Purpose: Limb realignment surgery is increasingly guided by preoperative 3D imaging to develop precise patient specific treatments. Current standard 3D imaging systems such as CT scanners require the patient be imaged supine, complicating surgical decisions attempting to improve limb performance under load. Here, we investigate the possibility of conducting weight bearing 3D imaging on a standard robotic cone-beam CT system, imaging the ankle, knee and hip in a single scan.
Methods: A Siemens ARTIS pheno robotic cone-beam CT system (Siemens Healthcare) was used to image a synthetic ankle, knee and hip phantom (Sawbones) standing upright with a height of 110cm, mimicking stationary weight bearing conditions. The ARTIS pheno C-arm was manually manoeuvred away from the table and positioned with the source and detector parallel to the floor. In this position, the C-arm was able to rotate around the phantom through an arc of 135°. The phantom was imaged (7.5 fps, 90 kV) from ankle to hip via a series of eight 135° arcs separated by approximately 17cm upward axial translations. The 3D images were reconstructed using a total variation regularised reconstruction.
Results: The multi-arc acquisition enabled a total axial coverage of 100 cm, capturing the ankle, knee and hip joints in a single scan. The scan took ~120 seconds to complete, acquiring 1357 projections. The gantry movements were manually controlled via the pilot-joystick, limiting the gantry rotation velocity to 10°/s, elongating the scan time.
Conclusion: This is the first-time upright 3D imaging of the ankle, knee and hip in a single scan has been implemented on a standard robotic angiography system. It represents the first step towards full body upright 3D imaging on a standard system, as well as 3D imaging of lower body limbs moving (i.e. bending and walking) for high quality preoperative planning and postoperative assessment.
Funding Support, Disclosures, and Conflict of Interest: This research was supported by G201166 IPA2 with Siemens Healthineers; ACRF grant G175269; Ricky O'Brien Fellowship CI NSW Fellowship G195559, NHMRC Project Grant G193048; Tess Reynolds USyd Postdoctoral Fellowship Scheme G200793.