Comparison of breathing gated CT images generated using a 5DCT technique and a commercial clinical protocol in a porcine model. Issue 7 (11th June 2015)

• Record Type: Journal Article
• Authors: O'Connell, Dylan P.; Thomas, David H.; Dou, Tai H.; Lamb, James M.; Feingold, Franklin; Low, Daniel A.; Fuld, Matthew K.; Sieren, Jered P.; Sloan, Chelsea M.; Shirk, Melissa A.; Hoffman, Eric A.; Hofmann, Christian
• Is Part Of: Medical physics. Volume 42:Issue 7(2015)
• Page Start: 4033
• Page End: 4042
• Publication Date: 2015-06-11
• Subjects: biological tissues -- cardiology -- computerised tomography -- image motion analysis -- image reconstruction -- image registration -- lung -- medical image processing -- pneumodynamics; Computed tomography -- Reconstruction -- Registration -- Noise -- Pneumodyamics, respiration; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Analysis of motion; 4DCT -- breathing motion modeling; Medical image reconstruction -- Image reconstruction -- Lungs -- Tissues -- Medical image artifacts -- Computed tomography -- Image registration -- Dosimetry -- Cancer; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4922201
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: To demonstrate that a "5DCT" technique which utilizes fast helical acquisition yields the same respiratory‐gated images as a commercial technique for regular, mechanically produced breathing cycles. Methods: Respiratory‐gated images of an anesthetized, mechanically ventilated pig were generated using a Siemens low‐pitch helical protocol and 5DCT for a range of breathing rates and amplitudes and with standard and low dose imaging protocols. 5DCT reconstructions were independently evaluated by measuring the distances between tissue positions predicted by a 5D motion model and those measured using deformable registration, as well by reconstructing the originally acquired scans. Discrepancies between the 5DCT and commercial reconstructions were measured using landmark correspondences. Results: The mean distance between model predicted tissue positions and deformably registered tissue positions over the nine datasets was 0.65 ± 0.28 mm. Reconstructions of the original scans were on average accurate to 0.78 ± 0.57 mm. Mean landmark displacement between the commercial and 5DCT images was 1.76 ± 1.25 mm while the maximum lung tissue motion over the breathing cycle had a mean value of 27.2 ± 4.6 mm. An image composed of the average of 30 deformably registered images acquired with a low dose protocol had 6 HU image noise (single standard deviation) in the heart versus 31 HU for the commercial images. Conclusions: An end to end evaluation of the 5DCT technique was conducted through landmark based comparison to breathing gated images acquired with a commercial protocol under highly regular ventilation. The techniques were found to agree to within 2 mm for most respiratory phases and most points in the lung.