Integrating Robotic Bilateral Axillo-Breast Approach Thyroidectomy with Molecular Diagnostics and Artificial Intelligence in Thyroid Cancer Care

Abstract

Thyroid cancer is one of the most prevalent cancers in the world, accounting for the increased sensitivity of diagnostic assessments, the environment, and extensive imaging. While open thyroidectomy still forms the base surgical treatment of differentiated thyroid carcinoma (DTC), its visible scarring and postoperative morbidity have mandatorily propelled a longitudinal shift to minimally invasive techniques. Robotic thyroidectomy using the bilateral axillo-breast approach (BABA) is an emerging transformative technique that combines robotic precision and visualization with oncologic efficacy and superior cosmetic outcomes to enhance recovery. Molecular diagnostics such as next-generation sequencing (NGS) and microRNA classifiers have transformed preoperative planning. These tools aid in accurate risk stratification, enabling clinicians to determine the course of surgery and avoid overtreatment. Artificial intelligence (AI) enhances precision medicine by improving nodule classification, predicting surgical risks, providing intraoperative navigation guidance, and supporting postoperative histopathological evaluations. Despite these innovations, cost, accessibility, and ethical governance issues highlight persistent challenges. This review consolidates the current state of robotic-assisted surgery for thyroid cancer with molecular profiling and AI. It proposes future aims and strides toward precision surgery that is accessible worldwide.

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