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Postacquisition Detection of Tumor Motion in the Lung and Upper Abdomen Using List-Mode PET Data: A Feasibility Study

Ralph A. Bundschuh, Axel Martínez-Moeller, Markus Essler, María-José Martínez, Stephan G. Nekolla, Sibylle I. Ziegler and Markus Schwaiger

Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar der Technischen Universität München, Munich, Germany


Figure 1
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  		FIGURE 1.  Comparison of ungated (left) and gated (right) 18F-FDG PET study of a lung tumor.

 

Figure 2
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  		FIGURE 2.  (A) Activity distribution within VOI around tumor for 2 different 500-ms frames: one in expiration state (solid line) and one in inspiration state (dotted line). (B) Data-driven curve of first 200 s of patient 1 (solid line), compared with curve obtained by pressure-sensitive belt (dotted line).

 

Figure 3
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  		FIGURE 3.  (A) Use of Savitzky-Golay filter in 200-s sequence of patient 5 (lesion 1). Filtered curve (solid line) is shifted for demonstration. (B) Example of data-driven curve (solid line) showing no correlation with curve obtained by pressure-sensitive belt (dotted line).

 

Figure 4
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  		FIGURE 4.  (A) Data-driven curve of patient 2 for the full 10 min. Baseline shift, which might indicate rigid body motion, is visible at about 420 s. (B) Example of irregular breathing pattern (coughing) in patient 8 at beginning of displayed 100-s sequence (arrow). Data-driven curve (solid line) is compared with signal from pressure-sensitive belt (dotted line).

 




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