Respiratory motion correction for quantitative PET/CT using all detected events with internal—external motion correlation

Purpose: We present a method to correct respiratory motion blurring in PET/CT imaging using internal–external (INTEX) motion correlation. The internal motion of a known tumor is derived from respiratory-gated PET images; this internal motion is then correlated with external respiratory signals to de...

Full description

Saved in:
Bibliographic Details
Published in:Medical physics (Lancaster) 2011-05, Vol.38 (5), p.2715-2723
Main Authors: Liu, Chi, Alessio, Adam M., Kinahan, Paul E.
Format: Article
Language:English
Subjects:
Algorithms
Cancer
Computed tomography
computerised tomography
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
image reconstruction
Image registration
internal-external motion correlation
Liver
Lungs
Medical image noise
medical image processing
Medical image reconstruction
Medical imaging
Motion
Movement
Neoplasms - diagnosis
noise
Nuclear Medicine Physics
PET/CT
Pneumodyamics, respiration
pneumodynamics
positron emission tomography
Positron emission tomography (PET)
Positron-Emission Tomography - methods
Reconstruction
Reproducibility of Results
Respiratory Mechanics
respiratory motion correction
Respiratory-Gated Imaging Techniques - methods
Sensitivity and Specificity
Statistics as Topic
Subtraction Technique
Tomography, X-Ray Computed - methods
tumours
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Purpose: We present a method to correct respiratory motion blurring in PET/CT imaging using internal–external (INTEX) motion correlation. The internal motion of a known tumor is derived from respiratory-gated PET images; this internal motion is then correlated with external respiratory signals to determine the complete information of tumor motion during the scan. Methods: For each PET/CT data, PET listmode data were phase-gated into five bins and reconstructed. The centroid of a targeted tumor in each bin was determined and correlated with the corresponding mean displacement of externally monitored respiratory motion signal. Based on this correlation, the external motion signal was converted into internal tumor motion information in the superior–inferior direction. Then, the PET listmode data were binned sequentially to multiple 1-s sinograms. According to the converted internal tumor motion signal, each 1-s sinogram was registered to a reference frame, which best matched the helical CT attenuation map based on consistency conditions. The registered sinograms were summed and reconstructed to form an image, corrected for the motion of the specific tumor. In this study, the proposed INTEX method was evaluated with phantom and patient studies in terms of tracer concentration and volume. Results: The INTEX method effectively recovered the tracer concentration to the level of the stationary scan data in the phantom experiment. In the patient study, the INTEX method yielded a (17 ± 22)% tumor volume decrease and a (10 ± 10)% tumor SUVmax increase compared to nongated images. Conclusions: The proposed INTEX method reduces respiratory motion degradation of PET tumor quantification and delineation in an effective manner. This can be used to improve the assessment of response to therapy for a known tumor by minimizing residual motion and matching the attenuation correction, without increasing image noise.
ISSN:0094-2405
2473-4209
0094-2405
DOI:10.1118/1.3582692