F-18 FDG uptake on positron emission tomography as a predictor for lymphovascular invasion in patients with lung adenocarcinoma

Correlatıon between PET-CT uptake values and pathologıcaly features ın head and neck cancer

OBJECTIVES

To evaluate the correlation between SUV-Max values and pathological outcomes in head and neck squamous cell carcinoma (HNSCC) and determine the predictive power of SUV-Max for disease prognosis.

DATA SOURCES

Retrospective analysis of medical records and PET-CT imaging results from patients diagnosed with HNSCC at our institution between 2014 and 2023.

REVIEW METHODS

Examination of SUV-Max values from F18-FDG PET-CT scans and their association with pathological findings such as perineural invasion, lymphovascular invasion, and neck lymph node metastasis. Statistical analysis was conducted to establish cutoff values and assess the significance of correlations.

RESULTS

Our study identified significant cutoff values for PET-CT SUV-Max that correlate with the pathological features of head and neck cancer. For primary tumors, a SUV-Max cutoff of 14.71 predicted neck metastasis with a sensitivity of 67.6% and specificity of 64.2%, demonstrating moderate diagnostic accuracy with an AUC of 0.648. Perineural invasion was optimally predicted at a cutoff of 13.28, with a sensitivity of 74%, specificity of 67.3%, and an AUC of 0.728. Similarly, a cutoff of 13.28 for lymphovascular invasion yielded a sensitivity and specificity of 63%, with an AUC of 0.628. Additionally, neck lymph node metastasis was effectively assessed with a SUV-Max cutoff of 2.74, achieving a sensitivity of 62.2%, specificity of 67%, and an AUC of 0.694. These cutoff values highlight the potential of SUV-Max in enhancing diagnostic precision for both primary tumors and lymph node assessments in head and neck oncology.

CONCLUSION

SUV-Max values from PET-CT scans are significant predictors of pathological outcomes in HNSCC, aiding in the stratification of patient prognosis and guiding clinical decision-making.

Preoperative CT Radiomics Nomogram for Predicting Microvascular Invasion in Stage I Non-Small Cell Lung Cancer

RATIONALE AND OBJECTIVES: This study aims to develop and validate a nomogram integrating clinical-CT and radiomic features for preoperative prediction of microvascular invasion (MVI) in patients with stage I non‑small cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective study analyzed 188 cases of stage I NSCLC (63 MVI positives and 125 negatives), which were randomly assigned to training (n = 133) and validation cohorts (n = 55) at a ratio of 7:3. Preoperative non-contrast and contrast-enhanced CT (CECT) images were used to analyze computed tomography (CT) features and extract radiomics features. The student's t-test, the Mann-Whitney-U test, the Pearson correlation, the least absolute shrinkage and selection operator, and multivariable logistic analysis were used to select the significant CT and radiomics features. Multivariable logistic regression analysis was performed to build the clinical-CT, radiomics, and integrated models. The predictive performances were evaluated through the receiver operating characteristic curve and compared with the DeLong test. The integrated nomogram was analyzed regarding discrimination, calibration, and clinical significance.

RESULTS

The rad-score was developed with one shape and four textural features. The integrated nomogram incorporating radiomics score, spiculation, and the number of tumor-related vessels (TVN) demonstrated better predictive efficacy than the radiomics and clinical-CT models in the training cohort (area under the curve [AUC], 0.893 vs 0.853 and 0.828, and p = 0.043 and 0.027, respectively) and validation cohort (AUC, 0.887 vs 0.878 and 0.786, and p = 0.761 and 0.043, respectively). The nomogram also demonstrated good calibration and clinical usefulness.

CONCLUSION

The radiomics nomogram integrating the radiomics with clinical-CT features demonstrated good performance in predicting MVI status in stage I NSCLC. The nomogram may be a useful tool for physicians in improving personalized management of stage I NSCLC.

Computed Tomography and 18F-Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography Imaging Biomarkers of Lung Invasive Non-mucinous Adenocarcinoma: Prediction of Grade 3 Tumour Based on World Health Organization Grading System

AIMS

To evaluate computed tomography (CT) and 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG-PET/CT) findings of invasive non-mucinous adenocarcinoma (INMA) of the lung as a predictor of histological tumour grade according to 2021 World Health Organization (WHO) classification.

MATERIALS AND METHODS

This retrospective study included consecutive patients with surgically resected INMA who underwent both preoperative CT and 18F-FDG-PET/CT. A three-tiered tumour grade was performed based on the fifth edition of the WHO classification of lung tumours. CT imaging features and the maximum standardised uptake value (SUVmax) were compared among the three tumour grades.

RESULTS

In total, 214 patients with INMA (median age 70 years; interquartile range 65-76 years; 123 men) were histologically categorised: 36 (17%) as grade 1, 102 (48%) as grade 2 and 76 (35%) as grade 3. Pure solid appearance was more frequent in grade 3 (83%) than in grades 1 (0%) and 2 (26%) (P < 0.001). The SUVmax of the entire tumour was higher in grade 3 than in grades 1 and 2 (P < 0.001). Multivariable analysis revealed that pure solid appearance (odds ratio = 94.0; P < 0.001), round/oval shape (odds ratio = 4.01; P = 0.001), spiculation (odds ratio = 2.13; P = 0.04), air bronchogram (odds ratio = 0.40; P = 0.03) and SUVmax (odds ratio = 1.45; P < 0.001) were significant predictors for grade 3 INMAs.

CONCLUSION

Pure solid appearance, round/oval shape, spiculation, absence of air bronchogram and high SUVmax were associated with grade 3 INMAs. CT and 18F-FDG-PET/CT were potentially useful non-invasive imaging methods to predict the histological grade of INMAs.

Differentiating primary from secondary lung cancer with FDG PET/CT and extra-pulmonary tumor grade

OBJECTIVE

Assess feasibility of differentiating primary from secondary lung cancer in patients with a solid solitary malignant pulmonary lesion (SMPL) and a previously resected extrapulmonary tumor.

METHODS

Patients with pathology proven primary or secondary lung cancer from a solitary pulmonary lesion and known histopathology of extrapulmonary tumor were included. Patients with a small pulmonary lesion size, multiple malignant pulmonary nodules or an active infectious/inflammatory process were excluded. Extrapulmonary tumor grade was categorized as low, intermediate and high and was matched to FDG uptake intensity of SMPL, with FDG uptake range (SMPL/Liver SUVmax) of <0.9 for low, 0.91-1.99 for intermediate and >2.0 for high extrapulmonary tumor grade.

RESULTS

Of 274 patients, 62 met the study criteria. 46 are primary and 16 are secondary lung cancer. There are 19 low, 27 intermediate and 16 high grade extrapulmonary tumors. Mean SMPL SUVmax is 8.2 ± 4.5 and SMPL/liver SUVmax is 2.4 ± 1.4. There are 37 cases (60%) with mismatched results (e.g., low FDG SMPL with intermediate or high grade extrapulmonary tumor or vice versa) and 25 matched cases (40%) that are inconclusive (e.g., low FDG with low tumor grade or high FDG with high tumor grade). Of the mismatched cases, we correctly predicted 30 cases (81%) as primary lung cancers.

CONCLUSION

A mismatch between the SMPL SUVmax and the extrapulmonary tumor grade could be used to differentiate a primary lung cancer from a metastasis with reasonable accuracy. Our preliminary results support the hypothesis that FDG uptake intensity of a metastatic pulmonary lesion mirrors the tumor aggressiveness of its extrapulmonary neoplasm of origin.

18F-FDG PET/CT radiomics for prediction of lymphovascular invasion in patients with early stage non-small cell lung cancer

Objective

To explore a prediction model for lymphovascular invasion (LVI) on cT1-2N0M0 radiologic solid non-small cell lung cancer (NSCLC) based on a 2-deoxy-2[18F]fluoro-D-glucose ([18F]F-FDG) positron emission tomography-computed tomography (PET-CT) radiomics analysis.

Methods

The present work retrospectively included 148 patients receiving surgical resection and verified pathologically with cT1-2N0M0 radiologic solid NSCLC. The cases were randomized into training or validation sets in the ratio of 7:3. PET and CT images were used to select optimal radiomics features. Three radiomics predictive models incorporating CT, PET, as well as PET/CT images radiomics features (CT-RS, PET-RS, PET/CT-RS) were developed using logistic analyses. Furthermore, model performance was evaluated by ROC analysis for predicting LVI status. Model performance was evaluated in terms of discrimination, calibration along with clinical utility. Kaplan-Meier curves were employed to analyze the outcome of LVI.

Results

The ROC analysis demonstrated that PET/CT-RS (AUCs were 0.773 and 0.774 for training and validation sets) outperformed both CT-RS(AUCs, 0.727 and 0.752) and PET-RS(AUCs, 0.715 and 0.733). A PET/CT radiology nomogram (PET/CT-model) was developed to estimate LVI; the model demonstrated conspicuous prediction performance for training (C-index, 0.766; 95%CI, 0.728-0.805) and validation sets (C-index, 0.774; 95%CI, 0.702-0.846). Besides, decision curve analysis and calibration curve showed that PET/CT-model provided clinically beneficial effects. Disease-free survival and overall survival varied significantly between LVI and non-LVI cases (P<0.001).

Conclusions

The PET/CT radiomics models could effectively predict LVI on early stage radiologic solid lung cancer and provide support for clinical treatment decisions.

Retention index of FDG-PET/CT SUVmax of the primary tumor in non-small cell lung cancer as a predictor of lymph node metastasis: a retrospective study

Background

Accurate staging of non-small cell lung cancer is key in treatment planning and prediction of prognosis. We investigated the correlation between the maximum standardized uptake value (SUVmax) retention index (RI) of the primary tumor and lymph node metastasis in non-small cell lung carcinoma. We also evaluated the tendencies according to the histological types.

Methods

We retrospectively evaluated 218 non-small cell lung cancer (NSCLC) tumors from 217 patients who underwent preoperative fluorodeoxyglucose-positron emission tomography/computed tomography (PET/CT) followed by lung surgery and lymph node resection between July 2015 and August 2020. All primary tumors were calculated as the SUVmax at 50 min (SUVmax_early [SUVmax_e]) and 120 min (SUVmax_delayed [SUVmax_d]), and RI. The clinicopathological factors of interest were compared based on lymph node metastasis status and NSCLC histopathological subtype.

Results

The median SUVmax_e and SUVmax_d of the primary tumors were 3.3 and 4.2, respectively, and the median RI was 0.25. The RI was significantly higher in the pN(+) (n = 44) group (0.30) compared to the pN0 (n = 174) group (0.24) (p = 0.01). In patients with adenocarcinoma (n = 145), the RI was also significantly higher in the pN(+) (n = 29) group (0.29) compared to the pN0 (n = 116) group (0.16) (p < 0.01). A high RI of the primary tumor was an independent risk factor for lymph node metastasis, particularly in patients with adenocarcinoma (odds ratio: 12.30, p < 0.05).

Conclusions

The RI of primary NSCLC tumors can help predict lymph node metastases, particularly in patients with adenocarcinoma.

Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using 18F-FDG PET/CT Images

Background

Lymph vascular invasion (LVI) is an unfavorable prognostic indicator in gastric cancer (GC). However, there are no reliable clinical techniques for preoperative predictions of LVI. The aim of this study was to develop and validate PET/CT-based radiomics signatures for predicting LVI of GC preoperatively. Radiomics nomograms were also established to predict patient survival outcomes.

Methods

This retrospective study registered 148 GC patients with histopathological confirmation for LVI status, who underwent pre-operative PET/CT scans (Discovery VCT 64 PET/CT system) from December 2014 to June 2019. Clinic-pathological factors (age, gender, and tumor grade, etc.) and metabolic PET data (maximum and mean standardized uptake value, total lesion glycolysis and metabolic tumor volume) were analyzed to identify independent LVI predictors. The dataset was randomly assigned to either the training set or test set in a 7:3 ratios. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with LVI status is built by feature selection. Four models with different modalities (PET-RS: only PET radiomics features; CT-RS: only CT radiomics features; PET/CT-RS: both PET and CT radiomics features; PET/CT-RS plus clinical data) were developed to predict LVI. Patients were postoperatively followed up with PET/CT every 6-12 months for the first two years and then annually up to five years after surgery. The PET/CT radiomics score (Rad-scores) was calculated to assess survival outcome, and corresponding nomograms with radiomics (NWR) or without radiomics (NWOR) were established.

Results

Tumor grade and maximum standardized uptake value (SUVmax) were the independent LVI predictor. 1037 CT and PET 3D radiomics features were extracted separately and reduced to 4 and 5 features to build CT-RS and PET-RS, respectively. PET/CT-RS and PET/CT-RS plus clinical data (tumor grade and SUVmax) were also developed. The ROC analysis demonstrated clinical usefulness of PET/CT-RS plus clinical data (AUC values for training and validation, respectively 0.936 and 0.914) and PET/CT-RS (AUC values for training and validation, respectively 0.881 and 0.854), which both are superior to CT-RS (0.838 and 0.824) and PET-RS (0.821 and 0.812). SUVmax and LVI were independent prognostic indicators of both OS and PFS. Decision curve analysis (DCA) demonstrated NWR outperformed NWOR and was established to assess survival outcomes. For estimation of OS and PFS, the C-indexes of the NWR were 0. 88 and 0.88 in the training set, respectively, while the C-indexes of the NWOR were 0. 82 and 0.85 in the training set, respectively.

Conclusions

The PET/CT-based radiomics analysis might serve as a non-invasive approach to predict LVI status in GC patients and provide effective predictors of patient survival outcomes.

Feasibility of ultra-low 18F-FDG activity acquisitions using total-body PET/CT

The present study aimed to evaluate the feasibility of ultra-low ¹⁸F-fluorodeoxyglucose (FDG) activity in total-body positron emission tomography (PET)/computed tomography (CT) oncological studies. Methods: Thirty patients with cancer were enrolled prospectively and underwent a total-body PET/CT examination with an ultra-low ¹⁸F-FDG activity (0.37 MBq/kg) after an uptake time of 60 minutes. Among the enrolled patients, 11 were diagnosed with colorectal cancer (CRC). PET raw data were acquired within 15 minutes and reconstructed using data from the first 1, 2, 4, 8, 10 and the entire 15 min (G1, G2, G4, G8, G10, G15). Image quality was assessed qualitatively by two readers using a 5-point Likert scale twice. Cohen's kappa test was performed to investigate the intra-reader and inter-reader agreement. The standard uptake value (SUV)max of lesions, SUV_max, SUVmean, and standard deviation (SD) of the livers, the tumor-to-background ratio (TBR), and the signal-to-noise ratio (SNR) were measured and compared. The acquisition time for a clinically acceptable image quality was determined using an ultra low activity injection. In a matched-pair study, 11 patients with CRC who received a full FDG activity (3.7 MBq/kg) with a 2-min PET acquisition were selected retrospectively with matched sex, height, weight, body mass index, glucose level, uptake time, and pathological types with the 11 CRC subjects in the prospective study. Qualitative and quantitative analyses were performed and compared between the 11 patients with CRC in the ultra-low activity group and their matched full activity controls. Results: Qualitative analysis of image quality showed good intra- and inter-reader agreements (all kappa > 0.7). All the images acquired for 8-min or longer scored over 3 (indicating clinical acceptability). There was no significant difference in TBR and liver SNR among all the images acquired for 8-min or longer. In the matched study, no significant difference was found in the image quality score and quantitative parameters between the ultra-low activity group with an 8-min acquisition and the full activity group with a 2-min acquisition. Conclusion: Ultra-low FDG activity injection with 8-min acquisition in a total-body PET/CT study can achieve acceptable image quality equivalent to that in the full activity group using 2-min acquisition.

Utility of Volumetric Metabolic Parameters on Preoperative FDG PET/CT for Predicting Tumor Lymphovascular Invasion in Non-Small Cell Lung Cancer

Background: Lymphovascular invasion (LVI) is an adverse prognostic indicator in non-small cell lung cancer (NSCLC) and serves as an indication for postoperative adjuvant chemotherapy recommendation after resection. Objective: To assess the utility of clinicopathologic factors and volumetric metabolic parameters from preoperative FDG PET/CT in predicting primary tumor LVI in NSCLC. Methods: This retrospective study included 161 patients (mean age, 61.8±8.1 years; 111 men, 50 women) with surgically-confirmed NSCLC who underwent preoperative FDG PET/CT between January 2018 and November 2020. Two nuclear medicine physicians used software to place automated volumes of interest delineating each tumor to record metabolic indices (SUVmax, SUVmean, and metabolictumor volume [MTV]), which in turn were used to calculate total lesion glycolysis (TLG). Measurements were first performed independently to determine interobserver agreement using intraclass correlation coefficients (ICCs) and then repeated in consensus. Associations of clinicopathologic and metabolic parameters with tumor LVI status were assessed using t test, Mann-Whitney U test, and chi-squared test. Diagnostic performance was assessed using ROC analysis. Multivariable logistic regression analysis was performed to identify independent predictors of tumor LVI. Results: A total of 23.6% (38/161) of patients had LVI. Interobserver agreement was ICC=1.000 for SUVmax, ICC=0.997 for SUVmean, and 0.999 for MTV. Tumors with LVI, compared with tumors without LVI, exhibited higher SUVmax (15.4±5.9 vs 11.7±7.5, p=.006), SUVmean (6.0±1.6 vs 5.1±2.0, p=.009), MTV (median 15.8 cm3 vs 5.5 cm3, p<.001), and TLG (median 88.8 vs 24.5, p<.001). Among the metabolic parameters, AUC was highest for MTV (0.704), with optimal MTV cutoff of 6.4 cm3 yielding sensitivity 92.1% (35/38), specificity 56.1% (69/123), PPV 39.3% (35/89), and NPV 95.8% (69/72) for LVI. Independent predictors (p<.05) of LVI were MTV (≥6.4 cm3, odds ratio [OR]=6.5), N1 (OR=6.4) or N2 (OR=4.0) disease, and T2 disease (OR=3.6). These factors combined achieved AUC of 0.854 for LVI. Conclusion: The volumetric metabolic parameter MTV from preoperative FDG PET/CT is an independent predictor of tumor LVI in NSCLC. Clinical Impact: Further studies are warranted to assess the potential role of preoperative prediction of LVI using FDG PET/CT to help guide clinical decision making in NSCLC.

Value of integrated PET-IVIM MRI in predicting lymphovascular space invasion in cervical cancer without lymphatic metastasis

PURPOSE

To evaluate the contributory value of positron emission tomography (PET)-intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the prediction of lymphovascular space invasion (LVSI) in patients with cervical cancer without lymphatic metastasis.

MATERIALS AND METHODS

A total of 90 patients with cervical cancer without signs of lymph node metastasis on PET/MRI were enrolled in this study. The tumours were classified into LVSI-positive (n = 25) and LVSI-negative (n = 65) groups according to postoperative pathology. The PET-derived parameters (SUV_max, SUV_mean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG)) and IVIM-derived parameters (ADC_mean, ADC_min, D_mean, D_min, f, D* and gross tumour volume (GTV)) between the two groups were evaluated using a Student's t test (Mann-Whitney U test for variables with a nonnormal distribution) and receiver operating characteristic (ROC) curves. The optimal combination of PET/MR parameters for predicting LVSI was investigated using univariate and multivariate logistic regression models and evaluated by ROC curves. The optimal cutoff threshold values corresponded to the maximal values of the Youden index. A control model was established using 1000 bootstrapped samples, for which the performance was validated using calibration curves and ROC curves.

RESULTS

PET-derived parameters (SUV_max, SUV_mean, MTV, TLG) and IVIM MRI-derived parameters (D_min, ADC_min, GTV) were significantly different between patients with and without LVSI (P < 0.05). Logistic analyses showed that a combination of TLG and D_min had the strongest predictive value for LVSI diagnosis (area under the curve (AUC), 0.861; sensitivity, 80.00; specificity, 86.15; P < 0.001). The optimal cutoff threshold values for D_min and TLG were 0.58 × 10^-3 mm²/s and 66.68 g/cm³, respectively. The verification model showed the combination of TLG and D_min had the strongest predictive value, and its ROC curve and calibration curve showed good accuracy (AUC, 0.878) and consistency.

CONCLUSIONS

The combination of TLG and D_min may be the best indicator for predicting LVSI in cervical cancer without lymphatic metastasis.

2D and 3D texture analysis to predict lymphovascular invasion in lung adenocarcinoma

PURPOSE

Lymphovascular invasion (LVI) impairs surgical outcomes in lung adenocarcinoma (LAC) patients. Preoperative prediction of LVI is challenging by using traditional clinical and imaging factors. The purpose of this study was to evaluate the value of two-dimensional (2D) and three-dimensional (3D) CT texture analysis (CTTA) in predicting LVI in LAC.

METHODS

A total of 149 LAC patients (50 LVI-present LACs and 99 LVI-absent LACs) were retrospectively enrolled. Clinical data and CT findings were analyzed to select independent clinical predictors. Texture features were extracted from 2D and 3D regions of interest (ROI) in 1.25 mm slice CT images. The 2D and 3D CTTA signatures were constructed with the least absolute shrinkage and selection operator algorithm and texture scores were calculated. The optimized CTTA signature was selected by comparing the predicting efficacy and clinical usefulness of 2D and 3D CTTA signatures. A CTTA nomogram was developed by integrating the optimized CTTA signature and clinical predictors, and its calibration, discrimination and clinical usefulness were evaluated.

RESULTS

Maximum diametre and spiculation were independent clinical predictors. 1125 texture features were extracted from 2D and 3D ROIs and reduced to 11 features to build 2D and 3D CTTA signatures. There was significant difference (P < 0.001) in AUC (area under the curve) between 2D signature (AUC, 0.938) and 3D signature (AUC, 0.753) in the training set. There was no significant difference (P = 0.056) in AUC between 2D signature (AUC, 0.856) and 3D signature (AUC, 0.701) in the test set. Decision curve analysis showed the 2D signature outperformed the 3D signature in terms of clinical usefulness. The 2D CTTA nomogram (AUC, 0.938 and 0.861, in the training and test sets), which incorporated the 2D signature and clinical predictors, showed a similar discrimination capability (P = 1.000 and 0.430, in the training and test sets) and clinical usefulness as the 2D signature, and outperformed the clinical model (AUC, 0.678 and 0.776, in the training and test sets).

CONCLUSIONS

2D CTTA signature performs better than 3D CTTA signature. The 2D CTTA nomogram with the 2D signature and clinical predictors incorporated provides the similar performance as the 2D signature for individual LVI prediction in LAC.

Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma

PURPOSE

Lymphovascular invasion (LVI) impairs surgical outcomes in lung adenocarcinoma (LAC) patients. Preoperative prediction of LVI is challenging by using traditional clinical and imaging parameters. The purpose of this study was to investigate the value of the radiomics nomogram integrating clinical factors, CT features, and maximum standardized uptake value (SUVmax) to predict LVI and outcome in LAC and to evaluate the additional value of the SUVmax to the PET/CT-based radiomics nomogram.

METHODS

A total of 272 LAC patients (87 LVI-present LACs and 185 LVI-absent LACs) with PET/CT scans were retrospectively enrolled, and 160 patients with SUVmax ≥ 2.5 of them were used for PET radiomics analysis. Clinical data and CT features were analyzed to select independent LVI predictors. The performance of the independent LVI predictors and SUVmax was evaluated. Two-dimensional (2D) and three-dimensional (3D) CT radiomics signatures (RSs) and PET-RS were constructed with the least absolute shrinkage and selection operator algorithm and radiomics scores (Rad-scores) were calculated. The radiomics nomograms, incorporating Rad-score and independent clinical and CT factors, with SUVmax (RNWS) or without SUVmax (RNWOS) were built. The performance of the models was assessed with respect to calibration, discrimination, and clinical usefulness. All the clinical, PET/CT, pathologic, therapeutic, and radiomics parameters were assessed to identify independent predictors of progression-free survival (PFS).

RESULTS

CT morphology was the independent LVI predictor. SUVmax provided better discrimination capability compared with CT morphology in the training set (P < 0.001) and test set (P = 0.042). A total of 1409 CT and PET radiomics features were extracted and reduced to 8, 8, and 10 features to build the 2D CT-RS, 3D CT-RS, and the PET-RS, respectively. There was no significant difference in AUC between the 2D-RS and 3D-RS (P > 0.05), and 2D CT-RS showed a relatively higher AUC than 3D CT-RS. The CT-RS, the CT-RNWOS, and the CT-RNWS showed good discrimination in the training set (AUC [area under the curve], 0.799, 0.796, and 0.851, respectively) and the test set (AUC, 0.818, 0.822, and 0.838, respectively). There was significant difference in AUC between the CT-RNWS and CT-RNWOS (P = 0.044) in the training set. Decision curve analysis (DCA) demonstrated the CT-RNWS outperformed the CT-RS and the CT-RNWOS in terms of clinical usefulness. Furthermore, DCA showed the PETCT-RNWS provided the highest net benefit compared with the PET-RNWS and CT-RNWS. PFS was significantly different between the pathologic and RNWS-predicted LVI-present and LVI-absent patients (P < 0.001). Carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), pathologic LVI, histologic subtype, and SUVmax were independent predictors of PFS in the 244 CT-RNWS-predicted cohort; and CA125, NSE, pathologic LVI, and SUVmax were the independent predictors of PFS in the 141 PETCT-RNWS-predicted cohort.

CONCLUSIONS

The radiomics nomogram, incorporating Rad-score, clinical and PET/CT parameters, shows favorable predictive efficacy for LVI status in LAC. Pathologic LVI and SUVmax are associated with LAC prognosis.

Combining fluorine-18 fluorodeoxyglucose positron emission tomography and pathological risk factors to predict postoperative recurrence in stage I lung adenocarcinoma

OBJECTIVE

The aim of this study was to investigate the predictive value of qualitative assessment of tumor fluorine-18 fluorodeoxyglucose (F-FDG) uptake on PET and pathological risk factors for postoperative tumor recurrence in patients with stage I lung adenocarcinoma.

PATIENTS AND METHODS

Eighty-seven patients with stage I lung adenocarcinoma who had undergone F-FDG-PET and sequential surgical treatment without adjuvant chemotherapy were enrolled into this retrospective study. Qualitative assessment visually compared tumor F-FDG uptake with liver uptake. Tumors with one or more risk factors of tumor size of at least 4 cm, poorly differentiated, visceral pleural invasion, and lymphovascular invasion were defined as pathological high-risk tumors.

RESULTS

Patients with pathological high-risk tumors had a significantly (P=0.015) higher standardized uptake value. A multivariable Cox's proportional hazard analysis showed that tumor F-FDG uptake>liver uptake (adjusted hazard ratio: 3.54; 95% confidence interval: 1.36-9.21, P=0.010) and pathological high-risk tumors (adjusted hazard ratio: 2.34; 95% confidence interval: 1.13-4.87, P=0.023) were significant independent predictors of postoperative tumor recurrence. Patients with tumor F-FDG uptake>liver uptake and pathological high-risk tumors had significantly (P=0.001) worse 5-year disease-free survival (38.8%) and significantly (P=0.011) worse overall survival (68.5%).

CONCLUSION

Tumor F-FDG uptake>liver uptake and pathological high-risk tumors were significant independent predictors of postoperative tumor recurrence in stage I lung adenocarcinoma. Combining the two factors improves the prediction of disease-free and overall survivals, which could offer a feasible prediction model for clinically recommending adjuvant chemotherapy.

A comparative analysis of dual-phase dual-energy CT and FDG-PET/CT for the prediction of histopathological invasiveness of non-small cell lung cancer

PURPOSE

To compare dual-phase dual-energy CT (DE-CT) with FDG-PET/CT for predicting histopathological locoregional invasiveness of non-small cell lung cancers (NSCLCs).

MATERIALS AND METHODS

We selected 63 consecutive patients with NSCLC lesions (37 males, 26 females; age range, 44-85 years; mean age, 69 years) who were evaluated preoperatively by both DE-CT and PET/CT at our institution. Postoperative microscopic invasiveness (lymphatic permeation, vascular invasion, and/or pleural involvement) was reviewed, and we defined locoregionally invasive tumors as those that had at least one positive finding of microscopic invasiveness. DE-CT scanning in the arterial and delayed phases was performed after injection of iodinated contrast media using 140-kVp and 80-kVp tube voltages. Three-dimensional iodine-related attenuation of primary tumors in the arterial and delayed phases was quantified automatically using "syngo Dual Energy Lung Nodules" application software, and the ratio of arterial phase to delayed phase enhancement (A/D ratio) was calculated. The A/D ratio and SUVmax on PET/CT were evaluated with respect to postoperative invasiveness by univariate logistic regression analysis.

RESULTS

The A/D ratio was significantly correlated with lymphatic permeation, vascular invasion, and pleural involvement (p=0.011, p=0.021, and p=0.010, respectively). In contrast, the SUVmax was significantly correlated with pleural involvement (p=0.020) but not with lymphatic permeation or vascular invasion (p=0.088 and p=0.100, respectively). In the subgroup of patients with lesion diameters ≤2cm, the A/D ratio was significantly correlated with locoregional invasiveness (p=0.040), while the SUVmax was not (p=0.121).

CONCLUSION

For the prediction of microscopic invasiveness of NSCLCs, the diagnostic performance of dual-phase DE-CT may be comparable to that of FDG-PET/CT.