A comparison of two image fusion techniques in CT-on-Rails localization of radiation delivery

Albert Y. C. Fung¹, James R. Wong², Chee-Wai Cheng³, S. Lisa Grimm⁴, Minoru Uematsu⁵

1. Department of Radiation Oncology, Nebraska Medical Center, Omaha (NE, USA), 69198

2. Department of Radiation Oncology, Morristown Memorial Hospital, Morristown (NJ, USA), 07962

3. Department of Radiation Oncology, Arizona Oncology Associates, Tucson (AZ, USA), 85712

4. Department of Radiology, Oncology, Albert Einstein Medical Center, Philadelphia (PA, USA), 19141

5. Department of Radiology, National Defense Medical College, 3-2 Namiki Tokorozawa, Saitama 359 (Japan)

Manuscript received: December 29, 2004; revised: March 15, 2005

Accepted for publication: May 2, 2005

Abstract

A computed tomography (CT) scanner on Rails has been installed in a linear accelerator room at Morristown Memorial Hospital since 2000. The CT-on-Rails has been used for the localization of patient position during radiation delivery for prostate, lung and liver cancer patients. The image management system, the Siemens Syngo system, is the primary software employed in the registration of the planning CT and the treatment CT images. This study compares the two image fusion methods available in the system : Landmark Registration and Visual Alignment. Shifts in 6 CT scans with Rando phantom were deduced from Landmark Registration (automatic algorithm) and from Visual Alignment (manual registration), and compared with the shifts directly measured on the phantom. For Visual Alignment, the isocenter shifts deduced from the fused images generally agreed well with the directly measured shifts on the Rando phantom, with average absolute error of 0.9 mm in anterior-posterior (AP) direction, 1.0 mm in right-left (RL) direction, and 2.0 mm in superior-inferior (SI) direction. The image fusion algorithm was confirmed to be accurate. Some scans with Landmark Registration gave erroneous AP shifts when the anterior radio-opaque marker (BB) registration was off in the AP direction. Visual Alignment was more robust than Landmark Registration in these clinical situations.

KEYWORDS: Fusion localization computed tomography.