PET respiratory motion correction: quo vadis?

Positron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.

Characterization of the Physiological Displacement of the Aortic Arch Using Non-Rigid Registration and MR Imaging.

OBJECTIVES: The aim of this work was to study physiological aortic arch three-dimensional displacement using non-rigid registration methods and magnetic resonance imaging (MRI). MATERIALS AND METHODS: Ten healthy volunteers underwent thoracic MRI. Prospective cardiac gating was performed with a 3D turbo field echo sequence to obtain end-systolic and end-diastolic MR images. The rigid and elastic behavior between these two cardiac phases was detected and compared using either an affine or an elastic registration method. To assess reproducibility, a second MRI acquisition was performed 14 days later. RESULTS: Affine registration between the end-systolic and end-diastolic MR images showed significant global translations of the aortic arch and the supra-aortic vessels in the x, y, and z directions (2.02 ± 1.6, -0.71 ± 1.1, and -1.21 ± 1.4 mm, respectively). Corresponding elastic registration indicated significant local displacement with a vector magnitude of 5.1 ± 0.89 mm for the brachiocephalic artery (BCA), of 4.26 ± 0.83 mm for the left common carotid artery (LCCA), and of 4.8 ± 0.86 mm for the left subclavian artery (LSCA). There was a difference in displacement between the supra-aortic trunks of the order of 2 mm. Vector displacement was not statistically different between the repeated acquisitions. CONCLUSIONS: The present results showed important deformations in the ostia of supra-aortic vessels during the cardiac cycle. It seems that aortic arch motions should be taken into account when designing and manufacturing fenestrated endografts. The elastic registration method provides more precise results, but is more complex and time-consuming than other methods.

Patient positioning in radiotherapy based on surface imaging using time of flight cameras.

PURPOSE: To evaluate the patient positioning accuracy in radiotherapy using a stereo-time of flight (ToF)-camera system. METHODS: A system using two ToF cameras was used to scan the surface of the patients in order to position them daily on the treatment couch. The obtained point clouds were registered to (a) detect translations applied to the table (intrafraction motion) and (b) predict the displacement to be applied in order to place the patient in its reference position (interfraction motion). The measures provided by this system were compared to the effectively applied translations. The authors analyzed 150 fractions including lung, pelvis/prostate, and head and neck cancer patients. RESULTS: The authors obtained small absolute errors for displacement detection: 0.8 ± 0.7, 0.8 ± 0.7, and 0.7 ± 0.6 mm along the vertical, longitudinal, and lateral axes, respectively, and 0.8 ± 0.7 mm for the total norm displacement. Lung cancer patients presented the largest errors with a respective mean of 1.1 ± 0.9, 0.9 ± 0.9, and 0.8 ± 0.7 mm. CONCLUSIONS: The proposed stereo-ToF system allows for sufficient accuracy and faster patient repositioning in radiotherapy. Its capability to track the complete patient surface in real time could allow, in the future, not only for an accurate positioning but also a real time tracking of any patient intrafraction motion (translation, involuntary, and breathing).

Local respiratory motion correction for PET/CT imaging: Application to lung cancer.

PURPOSE: Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications. METHODS: Both simulated (NURBS based 4D cardiac-torso phantom) and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions. RESULTS: Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the nonrigid deformation model in LRMC led to over an order of magnitude gain in computational efficiency of the correction relative to the application of the deformable model to the whole FOV. CONCLUSIONS: The results of this study support the use of LMRC as a flexible and efficient correction approach for respiratory motion effects for single lesions in the thoracic area.

Influence of partial volume correction in staging of head and neck squamous cell carcinoma using PET/CT.

AIM: PET/CT is widely used for the detection of lymph node involvement in head and neck squamous cell carcinoma (HNSCC). However, PET qualitative and quantitative capabilities are hindered by partial volume effects (PVE). Therefore, a retrospective study on 32 patients (57 lymph nodes) was carried out to evaluate the potential improvement of PVE correction (PVEC) in FDG PET/CT imaging for the diagnosis of HNSCC. Histopathological analysis of lymph nodes following neck dissection was used as the gold standard. METHODS: A previously proposed deconvolution based PVEC approach was used to derive improved quantitative accuracy PET images, while the anatomical lymph node volumes were determined on the CT images. Different parameters including SUVmax and SUVmean were derived from both original and PVEC PET images for each patient. RESULTS: Histopathology confirmed that SUVmax and SUVmean after PVEC allows a statistically significant differentiation of malignant and benign lymph nodes (P<0.05). The sensitivity of SUVmax and SUVmean was 64% and 57% respectively with or without PVEC. PVEC increased specificity from 71% to 76% for SUVmax and 57% to 66% for SUVmean. Corresponding accuracy increased from 66% to 71% for SUVmax and from 59% to 66% for SUVmean. However, the most accurate differentiation between benign and malignant nodes was obtained while using the magnitude of SUVmax increase after PVEC with a corresponding sensitivity, specificity and accuracy of 77%, 82% and 80% respectively. CONCLUSION: Our work shows that the use of partial volume effects correction allows a more accurate nodal staging using FDG PET imaging in HNSCC.

Influence of partial volume correction in staging of head and neck squamous cell carcinoma using PET/CT.

Aim: PET/CT is widely used for the detection of lymph node involvement in head and neck squamous cell carcinoma (HNSCC). However, PET qualitative and quantitative capabilities are hindered by partial volume effects (PVE). Therefore, a retrospective study on 32 patients (57 lymph nodes) was carried out to evaluate the potential improvement of PVE correction (PVEC) in FDG PET/CT imaging for the diagnosis of HNSCC. Histopathological analysis of lymph nodes following neck dissection was used as the gold standard. Methods: A previously proposed deconvolution based PVEC approach was used to derive improved quantitative accuracy PET images, while the anatomical lymph node volumes were determined on the CT images. Different parameters including SUVmax and SUVmean were derived from both original and PVEC PET images for each patient. Results: Histopathology confirmed that SUVmax and SUVmean after PVEC allows a statistically significant differentiation of malignant and benign lymph nodes (p<0.05). The sensitivity of SUVmax and SUVmean was 64% and 57% respectively with or without PVEC. PVEC increased specificity from 71% to 76% for SUVmax and 57% to 66% for SUVmean. Corresponding accuracy increased from 66% to 71% for SUVmax and from 59% to 66% for SUVmean. However, the most accurate differentiation between benign and malignant nodes was obtained while using the magnitude of SUVmax increase after PVEC with a corresponding sensitivity, specificity and accuracy of 77%, 82% and 80% respectively. Conclusion: Our work shows that the use of partial volume effects correction allows a more accurate nodal staging using FDG PET imaging in HNSCC.

Accuracy of dynamic patient surface monitoring using a time-of-flight camera and B-spline modeling for respiratory motion characterization.

Time-of-flight (ToF) camera technology provides a real-time depth map of a scene with adequate frequency for the monitoring of physiological patient motion. However, dynamic surface motion estimation using a ToF camera is limited by issues such as the raw measurement accuracy and the absence of fixed anatomical landmarks. In this work we propose to overcome these limitations using surface modeling through B-splines. This approach was assessed in terms of both motion estimation accuracy and associated variability improvements using acquisitions of an anthropomorphic surface phantom for a range of observation distances (0.6-1.4 m). In addition, feasibility was demonstrated on patient acquisitions. Using the proposed B-spline modeling, the mean motion estimation error and associated repeatability with respect to the raw measurements decreased by a factor of 3. Significant correlation was found between patients' surfaces motion extracted using the proposed B-spline approach applied to the ToF data and the one extracted from synchronized 4D-CT acquisitions as the ground truth. ToF cameras represent a promising alternative for contact-less patient surface monitoring for respiratory motion synchronization or modeling in imaging and/or radiotherapy applications.