Anatomical validation of automatic respiratory motion correction for coronary 18F‐sodium fluoride positron emission tomography by expert measurements from four‐dimensional computed tomography. Issue 11 (11th July 2022)

• Record Type: Journal Article
• Authors: Lassen, Martin Lyngby; Tzolos, Evangelos; Pan, Tinsu; Kwiecinski, Jacek; Cadet, Sebastien; Dey, Damini; Berman, Daniel; Slomka, Piotr
• Is Part Of: Medical physics. Volume 49:Issue 11(2022)
• Page Start: 7085
• Page End: 7094
• Publication Date: 2022-07-11
• Subjects: 18F‐sodium fluoride -- motion correction -- PET/CT; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.15834
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract: Background: Respiratory motion correction is of importance in studies of coronary plaques employing 18 F‐NaF; however, the validation of motion correction techniques mainly relies on indirect measures such as test–retest repeatability assessments. In this study, we aim to compare and, thus, validate the respiratory motion vector fields obtained from the positron emission tomography (PET) images directly to the respiratory motion observed during four‐dimensional cine‐computed tomography (CT) by an expert observer. Purpose: To investigate the accuracy of the motion correction employed in a software (FusionQuant) used for evaluation of 18 F‐NaF PET studies by comparing the respiratory motion of the coronary plaques observed in PET to the respiratory motion observed in 4D cine‐CT images. Methods: This study included 23 patients who undertook thoracic PET scans for the assessment of coronary plaques using 18 F‐sodium fluoride ( 18 F‐NaF). All patients underwent a 5‐s cine‐CT (4D‐CT), a coronary CT angiography (CTA), and 18 F‐NaF PET. The 4D‐CT and PET scan were reconstructed into 10 phases. Respiratory motion was estimated for the non‐contrast visible coronary plaques using diffeomorphic registrations (PET) and compared to respiratory motion observed on 4D‐CT. We report the PET motion vector fields obtained in the three principal axes in addition to the 3D motion. Statistical differences were examined using paired t ‐tests. Signal‐to‐noise ratios (SNR) are reported for the single‐phase images (end‐expiratory phase) and for the motion‐corrected image‐series (employing the motion vector fields extracted during the diffeomorphic registrations). Results: In total, 19 coronary plaques were identified in 16 patients. No statistical differences were observed for the maximum respiratory motion observed in x, y, and the 3D motion fields (magnitude and direction) between the CT and PET ( X direction: 4D CT = 2.5 ± 1.5 mm, PET = 2.4 ± 3.2 mm; Y direction: 4D CT = 2.3 ± 1.9 mm, PET = 0.7 ± 2.9 mm, 3D motion: 4D CT = 6.6 ± 3.1 mm, PET = 5.7 ± 2.6 mm, all p ≥ 0.05). Significant differences in respiratory motion were observed in the systems' Z direction: 4D CT = 4.9 ± 3.4 mm, PET = 2.3 ± 3.2 mm, p = 0.04. Significantly improved SNR is reported for the motion corrected images compared to the end‐expiratory phase images (end‐expiratory phase = 6.8±4.8, motion corrected = 12.2±4.5, p = 0.001). Conclusion: Similar respiratory motion was observed in two directions and 3D for coronary plaques on 4D CT as detected by automatic respiratory motion correction of coronary PET using FusionQuant. The respiratory motion correction technique significantly improved the SNR in the images.