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Multidetector CT angiography of arterial inflow and runoff in the lower extremities: a challenge in data acquisition
Daniel T Boll1, Jonathan S Lewin, Thorsten R Fleiter
1Department of Radiology, Case Western Reserve University, University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, OH 4410-106, USA.
Insights
High-resolution computed tomographic angiography (CTA) of lower extremities provides homogenous datasets suitable for automated vessel tracking. Automated 3D visualization offers reliable and time-efficient centerline extraction comparable to manual methods.
Area of Science:
- Vascular imaging
- Medical imaging analysis
- Radiology
Background:
- Computed tomographic angiography (CTA) is crucial for evaluating lower extremity vascular diseases.
- Acquiring homogenous, high-resolution 3D datasets is essential for accurate vascular assessment.
- Automated vessel-tracking techniques offer potential for efficient and reliable vascular analysis.
Purpose of the Study:
- To demonstrate the feasibility of obtaining homogenous 3D datasets with high temporal and spatial resolution from lower extremity CTA scans.
- To evaluate the efficacy of automated vessel-tracking techniques for vascular analysis in the lower extremities.
Main Methods:
- Eighteen male patients with vascular disease underwent contrast-enhanced CTA of lower limb arteries using a 16-row CT imager.
- Manual centerline selection and volume-rendering techniques were used to generate curved multiplanar reformations.
- Automated vessel-tracking strategies were compared against manual segmentation by five radiologists using Differential Receiver Operating Characteristic (DROC) analysis.
Main Results:
- High-quality CTA datasets were acquired with increased temporal and spatial resolution.
- Homogenous vascular contrast-to-noise ratios were achieved across pelvic, thigh, and calf vessels.
- Radiologists could not differentiate between manual and automated vascular segmentation (Area Under DROC curve = 0.56).
Conclusions:
- High-resolution CTA of the lower extremities yields homogenous datasets suitable for automated vessel tracking.
- Automated 3D visualization tools provide reliable, reproducible, and time-efficient centerline extractions.
- Automated methods are comparable to manual segmentation for vascular evaluation in lower extremity CTA.
Purpose:
To show the feasibility of acquiring homogenous 3-dimensional datasets with high temporal and spatial resolution from computed tomographic angiographic (CTA) scans of the lower extremities and to assess automated vessel-tracking techniques for vascular evaluation.
Methods:
Eighteen men (mean age 67.0 years, range 43-83) with aneurysmal or occlusive vascular diseases underwent contrast-enhanced CTA of the lower limb arteries utilizing a 16-row CT imager. Curved multiplanar reformations were generated by manual selection of vessel centerlines in the infrarenal aorta and the arterial vasculature in the pelvis, thigh, and calf based on volume-rendering techniques. For each vessel, opacification and depiction were quantitatively evaluated. The manually segmented images were compared to datasets processed with automated vessel-tracking strategies by 5 radiologists, who evaluated diagnostic reliability and image quality. A Differential Receiver Operating Characteristic (DROC) analysis was performed.
Results:
An increase in the temporal and spatial resolution led to acquisition of high quality CTA datasets. Significant homogeneity of the vascular contrast-to-noise ratios was achieved in the pelvic (coefficient of variance 1.5% to 10.1%), thigh (0.1% to 9.4%), and calf (3.3% to 19.2%) vessels. The assessment of vascular delineation revealed full-width-at-half-maximum contrast values of 96.4%, 95.5%, and 111.3% in the pelvis, thigh, and calf, respectively. Observers were not able to distinguish between manual and automated vascular segmentation, as represented by a 0.56 value for the area under the DROC curve.
Conclusions:
High-resolution CTA lower extremity datasets were acquired successfully, presenting vascular signal intensities of high homogeneity suitable for automated vessel-tracking techniques. Automated 3D visualization tools produced reliable, reproducible, and time-efficient centerline extractions that were comparable to manually defined centerlines.
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