Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

Kalantari, Faraz; Li, Tianfang; Mu, Jin; Wang, Jing

doi:10.1088/0031-9155/61/15/5639

Cited by 15 publications

(14 citation statements)

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“…Recently, we have developed a new technique for motion‐compensated 4D‐CBCT image reconstruction based on simultaneous motion estimation and motion‐compensated image reconstruction (SMEIR) . Simultaneous motion estimation and motion‐compensated image reconstruction obtains the deformation vector fields (DVF) by warping the projection of the reference phase image to those of all other phases in an iterative process . Hence, SMEIR can reconstruct any phase 4D‐CBCT by explicitly considering the motion model between different phases, effectively suppressing the view aliasing artifacts caused by the limited number of projections.…”

Section: Introductionmentioning

confidence: 99%

“…22 Simultaneous motion estimation and motion-compensated image reconstruction obtains the deformation vector fields (DVF) by warping the projection of the reference phase image to those of all other phases in an iterative process. 23,24 Hence, SMEIR can reconstruct any phase 4D-CBCT by explicitly considering the motion model between different phases, effectively suppressing the view aliasing artifacts caused by the limited number of projections. This will enable us to reevaluate dose to the PTV and interfractional plan adaptation for carbon ion therapy of lung cancer.…”

Section: Introductionmentioning

confidence: 99%

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Dosimetric evaluation of 4D‐CBCT reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for carbon ion therapy of lung cancer

et al. 2019

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Purpose Motion management is critical for the efficacy of carbon ion therapy for moving targets such as lung tumors. We evaluated the feasibility of using four‐dimensional cone beam computed tomography (4D‐CBCT) reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for dose calculation and accumulation in carbon ion treatment of lung cancer. Methods Motion‐compensated 4D‐CBCT images were reconstructed with the SMEIR algorithm to capture the most updated anatomy and motion with an updated interphase motion model on the treatment day. Projections of all CBCT phases were simulated from the planning 4D‐CT by the ray tracing technique. Treatment planning and dose calculation were performed with a GPU‐based Monte Carlo dose calculation software for carbon ion therapy. The treatment plan was optimized on the average computed tomography (CT) to obtain optimal intensity of the carbon ions. From the optimized plan, dose distributions on individual phases of 4D‐CT and 4D‐CBCT were calculated by the Monte Carlo‐based dose engine. Dose accumulation was performed on 4D‐CBCT images using deformable vector fields (DVF) generated by SMEIR. The accumulated planning target volume (PTV) dose based on 4D‐CBCT was then compared to the accumulated dose calculated on 4D‐CT, where the DVFs between different phases were obtained by the demons deformable registration algorithm. Results Dose value histograms (DVH) as well as absolute deviations of the maximum dose (ΔDmax), mean dose (ΔDmean), and dose coverage metrics (ΔV95% and ΔV100%) for PTV were quantitatively evaluated for the two sets of plans. Good agreement was found between the 4D‐CT and 4D‐CBCT‐based PTV‐DVH curves. The average values of ΔDmax, ΔDmean,ΔV95%, and ΔV100% calculated between the 4D‐CT and SMEIR‐4D‐CBCT‐based plans were 1.91%, 3.55%, 2.12%, and 1.15%, respectively, for the PTVs of ten patient case studies. Conclusions Based on these results, SMEIR‐reconstructed 4D‐CBCTs can potentially be used for motion estimation, dose evaluation, and adaptive treatment planning in lung cancer carbon ion therapy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dosimetric evaluation of 4D‐CBCT reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for carbon ion therapy of lung cancer

et al. 2019

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“…The relative distribution of the activity is tabulated in Table based on the biodistribution of [99mTc](Tc‐Dpa)‐(Cys‐PEG10kDa)‐PNA radiotracer in rat in the study by Leonidova et al Three different size spherical tumors (2, 3 and 4 mm in diameter) were placed in the liver region near the diaphragm. In this study, we refer to contrast as the ratio of activity in the tumor to the liver activity (as the tumor background) using the following formula:

C o n t r a s t = \frac{A c t i v i t y_{italicTumor}}{A c t i v i t y_{italicBackground}}

…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, projections of all different frames can be used to reconstruct a single final image . The advantages of the method using this algorithm have successfully been tested for simultaneous motion estimation and image reconstruction in 4D cone‐beam computerized tomography and 4D‐positron emission tomography . In this study, we modify this algorithm to enhance the quality of the images acquired by MPS for motion correction in small animal imaging.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous respiratory motion correction and image reconstruction in 4D‐multi pinhole small animal SPECT

et al. 2019

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Purpose: Respiratory motion in the chest region during single photon emission computed tomography (SPECT) is a major degrading factor that reduces the accuracy of image quantification. This effect is more notable when the tumor is very small, or the spatial resolution of the imaging system is less than the respiratory motion amplitude. Small animals imaging systems with sub-millimeter spatial resolution need more attention to the respiratory motion for quantitative studies. We developed a motion-embedded four-dimensional (4D)-multi pinhole SPECT (MPS) reconstruction algorithm for respiratory motion correction. This algorithm makes full use of projection statistics for reconstruction of every individual frame. Methods: The ROBY phantom with small tumors in liver was generated in eight different phases during one respiratory cycle. The MPS projections were modeled using a fast ray tracing method simulating an MPS acquisition. Individual frames were reconstructed and used for motion estimation. The Demons non-rigid registration algorithm was used to calculate deformation vector fields (DVFs) for simultaneous motion correction and image reconstruction. A motion-embedded 4D-MPS method was used to reconstruct images using all the projections and corresponding DVFs, simultaneously. The 4D-MPS reconstructed images were compared to the low-count single frame (LCSF) reconstructed image, the three-dimensional (3D)-MPS images reconstructed using individual frames, and post reconstruction registration (PRR) that aligns all individual phases to a reference frame using Demons-derived DVFs. The tumor volume relative error (TVE), tumor contrast relative error (TCE), and dice index (DI) for 2, 3, and 4 mm liver were calculated and compared for different reconstruction methods. Results: For the 4D-MPS reconstruction method, TVE was reduced and DI was higher compared to PRR, 3D-MPS, and LCSF. The extent of the improvement was higher for the small tumor size (i.e. 2 mm). For the biggest tumor in contrast 3 (i.e. 4 mm) TVE for 4D-MPS, PRR, 3D-MPS and, LCSF were 1.33%, 8%, 8%, and 14.67%, respectively. Conclusions: The results suggest that motion-embedded 4D-MPS method is an effective and practical way for respiratory motion correction. It reconstructs high quality gated frames while using all projection data to reconstruct each frame.

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“…Final reconstructed PET images are degraded in two different ways as a consequence of respiratory motion: (a) Respiration causes lesion smearing, image blurring and quality degradation in PET images, and errors in the quantification of FDG uptake; and (b) The mismatch between PET and CT images results in incorrect AC and induces artifacts in the attenuation‐corrected PET images …”

Section: Introductionmentioning

confidence: 99%

Attenuation correction in 4D‐PET using a single‐phase attenuation map and rigidity‐adaptive deformable registration

Kalantari

Wang

2017

Medical Physics

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Purpose Four-dimensional positron emission tomography (4D-PET) imaging is a potential solution to the respiratory motion effect in the thoracic region. Computed tomography (CT)-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference between 4D-PET and a single attenuation map from CT, typically available in routine clinical scanning, motion artifacts are observed in the attenuation-corrected PET images, leading to errors in tumor shape and uptake. We introduced a practical method to align single-phase CT with all other 4D-PET phases for AC. Methods A penalized non-rigid Demons registration between individual 4D-PET frames without AC provides the motion vectors to be used for warping single-phase attenuation map. The non-rigid Demons registration was used to derive deformation vector fields (DVFs) between PET matched with the CT phase and other 4D-PET images. While attenuated PET images provide useful data for organ borders such as those of the lung and the liver, tumors cannot be distinguished from the background due to loss of contrast. To preserve the tumor shape in different phases, an ROI-covering tumor was excluded from non-rigid transformation. Instead the mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of the tumor along with a non-rigid transformation of other organs. A 4D-XCAT phantom with spherical lung tumors, with diameters ranging from 10 to 40 mm, was used to evaluate the algorithm. The performance of the proposed hybrid method for attenuation map estimation was compared to 1) the Demons non-rigid registration only and 2) a single attenuation map based on quantitative parameters in individual PET frames. Results Motion-related artifacts were significantly reduced in the attenuation-corrected 4D-PET images. When a single attenuation map was used for all individual PET frames, the normalized root mean square error (NRMSE) values in tumor region were 49.3% (STD: 8.3%), 50.5% (STD: 9.3%), 51.8% (STD: 10.8%) and 51.5% (STD: 12.1%) for 10-mm, 20-mm, 30-mm and 40-mm tumors respectively. These errors were reduced to 11.9% (STD: 2.9%), 13.6% (STD: 3.9%), 13.8% (STD: 4.8%), and 16.7% (STD: 9.3%) by our proposed method for deforming the attenuation map. The relative errors in total lesion glycolysis (TLG) values were −0.25% (STD: 2.87%) and 3.19% (STD: 2.35%) for 30-mm and 40-mm tumors respectively in proposed method. The corresponding values for Demons method were 25.22% (STD: 14.79%) and 18.42% (STD: 7.06%). Our proposed hybrid method outperforms the Demons method especially for larger tumors. For tumors smaller than 20 mm, non-rigid transformation could also provide quantitative results. Conclusion Although non-AC 4D-PET frames include insignificant anatomical information, they are still useful to estimate the DVFs to align the attenuation map for accurate AC. The proposed hybrid method can recover the AC-related artifacts and provide quantitative ...

show abstract

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

Cited by 15 publications

References 59 publications

Dosimetric evaluation of 4D‐CBCT reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for carbon ion therapy of lung cancer

Dosimetric evaluation of 4D‐CBCT reconstructed by Simultaneous Motion Estimation and Image Reconstruction (SMEIR) for carbon ion therapy of lung cancer

Simultaneous respiratory motion correction and image reconstruction in 4D‐multi pinhole small animal SPECT

Attenuation correction in 4D‐PET using a single‐phase attenuation map and rigidity‐adaptive deformable registration

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