Real-time X-ray-based 4D image guidance of minimally invasive interventions
A new technology is introduced that enables real-time 4D (three spatial dimensions plus time) X-ray guidance for vascular catheter interventions with acceptable levels of ionising radiation.
The enabling technology is a combination of low-dose tomographic data acquisition with novel compressed sensing reconstruction and use of prior image information. It was implemented in a prototype set-up consisting of a gantry-based flat detector system. In pigs (n = 5) angiographic interventions were simulated. Radiation dosage on a per time base was compared with the “gold standard” of X-ray projection imaging.
Contrary to current image guidance methods that lack permanent 4D updates, the spatial position of interventional instruments could be resolved in continuous, spatial 4D guidance; the movement of the guide wire as well as the expansion of stents could be precisely tracked in 3D angiographic road maps. Dose rate was 23.8 μGy/s, similar to biplane standard angiographic fluoroscopy, which has a dose rate of 20.6 μGy/s.
Real-time 4D X-ray image-guidance with acceptable levels of radiation has great potential to significantly influence the field of minimally invasive medicine by allowing faster and safer interventions and by enabling novel, much more complex procedures for vascular and oncological minimally invasive therapy.
• Real-time 4D (three spatial dimensions plus time) angiographic intervention guidance is realistic.
• Low-dose tomographic data acquisition with special compressed sensing-based algorithms is enabled.
• Compared with 4D CT fluoroscopy, this method reduces radiation to acceptable levels.
• Once implemented, vascular interventions may become safer and faster.
• More complex intervention approaches may be developed.
KeywordsIntervention guidance 4D imaging Compressed sensing Catheter lab Minimally invasive
The research is funded by DFG (German Research Foundation) grant (KA 1678/6-1 and BA 3546/2-1) and Siemens Healthcare. We acknowledge Stefan Sawall’s support in the creation of the reconstruction algorithm and his contribution to the discussion of the methodology. We thank Dr. Michaela Socher and Roland Galmbacher for animal handling. Furthermore, we would like to acknowledge Barbara Flach and Rolf Kueres for help during experimental set-ups and discussion of future developments. We would like to thank Dr. Michael Grasruck, Dr. Andreas Maier and Dr. Yiannis Kyriakou for extensive help with the experimental set-up, as well as discussion of applications, clinical implementation and future developments.
- 7.Schulz B, Eichler K, Siebenhandl P, Gruber-Rouh T, Czerny C, Vogl TJ, Zangos S (2012) Accuracy and speed of robotic assisted needle interventions using a modern cone beam computed tomography intervention suite: a phantom study. Eur Radiol 23:198-204Google Scholar
- 8.Kroeze SGC, Huisman M, Verkooijen HM, van Diest PJ, Ruud Bosch JLH, van den Bosch MAAJ (2012) Real-time 3D fluoroscopy-guided large core needle biopsy of renal masses: a critical early evaluation according to the IDEAL recommendations. Cardiovasc Intervent Radiol 35:680–685PubMedCrossRefGoogle Scholar
- 16.Chen G-H, Tang J, Nett B, Qi Z, Leng S, Szczykutowicz T (2010) Prior image constrained compressed sensing (PICCS) and applications in X-ray computed tomography. Curr Med Imaging Rev 2:119–134Google Scholar