Evaluation of a Novel Elastic Respiratory Motion Correction Algorithm on Quantification and Image Quality in Abdominothoracic PET/CT

Abstract

Our aim is to evaluate in phantom and patient studies a recently developed elastic motion debluring (EMDB) technique which makes use of all the acquired PET data and compare its performance to other conventional techniques such as phase based gating (PBG) and HDChest (HDC) both of which use fractions of the acquired data. Comparisons were made with respect to static whole-body (SWB) images with no motion correction. A phantom simulating respiratory motion of the thorax with lung lesions (5 spheres with ID=10- 28 mm) was scanned with 0, 1, 2, and 3 cm motion. Four reconstructions were performed: SWB, PBG, HDC, and EMDB. For PBG, the average (PBGave) and maximum bin (PBGmax) were used. To compare the reconstructions, the ratios of SUV (RSmax), SUVpeak (RSpeak), and CNR (RCNR) were calculated with respect to SWB. Additionally, 46 patients with lung or liver tumors < 3 cm diameter were also studied. Measurements of SUV, SUVpeak, and contrast-to-noise ratio (CNR) were made for 46 lung and 19 liver lesions. To evaluate image noise, the SUV standard deviation was measured in healthy lung and liver tissue and in the phantom background. Finally, subjective image quality of patient exams was scored on a 5 point scale by four radiologists. In the phantom, EMDB increased SUV/SUVpeak over SWB but to a lesser extent than the other reconstruction methodologies. The RCNR for EMDB however was higher than all other reconstructions (0.68 EMDB > 0.54 HDC > 0.41 PBGmax > 0.31 PBGave). Similar results were seen in patient studies. The SUV/SUVpeak were higher by 19.3/11.1% EMDB, 21.6/13.9% HDC, 22.8/12.8% PBGave, and 45.6/26.8% PBGmax compared to SWB. Lung/liver noise increased EMDB (3/15%), HDC (35/56%), PBGave (100/170%), and PBGmax (146/219%). CNR increased in lung/liver tumors only for EMDB (18/13%), and decreased for HDC (-14/-23%), PBGave (-39/-63%), and PBGmax (-18/-46%). Average radiologist scores of image quality were SWB (4.0 ± 0.8) > EMDB (3.7 ± 1.0) > HDC (3.1 ± 1.0) > PBG (1.5 ± 0.7). The EMDB algorithm had the least increase in image noise, improved lesion CNR, and had the highest overall image quality score.

Comparison of two elastic motion correction approaches for whole-body PET/CT: motion deblurring vs gate-to-gate motion correction

“…In this study, a fast elastic motion compensation approach based on motion deblurring (DEB-MC) is evaluated for clinical usage. DEB-MC has already been evaluated before showing its potential of performing whole-body PET motion correction comparable to OG results [17]. However, as OG cannot be regarded as the gold standard for motion correction, we aim here for a systematic comparison of DEB-MC with an established gate-to-gate elastic motion compensation technique (G2G-MC) within a clinical patient cohort and advanced phantom scans.…”

Characterization of continuous bed motion effects on patient breathing and respiratory motion correction in PET/CT imaging

“…PET image reconstruction was performed with and without motion correction using: 2 iterations, 21 subsets, time‐of‐flight information, point‐spread function correction, 200 × 200 matrix, 4.07 mm × 4.07 mm × 2.03 mm voxel size, and 5‐mm full width at half‐maximum isotropic Gaussian post‐reconstruction filter. Reconstruction without motion correction for both acquisition modes (CBM and SS) will here onwards be referred to as static whole body (SWB), while reconstructions with motion correction for both acquisition modes (CBM and SS) were performed using a recently introduced respiratory motion correction algorithm (OncoFreeze) that utilizes elastic motion deblurring (EMDB) …”

“…Respiratory motion blur in PET/CT can cause a multitude of challenges, including decreased tumor detectability, underestimation of radiotracer concentrations, and misalignments with anatomical images in areas affected by respiratory motion . Although numerous methodologies have been developed to correct for respiratory motion blur, several studies have demonstrated that the regularity of patient breathing patterns can greatly impact the efficacy of PET images both without and with respiratory motion correction …”

Improved Alignment of PET and CT Images in Whole-Body PET/CT in Cases of Respiratory Motion During CT

“…Patient data in this study had been used in previous work. (9) The institutional review board (IRB) approved the study (M D Anderson IRB 2015-0989 and PA18-1159). All subjects signed a written informed consent prior to imaging.…”

“…In a recent advance, image noise was reduced by methods like elastic motion deblurring. (8,9) Other approaches used a displacement field, in some cases by on November 4, 2020. For personal use only.…”