Automated attenuation-based tube potential selection for thoracoabdominal computed tomography angiography: improved...

Area of Science:

• Medical Imaging
• Radiology
• Computed Tomography

Background:

• Computed tomography angiography (CTA) is crucial for diagnosing vascular diseases.
• Optimizing radiation dose while maintaining image quality in CTA remains a challenge.
• Tube potential selection significantly impacts image quality and radiation exposure.

Purpose of the Study:

• To introduce a novel automated algorithm for attenuation-based tube potential selection in body CTA.
• To evaluate the algorithm's impact on diagnostic image quality.
• To assess the effect of the algorithm on patient radiation dose.

Main Methods:

• 40 patients underwent 64-slice thoracoabdominal CTA using an automated tube potential selection algorithm (CAREkV).
• The algorithm optimized tube potential (70-140 kV) and tube-current based on topogram attenuation and diagnostic task.
• Image quality was assessed semiquantitatively; attenuation, noise, and contrast-to-noise ratio were measured; CT dose index (CTDIvol) was recorded and compared to a standard 120 kV protocol.

Main Results:

• Diagnostic image quality was achieved in all patients with excellent interreader agreement (κ=0.78).
• Automated selection led to reduced tube potential in 24/40 patients (mean kV reduction), correlating with BMI and topogram attenuation.
• CTDIvol was significantly lower (7.95±2.6 mGy) compared to the standard 120 kV protocol (10.59±1.8 mGy), resulting in a 25.1% overall dose reduction.

Conclusions:

• Automated attenuation-based tube potential selection is feasible for body CTA.
• The algorithm provides diagnostic image quality.
• This method significantly reduces overall radiation dose by approximately 25% compared to standard protocols.