deformation is associated with the invasiveness of lung adenocarcinoma(LAC). Our study focused on the pathological components of the area adjacent pleura in pulmonary pure ground-glass nodules(pGGNs) with pleural deformations(P-pGGNs) confirmed to be invasive LAC without visceral pleural invasion (VPI) pathologically. METHODS: Computed tomography(CT) imaging features of nodules and pathological components of the area adjacent pleura were analyzed and recorded. Statistical analysis was performed for subgroups of P-pGGNs. RESULTS: The 81 enrolled patients with 81 P-pGGNs were finally involved in the analysis. None of solid/micropapillary group and none of VPI was observed, 54 alveoli/lepidics and 27 acinar/papillarys were observed. In P-pGGN with acinar/papillary components of the area adjacent pleura, invasive adenocarcinoma (IAC) was more common compared to minimally invasive adenocarcinoma (MIA, 74.07% vs. 25.93%; p < 0.001). The distance in alveoli/lepidic group was significantly larger (1.50 mm vs. 0.00 mm; p < 0.001) and the depth was significantly smaller (2.00 mm vs. 6.00 mm; p < 0.001) than that in acinar/papillary group. The CT attenuation value, maximum diameter and maximum vertical diameter was valuable to distinguish acinar/papillary group form alveoli/lepidic group(p < 0.05). The type d pleural deformation was the common pleural deformation in IAC(p = 0.028). CONCLUSIONS: The pathological components of the area adjacent pleura in P-pGGN without VPI confirmed to be invasive LAC could included alveoli/lepidics and acinar/papillarys. Some CT indicators that can identify the pathological invasive components of the area adjacent pleura in P-pGGNs.

KLRB1 defines an activated phenotype of CD4+ T cells and shows significant upregulation in patients with primary Sjögren's syndrome.

OBJECTIVE: This study aimed to investigate the role of KLRB1 (CD161) in human CD4+ T cells and elucidate its significance in primary Sjögren's syndrome (pSS). METHODS: Peripheral blood samples from 37 healthy controls and 44 pSS patients were collected. The publicly available single-cell RNA-Seq data from pSS patient PBMCs were utilized to analyse KLRB1 expression in T cells. KLRB1-expressing T lymphocyte subset proportions in pSS patients and healthy controls were determined by flow cytometry. CD25, Ki-67, cytokine secretion, and chemokine receptor expression in CD4+ KLRB1+ T cells were detected and compared with those in CD4+ KLRB1- T cells. Correlation analysis was conducted between KLRB1-related T-cell subsets and clinical indicators. ROC curves were generated to explore the diagnostic potential of KLRB1 for pSS. RESULTS: KLRB1 was significantly upregulated following T-cell activation, and Ki-67 and CD25 expression was significantly greater in CD4+ KLRB1+ T cells than in CD4+ KLRB1- T cells. KLRB1+ CD4+ T cells exhibited greater IL-17A, IL-21, IL-22, and IFN-γ secretion upon stimulation, and there were significantly greater proportions of CCR5+, CCR2+, CX3CR1+, CCR6+, and CXCR3+ cells among CD4+ KLRB1+ T cells than among CD4+ KLRB1- T cells. Compared with that in HCs, KLRB1 expression in CD4+ T cells was markedly elevated in pSS patients and significantly correlated with clinical disease indicators. CONCLUSION: KLRB1 is a characteristic molecule of the CD4+ T-cell activation phenotype. The increased expression of KLRB1 in the CD4+ T cells of pSS patients suggests its potential involvement in the pathogenesis of pSS and its utility as an auxiliary diagnostic marker for pSS.

SIT1 identifies circulating hypoactive T cells with elevated cytotoxic molecule secretion in systemic lupus erythematosus patients.

This study aims to elucidate the expression and functionality of SIT1 in circulating CD8/CD4 + T cells in humans and to delineate its significance in systemic lupus erythematosus (SLE) patients. We employed multiparametric flow cytometry to investigate the expression of SIT1 in circulating CD8/CD4 + T cells and their respective subsets, comparing healthy controls (HCs) with SLE patients. Furthermore, we assessed the levels of granzyme B, perforin, IL-17, and IFN-γ in SIT1-related CD8/CD4 + T cells from both HCs and SLE patients, both before and after PMA stimulation. Clinically, we conducted receiver operating characteristic curve analysis and correlation analysis to evaluate the clinical relevance of SIT1-related CD8/CD4 + T cells in SLE patients. SIT1 exhibited higher expression in CD4 + T cells, with SIT1 - T cells demonstrating elevated levels of granzyme B, perforin, and IFN-γ compared to SIT1 + T cells. PMA-stimulated T cells exhibited reduced SIT1 expression compared to unstimulated T cells. SLE patients displayed increased SIT1 + proportions in CD8 + T cells and decreased SIT1 + CD4 + T cell numbers. Additionally, SIT1 + cells in SLE patients exhibited significantly higher levels of granzyme B and perforin compared to HCs. SIT1 + cells demonstrated significant associations with clinical indicators in SLE patients, with indicators related to SIT1 proving valuable in the diagnosis of SLE patients. SIT1 is inversely correlated with T cell activation. In SLE patients, SIT1 expression is altered in T cells concomitant with an augmented secretion of cytotoxic molecules. This upregulation may contribute to the pathogenesis of SLE and enhance its diagnostic potential.

Circulating CD8 + LGALS9 + T Cell Population Exhibiting Low Cytotoxic Characteristics are Decreased in Patients with Systemic Lupus Erythematosus.

LGALS9, also known as Galectin-9 and a member of the ß-galactosidase family, plays a crucial role in immune regulation. However, its expression and function in CD8 T cells, as well as its association with cytotoxic T lymphocytes (CTL), remain unclear. This study aims to investigate LGALS9 expression patterns in human circulating CD8 T lymphocytes and elucidate its clinical significance in Systemic Lupus Erythematosus (SLE). Blood samples from 56 healthy controls and 50 new-onset SLE patients were collected. Flow cytometry was utilized to analyze LGALS9 expression in circulating CD8 T lymphocytes via intracellular staining. Compared to LGALS9 + CD8 + T cells, LGALS9-CD8 + T cells showed increased secretion of Granzyme B (GZMB) and Perforin, along with elevated expression levels of GPR56, CX3CR1, KLRD1, KLRF1, PD1, and CD29. A higher proportion of Tn (naive T cells) and TCM (central memory T cells) showed LGALS9 positivity, compared to TEM (effector memory T cells) and TEMRA (terminally differentiated effector memory T cells re-expressing CD45RA). Clinically, the downregulation of LGALS9 expression was significant in SLE patients. LGALS9 + CD8 + T cells exhibited an Area Under the Curve (AUC) of 0.6916, while CX3CR1 + in LGALS9 + CD8 + T cells had an AUC of 0.6478, and KLRF1 + had an AUC of 0.6419, for distinguishing SLE from healthy individuals. In conclusion, CD8 + LGALS9 + T cells display characteristics of low cytotoxicity, and their reduction is evident in SLE patients, potentially implicating them in SLE pathogenesis and providing diagnostic assistance.

Natural progression of persistent pure ground-glass nodules 10 mm or smaller: long-term observation and risk factor assessment.

PURPOSE: Semi-automatic segmentation was used to investigate the natural progression of pure ground-glass nodules (pGGNs) of 5-10 mm in long-term follow-up and to analyze independent risk factors for subsequent growth. MATERIALS AND METHODS: A total of 154 pGGNs of 5-10 mm from 132 patients with 698 follow-up CT scans were retrospectively identified. Subsequently, enrolled pGGNs were semiautomatically segmented on initial and follow-up CT to obtain diameter, density and volume, thus calculating mass, volume doubling time (VDT), and mass doubling time (MDT). Kaplan‒Meier analysis and multivariate Cox proportional risk regression were performed to explore independent predictors of pGGN growth. We analyzed growth differences among different pathological results of pGGNs confirmed by surgery. The prognosis was analyzed using the total diameter or solid size of the nodules on the last preoperative CT. RESULTS: Among the 85 (55.2%) pGGNs with growth, 5.9%, 51.8%, and 80.0% showed growth within 1, 3, and 5 years, respectively. The median VDT and MDT were 1206.4 (range 349.8-5134.4) days and 1161.3 (range 339.4-6630.4) days, respectively. The multivariate Cox risk regression analysis showed that mean CT attenuation (m-CTA) [hazard ratio (HR) = 2.098, p = 0.010] and roundness index (HR = 1.892, p = 0.021) were independent risk factors for pGGN growth. In total, 67.6% of surgically resected and growing pGGNs were invasive non-mucinous adenocarcinoma (IA), including 2 cases of endpoint events, showing a PSN with solid components of 5.6 mm and a solid nodule with a diameter of 19.9 mm. CONCLUSIONS: pGGNs of 5-10 mm showed an indolent clinical course. Follow-up CT imaging of pGGNs in the latter half of the first two years should be a rational management strategy. Small pGGNs with a larger overall m-CTA and roundness index on baseline CT are more likely to grow.

Compressed sensing cine imaging with higher temporal resolution for analysis of left atrial strain and strain rate by cardiac magnetic resonance feature tracking.

PURPOSE: Cardiac magnetic resonance (CMR) feature tracking (FT) is more widely used in the measurement of left atrial (LA) strain and strain rate (SR). However, in recent years, researchers have attempted to improve the low temporal resolution of CMR-FT to better capture the subtle deformations of the myocardium. The technique of compressed sensing (CS) has been applied clinically, reducing scan time while increasing temporal resolution. The purpose of this study was to explore the effect of the increased temporal resolution of CS cine sequences on the analysis of LA longitudinal strain and SR. MATERIALS AND METHODS: Twenty-nine healthy subjects were included in the study. They underwent CMR with a reference steady-state free precession cine sequence of conventional temporal resolution (standard SSFP sequence), a cine sequence of higher temporal resolution (HT sequence), and an HT cine sequence with CS (CS HT sequence) (temporal resolution: 22.1-44.3/24.9-47.1 ms, 11.1-19.4 ms, and 8.3-19.4 ms, respectively). The standard SSFP sequence, HT sequence, and CS HT sequence were acquired in all subjects during the same scanning session. LA longitudinal strain and SR, reflecting LA reservoir, conduit, and contraction booster-pump function, were measured by CMR-FT and compared among the three sequences. RESULTS: The measurements of LASR reservoir, conduit, and booster-pump were significantly higher on the HT and CS HT sequences than on the standard SSFP sequence. The standard SSFP sequence was correlated significantly with the HT and CS HT sequences in terms of LA strain and SR analysis, respectively. The LA strain and SR measurements also showed excellent agreement between the HT and CS HT sequences. CONCLUSION: Higher temporal resolution led to significantly higher measured LASR values in CMR-FT. Furthermore, the addition of CS reduced scan time and did not affect LA longitudinal strain or SR analysis.

Invasiveness identification in pure ground-glass nodules: exploring the generalizability of radiomics based on external validation and stress testing.

PURPOSE: This study aimed to apply external validation and stress tests to evaluate the generalizability of radiomics models built using various machine-learning methods for identifying the invasiveness of lung adenocarcinomas manifesting as pure ground-glass nodules (pGGNs). METHODS: This retrospective study enrolled 495 patients (514 pGGNs) confirmed as lung adenocarcinomas by postoperative pathology from three centers. All nodules were included in the primary cohort (randomly divided into training and test cohorts), two external validation cohorts, and two stress test cohorts. Six machine-learning radiomics models were constructed in the training cohort using the optimal features. Performance of radiomics models and clinical models were compared in primary cohort and external validation cohorts. The stress tests included stratified performance evaluation and shifted performance evaluation and contrastive evaluation under three single-condition modification settings. The predictive performance was validated by area under curve (AUC) of receiver operating characteristic (ROC). RESULTS: Of the six radiomics models, the best logistic regression (LR) model was able to maintain high differential diagnostic capability (AUC: 0.849 ± 0.049) and good stability (relative standard deviation, 5.719%), but it showed poorer performance (AUC = 0.835) than the clinical model (AUC = 0.862) in the external validation cohort E1. The stress tests suggested LR model had no significant difference in performance between subgroups after stratification and had good consistency in the predictions before and after the three transformations (Kappa = 0.960, 0.840, and 0.933, respectively; p < 0.05, all). CONCLUSION: The rigorous testing procedure facilitates the selection of high-performance radiomics models with good clinical generalizability.

Growth assessment of pure ground-glass nodules on CT: comparison of density and size measurement methods.

PURPOSE: To investigate the differences of size and density measurements in assessing pure ground-glass nodules (pGGNs) growth, and compare the growth rates and growth proportions of the two methods during follow-up period. METHODS: Ninety patients with at least 3 consecutive thin-section chest CTs and confirmed 103 pGGNs on baseline CT were enrolled retrospectively. Using the two definitions of size and density to evaluate pGGNs growth with semi-automated segmentation. Then, the two methods were compared to assess differences in pGGNs growth. RESULTS: For the size and density methods to assess nodule growth, 50.5% and 26.2% showed interval growth at the last CT (p < 0.001). Among the 19 nodules that grew in both size and density, the volume doubling time (VDT) of solid component (mean, 317.1; standard deviation, 224.8 days) was shorter than total VDT (median, 942.8; range, 400.1-2315.9 days) (p < 0.001). Of the 27 growth pGGNs assessed by the density method, the growth rates at years 1 and 2 were 25.9% and 63.0%, while the growth rates of 52 growing nodules assessed by size method were 11.5% and 48.1%, respectively. Twenty of 103 (19.4%) nodules were classified into category 4A lesions, and 7 (6.8%) were 4B lesions. CONCLUSION: Compared to size measurements, observed density increases have a higher proportion of early growth and faster growth rates in growing nodules. Clinicians need to pay close attention to the nodules of new solid components and make timely decision management.

Radiomics based on enhanced CT for differentiating between pulmonary tuberculosis and pulmonary adenocarcinoma presenting as solid nodules or masses.

PURPOSE: To investigate the incremental value of enhanced CT-based radiomics in discriminating between pulmonary tuberculosis (PTB) and pulmonary adenocarcinoma (PAC) presenting as solid nodules or masses and to develop an optimal radiomics model. METHODS: A total of 128 lesions (from 123 patients) from three hospitals were retrospectively analyzed and were randomly divided into training and test datasets at a ratio of 7:3. Independent predictors in subjective image features were used to develop the subjective image model (SIM). The plain CT-based and enhanced CT-based radiomics features were screened by the correlation coefficient method, univariate analysis, and the least absolute shrinkage and selection operator, then used to build the plain CT radiomics model (PRM) and enhanced CT radiomics model (ERM), respectively. Finally, the combined model (CM) combining PRM and ERM was established. In addition, the performance of three radiologists and one respiratory physician was evaluated. The areas under the receiver operating characteristic curve (AUCs) were used to assess the performance of each model. RESULTS: The differential diagnostic capability of the ERM (training: AUC = 0.933; test: AUC = 0.881) was better than that of the PRM (training: AUC = 0.861; test: AUC = 0.756) and the SIM (training: AUC = 0.760; test: AUC = 0.611). The CM was optimal (training: AUC = 0.948; test: AUC = 0.917) and outperformed the respiratory physician and most radiologists. CONCLUSIONS: The ERM was more helpful than the PRM for identifying PTB and PAC that present as solid nodules or masses, and the CM was the best.

Radiomics for identifying lung adenocarcinomas with predominant lepidic growth manifesting as large pure ground-glass nodules on CT images.

PURPOSE: To explore the value of radiomics in the identification of lung adenocarcinomas with predominant lepidic growth in pure ground-glass nodules (pGGNs) larger than 10 mm. METHODS: We retrospectively analyzed CT images of 204 patients with large pGGNs (≥ 10 mm) pathologically diagnosed as minimally invasive adenocarcinomas (MIAs), lepidic predominant adenocarcinomas (LPAs), and non-lepidic predominant adenocarcinomas (NLPAs). All pGGNs in the two groups (MIA/LPA and NLPA) were randomly divided into training and test cohorts. Forty-seven patients from another center formed the external validation cohort. Baseline features, including clinical data and CT morphological and quantitative parameters, were collected to establish a baseline model. The radiomics model was built with the optimal radiomics features. The combined model was developed using the rad_score and independent baseline predictors. The performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) and compared using the DeLong test. The differential diagnosis performance of the models was compared with three radiologists (with 20+, 10+, and 3 years of experience) in the test cohort. RESULTS: The radiomics (training AUC: 0.833; test AUC: 0.804; and external validation AUC: 0.792) and combined (AUC: 0.849, 0.820, and 0.775, respectively) models performed better for discriminating than the baseline model (AUC: 0.756, 0.762, and 0.725, respectively) developed by tumor location and mean CT value of the whole nodule. The DeLong test showed that the AUCs of the combined and radiomics models were significantly increased in the training cohort. The highest AUC value of the radiologists was 0.600. CONCLUSION: The application of CT radiomics improved the identification performance of lung adenocarcinomas with predominant lepidic growth appearing as pGGNs larger than 10 mm.

The adding value of contrast-enhanced CT radiomics: Differentiating tuberculosis from non-tuberculous infectious lesions presenting as solid pulmonary nodules or masses.

Purpose: To compare the value of contrast-enhanced CT (CECT) and non-contrast-enhanced CT (NCECT) radiomics models in differentiating tuberculosis (TB) from non-tuberculous infectious lesions (NTIL) presenting as solid pulmonary nodules or masses, and develop a combine radiomics model (RM). Materials and methods: This study was a retrospective analysis of 101 lesions in 95 patients, including 49 lesions (from 45 patients) in the TB group and 52 lesions (from 50 patients) in the NTIL group. Lesions were randomly divided into training and test sets in the ratio of 7:3. Conventional imaging features were used to construct a conventional imaging model (IM). Radiomics features screening and NCECT or CECT RM construction were carried out by correlation analysis and gradient boosting decision tree, and logistic regression. Finally, conventional IM, NCECT RM, and CECT RM were used for combine RM construction. Additionally, we recruited three radiologists for independent diagnosis. The differential diagnostic performance of each model was assessed using the areas under the receiver operating characteristic curve (AUCs). Results: The CECT RM (training AUC, 0.874; test AUC, 0.796) outperformed the conventional IM (training AUC, 0.792; test AUC, 0.708), the NCECT RM (training AUC, 0.835; test AUC, 0.704), and three radiologists. The diagnostic efficacy of the combine RM (training AUC, 0.922; test AUC, 0.833) was best in the training and test sets. Conclusions: The diagnostic efficacy of the CECT RM was superior to that of the NCECT RM in identifying TB from NTIL presenting as solid pulmonary nodules or masses. The combine RM had the best performance and may outperform expert radiologists.

Computed tomography radiomics-based distinction of invasive adenocarcinoma from minimally invasive adenocarcinoma manifesting as pure ground-glass nodules with bubble-like signs.

BACKGROUND: To explore an effective model based on radiomics features extracted from nonenhanced computed tomography (CT) images to distinguish invasive adenocarcinoma (IAC) from minimally invasive adenocarcinoma (MIA) presenting as pure ground-glass nodules (pGGNs) with bubble-like (B-pGGNs) signs. PATIENTS AND METHODS: We retrospectively reviewed 511 nodules (MIA, n = 288; IAC, n = 223) between November 2012 and June 2018 from almost all pGGNs pathologically confirmed MIA or IAC. Eventually, a total of 109 B-pGGNs (MIA, n = 55; IAC, n = 54) from 109 patients fulfilling the criteria were randomly assigned to the training and test cluster at a ratio of 7:3. The gradient boosting decision tree (GBDT) method and logistic regression (LR) analysis were applied to feature selection (radiomics, semantic, and conventional CT features). LR was performed to construct three models (the conventional, radiomics and combined model). The performance of the predictive models was evaluated using the area under the curve (AUC). RESULTS: The radiomics model had good AUCs of 0.947 in the training cluster and of 0.945 in the test cluster. The combined model produced an AUC of 0.953 in the training cluster and of 0.945 in the test cluster. The combined model yielded no performance improvement (vs. the radiomics model). The rad_score was the only independent predictor of invasiveness. CONCLUSION: The radiomics model showed excellent predictive performance in discriminating IAC from MIA presenting as B-pGGNs and may provide a necessary reference for extending clinical practice.

Use of CT radiomics to differentiate minimally invasive adenocarcinomas and invasive adenocarcinomas presenting as pure ground-glass nodules larger than 10 mm.

PURPOSE: This study aimed to develop a model based on radiomics features extracted from computed tomography (CT) images to effectively differentiate between minimally invasive adenocarcinomas (MIAs) and invasive adenocarcinomas (IAs) manifesting as pure ground-glass nodules (pGGNs) larger than 10 mm. METHOD: This retrospective study included patients who underwent surgical resection for persistent pGGN between November 2012 and June 2018 and diagnosed with MIAs or IAs. The patients were randomly assigned to the training and test cohorts. The correlation coefficient method and the least absolute shrinkage and selection operator (LASSO) method were applied to select radiomics features useful for constructing a model whose performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC). The radiomics model was compared to a standard CT model (shape, volume and mean CT value of the largest cross-section) and the combined radiomics-standard CT model using univariate and multivariate logistic regression analysis. RESULTS: The radiomics model showed better discriminative ability (training AUC, 0.879; test AUC, 0.877) than the standard CT model (training AUC, 0.820; test AUC, 0.828). The combined model (training AUC, 0.879; test AUC, 0.870) did not demonstrate improved performance compared with the radiomics model. Radiomics_score was an independent predictor of invasiveness following multivariate logistic analysis. CONCLUSIONS: For pGGNs larger than 10 mm, the radiomics model demonstrated superior diagnostic performance in differentiating between IAs and MIAs, which may be useful to clinicians for diagnosis and treatment selection.