Enter the matrix: On how to improve thyroid nodule management using 3D ultrasound

Roughly two-thirds of the adult population has a thyroid nodule, of which 90% are benign. Of the adults that have a nodule, approximately 5% will experience symptoms that include a feeling of a marble stuck in the throat, difficulty swallowing and breathing, and cosmetic complaints.

Thyroid nodule management primarily makes use of ultrasound as the imaging modality for diagnosis, image guidance during therapy (radiofrequency ablation i.e. RFA), and follow-up. Although ultrasound is relatively easy to apply, it is hard to standardize for repeated measurements and across various users. Further, RFA can benefit from 3D imaging information and a planning and navigation system to improve clinical outcome. These challenges may be overcome by using 3D ultrasound.

In this thesis, two phantoms were created on which these methods can be developed. Further, it offers insight into the use of 2D and 3D ultrasound for thyroid nodule management.

To assess the impact of changes to an intervention, a baseline was determined of the effectiveness of RFA in Dutch hospitals
Using a simple phantom, we have shown that utilizing a volume-based measurement technique, that the matrix transducer offers, results in improved measurement accuracy.

The more complex, anthropomorphic, phantom serves as a platform on which thermal treatments, such as RFA, can be improved. Using this phantom, we have shown that the impact of 2D and 3D ultrasound on RFA efficacy does not differ from one another; however, the matrix transducer might be more user-friendly for needle placement due to the dual-plane imaging. An additional use case for these phantoms is their capacity to compare dominant and non-dominant hand ablations, as well as serve as a training platform. Additional research is required that employs more operators to find stronger evidence supporting a difference between the ablating hands and the difference in effect of 2D and 3D ultrasound guidance.

To make full use of 3D ultrasound, stitching algorithms should be integrated into the ultrasound systems to acquire larger volumes. These can then be processed by deep-learning algorithms for use in computer-aided diagnosis and intervention systems. To further improve the applicability of 3D ultrasound in the clinic, integrating analysis methods such as 3D elastography and 3D Doppler is suggested.