CT-augmented digital tomosynthesis image reconstruction in image-guided bronchoscopy interventions.

Area of Science:

• Medical Imaging
• Radiology
• Pulmonology

Background:

• Transbronchial needle biopsy is vital for lung cancer diagnosis but requires precise localization.
• Digital tomosynthesis (DTS) is a promising, low-dose imaging tool for guiding bronchoscopy.
• Current DTS image quality is limited by narrow-angle acquisition, hindering accurate guidance.

Purpose of the Study:

• To enhance intraoperative DTS image quality by leveraging preoperative computed tomography (CT) scans.
• To address differences in patient positioning and motion between CT and DTS for improved image registration.
• To utilize high-resolution CT data as prior knowledge to augment DTS image reconstruction.

Main Methods:

• A prior-aided DTS image reconstruction technique was developed, incorporating deformable CT-to-DTS registration.
• Prior CT images were registered to intermediate DTS images reconstructed via algebraic reconstruction technique (ART).
• DTS images were re-reconstructed using ART with the registered CT image as an initial estimate.

Main Results:

• The prior-aided method demonstrated significant improvements in DTS image quality over standard ART reconstruction.
• Evaluations on phantoms and patient data showed enhanced image quality, confirmed by visual inspection and quantitative correlation (Pearson's correlation).
• Average PC coefficients improved substantially with the prior-aided method compared to zero-initialized ART.

Conclusions:

• Initial estimation is critical for DTS image reconstruction quality.
• Integrating prior CT images into intraoperative DTS significantly enhances image quality.
• CT-augmented DTS presents a viable, lower-radiation alternative to CBCT for bronchoscopy guidance, warranting further clinical validation.