A novel respiratory tracking system for smart‐gated PET acquisition

Nehmeh, Sadek; Haj-Ali, Amin; Qing, Chun; Stearns, C.W.; Kalaigian, Hovanes; Kohlmyer, S.G.; Schöder, Heiko; Ho, Adelyn L.; Larson, Steven M.; Humm, John L.

doi:10.1118/1.3523100

Cited by 23 publications

(12 citation statements)

References 21 publications

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“…Reconstruction is then based on a selection of the acquired data. Such signals can be acquired by an external device and include electrocardiogram [2], Real-time Position Management [3] or Multidimensional Respiratory Gating [4], and pressure sensor (chest belt) [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…For instance, images at end of exhalation or inhalation can be reconstructed by selecting either the lowest or the highest amplitude values of a respiratory representative signal. In human imaging, such a method has been used for respiratory motion in PET [5,4,6]. In the case when a motion model is available, some authors proposed to incorporate the model into the tomographic reconstruction procedure in order to take into account all the acquired data to reconstruct a 3D still image.…”

Section: Introductionmentioning

confidence: 99%

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Image-based motion detection in 4D images and application to respiratory motion suppression

Breuilly

Malandain

Ayache

et al. 2013

2013 IEEE 10th International Symposium on Biomedical Imaging

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Respiratory motion may blur the tomographic reconstruction of PET or SPECT images, which subsequently impairs quantitative measurements, e.g. in the upper abdomen area. Respiratory phase-based gated reconstruction addresses this problem for CT images, but deteriorates the signal-to-noise ratio and other intensity-based quality measures for ET images.This article describes an image-based motion detection method for dynamic images, which works for both 4D-CT and 4D-SPECT images. This method allowed us to identify the motionless phases from the image-based motion signal. Interestingly, we found that the peak of motion according to the pressure signal, recorded during the acquisition and considered as a reference, is temporally shifted compared to the motion-phases identified by the proposed method. Moreover, these observations permit to reconstruct a breath hold like 3D SPECT image improving the quality of the 3D reconstruction compared to both 4D reconstruction and standard 3D reconstruction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Image-based motion detection in 4D images and application to respiratory motion suppression

Breuilly

Malandain

Ayache

et al. 2013

2013 IEEE 10th International Symposium on Biomedical Imaging

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“…[3][4][5] Although 4D PET improves image quality significantly, substantial residual motion artifacts remain in the retrospectively reconstructed 4D PET and 4D CT, primarily due to irregularities in patient breathing. [6][7][8][9][10] There are two main types of 4D PET scan and reconstruction, including respiratory-gated and motion-compensated 3D PET: (1) scanning throughout breathing cycles and sorting raw data into multiple bins of respiratory phases, or scanning only one particular phase with respiratory gating [11][12][13] and (2) scanning breathing cycles and applying a deformable model derived from 4DCT to reconstruct a single phase scan without suffering from low quantum or long acquisition. [14][15][16] The former requires considerably longer scan duration than a 3D PET scan, to achieve the same count statistics, while the latter may suffer from deformation uncertainty, which is propagated from residual motion artifacts in 4DCT (Ref.…”

Section: Introductionmentioning

confidence: 99%

Assessing and accounting for the impact of respiratory motion on FDG uptake and viable volume for liver lesions in free‐breathing PET using respiration‐suspended PET images as reference

Schmidtlein

Burger

et al. 2014

Medical Physics

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Purpose: To assess and account for the impact of respiratory motion on the variability of activity and volume determination of liver tumor in positron emission tomography (PET) through a comparison between free-breathing (FB) and respiration-suspended (RS) PET images. Methods: As part of a PET/computed tomography (CT) guided percutaneous liver ablation procedure performed on a PET/CT scanner, a patient's breathing is suspended on a ventilator, allowing the acquisition of a near-motionless PET and CT reference images of the liver. In this study, baseline RS and FB PET/CT images of 20 patients undergoing thermal ablation were acquired. The RS PET provides near-motionless reference in a human study, and thereby allows a quantitative evaluation of the effect of respiratory motion on PET images obtained under FB conditions. Two methods were applied to calculate tumor activity and volume: (1) threshold-based segmentation (TBS), estimating the total lesion glycolysis (TLG) and the segmented volume and (2) histogram-based estimation (HBE), yielding the background-subtracted lesion (BSL) activity and associated volume. The TBS method employs 50% of the maximum standardized uptake value (SUV max ) as the threshold for tumors with SUV max ≥ 2× SUV liver-bkg , and tumor activity above this threshold yields TLG 50% . The HBE method determines local PET background based on a Gaussian fit of the low SUV peak in a SUV-volume histogram, which is generated within a user-defined and optimized volume of interest containing both local background and lesion uptakes. Voxels with PET intensity above the fitted background were considered to have originated from the tumor and used to calculate the BSL activity and its associated lesion volume. Results: Respiratory motion caused SUV max to decrease from RS to FB by −15% ± 11% (p = 0.01). Using TBS method, there was also a decrease in SUV mean (−18% ± 9%, p = 0.01), but an increase in TLG 50% (18% ± 36%) and in the segmented volume (47% ± 52%, p = 0.01) from RS to FB PET images. The background uptake in normal liver was stable, 1% ± 9%. In contrast, using the HBE method, the differences in both BSL activity and BSL volume from RS to FB were −8% ± 10% (p = 0.005) and 0% ± 16% (p = 0.94), respectively. Conclusions: This is the first time that almost motion-free PET images of the human liver were acquired and compared to free-breathing PET. The BSL method's results are more consistent, for the calculation of both tumor activity and volume in RS and FB PET images, than those using conventional TBS. This suggests that the BSL method might be less sensitive to motion blurring and provides an improved estimation of tumor activity and volume in the presence of respiratory motion.

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“…Investigators have used different respiration tracking systems such as pressure sensors, 17 spirometers, 17 temperature sensors, 11 and optical tracking 7,9,10 to monitor the respiratory motion and simultaneously generate a trigger signal at a user-predefined phase 7,10,11,16 or displacement. 19,35 Gated PET or four dimensional (4D) PET retrospectively correlates a respiratory signal with the PET data acquisition to allow reconstruction at different phases or displacement of the respiratory cycle. The drawbacks of gated PET are (1) the reduction in the signal-to-noise ratio (SNR) due to the short acquisition time per gated bin, (2) possible weak correlation between internal tumor motion and external respiratory motion (dependence on the size and location of the tumor) (Refs.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, respiratory motion management techniques need to be implemented to increase the accuracy of tumor volume delineation. [9][10][11][12][13][14] There are four broad classes to reconstruct PET images to reduce artifacts in the presence of motion: 15 (1) hardwarebased gating, 7,[9][10][11]13,[16][17][18][19] (2) software-based gating, [20][21][22][23][24][25][26][27] (3) incorporated-motion-model (IMM) based algorithms, [28][29][30] and (4) joint estimation. [31][32][33][34] The hardware-based gating is based on the assumption that external respiratory motion is a surrogate for motion of internal structures.…”

Section: Introductionmentioning

confidence: 99%

The impact of audio-visual biofeedback on 4D PET images: Results of a phantom study

et al. 2012

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Purpose: Irregular breathing causes motion blurring artifacts in 4D PET images. Audiovisual (AV) biofeedback has been demonstrated to improve breathing regularity. To investigate the hypothesis that, compared with free breathing, motion blurring artifacts are reduced with AV biofeedback, the authors performed the first experimental phantom-based quantification of the impact of AV biofeedback on 4D PET image quality. Methods: The authors acquired 4D PET dynamic phantom images with AV biofeedback and free breathing by moving a phantom programmed with AV biofeedback trained and free breathing respiratory traces of ten healthy subjects. The authors also acquired stationary phantom images for reference. The phantom was cylindrical with six hollow sphere targets (10, 13, 17, 22, 28, and 37 mm in diameter). The authors quantified motion blurring using the target diameter, Dice coefficient and recovery coefficient (RC) metrics to estimate the effect of motion. Results: The average increase in target diameter for AV biofeedback was 0:661:6 mm ð4:7 6 13%Þ, which was significantly (p < 0:001) smaller than for free breathing 1:3 6 2:2 mm ð9:1 6 19%Þ. The average Dice coefficient for AV biofeedback was 0:9060:07, which was significantly (p < 0:001) larger than for free breathing (0:8860:10). The RCs for AV biofeedback were consistently higher than those for free breathing and comparable to those for stationary targets. However, for RCs the impact of target sizes was more dominant than that of motion. In addition, the authors observed large variations in the results with respect to target sizes, subject traces and respiratory bins due to partial volume effects and respiratory motion irregularity. Conclusions:The results indicate that AV biofeedback can significantly reduce motion blurring artifacts and may facilitate improved identification and localization of lung tumors in 4D PET images. The results justify proceeding with clinical studies to quantify the impact of AV biofeedback on 4D PET image quality and tumor detectability.

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A novel respiratory tracking system for smart‐gated PET acquisition

Abstract: MDRT has been shown to be accurate in tracking breathing motion and assisted in implementing a smart-gating PET acquisition technique that allowed to acquire prospectively motion-free PET images.

Cited by 23 publications

References 21 publications

Image-based motion detection in 4D images and application to respiratory motion suppression

Image-based motion detection in 4D images and application to respiratory motion suppression

Assessing and accounting for the impact of respiratory motion on FDG uptake and viable volume for liver lesions in free‐breathing PET using respiration‐suspended PET images as reference

The impact of audio-visual biofeedback on 4D PET images: Results of a phantom study

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