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Lung cancer is the most common cancer and the leading cause of cancer-related death worldwide. The optimal management of computed tomography (CT)-indeterminate pulmonary nodules is important. To optimize individualized follow-up strategies, we developed a radiomics nomogram for predicting 2-year growth in case of indeterminate small pulmonary nodules. A total of 215 histopathology-confirmed small pulmonary nodules (21 benign and 194 malignant) in 205 patients with ultra-high-resolution CT (U-HRCT) were divided into growth and nongrowth nodules and were randomly allocated to the primary (n = 151) or validation (n = 64) group. The least absolute shrinkage and selection operator (LASSO) method was used for radiomics feature selection and radiomics signature determination. Multivariable logistic regression analysis was used to develop a radiomics nomogram that integrated the radiomics signature with significant clinical parameters (sex and nodule type). The area under the curve (AUC) was applied to assess the predictive performance of the radiomics nomogram. The net benefit of the radiomics nomogram was assessed using a clinical decision curve. The radiomics signature and nomogram yielded AUCs of 0.892 (95% confidence interval [CI]: 0.843–0.940) and 0.911 (95% CI: 0.867–0.955), respectively, in the primary group and 0.826 (95% CI: 0.727–0.926) and 0.843 (95% CI: 0.749–0.937), respectively, in the validation group. The clinical usefulness of the nomogram was demonstrated by decision curve analysis. A radiomics nomogram was developed by integrating the radiomics signature with clinical parameters and was easily used for the individualized prediction of two-year growth in case of CT-indeterminate small pulmonary nodules. • A radiomics nomogram was developed for predicting the two-year growth of CT-indeterminate small pulmonary nodules. • The nomogram integrated a CT-based radiomics signature with clinical parameters and was valuable in developing an individualized follow-up strategy for patients with indeterminate small pulmonary nodules.

BACKGROUND: Due to submucosal infiltration’s biological nature along the airway, adenoid cystic carcinoma (ACC) frequently leaves positive surgical margins. This study evaluated the clinicopathologic, and computed tomography (CT) features for predicting surgical margin status in central airway ACC. METHODS: We retrospectively analyzed the files of 71 patients with ACC of the central airway proven by histopathology and surgery who had presented between January 2010 and December 2018. All patients were classified into positive and negative surgical margin groups according to margin status. Univariate analysis and multivariable logistic regression models were then performed to compare demography, histopathology, and CT characteristics between ACC patients with positive and negative margins. RESULTS: After surgical resection, 59 (83.1%) patients had positive margins, and 12 (16.9%) had negative margins. The contrast-enhanced CT (CECT) longitudinal tail sign (LTS) was identified in 55 of 59 (93.2%) patients with positive margins and was the only feature that had a significant association with positive margins (odds ratio 41.250, 95% CI: 7.886–215.767; P

BACKGROUND: Lung cancer is a major cause of death, and adenocarcinoma is the most common histologic subtype. Precise diagnosis and treatment of invasive adenocarcinoma (IAC) can substantially improve the survival of patients. However, early-stage adenocarcinomas frequently appear as subsolid nodules (SSN) on computed tomography (CT), and the optimal cut-off CT value for differentiating the invasiveness of SSNs in emphysematous patients is unclear. METHODS: High-resolution CT targeted scans of 187 pulmonary SSNs in 175 patients with emphysema as confirmed by surgery and histology were retrospectively reviewed. The mean CT value, the relative CT (rCT) values of 1 (nodule CT value − lung CT value), and 2 (nodule CT value/lung CT value), and the size of the SSNs were measured and calculated. The differentiating performance of the CT values between pre-invasive and invasive tumors was evaluated using a receiver operating characteristic (ROC) curve. RESULTS: Significant differences were found in the rCT values of 1 and 2 among pure ground-glass nodules (GGNs) with different levels of invasiveness, in the rCT values of 1 and 2 for the ground-glass component (GGC) and the mean CT value of the solid component (SC) of part-solid nodules (PSNs) between minimally invasive adenocarcinoma (MIA) and IAC (all P<

To evaluate computed tomography (CT) features and establish a predictive model for the clinical diagnosis and prognosis of tracheal adenoid cystic carcinoma (ACC).From January 2010 to December 2018, 82 patients with tracheal tumors, including 46 patients with ACC confirmed by surgery and histopathology, were enrolled in this study. These patients' clinicopathologic information, CT features and survival outcomes were recorded and analyzed. Independent predictors of diagnosis and prognosis of tracheal ACC were determined by both univariate and multivariate analyses.Compared with tracheal non-ACC patients, univariate analysis showed that ACC patients were more likely to have extensive longitudinal length (p0.001) and to appear as annular wall thickening (p = 0.001), transmural growth (p = 0.036), poorly defined border (p = 0.003) and mild enhancement (p = 0.001). Multivariate logistic analysis showed that longitudinal length and enhancement degree were independent predictors of tracheal ACC. The 3-year and 5-year disease-free survival (DFS) were 75.7 % and 64.5 %, respectively. Longitudinal length (≥ 34 mm), transverse length (≥ 20 mm) and transmural growth were associated with poor DFS in univariate analysis. After multivariate adjustment, only transverse length (≥ 20 mm) was an adverse prognostic factor for DFS (hazard ratio = 4.594, 95 % confidence interval = 1.240-17.017; p = 0.022).CT longitudinal length and enhancement degree of tumors showed satisfactory discrimination for tracheal ACC. Excessive CT transverse length might be an unfavorable indicator for ACC recurrence and could be helpful for predicting the survival outcomes of ACC at the initial diagnosis.

Accurate assessment of the invasion of intrathoracic structures by stage III thymic tumors assists their appropriate management. The present study aimed to evaluate the efficacy of computed tomography (CT) features for the prediction of stage III thymoma invasion. The pre-operative CT images of 66 patients with confirmed stage III thymic tumors were reviewed retrospectively. The CT features of invasion into the mediastinal pleura, lungs, pericardium and great vessels were analyzed, and their sensitivity, specificity, positive predictive value (PPV), negative predictive value and accuracy were calculated. For mediastinal pleural and pericardial invasion, an absence of space between the tumor and the mediastinal pleura/pericardium with mediastinal pleural/pericardial thickening and pleural/pericardial effusion exhibited a specificity and PPV of 100%, respectively. For lung invasion, a multi-lobular tumor convex to the lung with adjacent lung abnormalities exhibited a specificity and PPV of 91.2 and 81.3%, respectively. For vessel invasion, the specificity and PPV were each 100% for tumors abutting ≥50% of the vessel circumference, and for tumor oppression, deformation and occlusion of the vessel. In conclusion, recognition of the appropriate CT features can serve as a guide to invasion by stage III thymic tumors, and can facilitate the selection of appropriate pre-operative treatment.

Purpose: Idiopathic normal pressure hydrocephalus (iNPH) is known as a treatable form of dementia. Network analysis is emerging as a useful method to study neurological disorder diseases. No study has examined changes of structural brain networks of iNPH patients. We aimed to investigate alterations in the gray matter (GM) structural network of iNPH patients compared with normal elderly volunteers.Materials and Methods: Structural networks were reconstructed using covariance between regional GM volumes extracted from three-dimensional T1-weighted images of 29 possible iNPH patients and 30 demographically similar normal-control (NC) participants and compared with each other.Results: Global network modularity was significantly larger in the iNPH network (P < 0.05). Global network measures were not significantly different between the two networks (P > 0.05). Regional network analysis demonstrated eight nodes with significantly decreased betweenness located in the bilateral frontal, right temporal, right insula and right posterior cingulate regions, whereas only the left anterior cingulate was detected with significantly larger betweenness. The hubs of the iNPH network were mostly located in temporal areas and the limbic lobe, those of the NC network were mainly located in frontal areas.Conclusions: Network analysis was a promising method to study iNPH. Increased network modularity of the iNPH group was detected here, and modularity analysis should be paid much attention to explore the biomarker to select shunting-responsive patients.

Purpose To investigate the prevalence of multidetector CT (MDCT) air bronchograms and their value in predicting the invasiveness of lung adenocarcinomas. Methods MDCT scans of 606 nodules in 582 patients with a lung adenocarcinoma less than 2 cm in diameter confirmed by surgery and pathology were reviewed. Air bronchograms were classified into three patterns: type I, bronchus with intact lumen; type II, bronchus with dilated or tortuous lumen; and type III, bronchus with obstructed lumen. Results Air bronchograms were demonstrated on MDCT in 210 of 606 (34.7%) lung adenocarcinomas with 16.6% (35/211) preinvasive lesions (PL), 30.5% (50/164) minimally invasive adenocarcinoma (MIA), and 54.1% (125/231) invasive adenocarcinoma (IAC) (P = 0.000); 18.3% (44/240) pure ground-glass nodules (GGNs), 44.2% (137/310) mixed GGNs, and 51.8% (29/56) solid nodules (P = 0.000). Type I was slightly more common in MIA (36/164, 22.0%) than IAC (40/231, 17.3%) and PL (30/211, 14.2%) but without differences among them (P = 0.147). Type II (PL: 5/211, 2.4%; MIA: 13/164, 7.9%; IAC: 53/231, 22.9%) and type III (PL: 0/211; MIA: 1/164, 0.6%; IAC: 32/231, 13.9%) were observed more frequently with increasing lung adenocarcinoma invasiveness (both P = 0.000). Conclusions The prevalence and patterns of air bronchograms on MDCT can predict the invasiveness of small lung adenocarcinomas.

To investigate the high-resolution computed tomography (HRCT) features that distinguish lung adenocarcinomas in situ (AISs) and minimally invasive adenocarcinomas (MIAs) from invasive adenocarcinomas (IACs) appearing as ground-glass nodules (GGNs), and to select candidates for sublobar resection. Two hundred and twenty-nine patients with 237 GGNs of less than 2 cm (139 AIS-MIA nodules and 98 IAC nodules) confirmed by surgery and pathology were retrospectively reviewed. The HRCT features of the AIS-MIAs and IACs were analysed and compared. Receiver operating characteristic (ROC) analyses were conducted to determine the cutoff values for the qualitative variables and their diagnostic performances. Significant differences were found in the density, nodule and solid component diameters, CT values of the ground-glass and solid components, lobulated shape, spiculated margin, abnormal pulmonary vein and artery, air bronchogram, and pleural indentation of the GGNs between the two groups. Multivariate and ROC analyses revealed that larger diameter of nodules (≥12.2 mm) and solid components (≥6.7 mm), and higher CT values of the solid components (≥ -192 HU) in the GGNs with air bronchogram were significantly associated with IACs. HRCT can identify distinguishing morphological features between AIS-MIAs and IACs, and is helpful for selecting candidates for sublobar resection. • IACs appearing as GGNs were often ≥ 12.2 mm in diameter. • IACs were often ≥ 6.7 mm in solid component diameter. • The solid components of the IACs often exhibited ≥ -192 HU. • IACs exhibited air bronchogram more frequently than AIS-MIAs.

The purpose of this study was to determine whether computed tomographic scans and attenuation measurements on contrast material-enhanced and non-enhanced computed tomographic scans could be used to characterize solitary pulmonary nodules and, in particular, to characterize these lesions using washout characteristics on contrast-enhanced computed tomography. A total of 63 patients (38 males, 25 females; age range, 21–80 years; mean age, 58±13.2 years) with pulmonary nodules revealed on contrast-enhanced computed tomography underwent 20-min delayed enhanced scans. The mean diameter of the pulmonary nodules was 1.8±0.6 cm (range, 0.8–2.9). Region-of-interest measurements were obtained at non-enhanced, dynamic enhanced and delayed enhanced computed tomography and were used to calculate a relative percentage washout as follows: 1 - (Hounsfield unit measurement on delayed image/Hounsfield unit measurement on dynamic image) × 100%. There was a mean relative washout of 33% on the delayed computed tomographic scans (range, 12–46) in benign solitary pulmonary nodules; and a mean relative washout of 7% (range, −36–51) in malignant solitary pulmonary nodules (Mann-Whitney U test, p

Objectives To analyze high-resolution computed tomography (HRCT) appearances of early lung adenocarcinoma and evaluate HRCT in the differentiation of minimally invasive component in early lung adenocarcinoma. Materials and methods HRCT appearances of 140 nodules (less than 2cm in diameter) of early lung adenocarcinoma were reviewed retrospectively. All these nodules were proven by surgery and pathology including 60 nodules of minimally invasive adenocarcinoma (MIA) and 80 nodules of preinvasive lesion (PL). HRCT features of two groups of lung nodules, including shape, margin, pattern, diameter, diameter of solid component, vascular changes, air bronchogram, vacuole, pleural indentation and multiplicity were analyzed and compared using univariate logistic regression analysis. Attenuation values of pure ground-glass nodule, pure ground-glass component and solid component of mixed ground-glass nodule were compared by using unpaired t -test or Wilcoxon rank-sum test. Results The statistically significant differences were found in shape, margin, pattern, diameter, diameter of solid component, pulmonary vein changes, air bronchogram and pleural indentation (Odds ratio [OR]=3.115 [ P =0.001], OR=3.754 [ P =0.011], OR=9.815 [ P =0.000], OR=1.306 [ P =0.000], OR=1.361 [ P =0.031], OR=6.971 [ P =0.000], OR=6.167 [ P =0.000], OR=2.296 [ P =0.027], respectively). The statistically significant difference was also found in attenuation value of solid component ( t =3.702, P =0.000). By multivariate logistic analysis, attenuation value of solid component was significantly associated with MIA (OR=1.005, P =0.032). MIA was more often a larger, lobulated or irregular, mixed ground-glass nodule with a solid component larger than 5mm, and higher attenuation values. In addition, MIA often had an abnormality in pulmonary vein, air bronchogram and pleural indentation. Conclusions HRCT can demonstrate the morphological features of early lung adenocarcinoma and identify minimally invasive component.

To prospectively assess the role of the dynamic contrast-enhanced CT enhancement characteristics in distinguishing malignant form of benign solitary pulmonary nodules. The study included 87 patients (59 men, 28 women; median age, 59 years) with 87 solitary pulmonary nodules. In all cases, dynamic CT images were obtained before and 20, 30, 45, 60, 75, 90, 120 s, 3, 5, 9, 12, 15 and 20 min after injection of contrast medium. Peak enhancement attenuation value, net enhancement attenuation value, the slope of enhancement, enhancement ratio, outflow of contrast medium (washout), washout ratio and the slope of washout ratio were assessed. Statistical analyses were performed with the Mann–Whitney test, χ2 test, and receiver-operating characteristic curves. There were 52 malignant and 35 benign nodules. There were no significant differences in net enhancement value, enhancement ratio and the slope of enhancement ratio between malignant and benign nodules (P > 0.05). Malignant nodules showed smaller outflow of contrast medium than did benign nodules. With 12.4HU or lower washout as a cutoff value, the sensitivity and specificity for malignancy were 52.5 and 65.0 %, respectively. With 18.9 % or lower washout ratio as a cutoff value, sensitivity and specificity for malignancy were 60.0 and 75.0 %, respectively. With 0.0180 %/s or lower slope of washout ratio as a cutoff value, sensitivity and specificity for malignancy were 60.0 and 80.0 %, respectively. Dynamic contrast-enhanced CT is helpful in differentiating malignant from benign solitary pulmonary nodules. Smaller washout of contrast enhancement is a predictor that a lesion is malignant.