Detecting pulmonary nodules by using ultrasound multiple scattering.

Area of Science:

• Medical Imaging
• Pulmonary Medicine
• Biomedical Engineering

Background:

• X-ray Computed Tomography (CT) is standard for pulmonary nodule detection but unsuitable for intraoperative use.
• Lung ultrasound imaging is hindered by severe multiple scattering from lung parenchyma.
• Pulmonary nodules present as homogeneous regions distinct from the highly scattering lung tissue.

Purpose of the Study:

• To develop and validate a real-time, non-ionizing ultrasound technique for intraoperative pulmonary nodule localization.
• To exploit ultrasound multiple scattering properties for improved nodule detection in the lung.
• To enable precise resection margins during lung surgeries via accurate nodule identification.

Main Methods:

• Acquisition of impulse response matrices using a linear array transducer in ex-vivo animal lungs.
• Utilizing singular-value decomposition to extract multiple scattering contributions.
• Employing a depression detection algorithm to identify regions with reduced scattering, indicative of nodules.

Main Results:

• Successful detection and localization of pulmonary nodules using the developed ultrasound scattering mapping method.
• Ninety-five percent of artificial nodules (20 total) were detected in five ex-vivo lungs.
• Significant correlations found between ultrasound-estimated and CT-estimated nodule depth (R=0.960) and diameter (R=0.563).

Conclusions:

• The proposed ultrasound-based method effectively detects and localizes pulmonary nodules in ex-vivo lungs.
• This technique offers a promising real-time, non-ionizing alternative for intraoperative nodule identification.
• The findings support the potential for improved surgical safety and efficacy in lung nodule resection.