Identification of false-negative and false-positive diagnoses of lymph node metastases in non-small cell lung cancer patients staged by integrated (18F-)fluorodeoxyglucose-positron emission tomography/computed tomography: A retrospective cohort study

The burden of tuberculosis among patients with non-small cell lung carcinoma in a tertiary care center

BACKGROUND

Lung cancer and tuberculosis share similar risk factors, clinical spectrum, radiological features and it is difficult to differentiate but it is important to diagnose both conditions for targeted therapy and better outcome.

AIMS

Our primary objective was to estimate the proportion of TB in primary biopsy proven non-small cell lung carcinoma (NSCLC) cases.

MATERIAL & METHODS

This prospective observational study was conducted in the Departments of Medicine/Pulmonary Medicine/Medical Oncology and Microbiology at the All India Institute of Medical Sciences, New Delhi for a period of 2 years (January 2020-December 2021). Patients with biopsy proven, primary non-small cell lung cancer were recruited and sputum samples were subjected to microbiological investigations to confirm tuberculosis. Comparison was done in two groups of lung cancer patients with confirmed TB (Group A) and without confirmed tuberculosis (Group B).

RESULTS

Total 75 patients with biopsy proven, primary NSCLC were recruited and 16 % (12/75) were diagnosed with confirmed TB. Adenocarcinoma (36.48 %) and Squamous cell carcinoma (33.44 %) were the two predominant histopathological subtypes of NSCLC. About 57 (76 %) of them were found to be in stage IV of Lung cancer at initial presentation itself (75 % in group A & 74.6 % in group B; p value < 0.80). A majority of patients (11/12 cases; 91 %) of group A were males with a mean age of 59 ± 7.5 years. The upper lobes of the lung were involved in 65 % (49/75) of the cases and showing a mass lesion on imaging (75 % in group A & 65 % in group B; p value < 0.52). Kaplan Meier survival revealed a median survival time of 11 months in subjects with only NSCLC and a median survival time of 4 months in the group with concomitant TB and NSCLC (p value < 0.44).

Predictability and Utility of Contrast-Enhanced CT on Occult Lymph Node Metastasis for Patients with Clinical Stage IA-IIA Lung Adenocarcinoma: A Double-Center Study

RATIONALE AND OBJECTIVES

With the advantage of minimizing damage and preserving more functional lung tissue, limited surgery is considered depend on the lymph node (LN) involvement situation. However, occult lymph node metastasis (OLM) may be ignored by limited surgery and become a risk factor for local recurrence after surgical resection. The aim of this study was to assess the risk factors for OLM based on computed tomography enhanced image in patients with clinical lung adenocarcinoma (ADC).

MATERIALS AND METHODS

From January 2016 to July 2022, 707 patients with clinical stage IA-IIA ADC underwent lobectomy with systematic LN dissection and were divided into training and validation group based on different institution. Univariate analysis followed by multivariable logistic regression were performed to estimate different risk factors of OLM. A predictive model was established with visual nomogram and external validation, and evaluated in terms of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).

RESULTS

Fifty-nine patients were diagnosed with OLM (11.9%), and four independent predictors of LN involvement were identified: larger consolidation diameter (odds ratio [OR], 2.35, 95% confidence interval [CI]: 1.06, 5.22, p = 0.013), bronchovascular bundle thickening (OR, 1.99, 95% CI: 1.00, 3.95, p = 0.049), lobulation (OR, 2.92, 95% CI: 1.22, 6.99, p = 0.016) and obstructive change (OR, 1.69, 95% CI: 1.17, 6.16, p = 0.020). The model showed good calibration (Hosmer-Lemeshow goodness-of-fit, p = 0.816) with an AUC of 0.821 (95% CI: 0.775, 0.853). For the validation group, the AUC was 0.788 (95% CI: 0.732, 0.806).

CONCLUSION

Our predictive model can non-invasively assess the risk of OLM in patients with clinical stage IA-IIA ADC, enable surgeons perform an individualized prediction preoperatively, and assist the clinical decision-making procedure.

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.

Histology of the Primary Tumor Correlates with False Positivity of Integrated 18F-FDG-PET/CT Lymph Node Staging in Resectable Lung Cancer Patients

This study aimed to evaluate the diagnostic accuracy and false positivity rate of lymph node (LN) staging assessed by integrated 18F-fluorodeoxyglucose positron emission computed tomography (18F-FDG-PET/CT) in patients with operable lung cancer to the tumor histology. In total, 129 consecutive patients with non-small-cell lung cancer (NSCLC) undergoing anatomical lung resections were included. Preoperative LN staging was evaluated in the relationship to the histology of the resected specimens (group 1: lung adenocarcinoma/LUAD; group 2: squamous cell carcinoma/SQCA). Statistical analysis was performed by the Mann-Whitney U-test, the chi² test, and binary logistic regression analysis. To establish an easy-to-use algorithm for the identification of LN false positivity, a decision tree including clinically meaningful parameters was generated. In total, 77 (59.7%) and 52 (40.3%) patients were included in the LUAD and SQCA groups, respectively. SQCA histology, non-G1 tumors, and tumor SUVmax > 12.65 were identified as independent predictors of LN false positivity in the preoperative staging. The corresponding ORs and their 95% CIs were 3.35 [1.10-10.22], p = 0.0339; 4.60 [1.06-19.94], p = 0.0412; and 2.76 [1.01-7.55], and p = 0.0483. The preoperative identification of false-positive LNs is an important aspect of the treatment regimen for patients with operable lung cancer; thus, these preliminary findings should be further evaluated in larger patient cohorts.

18F-FDG primary tumor uptake to improve N status prediction in cT1 non-metastatic non-small cell lung cancer: development and validation of a positron emission tomography model

Purpose

Occult lymph node involvement is a major issue in the management of non-small cell lung carcinoma (NSCLC), with an estimated prevalence of approximately 2.9-21.6% in 18F-FDG PET/CT series. The aim of the study is to construct a PET model to improve lymph node assessment.

Methods

Patients with a non-metastatic cT1 NSCLC were retrospectively included from two centers, one used to constitute the training set, the other for the validation set. The best multivariate model based on Akaike's information criterion was selected, considering age, sex, visual assessment of lymph node (cN0 status), lymph node SUVmax, primary tumor location, tumor size, and tumoral SUVmax (T_SUVmax). A threshold minimizing false pN0 prediction was chosen. This model was then applied to the validation set.

Results

In total, 162 patients were included (training set: 44, validation set: 118). A model combining cN0 status and T_SUVmax was selected (AUC 0.907, specificity at threshold: 88.2%). In the validation cohort, this model resulted in an AUC of 0.832 and a specificity of 92.3% versus 65.4% for visual interpretation alone (p = 0.02). A total of two false N0 predictions were noted (1 pN1 and 1 pN2).

Conclusion

Primary tumor SUVmax improves N status prediction and could allow a better selection of patients who are candidates for minimally invasive approaches.

Preoperative Hilar and Mediastinal Lymph Node Staging in Patients with Suspected or Diagnosed Lung Cancer: Accuracy of 18F-FDG-PET/CT:A Retrospective Cohort Study of 138 Patients

The aim of this study was to evaluate the diagnostic accuracy of integrated 18F-fluorodeoxyglucose positron emission computed tomography (18F-FDG-PET/CT) in hilar and mediastinal lymph node (HMLN) staging of suspected or proven lung cancer, and to investigate potential risk factors for false negative and false positive HMLN metastases. We retrospectively analyzed 162 consecutive patients with suspected or pathologically proven non-small cell lung cancer (NSCLC). The receiver operating characteristic (ROC) curve was generated to determine the diagnostic efficacy of 18F-FDG-PET/CT. Univariate and multivariate analyses were conducted to detect risk factors of false positives and false negatives. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of integrated 18F-FDG-PET/CT in detecting HMLN metastases were 59.1% (26/44), 69.1% (65/94), 47.3% (26/55), 78.3% (65/83), and 65.9% (91/138), respectively. The ROC curve showed an area under the curve (AUC) of 0.625 (95%-CI 0.468-0.782). The incidence of false negative and false positive HMLN metastases was 21.7% (18/83) and 52.7% (29/55), respectively. Our data shows that integrated 18F-FDG-PET/CT staging provides lower specificity and sensitivity. This confirms the ESTS guideline on lymph node staging for PET-positive HMLN. Yet it advocates more invasive staging even for PET-negative HMLN.

Comparison of recurrence risk between patients with clinically node-positive and -negative stage I non-small cell lung cancer following surgery: A propensity score matching analysis

Background

Identifying patients with stage I non‐small cell lung cancer (NSCLC) at increased risk of tumor recurrence following surgery remains a major challenge. The current study aimed to compare disease‐free survival (DFS) rates after surgery between patients with clinically node‐positive (cN+) and ‐negative (cN0) stage I NSCLC.

Methods

Patients with pathological stage I resected NSCLC were identified from the lung cancer database of Changhua Christian Hospital in Taiwan. Patients with clinical N status 1 or 2 and pathological N status 0 were identified as the cN+/pN0 cohort, whereas others were identified as the cN0/pN0 cohort. Propensity score matching (PSM) was used to balance the baseline characteristics between both cohorts. Kaplan–Meier method and Cox proportional hazards model were used to evaluate DFS.

Results

From January 2010 to July 2019, 754 eligible patients were enrolled into the study, among whom 41 (5.4%) were cN+/pN0. The median follow‐up time was 43.4 months. Before PSM, the 5‐year DFS rate was 79.0% and 90.3% in cN+/pN0 and cN0/pN0 cohorts (log‐rank test, p = 0.009), respectively. After a 1:4 PSM, multivariate analysis showed that the cN+/pN0 cohort still had a poorer DFS compared to the cN0/pN0 cohort in (hazard ratio, 3.17; p = 0.040).

Conclusion

Among patients with stage I resected NSCLC, cN+ patients had a worse DFS compared to cN0 patients. Surgeons should therefore consider more aggressive adjuvant therapy or frequent follow‐up in patients with surgically resected stage I NSCLC with cN+ status.

The Differentiation of Metastatic Mediastinal Lymph Nodes From Benign Hypermetabolic Lesions

Background

Anthracosis may cause a positron emission tomography/computed tomography (PET/CT) false positivity in mediastinal and hilar lymph nodes. We aimed to evaluate the radiological features and the maximum standardized uptake values (SUVmax) of the mediastinal lymph nodes with anthracosis or squamous cell lung cancer metastasized.

Methodology

Patients diagnosed with anthracosis or squamous cell lung cancer with endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) between January 1, 2015, and November 15, 2020, in a tertiary hospital were enrolled. The squamous cell subtype of lung cancer was selected due to its association with tobacco use, biomass, and air pollution. Anthracosis may occur due to the same etiologic reasons.

Results

A total of 190 patients met the study enrollment criteria, of which 86 were diagnosed with anthracosis and 33 with squamous cell lung cancer lymph metastasis. Median values for short axis, long axis, SUVmax, shape features, and presence of calcification were found significantly different between the groups. In receiver operating characteristic (ROC) analysis, the SUVmax cut-off value was calculated as 6.61. With this cutoff value, the negative predictive value (NPV) was 92.5% and the positive predictive value (PPV) was 54% for differentiating anthracosis and malignant lymph nodes metastasis.

Conclusions

We conclude that the evaluation of the shape and metabolic activities of the anthracotic lymph nodes detected by PET/CT together with EBUS-TBNA granted a more accurate staging of the patients and more cancer patients will benefit from surgical treatment.

Patterns of nodal spread in stage III NSCLC: importance of EBUS-TBNA and 18F-FDG PET/CT for radiotherapy target volume definition

Purpose

The aim of this study was to compare the pattern of intra-patient spread of lymph-node (LN)-metastases within the mediastinum as assessed by ¹⁸F-FDG PET/CT and systematic endobronchial ultrasound-guided transbronchial-needle aspiration (EBUS-TBNA) for precise target volume definition in stage III NSCLC.

Methods

This is a single-center study based on our preceding investigation, including all consecutive patients with initial diagnosis of stage IIIA-C NSCLC, receiving concurrent radiochemotherapy (12/2011–06/2018). Inclusion criteria were curative treatment intent, ¹⁸F-FDG PET/CT and EBUS-TBNA prior to start of treatment. The lymphatic drainage was classified into echelon-1 (ipsilateral hilum), echelon-2 (ipsilateral LN-stations 4 and 7) and echelon-3 (rest of the mediastinum, contralateral hilum). The pattern of spread was classified according to all permutations of echelon-1, echelon-2, and echelon-3 EBUS-TBNA findings.

Results

In total, 180 patients were enrolled. Various patterns of LN-spread could be identified. Skip lesions with an involved echelon distal from an uninvolved one were detected in less than 10% of patients by both EBUS-TBNA and PET. The pattern with largest asymmetry was detected in cases with EBUS-TBNA- or PET-positivity at all three echelons (p < 0.0001, exact symmetry test). In a multivariable logistic model for EBUS-positivity at echelon-3, prognostic factors were PET-positivity at echelon-3 (Hazard ratio (HR) = 12.1; 95%-CI: 3.2–46.5), EBUS-TBNA positivity at echelon-2 (HR = 6.7; 95%-CI: 1.31–31.2) and left-sided tumor location (HR = 4.0; 95%-CI: 1.24–13.2). There were significantly less combined ipsilateral upper (LN-stations 2 and 4) and lower (LN-station 7) mediastinal involvements (16.8% of patients) with EBUS-TBNA than with PET (38.9%, p < 0.0001, exact symmetry test). EBUS-TBNA detected a lobe specific heterogeneity between the odds ratios of LN-positivity in the upper versus lower mediastinum (p = 0.0021, Breslow-Day test), while PET did not (p = 0.19).

Conclusion

Frequent patterns of LN-metastatic spread could be defined by EBUS-TBNA and PET and discrepancies in the pattern were seen between both methods. EBUS-TBNA showed more lobe and tumor laterality specific patterns of LN-metastases than PET and skipped lymph node stations were rare. These systematic relations offer the opportunity to further refine multi-parameter risk of LN-involvement models for target volume delineation based on pattern of spread by EBUS-TBNA and PET.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-021-01904-4.

Clinical Characteristics and Outcome of Pathologic N0 Non-small Cell Lung Cancer Patients With False Positive Mediastinal Lymph Node Metastasis on FDG PET-CT

BACKGROUND/AIM

Preoperative fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET-CT) is a non-invasive and useful diagnostic tool to evaluate mediastinal lymph node (LN) metastasis in lung cancer. However, there are often false-positive LN cases in FDG PET-CT. This study aimed to explore the clinical characteristics and outcome of pathologic N0 non-small cell lung cancer patients with false-positive mediastinal LN on FDG PET-CT.

PATIENTS AND METHODS

We enrolled 147 patients who underwent preoperative FDG PET-CT scan and mediastinal LN dissection. These patients were re-evaluated for post-operative pathologic nodal metastasis and divided into a false-positive group and a group of others.

RESULTS

Among 40 patients diagnosed with clinical N1-3 on FDG PET-CT, 19 (47.5%) patients were pathologic N0, meaning false-positive LN by PET-CT. Preoperative absolute platelet count and platelet-lymphocyte ratio were significantly higher in patients with pathologic N0. The presence of lymphatic invasion was significantly lower in patients with pathologic N0 than in the group of others. Recurrence-free survival was significantly shorter in patients with false positive LN than in patients with true positive LN or true negative LN at the same pathologic stage.

CONCLUSION

Higher absolute platelet count and PLR, lower proportion of lymphatic invasion and shorter recurrence-free survival were associated with false positive mediastinal LN on preoperative FDG PET-CT.

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.

Impact of EBUS-TBNA in addition to [18F]FDG-PET/CT imaging on target volume definition for radiochemotherapy in stage III NSCLC

Purpose/introduction

[¹⁸F]FDG-PET/CT is the standard imaging-technique for radiation treatment (RT) planning in locally advanced non-small cell lung cancer (NSCLC). The purpose of this study was to examine the additional value of endobronchial-ultrasound transbronchial needle aspiration (EBUS-TBNA) to standard PET/CT for mediastinal lymph-node (LN) staging and its impact on clinical target volume (CTV).

Materials and methods

All consecutive patients with primary stage III NSCLC who underwent [¹⁸F]FDG-PET/CT and EBUS-TBNA prior to RT were analyzed from 12/2011 to 06/2018. LN-stations were assessed by an expert-radiologist and a nuclear medicine-physician. CTV was evaluated by two independent radiation oncologists. LNs were grouped with increasing distance along the lymphatic chains from primary tumor into echelon-1 (ipsilateral hilum), echelon-2 (LN-station 7 and ipsilateral 4), and echelon-3 (remaining mediastinum and contralateral hilum).

Results

A total of 675 LN-stations of which 291 were positive for tumor-cells, were sampled by EBUS-TBNA in 180 patients. The rate of EBUS-positive LNs was 43% among all sampled LNs. EBUS-positivity in EBUS-probed LNs decreased from 85.8% in echelon-1 LNs to 42.4%/ 9.6% in echelon-2/ -3 LNs, respectively (p < 0.0001, Fisher’s exact test). The false discovery rate of PET in comparison with EBUS results rose from 5.3% in echelon-1 to 32.9%/ 69.1% in echelon-2/ -3 LNs, respectively (p < 0.0001, Fisher’s exact test). Sensitivity and specificity of FDG-PET/CT ranged from 85 to 99% and 67 to 80% for the different echelons. In 22.2% patients, EBUS-TBNA finding triggered changes of the treated CTV, compared with contouring algorithms based on FDG-avidity as the sole criterion for inclusion. CTV was enlarged in 6.7% patients due to EBUS-positivity in PET-negative LN-station and reduced in 15.5% by exclusion of an EBUS-negative but PET-positive LN-station.

Conclusion

The false discovery rate of [¹⁸F]FDG-PET/CT increased markedly with distance from the primary tumor. Inclusion of systematic mediastinal LN mapping by EBUS-TBNA in addition to PET/CT has the potential to increase accuracy of target volume definition, particularly in echelon-3 LNs. EBUS-TBNA is recommended as integral part of staging for radiochemotherapy in stage III NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05204-7.

Machine learning-based diagnostic method of pre-therapeutic 18F-FDG PET/CT for evaluating mediastinal lymph nodes in non-small cell lung cancer

OBJECTIVES

We aimed to find the best machine learning (ML) model using ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for evaluating metastatic mediastinal lymph nodes (MedLNs) in non-small cell lung cancer, and compare the diagnostic results with those of nuclear medicine physicians.

METHODS

A total of 1329 MedLNs were reviewed. Boosted decision tree, logistic regression, support vector machine, neural network, and decision forest models were compared. The diagnostic performance of the best ML model was compared with that of physicians. The ML method was divided into ML with quantitative variables only (MLq) and adding clinical information (MLc). We performed an analysis based on the ¹⁸F-FDG-avidity of the MedLNs.

RESULTS

The boosted decision tree model obtained higher sensitivity and negative predictive values but lower specificity and positive predictive values than the physicians. There was no significant difference between the accuracy of the physicians and MLq (79.8% vs. 76.8%, p = 0.067). The accuracy of MLc was significantly higher than that of the physicians (81.0% vs. 76.8%, p = 0.009). In MedLNs with low ¹⁸F-FDG-avidity, ML had significantly higher accuracy than the physicians (70.0% vs. 63.3%, p = 0.018).

CONCLUSION

Although there was no significant difference in accuracy between the MLq and physicians, the diagnostic performance of MLc was better than that of MLq or of the physicians. The ML method appeared to be useful for evaluating low metabolic MedLNs. Therefore, adding clinical information to the quantitative variables from ¹⁸F-FDG PET/CT can improve the diagnostic results of ML.

KEY POINTS

• Machine learning using two-class boosted decision tree model revealed the highest value of area under curve, and it showed higher sensitivity and negative predictive values but lower specificity and positive predictive values than nuclear medicine physicians. • The diagnostic results from machine learning method after adding clinical information to the quantitative variables improved accuracy significantly than nuclear medicine physicians. • Machine learning could improve the diagnostic significance of metastatic mediastinal lymph nodes, especially in mediastinal lymph nodes with low 18F-FDG-avidity.

Morbidity, mortality and long-term outcome of lung cancer resections performed in palliative intent

Background

Surgery is seldom used for palliation in advanced lung cancer and the published data on this issue are very limited. We aimed to assess the results of palliative lung resections and identify criteria to guide surgical therapy in this situation.

Methods

This is a retrospective single-institution analysis of patients with palliative intended lung cancer resection. Survival analysis was performed by Kaplan-Meier method, log-rank test and Cox proportional hazards regression at a statistical significance level of P=0.05.

Results

Forty-eight patients received palliative intended lung resections (31 lobectomies, 4 bilobectomies, 13 pneumonectomies) with acceptable rates of severe complications (Clavien-Dindo >IIIa 29%) and 30-day mortality (4%). The most frequent indications were infection and hemoptysis. The median survival for the entire group was 12 months (95% CI: 6.9-17.1 months). Due to unexpectedly favorable histopathologic tumor stage, a switch to curative treatment in 17 completely resected patients resulted in a 2-year survival rate of 46%. In a subgroup of 20 patients with favorable prognostic factors as identified by uni- and multivariable analysis, a median survival of 26 months was observed.

Conclusions

In well selected patients with lung cancer, resection in palliative intent can offer symptom relief and even a survival benefit with acceptable morbidity and low mortality. Prognostic factors were identified and can be used to guide operative treatment. Due to the low specificity of CT and FDG-PET/CT in the presence of inflammation or centrally located lung tumors, a large proportion of patients with lung resection in palliative intent experience a down-staging and frequently also a switch from palliative to curative treatment with additional survival benefit. Factors like expected complete resection, a squamous cell type and the ability to receive adjuvant therapy are useful to support the decision to perform palliative tumor resection.

Comparison of prognostic values of primary tumor and nodal 18F-fluorodeoxyglucose uptake in non-small cell lung cancer with N1 disease

INTRODUCTION

We hypothesized that, in non-small cell lung cancer (NSCLC) with N1 metastasis, N1 nodal ¹⁸F-fluorodeoxyglucose (FDG) status offers independent and incremental prognostic value.

METHODS

We enrolled 106 NSCLC patients with pathology-confirmed N1 metastasis. N1 node FDG positivity, primary tumor maximum standard uptake value (SUV_max), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured. Kaplan-Meier method and Cox regression analyses were performed for cancer-specific survival (CSS) and disease-free survival (DFS).

RESULTS

Subjects were 67 males and 39 females (61.9 ± 9.4 years). Eighty-one (76.4%) and 25 (23.6%) had pathologic stage IIB and IIIA NSCLC, respectively. All underwent complete tumor resection. FDG-positive N1 nodes were larger and had higher primary tumor SUV_max. During a follow-up of 42 months, there were 56 recurrences and 31 cancer deaths. Significant univariate predictors were stage, no adjuvant therapy, and FDG-positive nodes for DFS, and stage, no adjuvant therapy, node size, tumor MTV, TLG, and SUV_max, and FDG-positive nodes for CSS. Independent predictors on multivariate analyses were FDG-positive nodes (HR = 3.071, p = 0.003), greater tumor TLG (HR = 3.224, p = 0.002), and no adjuvant therapy (HR = 3.631, p < 0.001) for poor CSS, and FDG-positive nodes (HR = 1.771, p = 0.040) and no adjuvant therapy (HR = 2.666, p = 0.002) for poor DFS. Harrell's concordance and net reclassification improvement tests showed that CSS prediction was significantly improved by the addition of N1 FDG status to a model containing tumor TLG.

CONCLUSION

N1 node FDG status can be useful for predicting the outcome of NSCLC patients with N1 metastasis beyond that provided by other prognostic variables.

KEY POINTS

• In NSCLC with N1 disease, N1 node FDG status is useful as a prognostic predictor. • FDG-positive N1 nodes provide additional prognostic value beyond TLG of primary tumor. • Combining TLG of primary tumor and N1 node uptake can stratify the survival of patients.

Excellence in non-small cell lung cancer staging by endobronchial-TBNA: Comparison with PET-CT and surgery

Objective: To determine the correlation and/or discrepancies between positron emission tomography (PET-CT) findings, endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and surgery in the staging of non-small cell lung carcinoma. Material and methods: Data were evaluated retrospectively from a prospective interventional endoscopy database. Positive results with EBUS-TBNA was the first end point and all cytology negatives were confirmed with mediastinoscopy/surgery. Results: Four hundred and eighty three patients were included and 1017 lymph nodes (LNs) were sampled in the study. One hundred and twenty eight LNs were excluded (positive with EBUS-TBNA). Four hundred and sixty five LN (52.3%) were found benign with EBUS-TBNA; however, only 15 of these were confirmed to be malignant by surgery (1.7%). The sensitivity, specificity, PPV, NPV and diagnostic accuracy of EBUS-TBNA were 96.5, 100, 100, 96.7 and 98.3%, respectively. The sensitivity, specificity, PPV, NPV and diagnostic accuracy of PET-CT for maximum standardized uptake value (SUVmax) 2.5 were 90.1, 29.2, 55.3, 75.4, 59.2%, respectively. A cut-off SUVmax of 5.2 was detected with 74.8% sensitivity, 84% specificity, 82.0% PPV, 77.5% NPV and 79.5% accuracy (area under the curve (AUC) of 0.818, 95% CI 0.791-0.843, p<.001). Conclusion: EBUS is a reliable, repeatable and safe technique with a high diagnostic accuracy and should be performed quickly to avoid superfluous time loss in the staging of lung cancer. Abbreviations PET-CT F-18 fluorodeoxyglucose positron emission computed tomography NSCLC Non-small cell lung cancer EBUS-TBNA Endobronchial ultrasound-guided transbronchial needle aspiration SUVmax Maximum standardized uptake value LNs Lymph nodes TTF-1 Thyroid transcription factor-1 H&E Hematoxylin and eosin; Med: Mediastinoscopy VATS Video associated thoracic surgery AUC Area under curve OR Odds ratio CI Confidence intervals.

Contrast-enhanced magnetic resonance imaging with a novel nano-size contrast agent for the clinical diagnosis of patients with lung cancer

Recent studies have indicated that magnetic resonance imaging (MRI) efficiently diagnoses lung cancer. However, the efficacy of MRI in diagnosing lung cancer requires improving for patients in the early stage of the disease. In the present study, a novel nano-sized contrast agent of chistosan/Fe₃O₄-enclosed bispecific antibodies (BsAbCENS) was introduced, which targeted carcino-embryonic antigen (CEA) and neuron-specific enolase (NSE) in lung cancer cells. The diagnostic efficacy of contrast-enhanced MRI with BsAbCENS (CEMRI-BsAbCENS) was investigated in a total of 182 patients with suspected lung cancer who had high serum levels of CEA and NSE. BsAbCENS was administered by pulmonary inhalation prior to the MRI scan. The results revealed that CEA and NSE were overexpressed in human lung cancer cell lines. BsAbCENS bound with CEA and NSE on the surface of human lung cancer cells and produced a higher signal intensity than MRI alone for the diagnosis of patients with lung cancer. The diagnostic data revealed that CEMRI-BsAbCENS diagnosed 124/182 lung cancer cases, whereas CEMRI only diagnosed 98/182, which was significantly less (P<0.01). In addition, the survival rate of patients with lung cancer diagnosed by CEMRI-BsAbCENS was significantly higher than the mean 5-year survival rate (P<0.01). Furthermore, the pharmacodynamics demonstrated that BsAbCENS was metabolized within 24 h. The results of the present study indicate that the efficacy and accuracy of lung cancer diagnosis are improved by CEMRI-BsAbCENS. In conclusion, these results provide a potential novel protocol for the diagnosis of tumors in patients with suspected early stage lung cancer.

Radiomics Approach to Prediction of Occult Mediastinal Lymph Node Metastasis of Lung Adenocarcinoma

OBJECTIVE

The purpose of this study was to evaluate the prognostic impact of radiomic features from CT scans in predicting occult mediastinal lymph node (LN) metastasis of lung adenocarcinoma.

MATERIALS AND METHODS

A total of 492 patients with lung adenocarcinoma who underwent preoperative unenhanced chest CT were enrolled in the study. A total of 300 radiomics features quantifying tumor intensity, texture, and wavelet were extracted from the segmented entire-tumor volume of interest of the primary tumor. A radiomics signature was generated by use of the relief-based feature method and the support vector machine classification method. A ROC regression curve was drawn for the predictive performance of radiomics features. Multivariate logistic regression models based on clinicopathologic and radiomics features were compared for discriminating mediastinal LN metastasis.

RESULTS

Clinical variables (sex, tumor diameter, tumor location) and predominant subtype were risk factors for pathologic mediastinal LN metastasis. The accuracy of radiomics signature for predicting mediastinal LN metastasis was 91.1% in ROC analysis (AUC, 0.972; sensitivity, 94.8%; specificity, 92%). Radiomics signature (Akaike information criterion [AIC] value, 80.9%) showed model fit superior to that of the clinicohistopathologic model (AIC value, 61.1%) for predicting mediastinal LN metastasis.

CONCLUSION

The radiomics signature of a primary tumor based on CT scans can be used for quantitative and noninvasive prediction of occult mediastinal LN metastasis of lung adenocarcinoma.

Current role of standardized uptake valuemax-derived ratios in N2 fluorine-18 fluorodeoxyglucose positron-emission tomography non-small cell lung cancer

Mediastinal staging is a crucial moment in management of non-small cell lung cancer (NSCLC) patients. In integrated pathways, 18-fluorine fluorodeoxyglucose positron-emission tomography (¹⁸F-FDG-PET/CT) is an indispensable imaging resource with its peculiarities and its limitations. A critical review of work up protocols would certainly help to standardize procedures with important reflections also on the diagnostic value of this examination. In this regard, new semi-quantitative and semi-qualitative indexes have been proposed with the aim of increasing the accuracy of ¹⁸F-FDG-PET/CT in mediastinal lymph node staging. These latter, such as SUV_n/t and SUV indexes, seem to overcome the problem of spatial resolution and discrimination of malignancy by endorsing a new predictive and prognostic role.

Texture Analysis and Synthesis of Malignant and Benign Mediastinal Lymph Nodes in Patients with Lung Cancer on Computed Tomography

Texture analysis of computed tomography (CT) imaging has been found useful to distinguish subtle differences, which are in- visible to human eyes, between malignant and benign tissues in cancer patients. This study implemented two complementary methods of texture analysis, known as the gray-level co-occurrence matrix (GLCM) and the experimental semivariogram (SV) with an aim to improve the predictive value of evaluating mediastinal lymph nodes in lung cancer. The GLCM was explored with the use of a rich set of its derived features, whereas the SV feature was extracted on real and synthesized CT samples of benign and malignant lymph nodes. A distinct advantage of the computer methodology presented herein is the alleviation of the need for an automated precise segmentation of the lymph nodes. Using the logistic regression model, a sensitivity of 75%, specificity of 90%, and area under curve of 0.89 were obtained in the test population. A tenfold cross-validation of 70% accuracy of classifying between benign and malignant lymph nodes was obtained using the support vector machines as a pattern classifier. These results are higher than those recently reported in literature with similar studies.

Molecular Imaging and Precision Medicine in Lung Cancer

Precision medicine allows tailoring of preventive or therapeutic interventions to avoid the expense and toxicity of futile treatment given to those who will not respond. Lung cancer is a heterogeneous disease functionally and morphologically. PET is a sensitive molecular imaging technique with a major role in the precision medicine algorithm of patients with lung cancer. It contributes to the precision medicine of lung neoplasia by interrogating tumor heterogeneity throughout the body. It provides anatomofunctional insight during diagnosis, staging, and restaging of the disease. It is a biomarker of tumoral heterogeneity that helps direct selection of the most appropriate treatment, the prediction of early response to cytotoxic and cytostatic therapies, and is a prognostic biomarker in patients with lung cancer.