Improvements and future perspective in diagnostic tools for neuroendocrine neoplasms

ABSTRACT

Introduction

Neuroendocrine neoplasms (NENs) represent a complex group of tumors arising from neuroendocrine cells, characterized by heterogeneous behavior and challenging diagnostics. Despite advancements in medical technology, NENs present a major challenge in early detection, often leading to delayed diagnosis and variable outcomes. This review aims to provide an in-depth analysis of current diagnostic methods as well as the evolving and future directions of diagnostic strategies for NENs.

Area covered

The review extensively covers the evolution of diagnostic tools for NENs, from traditional imaging and biochemical tests to advanced genomic profiling and next-generation sequencing. The emerging role of technologies such as artificial intelligence, machine learning, and liquid biopsies could improve diagnostic precision, as could the integration of imaging modalities such as positron emission tomography (PET)/magnetic resonance imaging (MRI) hybrids and innovative radiotracers.

Expert opinion

Despite progress, there is still a significant gap in the early diagnosis of NENs. Bridging this diagnostic gap and integrating advanced technologies and precision medicine are crucial to improving patient outcomes. However, challenges such as low clinical awareness, limited possibility of noninvasive diagnostic tools and funding limitations for rare diseases like NENs are acknowledged.

KEYWORDS:

• Diagnosis
• genomics
• liquid biopsy
• neuroendocrine neoplasms
• nuclear medicine
• proteomics
• radiomics

Article highlights

• Neuroendocrine neoplasms (NENs) still present challenges in diagnosis and treatment, even with considerable progress in medical technology. However, technological innovations have not yet significantly reduced the diagnostic delay in NENs, affecting mortality improvement despite advanced treatments.

• Improved clinical awareness and the integration of advanced diagnostic techniques are key to overcoming current challenges in NEN management.

• Artificial Intelligence (AI) and Machine Learning (ML) are expected to revolutionize NENs diagnostics by enabling more accuracy in radiologic, endoscopic and nuclear medicine techniques.

• Tailored medicine, rooted in a deep understanding of NENs’ molecular and genetic aspects, is essential for developing effective treatment strategies.

• Liquid biopsies, particularly through analyzing circulating tumor cells (CTCs), RNA transcripts and circulating tumor DNA (ctDNA), offer a promising noninvasive method for monitoring disease progression and treatment response.

• The rarity of NENs presents a significant challenge in securing funding for research and development of advanced diagnostic tools and treatments.

• The advancement in NENs diagnostics and treatments poses new challenges that require careful navigation to optimize patient outcomes.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.