Pleural Indentation Sign Research Articles

Predicting solitary pulmonary lesions in breast cancer patients using 18fluorodeoxyglucose-positron emission tomography/computed tomography combined with clinicopathological characteristics

BackgroundSolitary pulmonary nodules (SPNs) remain difficult to diagnose for clinical therapeutic purposes in patients with a history of breast cancer. This study try to investigate the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) combined with clinicopathological predictors for the differential diagnosis of SPNs in breast cancer patients.MethodsOne hundred and twenty breast cancer patients with newly detected SPNs were enrolled in the study and divided into a primary lung cancer (PLC) group and a breast cancer metastasis (BCM) group. The clinicopathological characteristics as well as metabolic and morphological characteristics on 18F-FDG-PET/CT images of 120 patients were retrospectively reviewed. The differences of clinicopathological and 18F-FDG-PET/CT characteristics between the two groups were analyzed, and multivariate analyses for the diagnosis of SPNs were performed.ResultsClinicopathological terms of carcinoembryonic antigen (CEA) and CA15-3 levels exhibited significant differences between PLC and BCM groups (P = 0.005 and P = 0.001, respectively). Metabolic characteristics of 18F-FDG-PET/CT images included FDG uptake, SUVmax of SPNs, hilar and/or mediastinal lymph node metastasis, SUVmax of hilar and/or mediastinal lymph node, and extrapulmonary metastasis showed significant differences between PLC and BCM groups (P = 0.004, P < 0.001, P = 0.01, P = 0.032 and P = 0.023, respectively). The lobulation sign, spicule sign, and pleural indentation sign were identified as statistically different morphological features of PLC in CT images (all P < 0.001). Among these, the SUVmax of SPNs, lobulation sign, and pleural indentation sign were valuable predictive factors for accurate diagnosis of SPNs in breast cancer patients.Conclusions18F-FDG-PET/CT combined with serum tumor markers are valuable for the diagnosis of SPNs in breast cancer patients.

Analysis of the correlation between clinical and imaging features of malignant lung nodules and pathological types.

To explore the correlation between clinical and imaging features of malignant lung nodules and pathology types. Patients with lung nodules admitted to the Affiliated Hospital of Jiangsu University from January 1, 2020 to December 31, 2020 were collected as study subjects, and all of them underwent surgical treatment and were clearly diagnosed by pathology. The correlation between clinical and imaging features and pathological types of lung cancer patients was analyzed. Among them, The pathological types of malignant pulmonary nodules are correlated with age, gender, smoking history, ground glass sign, nodule size, solid to solid ratio, lobulation sign, pleural indentation sign, hair prick sign, CEA, SCCA. The imaging features of ground glass sign and nodule size are most significantly correlated with the pathological type. It was found that, the clinical and imaging characteristics of patients with malignant lung nodules have a certain correlation with the pathological type, and gender, age, smoking history, nodule size, nodule nature, burr sign, pleural depression sign, and tumor markers are of great value for pathological typing.

A decision tree model to distinguish between benign and malignant pulmonary nodules on CT scans.

Chest computed tomography (CT) is increasingly being used to screen for lung cancer. Machine learning models could facilitate the distinction between benign and malignant pulmonary nodules. This study aimed to develop and validate a simple clinical prediction model to distinguish between benign and malignant lung nodules. Patients who underwent a video thoracic-assisted lobectomy between January 2013 and December 2020 at a Chinese hospital were enrolled in the study. The clinical characteristics of the patients were extracted from their medical records. Univariate and multivariate analyses were used to identify the risk factors for malignancy. A decision tree model with 10-fold cross-validation was constructed to predict the malignancy of the nodules. The sensitivity, specificity, and area under the curve (AUC) of a receiver operatic characteristics curve were used to evaluate the model's prediction accuracy in relation to the pathological gold standard. Out of the 1,199 patients with pulmonary nodules enrolled in the study, 890 were pathologically confirmed to have malignant lesions. The multivariate analysis identified satellite lesions as an independent predictor for benign pulmonary nodules. Conversely, the lobulated sign, burr sign, density, vascular convergence sign, and pleural indentation sign were identified as independent predictors for malignant pulmonary nodules. The decision tree analysis identified the density of the lesion, the burr sign, the vascular convergence sign, and the drinking history as predictors of malignancy. The area under the curve of the decision tree model was 0.746 (95% CI 0.705-0.778), while the sensitivity and specificity were 0.762 and 0.799, respectively. The decision tree model accurately characterized the pulmonary nodule and could be used to guide clinical decision-making.

Correlation between HRCT signs and levels of CA125, SCCA, and NSE for different pathological types of lung cancer.

The aim of this study was to investigate the correlation between high-resolution CT (HRCT) signs and serum tumor markers, to improve the diagnostic level and identify different pathological types of lung cancer. 102 patients with pathologically confirmed lung cancer were selected as the observation group. HRCT scan and serum tumor markers [cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), and neuron-specific enolase (NSE)] were performed to analyze the correlation. Among the 102 cases of lung cancer, 88 cases were of lobulation sign, 78 cases of speculation sign, 45 cases of pleural indentation sign, 35 cases of vessel tracking sign, and 34 cases of vacuole sign. CA125 had the highest concentration in lung adenocarcinoma (55.74±14.18) ng/ml, and SCCA had the highest concentration in lung squamous cell carcinoma (18.98±6.37) ng/ml. The concentration of NSE in small cell lung cancer was the highest (48.12±16.19) ng/ml. Pleural indentation sign and vacuole sign were more likely to happen in lung adenocarcinoma and lung squamous cell carcinoma, respectively. The significant increase of CA125, SCCA, and NSE concentrations suggested that lung cancer patients were more likely to suffer from lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung cancer, respectively.

Value of preoperative 18F-FDG PET/CT and HRCT in predicting the differentiation degree of lung adenocarcinoma dominated by solid density.

To evaluate the value of positron emission tomography/computed tomography (PET/CT) combined with high-resolution CT (HRCT) in determining the degree of differentiation of lung adenocarcinoma. From January 2018 to January 2022, 88 patients with solid density nodules that are lung adenocarcinoma were surgically treated. All patients were examined using HRCT and PET/CT before surgery. During HRCT, two independent observers assessed the presence of lobulation, spiculation, pleural indentation, vascular convergence, and air bronchial signs (bronchial distortion and bronchial disruption). The diameter and CT value of the nodules were measured simultaneously. During PET/CT, the maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the nodules were measured. The risk factors of pathological classification were predicted by logistic regression analysis. All 88 patients (mean age 60 ± 8 years; 44 males and 44 females) were evaluated. The average nodule size was 2.6 ± 1.1 cm. The univariate analysis showed that carcinoembryonic antigen (CEA), pleural indentation, vascular convergence, bronchial distortion, and higher SUVmax were more common in poor differentiated lung adenocarcinoma, and in the multivariate analysis, pleural indentation, vascular convergence, and SUVmax were predictive factors. The combined diagnosis using these three factors showed that the area under the curve (AUC) was 0.735. SUVmax >6.99 combined with HRCT (pleural indentation sign and vascular convergence sign) is helpful to predict the differentiation degree of lung adenocarcinoma dominated by solid density.

CT Radiomics Predict EGFR-T790M Resistance Mutation in Advanced Non-Small Cell Lung Cancer Patients After Progression on First-line EGFR-TKI

We aim to explore the value of chest CT radiomics in predicting the epidermal growth factor receptor (EGFR)-T790M resistance mutation of advanced non-small cell lung cancer (NSCLC) patients after the failure of first-line EGFR-tyrosine kinase inhibitor (EGFR-TKI). A total of 211 and 135 advanced NSCLC patients with tumor tissue-based (Cohort-1) or circulating tumor DNA (ctDNA)-based (Cohort-2) EGFR-T790M testing were included, respectively. Cohort-1 was used for modeling and Cohort-2 was for models' validation. Radiomic features were extracted from tumor lesions on chest nonenhanced CT (NECT) and/or contrast-enhanced CT (CECT). We used eight feature selectors and eight classifier algorithms to establish radiomic models. Models were evaluated by area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). CT morphological manifestations of peripheral location and pleural indentation sign were associated with EGFR-T790M. For NECT, CECT, and NECT+CECT radiomic features, the feature selector and classifier algorithms of LASSO and Stepwise logistic regression, Boruta and SVM, and LASSO and SVM were chosen to develop the optimal model, respectively (AUC: 0.844, 0.811, and 0.897). All models performed well in calibration curves and DCA. Independent validation of models in Cohort-2 revealed that both NECT and CECT models individually had limited power for predicting EGFR-T790M mutation detected by ctDNA (AUC: 0.649, 0.675), while the NECT+CECT radiomic model had a satisfactory AUC (0.760). This study proved the feasibility of using CT radiomic features to predict the EGFR-T790M resistance mutation, which could be helpful in guiding personalized therapeutic strategies.

Predicting Ki-67 labeling index level in early-stage lung adenocarcinomas manifesting as ground-glass opacity nodules using intra-nodular and peri-nodular radiomic features.

To explore the diagnostic value of radiomics in differentiating between lung adenocarcinomas appearing as ground-glass opacity nodules (GGO) with high- and low Ki-67 expression levels. From January 2018 to January 2021, patients with pulmonary GGO who received lung resection were evaluated for potential enrollment. The included GGOs were then randomly divided into a training cohort and a validation cohort with a ratio of 7:3. Logistic regression (LR), decision tree (DT), support vector machines (SVM), and adaboost (AB) were applied for radiomic model construction. Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the established models. Seven hundred and sixty-nine patients with 769 GGOs were included in this study. Two hundred and forty-five GGOs were confirmed to be of high Ki-67 labeling index (LI). In the training cohort, gender, age, spiculation sign, pleural indentation sign, bubble sign, and maximum 2D diameter of the nodule were found to be significantly different between high- and low Ki-67 LI groups (p < 0.05), and spiculation sign and maximum 2D diameter of the nodule were further confirmed to be risk factors for Ki-67 LI. The radiomic model established using SVM exhibited an AUC of 0.731 in the validation cohort, which was higher than that of the clinical-radiographic model (AUC=0.675). Moreover, radiomic model combining both intra- and peri-nodular features showed better diagnostic efficacy than using intra-nodular features alone (AUC=0.731 and 0.720, respectively). The established radiomic model exhibited good diagnostic efficacy in differentiating between lung adenocarcinoma GGOs with high and low Ki-67 LI, which was higher than the clinical-radiographic model. Peri-nodular radiomic features showed added benefits to the radiomic model. As a novel noninvasive method, radiomics have the potential to be applied in the preliminary classification of Ki-67 expression level in lung adenocarcinoma GGOs.

Lung cancer associated with cystic airspaces: CT and pathological features

BackgroundLung cancer associated with cystic airspaces (LC-CAS) is a special type of lung cancer that is often misdiagnosed due to its similar imaging appearances to pulmonary bulla or pulmonary cyst. This study was designed to explore the imaging and pathological features of LC-CAS.MethodsA retrospective analysis was performed on 35 LC-CAS patients treated in our center from January 2017 to January 2020. There were 23 men and 12 women aged 61.4±9.2 years, with a range of 44–78 years. All patients underwent chest computed tomography (CT), and the diagnoses were surgically and pathologically confirmed.ResultsThe lesions were 0.5–3.0 cm (mean: 1.6±0.7 cm) in diameter. The CT signs of these lesions included lobulation sign (n=25), spicule sign (n=21), pleural indentation sign (n=22), vessel convergence sign (n=17), nodules on cystic wall (n=16), bronchial cut-off sign (n=15), uneven thickening of the cystic wall (n=10), and honeycombing (n=7). Postoperative pathological types included 30 cases of adenocarcinoma [which included 22 cases of invasive adenocarcinoma (IAC) and 8 cases of minimally invasive adenocarcinoma (MIA)], 4 cases of squamous cell carcinoma, and 1 case of adenosquamous carcinoma.ConclusionsLC-CAS has diverse CT signs. The most common pathological type of LC-CAS is adenocarcinoma.

Radiomics Signature: A Biomarker for the Preoperative Distant Metastatic Prediction of Stage I Nonsmall Cell Lung Cancer

To evaluate the predictive value of radiomics features on the distant metastasis (DM) of stage I nonsmall cell lung cancer (NSCLC) preoperatively, by comparing with clinical characteristics and CT morphological features, and to screen the important prognostic predictors. One hundred ninety-four stage I NSCLC patients were retrospectively enrolled, DM free survival (DMFS) was evaluated. The consensus clustering analysis was used to build the radiomics signatures in the primary cohort and validated in the validation cohort. The univariate survival analysis was performed in clinical characteristics, CT morphological features and radiomics signatures, respectively. Cox model was performed and C-index was calculated. There were 25 patients (12.9%) with DM. The median DMFS was 15 months. Three hundred thirteen radiomics features were selected, then classified into five groups, two subtypes (I and II) with each group. The RS1 showed the best prognostic ability with C-index of 0.355(95% confidence interval [CI], 0.269-0.442; p < 0.001). The histological type exhibited a good prognostic ability with C-index of 0.123 (95% CI, 0.000-0.305; p < 0.001) for DMFS. Cox model showed RS1(hazard ratio [HR] 18.025, 95% CI 2.366-137.340), pleural indentation sign (HR 2.623, 95% CI 1.070-6.426) and histological type (HR 4.461, 95% CI 1.783-11.162) were the independent prognostic factors (p < 0.05). Radiomics provided a new modality for the distant metastatic prediction of stage I NSCLC. Patients with type II of RS1, pleural indentation sign and nonadenocarcinoma indicated the high probability of postsurgical DM.

Contrast analysis of the relationship between the HRCT sign and new pathologic classification in small ground glass nodule-like lung adenocarcinoma

To perform contrast analysis of the relationship between high-resolution computed tomography (HRCT) signs and new pathologic classification of small GGNs-like lung adenocarcinoma. The HRCT data from 145 pathologically confirmed cases of small GGNs of lung adenocarcinoma were analysed retrospectively. The 145 cases of GGNs were divided into pre-invasive (PI) group (n = 46), micro-invasive adenocarcinoma (MIA) group (n = 48), and invasive adenocarcinoma (IAC) group (n = 51). HRCT imaging sign of GGNs in each group was assessed and compared. Significant differences in GGN size were found among the three groups (P < 0.05). The presence of a tumour-lung interface in the MIA and IAC groups was significantly higher than that in the PI group (P < 0.05), but no significant difference was found between the MIA and IAC groups. The presence of a pleural indentation sign in the IAC group was significantly higher than that in the other two groups (P < 0.05), but no significant difference was noted between the latter two groups. Significant differences were found in the lobulated and spicule signs among the three groups (P < 0.05). The presence of a microvascular sign in the MIA and IAC groups was significantly higher than that in the PI group (P < 0.05). No significant difference was found in the GGN density, vacuole sign, air bronchus sign and notch sign among the three groups. The HRCT signs of GGNs could be used to differentiate among pre-invasive lesions, micro-invasive lesions and invasive lung adenocarcinoma.

High-resolution computed tomography features and CT-guided microcoil localization of subcentimeter pulmonary ground-glass opacities: radiological processing prior to video-assisted thoracoscopic surgery.

With the rapid development of high-resolution computed tomography (HRCT), low-dose CT scanning and video-assisted thoracoscopic surgery (VATS), smaller pulmonary nodules can be detected. Subcentimeter ground-glass opacities (GGOs) are extremely difficult to diagnose and accurately locate during VATS and in surgically resected specimens. From September 2013 to September 2017, 42 subcentimeter GGO lesions (≤1 cm) in 31 patients who underwent CT-guided microcoil insertion followed by VATS resection were included. All HRCT images were assessed by two experienced radiologists, and CT-guided microcoil localization procedures were performed by two experienced interventional radiologists. A total of 42 subcentimeter GGOs included 28 malignancies (66.7%) and 14 benign lesions (33.3%). The diameter of malignant GGOs (8.52±1.46 mm) was significantly larger than that of benign lesions (7.04±1.52 mm) (P<0.05). Seven patients had more than one GGO nodule. There were no significant differences in the location, composition, shape, margins, presence of air bronchograms, presence of the pleural indentation sign and presence of the vascular convergence sign between benign and malignant GGOs (P>0.05). All the localization procedures were performed successfully. A small pneumothorax occurred in 9 patients (21.4%), and minor hemorrhage in the lung parenchyma occurred in 8 patients (19.0%). All GGOs were easily identified during VATS and were definitively diagnosed. Common HRCT features cannot be used as criteria for the differential diagnosis of subcentimeter benign and malignant pulmonary GGOs. CT-guided microcoil marking of these lesions prior to VATS is a feasible, safe, and effective procedure for the localization of subcentimeter pulmonary GGOs.

Is a 5-mm diameter an appropriate cut-off value for the diagnosis of atypical adenomatous hyperplasia and adenocarcinoma in situ on chest computed tomography and pathological examination?

Preinvasive lesions, such as atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS), usually appear as pure ground-glass nodules (pGGNs) on thin-section computed tomography (TSCT). AAH is usually less than 5 mm wide on imaging and pathological examinations. We aimed to determine whether a 5-mm cut-off value was appropriate for the diagnosis of AAH and AIS. We retrospectively analyzed the performance of TSCT in evaluating 80 pathologically confirmed preinvasive lesions (33 AAH lesions in 31 patients and 47 AIS lesions in 45 patients). We compared the following characteristics between the AAH and AIS groups: lesion diameter, density, rim, lobulation, spiculation, vacuole sign, aerated bronchus sign, pleural indentation sign, and pathological findings. All 80 lesions appeared as pGGNs. On TSCT, the average diameter of AAH lesions (6.0±1.64 mm) was significantly smaller than that of AIS lesions (8.7±3.16 mm; P<0.001). The area under the curve (AUC) for diameter was 0.792, and the best diagnostic cut-off value was 6.99 mm. On gross pathological examination, the average diameter of AAH lesions (4.6±1.99 mm) was significantly smaller that of AIS lesions (6.8±2.06 mm; P<0.001). The AUC was 0.794, and the best diagnostic cut-off value was 4.5 mm. The vacuole sign was common in AIS (P=0.021). AAH did not significantly differ from AIS (P>0.05) in terms of average CT value, uniformity of density, morphology, rim, lobulation, spiculation, pleural indentation sign, and aerated bronchus sign. Lesion size and the vacuole sign were beneficial in the diagnosis of AAH and AIS. The vacuole sign was common in AIS. The best diagnostic cut-off value of nodular diameter for differentiating between AAH and AIS was 6.99 mm on TSCT and 4.5 mm on gross pathology.

Differential diagnosis of solitary pulmonary nodules with dual-source spiral computed tomography.

The aim of the present study was to analyze the value of applying dual-source 64-layer spiral computed tomography (CT) in the differential diagnosis of solitary pulmonary nodules (SPNs). Mediastinal windows from 45 cases were selected to study SPNs (maximum diameter, ≤3 cm), and the pathological nature of lesions was determined by clinical and pathological diagnosis. Conventional 64-layer spiral CT scanning, local enhancement and 3D recombination technologies were used to determine the occurrence rate, lesion diameter, degree of enhancement, lobular sign, spicule sign, pleural indentation sign, vessel convergence sign and bronchus sign. The final diagnoses indicated 34 cases of malignant SPNs (75.6%) and 11 benign cases (24.4%). When the nodule diameter in the malignant group was compared with that of the benign group, the difference was not statistically significant (P>0.05). Nodules in the malignant group showed inhomogeneous enhancement while nodules in the benign group showed homogeneous enhancement. The enhanced CT values in the malignant group were higher than those in the benign group, and the difference was statistically significant (P<0.05). The proportion of nodules with lobular sign in the malignant group was significantly higher than that in the benign group (P<0.05). The proportion of nodules with calcification, vessel convergence sign and bronchus sign in the malignant group were significantly higher than those in the benign group, and the differences were statistically significant (P<0.05). A comparison of vacuole sign, pleural indentation sign, spiculate protuberance and fat occurrence between the two groups yielded no statistically significant differences (P>0.05). The sensitivity of CT enhancement was 85.6%, specificity was 79.6%, positive predicated value was 92.3%, and the negative predicted value was 85.2%. In conclusion, SPNs diagnosed by CT enhancement manifested with enhancement degree, lobular sign, calcification, vessel convergence sign and bronchus sign with high diagnostic accuracy.

Clinicopathological characteristics and imaging features of pulmonary adenocarcinoma with micropapillary pattern

To explore the clinicopathological characteristics and imaging features of lung adenocarcinoma with a micropapillary pattern (MPP). Eighty cases of pulmonary adenocarcinoma with a micropapillary pattern treated in our hospital from July 2011 to December 2012 were selected to retrospectively analyze their clinicopathological characteristics and imaging features. Among the 80 cases of lung adenocarcinoma with MPP, there were 38 cases of stage I (47.5%), 12 cases of stage II (15.0%), 25 cases of stage III (31.3%) and 5 cases of stage IV (6.2%). There were 14 cases of moderately differentiated (17.5%) and moderately/poorly differentiated (82.5%) tumors. Sixty-three cases had pleural involvement, vascular invasion, involving the bronchial wall, invasion of large vessels, nerve invasion, and lymph node metastasis (at least one of them) (78.8%). Immunohistochemical staining revealed that both positive rates of TTF-1 and CK7 were 100%, and that of pulmonary surfactant apolipoprotein-A (SPA) was 84.0%. Imaging examination revealed hilar or mediastinal lymph node enlargement in 15 cases (18.8%). but the pathology confirmed hilar or mediastinal lymph node metastasis in 36 cases (45.0%). Lung CT imaging showed that the majority of the cases were peripheral type, and only a few of central type, and most cases were solid lesions, with lobulation, spiculation, pleural indentation, and vascular convergence sign, while there were few ground-glass opacity sign and vacuole sign. Lung adenocarcinoma with MPP component often presents with early invasions of pleura, blood vessels, lymphatic vessels, and lymph nodes. Imaging manifestation of this cancer mainly shows as peripheral and solid lesions, often with lobulation, spiculation, pleural indentation, vascular convergence sign, but GGO and vacuole signs are unusual. Overexpression of TTF-1, CK7 and SPA, and elevated CEA level are associated with clinical staging of the disease.