INTERVENTIONAL DIAGNOSTIC METHODS IN MAMMOLOGY

Vollständiger Abstract

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Interventional diagnostic methods in mammology represent a group of minimally invasive procedures performed under imaging guidance to obtain cellular or tissue samples for the morphological verification of breast lesions. The relevance of this topic is обусловлена the high global prevalence of breast cancer and the need for timely and accurate diagnosis to determine the optimal treatment strategy. The aim of this review is to analyze contemporary domestic and international studies focused on interventional diagnostic methods in mammology, as well as to assess their diagnostic effectiveness and safety profile. Materials and methods included an analysis of publications from scientific databases such as PubMed, eLibrary, and CyberLeninka over recent years. The review incorporates original clinical studies, randomized controlled trials, systematic reviews, and meta-analyses. The results indicate that core needle biopsy is considered the “gold standard” for preoperative morphological verification of breast lesions due to its high sensitivity and specificity, reaching 95–98%. Vacuum-assisted biopsy allows for the collection of a larger volume of tissue and demonstrates high diagnostic accuracy, particularly in cases involving microcalcifications and high-risk lesions. MRI-guided biopsy is used for lesions visualized exclusively by magnetic resonance imaging and is characterized by high technical success rates and a low false-negative rate. The safety profile of interventional methods is generally favorable. The most common complications include minor bleeding and hematoma formation, whereas severe complications are extremely rare. Pain is typically mild to moderate and depends on the technique used and individual patient characteristics. Thus, interventional diagnostic methods in mammology are highly effective and safe tools that play a key role in the modern diagnosis of breast diseases. At the same time, further standardization of approaches and multicenter studies are required to optimize diagnostic algorithms.