Abstract
Pancreatic neuroendocrine neoplasms (panNENs) are heterogeneous neoplasms with neuroendocrine differentiation that show peculiar clinical and histomorphological features, with variable prognosis. In recent years, advances in knowledge regarding the pathophysiology and heterogeneous clinical presentation, as well as the availability of different diagnostic procedures for panNEN diagnosis and novel therapeutic options for patient clinical management, has led to the recognition of the need for an active multidisciplinary discussion for optimal patient care. Molecular imaging with positron emission tomography/computed tomography (PET/CT) has become indispensable for the management of panNENs. Several PET radiopharmaceuticals can be used to characterize either panNEN receptor expression or metabolism. The aim of this review is to offer an overview of all the currently used radiopharmaceuticals and of the new upcoming tracers for pancreatic neuroendocrine tumors (panNETs), and their clinical impact on therapy management. [68Ga]Ga-DOTA-peptide PET/CT (SSA-PET/CT) has high sensitivity, specificity, and accuracy and is recommended for the staging and restaging of any non-insulinoma well-differentiated panNEN cases to carry out detection of unknown primary tumor sites or early relapse and for evaluation of in vivo somatostatin receptors expression (SRE) to select patient candidates for peptide receptor radiometabolic treatment (PRRT) with 90Y or 177Lu and/or cold analogs. SSA-PET/CT also has a strong impact on clinical management, leading to a change in treatment in approximately a third of the cases. Its role for treatment response assessment is still under debate due to the lack of standardized criteria, even though some semiquantitative parameters seem to be able to predict response. [18F]FDG PET/CT generally shows low sensitivity in small growing and well-differentiated neuroendocrine tumors (NET; G1 and G2), while it is of utmost importance in the evaluation and management of high-grade NENs and also provides important prognostic information. When positive, [18F]FDG PET/CT impacts therapeutical management, indicating the need for a more aggressive treatment regime. Although FDG positivity does not exclude the patient from PRRT, several studies have demonstrated that it is certainly useful to predict response, even in this setting. The role of [18F]FDOPA for the study of panNET is limited by physiological uptake in the pancreas and is therefore not recommended. Moreover, it provides no information on SRE that has crucial clinical management relevance. Early acquisition of the abdomen and premedication with carbidopa may be useful to increase the accuracy, but further studies are needed to clarify its utility. GLP-1R agonists, such as exendin-4, are particularly useful for benign insulinoma detection, but their accuracy decreases in the case of malignant insulinomas. Being a whole-body imaging technique, exendin-PET/CT gives important preoperative information on tumor size and localization, which is fundamental for surgical planning as resection (enucleation of the lesion or partial pancreatic resection) is the only curative treatment. New upcoming tracers are under study, such as promising SSTR antagonists, which show a favorable biodistribution and higher tumor-to-background ratio that increases tumor detection, especially in the liver. [68Ga]pentixafor, an in vivo marker of CXCR4 expression associated with the behavior of more aggressive tumors, seems to only play a limited role in detecting well-differentiated NET since there is an inverse expression of SSTR2 and CXCR4 in G1 to G3 NETs with an elevation in CXCR4 and a decrease in SSTR2 expression with increasing grade. Other tracers, such as [68Ga]Ga-PSMA, [68Ga]Ga-DATA-TOC, [18F]SiTATE, and [18F]AlF-OC, are also under investigation.
Highlights
Pancreatic neuroendocrine neoplasms are heterogeneous neoplasms with neuroendocrine differentiation that show peculiar clinical and histomorphological features, with variable prognosis
The most recent WHO 2019 classification introduced a new distinction for neuroendocrine neoplasms with Ki-67 > 20% in two groups, well-differentiated pancreatic neuroendocrine tumors (panNETs) grade 3 and poorly differentiated small and large-cell type pancreatic neuroendocrine carcinomas (panNECs), based on the morphologic characteristics [4,5]. Pancreatic neuroendocrine neoplasms (panNENs) account for 5% of all pancreatic tumors, but their incidence is on the rise, most likely due to a combination of increased clinical awareness, more accurate and rapidly evolving diagnostic procedures, and increased incidental findings [6]
The current review offers an overview of all the currently-used radiopharmaceuticals and of new upcoming tracers for panNENs and their clinical impact on therapy management
Summary
Pancreatic neuroendocrine neoplasms (panNENs) are heterogeneous neoplasms with neuroendocrine differentiation that show peculiar clinical and histomorphological features, with variable prognosis. The association of these two tracers is often performed, with high regional and national differences, in patients affected by intermediate or high-grade panNETs in different scenarios: at initial diagnosis, when the SSA-PET shows a heterogeneous SSTR expression among different tumor lesions or within the same lesion, in case of a discrepancy between conventional radiological imaging and SSA-PET at the diagnosis or during therapy (earlier identifying the non-responders) and before starting a new line of therapy, such as PRRT [75] (Figure 2). Patient oral carbidopa was administered before PET, and image acquisition consisted of an early scan centered over the pancreas (5 min after [18F]FDOPA injection, field of view including the upper abdomen), and a delayed whole-body acquisition, starting 20–30 min later Using this approach, [18F]FDOPA localized insulinoma in 21 of the 25 studies, leading to a primary lesion detection rate of 84%. Further studies are necessary to clarify if [18F]FDOPA PET/CT, with or without carbidopa premedication, may have a role in insulinoma detection
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