Intrinsic Respiratory Gating for Simultaneous Multi-Mouse μCT Imaging to Assess Liver Tumors

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Oncology

Background:

• Small animal micro computed tomography (μCT) is crucial for quantifying liver and lung tumors, particularly hepatocellular carcinoma (HCC).
• Respiratory motion during μCT scans introduces artifacts, degrading image quality and hindering small tumor detection.
• Current methods for motion correction in high-throughput μCT are often limited by image quality and dose efficiency concerns.

Purpose of the Study:

• To develop and validate an intrinsic respiratory gating method for μCT imaging in mice with HCC.
• To improve image quality and tumor detectability by mitigating respiratory motion artifacts.
• To enable high-throughput scanning of multiple mice without compromising image quality or dose efficiency.

Main Methods:

• Utilized inhalation anesthesia to induce regular respiration patterns in mice, allowing for identification of motion-corrupted projections.
• Developed an automated intrinsic breathing projection selection algorithm, validated against manual selection with 97% accordance.
• Employed iterative reconstruction capable of handling missing projection angles to reconstruct volumetric images.

Main Results:

• The intrinsic gating method significantly reduced hypodense intensity artifacts at the liver edge.
• Improved detectability of small HCC tumors was demonstrated.
• Simultaneous scanning of four mice showed only a marginal increase (7.5%) in discarded projections compared to single-mouse scans, maintaining dose efficiency and image quality.

Conclusions:

• The proposed intrinsic respiratory gating method effectively reduces motion artifacts in μCT scans of mice with HCC.
• This technique enhances small tumor detectability and is suitable for high-throughput applications.
• The method offers a practical solution for improving liver tumor imaging in multi-mouse μCT studies.