Metformin and pancreatic neuroendocrine tumors: A systematic review and meta-analysis.

BACKGROUND: Most patients with advanced pancreatic neuroendocrine tumors (pNETs) die due to tumor progression. Therefore, identifying new therapies with low toxicity and good tolerability to use concomitantly with the established pNET treatment is relevant. In this perspective, metformin is emerging as a molecule of interest. Retrospective studies have described metformin, a widely used agent for the treatment of patients with type 2 diabetes mellitus (T2DM), to be effective in modulating different tumor-related events, including cancer incidence, recurrence and survival by inhibiting mTOR phosphorylation. This systematic review evaluates the role of T2DM and metformin in the insurgence and post-treatment outcomes in patients with pNET. AIM: To systematically analyze and summarize evidence related to the diagnostic and prognostic value of T2DM and metformin for predicting the insurgence and post-treatment outcomes of pNET. METHODS: A systematic review of the published literature was undertaken, focusing on the role of T2DM and metformin in insurgence and prognosis of pNET, measured through outcomes of tumor-free survival (TFS), overall survival and progression-free survival. RESULTS: A total of 13 studies (5674 patients) were included in this review. Analysis of 809 pNET cases from five retrospective studies (low study heterogeneity with I² = 0%) confirms the correlation between T2DM and insurgence of pNET (OR = 2.13, 95%CI = 1.56-4.55; P < 0.001). The pooled data from 1174 pNET patients showed the correlation between T2DM and post-treatment TFS in pNET patients (hazard ratio = 1.84, 95%CI = 0.78-2.90; P < 0.001). The study heterogeneity was intermediate, with I² = 51%. A few studies limited the possibility of performing pooled analysis in the setting of metformin; therefore, results were heterogeneous, with no statistical relevance to the use of this drug in the diagnosis and prognosis of pNET. CONCLUSION: T2DM represents a risk factor for the insurgence of pNET and is a significant predictor of poor post-treatment TFS of pNET patients. Unfortunately, a few studies with heterogeneous results limited the possibility of exploring the effect of metformin in the diagnosis and prognosis of pNET.

Operative treatment of pulmonary primitive neuroectodermal tumor: a case report and literature review.

BACKGROUND: Pulmonary primitive neuroectodermal tumor (PNET), a member of the Ewing sarcoma family of tumors, is a rare malignancy that is associated with a grim prognosis. To date, fewer than 30 cases of pulmonary PNET have been reported. In this case report, we present the clinical details of a 12-year-old girl with pulmonary PNET who underwent surgical treatment. We also conducted an analysis and summary of other relevant studies and the surgical outcomes. CASE PRESENTATION: In May 2018, a 12-year-old girl was admitted with symptoms of cough and blood-tinged phlegm. A computed tomography scan revealed a large mass, measuring 12.9 cm × 8.1 cm, in the right middle and lower lungs. A percutaneous lung biopsy confirmed poorly differentiated tumor cells with a nested growth pattern. Immunohistochemical staining demonstrated positive expression of CD99, CD56, Vimentin, and Synaptophysin. The patient was diagnosed with pulmonary PNET. Following three cycles of neoadjuvant chemotherapy, a substantial reduction in tumor volume was observed. Subsequently, the patient underwent a surgical procedure involving pneumonectomy and partial resection of the left atrium with the assistance of cardiopulmonary bypass. The patient was discharged 37 days after surgery. During a three-year follow-up period, she exhibited no signs of tumor recurrence and has successfully returned to school. CONCLUSIONS: This case highlights the successful management of an advanced PNET with neoadjuvant chemotherapy, pneumonectomy, and partial resection of the left atrium employing cardiopulmonary bypass. The patient remained disease-free after three years. Our analysis of surgically treated cases indicates that neoadjuvant chemotherapy can contribute to improved prognoses for PNET patients. It is crucial to emphasize that complete surgical excision remains the cornerstone of treatment, underscoring the importance of surgeons considering radical surgical approaches whenever feasible for patients with pulmonary PNETs.

Clinical and histopathological spectrum of cranial small round cell tumors: An experience from a tertiary care center.

BACKGROUND: Small round cell tumors (SRCTs) are a group of malignant neoplasms with minimal or no differentiation, characterized by the presence of round cells with high nuclear-cytoplasmic ratio. Although SRCTs can occur in any part of the body, involvement of central nervous system (CNS) is uncommon. AIM: We aimed to study the clinicopathological spectrum of cranial SRCT diagnosed in our institute over a period of four years (2016-2019). MATERIAL AND METHODS: A retrospective review of medical records (2016-2019) with a morphological diagnosis of cranial SRCT was made. Both intra-axial and extra-axial tumors were included. A total of 60 cases were retrieved, and the clinical and histopathological features were studied. Special cytochemical staining and immunohistochemistry were performed, where needed. RESULTS: The mean age at presentation was 18.4 years (range, 1-60 years), with a male-to-female ratio of 2.5:1. The most common site was posterior fossa of brain (n = 28, 47%), followed by dorso-lumbar spine (n = 9, 15%). The most common type of tumor was medulloblastoma (n = 29, 48.3%), followed by Ewing sarcoma (ES)/peripheral primitive neuroectodermal tumor (pPNET) (n = 11, 18.3%), non-Hodgkin lymphoma (NHL) (n = 9, 15%), neuroblastoma (n = 3, 5%), and CNS embryonal tumor, NOS (n = 2, 3.3%). One case each of atypical teratoid rhabdoid tumor (ATRT), rhabdomyosarcoma, pineoblastoma, melanoma, rhabdomyosarcoma, and undifferentiated pleomorphic sarcoma was also documented. CONCLUSIONS: SRCTs have a variable age of presentation. Their incidence in CNS is low as compared to other organ systems. On light microscopy, the histopathology of these lesions is overlapping, posing a great diagnostic dilemma for the pathologist. The use of ancillary techniques like immunohistochemistry helps in arriving at the correct diagnosis. Treatment strategy and tumor prognosis also vary along the entire spectrum of SRCT, thus making exact characterization essential for proper management.

Prognostic significance of systemic immune-inflammation index in patients with nonfunction pancreatic neuroendocrine tumor undergoing surgical resection.

PURPOSE: The purpose of our study was to investigate the clinical significance and prognostic role of the systemic immune-inflammation index (SII) in patients who underwent surgical resection for nonfunctioning pancreatic neuroendocrine tumors (pNETs). METHODS: We conducted a retrospective analysis of 364 patients with nonfunctioning pNETs. The association between the SII level and clinical parameters was investigated. The receiver operating characteristic (ROC) curve was used to calculate the optimal SII value. Cox proportional hazard analysis was performed to evaluate the prognostic factors. RESULTS: Our study included 364 patients with nonfunctioning pNETs who underwent surgery. The median age was 51.0 (43.0, 59.3), and 164 (45.1%) were male. The optimal threshold of SII determined by ROC analysis was 523.95. Higher SII levels were significantly associated with older age (p = 0.001), sex (p = 0.011), tumor size (p = 0.032), and tumor grade (p = 0.002). Recurrence was observed in 70 (19.2%) patients following a median follow-up of 98 months. Univariate analysis showed that higher SII (p < 0.0001), tumor size >4 cm (p = 0.015), and G2/G3 grade (p = 0.002) were significantly associated with disease-free survival (DFS). Multivariate analysis revealed that higher SII (HR: 7.35; 95% CI: 3.44, 15.70; p < 0.0001) and G2/G3 grade (HR: 3.11; 95% CI: 1.42, 6.82; p = 0.005) remained significantly associated with tumor recurrence. Furthermore, 46 (12.6%) patients died during the follow-up. Higher SII (HR: 8.43; 95% CI: 3.19, 22.72; p < 0.0001) and G2/G3 grade (HR: 3.16; 95% CI: 1.01, 9.86; p = 0.048) were independent predictors of overall survival (OS) by multivariate analysis. CONCLUSION: In conclusion, our study revealed that a higher SII level was associated with tumor-related features (larger tumor size and advanced grade) and subsequent shorter DFS and OS in patients with nonfunctioning pNETs. These results indicated that the SII could serve as an efficient prognostic biomarker for nonfunctioning pNETs.

Primitive neuroectodermal tumors of the ovary: a multidecade review of the scientific literature.

Primitive neuroectodermal tumor (PNET) is a general term used in scientific literature for a heterogeneous group of small round-cell malignant tumors primarily arising from neural crest cells. These are extremely aggressive neoplasms which usually occur within soft tissue or bone of young adults. Ovarian tumors composed of primitive neuroectodermal elements are extremely rare, with only few case reports in scientific literature. Due to being so exceedingly rare, PNETs are frequently misdiagnosed and there are no standard therapeutic guidelines. Young patients seem to have better prognoses and individualized strategy is recommended. Limited data suggests that various gene deletions as well as amplifications may be crucial factors for tumorigenesis and the aggressive behavior of PNET. In this paper, we performed a brief review of all cases of primary ovarian PNETs published in the scientific literature to date, in regard to their clinical, histopathological, and therapeutic aspects, with the aim to provide a more comprehensive understanding of this exceedingly rare pathology.

Endoscopic ultrasound-guided radiofrequency ablation of pancreatic insulinoma: a state of the art review.

INTRODUCTION: Insulinomas are the most common functional pancreatic neuroendocrine tumors (PNETs) that lead to incapacitating hypoglycemia. Guidelines recommend surgical resection as the mainstay of management. However, surgery is fraught with complications, causing significant peri/post-operative morbidity. Since insulinomas are usually benign, solitary, small (<2 cm), and do not need lymphadenectomy, hence, in this regard, endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA) is now being increasingly performed, to circumvent these adverse events and impairment of pancreatic function. AREAS COVERED: A comprehensive literature search was undertaken across various databases (PubMed/MEDLINE, Embase, Scopus), with no language restriction, for relevant articles (case series, reviews, case reports) pertaining to EUS-RFA for insulinoma and PNETs, till October 2023. In this review, we have explicated the role of EUS-RFA for insulinoma management, detailing thoroughly its mechanism of action, EUS-RFA devices with data on its safety and efficacy, and an algorithmic approach for its management. EXPERT OPINION: EUS-RFA is being advocated as a 'mini-invasive' option with the potential to replace surgery as a first-line approach for benign, sporadic, solitary, and small (<2 cm) insulinomas. Under real-time guidance, EUS-RFA has immense precision, is safe, predictable, with acceptable safety profile. Presently, it is being frequently performed for high-risk or inoperable candidates. Current need-of-the-hour is a randomized controlled trial to substantiate its role in the therapeutic algorithm for insulinoma management.

Value of markers of systemic inflammation for the prediction of postoperative progression in patients with pancreatic neuroendocrine tumors.

Background: Non-invasive prognostic predictors for rare pancreatic neuroendocrine tumors (PNETs) are lacking. We aimed to approach the prognostic value of preoperative systemic inflammatory markers in patients with PNETs. Methods: The clinical data of 174 patients with PNETs undergoing surgical treatment were retrospectively analyzed to explore the correlation of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and platelet to white blood cell ratio (PWR) with clinicopathological parameters and the progression of tumor after the operation. The optimal cutoff values for predictors and the area under the curve (AUC) of the receiver operating characteristic (ROC) were estimated. Univariate and multivariate Cox proportional hazards models were used to assess the relation between NLR, LMR, PLR, and progression-free survival (PFS), examined by the Kaplan-Meier and log-rank tests. Results: The scores of the NLR (P = 0.039) and PLR (P = 0.011) in the progression group were significantly higher than those in the progression-free group, and the LMR was significantly lower than those in the progression-free group (P = 0.001). The best cutoff values of NLR, LMR, and PLR before operation were 2.28, 4.36, and 120.91. The proportions of tumor progression in the high NLR group (P = 0.007) and high PLR group (P = 0.013) obviously increased, and the proportion of tumor development in the low LMR group was higher than that in the high LMR group (P < 0.001). The K-M survival curve showed that the progression-free survival rate was lower in the high NLR group (P = 0.004), the low LMR group (P < 0.001), and the high PLR group (P = 0.018). The results of the multivariate Cox proportional hazards model suggested that preoperative LMR (HR = 3.128, 95% CI: 1.107~8.836, P = 0.031) was an independent predictor of PFS. Conclusion: The markers of systemic inflammation, especially LMR, can predict the postoperative progression of PNETs.

Pigmented medulloepithelioma of the optic nerve: A challenging diagnostic entity.

Because of its rarity, the diagnosis of optic nerve medulloepithelioma poses a real diagnostic challenge. Medulloepithelioma is a congenital tumor that derives from the primitive medullary epithelium present in the neural tube and the optic vesicle. Its classical location is the ciliary body. Cases of retinal or optic nerve locations have been rarely reported in the literature. Only 11 cases have been published in the English literature. Herein, we report the case of a 2-year-old boy who underwent enucleation of the right eye for a presumed diagnosis of right-eye retinoblastoma, based on the presence of leukocoria on ophthalmological examination. Pathological examination showed an optic nerve medulloepithelioma. A review of the literature is also discussed in our work.

Epidemiology and economic burden of Von Hippel-Lindau Disease-associated central nervous system hemangioblastomas and pancreatic neuroendocrine tumors in the United States.

BACKGROUND: To date, real-world evidence around the clinical and economic burden related to von Hippel-Lindau (VHL) disease is limited. Therefore, this study characterized the prevalence, healthcare resource utilization (HRU), and economic burden of von Hippel-Lindau-associated central nervous system hemangioblastoma (VHL-CNS-Hb) and pancreatic neuroendocrine tumors (VHL-pNET) in the United States (US). METHODS: Patients with VHL-CNS-Hb or VHL-pNET were identified from Optum's de-identified Clinformatics® Data Mart Database (2007-2020) and matched 1:5 to control patients without VHL disease or CNS-Hb/pNET. Prevalence rates of VHL-CNS-Hb and VHL-pNET (standardized by age and sex) in 2019 were estimated. HRU and healthcare costs (2020 US dollars) were compared between the VHL-CNS-Hb/VHL-pNET and control cohorts. RESULTS: In 2019, US prevalence rates of VHL-CNS-Hb and VHL-pNET were estimated to be 1.12 cases per 100,000 (3,678 patients) and 0.12 cases per 100,000 (389 patients), respectively. Patients with VHL-CNS-Hb (N = 220) had more inpatient, outpatient, and emergency department visits and $49,645 higher annual healthcare costs than controls (N = 1,100). Patients with VHL-pNET (N = 20) had more inpatient and outpatient visits and $56,580 higher annual healthcare costs than controls (N = 100). Costs associated with surgical removal of CNS-Hb and pNET were particularly high. CONCLUSIONS: In this retrospective, claims-based study, both VHL-CNS-Hb and VHL-pNET were associated with substantial HRU and healthcare costs, particularly tumor reduction surgery-related costs. These findings provide important insight for healthcare payers regarding the expected real-world costs that enrollees with VHL-CNS-Hb and VHL-pNET may incur over the course of their disease.

Efficacy and safety of temozolomide-based regimens in advanced pancreatic neuroendocrine tumors: a systematic review and meta-analysis.

BACKGROUND: Recent advances in the management of pancreatic neuroendocrine tumors (pNETs) highlight the potential benefits of temozolomide, an alkylating agent, for these patients. In this meta-analysis, we aimed to assess the outcome of temozolomide, alone or in combination with other anticancer medications in patients with advanced pNET. METHODS: Online databases of PubMed, Web of Science, Embase, the Cochrane Library, and ClinicalTrials.gov were searched systematically for clinical trials that reported the efficacy and safety of temozolomide in patients with advanced pNET. Random-effect model was utilized to estimate pooled rates of outcomes based on Response Evaluation Criteria in Solid Tumors criteria, biochemical response, and adverse events (AEs). RESULTS: A total of 14 studies, providing details of 441 individuals with advanced pNET, were included. The quantitative analyses showed a pooled objective response rate (ORR) of 41.2% (95% confidence interval, CI, of 32.4%-50.6%), disease control rate (DCR) of 85.3% (95% CI of 74.9%-91.9%), and a more than 50% decrease from baseline chromogranin A levels of 44.9% (95% CI of 31.6%-49.0%). Regarding safety, the results showed that the pooled rates of nonserious AEs and serious AEs were 93.8% (95% CI of 88.3%-96.8%) and 23.7% (95% CI of 12.0%-41.5%), respectively. The main severe AEs encompassed hematological toxicities. CONCLUSIONS: In conclusion, our meta-analysis suggests that treatment with temozolomide, either as a monotherapy or in combination with other anticancer treatments might be an effective and relatively safe option for patients with advanced locally unresectable and metastatic pNET. However, additional clinical trials are required to further strengthen these findings. This study has been registered in PROSPERO (CRD42023409280).

Unraveling the impact of cancer-associated fibroblasts on hypovascular pancreatic neuroendocrine tumors.

BACKGROUND: Pancreatic neuroendocrine tumors (PNETs) with low microvessel density and fibrosis often exhibit clinical aggressiveness. Given the contribution of cancer-associated fibroblasts (CAFs) to the hypovascular fibrotic stroma in pancreatic ductal adenocarcinoma, investigating whether CAFs play a similar role in PNETs becomes imperative. In this study, we investigated the involvement of CAFs in PNETs and their effects on clinical outcomes. METHODS: We examined 79 clinical PNET specimens to evaluate the number and spatial distribution of α-smooth muscle actin (SMA)-positive cells, which are indicative of CAFs. Then, the findings were correlated with clinical outcomes. In vitro and in vivo experiments were conducted to assess the effects of CAFs (isolated from clinical specimens) on PNET metastasis and growth. Additionally, the role of the stromal-cell-derived factor 1 (SDF1)-AGR2 axis in mediating communication between CAFs and PNET cells was investigated. RESULTS: αSMA-positive and platelet-derived growth factor-α-positive CAFs were detected in the hypovascular stroma of PNET specimens. A higher abundance of α-SMA-positive CAFs within the PNET stroma was significantly associated with a higher level of clinical aggressiveness. Notably, conditioned medium from PNET cells induced an inflammatory phenotype in isolated CAFs. These CAFs promoted PNET growth and metastasis. Mechanistically, PNET cells secreted interleukin-1, which induced the secretion of SDF1 from CAFs. This cascade subsequently elevated AGR2 expression in PNETs, thereby promoting tumor growth and metastasis. The downregulation of AGR2 in PNET cells effectively suppressed the CAF-mediated promotion of PNET growth and metastasis. CONCLUSION: CAFs drive the growth and metastasis of aggressive PNETs. The CXCR4-SDF1 axis may be a target for antistromal therapy in the treatment of PNET. This study clarifies mechanisms underlying PNET aggressiveness and may guide future therapeutic interventions targeting the tumor microenvironment.

Pseudo-medical image-guided technology based on 'CBCT-only' mode in esophageal cancer radiotherapy.

Purpose To minimize the various errors introduced by image-guided radiotherapy (IGRT) in the application of esophageal cancer treatment, this study proposes a novel technique based on the 'CBCT-only' mode of pseudo-medical image guidance. Methods The framework of this technology consists of two pseudo-medical image synthesis models in the CBCT→CT and the CT→PET direction. The former utilizes a dual-domain parallel deep learning model called AWM-PNet, which incorporates attention waning mechanisms. This model effectively suppresses artifacts in CBCT images in both the sinogram and spatial domains while efficiently capturing important image features and contextual information. The latter leverages tumor location and shape information provided by clinical experts. It introduces a PRAM-GAN model based on a prior region aware mechanism to establish a non-linear mapping relationship between CT and PET image domains.  As a result, it enables the generation of pseudo-PET images that meet the clinical requirements for radiotherapy. Results The NRMSE and multi-scale SSIM (MS-SSIM) were utilized to evaluate the test set, and the results were presented as median values with lower quartile and upper quartile ranges. For the AWM-PNet model, the NRMSE and MS-SSIM values were 0.0218 (0.0143, 0.0255) and 0.9325 (0.9141, 0.9410), respectively. The PRAM-GAN model produced NRMSE and MS-SSIM values of 0.0404 (0.0356, 0.0476) and 0.9154 (0.8971, 0.9294), respectively. Statistical analysis revealed significant differences (p < 0.05) between these models and others. The numerical results of dose metrics, including D98 %, Dmean, and D2 %, validated the accuracy of HU values in the pseudo-CT images synthesized by the AWM-PNet. Furthermore, the Dice coefficient results confirmed statistically significant differences (p < 0.05) in GTV delineation between the pseudo-PET images synthesized using the PRAM-GAN model and other compared methods. Conclusion The AWM-PNet and PRAM-GAN models have the capability to generate accurate pseudo-CT and pseudo-PET images, respectively. The pseudo-image-guided technique based on the 'CBCT-only' mode shows promising prospects for application in esophageal cancer radiotherapy.

Pancreatic Neuroendocrine Tumors: Signaling Pathways and Epigenetic Regulation.

Pancreatic neuroendocrine tumors (PNETs) are characterized by dysregulated signaling pathways that are crucial for tumor formation and progression. The efficacy of traditional therapies is limited, particularly in the treatment of PNETs at an advanced stage. Epigenetic alterations profoundly impact the activity of signaling pathways in cancer development, offering potential opportunities for drug development. There is currently a lack of extensive research on epigenetic regulation in PNETs. To fill this gap, we first summarize major signaling events that are involved in PNET development. Then, we discuss the epigenetic regulation of these signaling pathways in the context of both PNETs and commonly occurring-and therefore more extensively studied-malignancies. Finally, we will offer a perspective on the future research direction of the PNET epigenome and its potential applications in patient care.

A nomogram to preoperatively predict the aggressiveness of non-functional pancreatic neuroendocrine tumors based on CT features.

OBJECTIVES: To develop a nomogram to predict the aggressiveness of non-functional pancreatic neuroendocrine tumors (NF-pNETs) based on preoperative computed tomography (CT) features. METHODS: This study included 176 patients undergoing radical resection for NF-pNETs. These patients were randomly divided into the training (n = 123) and validation sets (n = 53). A nomogram was developed based on preoperative predictors of aggressiveness of the NF-pNETs which were identified by univariable and multivariable logistic regression analysis. The aggressiveness of NF-pNETs was defined as a composite measure including G3 grading, N+, distant metastases, and/ or disease recurrence. RESULTS: Altogether, the number of patients with highly aggressive NF-pNETs was 37 (30.08 %) and 15 (28.30 %) in the training and validation sets, respectively. Multivariable logistic regression analysis identified that tumor size, biliopancreatic duct dilatation, lymphadenopathy, and enhancement pattern were preoperative predictors of aggressiveness. Those variables were used to develop a nomogram with good concordance statistics of 0.89 and 0.86 for predicting aggressiveness in the training and validation sets, respectively. With a nomogram score of 59, patients with NF-pNETs were divided into low-aggressive and high-aggressive groups. The high-aggressive group had decreased overall survival (OS) and disease-free survival (DFS). Moreover, the nomogram showed good performance in predicting OS and DFS at 3, 5, and 10 years. CONCLUSION: The nomogram integrating CT features helped preoperatively predict the aggressiveness of NF-pNETs and could potentially facilitate clinical decision-making.

Patient Priorities Concerning Treatment Decisions for Advanced Neuroendocrine Tumors Identified by Discrete Choice Experiments.

BACKGROUND: Patients with advanced neuroendocrine tumors (NETs) have multiple treatment options. Ideally, treatment decisions are shared between physician and patient; however, previous studies suggest that oncologists and patients place different value on treatment attributes such as adverse event (AE) rates. High-quality information on NET patient treatment preferences may facilitate patient-centered decision making by helping clinicians understand patient priorities. METHODS: This study used 2 discrete choice experiments (DCE) to elicit preferences of NET patients regarding advanced midgut and pancreatic NET (pNET) treatments. The DCEs used the "potentially all pairwise rankings of all possible alternatives" (PAPRIKA) method. The primary objective was to determine relative utility rankings for treatment attributes, including progression-free survival (PFS), treatment modality, and AE rates. Ranking of attribute profiles matching specific treatments was also determined. Levels for treatment attributes were obtained from randomized clinical trial data of NET treatments. RESULTS: One hundred and 10 participants completed the midgut NET DCE, and 132 completed the pNET DCE. Longer PFS was the highest ranked treatment attribute in 64.5% of participants in the midgut NET DCE, and in 59% in the pNET DCE. Approximately, 40% of participants in both scenarios prioritized lower AE rates or less invasive treatment modalities over PFS. Ranking of treatment profiles in the midgut NET scenario identified 60.9% of participants favoring peptide receptor radionuclide therapy (PRRT), and 30.0% somatostatin analogue dose escalation. CONCLUSION: NET patients have heterogeneous priorities when choosing between treatment options based on the results of 2 independent DCEs. These results highlight the importance of shared decision making for NET patients.

Radiomics analysis from magnetic resonance imaging in predicting the grade of nonfunctioning pancreatic neuroendocrine tumors: a multicenter study.

OBJECTIVES: To explore the potential of radiomics features to predict the histologic grade of nonfunctioning pancreatic neuroendocrine tumor (NF-PNET) patients using non-contrast sequence based on MRI. METHODS: Two hundred twenty-eight patients with NF-PNETs undergoing MRI at 5 centers were retrospectively analyzed. Data from center 1 (n = 115) constituted the training cohort, and data from centers 2-5 (n = 113) constituted the testing cohort. Radiomics features were extracted from T2-weighted images and the apparent diffusion coefficient. The least absolute shrinkage and selection operator was applied to select the most important features and to develop radiomics signatures. The area under receiver operating characteristic curve (AUC) was performed to assess models. RESULTS: Tumor boundary, enhancement homogeneity, and vascular invasion were used to construct the radiological model to stratify NF-PNET patients into grade 1 and 2/3 groups, which yielded AUC of 0.884 and 0.684 in the training and testing groups. A radiomics model including 4 features was constructed, with an AUC of 0.941 and 0.871 in the training and testing cohorts. The fusion model combining the radiomics signature and radiological characteristics showed good performance in the training set (AUC = 0.956) and in the testing set (AUC = 0.864), respectively. CONCLUSION: The developed model that integrates radiomics features with radiological characteristics could be used as a non-invasive, dependable, and accurate tool for the preoperative prediction of grade in NF-PNETs. CLINICAL RELEVANCE STATEMENT: Our study revealed that the fusion model based on a non-contrast MR sequence can be used to predict the histologic grade before operation. The radiomics model may be a new and effective biological marker in NF-PNETs. KEY POINTS: The diagnostic performance of the radiomics model and fusion model was better than that of the model based on clinical information and radiological features in predicting grade 1 and 2/3 of nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs). Good performance of the model in the four external testing cohorts indicated that the radiomics model and fusion model for predicting the grades of NF-PNETs were robust and reliable, indicating the two models could be used in the clinical setting and facilitate the surgeons' decision on risk stratification. The radiomics features were selected from non-contrast T2-weighted images (T2WI) and diffusion-weighted imaging (DWI) sequence, which means that the administration of contrast agent was not needed in grading the NF-PNETs.

Accurate non-invasive grading of nonfunctional pancreatic neuroendocrine tumors with a CT derived radiomics signature.

PURPOSE: The purpose of this study was to develop a radiomics-signature using computed tomography (CT) data for the preoperative prediction of grade of nonfunctional pancreatic neuroendocrine tumors (NF-PNETs). MATERIALS AND METHODS: A retrospective study was performed on patients undergoing resection for NF-PNETs between 2010 and 2019. A total of 2436 radiomic features were extracted from arterial and venous phases of pancreas-protocol CT examinations. Radiomic features that were associated with final pathologic grade observed in the surgical specimens were subjected to joint mutual information maximization for hierarchical feature selection and the development of the radiomic-signature. Youden-index was used to identify optimal cutoff for determining tumor grade. A random forest prediction model was trained and validated internally. The performance of this tool in predicting tumor grade was compared to that of EUS-FNA sampling that was used as the standard of reference. RESULTS: A total of 270 patients were included and a fusion radiomic-signature based on 10 selected features was developed using the development cohort (n = 201). There were 149 men and 121 women with a mean age of 59.4 ± 12.3 (standard deviation) years (range: 23.3-85.0 years). Upon internal validation in a new set of 69 patients, a strong discrimination was observed with an area under the curve (AUC) of 0.80 (95% confidence interval [CI]: 0.71-0.90) with corresponding sensitivity and specificity of 87.5% (95% CI: 79.7-95.3) and 73.3% (95% CI: 62.9-83.8) respectively. Of the study population, 143 patients (52.9%) underwent EUS-FNA. Biopsies were non-diagnostic in 26 patients (18.2%) and could not be graded due to insufficient sample in 42 patients (29.4%). In the cohort of 75 patients (52.4%) in whom biopsies were graded the radiomic-signature demonstrated not different AUC as compared to EUS-FNA (AUC: 0.69 vs. 0.67; P = 0.723), however greater sensitivity (i.e., ability to accurately identify G2/3 lesion was observed (80.8% vs. 42.3%; P < 0.001). CONCLUSION: Non-invasive assessment of tumor grade in patients with PNETs using the proposed radiomic-signature demonstrated high accuracy. Prospective validation and optimization could overcome the commonly experienced diagnostic uncertainty in the assessment of tumor grade in patients with PNETs and could facilitate clinical decision-making.

Preoperative prediction of pancreatic neuroendocrine tumor grade based on 68Ga-DOTATATE PET/CT.

OBJECTIVE: To establish a prediction model for preoperatively predicting grade 1 and grade 2/3 tumors in patients with pancreatic neuroendocrine tumors (PNETs) based on 68Ga-DOTATATE PET/CT. METHODS: Clinical data of 41 patients with PNETs were included in this study. According to the pathological results, they were divided into grade 1 and grade 2/3. 68Ga-DOTATATE PET/CT images were collected within one month before surgery. The clinical risk factors and significant radiological features were filtered, and a clinical predictive model based on these clinical and radiological features was established. 3D slicer was used to extracted 107 radiomic features from the region of interest (ROI) of 68Ga-dotata PET/CT images. The Pearson correlation coefficient (PCC), recursive feature elimination (REF) based five-fold cross validation were adopted for the radiomic feature selection, and a radiomic score was computed subsequently. The comprehensive model combining the clinical risk factors and the rad-score was established as well as the nomogram. The performance of above clinical model and comprehensive model were evaluated and compared. RESULTS: Adjacent organ invasion, N staging, and M staging were the risk factors for PNET grading (p < 0.05). 12 optimal radiomic features (3 PET radiomic features, 9 CT radiomic features) were screen out. The clinical predictive model achieved an area under the curve (AUC) of 0.785. The comprehensive model has better predictive performance (AUC = 0.953). CONCLUSION: We proposed a comprehensive nomogram model based on 68Ga-DOTATATE PET/CT to predict grade 1 and grade 2/3 of PNETs and assist personalized clinical diagnosis and treatment plans for patients with PNETs.