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Respiratory-Induced Errors in Tumor Quantification and Delineation in CT Attenuation-Corrected PET Images: Effects of Tumor Size, Tumor Location, and Respiratory Trace: A Simulation Study Using the 4D XCAT Phantom

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Abstract

Purpose

We investigated the magnitude of respiratory-induced errors in tumor maximum standardized uptake value (SUVmax), localization, and volume for different respiratory motion traces and various lesion sizes in different locations of the thorax and abdomen in positron emission tomography (PET) images.

Procedures

Respiratory motion traces were simulated based on the common patient breathing cycle and three diaphragm motions used to drive the 4D XCAT phantom. Lesions with different diameters were simulated in different locations of lungs and liver. The generated PET sinograms were subsequently corrected using computed tomography attenuation correction involving the end exhalation, end inhalation, and average of the respiratory cycle. By considering respiration-averaged computed tomography as a true value, the lesion volume, displacement, and SUVmax were measured and analyzed for different respiratory motions.

Results

Respiration with 35-mm diaphragm motion results in a mean lesion SUVmax error of 24 %, a mean superior inferior displacement of 7.6 mm and a mean lesion volume overestimation of 129 % for a 9-mm lesion in the liver. Respiratory motion results in lesion volume overestimation of 50 % for a 9-mm lower lung lesion near the liver with just 15-mm diaphragm motion. Although there are larger errors in lesion SUVmax and volume for 35-mm motion amplitudes, respiration-averaged computed tomography results in smaller errors than the other two phases, except for the lower lung region.

Conclusions

The respiratory motion-induced errors in tumor quantification and delineation are highly dependent upon the motion amplitude, tumor location, tumor size, and choice of the attenuation map for PET image attenuation correction.

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Acknowledgments

We thank Dr. William Paul Segars for providing the XCAT phantom.

Conflict of Interest

None

Author information

Authors and Affiliations

  1. Faculty of Nuclear Engineering and Physics, Amirkabir University of Technology, Tehran, Iran

    Parham Geramifar & Mojtaba Shamsaie Zafarghandi

  2. Chronic Respiratory Disease Research Center, NRITLD, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Pardis Ghafarian

  3. Telemedicine Research Center, NRITLD, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Pardis Ghafarian

  4. Department of Radiology, Johns Hopkins University, Baltimore, MD, USA

    Arman Rahmim

  5. Medical Imaging Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Reza Ay

  6. Research Center for Nuclear Medicine, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Reza Ay

  7. Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Reza Ay

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  1. Parham Geramifar
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  2. Mojtaba Shamsaie Zafarghandi
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  3. Pardis Ghafarian
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Correspondence to Mohammad Reza Ay.

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Geramifar, P., Zafarghandi, M.S., Ghafarian, P. et al. Respiratory-Induced Errors in Tumor Quantification and Delineation in CT Attenuation-Corrected PET Images: Effects of Tumor Size, Tumor Location, and Respiratory Trace: A Simulation Study Using the 4D XCAT Phantom. Mol Imaging Biol 15, 655–665 (2013). https://doi.org/10.1007/s11307-013-0656-5

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