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

Development of a nomogram-based model incorporating radiomic features from follow-up longitudinal lung CT images to distinguish invasive adenocarcinoma from benign lesions: a retrospective study

PURPOSE

To develop and validate a radiomic model for differentiating pulmonary invasive adenocarcinomas from benign lesions based on follow-up longitudinal CT images.

METHODS

This is a retrospective study including 336 patients (161 with invasive adenocarcinomas and 175 with benign lesions) who underwent baseline (T0) and follow-up (T1) CT scans from January 2016 to June 2022. The patients were randomized in a 7:3 ratio into training and test sets. Radiomic features were extracted from lesion volumes of interest on longitudinal CT images at T0 and T1. Differences in radiomic features between T1 and T0 were defined as delta-radiomic features. Logistic regression was used to build models based on clinicoradiological (CR), T0, T1, and delta radiomic features and compute signatures. Finally, a nomogram based on the CR, T0, T1 and delta signatures was constructed. Model performance was evaluated for calibration, discrimination, and clinical utility.

RESULTS

The T1 radiomic model was superior to the other independent models. In the training set, it had an area under the curve (AUC) of 0.858), superior to the CR model (AUC 0.694), the T0 radiomic model (AUC 0.825), and the delta radiomic model (AUC 0.734). In the test set, it had an AUC of 0.817, again outperforming the CR model (AUC 0.578), the T0 radiomic model (AUC 0.789), and the delta radiomic model (AUC 0.647). The nomogram incorporating the CR, T0, T1 and delta signatures showed the best predictive performance in both the training (AUC: 0.906) and test sets (AUC: 0.856), and it exhibited excellent fit with calibration curves. Decision curve analysis provided additional validation of the clinical utility of the nomogram.

CONCLUSION

A nomogram utilizing radiomic features extracted from longitudinal CT images can enhance the discriminative capability between pulmonary invasive adenocarcinomas and benign lesions.

Risk factors for lung parenchyma hemorrhage and hemoptysis during computed tomography-guided microwave ablation in patients with stage I non-small cell lung cancer: A bicentric retrospective study

OBJECTIVES

This study aimed to identify the risk factors for lung parenchyma hemorrhage and hemoptysis during computed tomography-guided microwave ablation (MWA) in patients with stage I non-small cell lung cancer (NSCLC).

METHODS

A total of 417 patients from two medical centers were included, of whom 353 were from center 1 and 64 were from center 2. The risk factors for lung parenchyma hemorrhage and hemoptysis were selected by univariable and multivariable logistic analyses in the center 1 dataset. The selected risk factors were validated in the center 2 dataset.

RESULTS

The risk factors for lung parenchyma hemorrhage during MWA were focal blood supplies (odds ratio [OR], 2.602; 95% confidence interval [CI], 1.609-4.210; p < 0.001), near vessels larger than 2 mm (OR, 4.145; 95% CI, 1.963-8.755; p < 0.001), and traversing vessels in the track of ablation (OR, 2.961; 95% CI, 1.492-5.874; p = 0.002). The risk factors for hemoptysis were lung parenchyma hemorrhage (OR, 34.165; 95% CI, 12.255-95.247; p < 0.001), needle track traversing the lung parenchyma by >25 mm (OR, 4.494; 95% CI, 1.833-11.018; p = 0.001), and traversing vessels in the track of ablation (OR, 5.402; 95% CI, 2.269-12.865; p < 0.001).

CONCLUSIONS

Focal blood supplies, near vessels larger than 2 mm, and traversing vessels in the track of ablation were independent risk factors for lung parenchyma hemorrhage during MWA. Lung parenchyma hemorrhage, needle track traversing the lung parenchyma by >25 mm, and traversing vessels in the track of ablation were independent risk factors for hemoptysis during MWA.

Baseline computed tomography imaging findings could assist in early diagnosis of visceral pleural invasion for newly discovered early subpleural non-small cell lung cancer: T1 or T2

Background

Preoperative accurate visceral pleural infiltration (VPI) diagnosis for T1-size non-small cell lung cancer (NSCLC) is significant for clinical decision-making. The study aimed to explore the diagnostic efficacy of computed tomography (CT) imaging features and serum biomarkers in diagnosing VPI in newly discovered subpleural NSCLC ≤3 cm.

Methods

There were 447 patients with NSCLC ≤3 cm retrospectively enrolled and assigned to the VPI group (n=81) and the non-VPI group (n=366) based on elastic fiber staining results. The serum biomarkers and CT imaging features were obtained for each subject. Univariate and multivariate analyses were used to identify the independent predictors for VPI. Area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance of each independent predictor and combined predictors in predicting VPI, with performance compared using the DeLong test.

Results

For tumor biomarkers, the VPI group had a significantly higher percentage of cases with abnormal carcino-embryonic antigen (CEA) level, cytokeratin 19 fragment (CYFRA21-1) level, and pro-gastrin-releasing peptide (ProGRP) level than that of the non-VPI group (P<0.001, P=0.003, P=0.004). However, in multivariate analysis, only the lesion-pleura relationship patterns type Ia [odds ratio (OR) =20.689; 95% confidence interval (CI): 5.058-84.622; P<0.001], type Ib (OR =5.155; 95% CI: 1.178-22.552; P=0.03), type II (OR =7.154; 95% CI: 1.733-29.53; P=0.007) with type III as reference, solid lesion density (OR =9.954; 95% CI: 4.976-19.911; P<0.001) with part-solid density as reference were identified as the independent predictors for VPI. In predicting VPI, the combined model (AUC =0.885) significantly outperformed models based on lesion density (AUC =0.833) and lesion-pleura relationship patterns (AUC =0.655) (all P<0.001).

Conclusions

The CT predictors for VPI in patients with subpleural NSCLC (≤3 cm) were lesion density and lesion-pleura relationship patterns (pleural attachment and indentation), but not serum tumor biomarkers.

Differential Diagnosis of Preinvasive Lesions in Small Pulmonary Nodules by Dual Source Computed Tomography Imaging

This study was aimed to explore the differential diagnosis value of preinvasive lesions/minimally invasive adenocarcinoma and invasive adenocarcinoma manifesting as small pulmonary nodules under dual source computed tomography (DSCT) imaging. The patients with nodular manifestations of adenocarcinoma in situ (AIS)/microinfiltrating adenocarcinoma (MIA) were selected as group X, including 14 cases. A total of 31 cases with nodular infiltrating adenocarcinoma were selected as group Y. The enhanced dual-energy image obtained by DSCT dual-energy scan was transferred to the software to obtain the energy image and iodine distribution map. SPSS 18.0 was used for statistical analysis. P < 0.05 was considered statistically significant. All measurements were labeled as mean x͞±S standard deviation. In the CT findings of microinfiltrating adenocarcinoma and infiltrating adenocarcinoma, lobulation sign, burr sign, vacuole sign, and pleural depression sign can help the diagnosis of infiltrating adenocarcinoma. The results showed that lobulation sign, burr sign, vacuole sign, and pleural depression sign could be used as the distinguishing feature of preinvasive lesion/microinvasive adenocarcinoma and invasive adenocarcinoma. Receiver-operating characteristic (ROC) curve analysis showed that the critical value, sensitivity, and specificity of lesion diameter ≥1.4 cm and CT value ≥14.14HU for diagnosis of invasive lung adenocarcinoma were 1.32 and 14.14, 88.4% and 94.4%, and 67.3% and 75.8%, respectively. There were substantial differences in CT values between the two groups under low energy level (42-99 kev) (P < 0.05). DSCT dual-energy imaging can quantitatively identify preinvasive pulmonary nodules with multiple parameters.

Value of gadoxetic acid-enhanced MRI for microvascular invasion of small hepatocellular carcinoma: a retrospective study

Background

The objective of this study was to analyze the accuracy of gadolinium–ethoxybenzyl–diethylenetriamine penta–acetic acid enhanced magnetic resonance imaging (Gd–EOB–DTPA–MRI) for predicting microvascular invasion (MVI) in patients with small hepatocellular carcinoma (sHCC) preoperatively.

Methods

A total of 60 sHCC patients performed with preoperative Gd–EOB–DTPA–MRI in the Harbin Medical University Cancer Hospital from October 2018 to October 2019 were involved in the study. Univariate and multivariate analyses were performed by chi–square test and logistic regression analysis. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of Gd–EOB–DTPA–MRI were performed by receiver operating characteristic (ROC) curves.

Results

Univariate analysis indicated that alanine aminotransferase (≥ 39.00U/L), poorly differentiated pathology, and imaging features including grim enhancement, capsule enhancement, arterial halo sign and hepatobiliary features (tumor highly uptake, halo sign, spicule sign and brush sign) were associated with the occurrence of MVI (p < 0.05). Multivariate analysis revealed that rim enhancement and hepatobiliary spicule sign were independent predictors of MVI (p < 0.05). The area under the ROC curve was 0.917 (95% confidence interval 0.838–0.996), and the sensitivity was 94.74%.

Conclusions

The morphologies of hepatobiliary phase imaging, especially the spicule sign, showed high accuracy in diagnosing MVI of sHCC. Rim enhancement played a significant role in diagnosing MVI of sHCC.

Correlation study between dual source CT perfusion imaging and the microvascular composition of solitary pulmonary nodules

OBJECTIVE

To explore the correlation between dual source computed tomography perfusion imaging (CTPI) and microvascular parameters, and evaluate the value of CTPI in the differential diagnosis of solitary pulmonary nodule (SPN).

METHODS

65 consecutive patients with SPN who successfully underwent pre-operative CT perfusion imaging with dual source CT and received a final diagnosis by postoperative pathology. The cases were divided into malignant, benign and inflammatory groups according to the pathological results. CT perfusion parameters, such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface (PMB) were obtained by performing CTPI of SPNs. The postoperative specimens of SPNs were immunohistochemically stained for CD34 and SMA to detect microvessel density (MVD) and luminal vascular parameters, such as luminal vascular number (LVN), luminal vascular area (LVA) and luminal vascular perimeter (LVP). The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CT perfusion parameter in diagnosing malignant SPNs.

RESULTS

In these 65 cases, malignant, benign and inflammatory SPNs were respectively 39, 14 and 12 cases. Significant difference was observed in LVN/MVD, LVA and LVP among the three groups (P < 0.05). The correlation between CT perfusion parameters (BF, BV and PMB) and the luminal vascular parameters was stronger than that with MVD (P < 0.05). PMB has the strongest correlation with LVN/MVD. Using BF≥60ml/100ml/min, BV≥6.34ml/100ml and PMB≥13.35ml/100 ml/min for the diagnosis, the area under the curve (AUC) of the ROC curve was 0.760, the sensitivity was 82% and the specificity was 61%.

CONCLUSIONS

The main indicators reflecting blood perfusion of SPN are the degree of lumen or maturity of microvessels (LVN, LVA and LVP), not just the number of microvessels (e.g. MVD). CT perfusion imaging can be used as an important method to non-invasively evaluate tumour angiogenesis and help to distinguish malignant SPNs from benign and inflammatory SPNs.

The value of the air bronchogram sign on CT image in the identification of different solitary pulmonary consolidation lesions

The aim of the present study is to investigate the value of air bronchogram sign on computed tomography (CT) image in the differential diagnosis of solitary pulmonary consolidation lesions (SPLs).A total of 105 patients (including 39 cases of lung cancer, 43 cases of tuberculosis, and 23 cases of pneumonia) with SPLs were evaluated for the CT features of air bronchogram sign in this retrospective study. The shape and lumen of the bronchi with air bronchogram sign, the length of the involved bronchus with air bronchogram sign, the length of lesion on the same plane and direction, and the ratio between the length of the involved bronchus and that of the lesion were evaluated.In total, there were 172 segmental and subsegmental bronchi involved. There were 62 segmental and subsegmental bronchi involved among 39 lung cancer cases, 77 segmental and subsegmental bronchi involved among 43 tuberculosis cases, and 33 segmental and subsegmental bronchi involved among 23 pneumonia cases. The shape of the bronchi with air bronchogram sign was significantly different among lung cancer, tuberculosis, and pneumonia (P < .05). The lumen of the bronchi with air bronchogram sign was also significantly different among the 3 SPLs (P < .05). The length of the involved bronchus with air bronchogram sign and the ratio between the length of the involved bronchus and that of the lesion were significantly different between lung cancer and tuberculosis (P < .05), or between lung cancer and pneumonia (P < .05), but not between tuberculosis and pneumonia (P > .05). No significant difference was found in the length of lesion among the 3 SPLs (P > .05).The shape and lumen of the bronchi with air bronchogram sign can be used to distinguish lung cancer, tuberculosis, and pneumonia. The length of the involved bronchus with air bronchogram sign and the ratio between the length of the involved bronchus and that of the lesion can be used to distinguish lung cancer from tuberculosis and pneumonia.

Differential diagnostic value of 64-slice spiral computed tomography in solitary pulmonary nodule

The present study aimed to evaluate the diagnostic value of 64-slice spiral multivariate computed tomography (CT) combined with dynamic contrast-enhanced scanning for benign and malignant solitary pulmonary nodules (SPNs). A total of 93 patients with SPN as diagnosed by CT were included. All these patients were subjected to routine and dynamic enhancement CT scanning. After reconstruction, the morphological characteristics following dynamic enhancement were analyzed, and compared for the benign and malignant SPN cases. The incidences of lobulation, spicular sign, pleural indentation and vacuole sign in the malignant SPN group were significantly higher compared with the benign SPN group. During the dynamic enhancement scanning, the CT values at all the time points for the inflammatory and malignant SPN groups were significantly higher than the benign SPN group. No significant differences were observed in the dynamic enhancement CT values at 30, 60, 90 and 120 sec between the inflammatory, and malignant SPN groups. However, in the inflammatory SPN group, the dynamic enhancement CT values at 300 and 540 sec were significantly lower than the malignant SPN group. Notably, the diagnostic accordance rate for the morphological signs combined with dynamic enhancement diagnosis was significantly higher than the morphological signs alone. The 64-slice spiral CT morphological signs combined with dynamic enhancement detection can be more effective for the differential diagnosis of benign and malignant SPN, which may provide potent evidence for the early clinical treatment.