Respiratory motion compensation for simultaneous PET/MR based on highly undersampled MR data
Christopher M Rank1, Thorsten Heußer1, Andreas Wetscherek2
1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Purpose:
Positron emission tomography (PET) of the thorax region is impaired by respiratory patient motion. To account for motion, the authors propose a new method for PET/magnetic resonance (MR) respiratory motion compensation (MoCo), which uses highly undersampled MR data with acquisition times as short as 1 min/bed.
Methods:
The proposed PET/MR MoCo method (4D jMoCo PET) uses radial MR data to estimate the respiratory patient motion employing MR joint motion estimation and image reconstruction with temporal median filtering. Resulting motion vector fields are incorporated into the system matrix of the PET reconstruction. The proposed approach is evaluated for the thorax region utilizing a PET/MR simulation with 1 min MR acquisition time and simultaneous PET/MR measurements of six patients with MR acquisition times of 1 and 5 min and radial undersampling factors of 11.2 and 2.2, respectively. Reconstruction results are compared to 3D PET, 4D gated PET and a standard MoCo method (4D sMoCo PET), which performs iterative image reconstruction and motion estimation sequentially. Quantitative analysis comprises the parameters SUVmean, SUVmax, full width at half-maximum/lesion volume, contrast and signal-to-noise ratio.
Results:
For simulated PET data, our quantitative analysis shows that the proposed 4D jMoCo PET approach with temporal filtering achieves the best quantification accuracy of all tested reconstruction methods with a mean absolute deviation of 2.3% when compared to the ground truth. For measured PET patient data, the mean absolute deviation of 4D jMoCo PET using a 1 min MR acquisition for motion estimation is 2.1% relative to the 5 min MR acquisition. This demonstrates a robust behavior even in case of strong undersampling at MR acquisition times as short as 1 min. In contrast, 4D sMoCo PET shows considerable reduction of quantification accuracy for the 1 min MR acquisition time. Relative to 3D PET, the proposed 4D jMoCo PET approach with temporal filtering yields an average increase of SUVmean, SUVmax, and contrast of 29.9% and 13.8% for simulated and measured PET data, respectively.
Conclusions:
Employing artifact-robust motion estimation enables PET/MR respiratory MoCo with MR acquisition times as short as 1 min/bed improving PET image quality and quantification accuracy.
Insights
Respiratory motion significantly impacts thoracic Positron Emission Tomography (PET) imaging. A new joint motion estimation and reconstruction (jMoCo PET) method improves accuracy using rapid, undersampled Magnetic Resonance imaging (MR) data for motion compensation.
Area of Science:
- Medical Imaging
- Nuclear Medicine
- Magnetic Resonance Imaging
Background:
- Thoracic Positron Emission Tomography (PET) imaging is often degraded by patient respiratory motion.
- Accurate motion compensation is crucial for reliable PET image quantification.
Purpose of the Study:
- To introduce and evaluate a novel PET/magnetic resonance (MR) respiratory motion compensation (MoCo) technique.
- To enable motion compensation using highly undersampled MR data acquired in as little as 1 minute per bed position.
Main Methods:
- The proposed 4D jMoCo PET method utilizes radial MR data for joint motion estimation and image reconstruction, incorporating temporal median filtering.
- Motion vector fields derived from MR are integrated into the PET system matrix for reconstruction.
- The method was validated using PET/MR simulations and patient data, comparing it against 3D PET, 4D gated PET, and a standard sequential MoCo approach (4D sMoCo PET).
Main Results:
- 4D jMoCo PET with temporal filtering demonstrated superior quantification accuracy in simulations (2.3% mean absolute deviation) compared to other methods.
- For patient data, 4D jMoCo PET using 1-minute MR acquisition achieved a 2.1% mean absolute deviation relative to 5-minute acquisitions, showing robustness even with significant undersampling.
- The proposed method significantly increased SUVmean, SUVmax, and contrast compared to 3D PET.
Conclusions:
- Artifact-robust motion estimation using rapid MR acquisition is feasible for PET/MR respiratory MoCo.
- The developed 4D jMoCo PET technique significantly enhances PET image quality and quantification accuracy.
- This approach allows for reduced MR acquisition times (as short as 1 min/bed) without compromising motion compensation effectiveness.
