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Abstract Radiomics analysis of [18F]-fluorodeoxyglucose ([18F]-FDG) PET images could be leveraged for personalised cancer medicine. However, the inherent sensitivity of radiomic features to intensity discretisation and voxel interpolation complicates its clinical translation. In this work, we evaluated the robustness of tumour [18F]-FDG-PET radiomic features to 174 different variations in intensity resolution or voxel size, and determined whether implementing parameter range conditions or dependency corrections could improve their robustness. Using 485 patient images spanning three cancer types: non-small cell lung cancer (NSCLC), melanoma, and lymphoma, we observed features were more sensitive to intensity discretisation than voxel interpolation, especially texture features. In most of our investigations, the majority of non-robust features could be made robust by applying parameter range conditions. Correctable features, which were generally fewer than conditionally robust, showed systematic dependence on bin configuration or voxel size that could be minimised by applying corrections based on simple mathematical equations. Melanoma images exhibited limited robustness and correctability relative to NSCLC and lymphoma. Our study provides an in-depth characterisation of the sensitivity of [18F]-FDG-PET features to image processing variations and reinforces the need for careful selection of imaging biomarkers prior to any clinical application.

Abstract Background To study the reproducibility of 23Na magnetic resonance imaging (MRI) measurements from breast tissue in healthy volunteers. Methods Using a dual-tuned bilateral 23Na/1H breast coil at 3-T MRI, high-resolution 23Na MRI three-dimensional cones sequences were used to quantify total sodium concentration (TSC) and fluid-attenuated sodium concentration (FASC). B1-corrected TSC and FASC maps were created. Two readers manually measured mean, minimum and maximum TSC and mean FASC values using two sampling methods: large regions of interest (LROIs) and small regions of interest (SROIs) encompassing fibroglandular tissue (FGT) and the highest signal area at the level of the nipple, respectively. The reproducibility of the measurements and correlations between density, age and FGT apparent diffusion coefficient (ADC) values were evaluatedss. Results Nine healthy volunteers were included. The inter-reader reproducibility of TSC and FASC using SROIs and LROIs was excellent (intraclass coefficient range 0.945−0.979, p

Abstract Purpose Tracking cells in vivo using imaging can provide non-invasive information to understand the pharmacology, efficacy, and safety of novel cell therapies. Zirconium-89 (t 1/2 = 78.4 h) has recently been used to synthesize [89Zr]Zr(oxinate)4 for cell tracking using positron emission tomography (PET). This work presents an in vitro approach to estimate the detection limit for in vivo PET imaging of Jurkat T cells directly labeled with [89Zr]Zr(oxinate)4 utilizing clinical PET/CT and PET/MRI. Methods Jurkat T cells were labeled with varying concentrations of [89Zr]Zr(oxinate)4 to generate different cell-specific activities (0.43–31.91 kBq/106 cells). Different concentrations of labeled cell suspensions (104, 105, and 106 cells) were seeded on 6-well plates and into a 3 × 3 cubic-well plate with 1 cm3 cubic wells as a gel matrix. Plates were imaged on clinical PET/CT and PET/MRI scanners for 30 min. The total activity in each well was determined by drawing volumes of interest over each well on PET images. The total cell-associated activity was measured using a well counter and correlated with imaging data. Simulations for non-specific signal were performed to model the effect of non-specific radioactivity on detection. Results Using this in vitro model, the lowest cell number that could be visualized on 6-well plate images was 6.8 × 104, when the specific activity was 27.8 kBq/106 cells. For the 3 × 3 cubic-well, a plate of 3.3 × 104 cells could be detected on images with a specific activity of 15.4 kBq/106 cells. Conclusion The results show the feasibility of detecting [89Zr]Zr(oxinate)4-labeled Jurkat T cells on clinical PET systems. The results provide a best-case scenario, as in vivo detection using PET/CT or PET/MRI will be affected by cell number, specific activity per cell, the density of cells within the target volume, and non-specific signal. This work has important implications for cell labeling studies in patients, particularly when using radiosensitive cells (e.g., T cells), which require detection of low cell numbers while minimizing radiation dose per cell.

Abstract Purpose While the aetiology of rheumatoid arthritis (RA) remains unclear, many of the inflammatory components are well characterised. For diagnosis and therapy evaluation, in vivo insight into these processes would be valuable. Various imaging probes have shown value including dynamic contrast-enhanced (DCE) MRI and PET/CT using 18F-fluorodeoxyglucose (18F-FDG) or tracers targeting the translocator protein (TSPO). To evaluate 18F-GE-180, a novel TSPO PET tracer, for detecting and quantifying disease activity in RA, we compared 18F-GE-180 uptake with that of 18F-FDG and DCE-MRI measures of inflammation. Methods Eight RA patients with moderate-to-high, stable disease activity and active disease in at least one wrist were included in this study (NCT02350426). Participants underwent PET/CT examinations with 18F-GE-180 and 18F-FDG on separate visits, covering the shoulders and from the pelvis to the feet, including hands and wrists. DCE-MRI was performed on one affected hand. Uptake was compared visually between tracers as judged by an experienced radiologist and quantitatively using the maximum standardised uptake value (SUVmax). Uptake for both tracers was correlated with DCE-MRI parameters of inflammation, including the volume transfer coefficient K trans using Pearson correlation (r). Results PET/CT imaging with 18F-GE-180 in RA patients showed marked extra-synovial uptake around the affected joints. Overall sensitivity for detecting clinically affected joints was low (14%). 18F-GE-180 uptake did not or only weakly correlate with DCE-MRI parameters in the wrist (r = 0.09–0.31). 18F-FDG showed higher sensitivity for detecting symptomatic joints (34%), as well as strong positive correlation with DCE-MRI parameters (SUVmax vs. K trans: r = 0.92 for wrist; r = 0.68 for metacarpophalangeal joints). Conclusions The correlations between DCE-MRI parameters and 18F-FDG uptake support use of this PET tracer for quantification of inflammatory burden in RA. The TSPO tracer 18F-GE-180, however, has shown limited use for the investigation of RA due to its poor sensitivity and ability to quantify disease activity in RA.

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0.99, p

Adrenal lesions present a significant diagnostic burden for both radiologists and endocrinologists, especially with the increasing number of adrenal ‘incidentalomas’ detected on modern computed tomography (CT) or magnetic resonance imaging (MRI). A key objective is the reliable distinction of benign disease from either primary adrenal malignancy (e.g., adrenocortical carcinoma or malignant forms of pheochromocytoma/paraganglioma (PPGL)) or metastases (e.g., bronchial, renal). Benign lesions may still be associated with adverse sequelae through autonomous hormone hypersecretion (e.g., primary aldosteronism, Cushing’s syndrome, phaeochromocytoma). Here, identifying a causative lesion, or lateralising the disease to a single adrenal gland, is key to effective management, as unilateral adrenalectomy may offer the potential for curing conditions that are typically associated with significant excess morbidity and mortality. This review considers the evolving role of positron emission tomography (PET) imaging in addressing the limitations of traditional cross-sectional imaging and adjunctive techniques, such as venous sampling, in the management of adrenal disorders. We review the development of targeted molecular imaging to the adrenocortical enzymes CYP11B1 and CYP11B2 with different radiolabeled metomidate compounds. Particular consideration is given to iodo-metomidate PET tracers for the diagnosis and management of adrenocortical carcinoma, and the increasingly recognized utility of 11C-metomidate PET-CT in primary aldosteronism.

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance (  =  3.3  ±  2.1%) and improved the detection of BOLD activation (P  =  0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P  <  0.001). Fluctuations in HR and RVT appeared to be correlated with the stimulus and may contribute to apparent BOLD signal reactivity. [ABSTRACT FROM AUTHOR]