Diagnostics: Bethesda classification system for assessing cancer risk of a thyroid nodule by fine needle biopsy

 

What is The Bethesda system?

The Bethesda classification system is a standardized system used to categorize the results of fine needle aspiration (FNA) biopsies of the thyroid gland. Developed in 2007 during a conference at the National Cancer Institute in Bethesda, Maryland, it estimates risk of a thyroid nodule being malignant and is used to make treatment recommendations.

The system categorizes FNA results into six diagnostic categories:

  1. Benign: This category includes samples that are clearly non-cancerous and typically require no further intervention beyond routine monitoring.

  2. Atypia of Undetermined Significance (AUS): Samples in this category show some abnormal cells, but it is unclear whether these indicate a benign or malignant process. Further evaluation or repeat FNA may be recommended.

  3. Follicular Neoplasm / Suspicious for Follicular Neoplasm: This category indicates the presence of follicular cells that may suggest a neoplasm, which could either be benign or malignant. Surgical evaluation is usually warranted for a definitive diagnosis.

  4. Suspicious for Malignancy: This classification suggests a significant concern for thyroid cancer, though it is not definitive. Patients typically undergo surgical intervention for further assessment.

  5. Malignant: This category is reserved for samples that clearly exhibit cancerous cells. Immediate management typically includes surgical treatment.

  6. Non-diagnostic/Unsatisfactory: Samples in this category are inadequate for evaluation and may require repeat FNA or different diagnostic approaches. A Bethesda category 6, Non-diagnostic score does not indicate the likelihood of cancer—it only indicates that no information is available from the fine needle biopsy.

The Bethesda classification system enhances the management of thyroid nodules by providing a framework for assessing the likelihood of cancer and guiding clinical decision-making. It aids in stratifying the risk, which facilitates appropriate surveillance or treatment strategies for patients.