Dataset Information

Comparison of Step-and-Shoot and Continuous-Bed-Motion PET Modes of Acquisition for Limited-View Organ Scans.

ABSTRACT: Continuous-bed-motion (CBM) acquisition mode has been made commercially available in PET/CT scanners. CBM mode is designed for whole-body imaging, with a long scan length (multiple axial fields of view [aFOVs]) and short acquisition duration (2-3 min/aFOV). PET/CT has recently been used after ⁹⁰Y-microsphere therapy to quantify ⁹⁰Y activity distribution in the liver. Here we compared counting efficiencies along the bed-motion direction (z-axis) between CBM and step-and-shoot (SS) acquisition modes for limited-view organ scans, such as ⁹⁰Y PET/CT liver studies, that have short scan lengths (?2 aFOVs) and long acquisition durations (10-30 min/aFOV). Methods: The counting efficiencies, that is, analytic sensitivities, in SS mode (single-aFOV and multiple-aFOV scans) and CBM mode were theoretically derived and experimentally validated using a cylindric ⁶⁸Ge phantom. The sensitivities along the z-axis were compared between the SS and CBM modes. Results: The analytic and experimental count profiles were in good agreement, validating the analytic models. For fixed scan durations, the overall coincidence counting efficiency in CBM mode was lower (?60%) than those in SS modes, and the maximum sensitivity in CBM mode was 50% or less of that in 1-aFOV SS mode and 100% or less of that in 2-aFOV SS mode. Conclusion: The ability of CBM mode to tailor-fit the PET/CT scan length and local scan duration is not realized in studies with a short scan length (?30 cm) and long scan duration (20 min/aFOV for the scanner). SS acquisition mode is preferable to CBM mode for limited-view organ and count-starved scans, such as ⁹⁰Y PET/CT liver scans, because of the higher counting efficiency of SS mode, which leads to better image quality and quantification precision.

SUBMITTER: Siman W

PROVIDER: S-EPMC5721725 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Comparison of Step-and-Shoot and Continuous-Bed-Motion PET Modes of Acquisition for Limited-View Organ Scans.

Siman Wendy W Kappadath S Cheenu SC

Journal of nuclear medicine technology 20171017 4

Continuous-bed-motion (CBM) acquisition mode has been made commercially available in PET/CT scanners. CBM mode is designed for whole-body imaging, with a long scan length (multiple axial fields of view [aFOVs]) and short acquisition duration (2-3 min/aFOV). PET/CT has recently been used after 90Y-microsphere therapy to quantify 90Y activity distribution in the liver. Here we compared counting efficiencies along the bed-motion direction (z-axis) between CBM and step-a ...[more]

PMID: 29042468

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Project description:Objective.This work aims to generate realistic anatomical deformations from static patient scans. Specifically, we present a method to generate these deformations/augmentations via deep learning driven respiratory motion simulation that provides the ground truth for validating deformable image registration (DIR) algorithms and driving more accurate deep learning based DIR.Approach.We present a novel 3D Seq2Seq deep learning respiratory motion simulator (RMSim) that learns from 4D-CT images and predicts future breathing phases given a static CT image. The predicted respiratory patterns, represented by time-varying displacement vector fields (DVFs) at different breathing phases, are modulated through auxiliary inputs of 1D breathing traces so that a larger amplitude in the trace results in more significant predicted deformation. Stacked 3D-ConvLSTMs are used to capture the spatial-temporal respiration patterns. Training loss includes a smoothness loss in the DVF and mean-squared error between the predicted and ground truth phase images. A spatial transformer deforms the static CT with the predicted DVF to generate the predicted phase image. 10-phase 4D-CTs of 140 internal patients were used to train and test RMSim. The trained RMSim was then used to augment a public DIR challenge dataset for training VoxelMorph to show the effectiveness of RMSim-generated deformation augmentation.Main results.We validated our RMSim output with both private and public benchmark datasets (healthy and cancer patients). The structure similarity index measure (SSIM) for predicted breathing phases and ground truth 4D CT images was 0.92 ± 0.04, demonstrating RMSim's potential to generate realistic respiratory motion. Moreover, the landmark registration error in a public DIR dataset was improved from 8.12 ± 5.78 mm to 6.58mm ± 6.38 mm using RMSim-augmented training data.Significance.The proposed approach can be used for validating DIR algorithms as well as for patient-specific augmentations to improve deep learning DIR algorithms. The code, pretrained models, and augmented DIR validation datasets will be released athttps://github.com/nadeemlab/SeqX2Y.

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Dataset Information

Comparison of Step-and-Shoot and Continuous-Bed-Motion PET Modes of Acquisition for Limited-View Organ Scans.

Publications

Comparison of Step-and-Shoot and Continuous-Bed-Motion PET Modes of Acquisition for Limited-View Organ Scans.

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