Compensating for Patient Respiration in PET/CT Imaging with the Registered and Summed Phases (RASP) Procedure

Kinahan, Paul E.; MacDonald, L.R.; Ng, Lydia; Alessio, Adam M.; Segars, Paul; Tsui, B.M.W.; Pathak, Sayan

doi:10.1109/isbi.2006.1625115

Cited by 11 publications

(11 citation statements)

References 9 publications

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“…These results are in agreement with previous studies by others [10]. A respiratory motion corrected image was obtained based on previously proposed approaches by summing the individually reconstructed synchronized frame images following deformable image registration [5], [6]. As expected the performance of this approach in terms of SNR as well as in determining lesion location and/or size was similar to that of the single respiratory synchronized frame using the same count statistics as the motion average image.…”

Section: Discussionsupporting

confidence: 89%

“…Therefore motion compensation approaches have been developed allowing the combination of these synchronized datasets to a particular part of the respiratory cycle, hence making use of all the available statistics. Most existing compensation techniques follow a register-and-sum approach, with transformation maps derived either from 4-D CT or gated PET datasets [5]- [7]. Assuming an afflne motion model, these transformations have been applied to correct the raw data prior to reconstruction [7], [8].…”

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confidence: 99%

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Super-Resolution in Respiratory Synchronized Positron Emission Tomography

Wallach

Lamare²,

Kontaxakis³

et al. 2012

IEEE Trans. Med. Imaging

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Abstract-Respiratorymotion is a major source of reduced quality in positron emission tomography (PET). In order to minimize its effects, the use of respiratory synchronized acquisitions, leading to gated frames, has been suggested. Such frames, however, are of low signal-to-noise ratio (SNR) as they contain reduced statistics. Super-resolution (SR) techniques make use of the motion in a sequence of images in order to improve their quality. They aim at enhancing a low-resolution image belonging to a sequence of images representing different views of the same scene. In this work, a maximum a posteriori (MAP) super-resolution algorithm has been implemented and applied to respiratory gated PET images for motion compensation. An edge preserving Huber regularization term was used to ensure convergence. Motion fields were recovered using a B-spline based elastic registration algorithm. The performance of the SR algorithm was evaluated through the use of both simulated and clinical datasets by assessing image SNR, as well as the contrast, position and extent of the different lesions. Results were compared to summing the registered synchronized frames on both simulated and clinical datasets. The super-resolution image had higher SNR (by a factor of over 4 on average) and lesion contrast (by a factor of 2) than the single respiratory synchronized frame using the same reconstruction matrix size. In comparison to the motion corrected or the motion free images a similar SNR was obtained, while improvements of up to 20% in the recovered lesion size and contrast were measured. Finally, the recovered lesion locations on the SR images were systematically closer to the true simulated lesion positions. These observations concerning the SNR, lesion contrast and size were confirmed on two clinical datasets included in the study. In conclusion, the use of SR techniques applied to respiratory motion synchronized images lead to motion compensation combined with improved image SNR and contrast, without any increase in the overall acquisition times. Index Terms-Four-dimensional(4-D) positron emission tomography, respiratory motion, super-resolution.

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Section: Discussionsupporting

confidence: 89%

mentioning

confidence: 99%

Super-Resolution in Respiratory Synchronized Positron Emission Tomography

Wallach

Lamare²,

Kontaxakis³

et al. 2012

IEEE Trans. Med. Imaging

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“…The first of these includes classifying iodine versus bone using the principles illustrated in Figure 5. This approach can be used to account for soft tissue, bone, and any third material, such as iodine (52). …”

Section: New Algorithms For Image Reconstruction and Data Processingmentioning

confidence: 99%

Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems

Vaquero

Kinahan

2015

Annu. Rev. Biomed. Eng.

286

183

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Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.

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“…One of the difficulties with this approach, however, is the multitude of noisy images that are produced. This has led to the development of more sophisticated methods that remove respiratory motion artifacts of both types while preserving quantitative accuracy and without increasing noise [38]. …”

Section: Technical Developments For Multimodal Imagingmentioning

confidence: 99%

Multimodality molecular imaging of the lung

Chen

Kinahan

2014

Clin Transl Imaging

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Lung diseases cause significant morbidity and mortality and lead to high healthcare utilization. However, few lung disease-specific biomarkers are available to accurately monitor disease activity for the purposes of clinical management or drug development. Advances in cross-modal imaging technologies, such as combined positron emission tomography (PET) and magnetic resonance (MR) imaging scanners and PET or single-photon emission computed tomography (SPECT) combined with computed tomography (CT), may aid in the development of noninvasive, molecular-based biomarkers for lung disease. However, the lungs pose particular challenges in obtaining accurate quantification of imaging data due to the low density of the organ and breathing motion. This review covers the basic physics underlying PET, SPECT, CT, and MR lung imaging and presents technical considerations for multimodal imaging with regard to PET and SPECT quantification. It also includes a brief review of the current and potential clinical applications for these hybrid imaging technologies.

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Compensating for Patient Respiration in PET/CT Imaging with the Registered and Summed Phases (RASP) Procedure

Cited by 11 publications

References 9 publications

Super-Resolution in Respiratory Synchronized Positron Emission Tomography

Super-Resolution in Respiratory Synchronized Positron Emission Tomography

Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems

Multimodality molecular imaging of the lung

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