A deep learning anthropomorphic model observer for a detection task in PET.

Background: Lesion detection is one of the most important clinical tasks in positron emission tomography (PET) for oncology. An anthropomorphic model observer (MO) designed to replicate human observers (HOs) in a detection task is an important tool for assessing task-based image quality. The channelized Hotelling observer (CHO) has been the most popular anthropomorphic MO.

Data driven surrogate signal extraction for dynamic PET using selective PCA: time windows versus the combination of components.

Respiratory motion correction is beneficial in positron emission tomography (PET), as it can reduce artefacts caused by motion and improve quantitative accuracy. Methods of motion correction are commonly based on a respiratory trace obtained through an external device (like the real time position management system) or a data driven method, such as those based on dimensionality reduction techniques (for instance principal component analysis (PCA)). PCA itself being a linear transformation to the axis of greatest variation.

Ecotoxicological evaluation of surface waters in Northern Namibia.

The increasing pressure on freshwater systems due to intensive anthropogenic use is a big challenge in central-northern Namibia and its catchment areas, the Kunene and the Kavango Rivers, and the Cuvelai-Etosha Basin, that provide water for more than 1 million people. So far, there is no comprehensive knowledge about the ecological status and only few knowledge about the water quality. Therefore, it is crucial to learn about the state of the ecosystem and the ecological effects of pollutants to ensure the safe use of these resources.

Sequential deep learning image enhancement models improve diagnostic confidence, lesion detectability, and image reconstruction time in PET.

Background: Investigate the potential benefits of sequential deployment of two deep learning (DL) algorithms namely DL-Enhancement (DLE) and DL-based time-of-flight (ToF) (DLT). DLE aims to enhance the rapidly reconstructed ordered-subset-expectation-maximisation algorithm (OSEM) images towards block-sequential-regularised-expectation-maximisation (BSREM) images, whereas DLT aims to improve the quality of BSREM images reconstructed without ToF. As the algorithms differ in their purpose, sequential application may allow benefits from each to be combined.

Results of an international interlaboratory study on dioxin-like activities in drinking-, river surface- and wastewater using DR CALUX bioassay.

Aquatic animals and consumers of aquatic animals are exposed to increasingly complex mixtures of known and as-yet-unknown chemicals with dioxin-like toxicities in the water cycle. Effect- and cell-based bioanalysis can cover known and yet unknown dioxin and dioxin-like compounds as well as complex mixtures thereof but need to be standardized and integrated into international guidelines for environmental testing. In an international laboratory testing (ILT) following ISO/CD 24295 as standard procedure for rat cell-based DR CALUX un-spiked and spiked extracts of drinking-, surface-, and wastewater were validated to generate precision data for the development of the full ISO-standard.

Phantom and methodology for comparison of small lesion detectability in PET.

Purpose: The main goal of this work is to describe a phantom design, data acquisition and data analysis methodology enabling comparison of small lesion detectability between PET imaging systems and reconstruction algorithms. Several methods are currently available to characterize intrinsic and image quality performance, but none focus exclusively on small lesion detectability.

Methods: We previously developed a small-lesion detection phantom and described initial results using a head-size phantom.

Deep learning-based time-of-flight (ToF) image enhancement of non-ToF PET scans.

Purpose: To improve the quantitative accuracy and diagnostic confidence of PET images reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image enhancement (DL-ToF).

Methods: A total of 273 [F]-FDG PET scans were used, including data from 6 centres equipped with GE Discovery MI ToF scanners. PET data were reconstructed using the block-sequential-regularised-expectation-maximisation (BSREM) algorithm with and without ToF.

Image enhancement of whole-body oncology [F]-FDG PET scans using deep neural networks to reduce noise.

Purpose: To enhance the image quality of oncology [F]-FDG PET scans acquired in shorter times and reconstructed by faster algorithms using deep neural networks.

Methods: List-mode data from 277 [F]-FDG PET/CT scans, from six centres using GE Discovery PET/CT scanners, were split into ¾-, ½- and ¼-duration scans. Full-duration datasets were reconstructed using the convergent block sequential regularised expectation maximisation (BSREM) algorithm.

The QIBA Profile for FDG PET/CT as an Imaging Biomarker Measuring Response to Cancer Therapy.

The Quantitative Imaging Biomarkers Alliance (QIBA) Profile for fluorodeoxyglucose (FDG) PET/CT imaging was created by QIBA to both characterize and reduce the variability of standardized uptake values (SUVs). The Profile provides two complementary claims on the precision of SUV measurements. First, tumor glycolytic activity as reflected by the maximum SUV (SUV) is measurable from FDG PET/CT with a within-subject coefficient of variation of 10%-12%.

Sign determination methods for the respiratory signal in data-driven PET gating.

Patient respiratory motion during PET image acquisition leads to blurring in the reconstructed images and may cause significant artifacts, resulting in decreased lesion detectability, inaccurate standard uptake value calculation and incorrect treatment planning in radiation therapy. To reduce these effects data can be regrouped into (nearly) 'motion-free' gates prior to reconstruction by selecting the events with respect to the breathing phase. This gating procedure therefore needs a respiratory signal: on current scanners it is obtained from an external device, whereas with data driven (DD) methods it can be directly obtained from the raw PET data.

Evaluation of lesion detectability in positron emission tomography when using a convergent penalized likelihood image reconstruction method.

We have previously developed a convergent penalized likelihood (PL) image reconstruction algorithm using the relative difference prior (RDP) and showed that it achieves more accurate lesion quantitation compared to ordered subsets expectation maximization (OSEM). We evaluated the detectability of low-contrast liver and lung lesions using the PL-RDP algorithm compared to OSEM. We performed a two-alternative forced choice study using a channelized Hotelling observer model that was previously validated against human observers.

Technical Note: Rod phantom analysis for comparison of PET detector sampling and reconstruction methods.

Purpose: This investigation aimed to develop a scanner quantification performance methodology and compare multiple metrics between two scanners under different imaging conditions. Most PET scanners are designed to work over a wide dynamic range of patient imaging conditions. Clinical constraints, however, often impact the realization of the entitlement performance for a particular scanner design.

Clinical evaluation of a block sequential regularized expectation maximization reconstruction algorithm in 18F-FDG PET/CT studies.

Purpose: To investigate the clinical performance of a block sequential regularized expectation maximization (BSREM) penalized likelihood reconstruction algorithm in oncologic PET/computed tomography (CT) studies.

Methods: A total of 410 reconstructions of 41 fluorine-18 fluorodeoxyglucose-PET/CT studies of 41 patients with a total of 2010 lesions were analyzed by two experienced nuclear medicine physicians. Images were reconstructed with BSREM (with four different β values) or ordered subset expectation maximization (OSEM) algorithm with/without time-of-flight (TOF/non-TOF) corrections.

A phantom design for assessment of detectability in PET imaging.

Purpose: The primary clinical role of positron emission tomography (PET) imaging is the detection of anomalous regions of (18)F-FDG uptake, which are often indicative of malignant lesions. The goal of this work was to create a task-configurable fillable phantom for realistic measurements of detectability in PET imaging. Design goals included simplicity, adjustable feature size, realistic size and contrast levels, and inclusion of a lumpy (i.

Clinical image quality perception and its relation to NECR measurements in PET.

Background: The purpose of this study is to describe a clinical relation of noise equivalent count rate (NECR) - an objective measurement of positron emission tomography (PET) systems - measured in a large number of patients, to clinical image quality of PET and their relation to 18F-fluoro-2-deoxyglucose (FDG) activity and patient's weight.

Methods: A total of 71 consecutive patients were evaluated in this retrospective study. All data was automatically analysed using Matlab to estimate the noise equivalent count rate.

Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET.

Ordered subset expectation maximization (OSEM) is the most widely used algorithm for clinical PET image reconstruction. OSEM is usually stopped early and post-filtered to control image noise and does not necessarily achieve optimal quantitation accuracy. As an alternative to OSEM, we have recently implemented a penalized likelihood (PL) image reconstruction algorithm for clinical PET using the relative difference penalty with the aim of improving quantitation accuracy without compromising visual image quality.

Assessment of patient selection criteria for quantitative imaging with respiratory-gated positron emission tomography.

The objective of this investigation was to propose techniques for determining which patients are likely to benefit from quantitative respiratory-gated imaging by correlating respiratory patterns to changes in positron emission tomography (PET) metrics. Twenty-six lung and liver cancer patients underwent PET/computed tomography exams with recorded chest/abdominal displacements. Static and adaptive amplitude-gated [[Formula: see text]]fluoro-D-glucose (FDG) PET images were generated from list-mode acquisitions.

Dose Optimization in TOF-PET/MR Compared to TOF-PET/CT.

Purpose: To evaluate the possible activity reduction in FDG-imaging in a Time-of-Flight (TOF) PET/MR, based on cross-evaluation of patient-based NECR (noise equivalent count rate) measurements in PET/CT, cross referencing with phantom-based NECR curves as well as initial evaluation of TOF-PET/MR with reduced activity.

Materials And Methods: A total of 75 consecutive patients were evaluated in this study. PET/CT imaging was performed on a PET/CT (time-of-flight (TOF) Discovery D 690 PET/CT).

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study.

Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [(18)F]FDG.

Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging.

Purpose: Respiratory-correlated positron emission tomography (PET/CT) 4D PET/CT is used to mitigate errors from respiratory motion; however, the optimal CT attenuation correction (CTAC) method for 4D PET/CT is unknown. The authors performed a phantom study to evaluate the quantitative performance of CTAC methods for 4D PET/CT in the ground truth setting.

Methods: A programmable respiratory motion phantom with a custom movable insert designed to emulate a lung lesion and lung tissue was used for this study.

Characterization of the impact to PET quantification and image quality of an anterior array surface coil for PET/MR imaging.

Object: The aim of this study was to determine the impact to PET quantification, image quality and possible diagnostic impact of an anterior surface array used in a combined PET/MR imaging system.

Materials And Methods: An extended oval phantom and 15 whole-body FDG PET/CT subjects were re-imaged for one bed position following placement of an anterior array coil at a clinically realistic position. The CT scan, used for PET attenuation correction, did not include the coil.

MR-driven metal artifact reduction in PET/CT.

Among the proposed system architectures capable of delivering positron emission tomography/magnetic resonance (PET/MR) datasets, tri-modality systems open an interesting field in which the synergies between these modalities can be exploited to address some of the problems encountered in standalone systems. In this paper we present a feasibility study of the correction of dental streak artifacts in computed tomography (CT)-based attenuation correction images using complementary MR data. The frequency and severity of metal artifacts in oncology patients was studied by inspecting the CT scans of 152 patients examined at our hospital.

PET/MR imaging of bone lesions--implications for PET quantification from imperfect attenuation correction.

Purpose: Accurate attenuation correction (AC) is essential for quantitative analysis of PET tracer distribution. In MR, the lack of cortical bone signal makes bone segmentation difficult and may require implementation of special sequences. The purpose of this study was to evaluate the need for accurate bone segmentation in MR-based AC for whole-body PET/MR imaging.

Quiescent period respiratory gating for PET/CT.

Purpose: To minimize respiratory motion artifacts, this work proposes quiescent period gating (QPG) methods that extract PET data from the end-expiration quiescent period and form a single PET frame with reduced motion and improved signal-to-noise properties.

Methods: Two QPG methods are proposed andevaluated. Histogram-based quiescent period gating (H-QPG) extracts a fraction of PET data determined by a window of the respiratory displacement signal histogram.

Image Reconstruction for a Partially Collimated Whole Body PET Scanner.

Partially collimated PET systems have less collimation than conventional 2-D systems and have been shown to offer count rate improvements over 2-D and 3-D systems. Despite this potential, previous efforts have not established image-based improvements with partial collimation and have not customized the reconstruction method for partially collimated data. This work presents an image reconstruction method tailored for partially collimated data.