4D numerical observer for lesion detection in respiratory‐gated PET

Lorsakul, Auranuch; Li, Quanzheng; Trott, Cathryn M.; Hoog, Christopher; Petibon, Yoann; Ouyang, Jinsong; Laine, Andrew F.; Fakhri, Georges El

doi:10.1118/1.4895975

Cited by 5 publications

(4 citation statements)

References 65 publications

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“…Our numerical observer included two processing steps as shown in Fig. 1 [7][8][9][10]. First, a Channelized Hotelling Observer (CHO) model accounted for preprocessing on a spectral image in energy bin j, f j , where j = 1,2,..,N. A set of Laguerre-Gaussian (LG) channels, U, was used to extract the main features of a spectral image to compute a channel output,…”

Section: A Numerical Observermentioning

confidence: 99%

Numerical observer for objective assessment on carotid plaque using spectral CT

Lorsakul

Fakhri

Ouyang

et al. 2014

2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

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We developed a novel numerical observer with signal variability to assess feature discrimination and compare the classification performance of carotid plaque using multienergy, dual-energy, and conventional CT images. Our numerical observer was performed in two processing steps. First, a preprocessing step accounted for each spectral image bin using Channelized Hotelling Observer with a set of Laguerre-Gaussian channels, localized prewhitening, and localized matched filtering. The intermediate score of test statistics was obtained for each spectral image bin. The scores of all the CHOs were formed as a vector. Second, in an integration step, the test statistic vectors were used to make the classification decision of plaque features using the one-dimensional Hotelling Observer with additional prewhitening and matched filtering, yielding the figure-of-merit computation. To mimic a scenario in the clinical classification task, the known statistical distribution of signal variability was included. The validation of distinguishing two different plaque features in a known background was performed on simulated images using a digital anthropomorphic phantom with known compositions of inserted carotid plaques. The comparison of the performance for the calcified-plaque and fatty-mixed-plaque identification task showed that multi-energy CT outperformed dual-energy and conventional CT systems by 153.4%-174.3% (all p < 0.01). For the differentiation task of the calcified plaque in the presence of iodinated blood, multi-energy CT yielded superior performance to the other CT systems by 158.1%-173.8% (all p < 0.01). This proposed numerical observer with signal variability is an appropriate approach for the classification performance and can be extended to other clinical tasks such as kidney or urinary stone identification applications.

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Section: A Numerical Observermentioning

confidence: 99%

Numerical observer for objective assessment on carotid plaque using spectral CT

Lorsakul

Fakhri

Ouyang

et al. 2014

2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

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“…However, these phantoms have limited ability to model patient anatomy and physiology. Thus, to improve clinical realism, anthropomorphic phantom-based studies, such as using the XCAT phantom 8 , have been conducted 9 . However, recent studies suggest that anthropomorphic phantoms may have limitations in modeling patient physiology 1 .…”

Section: Introductionmentioning

confidence: 99%

“…However, recent studies suggest that anthropomorphic phantoms may have limitations in modeling patient physiology 1 . Another limitation of existing simulation studies is that the tumor is typically modeled as a spherically shaped structure with limited incorporation of intra-tumor heterogeneity 7,9,10 . To incorporate variabilities in patient population and tumor models for more clinically relevant evaluation, Leung et al 1 developed a simulation-based strategy that uses patient images as backgrounds and generates a wide variety of clinically observed tumor types.…”

Section: Introductionmentioning

confidence: 99%

Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images

Liu

Laforest

Mhlanga

et al. 2021

Preprint

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Objective evaluation of new and improved methods for PET imaging requires access to images with ground truth, as can be obtained through simulation studies. However, for these studies to be clinically relevant, it is important that the simulated images are clinically realistic. In this study, we develop a stochastic and physics-based method to generate realistic oncological two-dimensional (2-D) PET images, where the ground-truth tumor properties are known. The developed method extends upon a previously proposed approach 1 . The approach captures the observed variabilities in tumor properties from actual patient population. Further, we extend that approach to model intra-tumor heterogeneity using a lumpy object model. To quantitatively evaluate the clinical realism of the simulated images, we conducted a human-observer study. This was a two-alternative forced-choice (2AFC) study with trained readers (five PET physicians and one PET physicist). Our results showed that the readers had an average of ∼ 50% accuracy in the 2AFC study. Further, the developed simulation method was able to generate wide varieties of clinically observed tumor types. These results provide evidence for the application of this method to 2-D PET imaging applications, and motivate development of this method to generate 3-D PET images.

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“…A numerical observer that estimates the cardiac motion field using a deformable mesh model was proposed for cardiac gated SPECT . For respiratory-gated positron emission tomography (PET) imaging, applying 3D or 2D CHO in the spatial domain followed by a second Hotelling observer in the temporal domain has been proposed for the detection of pulmonary lesions (Lorsakul et al 2013). In this study, we investigated the extension of the CHO to include the time dimension by developing two mathematical observers for the task of detecting regional wall motion abnormalities.…”

Section: Introductionmentioning

confidence: 99%

Development of 4D mathematical observer models for the task-based evaluation of gated myocardial perfusion SPECT

Lee

Frey²,

Tsui³

2015

Phys. Med. Biol.

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This paper presents two 4D mathematical observer models for the detection of motion defects in 4D gated medical images. Their performance was compared with results from human observers in detecting a regional motion abnormality in simulated 4D gated myocardial perfusion (MP) SPECT images. The first 4D mathematical observer model extends the conventional channelized Hotelling observer (CHO) based on a set of 2D spatial channels and the second is a proposed model that uses a set of 4D space-time channels. Simulated projection data were generated using the 4D NURBS-based cardiac-torso (NCAT) phantom with 16 gates/cardiac cycle. The activity distribution modelled uptake of (99m)Tc MIBI with normal perfusion and a regional wall motion defect. An analytical projector was used in the simulation and the filtered backprojection (FBP) algorithm was used in image reconstruction followed by spatial and temporal low-pass filtering with various cut-off frequencies. Then, we extracted 2D image slices from each time frame and reorganized them into a set of cine images. For the first model, we applied 2D spatial channels to the cine images and generated a set of feature vectors that were stacked for the images from different slices of the heart. The process was repeated for each of the 1,024 noise realizations, and CHO and receiver operating characteristics (ROC) analysis methodologies were applied to the ensemble of the feature vectors to compute areas under the ROC curves (AUCs). For the second model, a set of 4D space-time channels was developed and applied to the sets of cine images to produce space-time feature vectors to which the CHO methodology was applied. The AUC values of the second model showed better agreement (Spearman's rank correlation (SRC) coefficient = 0.8) to human observer results than those from the first model (SRC coefficient = 0.4). The agreement with human observers indicates the proposed 4D mathematical observer model provides a good predictor of the performance of human observers in detecting regional motion defects in 4D gated MP SPECT images. The result supports the use of the observer model in the optimization and evaluation of 4D image reconstruction and compensation methods for improving the detection of motion abnormalities in 4D gated MP SPECT images.

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4D numerical observer for lesion detection in respiratory‐gated PET

Cited by 5 publications

References 65 publications

Numerical observer for objective assessment on carotid plaque using spectral CT

Numerical observer for objective assessment on carotid plaque using spectral CT

Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images

Development of 4D mathematical observer models for the task-based evaluation of gated myocardial perfusion SPECT

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