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Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model

In PET imaging, patient motion due to respiration can lead to artifacts and blurring, in addition to quantification errors. The integration of PET imaging with MRI in PET/MRI scanners provides spatially aligned complementary clinical information and allows the use of high-contrast, high-spatial-reso...

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Autores principales: Manber, Richard, Thielemans, Kris, Hutton, Brian F., Wan, Simon, Fraioli, Francesco, Barnes, Anna, Ourselin, Sébastien, Arridge, Simon, Atkinson, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Nuclear Medicine 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126439/
https://www.ncbi.nlm.nih.gov/pubmed/29523630
http://dx.doi.org/10.2967/jnumed.117.191460
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author Manber, Richard
Thielemans, Kris
Hutton, Brian F.
Wan, Simon
Fraioli, Francesco
Barnes, Anna
Ourselin, Sébastien
Arridge, Simon
Atkinson, David
author_facet Manber, Richard
Thielemans, Kris
Hutton, Brian F.
Wan, Simon
Fraioli, Francesco
Barnes, Anna
Ourselin, Sébastien
Arridge, Simon
Atkinson, David
author_sort Manber, Richard
collection PubMed
description In PET imaging, patient motion due to respiration can lead to artifacts and blurring, in addition to quantification errors. The integration of PET imaging with MRI in PET/MRI scanners provides spatially aligned complementary clinical information and allows the use of high-contrast, high-spatial-resolution MR images to monitor and correct motion-corrupted PET data. On a patient cohort, we tested the ability of our joint PET/MRI-based predictive motion model to correct respiratory motion in PET and show it can improve lesion detectability and quantitation and reduce image artifacts. Methods: Using multiple tracers and multiple organ locations, we applied our motion correction method to 42 clinical PET/MRI patient datasets containing 162 PET-avid lesions. Quantitative changes were calculated using SUV changes in avid lesions. Lesion detectability changes were explored with a study in which 2 radiologists identified lesions in uncorrected and motion-corrected images and provided confidence scores. Results: Mean increases of 12.4% for SUV(peak) and 17.6% for SUV(max) after motion correction were found. In the detectability study, confidence scores for detecting avid lesions increased, with a rise in mean score from 2.67 to 3.01 (of 4) after motion correction and a rise in detection rate from 74% to 84%. Of 162 confirmed lesions, 49 showed an increase in all 3 metrics—SUV(peak), SUV(max), and combined reader confidence score—whereas only 2 lesions showed a decrease. We also present clinical case studies demonstrating the effect that respiratory motion correction of PET data can have on patient management, with increased numbers of detected lesions, improved lesion sharpness and localization, and reduced attenuation-based artifacts. Conclusion: We demonstrated significant improvements in quantification and detection of PET-avid lesions, with specific case study examples showing where motion correction has the potential to affect diagnosis or patient care.
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spelling pubmed-61264392019-03-01 Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model Manber, Richard Thielemans, Kris Hutton, Brian F. Wan, Simon Fraioli, Francesco Barnes, Anna Ourselin, Sébastien Arridge, Simon Atkinson, David J Nucl Med Physics and Instrumentation In PET imaging, patient motion due to respiration can lead to artifacts and blurring, in addition to quantification errors. The integration of PET imaging with MRI in PET/MRI scanners provides spatially aligned complementary clinical information and allows the use of high-contrast, high-spatial-resolution MR images to monitor and correct motion-corrupted PET data. On a patient cohort, we tested the ability of our joint PET/MRI-based predictive motion model to correct respiratory motion in PET and show it can improve lesion detectability and quantitation and reduce image artifacts. Methods: Using multiple tracers and multiple organ locations, we applied our motion correction method to 42 clinical PET/MRI patient datasets containing 162 PET-avid lesions. Quantitative changes were calculated using SUV changes in avid lesions. Lesion detectability changes were explored with a study in which 2 radiologists identified lesions in uncorrected and motion-corrected images and provided confidence scores. Results: Mean increases of 12.4% for SUV(peak) and 17.6% for SUV(max) after motion correction were found. In the detectability study, confidence scores for detecting avid lesions increased, with a rise in mean score from 2.67 to 3.01 (of 4) after motion correction and a rise in detection rate from 74% to 84%. Of 162 confirmed lesions, 49 showed an increase in all 3 metrics—SUV(peak), SUV(max), and combined reader confidence score—whereas only 2 lesions showed a decrease. We also present clinical case studies demonstrating the effect that respiratory motion correction of PET data can have on patient management, with increased numbers of detected lesions, improved lesion sharpness and localization, and reduced attenuation-based artifacts. Conclusion: We demonstrated significant improvements in quantification and detection of PET-avid lesions, with specific case study examples showing where motion correction has the potential to affect diagnosis or patient care. Society of Nuclear Medicine 2018-09 /pmc/articles/PMC6126439/ /pubmed/29523630 http://dx.doi.org/10.2967/jnumed.117.191460 Text en © 2018 by the Society of Nuclear Medicine and Molecular Imaging. Immediate Open Access: Creative Commons Attribution 4.0 International License (CC BY) allows users to share and adapt with attribution, excluding materials credited to previous publications. License: https://creativecommons.org/licenses/by/4.0/. Details: http://jnm.snmjournals.org/site/misc/permission.xhtml.
spellingShingle Physics and Instrumentation
Manber, Richard
Thielemans, Kris
Hutton, Brian F.
Wan, Simon
Fraioli, Francesco
Barnes, Anna
Ourselin, Sébastien
Arridge, Simon
Atkinson, David
Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model
title Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model
title_full Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model
title_fullStr Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model
title_full_unstemmed Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model
title_short Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR, Using a Joint PET/MR Predictive Motion Model
title_sort clinical impact of respiratory motion correction in simultaneous pet/mr, using a joint pet/mr predictive motion model
topic Physics and Instrumentation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126439/
https://www.ncbi.nlm.nih.gov/pubmed/29523630
http://dx.doi.org/10.2967/jnumed.117.191460
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