CT differentiation of poorly-differentiated gastric neuroendocrine tumours from well-differentiated neuroendocrine tumours and gastric adenocarcinomas

Targeted gene sequencing and bioinformatics analysis of patients with gallbladder neuroendocrine carcinoma: A case report

BACKGROUND

Gallbladder neuroendocrine carcinoma (NEC) represents a subtype of gallbladder malignancies characterized by a low incidence, aggressive nature, and poor prognosis. Despite its clinical severity, the genetic alterations, mechanisms, and signaling pathways underlying gallbladder NEC remain unclear.

CASE SUMMARY

This case study presents a rare instance of primary gallbladder NEC in a 73-year-old female patient, who underwent a radical cholecystectomy with hepatic hilar lymphadenectomy and resection of liver segments IV-B and V. Targeted gene sequencing and bioinformatics analysis tools, including STRING, GeneMANIA, Metascape, TRRUST, Sangerbox, cBioPortal and GSCA, were used to analyze the biological functions and features of mutated genes in gallbladder NEC. Twelve mutations (APC, ARID2, IFNA6, KEAP1, RB1, SMAD4, TP53, BTK, GATA1, GNAS, and PRDM3) were identified, and the tumor mutation burden was determined to be 9.52 muts/Mb via targeted gene sequencing. A protein-protein interaction network showed significant interactions among the twelve mutated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to assess mutation functions and pathways. The results revealed 40 tumor-related pathways. A key regulatory factor for gallbladder NEC-related genes was identified, and its biological functions and features were compared with those of gallbladder carcinoma.

CONCLUSION

Gallbladder NEC requires standardized treatment. Comparisons with other gallbladder carcinomas revealed clinical phenotypes, molecular alterations, functional characteristics, and enriched pathways.

Synergizing traditional CT imaging with radiomics: a novel model for preoperative diagnosis of gastric neuroendocrine and mixed adenoneuroendocrine carcinoma

Objective

To develop diagnostic models for differentiating gastric neuroendocrine carcinoma (g-NEC) and gastric mixed adeno-neuroendocrine carcinoma (g-MANEC) from gastric adenocarcinoma (g-ADC) based on traditional contrast enhanced CT imaging features and radiomics features.

Methods

We retrospectively analyzed 90 g-(MA)NEC (g-MANEC and g-NEC) patients matched 1:1 by T-stage with 90 g-ADC patients. Traditional CT features were analyzed using univariable and multivariable logistic regression. Tumor segmentation and radiomics features extraction were performed with Slicer and PyRadiomics. Feature selection was conducted through univariable analysis, correlation analysis, LASSO, and multivariable stepwise logistic. The combined model incorporated clinical and radiomics predictors. Diagnostic performance was assessed with ROC curves and DeLong's test. The models' diagnostic efficacy was further validated in subgroup of g-NEC vs. g-ADC and g-MANEC vs. g-ADC cases.

Results

Tumor necrosis and lymph node metastasis were independent predictors for differentiating g-(MA)NEC from g-ADC (P < 0.05). The clinical model's AUC was 0.700 (training) and 0.667(validation). Five radiomics features were retained, with the radiomics model showing AUC of 0.809 (training) and 0.802 (validation). The combined model's AUCs were 0.853 (training) and 0.812 (validation), significantly outperforming the clinical model (P < 0.05). Subgroup analysis revealed that the combined model exhibited acceptable performance in differentiating g-NEC from g-ADC and g-MANEC from g-ADC, with AUC of 0.887 and 0.823 in the training cohort and 0.852 and 0.762 in the validation cohort.

Conclusion

A combined model based on traditional CT imaging and radiomic features provides a non-invasive and effective preoperative diagnostic method for differentiating g-(MA)NEC from g-ADC.

CT gastrography and enterography retrospective analysis: thickened diaphragm crura is a false indication for a gastric fundic tumor

Objectives

To mitigate the incidence of misdiagnosis and distinguish between gastric fundic tumors (GFTs) and thickened diaphragmatic crura (TDC).

Materials and methods

Computed tomographic enterography (CTE) data from 3844 cases and computed tomographic gastrography (CTG) data from 4351 cases were retrospectively analyzed. A total of 105 cases were selected and categorized into three groups: 47 cases with TDC examined via CTE, 31 with adenocarcinoma, and 27 with gastrointestinal stromal tumors (GIST) examined via CTG. Inter-group differences in age, sex distribution, mass dimensions, mass-stomach interface (MSI), chief complaints, gastric underlying diseases, and enhancement patterns were analyzed.

Results

The misdiagnosis rate of TDC as a tumor by radiologists is approximately 1.2% (47/3844). Age (p<0.05), sex ratio (p<0.05), mean mass size (p<0.05), chief complaint (p<0.05) and mass-stomach interface (MSI, p<0.05) were significantly different among patients with GIST, adenocarcinoma and TDC. The contrast enhancement pattern of TDC markedly differed from that observed in adenocarcinoma (p<0.05) and GIST (p<0.05) patients.

Conclusions

Misdiagnosis of GFTs is occasionally and may be challenging to differentiate from TDC using CTE. To drastically lower the chance of misdiagnosis, this research aimed to assist radiologists in identifying and considering the possibility of TDC.

Advancements in Neuroendocrine Neoplasms: Imaging and Future Frontiers

Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans. Imaging methods like CT, MRI, and PET/CT are crucial for detection, staging, treatment planning, and monitoring, but each of them poses different interpretative challenges and none are immune to pitfalls. Treatment options include surgery, targeted therapies, and chemotherapy, based on the tumor type, stage, and patient-specific factors. This review aims to provide insights into the latest developments and challenges in NEN imaging, diagnosis, and management.

Gastric neuroendocrine neoplasms: a primer for radiologists

Gastric neuroendocrine neoplasms are uncommon tumors with variable differentiation and malignant potential. Three main subtypes are recognized: type 1, related to autoimmune atrophic gastritis; type 2, associated with Zollinger-Ellison and MEN1 syndrome; and type 3, sporadic. Although endoscopy alone is often sufficient for diagnosis and management of small, indolent, multifocal type 1 tumors, imaging is essential for evaluation of larger, high-grade, and type 2 and 3 neoplasms. Hypervascular intraluminal gastric masses are typically seen on CT/MRI, with associated perigastric lymphadenopathy and liver metastases in advanced cases. Somatostatin receptor nuclear imaging (such as Ga-68-DOTATATE PET/CT) may also be used for staging and assessing candidacy for peptide receptor radionuclide therapy. Radiotracer uptake is more likely in well-differentiated, lower-grade tumors, and less likely in poorly differentiated tumors, for which F-18-FDG-PET/CT may have additional value. Understanding disease pathophysiology and evolving histologic classifications is particularly useful for radiologists, as these influence tumor behavior, preferred imaging, therapy options, and patient prognosis.

Comprehensive Clinical Analysis of Gallbladder Neuroendocrine Neoplasms: A Large-Volume Multicenter Study During One Decade

BACKGROUND

This study aimed to comprehensively investigate the clinicopathologic characteristics and therapeutic situations of gallbladder neuroendocrine neoplasms (GB-NENs) in the real world via a multicenter, large-scale cohort study.

METHODS

The study searched for patients in 143 hospitals in China and enrolled 154 patients with GB-NENs diagnosed in 40 hospitals between 2004 and 2021. Clinicopathologic characteristics and therapeutic approaches were analyzed retrospectively.

RESULTS

The median age at the initial diagnosis of the patients with GB-NENs was 63 years (range 33-83 years), and 61.7% of the patients were women. Tumor-node-metastasis staging classified 92 patients as stage 3 or above. Based on the 2019 World Health Organization classification, 96 cases (62.3%) were confirmed pathologically as poorly differentiated neuroendocrine carcinomas, 13 cases (8.4%) as well-differentiated neuroendocrine tumors, and 45 cases as mixed neuroendocrine-non-neuroendocrine neoplasms. The liver was the most frequent metastatic site. Immunohistochemistry showed that synaptophysin was most frequently positive (80.4%), followed by chromogranin A (61.7%), and CD56 (58.4%). Computed tomography and magnetic resonance imaging showed more common clear boundaries (25/39 cases) and invasive growth features (27 cases). None of these cases had an accurate diagnosis before surgery, with a misdiagnosis rate of 100%. Surgical resection is the main treatment, and platinum-based chemotherapeutic regimens were preferred as adjuvant therapies for patients with GB-NENs. The available survival data for 74 patients showed an overall survival rate of 59% at 1 year, 33% at 3 years, and 29% at 5 years. No significant difference was found between the patients treated with and those treated without adjuvant chemotherapy.

CONCLUSIONS

Gallbladder neuroendocrine neoplasms have high malignancy and a poor prognosis. Importantly, this large-scale cohort study significantly improves our understanding of GB-NENs and will benefit the exploration of its mechanism and treatment modes. Further investigation is necessary to explore the management of this disease.

New Developments in Gastric Neuroendocrine Neoplasms

Purpose of Review

Gastric neuroendocrine neoplasms (g-NENs) are a rare type of stomach cancer. The three main subtypes have different pathogeneses, biological behaviours and clinical characteristics, so they require different management strategies. This article will provide an overview of g-NENs and highlight recent advances in the field.

Recent Findings

Molecular profiling has revealed differences between indolent and aggressive g-NENs, as well as a new somatic mutation responsible for some familial type I g-NENs. Novel biomarkers have been developed which will hopefully improve diagnosis, treatment, risk stratification and follow-up. Patient treatment is also changing, as evidence supports the use of less aggressive options (e.g. endoscopic surveillance or resection) in some patients with more indolent tumours.

Summary

g-NEN heterogeneity poses challenges in understanding and managing this rare disease. More basic science research is needed to investigate molecular pathogenesis, and future larger clinical studies will hopefully also further improve treatment and patient outcomes.

Insight into gastrointestinal heterotopic pancreas: imaging evaluation and differential diagnosis

Heterotopic pancreas (HP) is an uncommon congenital abnormality in the developmental process of the pancreas, with gastrointestinal heterotopic pancreas (GHP) being the most common HP. The clinical manifestations of GHP may have variable patterns of presentation, dictated by both the anatomic location and the functional ability of the lesion. The most common imaging modality in detecting GHP is computed tomography (CT), while gastrointestinal barium fluoroscopy, endoscopic ultrasonography, and magnetic resonance imaging (MRI) are also applied. The density and enhancement patterns of GHP are consistent with histological classifications. GHP with a predominantly acinar tissue component manifests homogeneous and marked enhancement on CT images, whereas a predominantly ductal GHP presents heterogeneous and mild enhancement. On MRI, the appearance and signal intensity of GHP were paralleled to the normal pancreas on all sequences and were characterized by T1-weighted high signal and early marked enhancement. This article provides a comprehensive review of the histopathology, clinical manifestations, imaging features of various modalities, and differential diagnosis of GHP. It is hoped that this review will improve clinicians' knowledge of GHP and aid in accurate preoperative diagnosis, thereby reducing the misdiagnosis rate.

Comparison of the Clinical Features and Outcomes of Gallbladder Neuroendocrine Carcinoma with Those of Adenocarcinoma: A Propensity Score-Matched Analysis

Simple Summary

Neuroendocrine neoplasms (NENs) of the gallbladder (GB) are extremely rare. We aimed to compare the clinical features of GB-NENs with those of adenocarcinomas (ADCs) of the GB. Among 21 patients with GB-NENs, 20 were diagnosed with poorly differentiated small-cell neuroendocrine carcinoma (NEC), and 1 patient had large-cell NEC. At initial presentation, all patients had advanced stages of cancer, with extensive local extension and/or distant metastasis. Nine patients with GB-NEC who underwent surgical resection had a significantly better progression-free survival (PFS) than those who did not undergo surgery. After a propensity score matching with a 1:1 ratio using the American Joint Committee on Cancer (AJCC) stage, age, sex, and operation status, there was no difference in the overall survival or PFS between AJCC stage-matched patients with GB-NEC or GB-ADC. In conclusion, GB-NEC is difficult to diagnose early and has a prognosis similar to that of GB-ADC.

Abstract

Neuroendocrine neoplasms (NENs) of the gallbladder (GB) are extremely rare. We aimed to compare the clinical features, disease progression, management, and prognosis of patients with GB-NENs with those of patients with GB-adenocarcinomas (ADCs). A total of 21 patients with GB-NENs and 206 patients with GB-ADCs, treated at three tertiary medical centers between January 2010 and December 2020, were enrolled. Of the 21 patients with GB-NENs, 20 were diagnosed with poorly differentiated small-cell neuroendocrine carcinomas (NECs), and 1 patient had large-cell NEC. All patients presented with advanced stages of cancer with extensive local extension and/or distant metastasis and non-specific symptoms. Tumor-node-metastasis stage IIIB and IV (A/B) tumors were found in 6 and 15 (1/14) patients, respectively. Nine patients with GB-NEC who underwent surgical resection had a significantly better progression-free survival (PFS) than those who did not undergo surgery. After a propensity score matching with a 1:1 ratio using the American Joint Committee on Cancer stage, age, sex, and operation status, 19 pairs of patients were included. Compared with stage-matched patients with GB-ADC, patients with GB-NEC had similar overall survival and PFS. However, as GB-NEC is rarely diagnosed early, further studies investigating methods for the early diagnosis and improvement in the survival of patients with GB-NEC are needed.

Update in clinical management for gallbladder neuroendocrine carcinoma

BACKGROUND

Gallbladder neuroendocrine carcinoma (GB-NEC) is rare and there are few reports at present. We sought to review the current knowledge of GB-NEC and provide recommendations for clinical management.

METHODS

A systemic literature research was conducted in the websites of Pubmed, Medline, Web of Science, CNKI, Wanfang Data using the keywords including gallbladder combined with neuroendocrine carcinoma or neuroendocrine tumor or neuroendocrine neoplasm. Two reviewers independently screened the articles by reading the title, abstract and full-text.

RESULTS

In computed tomography (CT) and magnetic resonance imaging (MRI) examination, a well-defined margin, gallbladder replacing type with larger hepatic and lymphatic metastases could be helpful for differential diagnosis of GB-NEC and gallbladder adenocarcinoma (GB-ADC). Older age, unmarried status, large tumor size (>5 cm), positive margins, and distant Surveillance, Epidemiology and End result (SEER) stage are independently associated with poor survival. Surgical resection remains as the preferred and primary treatment. The potential survival benefit of lymphadenectomy for patients remains controversial. Platinum-based postoperative adjuvant chemotherapy may improve the survival. The efficacy of other treatments including immunotherapy, targeted therapy and somatostatin analogue needs further investigation.

CONCLUSION

Typical imaging features could be helpful for preoperative diagnosis. Age, margin status, tumor size, marital status, histopathologic subtype and SEER stage may be independent predictors for the survival. Remarkable advances regarding the treatment for GB-NEC have been achieved in recent years. Further studies are needed to investigate the survival benefit of lymphadenectomy for patients with GB-NEC.

Radiomics analysis of CT imaging for differentiating gastric neuroendocrine carcinomas from gastric adenocarcinomas

PURPOSE

To develop and evaluate a CT-based radiomics nomogram for differentiating gastric neuroendocrine carcinomas (NECs) from gastric adenocarcinomas (ADCs).

METHODS

CT images of 63 patients with gastric NECs were collected retrospectively, and 63 patients with gastric ADCs were selected as the control group. Univariate analysis was used to identify the significant factors of clinical characteristics and CT findings for differentiating gastric NECs from ADCs. Radiomics analysis was applied to CT images of unenhanced, arterial phase and venous phase, respectively. A radiomics nomogram incorporating the radiomics signature and the subjective CT findings was developed and its diagnostic ability was evaluated. The diagnostic performances of CT findings model, radiomics signature and radiomics nomogram were compared using DeLong test.

RESULTS

The tumor margin and lymph node (LN) metastasis were independent predictors for differentiating gastric NECs from ADCs. The radiomics signature based on venous phase presented superior AUC of 0.798 [95 % confidence interval (CI), 0.657-0.938] in validation cohort. The nomogram incorporated the radiomics signature, tumor margin and LN metastasis showed AUCs of 0.821 (95 %CI: 0.725-0.895) in the primary cohort and 0.809 (95 %CI: 0.649-0.918) in the validation cohort. Moreover, the radiomics nomogram showed good discrimination and calibration. The diagnostic performance of CT findings model was significantly lower than that of radiomics nomogram (p =  0.001) and radiomics signature (p = 0.025).

CONCLUSIONS

Radiomics analysis exhibited good performance in differentiating gastric NECs from ADCs, and the radiomics nomogram may have significant clinical implications on preoperative detection of gastric malignant tumors.

Preoperative CT feature of incomplete overlying enhancing mucosa as a high-risk predictor in gastrointestinal stromal tumors of the stomach

OBJECTIVES

To determine whether the CT finding of overlying enhancing gastric mucosa (OEGM) can be used to predict risk stratifications by observing CT features of gastrointestinal stromal tumors (GISTs) of the stomach.

METHODS

Clinical characteristics and CT features within pathologically demonstrated GISTs were retrospectively reviewed. Risk stratifications were classified into non-high group and high-risk group according to the modified National Institutes of Health criteria. Univariate analysis and multivariate logistic regression analysis were performed in order to determine significant predictors for high-risk stratification. Receiver operating characteristic (ROC) curve analysis, subgroup analysis, and pathologic-radiologic correlation analysis were all executed.

RESULTS

A total of 147 patients were finally enrolled as test subjects. Within the univariate analysis, high-risk tumors tended to have a larger diameter, irregular shape, exophytic growth pattern, present necrosis, incomplete OEGM, tumor vessels, heterogeneous enhancement, and present rupture. According to ROC curve analysis, incomplete OEGM showed the largest area under curve values for diagnosing lesions (0.835; 95% CI, 0.766-0.904; p < 0.001). Multivariate analysis showed that the incomplete OEGM was the strongest independent predictor for high-risk stratification of gastric GISTs (OR = 21.944; 95% CI, 4.344-110.863; p < 0.001). Within the subgroup analysis, incomplete OEGM was more frequently associated with tumors size > 10 cm, irregular shape, exophytic growth pattern, high mitotic count, and disrupted mucosa on pathology.

CONCLUSIONS

The CT feature of incomplete OEGM is an independent predictive factor for high-risk stratification of gastric GISTs and strongly correlated with pathological mucosal changes.

KEY POINTS

• Preoperative CT features can be helpful in assessment of risk stratifications of gastric GISTs. • OEGM is an independent predictor for high-risk stratification of gastric GISTs. • Incomplete OEGM likely indicates high-risk stratification of gastric GISTs.

Differential and prognostic MRI features of gallbladder neuroendocrine tumors and adenocarcinomas

OBJECTIVES

To identify MRI features that are helpful for the differentiation of gallbladder neuroendocrine tumors (GB-NETs) from gallbladder adenocarcinomas (GB-ADCs) and to evaluate their prognostic values.

METHODS

Between January 2008 and December 2018, we retrospectively enrolled patients who underwent MRI for GB malignancy. Two radiologists independently assessed the MRI findings and reached a consensus. Significant MRI features, which distinguish GB-NETs from GB-ADCs, were identified. Cox regression analyses were performed to find MRI features that were prognostic for overall survival.

RESULTS

There were 63 patients with GB-NETs (n = 21) and GB-ADCs (n = 42). Compared with GB-ADCs, GB-NETs more frequently demonstrated the following MRI features: well-defined margins, intact overlying mucosa, and thick rim contrast enhancement and/or diffusion restriction (ps < 0.001). Liver metastases were more common and demonstrated thick rim contrast enhancement and diffusion restriction in GB-NETs (ps < 0.001). Lymph node (LN) metastasis showed thick rim diffusion restriction more often in GB-NETs than in GB-ADCs (p = 0.009). On quantitative analysis, the sizes of the GB mass and metastatic LNs in GB-NETs were larger than those in GB-ADCs (p = 0.002 and p = 0.010, respectively). The ratio of apparent diffusion coefficient values between the lesion and the spleen was lower in the GB mass, liver metastases, and LN metastases of GB-NETs than those of GB-ADCs (p < 0.001, p = 0.017, and p < 0.001, respectively). Survival analysis revealed that a large metastatic LN (hazard ratio 1.737; 95% confidence interval, 1.112-2.712) was the only poor prognostic factor (p = 0.015).

CONCLUSION

Several MRI features aided in differentiating between GB-NETs and GB-ADCs. A large metastatic LN was associated with poor survival.

KEY POINTS

• Compared with gallbladder adenocarcinomas (GB-ADCs), neuroendocrine tumors (GB-NETs) and their metastases to the liver and lymph nodes more frequently demonstrated a thick rim appearance on contrast-enhanced MRI and diffusion-weighted images. • The ratio of apparent diffusion coefficient values between the lesion and the spleen was significantly lower for the primary mass, liver metastases, and lymph node metastases of GB-NETs than for those of GB-ADCs. • A large metastatic lymph node was the only poor prognostic factor for overall survival in patients with GB-NETs and GB-ADCs.

Radiographic characteristics of neuroendocrine liver metastases do not predict clinical outcomes following liver resection

Background

Previous research has demonstrated that specific radiographic criteria, including the presence of calcifications and the enhancement pattern on computed tomography (CT) imaging, correlates with clinicopathologic features and outcomes of patients with gastroenteropancreatic neuroendocrine tumors (NET). We sought to investigate whether these radiographic characteristics were prognostic among patients with neuroendocrine liver metastases (NELM) undergoing surgical resection.

Methods

The preoperative contrast-enhanced CT scans of all patients who underwent resection of NELM at a single institution between 2000-2015 were retrospectively reviewed. The presence of calcifications was determined on non-contrast phase imaging. Enhancement on the arterial phase scan was categorized as hyperenhancing, hypoenhancing, or mixed. Relevant clinicopathologic characteristics as well as recurrence-free survival (RFS) and overall survival (OS) were compared between groups.

Results

Among 82 patients who underwent resection of NELM, 57 had available data on calcifications while 51 had data available on arterial enhancement patterns. Among all patients, median age was 58 (IQR: 47-63) and the majority were female (N=48, 59.5%). The most common primary tumor locations were pancreas (N=25, 30.5%) and small bowel (N=27, 32.9%). The most commonly performed operations were right hepatectomy (N=29, 35.4%), bisegmentectomy (N=15, 18.3%), and segmentectomy (N=14, 17.1%). Median tumor number was 4 (IQR: 2-9), median Ki-67 was 5% (IQR: 2-10%), and median size of the largest liver metastasis was 4.5 (IQR: 2.8-7.7) cm. Twelve (21%) patients had tumor calcifications. Among patients with and without calcifications there were no differences in demographics, clinicopathologic characteristics, RFS (P=0.772) or OS (P=0.095). Arterial enhancement was hypoenhancing in 23 (45.1%), hyperenhancing in 10 (19.6%), and mixed in 18 (35.3%). Similarly, there were no differences between arterial enhancement groups in demographics, clinicopathologic characteristics, RFS (P=0.618) or OS (P=0.268).

Conclusions

Radiographic characteristics on contrast-enhanced CT are not associated with the outcomes of patients undergoing resection of NELM. Future investigations should evaluate the prognostic impact of functional neuroendocrine imaging.

Value of computed tomography evaluation in pathologic classification and prognosis prediction of gastric neuroendocrine tumors

Background

The study aims to investigate the correlation of CT characteristics with pathological classifications and the prognostic value of CT features in patients with gastric neuroendocrine neoplasms (g-NENs).

Methods

Ninety-one cases of pathologically diagnosed g-NENs, including 15 cases of well-differentiated neuroendocrine tumors (NETs) (G1 and G2) and 76 cases of poor-differentiated neuroendocrine carcinomas (NECs) (G3 and MANEC) were retrospectively studied. All cases were included in correlation analysis of CT characteristics with pathologic grades. Among them, 76 patients who had fulfilled follow-up data were included for overall survival (OS) and disease-free survival (DFS) analysis.

Results

CT characteristics that favor poor differentiation include tumor location (fundus and cardia), larger tumor size (>3.0 cm), infiltrative growth, unclear tumor margin, serosa involvement, ulceration and lymph node metastasis (P<0.05). Most variables had sensitivities >80% and specificities >60% to distinguish NECs from NETs. Through log-rank analysis, it was revealed that serosa involvement, cystic degeneration, necrosis, heterogeneous enhancement and lymph node metastasis led to worse DFS and OS for patients with g-NENs (P<0.05). COX regression analysis showed that serosa involvement and lymph node metastasis were independent risk factor for DFS and OS, respectively, despite of grading, staging and therapeutic choices (P<0.05). Moreover, high Ki-67 index (>55%) in G3 g-NENs is in correlation with serosa involvement and lymph node metastasis; accordingly, patients with higher Ki-67 index had worse 1-year DFS (61.7% vs. 92.3%; P<0.05).

Conclusions

CT characteristics can be useful discriminators and prognostic factors for g-NENs and may help identify G3 g-NEC from G3 g-NEN by revealing its poor differentiation and high invasive potential.

Utility of CT in differentiating liver metastases of well-differentiated gastroenteropancreatic neuroendocrine neoplasms from poorly-differentiated neuroendocrine neoplasms

Objective

To determine the capability of dynamic enhanced computed tomography (CT) to differentiate liver metastases (LMs) of well-differentiated from poorly-differentiated gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs).

Methods

Patients with LMs of GEP-NENs who underwent dynamic enhanced CT examination in Peking University Cancer Hospital from January 2009 to October 2015 were included and data were retrospectively analyzed. We assessed the qualitative and quantitative CT features to identify the significant differentiating CT features of LMs of poorly-differentiated GEP-NENs from those of well-differentiated GEP-NENs using univariate analysis and a multivariate logistic regression model.

Results

The study included 22 patients with LMs of well-differentiated GEP-NENs and 32 patients with LMs of poorly-differentiated GEP-NENs. Univariate analysis revealed statistically significant differences between the LMs of well- and poorly-differentiated GEP-NENs in terms of feeding arteries (36.4% vs. 75.0%, χ²=8.061, P=0.005), intratumoral neovascularity (18.2% vs. 59.4%, χ²=9.047, P=0.003), lymphadenopathy (27.3% vs. 81.2%, χ²=15.733, P<0.001), tumor-to-aortic ratio in the hepatic arterial and portal venous phase (T-A/AP: 0.297±0.080vs. 0.251±0.059, t=2.437, P=0.018; T-A/PVP: 0.639±0.138 vs. 0.529±0.117, t=3.163, P=0.003) and tumor-to-liver ratio in the hepatic arterial phase (T-L/AP: 1.108±0.267 vs. 0.907±0.240, t=2.882, P=0.006). The LMs of poorly-differentiated GEP-NENs showed more feeding arteries, more intratumoral neovascularity, more lymphadenopathy and a lower tumor-to-aortic ratio. Multivariate analysis suggested that intratumoral neovascularity [P=0.015, OR=0.108, 95% confidence interval (95% CI), 0.018-0.646], lymphadenopathy (P=0.001, OR=0.055, 95% CI, 0.009-0.323) and T-A/PVP (P=0.004, OR=5.3E-5, 95% CI, 0.000-0.044) were independent factors for differentiating LMs of poorly-differentiated from well-differentiated GEP-NENs.

Conclusions

Dynamic enhanced CT features (intratumoral neovascularity, lymphadenopathy and T-A/PVP) are useful in the pathological classification of LMs of GEP-NENs.

Computed tomography-based radiomics for prediction of neoadjuvant chemotherapy outcomes in locally advanced gastric cancer: A pilot study

Objective

The standard treatment for patients with locally advanced gastric cancer has relied on perioperative radio-chemotherapy or chemotherapy and surgery. The aim of this study was to investigate the wealth of radiomics for pre-treatment computed tomography (CT) in the prediction of the pathological response of locally advanced gastric cancer with preoperative chemotherapy.

Methods

Thirty consecutive patients with CT-staged II/III gastric cancer receiving neoadjuvant chemotherapy were enrolled in this study between December 2014 and March 2017. All patients underwent upper abdominal CT during the unenhanced, late arterial phase (AP) and portal venous phase (PP) before the administration of neoadjuvant chemotherapy. In total, 19,985 radiomics features were extracted in the AP and PP for each patient. Four methods were adopted during feature selection and eight methods were used in the process of building the classifier model. Thirty-two combinations of feature selection and classification methods were examined. Receiver operating characteristic (ROC) curves were used to evaluate the capability of each combination of feature selection and classification method to predict a non-good response (non-GR) based on tumor regression grade (TRG).

Results

The mean area under the curve (AUC) ranged from 0.194 to 0.621 in the AP, and from 0.455 to 0.722 in the PP, according to different combinations of feature selection and the classification methods. There was only one cross-combination machine-learning method indicating a relatively higher AUC (>0.600) in the AP, while 12 cross-combination machine-learning methods presented relatively higher AUCs (all >0.600) in the PP. The feature selection method adopted by a filter based on linear discriminant analysis + classifier of random forest achieved a significantly prognostic performance in the PP (AUC, 0.722±0.108; accuracy, 0.793; sensitivity, 0.636; specificity, 0.889; Z=2.039; P=0.041).

Conclusions

It is possible to predict non-GR after neoadjuvant chemotherapy in locally advanced gastric cancers based on the radiomics of CT.

Dynamic enhanced CT: is there a difference between liver metastases of gastroenteropancreatic neuroendocrine tumor and adenocarcinoma

This study proposed to evaluate the feasibility of dynamic enhanced CT in differentiation of liver metastases of gastroenteropancreatic well-differentiated neuroendocrine tumors (GEP NETs) from GEP adenocarcinomas based on their characteristic features. CT images of 23 well-differentiated (G1 or G2) GEP NETs and 23 GEP adenocarcinomas patients with liver metastases were retrospectively reviewed. The distribution type, shape, intra-tumoral neovascularity, enhancement on hepatic artery phase, dynamic enhancement pattern and lymphadenopathy were subjective analyzed. Meanwhile, the size, number, CT value of tumor and adjacent normal liver parenchyma were measured and the metastasis-to-liver ratios were calculated objectively. Compared with GEP adenocarcinomas, the liver metastases of GEP NETs more frequently demonstrated a hyper enhancement on hepatic artery phase, washout dynamic enhancement pattern, absence of lymphadenopathy and higher metastasis-to-liver ratios on both hepatic artery phase and portal venous phase (P=0.017, P<0.001, P =0.038, P <0.001 and P =0.008, respectively). Logistic regression analysis showed that the dynamic enhancement pattern (P=0.012), and the metastasis-to-liver ratios on hepatic artery phase (P=0.009) were independent CT predictors for liver metastases of GEP NETs. The sensitivity and specificity of combing the two predictors in differentiation of liver metastases of GEP adenocarcinomas from GEP NET were 82.6% (19 of 23) and 91.3% (21 of 23), respectively. CT features are helpful in differentiating liver metastases of well-differentiated GEP NETs from that of GEP adenocarcinomas.

CT Perfusion evaluation of gastric cancer: correlation with histologic type

OBJECTIVES

To prospectively evaluate if the perfusion parameters of gastric cancer can provide information on histologic subtypes of gastric cancer.

METHODS

We performed preoperative perfusion CT (PCT) and curative gastrectomy in 46 patients. PCT data were analysed using a dedicated software program. Perfusion parameters were obtained by two independent radiologists and were compared according to histologic type using Kruskal-Wallis, Mann-Whitney U test and receiver operating characteristic analysis. To assess inter-reader agreement, we used intraclass correlation coefficient (ICC).

RESULTS

Inter-reader agreement for perfusion parameters was moderate to substantial (ICC = 0.585-0.678). Permeability surface value of poorly cohesive carcinoma (PCC) was significantly higher than other histologic types (47.3 ml/100 g/min in PCC vs 26.5 ml/100 g/min in non-PCC, P < 0.001). Mean transit time (MTT) of PCC was also significantly longer than non-PCC (13.0 s in PCC vs 10.3 s in non-PCC, P = 0.032). The area under the curve to predict PCC was 0.891 (P < 0.001) for permeability surface and 0.697 (P = 0.015) for MTT.

CONCLUSION

Obtaining perfusion parameters from PCT was feasible in gastric cancer patients and can aid in the preoperative imaging diagnosis of PCC-type gastric cancer as the permeability surface and MTT value of PCC type gastric cancer were significantly higher than those of non-PCC.

KEY POINTS

• Obtaining perfusion parameters from PCT was feasible in patients with gastric cancer. • Permeability surface and MTT were significantly higher in poorly cohesive carcinoma (PCC). • Permeability surface, MTT can aid in the preoperative imaging diagnosis of PCC.

Human Epidermal Growth Factor Receptor 2 Expression in Unresectable Gastric Cancers: Relationship with CT Characteristics

Objective

To retrospectively analyze the qualitative CT features that correlate with human epidermal growth factor receptor 2 (HER2)-expression in pathologically-proven gastric cancers.

Materials and Methods

A total of 181 patients with pathologically-proven unresectable gastric cancers with HER2-expression (HER2-positive [n = 32] and negative [n = 149]) were included. CT features of primary gastric and metastatic tumors were reviewed. The prevalence of each CT finding was compared in both groups. Thereafter, binary logistic regression determined the most significant differential CT features. Clinical outcomes were compared using Kaplan-Meier method.

Results

HER2-postive cancers showed lower clinical T stage (21.9% vs. 8.1%; p = 0.015), hyperattenuation on portal phase (62.5% vs. 30.9%; p = 0.003), and was more frequently metastasized to the liver (62.5% vs. 32.2%; p = 0.001), than HER2-negative cancers. On binary regression analysis, hyperattenuation of the tumor (odds ratio [OR], 4.68; p < 0.001) and hepatic metastasis (OR, 4.43; p = 0.001) were significant independent factors that predict HER2-positive cancers. Median survival of HER2-positive cancers (13.7 months) was significantly longer than HER2-negative cancers (9.6 months) (p = 0.035).

Conclusion

HER2-positive gastric cancers show less-advanced T stage, hyperattenuation on the portal phase, and frequently metastasize to the liver, as compared to HER2-negative cancers.

Outcome and CT differentiation of gallbladder neuroendocrine tumours from adenocarcinomas

OBJECTIVES

To retrospectively investigate clinical outcome and differential CT features of gallbladder (GB) neuroendocrine tumours (NETs) from adenocarcinomas (ADCs).

MATERIALS AND METHODS

Nineteen patients with poorly-differentiated (PD) NETs and 19 patients with PD ADCs were enrolled. Clinical outcome was compared by the Kaplan-Meier method. We assessed qualitative and quantitative CT features to identify significant differential CT features of PD NETs from ADCs using univariate and multivariate analyses. Receiver operating characteristic (ROC) analysis was used for quantitative CT features.

RESULTS

PD NETs showed poorer prognosis with significantly shorter median survival days than ADCs (363 vs. 590 days, P = 0.03). On univariate analysis, NETs more frequently manifested as GB-replacing type and showed well-defined margins accompanied with intact overlying mucosa. On multivariate analysis, well-defined margin was the sole significant CT differentiator (odds ratio = 27.817, P = 0.045). Maximum size of hepatic and lymph node (LN) metastases was significantly larger in NETs (11.0 cm and 4.62 cm) than ADCs (2.40 cm and 2.41 cm). Areas under ROC curves for tumour-to-mucosa ratio, maximum size of hepatic and LN metastasis were 0.772, 0.932 and 0.919, respectively (P < 0.05).

CONCLUSION

GB PD NETs show poorer prognosis than ADCs. Well-defined margin, larger hepatic and LN metastases are useful CT differentiators of GB NETs from ADCs.

KEY POINTS

• A well-defined margin is a useful CT differentiator of GB NETs from ADCs. • Hepatic and LN metastases are significantly larger in NETs than in ADCs. • Primary tumour and hepatic metastasis of NETs are more hyperattenuated than ADCs.