Lung cancer with PET/CT-defined occult nodal metastasis yields favourable prognosis and benefits from adjuvant therapy: a multicentre study

Multicenter evaluation of predictive clinical and imaging factors for pathological response in non-small cell lung cancer patients treated with neoadjuvant chemotherapy and immune checkpoint inhibitors

BACKGROUND

This study aimed to identify clinical factors and develop a predictive model for pathological complete response (pCR) and major pathological response (MPR) in non-small cell lung cancer (NSCLC) patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors (ICIs).

METHODS

Cases meeting inclusion criteria were divided into high- and low-risk groups according to 75 clinical indicators based on tenfold LASSO selection. Logistic regression was employed to analyze both pCR and MPR. The accuracy of the nomograms was assessed using the time-dependent area under the curve (AUC).

RESULTS

A total of 297 patients from four multiple centers were included in the study, with 212 assigned to the training set and 85 to the testing set. The AUC was determined for the prediction of pCR (training: 0.97; testing: 0.88) and MPR (training: 0.98; testing: 0.81). Significant associations were observed between the preoperative tumor maximum diameter, preoperative tumor maximum standardized uptake value (SUVmax), changes in tumor SUVmax, percentage of tumor reduction, baseline total prostate-specific antigen (TPSA) and pathological response (P < 0.001).

CONCLUSIONS

The combined application of clinical indicators including non-invasive tumor imaging and hematology can help clinicians to obtain a higher ability to predict NSCLC patient's pathological remission, and the effect is better than that of clinical factors alone. These findings could help guide personalized treatment strategies in this patient population.

Prediction of EGFR mutation status and its subtypes in non-small cell lung cancer based on 18 F-FDG PET/CT radiological features

PURPOSE

Prediction of epidermal growth factor receptor (EGFR) mutation status and subtypes in patients with non-small cell lung cancer (NSCLC) based on 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (CT) radiomics features.

PATIENTS AND METHODS

Retrospective analysis of 201 NSCLC patients with 18 F-FDG PET/CT and EGFR genetic testing was carried out. Radiomics features and clinical factors were used to construct a combined model for identifying EGFR mutation status. Mutation/wild-type models were trained in a training cohort ( n  = 129) and validated in an internal validation cohort ( n  = 41) vs an external validation cohort ( n  = 50). A second model predicting the 19/21 mutation locus was also built and evaluated in a subset of EGFR mutations (training cohort, n  = 55; validation cohort, n  = 14). The predictive performance and net clinical benefit of the models were assessed by analysis of the area under curve (AUC) of the subjects, nomogram, calibration curve and decision curve.

RESULTS

The AUC of the combined model distinguishing EGFR mutation status was 0.864 in the training cohort and 0.806 and 0.791 in the internal vs external test sets respectively, and the AUC of the 19/21 mutation site model was 0.971 and 0.867 in the training cohort and internal validation cohort respectively. The calibration curves of the individual models showed better model predictions (Brier score <0.25). Decision curve analysis showed that the models had clinical application.

CONCLUSION

The combined model based on 18 F-FDG PET/CT radiomics features combined and clinical features can predict EGFR mutation status and subtypes in NSCLC patients, and guiding targeted therapy, and facilitate precision medicine development.

FDG PET/CT for Staging Lung Carcinoma: An Update

In non-small cell lung carcinoma (NSCLC) carcinoma, the CT-part of the FDG PET/CT examination is of primary importance for T (tumor)-status assessment, while information derived from the primary tumor on the FDG-part of the examination may provide additional information on N- (lymph node) status. FDG PET/CT imaging was shown to have an overall sensitivity of 85% and a specificity of 84% for identifying LN involvement in NSCLC. Parameters that may predict the presence and quantify the risk of LN-involvement in NSCLC missed on FDG PET/CT imaging are tumor size and its increase over time, tumor differentiation degree, the number of days elapsed from the time of initial diagnosis, an adenocarcinoma subtype, a central versus peripheral location of the primary tumor and a solid versus mixed solid-ground glass radiologic character. Nomograms incorporating several of these variables have been published and made available for clinical usage. Furthermore, FDG PET/CT imaging was shown to have an overall higher sensitivity for identifying extra-thoracic metastases than convential morphological imaging and this especially for bone and adrenal lesions. In small cell lung carcinoma (SCLC), limited available data have shown FDG PET/CT imaging to be systematically more accurate for staging purposes when compared to conventional staging and to lead to a change in disease stage (limited versus extensive disease) in up to 15% of SCLC-patients.

Surgery versus concurrent chemoradiotherapy for stage III non-small cell lung cancer: a retrospective study with propensity score matching

BACKGROUND

No study has directly compared the outcomes of surgery and concurrent chemoradiotherapy (cCRT) in patients with stage III non-small cell lung cancer (NSCLC) to date. This study aimed to compare the treatment efficacy of complete resection and definitive cCRT.

METHODS

Patients were recruited in this retrospective study from Yokohama Municipal Citizens' Hospital between January 2013 and December 2022. We analyzed patients with pathological stage III NSCLC who underwent complete surgical resection and those with clinical stage III NSCLC who underwent definitive cCRT. Propensity score matching was performed to balance baseline clinicopathological factors, and the prognoses of patients in each treatment group were examined using Cox proportional hazards regression.

RESULTS

Of the 923 patients with NSCLC who underwent surgery, 97 with pathologic stage III NSCLC underwent complete resection (surgery group) and 125 with clinical stage III NSCLC underwent cCRT (cCRT group), of whom 54 (43.2%) received consolidation therapy with durvalumab. Overall survival (OS) was significantly higher in the surgery group than in the cCRT group (5-year OS: 60.5% versus 43.0%), hazard ratio [HR] = 0.585, 95% confidence interval [CI]: 0.390-0.877, p = 0.010). However, no significant difference in OS was found between the two groups after propensity score matching (5-year OS: 59.8% versus 48.1%, HR = 0.728, 95% CI: 0.416-1.277, p = 0.268).

CONCLUSIONS

The outcomes of the surgery and cCRT groups did not significantly differ in the treatment of stage III NSCLC. Appropriate evaluation of the treatment required should be reviewed on a case-by-case basis.

Predicting invasiveness of ground-glass nodules in lung adenocarcinoma: based on preoperative 18 F-fluorodeoxyglucose PET/computed tomography and high-resolution computed tomography

OBJECTIVE

This study was conducted to explore the differential diagnostic value of PET/computed tomography (PET/CT) combined with high-resolution computed tomography (HRCT) in predicting the invasiveness of ground-glass nodules (GGNs).

MATERIALS AND METHODS

This retrospective analysis included 67 patients (mean age 62.5 ± 8.4, including 45 females and 22 males) with GGNs who underwent preoperative 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT and HRCT examinations between January 2018 and October 2022. Based on the postoperative pathological results of lung adenocarcinoma, the patients were classified into two groups: invasive adenocarcinoma (IAC) and non-IAC. Besides, the clinical and imaging information of these patients was collected. HRCT signs include the existence of air bronchial signals, vascular convergence, pleural indentation, lobulation, and spiculation. Moreover, the diameter of solid components (D Solid ), diameter of ground-glass nodules (D GGN ), and computed tomography values of ground-glass nodules (CT GGN ) were measured concurrently. Furthermore, the mean standardized uptake value, maximal standardized uptake value (SUVmax), metabolic tumor volume, and total lesion glycolysis were assessed during PET/CT. Associations between invasiveness and these factors were evaluated using univariate and multivariate analyses.

RESULTS

The results of logistic regression analysis demonstrated that D GGN , D Solid , consolidation tumor ratio (CTR), CT GGN , and SUVmax were independent predictors in the IAC group. The combined diagnosis based on these five predictors revealed that area under the curve was 0.825.

CONCLUSION

The D GGN , D Solid , CTR, CT GGN , and SUVmax in GGNs were independent predictors of IAC, and combining 18 F-FDG PET/CT metabolic parameters with HRCT may improve the predictive value of pathological classification in lung adenocarcinoma.

Exploring clinical factors to predict the survival of patients with resectable non-small cell lung cancer with neoadjuvant immunotherapy

OBJECTIVES

The goal was to explore clinical factors and build a predictive model for the disease-free and overall survival of patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors.

METHODS

Inclusion criteria for patients in this multicentre study were as follows: (i) Patients who were diagnosed with stages I-III NSCLC after a bronchoscopy biopsy or puncture; (ii) patients who were examined with computed tomography/positron emission tomography-computed tomography before treatment and surgery; (iii) patients who received neoadjuvant chemotherapy combined with immune checkpoint inhibitors for 2 to 6 cycles preoperatively; (iv) patients whose peripheral blood indicators and tumour markers were assessed before treatment and preoperatively; (v) patients who underwent radical lung cancer surgery after neoadjuvant therapy. Cases were divided into high- and low-risk groups according to 78 clinical indicators based on a 10-fold Least Absolute Shrinkage and Selection Operator selection. We used Cox proportional hazards models to predict disease-free and overall survival. Then, we used time-dependent area under the curve and decision curve analyses to examine the accuracy of the results.

RESULTS

Data were collected continuously, and 212 and 85 cases were randomly assigned to training and testing sets, respectively. The area under the curve for the prediction of disease-free survival (training: 1 year, 0.83; 2 years, 0.81; 3 years, 0.83 versus testing: 1 year, 0.65; 2 years, 0.66; 3 years, 0.70), overall survival (training: 1 year, 0.86; 2 years, 0.85; 3 years, 0.86 versus testing: 1 year, 0.66; 2 years, 0.57; 3 years, 0.70) were determined. The coefficient factors including pathological response; preoperative tumour maximum diameter; preoperative lymph shorter diameter; preoperative tumour and lymph maximum standardized uptake value; change in tumour standardized uptake value preoperatively; and blood-related risk factors were favourably associated with prognosis (P < 0.001).

CONCLUSIONS

Our prediction model, which integrated data from preoperative positron emission tomography-CT, preoperative blood parameters and pathological response, was able to make highly accurate predictions for disease-free and overall survival in patients with NSCLC receiving neoadjuvant immunity with chemical therapy.

Dysfunction of CD8+ T cells around tumor cells leads to occult lymph node metastasis in NSCLC patients

Occult lymph node metastasis (OLNM) is one of the main causes of regional recurrence in inoperable N0 non-small cell lung cancer (NSCLC) patients following stereotactic ablation body radiotherapy (SABR) treatment. The integration of immunotherapy and SABR (I-SABR) has shown preliminary efficiency in mitigating this recurrence. Therefore, it is necessary to explore the functional dynamics of critical immune effectors, particularly CD8+ T cells in the development of OLNM. In this study, tissue microarrays (TMAs) and multiplex immunofluorescence (mIF) were used to identify CD8+ T cells and functional subsets (cytotoxic CD8+ T cells/predysfunctional CD8+ T cells (CD8+ Tpredys)/dysfunctional CD8+ T cells (CD8+ Tdys)/other CD8+ T cells) among the no lymph node metastasis, OLNM, and clinically evident lymph node metastasis (CLNM) groups. As the degree of lymph node metastasis escalated, the density of total CD8+ T cells and CD8+ Tdys cells, as well as their proximity to tumor cells, increased progressively and remarkably in the invasive margin (IM). In the tumor center (TC), both the density and proximity of CD8+ Tpredys cells to tumor cells notably decreased in the OLNM group compared with the group without metastasis. Furthermore, positive correlations were found between the dysfunction of CD8+ T cells and HIF-1α+CD8 and cancer microvessels (CMVs). In conclusion, the deterioration in CD8+ T cell function and interactive dynamics between CD8+ T cells and tumor cells play a vital role in the development of OLNM in NSCLC. Strategies aimed at improving hypoxia or targeting CMVs could potentially enhance the efficacy of I-SABR.

A clinical nomogram for predicting occult lymph node metastasis in patients with non-small-cell lung cancer ≤2 cm

OBJECTIVES

Sublobar resection has been shown to be feasible for non-small-cell lung cancers (NSCLC) <2 cm in size based on several prospective studies. However, the prognosis of clinical N0 patients who experience an N-stage upgrade after surgery [known as occult lymph node metastasis (OLM)] may be worse. The ability of predict OLM in patients eligible for sublobar resection remains a controversial issue.

METHODS

Patients with NSCLC ≤2 cm in diameter and containing a solid component who underwent surgical treatment at the Affiliated Hospital of Qingdao University were retrospectively enrolled, and 1:1 case matching was performed. The risk factors were identified through logistic regression analyses and theoretical criteria, followed by the development of a nomogram that was evaluated using 200 iterations of 10-fold cross-validation.

RESULTS

After case matching, 130 pairs of patients were selected for modelling. According to the multivariable logistic regression analysis, the carcinoembryonic antigen level, consolidation tumour ratio, mean computed tomography number and tumour margin were included in the nomogram. The cross-validated average area under the receiver operating characteristic curve was found to be 0.86. Furthermore, calibration curve and decision curve analyses demonstrated the excellent predictive accuracy and clinical utility of the nomogram respectively.

CONCLUSIONS

By utilizing accessible characteristics, we developed a nomogram that predicts the probability of OLM in patients with NSCLC ≤2 cm with a solid component. Risk stratification with this nomogram could aid in surgical method decision-making.

CLINICAL REGISTRATION NUMBER

Not applicable.

Incidence rate of occult lymph node metastasis in clinical T1-2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research

BACKGROUND

This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data.

METHODS

By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV).

RESULTS

The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients.

CONCLUSIONS

The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

Multiparametric evaluation of mediastinal lymph node metastases in clinical T0-T1c stage non-small-cell lung cancers

OBJECTIVES

This study aimed to determine the predictive factors of lymph node metastases in clinical T0-T1c stage non-small-cell lung cancers, so as to help making surgical strategy.

METHODS

From January 2016 to December 2017, patients with clinical T0-T1c stage non-small-cell lung cancers were retrospectively reviewed. We elucidated the lymph node metastatic incidence and distribution according to the primary tumour radiographic findings and maximal standard uptake values, and extracted the associated clinicopathological factors. Univariable and multivariable logistic regressions were used to identify independent predictive parameters for lymph node metastases. The performance of predictive model was evaluated using receiver operating characteristic analysis.

RESULTS

A total of 517 patients were included. Seventy-two patients had lymph node metastases. Among patients with pure ground-glass nodule and solid component size ≤10 mm, none had any lymph node metastasis. Multivariable logistic regression analysis demonstrated that age, carcinoembryonic antigen level, solid component size, consolidation-tumour ratio and tumour maximal standard uptake values were independent predictors of lymph nodal metastases. Receiver operating characteristic analyses indicated that the area under the curve of predictive model in evaluating lymph node metastases was 0.838 (95% CI 0.791-0.886).

CONCLUSIONS

Younger age, elevated carcinoembryonic antigen level, larger solid component size, higher consolidation-tumour ratio and tumour maximal standard uptake values were associated with lymph node involvement. Employing such a predictive model in the future may affect the surgical option of lymph node excision for patients in cT1 stage non-small-cell lung cancer.

Clinical utility of [18F]FDG PET/CT in the assessment of mediastinal lymph node disease after neoadjuvant chemoimmunotherapy for non-small cell lung cancer

OBJECTIVES

The performance of positron emission tomography/computed tomography (PET/CT) for the prediction of ypN2 disease in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy has not been reported. This multicenter study investigated the utility of PET/CT to assess ypN2 disease in these patients.

METHODS

A total of 181 consecutive patients (chemoimmunotherapy = 86, chemotherapy = 95) at four institutions were enrolled in this study. Every patient received a PET/CT scan prior to surgery and complete resection with systematic nodal dissection. The diagnostic performance was evaluated through area under the curve (AUC). Kaplan-Meier method and Cox analysis were performed to identify the risk factors affecting recurrences.

RESULTS

The sensitivity, specificity, and accuracy of PET/CT for ypN2 diseases were 0.667, 0.835, and 0.779, respectively. Therefore, the AUC was 0.751. Compared with the false positive cases, the mean value of max standardized uptake value (SUVmax) (6.024 vs. 2.672, p < 0.001) of N2 nodes was significantly higher in true positive patients. Moreover, the SUVmax of true positive (7.671 vs. 5.976, p = 0.365) and false (2.433 vs. 2.339, p = 0.990) positive cases were similar between chemoimmunotherapy and chemotherapy, respectively. Survival analysis proved that pathologic N (ypN) 2 patients could be stratified by PET/CT-N2(+ vs. -) for both chemoimmunotherapy (p = 0.023) and chemotherapy (p = 0.010).

CONCLUSIONS

PET/CT is an accurate and non-invasive test for mediastinal restaging of NSCLC patients who receive neoadjuvant chemoimmunotherapy. The ypN2 patients with PET/CT-N2( +) are identified as an independent prognostic factor compared with PET/CT-N2(-).

CLINICAL RELEVANCE STATEMENT

Imaging with 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) plays an integral role during disease diagnosis, staging, and therapeutic response assessments in patients with NSCLC. PET/CT could be an effective non-invasive tool for predicting ypN2 diseases after neoadjuvant chemoimmunotherapy.

KEY POINTS

• PET/CT could serve as an effective non-invasive tool for predicting ypN2 diseases. • The ypN2 patients with PET/CT-N2( +) were a strong and independent prognostic factor. • The application of PET/CT for restaging should be encouraged in clinical practice.

Occult lymph node metastasis is not a favorable factor for resected NSCLC patients

BACKGROUND

This study was to compare the clinical presentations and survivals between the non-small cell lung cancer (NSCLC) patients with occult lymph node metastasis (OLNM) and those with evident lymph node metastasis (ELNM). We also intended to analyze the predictive factors for OLNM.

METHODS

Kaplan-Meier method with log-rank test was used to compare survivals between groups. Propensity score matching (PSM) was used to reduce bias. The least absolute shrinkage and selection operator (LASSO)-penalized Cox multivariable analysis was used to identify the prognostic factors. Random forest was used to determine the predictive factors for OLNM.

RESULTS

A total of 2,067 eligible cases (N0: 1,497 cases; occult N1: 165 cases; evident N1: 54 cases; occult N2: 243 cases; evident N2: 108 cases) were included. The rate of OLNM was 21.4%. Patients with OLNM were tend to be female, non-smoker, adenocarcinoma and had smaller-sized tumors when compared with the patients with ELNM. Survival curves showed that the survivals of the patients with OLNM were similar to those of the patients with ELNM both before and after PSM. Multivariable Cox analysis suggested that positive lymph nodes (PLN) was the only prognostic factor for the patients with OLNM. Random forest showed that clinical tumor size was an important predictive factor for OLNM.

CONCLUSIONS

OLNM was not rare. OLNM was not a favorable sign for resected NSCLC patients with lymph node metastasis. PLN determined the survivals of the patients with OLNM. Clinical tumor size was a strong predictive factor for OLNM.

Predictive value of PET metabolic parameters for occult lymph node metastases in PET/CT defined node-negative patients with advanced epithelial ovarian cancer

Accurate lymph node metastasis (LNM) prediction is crucial for patients with advanced epithelial ovarian cancer (AEOC) since it guides the decisions about lymphadenectomy. Previous studies have shown that occult lymph node metastasis (OLNM) is common in AEOC. The objective of our study is to quantitatively assess the probability of occult lymph node metastasis defined by 18F-Fluorodeoxyglucose PET/CT in AEOC and explore relationship between OLNM and PET metabolic parameters. The patients with pathologically confirmed AEOC who underwent PET/CT for preoperative staging at our institute were reviewed. Univariate and multivariate analysis were performed to evaluate the predictive value of PET/CT-related metabolic parameters for OLNM. The result of our study showed metastatic TLG index had a better diagnostic performance than other PET/CT-related metabolic parameters. Two variables were independently and significantly associated with OLNM in multivariate analysis: metastatic TLG index and primary tumor location. The logistic model combining metastatic TLG index, primary tumor location, and CA125 might be a promising tool to effectively predict the individualized possibility of OLNM for AEOC patients.