A review of harmonization strategies for quantitative PET

Evaluating long-term performance and quality control of the uMI 550 positron emission tomography- computed tomography (PET-CT) system: A comprehensive scientific analysis

INTRODUCTION

Ensuring the long-term performance and reliability of positron emission tomography-computed tomography (PET-CT) systems is essential for accurate clinical diagnostics and treatment planning. This study provides a comprehensive analysis of the periodic quality control (QC) processes of the uMI 550 PET-CT system, focusing on key performance parameters such as standardized uptake value (SUV) accuracy, spatial alignment, and image uniformity.

METHODS

Periodic semi-annual QC tests were conducted to evaluate the system's performance across multiple parameters. Key metrics included SUV measurements, spatial alignment across X, Y, and Z axes, and uniformity tests. Statistical analyses assessed variability and stability over time, including ANOVA, t-tests, and linear regression.

RESULTS

The results demonstrated consistent SUV measurements within the reference range of 0.95-1.05, indicating robust quantitative accuracy. Spatial alignment was maintained within a tolerance of -1.5 mm to +1.5 mm, ensuring geometric integrity crucial for accurate image fusion in radiotherapy planning. Uniformity tests showed transverse and axial uniformity values remained within acceptable limits (0.00-0.05), ensuring high-quality imaging across the field of view. Statistical analyses confirmed no significant drift or variability across QC intervals, highlighting the system's reliability over time.

CONCLUSION

The uMI 550 PET-CT system demonstrated consistent performance across critical parameters, validating its suitability for a wide range of clinical applications. Regular QC testing plays a vital role in maintaining system accuracy and reliability.

IMPLICATIONS FOR PRACTICE

This study underscores the importance of routine quality control procedures in ensuring the long-term stability and reliability of PET-CT systems. The robust performance of the uMI 550 supports its use in oncology and other diagnostic fields, providing clinicians with confidence in treatment decisions.

Open-source phantom with dedicated in-house software for image quality assurance in hybrid PET systems

BACKGROUND

Patients' diagnosis, treatment and follow-up increasingly rely on multimodality imaging. One of the main limitations for the optimal implementation of hybrid systems in clinical practice is the time and expertise required for applying standardized protocols for equipment quality assurance (QA). Experimental phantoms are commonly used for this purpose, but they are often limited to a single modality and single quality parameter, lacking automated analysis capabilities. In this study, we developed a multimodal 3D-printed phantom and software for QA in positron emission tomography (PET) hybrid systems, with computed tomography (CT) or magnetic resonance (MR), by assessing signal, spatial resolution, radiomic features, co-registration and geometric distortions.

RESULTS

Phantom models and Python software for the proposed QA are available to download, and a user-friendly plugin compatible with the open-source 3D-Slicer software has been developed. The QA viability was proved by characterizing a Philips-Gemini-TF64-PET/CT in terms of signal response (mean, µ), intrinsic variability for three consecutive measurements (daily variation coefficient, CoVd) and reproducibility over time (variation coefficient across 5 months, CoVm). For this system, averaged recovery coefficient for activity concentration was µ = 0.90 ± 0.08 (CoVd = 0.6%, CoVm = 9%) in volumes ranging from 7 to 42 ml. CT calibration-curve averaged over time was HU = ( 951 ± 12 ) × density - ( 944 ± 15 ) with variability of slope and y-intercept of (CoVd = 0.4%, CoVm = 1.2%) and (CoVd = 0.4%, CoVm = 1.6%), respectively. Radiomics reproducibility resulted in (CoVd = 18%, CoVm = 30%) for PET and (CoVd = 15%, CoVm = 22%) for CT. Co-registration was assessed by Dice-Similarity-Coefficient (DSC) along 37.8 cm in superior-inferior (z) direction (well registered if DSC ≥ 0.91 and Δz ≤ 2 mm), resulting in 3/7 days well co-registered. Applicability to other scanners was additionally proved with Philips-Vereos-PET/CT (V), Siemens-Biograph-Vison-600-PET/CT (S) and GE-SIGNA-PET/MR (G). PET concentration accuracy was (µ = 0.86, CoVd = 0.3%) for V, (µ = 0.87, CoVd = 0.8%) for S, and (µ = 1.10, CoVd = 0.34%) for G. MR(T2) was well co-registered with PET in 3/4 cases, did not show significant distortion within a transaxial diameter of 27.8 cm and along 37 cm in z, and its radiomic variability was CoVd = 13%.

CONCLUSIONS

Open-source QA protocol for PET hybrid systems has been presented and its general applicability has been proved. This package facilitates simultaneously simple and semi-automated evaluation for various imaging modalities, providing a complete and efficient QA solution.

Practical value of fluorodeoxyglucose positron emission tomography in treatment strategies for thymic epithelial tumors: implications for more specific use in routine clinical practice

Many studies have demonstrated that 18-fluorine fluorodeoxyglucose positron emission tomography (FDG-PET) is useful for predicting the grade of malignancy of thymic epithelial tumors (TETs), and there is a close relationship between the maximum standardized uptake value (SUVmax) and tumor stage. However, more specific usage of FDG-PET for TETs has not been proposed, and the actual value of FDG-PET in routine clinical practice should be firmly clarified. In this review, following three cutoff values of SUVmax that may be helpful in determining treatment strategies in cases of anterior mediastinal masses, particularly presented as discrete and resectable lesions, are identified: (I) SUVmax of 7.5 as an indicator for pretreatment biopsy: differential diagnosis between TETs and mediastinal lymphoma (ML); (II) SUVmax of 4.2 as an indicator for a minimally invasive approach (MIA): differentiation of noninvasive TETs and invasive TETs; and (III) SUVmax of 5.9 as a reference value for the necessity of lymph node dissection (LND). There are still several challenges in using FDG-PET for routine clinical practice that need to be addressed, such as variations between instruments and institutions, leading to lower reproducibility. Harmonization methods should be applied to make clinical practice more uniform. Due to the rarity of these diseases, multi-institutional studies are warranted.

EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [18F]FDG brain studies

PURPOSE

PET imaging is a pivotal tool for biomarker research aimed at personalized medicine. Leveraging the quantitative nature of PET requires knowledge of plasma radiotracer concentration. Typically, the arterial input function (AIF) is obtained through arterial cannulation, an invasive and technically demanding procedure. A less invasive alternative, especially for [18F]FDG, is the image-derived input function (IDIF), which, however, often requires correction for partial volume effect (PVE), usually performed via venous blood samples. The aim of this paper is to present EMATA: Extraction and Modeling of Arterial inputs for Tracer kinetic Analysis, an open-source MATLAB toolbox. EMATA automates IDIF extraction from [18F]FDG brain PET images and additionally includes a PVE correction procedure that does not require any blood sampling.

METHODS

To assess the toolbox generalizability and present example outputs, EMATA was applied to brain [18F]FDG dynamic data of 80 subjects, extracted from two distinct datasets (40 healthy controls, 40 glioma patients). Additionally, to compare with the reference standard, quantification using both IDIF and AIF was carried out on a third open-access dataset of 18 healthy individuals.

RESULTS

EMATA consistently performs IDIF extraction across all datasets, despite differences in scanners and acquisition protocols. Remarkably high agreement is observed when comparing Patlak's Ki between IDIF and AIF (R2: 0.98 ± 0.02).

CONCLUSION

EMATA proved adaptability to different datasets characteristics and the ability to provide arterial input functions that can be used for reliable PET quantitative analysis.

Preliminary protocol for measuring the reproducibility and accuracy of flow values on digital PET/CT systems in [15O]H2O myocardial perfusion imaging using a flow phantom

BACKGROUND

Several factors may decrease the accuracy of quantitative PET myocardial perfusion imaging (MPI). It is therefore essential to ensure that myocardial blood flow (MBF) values are reproducible and accurate, and to design systematic protocols to achieve this. Until now, no systematic phantom protocols have been available to assess the technical factors affecting measurement accuracy and reproducibility in MPI.

MATERIALS AND METHODS

We implemented a standard measurement protocol, which applies a flow phantom in order to compare image-derived flow values with respect to a ground truth flow value with [15O]H2O MPI performed on both a Discovery MI (DMI-20, GE Healthcare) and a Biograph Vision 600 (Vision-600, Siemens Healthineers) system. Both systems have automatic [15O]H2O radio water generators (Hidex Oy) individually installed, allowing us to also study the differences occurring due to two different bolus delivery systems. To investigate the technical factors contributing to the modelled flow values, we extracted the [15O]H2O bolus profiles, the flow values from the kinetic modeling (Qin and Qout), and finally calculated their differences between test-retest measurements on both systems.

RESULTS

The measurements performed on the DMI-20 system produced Qin and Qout values corresponging to each other as well as to the reference flow value across all test-retest measurements. The repeatability differences on DMI-20 were 2.1% ± 2.6% and 3.3% ± 4.1% for Qin and Qout, respectively. On Vision-600 they were 10% ± 8.4% and 11% ± 10% for Qin and Qout, respectively. The measurements performed on the Vision-600 system showed more variation between Qin and Qout values across test-retest measurements and exceeded 15% difference in 7/24 of the measurements.

CONCLUSIONS

A preliminary protocol for measuring the accuracy and reproducibility of flow values in [15O]H2O MPI between digital PET/CT systems was assessed. The test-retest reproducibility falls below 15% in majority of the measurements conducted between two individual injector systems and two digital PET/CT systems. This study highlights the importance of implementing a standardized bolus injection and delivery protocol and importance of assessing technical factors affecting flow value reproducibility, which should be carefully investigated in a multi-center setting.

Multicenter PET image harmonization using generative adversarial networks

PURPOSE

To improve reproducibility and predictive performance of PET radiomic features in multicentric studies by cycle-consistent generative adversarial network (GAN) harmonization approaches.

METHODS

GAN-harmonization was developed to harmonize whole-body PET scans to perform image style and texture translation between different centers and scanners. GAN-harmonization was evaluated by application to two retrospectively collected open datasets and different tasks. First, GAN-harmonization was performed on a dual-center lung cancer cohort (127 female, 138 male) where the reproducibility of radiomic features in healthy liver tissue was evaluated. Second, GAN-harmonization was applied to a head and neck cancer cohort (43 female, 154 male) acquired from three centers. Here, the clinical impact of GAN-harmonization was analyzed by predicting the development of distant metastases using a logistic regression model incorporating first-order statistics and texture features from baseline 18F-FDG PET before and after harmonization.

RESULTS

Image quality remained high (structural similarity: left kidney ≥ 0.800, right kidney ≥ 0.806, liver ≥ 0.780, lung ≥ 0.838, spleen ≥ 0.793, whole-body ≥ 0.832) after image harmonization across all utilized datasets. Using GAN-harmonization, inter-site reproducibility of radiomic features in healthy liver tissue increased at least by ≥ 5 ± 14% (first-order), ≥ 16 ± 7% (GLCM), ≥ 19 ± 5% (GLRLM), ≥ 16 ± 8% (GLSZM), ≥ 17 ± 6% (GLDM), and ≥ 23 ± 14% (NGTDM). In the head and neck cancer cohort, the outcome prediction improved from AUC 0.68 (95% CI 0.66-0.71) to AUC 0.73 (0.71-0.75) by application of GAN-harmonization.

CONCLUSIONS

GANs are capable of performing image harmonization and increase reproducibility and predictive performance of radiomic features derived from different centers and scanners.

Position dependence of recovery coefficients in 177Lu-SPECT/CT reconstructions - phantom simulations and measurements

BACKGROUND

Although the importance of quantitative SPECT has increased tremendously due to newly developed therapeutic radiopharmaceuticals, there are still no accreditation programs to harmonize SPECT imaging. Work is currently underway to develop an accreditation for quantitative 177Lu SPECT/CT. The aim of this study is to verify whether the positioning of the spheres within the phantom has an influence on the recovery and thus needs to be considered in SPECT harmonization. In addition, the effects of these recovery coefficients on a potential partial volume correction as well as absorbed-dose estimates are investigated.

METHODS

Using a low-dose CT of a SPECT/CT acquisition, a computerized version of the NEMA body phantom was created using a semi-automatic threshold-based method. Based on the mass-density map, the detector orbit, and the sphere centers, realistic SPECT acquisitions of all possible 720 sphere configurations of both the PET and the SPECT versions of the NEMA Body Phantom were generated using Monte Carlo simulations. SPECT reconstructions with different numbers of updates were performed without (CASToR) and with resolution modeling (STIR). Recovery coefficients were calculated for all permutations, reconstruction methods, and phantoms, and their dependence on the sphere positioning was investigated. Finally, the simulation-based findings were validated using SPECT/CT acquisitions of six different sphere configurations.

RESULTS

Our analysis shows that sphere positioning has a significant impact on the recovery for both of the reconstruction methods and the phantom type. Although resolution modeling resulted in significantly higher recovery, the relative variation in recovery within the 720 permutations was even larger. When examining the extreme values of the recovery, reconstructions without resolution modeling were influenced primarily by the sphere position, while with resolution modeling the volume of the two adjacent spheres had a larger influence. The SPECT measurements confirmed these observations, and the recovery curves showed good overall agreement with the simulated data.

CONCLUSION

Our study shows that sphere positioning has a significant impact on the recovery obtained in NEMA sphere phantom measurements and should therefore be considered in a future SPECT accreditation. Furthermore, the single-measurement method normally performed for PVC should be reconsidered to account for the position dependency.

Characterization of sacral chordoma and differential diagnosis from other sacral malignancy using [18F]FDG PET/CT

2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET)/computed tomography (CT) is known to be a helpful imaging modality for sacral chordoma, but its detailed characteristics have not been fully described. The purpose of our study was to identify the [18F]FDG PET/CT imaging characteristics of sacral chordoma and compare them with other sacral malignancy. This retrospective study included patients who underwent [18F]FDG PET/CT because of a mass involving the sacrum. Investigated visual findings included visual score and distribution, and semiquantitative parameters measured included standardized uptake values (SUVmax, SUVpeak, SUVmean), tumor-to-liver ratio (TLR), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and tumor size. Comparison studies and receiver operating characteristics (ROC) curve analysis were performed to differentiate between sacral chordoma and other sacral malignancy. Ten patients with sacral chordoma were finally included (M:F = 6:4, median age = 67 yr). On [18F]FDG PET/CT, sacral chordomas presented as a mass with minimal-moderate uptake with a usually heterogenous distribution. Compared with 12 patients with other sacral malignancies (M:F = 4:8, median age 42 yr), sacral chordoma showed a significantly lower TLR (median value 2.1 vs 6.3, P = .021). In ROC curve analysis, TLR showed the largest area under the curve (AUC) of 0.79 (cutoff ≤ 4.0; sensitivity 100.0%, specificity 58.3%; P = .004), and SUVmax showed the second largest AUC of 0.73 (cutoff ≤ 6.9; sensitivity 80.0%, specificity 66.7%; P = .034). [18F]FDG PET/CT of sacral chordoma showed minimal-moderate uptake. The TLR of [18F]FDG PET/CT was significantly lower than that of other sacral malignancy and was the most useful parameter for differentiating sacral chordoma, with the largest AUC. SUVmax could be another helpful semiquantitative parameter.

PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group

Response Assessment in Neuro-Oncology (RANO) response criteria have been established and were updated in 2023 for MRI-based response evaluation of diffuse gliomas in clinical trials. In addition, PET-based imaging with amino acid tracers is increasingly considered for disease monitoring in both clinical practice and clinical trials. So far, a standardised framework defining timepoints for baseline and follow-up investigations and response evaluation criteria for PET imaging of diffuse gliomas has not been established. Therefore, in this Policy Review, we propose a set of criteria for response assessment based on amino acid PET imaging in clinical trials enrolling participants with diffuse gliomas as defined in the 2021 WHO classification of tumours of the central nervous system. These proposed PET RANO criteria provide a conceptual framework that facilitates the structured implementation of PET imaging into clinical research and, ultimately, clinical routine. To this end, the PET RANO 1.0 criteria are intended to encourage specific investigations of amino acid PET imaging of gliomas.

Prediction of misfolded proteins spreading in Alzheimer's disease using machine learning and spreading models

The pervasive impact of Alzheimer's disease on aging society represents one of the main challenges at this time. Current investigations highlight 2 specific misfolded proteins in its development: Amyloid-$\beta$ and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on 2 machine learning approaches which we compare with known simulation models. The first approach applies an autoregressive model constrained by structural connectivity, while the second is based on graph convolutional networks. The aim is to predict concentrations of Amyloid-$\beta$ 2 yr after a provided baseline. We also evaluate its real-world effectiveness and suitability by providing a web service for physicians and researchers. In experiments, the autoregressive model generally outperformed state-of-the-art models resulting in lower prediction errors. While it is important to note that a comprehensive prognostic plan cannot solely rely on amyloid beta concentrations, their prediction, achieved by the discussed approaches, can be valuable for planning therapies and other cures, especially when dealing with asymptomatic patients for whom novel therapies could prove effective.

Challenges and innovations in brain PET analysis of neurodegenerative disorders: a mini-review on partial volume effects, small brain region studies, and reference region selection

Positron Emission Tomography (PET) brain imaging is increasingly utilized in clinical and research settings due to its unique ability to study biological processes and subtle changes in living subjects. However, PET imaging is not without its limitations. Currently, bias introduced by partial volume effect (PVE) and poor signal-to-noise ratios of some radiotracers can hamper accurate quantification. Technological advancements like ultra-high-resolution scanners and improvements in radiochemistry are on the horizon to address these challenges. This will enable the study of smaller brain regions and may require more sophisticated methods (e.g., data-driven approaches like unsupervised clustering) for reference region selection and to improve quantification accuracy. This review delves into some of these critical aspects of PET molecular imaging and offers suggested strategies for improvement. This will be illustrated by showing examples for dopaminergic and cholinergic nerve terminal ligands.

Quantitative PET-based biomarkers in lymphoma: getting ready for primetime

The use of functional quantitative biomarkers extracted from routine PET-CT scans to characterize clinical responses in patients with lymphoma is gaining increased attention, and these biomarkers can outperform established clinical risk factors. Total metabolic tumour volume enables individualized estimation of survival outcomes in patients with lymphoma and has shown the potential to predict response to therapy suitable for  risk-adapted treatment approaches in clinical trials. The deployment of machine learning tools in molecular imaging research can assist in recognizing complex patterns and, with image classification, in tumour identification and segmentation of data from PET-CT scans. Initial studies using fully automated approaches to calculate metabolic tumour volume and other PET-based biomarkers have demonstrated appropriate correlation with calculations from experts, warranting further testing in large-scale studies. The extraction of computer-based quantitative tumour characterization through radiomics can provide a comprehensive view of phenotypic heterogeneity that better captures the molecular and functional features of the disease. Additionally, radiomics can be integrated with genomic data to provide more accurate prognostic information. Further improvements in PET-based biomarkers are imminent, although their incorporation into clinical decision-making currently has methodological shortcomings that need to be addressed with confirmatory prospective validation in selected patient populations. In this Review, we discuss the current knowledge, challenges and opportunities in the integration of quantitative PET-based biomarkers in clinical trials and the routine management of patients with lymphoma.