Large cell neuroendocrine carcinoma of the lung: CT and FDG PET findings

2021 WHO Classification of Lung Cancer: Molecular Biology Research and Radiologic-Pathologic Correlation

The 2021 World Health Organization (WHO) classification system for thoracic tumors (including lung cancer) contains several updates to the 2015 edition. Revisions for lung cancer include a new grading system for invasive nonmucinous adenocarcinoma that better reflects prognosis, reorganization of squamous cell carcinomas and neuroendocrine neoplasms, and description of some new entities. Moreover, remarkable advancements in our knowledge of genetic mutations and targeted therapies have led to a much greater emphasis on genetic testing than that in 2015. In 2015, guidelines recommended evaluation of only two driver mutations, ie, epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) fusions, in patients with nonsquamous non-small cell lung cancer. The 2021 guidelines recommend testing for numerous additional gene mutations for which targeted therapies are now available including ROS1, RET, NTRK1-3, KRAS, BRAF, and MET. The correlation of imaging features and genetic mutations is being studied. Testing for the immune biomarker programmed death ligand 1 is now recommended before starting first-line therapy in patients with metastatic non-small cell lung cancer. Because 70% of lung cancers are unresectable at patient presentation, diagnosis of lung cancer is usually based on small diagnostic samples (ie, biopsy specimens) rather than surgical resection specimens. The 2021 version emphasizes differences in the histopathologic interpretation of small diagnostic samples and resection specimens. Radiologists play a key role not only in evaluation of tumor and metastatic disease but also in identification of optimal biopsy targets. ©RSNA, 2024 Test Your Knowledge questions in the supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.

New horizon of radiopharmaceuticals in management of neuroendocrine tumors

Neuroendocrine neoplasms are rare and heterogenous group of tumors with varying degrees of clinical presentations and involvement of multiple organ systems in the body. In the modern clinical practice somatostatin receptor molecular imaging and targeted radioligand therapy plays a vital role in the diagnosis and management of the disease. Several new and promising radiotracers for NET imaging and theranostics, belonging to various groups and classes are being studied and investigated. This exponential growth of radiotracers poses concerns about the indication, clinical benefit, and safety profile of the agents. We discuss the basis behind these radiotracers clinical use, receptor targeting and intra and inter tumor heterogeneity. Furthermore, role of dual tracer imaging, combination therapy and potential applications of dosimetry in predicting treatment outcome and safety profile is reviewed. Individualized precision medicine with better tumor characterization, maximum therapeutic benefit and minimum toxicity is the way forward for future medicine.

Prognostic Factors across Poorly Differentiated Neuroendocrine Neoplasms: A Pooled Analysis

INTRODUCTION

Poorly differentiated neuroendocrine carcinomas (NECs) are characterized by aggressive clinical course and poor prognosis. No reliable prognostic markers have been validated to date; thus, the definition of a specific NEC prognostic algorithm represents a clinical need. This study aimed to analyze a large NEC case series to validate the specific prognostic factors identified in previous studies on gastro-entero-pancreatic and lung NECs and to assess if further prognostic parameters can be isolated.

METHODS

A pooled analysis of four NEC retrospective studies was performed to evaluate the prognostic role of Ki-67 cut-off, the overall survival (OS) according to primary cancer site, and further prognostic parameters using multivariable Cox proportional hazards model and machine learning random survival forest (RSF).

RESULTS

422 NECs were analyzed. The most represented tumor site was the colorectum (n = 156, 37%), followed by the lungs (n = 111, 26%), gastroesophageal site (n = 83, 20%; 66 gastric, 79%) and pancreas (n = 42, 10%). The Ki-67 index was the most relevant predictor, followed by morphology (pure or mixed/combined NECs), stage, and site. The predicted RSF response for survival at 1, 2, or 3 years showed decreasing survival with increasing Ki-67, pure NEC morphology, stage III-IV, and colorectal NEC disease. Patients with Ki-67 <55% and mixed/combined morphology had better survival than those with pure morphology. Morphology pure or mixed/combined became irrelevant in NEC survival when Ki-67 was ≥55%. The prognosis of metastatic patients who did not receive any treatment tended to be worse compared to that of the treated group. The prognostic impact of Rb1 immunolabeling appears to be limited when multiple risk factors are simultaneously assessed.

CONCLUSION

The most effective parameters to predict OS for NEC patients could be Ki-67, pure or mixed/combined morphology, stage, and site.

Pulmonary Combined Large Cell Neuroendocrine Carcinoma

Pulmonary combined large-cell neuroendocrine carcinoma (CLCNEC) is a rare neuroendocrine tumor pertained to lung large cell neuroendocrine carcinoma (LCNEC) with aggressive behavior and poor prognosis generally. The clinical features of CLCNEC are not specific including cough, expectoration, chest distress, chest pain, etc., which are prone to have different manifestations of the mixed components. Owing to the low incidence, there are few related small-scale retrospective studies and case reports. Currently, the treatment regimen of CLCNEC mainly refers to LCNEC that complete surgical resection is preferred in the early stage and according to previous researches, platinum-based small cell lung cancer (SCLC) standard treatment regimen showed promising results in postoperative and advanced CLCNEC as compared to that of non-small cell lung cancer (NSCLC). Adenocarcinoma-CLCNEC more likely harbor driver gene mutation, and may benefit from targeted therapy. As for immunotherapy, more clinical trial data are needed to support its benefits. This article will fill the gap and will provide new insight into the clinical characteristics, pathological diagnosis and treatment endeavors of CLCNEC.

Pulmonary Large Cell Neuroendocrine Carcinoma

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare subtype of malignant pulmonary tumor. The incidence rate of LCNEC was reported to be 0.3%–3% in lung cancers. Although LCNEC is classified as non-small cell lung cancer (NSCLC), it is more aggressive and malignant than other NSCLC, and its biological behavior is similar to that of small cell lung cancer (SCLC). Most of the LCNEC patients are elderly smoking male and the clinical manifestations are not specific. The imaging manifestations of the tumors are often located in the periphery and the upper lobes, and the enlargement of mediastinal or hilar lymph nodes is common. The diagnosis is mainly based on pathology by the histological features and immunohistochemistry (IHC). Specific neuroendocrine markers such as chromogranin A (CgA), synaptophysin (Syn) and CD56 are usually diffusely positive in LCNEC, and found that insulinoma-associated protein (INSM1) and high rate of Ki-67 are helpful for diagnosis. More differential diagnoses also increase the difficulty of correctly diagnosing LCNEC. The rise of LCNEC molecular typing in recent years may be helpful for diagnosis and subsequent treatment. This review focuses on the epidemiological features, imaging studies, pathology, diagnosis, treatment, and prognosis of LCNEC.

Large Cell Neuroendocrine Carcinoma of the Lung: Current Understanding and Challenges

Large cell neuroendocrine carcinoma of the lung (LCNEC) is a rare and highly aggressive type of lung cancer, with a complex biology that shares similarities with both small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). The prognosis of LCNEC is poor, with a median overall survival of 8-12 months. The diagnosis of LCNEC requires the identification of neuroendocrine morphology and the expression of at least one of the neuroendocrine markers (chromogranin A, synaptophysin or CD56). In the last few years, the introduction of next-generation sequencing allowed the identification of molecular subtypes of LCNEC, with prognostic and potential therapeutic implications: one subtype is similar to SCLC (SCLC-like), while the other is similar to NSCLC (NSCLC-like). Because of LCNEC rarity, most evidence comes from small retrospective studies and treatment strategies that are extrapolated from those adopted in patients with SCLC and NSCLC. Nevertheless, limited but promising data about targeted therapies and immune checkpoint inhibitors in patients with LCNEC are emerging. LCNEC clinical management is still controversial and standardized treatment strategies are currently lacking. The aim of this manuscript is to review clinical and molecular data about LCNEC to better understand the optimal management and the potential prognostic and therapeutic implications of molecular subtypes.

Pulmonary large cell carcinoma with neuroendocrine morphology shows genetic similarity to large cell neuroendocrine carcinoma

Background

Large cell neuroendocrine carcinoma (LCNEC) is a high-grade malignant pulmonary neuroendocrine tumour. The distinction of pulmonary large cell carcinoma (LCC) and LCNEC is based on the presence of neuroendocrine morphology and the expression of at least one neuroendocrine marker in at least 10% of tumour cells in the latter. According to the current classification, LCC with neuroendocrine morphology and without neuroendocrine marker expression is classified as LCC. This subgroup we have named LCNEC-null and aimed to analyze its characteristics.

Methods

31 surgical samples resected in West China Hospital of Sichuan University between 2017 to 2021 were collected, including 7 traditional LCCs, 11 LCNEC-nulls and 13 LCNECs. Each case was conducted to immunohistochemistry and 425-panel-NGS.

Results

Compared to other LCCs, detailed analysis of LCNEC-nulls revealed biological features similar to those of LCNECs, especially for immunohistochemistry and molecular analysis: 1. diffusive, coarse granular and high expression of Pan-CK; 2. rare PD-L1 expression; 3. High rate of p53 expression and Rb deficiency 4. abundant genetic alterations are similar to LCNEC. All characteristics above deviated from traditional LCC, indicating they have the same origin as LCNEC. Furthermore, LCNEC could be genetically divided into two subtypes when we reclassified LCNEC-null as LCNEC, and the mutational type and prognosis differed significantly.

Conclusions

We consider that LCNEC-null should be reclassified as LCNEC based on analysis above. In addition, two genetic types of LCNEC with different prognosis also indicate two mechanism of tumour formation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13000-022-01204-9.

Prognostic Value of 18F-FDG PET in Neuroendocrine Neoplasm: A Systematic Review and Meta-analysis

OBJECTIVES

Accurate assessment of the prognosis is critical for the rational treatment of neuroendocrine neoplasms (NENs). We performed a systematic review and meta-analysis of the prognostic value of 18F-FDG PET for NENs.

PATIENTS AND METHODS

PubMed and Embase databases were searched up to September 2020 for studies that evaluated 18F-FDG PET as prognostic factors in patients with NENs with overall survival (OS) and event-free survival (EFS) as outcomes. Hazards ratios (HRs) comparing high and low FDG uptakes were pooled using the DerSimonian-Laird method. Publication bias was assessed and adjusted for using the trim-and-fill method. Metaregression and subgroup analyses were performed to explore the cause of heterogeneity.

RESULTS

Twenty-three studies (1799 patients) were included. The overall pooled HRs of high FDG uptake on EFS and OS were 2.84 (95% confidence interval [CI], 2.21-3.64) and 3.50 (95% CI, 2.42-4.12), respectively. Publication biases were present regarding both EFS and OS (P = 0.0342 and 0.0009, respectively). After adjustment, effect sizes remained significant for EFS and OS (adjusted HR, 2.26 [95% CI, 1.76-2.89]; 3.16 [95% CI, 2.42-4.12]). In metaregression analyses, the proportion of grade 3 tumors positively correlated with the HR of OS (adjusted P = 0.0422).

CONCLUSIONS

18F-FDG PET is a significant prognostic factor in patients with NENs. 18F-FDG PET might be a useful prognostic biomarker in conjunction with the histologic grade and can help select the optimal treatment.

N-staging in large cell neuroendocrine carcinoma of the lung: diagnostic value of [18F]FDG PET/CT compared to the histopathology reference standard

Background

Large cell neuroendocrine carcinoma of the lung (LCNEC) is a rare entity occurring in less than 4% of all lung cancers. Due to its low differentiation and high glucose transporter 1 (GLUT1) expression, LCNEC demonstrates an increased glucose turnover. Thus, PET/CT with 2-[¹⁸F]-fluoro-deoxyglucose ([¹⁸F]FDG) is suitable for LCNEC staging. Surgery with curative intent is the treatment of choice in early stage LCNEC. Prerequisite for this is correct lymph node staging. This study aimed at evaluating the diagnostic performance of [¹⁸F]FDG PET/CT validated by histopathology following surgical resection or mediastinoscopy. N-staging interrater-reliability was assessed to test for robustness of the [¹⁸F]FDG PET/CT findings.

Methods

Between 03/2014 and 12/2020, 46 patients with LCNEC were included in this single center retrospective analysis. All underwent [¹⁸F]FDG PET/CT for pre-operative staging and subsequently either surgery (n = 38) or mediastinoscopy (n = 8). Regarding the lymph node involvement, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) were calculated for [¹⁸F]FDG PET/CT using the final histopathological N-staging (pN0 to pN3) as reference.

Results

Per patient 14 ± 7 (range 4–32) lymph nodes were resected and histologically processed. 31/46 patients had no LCNEC spread into the lymph nodes. In 8/46 patients, the final stage was pN1, in 5/46 pN2 and in 2/46 pN3. [¹⁸F]FDG PET/CT diagnosed lymph node metastasis of LCNEC with a sensitivity of 93%, a specificity of 87%, an accuracy of 89%, a PPV of 78% and a NPV of 96%. In the four false positive cases, the [¹⁸F]FDG uptake of the lymph nodes was 33 to 67% less in comparison with that of the respective LCNEC primary. Interrater-reliability was high with a strong level of agreement (κ = 0.82).

Conclusions

In LCNEC N-staging with [¹⁸F]FDG PET/CT demonstrates both high sensitivity and specificity, an excellent NPV but a slightly reduced PPV. Accordingly, preoperative invasive mediastinal staging may be omitted in cases with cN0 disease by [¹⁸F]FDG PET/CT. In [¹⁸F]FDG PET/CT cN1-cN3 stages histological confirmation is warranted, particularly in case of only moderate [¹⁸F]FDG uptake as compared to the LCNEC primary.

Diagnostic Value of Conventional PET Parameters and Radiomic Features Extracted from 18F-FDG-PET/CT for Histologic Subtype Classification and Characterization of Lung Neuroendocrine Neoplasms

Aim: To evaluate if conventional Positron emission tomography (PET) parameters and radiomic features (RFs) extracted by 18F-FDG-PET/CT can differentiate among different histological subtypes of lung neuroendocrine neoplasms (Lu-NENs). Methods: Forty-four naïve-treatment patients on whom 18F-FDG-PET/CT was performed for histologically confirmed Lu-NEN (n = 46) were retrospectively included. Manual segmentation was performed by two operators allowing for extraction of four conventional PET parameters (SUVmax, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG)) and 41 RFs. Lu-NENs were classified into two groups: lung neuroendocrine tumors (Lu-NETs) vs. lung neuroendocrine carcinomas (Lu-NECs). Lu-NETs were classified according to histological subtypes (typical (TC)/atypical carcinoid (AC)), Ki67-level, and TNM staging. The least absolute shrink age and selection operator (LASSO) method was used to select the most predictive RFs for classification and Pearson correlation analysis was performed between conventional PET parameters and selected RFs. Results: PET parameters, in particular, SUVmax (area under the curve (AUC) = 0.91; cut-off = 5.16) were higher in Lu-NECs vs. Lu-NETs (p < 0.001). Among RFs, HISTO_Entropy_log10 was the most predictive (AUC = 0.90), but correlated with SUVmax/SUVmean (r = 0.95/r = 0.94, respectively). No statistical differences were found between conventional PET parameters and RFs (p > 0.05) and TC vs. AC classification. Conventional PET parameters were correlated with N+ status in Lu-NETs. Conclusion: In our study, conventional PET parameters were able to distinguish Lu-NECs from Lu-NETs, but not TC from AC. RFs did not provide additional information.

Exploring imaging features of molecular subtypes of large cell neuroendocrine carcinoma (LCNEC)

OBJECTIVES

Radiological characteristics and radiomics signatures can aid in differentiation between small cell lung carcinoma (SCLC) and non-small cell lung carcinoma (NSCLC). We investigated whether molecular subtypes of large cell neuroendocrine carcinoma (LCNEC), i.e. SCLC-like (with pRb loss) vs. NSCLC-like (with pRb expression), can be distinguished by imaging based on (1) imaging interpretation, (2) semantic features, and/or (3) a radiomics signature, designed to differentiate between SCLC and NSCLC.

MATERIALS AND METHODS

Pulmonary oncologists and chest radiologists assessed chest CT-scans of 44 LCNEC patients for 'small cell-like' or 'non-small cell-like' appearance. The radiologists also scored semantic features of 50 LCNEC scans. Finally, a radiomics signature was trained on a dataset containing 48 SCLC and 76 NSCLC scans and validated on an external set of 58 SCLC and 40 NSCLC scans. This signature was applied on scans of 28 SCLC-like and 8 NSCLC-like LCNEC patients.

RESULTS

Pulmonary oncologists and radiologists were unable to differentiate between molecular subtypes of LCNEC and no significant differences in semantic features were found. The area under the receiver operating characteristics curve of the radiomics signature in the validation set (SCLC vs. NSCLC) was 0.84 (95% confidence interval (CI) 0.77-0.92) and 0.58 (95% CI 0.29-0.86) in the LCNEC dataset (SCLC-like vs. NSCLC-like).

CONCLUSION

LCNEC appears to have radiological characteristics of both SCLC and NSCLC, irrespective of pRb loss, compatible with the SCLC-like subtype. Imaging interpretation, semantic features and our radiomics signature designed to differentiate between SCLC and NSCLC were unable to separate molecular LCNEC subtypes, which underscores that LCNEC is a unique disease.

Thymic large cell neuroendocrine carcinoma - a rare and aggressive tumor: a case report

BACKGROUND

Neuroendocrine tumors are a large group of tumors with a wide spectrum of behavior, affecting mainly the digestive system and the lung. The thymus is very rarely affected.

CASE PRESENTATION

A 28-year-old Arab woman presented with chronic chest pain and dyspnea. A computed tomography scan showed a huge anterior mediastinal mass invading neighboring structures. A mediastinotomy was performed with biopsies of the mass. Pathological findings were consistent with a thymic large cell neuroendocrine carcinoma.

CONCLUSIONS

The occurrence of a large cell neuroendocrine carcinoma in the thymus, especially in young people, is extremely rare. In this current report, we discuss the clinicopathological issues of this rare tumor according to recent literature data.