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Mysterious neuroendocrine tumors: Why are they so difficult to diagnose?
Neuroendocrine tumors (NETs) are tumors that originate from cells of the endocrine and nervous systems. These tumors most commonly occur in the intestine, particularly those called carcinoid tumors, but they can also occur in the pancreas, lungs, and other parts of the body.
NETs are broadly classified clinically, and despite their heterogeneous origins, more and more medical experts now view them as a group of tissues with common characteristics. These features include a similar histologic appearance, distinctive secretory granules, and often the secretion of biogenic amines and polypeptide hormones.
According to the World Health Organization (WHO) classification, neuroendocrine tumors can be divided into three categories, with emphasis placed on the grade of the tumor rather than its anatomical location. The three categories are: well-differentiated tumors of benign and indeterminate behavior, well-differentiated neuroendocrine carcinomas of low malignant behavior, and poorly differentiated neuroendocrine carcinomas of high malignant behavior.
The basis for determining the tumor type includes histological characteristics, such as size, lymphovascular invasion, mitotic number, Ki-67 labeling index, etc.
The grading system for NETs is based on the assessment of proliferation and categorizes tumors into grade 1 (low grade), grade 2 (intermediate grade), and grade 3 (high grade). However, tumor necrosis is not always included in the rating of certain tumor types, which may lead to certain difficulties in judgment.
Why is it so difficult to diagnose these tumors?
The atypical presentation and cryptic nature of NETs pose challenges in the diagnosis of NETs. Many patients may have no obvious symptoms even after the tumor has spread, or it may only be discovered accidentally during an unexpected surgery. This often makes it difficult for clinicians to distinguish it from other diseases during the initial evaluation stage.
According to one study, one in ten patients was found to have a carcinoid tumor.
This type of tumor secretes a variety of biogenic amines and hormones, which can lead to a series of clinical symptoms, one of which is the carcinoid syndrome mentioned in this article. Although these symptoms can be distressing to patients, they are often ignored in the early stages or even misdiagnosed as other diseases.
Common diagnostic methods
The diagnosis of NETs relies in part on hormones secreted by the tumor cells. However, the secretory activity and corresponding tissue immune response of each type of tumor may not be consistent, so specific markers are needed for diagnosis.
Imaging tests such as CT, MRI and ultrasound play a key role in the detection of tumors. To obtain an accurate diagnosis, these imaging methods require multiphase scanning with the aid of contrast agents.
Furthermore, molecular imaging has also become a good aid in diagnosis, especially for neuroendocrine tumors.
Recent studies have shown that the use of potassium strontium PET scans can improve diagnostic accuracy, compared to traditional drug sketches which often render poor images. This new technology marks a major advance in tumor detection, however, obtaining the correct tissue examination results remains one of the biggest challenges in the current diagnostic process.
Future Prospects and Challenges
As research on neuroendocrine tumors progresses, we understand that different tumors share common features such as secretory diversity and composition, which can provide new ideas for future diagnostic and treatment strategies. However, how to effectively apply these new advances in clinical practice remains an issue that the medical community needs to explore in depth.
With the advancement of technology, the diagnosis of neuroendocrine tumors will become more precise and personalized. However, these advances have also triggered thinking about early detection methods, prognosis assessment and personalized treatment. How should future research be carried out around these aspects, and can it have a revolutionary impact in clinical applications?
