Bioacoustics response of small benign or malignant nodules

Area of Science:

• Biomedical Engineering
• Acoustic Physics
• Medical Diagnostics

Background:

• Distinguishing between benign and malignant tissues is crucial for accurate medical diagnosis.
• Tissue surface texture (smooth vs. rough) is an important indicator of malignancy.
• Current medical imaging techniques have limitations in evaluating the surface characteristics of small nodules.

Purpose of the Study:

• To present a new method for the early diagnosis of thyroid cancer.
• To utilize acoustic resonance frequencies to differentiate between benign and malignant thyroid nodules.
• To assess the surface characteristics (smooth or rough) of small 3D tissue samples.

Main Methods:

• Modeling sound propagation through human tissue using classical partial differential equations.
• Applying Neumann or Dirichlet boundary conditions to simulate tissue interactions.
• Analyzing acoustic eigenfrequencies (sound resonance frequencies) of spherical and elliptical nodules with varying surface roughness.

Main Results:

• A small number of acoustic eigenfrequency assessments (around ten) are sufficient for classification.
• The method can accurately determine if a nodule's surface is smooth or rough.
• This technique enables the evaluation of 3D bodies smaller than 5 mm, surpassing the resolution limits of ultrasound and CT scans for surface analysis.

Conclusions:

• Acoustic resonance frequency analysis offers a promising approach for early thyroid cancer detection.
• This method effectively characterizes nodule surface texture, aiding in the differentiation of benign from malignant tissues.
• The technique provides a valuable tool for analyzing micro-scale tissue structures beyond the capabilities of conventional imaging devices.