Respiratory-Induced Errors in Tumor Quantification and Delineation in CT Attenuation-Corrected PET Images: Effects of Tumor Size, Tumor Location, and Respiratory Trace: A Simulation Study Using the 4D XCAT Phantom

Geramifar, Parham; Zafarghandi, Mojtaba Shamsaie; Ghafarian, Pardis; Rahmim, Arman; Ay, Mohammad Reza

doi:10.1007/s11307-013-0656-5

Cited by 25 publications

(24 citation statements)

References 49 publications

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“…However, respiratory motion still is a largely neglected issue in clinical SPECT, in contrast to PET and preclinical SPECT . Quantitative images acquired without respiratory motion correction can potentially lead to inaccuracies in the estimated activity and consequently in the absorbed dose estimates …”

Section: Introductionmentioning

confidence: 99%

“…4,5 Quantitative images acquired without respiratory motion correction can potentially lead to inaccuracies in the estimated activity and consequently in the absorbed dose estimates. [6][7][8] Respiratory motion compensation in PET has received substantial attention in the literature [9][10][11][12][13] with applications in specific thoracic areas like the lungs, 9,11 the heart 14,15 and more generic approaches. 12,[16][17][18] In SPECT, respiratory motion compensation techniques are largely focused on myocardial imaging, [19][20][21][22] which is still its major application area.…”

Section: Introductionmentioning

confidence: 99%

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Impact of respiratory motion and acquisition settings on SPECT liver dosimetry for radioembolization

2017

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of respiratory motion and acquisition settings on SPECT liver dosimetry for radioembolization

2017

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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 ...

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“…The same group reported variation in tumor uptake during different respiratory phases due to the misregistration of PET and CT, and inaccurate attenuation correction in certain phases (Erdi et al ., 2004). Simulation studies have showed that respiratory motion-induced errors in tumor quantification and delineation highly depend on motion amplitude, tumor location, background activity and tumor size, with a 129% overestimation of volume for small liver tumors (Geramifar et al ., 2013; Park et al ., 2008). Severe artifacts have been reported for lesions near the lung base, where motion is more pronounced due to breathing (Cohade et al ., 2003; Geramifar et al ., 2013; Osman et al ., 2003; Park et al ., 2008).…”

Section: Introductionmentioning

confidence: 99%

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

Kalantari¹,

Li²,

Mu³

et al. 2016

Phys. Med. Biol.

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In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: 1) the reconstruction algorithms do not make full use of projection statistics; and 2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10 to 40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

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Respiratory-Induced Errors in Tumor Quantification and Delineation in CT Attenuation-Corrected PET Images: Effects of Tumor Size, Tumor Location, and Respiratory Trace: A Simulation Study Using the 4D XCAT Phantom

Abstract: The respiratory motion-induced errors in tumor quantification and delineation are highly dependent upon the motion amplitude, tumor location, tumor size, and choice of the attenuation map for PET image attenuation correction.

Cited by 25 publications

References 49 publications

Impact of respiratory motion and acquisition settings on SPECT liver dosimetry for radioembolization

Impact of respiratory motion and acquisition settings on SPECT liver dosimetry for radioembolization

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

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

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