Objectives The aim of this study was to develop a method for tracking respiratory motion throughout full MR or PET/MR studies that requires only minimal additional hardware and no modifications to the sequences. Materials and Methods Patient motion that is caused by respiration affects the quality of the signal of the individual radiofrequency receive coil elements. This effect can be detected as a modulation of a monofrequent signal that is emitted by a small portable transmitter placed inside the bore (Pilot Tone). The frequency is selected such that it is located outside of the frequency band of the actual MR readout experiment but well within the bandwidth of the radiofrequency receiver, that is, the oversampling area. Temporal variations of the detected signal indicate motion. After extraction of the signal from the raw data, principal component analysis was used to identify respiratory motion. The approach and potential applications during MR and PET/MR examinations that rely on a continuous respiratory signal were validated with an anthropomorphic, PET/MR-compatible motion phantom as well as in a volunteer study. Results Respiratory motion detection and correction were presented for MR and PET data in phantom and volunteer studies. The Pilot Tone successfully recovered the ground-truth respiratory signal provided by the phantom. Conclusions The presented method provides reliable respiratory motion tracking during arbitrary imaging sequences throughout a full PET/MR study. All results can directly be transferred to MR-only applications as well.

Methods for joint activity reconstruction and attenuation reconstruction of time-of-flight (TOF) PET data provide an effective solution to attenuation correction when no (or incomplete or inaccurate) information on attenuation is available. One of the main barriers limiting use of these methods in clinical practice is their lack of validation in a relatively large patient database. In this contribution, we aim to validate reconstruction performed with maximum-likelihood activity reconstruction and attenuation registration (MLRR) in a whole-body patient dataset. Furthermore, a partial validation (because the scale problem of the algorithm is avoided for now) of reconstruction performed with maximum-likelihood activity and attenuation (MLAA) is also provided. We present a quantitative comparison between these 2 methods of joint reconstruction and the current clinical gold standard, maximum-likelihood expectation maximization (MLEM) with CT-based attenuation correction. The whole-body TOF PET emission data of each patient dataset were processed as a whole to reconstruct an activity volume covering all the acquired bed positions, helping reduce the problem of a scale per bed position in MLAA to a global scale for the entire activity volume. Three reconstruction algorithms were used: MLEM, MLRR, and MLAA. A maximum-likelihood scaling of the single-scatter simulation estimate to the emission data was used for scatter correction. The reconstruction results for various regions of interest were then analyzed. The joint reconstructions of the whole-body patient dataset provided better quantification than the gold standard in cases of PET and CT misalignment caused by patient or organ motion. Our quantitative analysis showed a difference of -4.2% ± 2.3% between MLRR and MLEM and a difference of -7.5% ± 4.6% between MLAA and MLEM, averaged over all regions of interest. Joint reconstruction of activity and attenuation provides a useful means to estimate tracer distribution when CT-based-attenuation images are subject to misalignment or are not available. With an accurate estimate of the scatter contribution in the emission measurements, the joint reconstructions of TOF PET data are within clinically acceptable accuracy.

BackgroundInterest in MR-only treatment planning for radiation therapy is growing rapidly with the emergence of integrated MRI/linear accelerator technology. The purpose of this study was to evaluate the feasibility of using synthetic CT images generated from conventional Dixon-based MRI scans for radiation treatment planning of lung cancer.MethodsEleven patients who underwent whole-body PET/MR imaging following a PET/CT exam were randomly selected from an ongoing prospective IRB-approved study. Attenuation maps derived from the Dixon MR Images and atlas-based method was used to create CT data (synCT). Treatment planning for radiation treatment of lung cancer was optimized on the synCT and subsequently copied to the registered CT (planCT) for dose calculation. Planning target volumes (PTVs) with three sizes and four different locations in the lung were planned for irradiation. The dose-volume metrics comparison and 3D gamma analysis were performed to assess agreement between the synCT and CT calculated dose distributions.ResultsMean differences between PTV doses on synCT and CT across all the plans were −0.1% ± 0.4%, 0.1% ± 0.5%, and 0.4% ± 0.5% for D95, D98 and D100, respectively. Difference in dose between the two datasets for organs at risk (OARs) had average differences of −0.14 ± 0.07 Gy, 0.0% ± 0.1%, and −0.1% ± 0.2% for maximum spinal cord, lung V20, and heart V40 respectively. In patient groups based on tumor size and location, no significant differences were observed in the PTV and OARs dose-volume metrics (p > 0.05), except for the maximum spinal-cord dose when the target volumes were located at the lung apex (p = 0.001). Gamma analysis revealed a pass rate of 99.3% ± 1.1% for 2%/2 mm (dose difference/distance to agreement) acceptance criteria in every plan.ConclusionsThe synCT generated from Dixon-based MRI allows for dose calculation of comparable accuracy to the standard CT for lung cancer treatment planning. The dosimetric agreement between synCT and CT calculated doses warrants further development of a MR-only workflow for radiotherapy of lung cancer.

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