Hashimoto's thyroiditis (HT), the most frequent autoimmune thyroid disorder (AITD), is the leading cause of hypothyroidism in iodine-sufficient areas of the world¹. It is characterized by lymphocytic infiltration and autoantibodies against thyroid antigens, leading to the destruction of thyroid architecture and hypothyroidism². Staging of HT aims to assess the severity and guide treatment decisions. It relies on a combination of biochemical markers such as thyroid stimulating hormone (TSH) and thyroid autoantibodies³, as well as ultrasonographic features visible on thyroid ultrasound⁴^,⁵^,⁶.

On ultrasound examination, HT demonstrates characteristic findings, including diffusely decreased echogenicity, heterogeneous echotexture, micronodularity, and increased blood flow on color Doppler⁶^,⁷. However, conventional two-dimensional (2D) grayscale ultrasound lacks quantitative methods for systematically analyzing these features for HT staging⁸. The assessment of vascularity changes is also limited to qualitative visual inspection in 2D mode. The complex three-dimensional (3D) architecture of the thyroid gland further hampers thorough evaluation using conventional 2D slicing⁹^,¹⁰. These factors lead to imaging blind spots and misinterpretation, resulting in low sensitivity and specificity, especially for less experienced practitioners¹¹^,¹².

Conventional handheld ultrasound scanning integrates real-time acquisition and diagnosis. This coupled workflow reliance increases the likelihood of oversight errors during scanning. The lack of spatial localization and tracking also makes lesion identification and monitoring imprecise¹²^,¹³. Dedicated 3D ultrasound systems have emerged to address these limitations and have shown promising results¹⁴^,¹⁵. However, most 3D ultrasound technologies require complex mechanical scanning mechanisms and specialized transducers, leading to high costs and barriers to adoption.

To overcome the limitations of conventional 2D and 3D ultrasound techniques, this study proposes a novel 3D reconstruction and visualization solution tailored for thyroid examination. Using widely available handheld ultrasound, multiple 2D sweeps are first acquired to scan the entire thyroid gland. 3D volumetric reconstruction is then realized by spatial registration and fusion of the 2D sequences. Concurrently, color Doppler frames are coregistered to create vascularity maps visualizing blood flow changes. The reconstructed 3D grayscale volumes and colored vascularity maps are finally integrated into a single platform, enabling synchronized multi-planar visualization and combined structural-functional inspection.

This proposed 3D fusion technique provides a systematic and comprehensive evaluation of the complex thyroid morphology from different aspects. By minimizing blind spots and enabling global overview, it could help improve diagnostic accuracy and reduce oversight errors, especially benefiting novice practitioners. The multi-modal visualization also facilitates rapid and precise localization of lesions, holding promise for early diagnosis and treatment of thyroid nodules and tumors. Moreover, the method introduces quantitative 3D feature analysis which has not been investigated for HT staging before. With wide adoption, it has the potential to standardize and objectify the currently experience-dependent ultrasound diagnosis procedures. By synergistically integrating handheld 3D reconstruction, multi-modal fusion, quantitative feature analysis, and flexible visualization into a streamlined workflow, this low-cost, easy-to-use technique represents a diagnostically powerful leap from conventional 2D ultrasound for advancing thyroid examination.

Importing and Visualizing 4D B-Mode and Color Doppler Ultrasound Data of Thyroid Morphology in MATLAB