Prediction of occult lymph node metastasis using volume-based PET parameters in small-sized peripheral non-small cell lung cancer

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.

Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study

OBJECTIVE

To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment.

METHODS

We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively.

RESULTS

In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively).

CONCLUSIONS

Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.

Does high [18F]FDG uptake always mean poor prognosis? Colon cancer with high-level microsatellite instability is associated with high [18F]FDG uptake on PET/CT

OBJECTIVES

High-level microsatellite instability (MSI-high) is generally associated with higher F-18 fluorodeoxyglucose ([18F]FDG) uptake than stable microsatellite (MSI-stable) tumors. However, MSI-high tumors have better prognosis, which is in contrast with general understanding that high [18F]FDG uptake correlates with poor prognosis. This study evaluated metastasis incidence with MSI status and [18F]FDG uptake.

METHODS

We retrospectively reviewed 108 right-side colon cancer patients who underwent preoperative [18F]FDG PET/CT and postoperative MSI evaluations using a standard polymerase chain reaction at five Bethesda guidelines panel loci. The maximum standard uptake value (SUVmax), SUVmax tumor-to-liver ratio (TLR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor were measured using SUV 2.5 cut-off threshold. Student's t-test or Mann-Whitney U test was performed for continuous variables, and χ2 test or Fisher's exact test was performed for categorical variables (p value of  < 0.05 for statistical significance). Medical records were reviewed for metastasis incidence.

RESULTS

Our study population had 66 MSI-stable and 42 MSI-high tumors. [18F]FDG uptake was higher in MSI-high tumors than MSI-stable tumors (TLR, median (Q1, Q3): 7.95 (6.06, 10.54) vs. 6.08 (4.09, 8.82), p = 0.021). Multivariable subgroup analysis demonstrated that higher [18F]FDG uptake was associated with higher risks of distant metastasis in MSI-stable tumors (SUVmax: p = 0.025, MTV: p = 0.008, TLG: p = 0.019) but not in MSI-high tumors.

CONCLUSION

MSI-high colon cancer is associated with high [18F]FDG uptake, but unlike MSI-stable tumors, the degree of [18F]FDG uptake does not correlate with the rate of distant metastasis.

CLINICAL RELEVANCE STATEMENT

MSI status should be considered during PET/CT assessment of colon cancer patients, as the degree of [18F]FDG uptake might not reflect metastatic potential in MSI-high tumors.

KEY POINTS

• High-level microsatellite instability (MSI-high) tumor is a prognostic factor for distant metastasis. • MSI-high colon cancers had a tendency of demonstrating higher [18F]FDG uptake compared to MSI-stable tumors. • Although higher [18F]FDG uptake is known to represent higher risks of distant metastasis, the degree of [18F]FDG uptake in MSI-high tumors did not correlate with the rate at which distant metastasis occurred.

Additional Value of PET and CT Image-Based Features in the Detection of Occult Lymph Node Metastases in Lung Cancer: A Systematic Review of the Literature

Lung cancer represents the second most common malignancy worldwide and lymph node (LN) involvement serves as a crucial prognostic factor for tailoring treatment approaches. Invasive methods, such as mediastinoscopy and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), are employed for preoperative LN staging. Among the preoperative non-invasive diagnostic methods, computed tomography (CT) and, recently, positron emission tomography (PET)/CT with fluorine-18-fludeoxyglucose ([¹⁸F]FDG) are routinely recommended by several guidelines; however, they can both miss pathologically proven LN metastases, with an incidence up to 26% for patients staged with [¹⁸F]FDG PET/CT. These undetected metastases, known as occult LN metastases (OLMs), are usually cases of micro-metastasis or small LN metastasis (shortest radius below 10 mm). Hence, it is crucial to find novel approaches to increase their discovery rate. Radiomics is an emerging field that seeks to uncover and quantify the concealed information present in biomedical images by utilising machine or deep learning approaches. The extracted features can be integrated into predictive models, as numerous reports have emphasised their usefulness in the staging of lung cancer. However, there is a paucity of studies examining the detection of OLMs using quantitative features derived from images. Hence, the objective of this review was to investigate the potential application of PET- and/or CT-derived quantitative radiomic features for the identification of OLMs.

Efficacy of radiomics model based on the concept of gross tumor volume and clinical target volume in predicting occult lymph node metastasis in non-small cell lung cancer

Objective

This study aimed to establish a predictive model for occult lymph node metastasis (LNM) in patients with clinical stage I-A non-small cell lung cancer (NSCLC) based on contrast-enhanced CT.

Methods

A total of 598 patients with stage I-IIA NSCLC from different hospitals were randomized into the training and validation group. The "Radiomics" tool kit of AccuContour software was employed to extract the radiomics features of GTV and CTV from chest-enhanced CT arterial phase pictures. Then, the least absolute shrinkage and selection operator (LASSO) regression analysis was applied to reduce the number of variables and develop GTV, CTV, and GTV+CTV models for predicting occult lymph node metastasis (LNM).

Results

Eight optimal radiomics features related to occult LNM were finally identified. The receiver operating characteristic (ROC) curves of the three models showed good predictive effects. The area under the curve (AUC) value of GTV, CTV, and GTV+CTV model in the training group was 0.845, 0.843, and 0.869, respectively. Similarly, the corresponding AUC values in the validation group were 0.821, 0.812, and 0.906. The combined GTV+CTV model exhibited a better predictive performance in the training and validation group by the Delong test (p<0.05). Moreover, the decision curve showed that the combined GTV+CTV predictive model was superior to the GTV or CTV model.

Conclusion

The radiomics prediction models based on GTV and CTV can predict occult LNM in patients with clinical stage I-IIA NSCLC preoperatively, and the combined GTV+CTV model is the optimal strategy for clinical application.

The value on SUV-derived parameters assessed on 18F-FDG PET/CT for predicting mediastinal lymph node metastasis in non-small cell lung cancer

PURPOSE

To explore valuable predictors for mediastinal lymph node metastasis in non-small cell lung cancer (NSCLC) patients, we analyzed the potential roles of standardized uptake value (SUV)-derived parameters from preoperative ¹⁸F-FDG PET/CT combined with clinical characteristics.

METHODS

Data from 224 NSCLC patients who underwent preoperative ¹⁸F-FDG PET/CT scans in our hospital were collected. Then, a series of clinical parameters including SUV-derived features [SUVmax of mediastinal lymph node and primary-tumor SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG)] were evaluated. The best possible cutoff points for all measuring parameters were calculated using receiver operating characteristic curve (ROC) analysis. Predictive analyses were performed using a Logistic regression model to determine the predictive factors for mediastinal lymph node metastasis in NSCLC and lung adenocarcinoma patients. After multivariate model construction, data of another 100 NSCLC patients were recorded. Then, 224 patients and 100 patients were enrolled to validate the predictive model by the area under the receiver operating characteristic curve (AUC).

RESULTS

The mediastinal lymph node metastasis rates in 224 patients for model construction and 100 patients for model validation were 24.1% (54/224) and 25% (25/100), respectively. It was found that SUVmax of mediastinal lymph node ≥ 2.49, primary-tumor SUVmax ≥ 4.11, primary-tumor SUVpeak ≥ 2.92, primary-tumor SUVmean ≥ 2.39, primary-tumor MTV ≥ 30.88 cm³, and primary-tumor TLG ≥ 83.53 were more prone to mediastinal lymph node metastasis through univariate logistic regression analyses. The multivariate logistic regression analyses showed that the SUVmax of mediastinal lymph nodes (≥ 2.49: OR 7.215, 95% CI 3.326-15.649), primary-tumor SUVpeak (≥ 2.92: OR 5.717, 95% CI 2.094-15.605), CEA (≥ 3.94 ng/ml: OR 2.467, 95% CI 1.182-5.149), and SCC (< 1.15 ng/ml: OR 4.795, 95% CI 2.019-11.388) were independent predictive factors for lymph node metastasis in the mediastinum. It was found that SUVmax of the mediastinal lymph node (≥ 2.49: OR 8.067, 95% CI 3.193-20.383), primary-tumor SUVpeak (≥ 2.92: OR 9.219, 95% CI 3.096-27.452), and CA19-9 (≥ 16.6 U/ml: OR 3.750, 95% CI 1.485-9.470) were significant predictive factors for mediastinal lymph node metastasis in lung adenocarcinoma patients. The AUCs for the predictive value of the NSCLC multivariate model through internal and external validation were 0.833 (95% CI 0.769- 0.896) and 0.811 (95% CI 0.712-0.911), respectively.

CONCLUSION

High SUV-derived parameters (SUVmax of mediastinal lymph node and primary-tumor SUVmax, SUVpeak, SUVmean, MTV and TLG) might provide varying degrees of predictive value for mediastinal lymph node metastasis in NSCLC patients. In particular, the SUVmax of mediastinal lymph nodes and primary-tumor SUVpeak could be independently and significantly associated with mediastinal lymph node metastasis in NSCLC and lung adenocarcinoma patients. Internal and external validation confirmed that the pretherapeutic SUVmax of the mediastinal lymph node and primary-tumor SUVpeak combined with serum CEA and SCC can effectively predict mediastinal lymph node metastasis of NSCLC patients.

Do fine needle aspirate cytomorphological features correlate with positron emission tomography findings of metastatic non-small cell lung carcinoma in lymph nodes?

BACKGROUND

Our objective was to correlate cytomorphological features of metastatic non-small cell lung carcinoma (mNSCLC) with maximal standardized uptake value (mSUV) of positron emission tomography (PET) in Lymph nodes (LNs).

METHODS

Positive cytology slides of 114 LNs were reviewed from 100 patients with mNSCLC who had undergone PET study. Student's t-test was used for statistical comparisons.

RESULTS

Mean patients' age: 68.5, 54% male. LNs locations were: mediastinum: 99, lung hilum: 13, peribronchial: 1, axilla: 1. Final diagnoses were: Adenocarcinoma: 86, squamous cell carcinoma: 28 LNs. Within the adenocarcinoma subgroup, histological patterns correlate with mSUV. Acinar and papillary patterns were associated with significantly lower mSUVs (mean ± standard error (SE): 7.9 ± 0.9 and 9.2 ± 0.8, respectively) than solid pattern (13.0 ± 1.2; p values: 0.001 and 0.009, respectively). Similar difference exists between patterns associated with low- and high-grade adenocarcinoma (Mean ± SE: 9.2 ± 0.8 and 12.0 ± 1.0, respectively. p value: 0.02). Interestingly, micropapillary pattern was associated with the lowest mSUV amongst all patterns (Mean ± SE: 5.4 ± 1.1). Other features that correlated with higher mSUV were necrosis, moderate/severe nuclear atypia, lower lymphoid tissue yield, and contralateral LN involvement.

CONCLUSIONS

In LNs with mNSCLC, certain cytomorphological features are associated with higher mSUV. Micropapillary, a pattern considered as high-grade, is associated with lower SUV values; hence, a lower SUV threshold may raise concern for metastasis. Although high SUV is associated with LN metastasis, lower SUV levels in certain adenocarcinomas suggest correlation with clinical and morphological characteristics could be valuable in tailoring therapeutic management.

18F-FDG PET/CT radiomics nomogram for predicting occult lymph node metastasis of non-small cell lung cancer

Purpose

To investigate the ability of a PET/CT-based radiomics nomogram to predict occult lymph node metastasis in patients with clinical stage N0 non-small cell lung cancer (NSCLC).

Materials and methods

This retrospective study included 228 patients with surgically confirmed NSCLC (training set, 159 patients; testing set, 69 patients). ITKsnap3.8.0 was used for image(CT and PET images) segmentation, AK version 3.2.0 was used for radiomics feature extraction, and Python3.7.0 was used for radiomics feature screening. A radiomics model for predicting occult lymph node metastasis was established using a logistic regression algorithm. A nomogram was constructed by combining radiomics scores with selected clinical predictors. Receiver operating characteristic (ROC) curves were used to verify the performance of the radiomics model and nomogram in the training and testing sets.

Results

The radiomics nomogram comprising six selected features achieved good prediction efficiency, including radiomics characteristics and tumor location information (central or peripheral), which demonstrated good calibration and discrimination ability in the training (area under the ROC curve [AUC] = 0.884, 95% confidence interval [CI]: 0.826-0.941) and testing (AUC = 0.881, 95% CI: 0.8031-0.959) sets. Clinical decision curves demonstrated that the nomogram was clinically useful.

Conclusion

The PET/CT-based radiomics nomogram is a noninvasive tool for predicting occult lymph node metastasis in NSCLC.

PET/CT for Predicting Occult Lymph Node Metastasis in Gastric Cancer

A portion of gastric cancer patients with negative lymph node metastasis at an early stage eventually die from tumor recurrence or advanced metastasis. Occult lymph node metastasis (OLNM] is a potential risk factor for the recurrence and metastasis in these patients, and it is highly important for clinical prognosis. Positron emission tomography (PET)/computed tomography (CT) is used to assess lymph node metastasis in gastric cancer due to its advantages in anatomical and functional imaging and non-invasive nature. Among the major metabolic parameters of PET, the maximum standardized uptake value (SUVmax) is commonly used for examining lymph node status. However, SUVmax is susceptible to interference by a variety of factors. In recent years, the exploration of new PET metabolic parameters, new PET imaging agents and radiomics, has become an active research topic. This paper aims to explore the feasibility and predict the effectiveness of using PET/CT to detect OLNM. The current landscape and future trends of primary metabolic parameters and new imaging agents of PET are reviewed. For gastric cancer patients, the possibility to detect OLNM non-invasively will help guide surgeons to choose the appropriate lymph node dissection area, thereby reducing unnecessary dissections and providing more reasonable, personalized and comprehensive treatments.

The prognostic influence of histological subtypes of micropapillary tumors on patients with lung adenocarcinoma ≤ 2 cm

Objective

This study aimed to explore the value of micropapillary histological subtypes in predicting the specific surgical specificity and lymph node metastasis prognosis of early lung adenocarcinoma.

Methods

A total of 390 patients with lung adenocarcinoma were included who underwent surgery in the Department of Thoracic Surgery of the Affiliated Provincial Hospital of Anhui Medical University from January 2016 to December 2017. The data were analysed with SPSS 26.0 statistical software, and the clinicopathological data of the two groups were compared with the chi-square test. The survival rate was calculated by the Kaplan-Meier method, and the difference in survival rate between groups was analysed by the log-rank test. Multivariate survival analysis was performed using the Cox model.

Results

Univariate analysis of the clinicopathological data of the patients showed that the micropapillary histological subtype was significantly associated with the survival rate of patients (p=0.007). The clinicopathological data of the patients were substituted into the Cox model for multivariate analysis, and the results showed that the micropapillary histological subtype was an independent prognostic factor affecting the survival rate of the patients (p=0.009).The average survival time of Group A (micronipple composition > 5%) was 66.7 months; the 1-year, 3-year, and 5-year survival rates were 98.8%, 93.0%, and 80.9%, respectively.The survival of the lobectomy group was better than that of the sublobectomy group and the survival of patients with systematic dissection was better than that of patients with limited lymph node dissection. The average survival time of Group B (micronipple composition ≤ 5%) was 70.5 months; the 1-year, 3-year, and 5-year survival rates were 99.3%, 95.4%, and 90.6%, respectively. There was no difference in the survival rate between the lobectomy group and sublobectomy group, and there was also no difference in survival between systematic lymph node dissection and limited lymph node dissection, The survival rate of Group B was significantly better than that of Group A.

Conclusion

The micropapillary histological component is an independent risk factor after surgery in patients with ≤2 cm lung adenocarcinoma. When the proportion of micropapillary components is different, the prognosis of patients is different when different surgical methods and lymph node dissections are performed. Lobectomy and systematic lymph node dissection are recommended for patients with a micropapillary histological composition >5%; sublobar resection and limited lymph node dissection are recommended for patients with a micropapillary histological composition ≤5%.

Clinicopathological models for predicting lymph node metastasis in patients with early-stage lung adenocarcinoma: the application of machine learning algorithms

Background

Lymph node metastasis (LNM) status can be a critical decisive factor for clinical management of lung cancer. Accurately evaluating the risk of LNM during or after the surgery can be helpful for making clinical decisions. This study aims to incorporate clinicopathological characteristics to develop reliable machine learning (ML)-based models for predicting LNM in patients with early-stage lung adenocarcinoma.

Methods

A total of 709 lung adenocarcinoma patients with tumor size ≤2 cm were enrolled for analysis and modeling by multiple ML algorithms. The receiver operating characteristic (ROC) curve and decision curve were used for evaluating model’s predictive performance and clinical usefulness. Feature selection based on potential models was performed to identify most-contributed predictive factors.

Results

LNM occurred in 11.3% (80/709) of patients with lung adenocarcinoma. Most models reached high areas under the ROC curve (AUCs) >0.9. In the decision curve, all models performed better than the treat-all and treat-none lines. The random forest classifier (RFC) model, with a minimal number of five variables introduced (including carcinoembryonic antigen, solid component, micropapillary component, lymphovascular invasion and pleural invasion), was identified as the optimal model for predicting LNM, because of its excellent performance in both ROC and decision curves.

Conclusions

The cost-efficient application of RFC model could precisely predict LNM during or after the operation of early-stage adenocarcinomas (sensitivity: 87.5%; specificity: 82.2%). Incorporating clinicopathological characteristics, it is feasible to predict LNM intraoperatively or postoperatively by ML algorithms.

Prognostic Value of Combing Primary Tumor and Nodal Glycolytic-Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

We investigated whether the combination of primary tumor and nodal ¹⁸F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment ¹⁸F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell’s concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group.

Application of Artificial Neural Network to Preoperative 18F-FDG PET/CT for Predicting Pathological Nodal Involvement in Non-small-cell Lung Cancer Patients

Purpose: To evaluate the performance of artificial neural networks (aNN) applied to preoperative ¹⁸F-FDG PET/CT for predicting nodal involvement in non-small-cell lung cancer (NSCLC) patients.

Methods: We retrospectively analyzed data from 540 clinically resectable NSCLC patients (333 M; 67.4 ± 9 years) undergone preoperative ¹⁸F-FDG PET/CT and pulmonary resection with hilo-mediastinal lymphadenectomy. A 3-layers NN model was applied (dataset randomly splitted into 2/3 training and 1/3 testing). Using histopathological reference standard, NN performance for nodal involvement (N0/N+ patient) was calculated by ROC analysis in terms of: area under the curve (AUC), accuracy (ACC), sensitivity (SE), specificity (SP), positive and negative predictive values (PPV, NPV). Diagnostic performance of PET visual analysis (N+ patient: at least one node with uptake ≥ mediastinal blood-pool) and of logistic regression (LR) was evaluated.

Results: Histology proved 108/540 (20%) nodal-metastatic patients. Among all collected data, relevant features selected as input parameters were: patients' age, tumor parameters (size, PET visual and semiquantitative features, histotype, grading), PET visual nodal result (patient-based, as N0/N+ and N0/N1/N2). Training and testing NN performance (AUC = 0.849, 0.769): ACC = 80 and 77%; SE = 72 and 58%; SP = 81 and 81%; PPV = 50 and 44%; NPV = 92 and 89%, respectively. Visual PET performance: ACC = 82%, SE = 32%, SP = 94%; PPV = 57%, NPV = 85%. Training and testing LR performance (AUC = 0.795, 0.763): ACC = 75 and 77%; SE = 68 and 55%; SP = 77 and 82%; PPV = 43 and 43%; NPV = 90 and 88%, respectively.

Conclusions: aNN application to preoperative ¹⁸F-FDG PET/CT provides overall good performance for predicting nodal involvement in NSCLC patients candidate to surgery, especially for ruling out nodal metastases, being NPV the best diagnostic result; a high NPV was also reached by PET qualitative assessment. Moreover, in such population with low a priori nodal involvement probability, aNN better identify the relatively few and unexpected nodal-metastatic patients than PET analysis, so supporting the additional aNN use in case of PET-negative images.

Predicting occult lymph node metastasis by nomogram in patients with lung adenocarcinoma ≤2 cm

Background: Previous researches had not proposed any prediction models for occult lymph node metastasis (OLNM). Considering the occurrence of OLNM and the importance of OLNM management, we aimed to develop a nomogram to predict OLNM of patients with lung adenocarcinoma ≤2 cm. Methods: Characteristics of patients with lung adenocarcinoma of ≤2 cm diameter at the Peking Union Medical College Hospital were retrospectively reviewed. Univariate and multivariate logistic regressions were performed. A nomogram model was developed. The concordance index (C-index) and calibration and decision curves were used to evaluate the predictive ability. Results: A total of 473 patients were enrolled, with an OLNM incidence of 7.4%. Four factors were selected as risk factors. The model had a C-index of 0.932. Calibration and decision curves were determined. Conclusion: Patients with pure ground-glass opacity (pGGO) or noninvasive adenocarcinoma have significantly lower risk of OLNM. SUV_max, CEA, micropapillary and solid component were identified as independent risk factors. The nomogram model was effective in predicting OLNM preoperatively.

PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients

Despite the recent advances in lung cancer biology, molecular pathology, and treatment, this malignancy remains the leading cause of cancer-related death worldwide and non-small cell lung cancer (NSCLC) is the most common form found at diagnosis. Accurate staging of the disease is a fundamental prognostic factor that correctly predicts progression-free (PFS) and overall survival (OS) of NSCLC patients. However, outcome of patients within each TNM staging group can change widely highlighting the need to identify additional prognostic biomarkers to better stratify patients on the basis of risk. 18F-FDG PET/CT plays an essential role in staging, evaluation of treatment response, and tumoral target delineation in NSCLC patients. Moreover, a number of studies showed the prognostic role of imaging parameters derived from PET images, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). These parameters represent three-dimensional PET-based measurements providing information on both tumor volume and metabolic activity and previous studies reported their ability to predict OS and PFS of NSCLC patients. This review will primarily focus on the studies that showed the prognostic and predictive role of MTV and TLG in NSCLC patients, addressing also their potential utility in the new era of immunotherapy of NSCLC.

Tumor-to-liver standard uptake ratio using fluorine-18 fluorodeoxyglucose positron emission tomography computed tomography effectively predict occult lymph node metastasis of non-small cell lung cancer patients

OBJECTIVES

We aimed to investigate predictive factors of occult lymph node metastasis and to explore the diagnostic value of various standardized uptake value (SUV) parameters using fluorine-18 fluorodeoxyglucose (F-FDG) positron emission tomography computed tomography (PET/CT) in predicting occult lymph node metastasis of clinical N0 non-small cell lung cancer patients.

METHODS

We retrospectively analyzed PET/computed tomography parameters of tumor and clinical data of 124 clinical N0 non-small cell lung cancer patients who underwent both preoperative F-FDG PET/computed tomography and anatomical pulmonary resection with systematic lymph node dissections. The SUVmax, SUVmean, metabolic total volume, and total lesion glycolysis of the primary tumor was automatically measured on the PET/computed tomography workstation. Standardized uptake ratio (SUR) were derived from tumor standardized uptake value divided by blood SUVmean (B-SUR) or liver SUVmean (L-SUR), respectively.

RESULTS

According to postoperative pathology, 19 (15%) were diagnosed as occult lymph node metastasis among 124 clinical N0 non-small cell lung cancer patients. On univariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, lobulation, and all PET parameters were associated with occult lymph node metastasis. The area under the receiver operating characteristic curve, sensitivity, and negative predictive value of L-SURmax were the highest among all PET parameters (0.778, 94.7%, and 98.4%, respectively). On multivariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax were independent risk factors for predicting occult lymph node metastasis. Compared to L-SURmax alone and the combination of carcinoembryonic antigen and cytokeratin 19 fragment, the model consisting of three independent risk factors achieved a greater area under the receiver operating characteristic curve (0.901 vs. 0.778 vs. 0.780, P = 0.021 and 0.0141).

CONCLUSIONS

L-SURmax showed the most powerful predictive performance than the other PET parameters in predicting occult lymph node metastasis. The combination of three independent risk factors (carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax) can effectively predict occult lymph node metastasis in clinical N0 non-small cell lung cancer patients.

18F-FDG PET-based radiomics model for predicting occult lymph node metastasis in clinical N0 solid lung adenocarcinoma

Background

This study aimed to develop a preoperative positron emission tomography (PET)-based radiomics model for predicting occult lymph node metastasis (OLM) in clinical N0 (cN0) solid lung adenocarcinoma.

Methods

The preoperative fluorine-18-fludeoxyglucose (¹⁸F-FDG) PET images of 370 patients with cN0 lung adenocarcinoma confirmed by histopathological examination were retrospectively reviewed. Patients were divided into training and validation sets. Radiomics features and relevant data were extracted from PET images. A nomogram was developed in a training set via univariate and multivariate logistic analyses, and its performance was assessed by concordance-index (C-index), calibration curves, and decision curve analysis (DCA) in the training and validation sets.

Results

The multivariate logistic regression analysis showed that only carcinoembryonic antigen (CEA), metabolic tumor volume (MTV), and the radiomics signature had statistically significant differences between patients with and without OLM (P<0.05). A nomogram was developed based on the logistic analyses, and its C-index was 0.769 in the training set and 0.768 in the validation set. The calibration curve demonstrated good consistency between the nomogram-predicted probability of OLM and the actual rate. The DCA also confirmed the clinical utility of the nomogram.

Conclusions

A PET/computed tomography (CT)-based radiomics model including CEA, MTV, and the radiomics signature was developed and demonstrated adequate predictive accuracy and clinical net benefit in the present study, and was conveniently used to facilitate the individualized preoperative prediction of OLM.

Predictive Value of 18F-Fluorodeoxyglucose Positron Emission Tomography or Positron Emission Tomography/Computed Tomography for Assessment of Occult Lymph Node Metastasis in Non-Small Cell Lung Cancer

OBJECTIVE

The purpose of the current study was to investigate the diagnostic performance of 18F fluorodeoxyglucose (FDG) positron emission tomography (PET) or positron emission tomography/computed tomography (PET/CT) for the prediction of occult lymph node metastasis (OLNM) in non-small cell lung cancer (NSCLC) patients through a systematic review and meta-analysis.

METHODS

The PubMed, Cochrane, and EMBASE database, from the earliest available date of indexing through March 31, 2020, were searched for studies evaluating the diagnostic performance of preoperative 18F FDG PET or PET/CT for the prediction of OLNM in NSCLC patients.

RESULTS

Across 14 studies (3,535 patients), the pooled sensitivity for 18F FDG PET or PET/CT was 0.79 (95% CI; 0.70-0.86) with heterogeneity (I2 = 81.5, p < 0.001) and a pooled specificity of 0.65 (95% CI; 0.57-0.72) with heterogeneity (I2 = 93.7, p < 0.001). Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 2.3 (95% CI; 1.9-2.6) and a negative likelihood ratio (LR-) of 0.32 (95% CI; 0.23-0.44). The pooled diagnostic odds ratio (DOR) was 7 (95% CI; 5-10). The hierarchical summary receiver operating characteristic curve indicates that the area under the curve was 0.77 (95% CI; 0.74-0.81).

CONCLUSION

The current meta-analysis showed a moderate sensitivity and specificity of 18F FDG PET or PET/CT for the prediction of OLNM in NSCLC patients. The DOR was low and the likelihood ratio scatter-gram indicated that 18F FDG PET or PET/CT might not be useful for the prediction of OLNM in NSCLC patients and not for its exclusion.

Minor components of micropapillary and solid subtypes in lung invasive adenocarcinoma (≤ 3 cm): PET/CT findings and correlations with lymph node metastasis

OBJECTIVE

To investigate the PET/CT findings in lung invasive adenocarcinoma with minor components of micropapillary or solid contents and its association with lymph node metastasis.

MATERIALS AND METHODS

A total of 506 lung invasive adenocarcinoma (≤ 3 cm) patients who underwent a PET/CT examination and resection surgery were included. According to the proportion of solid/micropapillary components, the patients were classified into three groups: solid/micropapillary-negative (SMPN) (n = 258), solid/micropapillary-minor (SMPM; > 5% not predominant) (n = 158) and solid/micropapillary-predominant (SMPP; > 5% most dominant) (n = 90). The patients' PET/CT findings, including SUVmax, MTV, TLG and CT characteristics, and other clinical factors were compared by one-way ANOVA test. Logistic regression analysis was done to identify the most predictive findings for lymph node metastasis.

RESULTS

The value of SUVmax, MTV, TLG and tumor size was highest in SMPP group, followed by SMPM and SMPN group (P < 0.001).The areas under the curve for SUVmax, MTV and TLG for node metastasis were 0.822, 0.843 and 0.835, respectively. Univariate analysis found that the SMPP and SMPM group had more lymph node metastasis than the SMPN group (P < 0.001). Furthermore, the lymph node metastasis group had higher CEA, SUVmax, MTV, TLG, tumor size and more pleural invasion (P < 0.001). Logistic regression analysis found that SMPP pathological type, SMPM pathological type, higher CEA and male patients were risk factors for lymph node metastasis (P < 0.01).

CONCLUSIONS

Lung invasive adenocarcinoma with micropapillary or solid contents had higher SUVmax, MTV, TLG and tumor size and was associated with lymph node metastasis, even if they were not predominant.

Volume-Based Consolidation-to-Tumor Ratio Is a Useful Predictor for Postoperative Upstaging in Stage I and II Lung Adenocarcinomas

BACKGROUND

 We investigated the postoperative upstaging of stage I and II lung adenocarcinoma patients to identify useful predictors for accurate staging.

METHODS

 We retrospectively reviewed data from 80 consecutive patients undergoing lobectomy and mediastinal lymph node dissection for clinical stage I and II lung adenocarcinomas. We evaluated clinical variables, including the preoperative serum carcinoembryonic antigen (CEA), tumor diameter, consolidation-to-tumor ratio (CTR), maximum standardized uptake value (SUVmax) on FDG- PET, expression of epithelial growth factor receptor mutations, and pathological invasion to the pleura (pl), lymph duct (ly), and vein (v).

RESULTS

 Eleven patients (13.8%) showed postoperative upstaging. Three cases had pN1 migrating from cN0, four cases had pN2 from cN0, and four cases showed malignant pleural effusion. The CEA level and CTR were significantly higher in the upstaging group. The tumors in the upstaging group showed more frequent pathological invasion to the visceral pleura and vein. In patients with 3 cm or smaller consolidation, two-dimensional (2D)-CTR and volume-based CTR were independent predictors of upstaging.

CONCLUSIONS

 Volume-based CTR could be a useful predictor for accurate clinical staging in stage I and II adenocarcinoma patients in addition to consolidation size, serum CEA level, and 2D-CTR. Both volume-based and 2D-CTRs might be especially useful in T1 diseases.

Which patients benefit most from stereotactic body radiotherapy or surgery in medically operable non-small cell lung cancer? An in-depth look at patient characteristics on both sides of the debate

The role of stereotactic body radiotherapy (SBRT) in early stage medically operable non‐small cell lung cancer is currently under debate. SBRT's advantage is its ability to provide high radiotherapy doses to a tumor in a short timeframe, without the risk of postoperative complications and mortality. Currently, in part due to limited prospective data comparing both treatments, international guidelines continue to recommend surgical resection as the gold standard for medically operable patients. However, not all patients possess uniform characteristics, and there is some evidence that certain subgroups of patients would benefit more from one form of treatment ‐ SBRT or surgery ‐ than the other. The aim of this review is to provide a brief summary of the evidence comparing SBRT to surgery, followed by a deeper discussion of the subgroups of patients who would benefit most from surgery: those with large tumors, centrally located tumors, increased risk of occult nodal metastases, increased risk of toxicity from radiotherapy and radioresistant histological tumor subtypes. Meanwhile, patients who could benefit most from SBRT might include elderly patients, those with reduced lung function or cardiac comorbidities, those with synchronous lung nodules, and those with specific tumor mutational status. We hope that this review will aid in the clinical decision‐making process regarding patient selection for either treatment.

Prediction of occult lymph node metastasis using SUV, volumetric parameters and intratumoral heterogeneity of the primary tumor in T1-2N0M0 lung cancer patients staged by PET/CT

OBJECTIVE

The aim of this study was to identify whether PET/CT-related metabolic parameters of the primary tumor could predict occult lymph node metastasis (OLM) in patients with T1-2N0M0 NSCLC staged by ¹⁸F-FDG PET/CT.

METHODS

215 patients with clinical T1-2N0M0 (cT1-2N0M0) NSCLC who underwent both preoperative FDG PET/CT and surgical resection with the systematic lymph node dissection were included in the retrospective study. Heterogeneity factor (HF) was obtained by finding the derivative of the volume-threshold function from 40 to 80% of the maximum standardized uptake value (SUVmax). Univariate and multivariate stepwise logistic regression analyses were used to identify these PET parameters and clinicopathological variables associated with OLM.

RESULTS

Statistically significant differences were detected in sex, tumor site, SUVmax, mean SUV (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis and HF between patients with adenocarcinoma (ADC) and squamous cell carcinoma (SQCC). OLM was detected in 36 (16.7%) of 215 patients (ADC, 27/152 = 17.8% vs. SQCC, 9/63 = 14.3%). In multivariate analysis, MTV (OR = 1.671, P = 0.044) in ADC and HF (OR = 8.799, P = 0.023) in SQCC were potent associated factors for the prediction of OLM. The optimal cutoff values of 5.12 cm³ for MTV in ADC, and 0.198 for HF in SQCC were determined using receiver operating characteristic curve analysis.

CONCLUSIONS

In conclusion, MTV was an independent predictor of OLM in cT1-2N0M0 ADC patients, while HF might be the most powerful predictor for OLM in SQCC. These findings would be helpful in selecting patients who might be considered as candidates for sublobar resection or new stereotactic ablative radiotherapy.

MicroRNA in Lung Cancer Metastasis

Tumor metastasis is a hallmark of cancer, with distant metastasis frequently developing in lung cancer, even at initial diagnosis, resulting in poor prognosis and high mortality. However, available biomarkers cannot reliably predict cancer spreading sites. The metastatic cascade involves highly complicated processes including invasion, migration, angiogenesis, and epithelial-to-mesenchymal transition that are tightly controlled by various genetic expression modalities along with interaction between cancer cells and the extracellular matrix. In particular, microRNAs (miRNAs), a group of small non-coding RNAs, can influence the transcriptional and post-transcriptional processes, with dysregulation of miRNA expression contributing to the regulation of cancer metastasis. Nevertheless, although miRNA-targeted therapy is widely studied in vitro and in vivo, this strategy currently affords limited feasibility and a few miRNA-targeted therapies for lung cancer have entered into clinical trials to date. Advances in understanding the molecular mechanism of metastasis will thus provide additional potential targets for lung cancer treatment. This review discusses the current research related to the role of miRNAs in lung cancer invasion and metastasis, with a particular focus on the different metastatic lesions and potential miRNA-targeted treatments for lung cancer with the expectation that further exploration of miRNA-targeted therapy may establish a new spectrum of lung cancer treatments.

Intrapulmonary lymph node metastasis is common in clinically staged IA adenocarcinoma of the lung

BACKGROUND

Intrapulmonary lymph nodes (LNs, stations 11-14) are usually omitted in postoperative pathological examination. Some non-small cell lung cancer (NSCLC) patients with intrapulmonary LN metastasis are incorrectly diagnosed as N0 cases. Furthermore, underestimation of intrapulmonary LN involvement in clinically early stage NSCLC may lead to the incorrect choice of surgical procedure: lobectomy or sublobar resection. This study was conducted to determine the status of intrapulmonary LN involvement in clinically staged IA (c-T1N0M0) peripheral adenocarcinoma of the lung.

METHODS

Seventy-five lobectomy specimens of c-T1N0M0 peripheral adenocarcinoma of the lung were carefully dissected to find intrapulmonary LNs. The longest diameter of each intrapulmonary LN was measured and sent for pathological examination, together with hilar and mediastinal LNs, to investigate the relationship between LN metastasis and primary tumor size.

RESULTS

Intrapulmonary LN metastasis was detected in 22.7%(17/75) of patients. Positive LNs were detected in 21.7% (10/46) of T1b patients and 45% (11/24) of T1c patients, while no metastasis (0/5) was observed in T1a patients (P = 0.036). The mean longest diameter of the 17 involved intrapulmonary LNs was only 6.5 ± 2.1 mm, which was not significantly different to the size of negative intrapulmonary LNs (5.2 ± 1.4 mm).

CONCLUSIONS

Intrapulmonary LN metastasis is common in clinically staged IA peripheral adenocarcinoma of the lung. LN metastasis is related to tumor size, and this should be taken into account to determine appropriate surgical procedures and postoperative treatment. Computed tomography is not a reliable method to judge LN metastasis, particularly intrapulmonary LN metastasis.

Prognostic significance of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography-derived metabolic parameters in surgically resected clinical-N0 nonsmall cell lung cancer

OBJECTIVE

Our aim was to assess the significance of metabolic positron emission tomography (PET) parameters for the prediction of occult mediastinal lymph node metastasis (OLM) and recurrence in patients with clinical-N0 nonsmall cell lung cancer (NSCLC) after surgical resection and lymph node dissection.

MATERIALS AND METHODS

We evaluated 98 patients with NSCLC [52 adenocarcinoma (ADC), 46 squamous cell carcinoma (SQCC)] who had undergone initial/preoperative fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT). Eligibility criteria for participation were clinically staged as N0 and no FDG uptake in mediastinal lymph nodes on preoperative PET/CT. Clinicopathological characteristics and the diagnosis of recurrence were obtained by reviewing the hospital records. Metabolic parameters [maximum standardized uptake value, mean standardized uptake value, metabolic tumor volume (MTV), total lesion glycolysis] were determined on F-FDG PET/CT images. The association of metabolic parameters with OLM and recurrence was assessed.

RESULTS

OLM was found in 26 (26.53%) patients. T-stage, central location, and lymphovascular invasion were associated with OLM (respectively, P=0.007, 0.011, <0.001). None of the metabolic parameters was associated with OLM. Metabolic parameters of the tumor were significantly higher in patients with recurrence when the cohort was evaluated as a whole (P=0.002, 0.005, 0.016, and 0.004, respectively). In particular, there was a significant association between recurrence and tumor size, grade, stage, MTV (P<0.001), and TLG (P<0.001) in ADC. This association was not found in SQCC. Multivariate analysis showed that MTV was an independent prognostic factor for recurrence and associated with disease-free survival.

CONCLUSION

Metabolic parameters of the primary tumor on preoperative F-FDG PET/CT could not predict OLM in patients with clinical-N0 NSCLC. MTV was an independent risk factor for recurrence in ADC, but not in SQCC.

Prediction of Occult Lymph Node Metastasis Using Tumor-to-Blood Standardized Uptake Ratio and Metabolic Parameters in Clinical N0 Lung Adenocarcinoma

PURPOSE

We aimed to investigate whether the tumor-to-blood SUV ratio (SUR) and metabolic parameters of F-FDG uptake could predict occult lymph node metastasis (OLM) in clinically node-negative (cN0) lung adenocarcinoma.

MATERIALS AND METHODS

We retrospectively reviewed 157 patients with cN0 lung adenocarcinoma who underwent both preoperative F-FDG PET/CT and surgical resection with the systematic lymph node dissection. The SUVmax, SUVmean, MTV, and total lesion glycolysis (TLG) of the primary tumor was measured on the PET/CT workstation. SURmax, SURmean, and TLGsur were derived from each of them divided by descending aorta SUVmean. These PET parameters and clinicopathological variables were analyzed for OLM.

RESULTS

In our study, OLM was detected in 31 (19.7%) of 157 patients. Significantly higher values of tumor size, SUVmax, SUVmean, MTV, TLGsuv, SURmax, SURmean, and TLGsur were found in patients with OLM. In receiver operating characteristic curve analysis, the optimal cutoff values of the above parameters were 29.50, 4.38, 2.45, 6.37, 44.13, 5.30, 1.86, and 28.24, respectively. The multivariate analysis showed that TLGsur (odds ratio, 1.024; P = 0.002) was the most potent associated factor for the prediction of OLM in cN0 lung adenocarcinoma.

CONCLUSIONS

TLGsur showed the most powerful predictive performance than the other PET parameters for the prediction of OLM in cN0 lung adenocarcinoma. This normalized volumetric parameter would be helpful in selection of sublobar resection or aggressive tailored treatments in patients with cN0 lung adenocarcinoma.

Higher frequency of occult lymph node metastasis in clinical N0 pulmonary adenocarcinoma with ALK rearrangement

Objectives

There have been few studies that have fully elucidated the relationship between genomic mutations in pulmonary adenocarcinomas and occult lymph node (LN) metastases (pN1-2) despite a preoperative clinical N0 stage (cN0). It is well known that anaplastic lymphoma kinase (ALK) rearrangements are more likely to occur in younger patients with high grade tumors. The aim of this study was to investigate the genomic status, examine the clinicopathologic features, and evaluate whether ALK mutations are associated with occult LN metastases.

Materials and methods

We retrospectively evaluated 459 Japanese patients who underwent pulmonary resection of cN0 adenocarcinomas between January 2012 and December 2015. The clinicopathologic characteristics, including age, sex, smoking index, tumor maximum diameter and consolidation/tumor ratio on computed tomography (CT), maximum standardized uptake value on positron emission tomography (PET) and gene mutations (epidermal growth factor receptor [EGFR], ALK, and kirsten ras genes (KRAS), were evaluated.

Results

ALK and EGFR and KRAS mutations were all mutually exclusive. Among 324 patients found to have mutations, ALK was involved in 19 (5.9%), EGFR in 266 (82.1%), and KRAS in 39 (12.0%). The incidence of occult LN metastases did not differ significantly between those with or without mutations (p=0.27). On univariate and multivariate analyses, tumors with ALK were more likely to have occult LN metastases (p=0.03). In cN0 tumors with ALK, pN1 was diagnosed in 26.3% and pN2 in 10.5%, whereas pN1 or pN2 stage was found in <10.0% in those with EGFR or KRAS mutations or with no mutations at all. No significant difference was found in the 2-year disease-free survival among those with gene mutations (p=0.08).

Conclusion

This study highlights the frequency of PET- and CT-negative occult LN metastases in resected adenocarcinomas with ALK rearrangement. Our multivariate analysis showed that ALK rearrangements were associated with a significantly higher incidence of occult LN metastasis compared with ALK-negative adenocarcinomas.

Nomograms for predicting disease progression in patients of Stage I non-small cell lung cancer treated with stereotactic body radiotherapy

Objective

Non-local progression is a major concern in non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT). Herein we aimed to create a pre-treatment prognostic nomogram for patients with Stage I NSCLC receiving SBRT.

Methods

We retrospectively studied 182 eligible patients. Patients were randomly divided into a model (70%) group and a validation (30%) group. In the model group, thirteen parameters consisting of patient, treatment, and tumor factors were studied and multivariate Cox proportional hazards regression was performed to identify independent predictors for survival outcome, based on which we developed clinical nomogram. The nomogram was externally validated in the validation group.

Results

Multivariate analysis showed that tumor size (P = 0.011) was the only factor correlated with 2-year overall survival, whereas 2-year locoregional control (LRC) was significantly related to tumor size (P = 0.024) and the maximum standardized uptake value (SUVmax) (P = 0.044), so does 2-year progression-free survival (PFS) (tumor size: P = 0.026; SUVmax: P = 0.038). Nomogram for 2-year LRC and 2-year PFS were created based on aforementioned results. The C-indexes for the nomograms to predict 2-year LRC and PFS were 0.816 and 0.804, respectively, in model group, and were 0.729 and 0.731, respectively, in the validation group. Calibration plots also showed that the model performed well.

Conclusions

Tumor of larger size and higher SUVmax predisposed patients to early onset of locoregional and distant progression. The nomogram developed in our study would be helpful in clinical decision-making and selection of patients who may benefit from more rigorous follow-up and aggressive systemic treatment plan.

Blind spot in lung cancer lymph node metastasis: Cross-lobe peripheral lymph node metastasis in early stage patients

BACKGROUND

At present, it has not yet been determined whether metastasis can be transferred cross-lobe to peripheral lymph nodes (LNs) from other lobes in early stages of lung cancer, especially without any direct involvement to the pleura and parenchyma of the lobe. This study was conducted to investigate this issue.

METHODS

A retrospective analysis was conducted at the Chinese Academy of Medical Sciences. Patients undergoing right middle and lower lobectomy with lymphadenectomy for preoperative clinical stage Ia-IIIa from 2014 to 2015 were identified. To avoid interference, cases were limited to tumors within the primary lobe. When a tumor is completely located in the lower lobe, no direct invasion occurs into the visceral pleura/bronchus/parenchyma of the middle lobe and tumor cell metastasis into the peripheral LNs (stations 12-14) in the middle lobe is defined as cross-lobe lymph node metastasis (CLM).

RESULTS

A total of 68 patients were identified, of which nine (13.2%) had CLM. Seven had squamous cell carcinoma, one adenocarcinoma, and one small cell carcinoma. Seven cases (77.8%) had intermediate bronchus invasion, and seven cases (77.8%) intermediate bronchus adjacent lymph node involvement (station 11). Compared to non-CLM patients, tumor diameter (5.2 vs. 3.2; P = 0.28), N2 lymph node metastasis rate (66.7% vs. 28.8%; P = 0.03), late stage (IIIa 77.8% vs. 35.6%; P = 0.04), and invasion of intermediate bronchus (77.8% vs. 45.8%; P = 0.07) relatively increased.

CONCLUSION

Non-primary lobe peripheral LN metastasis exists in lung cancer and requires greater attention and further study.

Current Methods to Define Metabolic Tumor Volume in Positron Emission Tomography: Which One is Better?

Numerous methods to segment tumors using ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) have been introduced. Metabolic tumor volume (MTV) refers to the metabolically active volume of the tumor segmented using FDG PET, and has been shown to be useful in predicting patient outcome and in assessing treatment response. Also, tumor segmentation using FDG PET has useful applications in radiotherapy treatment planning. Despite extensive research on MTV showing promising results, MTV is not used in standard clinical practice yet, mainly because there is no consensus on the optimal method to segment tumors in FDG PET images. In this review, we discuss currently available methods to measure MTV using FDG PET, and assess the advantages and disadvantages of the methods.

Comparison of novel multi-level Otsu (MO-PET) and conventional PET segmentation methods for measuring FDG metabolic tumor volume in patients with soft tissue sarcoma

BACKGROUND

We have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET). The aim of this study was to evaluate the reliability of MO-PET compared to conventional PET segmentation methods for measuring 18F-FDG (FDG) PET metabolic tumor volume (MTV) in patients with soft tissue sarcoma (STS). Clinical and imaging data were obtained from the Cancer Imaging Archive. Forty-eight STS patients with FDG PET/CT and MR prior to therapy were analyzed. MTV of the tumor using MO-PET was compared to other conventional methods (absolute SUV threshold values of 2.0, 2.5, or 3.0 and percentage of tumor SUVmax values of 30, 40, 50, or 60%) and gradient-based method (PET Edge™). The reference volume was defined as an MR-based gross tumor volume (GTV). Spearman, intra-class correlation, and Bland-Altman analysis were performed to evaluate the correlation and agreement of MTV to GTV.

RESULTS

MTVs obtained using each conventional SUV parameter, PET Edge™, and MO-PET were highly correlated with the GTV in Spearman and intra-class correlation analysis (p < 0.05). MO-PET and PET Edge™ showed high intra-class correlation coefficient of MTV to GTV (0.93 and 0.84, respectively). The Bland-Altman bias results showed the highest agreement for MTV using MO-PET with GTV (26.0 ± 489.6 cm3) compared to other methods (SUV 2.0 with - 69.3 ± 765.8, 30% SUVmax with - 255.0 ± 876.6, and PET Edge™ with - 26.46 ± 668.82 cm3).

CONCLUSIONS

PET MTV segmented with MO-PET showed higher correlation and agreement with GTV in comparison to conventional percentage SUVmax and absolute SUV threshold-based PET segmentation methods. MO-PET is comparable to PET Edge™. MO-PET is a reliable and consistent method for measuring tumor MTV.

Standardized uptake value and radiological density attenuation as predictive and prognostic factors in patients with solitary pulmonary nodules: our experience on 1,592 patients

BACKGROUND

Multislice computed tomography (MSCT) increased detection of solitary pulmonary nodules (SPNs), changing the management based on radiological and clinical factors. When 18-fluorine fluorodeoxyglucose positron emission tomography combined with computed tomography (¹⁸F-FDG-PET/CT) was considered for the evaluation of nodules, the maximum standardized uptake value (SUVmax) more than 2.5 is used frequently as a cut off for malignancy. The purpose of this study is to evaluate SUVmax PET/CT and pulmonary attenuation patterns at MSCT in patients with SPN according to morphological and pathological characteristics of the lesion.

METHODS

A retrospective study on 1,592 SPN patients was carried out following approval by the Italian Registry of VATS Lobectomies.

RESULTS

All patients underwent VATS lobectomy. On histologic examination, 98.1% had primary or second metachronous primary lung cancers. In addition, 10.7% presented occult lymph node metastases (pN1 or pN2) on histological examination. Nodule attenuation on CT was associated with the histology of the lesion (p= 0.030); in particular, pure ground glass opacities (pGGOs) and partially solid nodules were related to adenocarcinomatous histotypes. Conversely, a significant relationship between SUVmax and age, nodule size, pathological node status (pN) was found (P=0.007, P=0.000 and P=0.002 respectively).

CONCLUSIONS

Nodule attenuation can predict the histology of the lesion whereas SUVmax may relate to the propensity to lymph node metastases.

A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL

RATIONALE

Estimating the probability of finding N2 or N3 (prN2/3) malignant nodal disease on endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in patients with non-small cell lung cancer (NSCLC) can facilitate the selection of subsequent management strategies.

OBJECTIVES

To develop a clinical prediction model for estimating the prN2/3.

METHODS

We used the AQuIRE (American College of Chest Physicians Quality Improvement Registry, Evaluation, and Education) registry to identify patients with NSCLC with clinical radiographic stage T1-3, N0-3, M0 disease that had EBUS-TBNA for staging. The dependent variable was the presence of N2 or N3 disease (vs. N0 or N1) as assessed by EBUS-TBNA. Univariate followed by multivariable logistic regression analysis was used to develop a parsimonious clinical prediction model to estimate prN2/3. External validation was performed using data from three other hospitals.

MEASUREMENTS AND MAIN RESULTS

The model derivation cohort (n = 633) had a 25% prevalence of malignant N2 or N3 disease. Younger age, central location, adenocarcinoma histology, and higher positron emission tomography-computed tomography N stage were associated with a higher prN2/3. Area under the receiver operating characteristic curve was 0.85 (95% confidence interval, 0.82-0.89), model fit was acceptable (Hosmer-Lemeshow, P = 0.62; Brier score, 0.125). We externally validated the model in 722 patients. Area under the receiver operating characteristic curve was 0.88 (95% confidence interval, 0.85-0.90). Calibration using the general calibration model method resulted in acceptable goodness of fit (Hosmer-Lemeshow test, P = 0.54; Brier score, 0.132).

CONCLUSIONS

Our prediction rule can be used to estimate prN2/3 in patients with NSCLC. The model has the potential to facilitate clinical decision making in the staging of NSCLC.

Impact of maximum standardized uptake value of non-small cell lung cancer on detecting lymph node involvement in potential stereotactic body radiotherapy candidates

BACKGROUND

The retrospective study investigated the association between the maximum standardized uptake value (SUV_max) of primary tumor and lymph node involvement in potential stereotactic body radiotherapy (SBRT) candidates.

METHODS

A total of 185 patients with clinical stage I NSCLC were enrolled in the current study. All patients underwent lobectomy with systematic lymph node dissection following preoperative FDG-PET/CT scanning. The association between clinicopathological variables and lymph node involvement was analyzed by univariate and multivariate analysis. Spearman's correlation test was used to evaluate the correlation between them. Receiver operating characteristic (ROC) analysis was performed to calculate the area under the curve.

RESULTS

Among these patients, 22.1% had occult lymph node involvement, 15.1% were N1 and 7.0% were N2. Greater tumor size (P=0.007), elevated CEA (P=0.006), central location (P=0.002), higher SUV_max (P<0.001), solid nodule type (P=0.002), visceral pleural invasion (P=0.001) and presence of micropapillary and solid patterns (P=0.002) were significantly associated with lymph node involvement. In multivariate analysis, lymph node involvement was associated with central location (OR 5.784, 95% CI: 1.584-21.114, P=0.008), SUV_max (increase of 1 unite, OR 1.147, 95% CI: 1.035-1.272, P=0.009) and visceral pleural invasion (OR 3.044, 95% CI: 1.369-6.769, P=0.006). ROC area under the curve of SUV_max for lymph node involvement was 0.770 (95% CI: 0.698-0.841), the sensitivity and specificity were 85.4% and 63.2%, respectively. Spearman's correlation test showed that SUV_max of tumor mostly depended on tumor size and nodule type.

CONCLUSIONS

SUV_max of primary tumor was a predictor of lymph node involvement for potential SBRT candidates. Centrally located tumor and visceral pleural invasion were related to higher rate of nodal metastasis. Lobectomy and systemic lymph node dissection should be performed in these patients, instead of SBRT.

Undetected lymph node metastases in presumed early stage NSCLC SABR patients

INTRODUCTION

Stereotactic body radiation therapy (SBRT, also called stereotactic ablative body radiation SABR) is the treatment of choice for many patients with early-stage non-small cell lung cancer (NSCLC), including those who are unfit for surgery or refuse surgery.

AREAS COVERED

In an effort to develop optimal staging for the evaluation of SBRT candidates, we review the performance of available lymph node staging methods, as well as risk factors for lymph node involvement. Pubmed was searched to identify relevant literature. Current staging methods for NSCLC, including Positron Emission Tomography/Computed Tomography(PET/CT) and endobronchial ultra sound (EBUS), have limited sensitivities. Expert commentary: There are several factors, including primary tumor location, tumor size, and histology that are possibly associated with the sensitivity of PET/CT to detect mediastinal lymph node metastasis. Small lymph node metastases typically remain undetected by PET/CT. Therefore invasive nodal staging procedures are indicated for most presumed early-stage NSCLC patients, but these also have limited sensitivity. Occult lymph node metastasis is associated with adverse outcome in NSCLC. Moreover, there is overwhelming evidence that certain patients who have lymph node metastases detected at the time of surgery derive an overall survival benefit from adjuvant therapies. It remains to be determined if improved detection of lymph node metastases in SABR candidates can indeed improve prognosis.

Expression of HIF-1α and P-gp in non-small cell lung cancer and the relationship with HPV infection

The aim of the study was to study the expression of hypoxia-inducible factor-1α (HIF-1α) and P-glycoprotein (P-gp) and analyze its correlation with human papillomavirus (HPV) infection. From January, 2012 to May, 2014, 72 cases of non-small cell lung cancer (NSCLC) pathologic tissue samples were selected from the study group. Fifty-four lung benign lesions were selected to serve as the control group. HIF-1α and P-gp expression levels were detected using immunohistochemistry. PCR was used to detect the expression of HPV genome employing specific primers for HPV 16 and 18 types. The results showed that there was 47.2 and 63.9% positive HIF-1α and P-gp expression in the study group. No P-gp or HIF-1α expression was detected in the control group. The results established a positive correlation between the expression of HIF-1α and P-gp. In the study group, the expression and differentiation degree of HIF-1α was related to lymphatic metastasis. The HIF-1α expression in the well-differentiated samples was lower than that in the moderate or poorly differentiated samples. HIF-1α expression in patients with lymphatic metastasis was higher than in patients without metastasis. The expression rate of P-gp in adenocarcinoma was higher than that in squamous carcinoma. The detection rate of HPV DNA was 45.83 and 3.70% in the study and control groups, respectively. The HPV infection and differentiation degree had relevance to lymphatic metastasis in the study group. The HPV DNA detection rate in the well-differentiated samples was lower than that in the moderate or poorly differentiated samples. The HPV DNA detection rate in patients with lymphatic metastasis was higher than that in patients with no lymphatic metastasis. There was a close link between HIF-1α, P-gp expression and NSCLC occurrence, and the development of multidrug resistance. In conclusion, the detection of HIF-1α and P-gp expression can effectively predict drug resistance during chemotherapy in NSCLC, and these proteins can be used in drug prognosis.