A simple prediction model using fluorodeoxyglucose-PET and high-resolution computed tomography for discrimination of invasive adenocarcinomas among solitary pulmonary ground-glass opacity nodules

[18F]FDG PET/CT is useful in discriminating invasive adenocarcinomas among pure ground-glass nodules: comparison with CT findings-a bicenter retrospective study

PURPOSE

Predicting the malignancy of pure ground-glass nodules (GGNs) using CT is challenging. The optimal role of [18F]FDG PET/CT in this context has not been clarified. We compared the performance of [18F]FDG PET/CT in evaluating GGNs for predicting invasive adenocarcinomas (IACs) with CT.

METHODS

From June 2012 to December 2020, we retrospectively enrolled patients with pure GGNs on CT who underwent [18F]FDG PET/CT within 90 days. Overall, 38 patients with 40 ≥ 1-cm GGNs were pathologically confirmed. CT images were analyzed for size, attenuation, uniformity, shape, margin, tumor-lung interface, and internal/surrounding characteristics. Visual [18F]FDG positivity, maximum standardized uptake value (SUVmax), and tissue fraction-corrected SUVmax (SUVmaxTF) were evaluated on PET/CT.

RESULTS

The histopathology of the 40 GGNs were: 25 IACs (62.5%), 9 minimally invasive adenocarcinomas (MIA, 22.5%), and 6 adenocarcinomas in situ (AIS, 15.0%). No significant differences were found in CT findings according to histopathology, whereas visual [18F]FDG positivity, SUVmax, and SUVmaxTF were significantly different (P=0.001, 0.033, and 0.018, respectively). The size, visual [18F]FDG positivity, SUVmax, and SUVmaxTF showed significant diagnostic performance to predict IACs (area under the curve=0.693, 0.773, 0.717, and 0.723, respectively; P=0.029, 0.001, 0.018, and 0.013, respectively). In the multivariate logistic regression analysis, visual [18F]FDG positivity discriminated IACs among GGNs among various CT and PET findings (P=0.008).

CONCLUSIONS

[18F]FDG PET/CT demonstrated superior diagnostic performance compared to CT in differentiating IAC from AIS/MIA among pure GGNs, thus it has the potential to guide the proper management of patients with pure GGNs.

Diagnostic challenge and survival analysis of pulmonary oligometastases and primary lung cancer in breast cancer patients

BACKGROUND

The aim of this study was to compare breast cancer patients with pulmonary oligometastases (POM) and primary lung cancer (PLC) and to assess whether there were differences in clinical features, CT features, and survival outcomes between the two groups.

METHODS

From January 2010 to December 2021, the clinical records of 437 with malignant pulmonary nodules who had breast cancer patients were reviewed. POM was identified in 45 patients and PLC in 43 patients after the initial detection of pulmonary nodules. The clinicopathological characteristics, CT appearance of pulmonary nodules, and survival of the two groups were compared.

RESULTS

Stage II to IV breast tumors (p < 0.001), high pathological grade of breast cancer (p = 0.001), low proportion of luminal-type breast cancer (p = 0.003), and the higher serum CYFRA 21-1 level (p = 0.046) were the clinical characteristics of pulmonary nodules suggestive of POM rather than PLC. The CT features of lung nodules indicative of PLC rather than POM were the subsolid component (p < 0.001), lobulation (p = 0.010), air bronchogram (p < 0.001) and pleural indentation (p = 0.004). Ten-year survival rate for PLC was 93.2%, which was higher compared with 57.8% in those with POM (p = 0.001).

CONCLUSIONS

Elevated serum CYFRA 21-1 levels and late-stage breast cancer may be beneficial for the diagnosis of POM. CT imaging appearances of the subsolid component, lobulation, air bronchogram, and pleural indentation increase the likelihood of PLC. Breast cancer patients with PLC presented better survival with attentive monitoring than those with POM.

A predictive model based on ground glass nodule features via high-resolution CT for identifying invasiveness of lung adenocarcinoma

Objective

The morphology of ground-glass nodule (GGN) under high-resolution computed tomography (HRCT) has been suggested to indicate different histological subtypes of lung adenocarcinoma (LUAD); however, existing studies only include the limited number of GGN characteristics, which lacks a systematic model for predicting invasive LUAD. This study aimed to construct a predictive model based on GGN features under HRCT for LUAD.

Methods

A total of 301 surgical LUAD patients with HRCT-confirmed GGN were enrolled, and their GGN-related features were assessed by 2 individual radiologists. The pathological diagnosis of the invasive LUAD was established by pathologic examination following surgery (including 171 invasive and 130 non-invasive LUAD patients).

Results

GGN features including shorter distance from pleura, larger diameter, area and mean CT attenuation, more heterogeneous uniformity of density, irregular shape, coarse margin, not defined nodule-lung interface, spiculation, pleural indentation, air bronchogram, vacuole sign, vessel changes, lobulation were observed in invasive LUAD patients compared with non-invasive LUAD patients. After adjustment by multivariate logistic regression model, GGN diameter (OR = 1.490, 95% CI, 1.326-1.674), mean CT attenuation (OR = 1.007, 95% CI, 1.004-1.011) and heterogeneous uniformity of density (OR = 3.009, 95% CI, 1.485-6.094) were independent risk factors for invasive LUAD. In addition, a predictive model integrating these three independent GGN features was established (named as invasion of lung adenocarcinoma by GGN features (ILAG)), and receiver-operating characteristic curve illustrated that the ILAG model presented good predictive value for invasive LUAD (AUC: 0.919, 95% CI, 0.889-0.949).

Conclusions

ILAG predictive model integrating GGN diameter, mean CT attenuation and heterogeneous uniformity of density via HRCT shows great potential for early estimation of LUAD invasiveness.

The value of positron emission tomography computed tomography in predicting invasiveness of ground glass nodules: A protocol for systematic review and meta-analysis

BACKGROUND

The study was conducted to investigate the value of Positron emission tomography computed tomography (PET/CT) in predicting invasiveness of ground glass nodule (GGN) by the method of meta-analysis.

METHODS

Two researchers independently searched for published literature on PET/CT diagnosis of GGN as of November 30, 2020. After extracting the data, RevMan5.3 was used to evaluate the quality of the included literature. The Stata14 software was used to test the heterogeneity of the original study that met the inclusion criteria, to calculate the combined sensitivity, specificity, positive likelihood ratio and negative likelihood ratio, the prior probability and posttest probability. The summary receiver operator characteristic curve was drawn and the area under the curve was calculated. Using Deeks funnel plot to evaluate publication bias.

RESULTS

Five studies were finally included, including 298 GGN cases. The included studies had no obvious heterogeneity and publication bias. The combined sensitivity and specificity of PET/CT for predicting invasive adenocarcinoma presenting as GGN were 0.74 (95% confidence interval [CI]: 0.68-0.79), 0.82 (95% CI: 0.71-0.90), positive likelihood ratio and negative likelihood ratio were 4.1 (95% CI: 2.5-6.9), 0.32 (95% CI: 0.25-0.40), and the diagnostic odds ratio was 13 (95% CI: 7-26). The prior probability is 20%, the probability of GGN being invasive adenocarcinoma when PET/CT was negative was reduced to 7%, and the probability of GGN being invasive adenocarcinoma when PET/CT was positive was increased to 51%. The area under the curve of the summary receiver operator characteristic curve was 0.85.

CONCLUSION

PET/CT has high diagnostic accuracy for invasive adenocarcinoma presenting as GGN.

Value of 18F-FDG PET/CT-based radiomics model to distinguish the growth patterns of early invasive lung adenocarcinoma manifesting as ground-glass opacity nodules

Background

To establish and validate ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT-based radiomics model and use it to predict the intermediate-high risk growth patterns in early invasive adenocarcinoma (IAC).

Methods

Ninety-three ground-glass nodules (GGNs) from 91 patients with stage I who underwent a preoperative ¹⁸F-FDG PET/CT scan and histopathological examination were included in this study. The LIFEx software was used to extract 52 PET and 49 CT radiomic features. The least absolute shrinkage and selection operator (LASSO) algorithm was used to select radiomic features and develop radiomics signatures. We used the receiver operating characteristics curve (ROC) to compare the predictive performance of conventional CT parameters, radiomics signatures, and the combination of these two. Also, a nomogram based on conventional CT indicators and radiomics signature score (rad-score) was developed.

Results

GGNs were divided into lepidic group (n = 18) and acinar-papillary group (n = 75). Four radiomic features (2 for PET and 2 for CT) were selected to calculate the rad-score, and the area under the curve (AUC) of rad-score was 0.790, which was not significantly different as the attenuation value of the ground-glass opacity component on CT (CT_GGO) (0.675). When rad-score was combined with edge (joint model), the AUC increased to 0.804 (95% CI [0.699–0.895]), but which was not significantly higher than CT_GGO (P = 0.109). Furthermore, the decision curve of joint model showed higher clinical value than rad-score and CT_GGO, especially under the purpose of screening for intermediate-high risk growth patterns.

Conclusion

PET/CT-based radiomics model shows good performance in predicting intermediate-high risk growth patterns in early IAC. This model provides a useful method for risk stratification, clinical management, and personalized treatment.

Hepatic steatosis is associated with abnormal hepatic enzymes, visceral adiposity, altered myocardial glucose uptake measured by 18F-FDG PET/CT

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is a multisystem disease that affects the liver and a variety of extra-hepatic organ systems. This study aimed to investigate the relationship between hepatic steatosis and glucose metabolism in liver and extra-hepatic tissues and organs.

METHODS

The whole body 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) images of 191 asymptomatic tumor screening patients were retrospectively analyzed. Patients with the ratio of spleen/liver CT densities > 1.1 were defined to have NAFLD, and their clinical symptoms, laboratory markers, FDG uptake in a variety of tissues and organs including heart, mediastinal blood pool, liver, spleen, pancreas, and skeletal muscle, as well as abdominal adipose tissue volumes including visceral adipose tissue (VAT) volume and subcutaneous adipose tissue (SAT) volume were compared with those of the non-NAFLD patients and used to analyze the independent correlation factors of NAFLD.

RESULTS

Among the 191 patients, 33 (17.3%) were NAFLD, and 158 (82.7%) were non-NAFLD. There was no significant correlation between the mean standardized uptake value (SUVmean) and CT density of liver as well as the ratio of spleen/liver CT densities. Hepatic steatosis, but not FDG intake, was more significant in NAFLD patients with abnormal liver function than those with normal liver function. Compared with the non-NAFLD patients, NAFLD patients had significantly reduced myocardial glucose metabolism, but significantly increased mediastinal blood pool, spleen SUVmean and abdominal adipose tissue volumes (including VAT and SAT volumes) (P < 0.05). Multivariate regression analysis showed that elevated serum ALT, increased abdominal VAT volume, and decreased myocardial FDG uptake were independent correlation factors for NAFLD. Further studies showed that hepatic steatosis and myocardial FDG uptake were mildly linearly correlated (r = 0.366 with hepatic CT density and - 0.236 with the ratio of spleen/liver CT densities, P < 0.05).

CONCLUSIONS

NAFLD is a systemic disease that can lead to the change of glucose metabolism in some extra-hepatic tissues and organs, especially the myocardium.