Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease.

Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.

Differential centiloid scale normalization techniques: comparison between hybrid PET/MRI and independently acquired MRI.

OBJECTIVE: Centiloid (CL) scales play an important role in semiquantitative analyses of amyloid-ß (Aß) PET. CLs are derived from the standardized uptake value ratio (SUVR), which needs Aß positron emission tomography (PET) normalization processing. There are two methods to collect the T1-weighted imaging (T1WI) for normalization: (i) anatomical standardization using simultaneously acquired T1WI (PET/MRI), usually adapted to PET images from PET/MRI scanners, and (ii) T1WI from a separate examination (PET + MRI), usually adapted to PET images from PET/CT scanners. This study aimed to elucidate the correlations and differences in CLs between when using the above two T1WI collection methods. METHODS: Among patients who underwent Aß PET/MRI (using 11C-Pittuberg compound B (11C-PiB) or 18F-flutemetamol (18F-FMM)) at our institution from 2015 to 2023, we selected 49 patients who also underwent other additional MRI examinations, including T1WI for anatomic standardization within 3 years. Thirty-one of them underwent 11C-PiB PET/MRI, and 18 participants underwent 18F-FMM PET/MRI. Twenty-five of them, additional MRI acquisition parameters were identical to simultaneous MRI during PET, and 24 participants were different. After normalization using PET/MRI or PET + MRI method each, SUVR was measured using the Global Alzheimer's Association Initiative Network cerebral cortical and striatum Volume of Interest templates (VOI) and whole cerebellum VOI. Subsequently, CLs were calculated using the previously established equations for each Aß PET tracer. RESULTS: Between PET/MRI and PET + MRI methods, CLs correlated linearly in 11C-PiB PET (y = 1.00x - 0.11, R2 = 0.999), 18F-FMM PET (y = 0.97x - 0.12, 0.997), identical additional MRI acquisition (y = 1.00x + 0.33, 0.999), different acquisition (y = 0.98x - 0.43, 0.997), and entire study group (y = 1.00x - 0.24, 0.999). Wilcoxon signed-rank test revealed no significant differences: 11C-PiB (p = 0.49), 18F-FMM (0.08), and whole PET (0.46). However, significant differences were identified in identical acquisition (p = 0.04) and different acquisition (p = 0.02). Bland-Altman analysis documented only a small bias between PET/MRI and PET + MRI in 11C-PiB PET, 18F-FMM PET, identical additional MRI acquisition, different acquisition, and whole PET (- 0.05, 0.67, - 0.30, 0.78, and 0.21, respectively). CONCLUSIONS: Anatomical standardizations using PET/MRI and using PET + MRI can lead to almost equivalent CL. The CL values obtained using PET/MRI or PET + MRI normalization methods are consistent and comparable in clinical studies.

Diagnostic Reference Levels in PET Imaging at Chulabhorn Hospital, Thailand.

Diagnostic reference levels (DRLs) are an important tool for controlling radiation exposure and ensuring safety in medical applications. In Thailand, DRL data have been gathered and established for nuclear medicine diagnostics since 2021. However, there is a lack of information on PET imaging examinations. At the National Cyclotron and PET Scan Centre, Chulabhorn Hospital, radiopharmaceuticals are produced for medical imaging and research, and a wide range of PET/CT and PET/MRI examinations are performed. Our objective was to investigate the administered activity of radiopharmaceuticals in patients undergoing PET imaging, especially the existing data on DRLs in medical diagnostic imaging. Methods: This was a retrospective study on nuclear medicine patients at the National Cyclotron and PET Scan Centre in 2023. Statistical analysis, including the mean and the 75th percentile values, was conducted to determine DRLs according to the International Commission on Radiological Protection guidelines. Results: The center performed 8,711 PET/CT and PET/MRI studies with 13 protocols in 2023. The most commonly administered activity was 18F-FDG in oncology and neurology examinations, with DRLs of 186.11 and 136.16 MBq, respectively. These values were notably almost twice lower than several reports in other countries. Conclusion: There is a lack of comprehensive data on most DRLs for PET imaging at this center because of the nonwidespread use of several radiopharmaceuticals. However, the lower DRLs for 18F-FDG can highlight the need for ongoing investigation toward the establishment of local DRLs, as well as assurance on the safety and efficiency of radiation used in nuclear medicine.

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.

Optimization-derived blood input function using a kernel method and its evaluation with total-body PET for brain parametric imaging.

Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation. METHODS: The conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored. RESULTS: The estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method. CONCLUSION: The proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.

Evaluation of MRI post-processing methods combined with PET in detecting focal cortical dysplasia lesions for patients with MRI-negative epilepsy.

OBJECTIVE: Accurate detection of focal cortical dysplasia (FCD) through magnetic resonance imaging (MRI) plays a pivotal role in the preoperative assessment of epilepsy. The integration of multimodal imaging has demonstrated substantial value in both diagnosing FCD and devising effective surgical strategies. This study aimed to enhance MRI post-processing by incorporating positron emission tomography (PET) analysis. We sought to compare the diagnostic efficacy of diverse image post-processing methodologies in patients presenting MRI-negative FCD. METHODS: In this retrospective investigation, we assembled a cohort of patients with negative preoperative MRI results. T1-weighted volumetric sequences were subjected to morphometric analysis program (MAP) and composite parametric map (CPM) post-processing techniques. We independently co-registered images derived from various methods with PET scans. The alignment was subsequently evaluated, and its correlation was correlated with postoperative seizure outcomes. RESULTS: A total of 41 patients were enrolled in the study. In the PET-MAP(p = 0.0189) and PET-CPM(p = 0.00041) groups, compared with the non-overlap group, the overlap group significantly associated with better postoperative outcomes. In PET(p = 0.234), CPM(p = 0.686) and MAP(p = 0.672), there is no statistical significance between overlap and seizure-free outcomes. The sensitivity of using the CPM alone outperformed the MAP (0.65 vs 0.46). The use of PET-CPM demonstrated superior sensitivity (0.96), positive predictive value (0.83), and negative predictive value (0.91), whereas the MAP displayed superior specificity (0.71). CONCLUSIONS: Our findings suggested a superiority in sensitivity of CPM in detecting potential FCD lesions compared to MAP, especially when it is used in combination with PET for diagnosis of MRI-negative epilepsy patients. Moreover, we confirmed the superiority of synergizing metabolic imaging (PET) with quantitative maps derived from structural imaging (MAP or CPM) to enhance the identification of subtle epileptogenic zones (EZs). This study serves to illuminate the potential of integrated multimodal techniques in advancing our capability to pinpoint elusive pathological features in epilepsy cases.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy.

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

Imaging chronic active lesions in multiple sclerosis: a consensus statement.

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis and have implications for non-relapsing biological progression. In recent years, the discovery of innovative MRI and PET-derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with multiple sclerosis, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted and T2-weighted scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a consensus statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this consensus statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.

Biochemically recurrent prostate cancer: rationalisation of the approach to imaging.

AIM: To assess the utility of magnetic resonance imaging (MRI) in addition to the additive benefit of the conventional imaging techniques, computed tomography (CT) and nuclear medicine (NM) bone scintigraphy, for investigation of biochemical recurrence (BCR) post-prostatectomy where access to prostate specific membrane antigen (PSMA) positron-emission tomography (PET)-CT is challenging. MATERIALS AND METHODS: Relevant imaging over a 5-year period was reviewed. Ethical approval was granted by the internal review board. All patients with suspected BCR, defined as a PSA ≥0.2 ng/ml on two separate occasions, underwent a retrospective imaging review. This was performed on PACS archive search database in a single centre using search terms "PSA" and "prostatectomy" in the three imaging methods; MRI, CT, and NM bone scintigraphy. All PSMA PET CT performed were recorded. RESULTS: One hundred and eighty-five patients were identified. Patients with an MRI pelvis that demonstrated distant metastases (i.e., pelvic bone metastases or lymph node involvement more cranial to the bifurcation of the common iliac arteries) were more likely to have a positive CT and/or NM bone scintigraphy. The Pearson correlation coefficient between the findings of M1 disease at MRI pelvis and the presence of distant metastases at CT thorax, abdomen, pelvis and NM bone scintigraphy was calculated at 0.81 (p<0.01) and 0.91 (p<0.01) respectively. CONCLUSION: An imaging strategy based on risk stratification and technique-specific selection criteria leads to more appropriate use of resources, and in turn, increases the yield of conventional imaging methods. MRI prostate findings can be used to predict the additive value of CT/NM bone scintigraphy allowing a more streamlined approach to their use.

An optimized reference tissue method for quantification of tau protein depositions in diverse neurodegenerative disorders by PET with 18F-PM-PBB3 (18F-APN-1607).

Positron emission tomography (PET) with 18F-PM-PBB3 (18F-APN-1607, 18F-Florzolotau) enables high-contrast detection of tau depositions in various neurodegenerative dementias, including Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). A simplified method for quantifying radioligand binding in target regions is to employ the cerebellum as a reference (CB-ref) on the assumption that the cerebellum has minimal tau pathologies. This procedure is typically valid in AD, while FTLD disorders exemplified by progressive supranuclear palsy (PSP) are characterized by occasional tau accumulations in the cerebellum, hampering the application of CB-ref. The present study aimed to establish an optimal method for defining reference tissues on 18F-PM-PBB3-PET images of AD and non-AD tauopathy brains. We developed a new algorithm to extract reference voxels with a low likelihood of containing tau deposits from gray matter (GM-ref) or white matter (WM-ref) by a bimodal fit to an individual, voxel-wise histogram of the radioligand retentions and applied it to 18F-PM-PBB3-PET data obtained from age-matched 40 healthy controls (HCs) and 23 CE, 40 PSP, and five other tau-positive FTLD patients. PET images acquired at 90-110 min after injection were averaged and co-registered to corresponding magnetic resonance imaging space. Subsequently, we generated standardized uptake value ratio (SUVR) images estimated by CB-ref, GM-ref and WM-ref, respectively, and then compared the diagnostic performances. GM-ref and WM-ref covered a broad area in HCs and were free of voxels located in regions known to bear high tau burdens in AD and PSP patients. However, radioligand retentions in WM-ref exhibited age-related declines. GM-ref was unaffected by aging and provided SUVR images with higher contrast than CB-ref in FTLD patients with suspected and confirmed corticobasal degeneration. The methodology for determining reference tissues as optimized here improves the accuracy of 18F-PM-PBB3-PET measurements of tau burdens in a wide range of neurodegenerative illnesses.

Source-to-Target Automatic Rotating Estimation (STARE) - A publicly-available, blood-free quantification approach for PET tracers with irreversible kinetics: Theoretical framework and validation for [18F]FDG.

INTRODUCTION: Full quantification of positron emission tomography (PET) data requires an input function. This generally means arterial blood sampling, which is invasive, labor-intensive and burdensome. There is no current, standardized method to fully quantify PET radiotracers with irreversible kinetics in the absence of blood data. Here, we present Source-to-Target Automatic Rotating Estimation (STARE), a novel, data-driven approach to quantify the net influx rate (Ki) of irreversible PET radiotracers, that requires only individual-level PET data and no blood data. We validate STARE with human [18F]FDG PET scans and assess its performance using simulations. METHODS: STARE builds upon a source-to-target tissue model, where the tracer time activity curves (TACs) in multiple "target" regions are expressed at once as a function of a "source" region, based on the two-tissue irreversible compartment model, and separates target region Ki from source Ki by fitting the source-to-target model across all target regions simultaneously. To ensure identifiability, data-driven, subject-specific anchoring is used in the STARE minimization, which takes advantage of the PET signal in a vasculature cluster in the field of view (FOV) that is automatically extracted and partial volume-corrected. To avoid the need for any a priori determination of a single source region, each of the considered regions acts in turn as the source, and a final Ki is estimated in each region by averaging the estimates obtained in each source rotation. RESULTS: In a large dataset of human [18F]FDG scans (N = 69), STARE Ki estimates were correlated with corresponding arterial blood-based Ki estimates (r = 0.80), with an overall regression slope of 0.88, and were precisely estimated, as assessed by comparing STARE Ki estimates across several runs of the algorithm (coefficient of variation across runs=6.74 ± 2.48%). In simulations, STARE Ki estimates were largely robust to factors that influence the individualized anchoring used within its algorithm. CONCLUSION: Through simulations and application to [18F]FDG PET data, feasibility is demonstrated for STARE blood-free, data-driven quantification of Ki. Future work will include applying STARE to PET data obtained with a portable PET camera and to other irreversible radiotracers.

18 F-fluorodeoxy-glucose positron emission tomography pattern and prognostic predictors in patients with anti-GABAB receptor encephalitis.

AIMS: To identify the metabolic pattern and prognostic predictors in anti-gamma-aminobutyric-acid B (GABAB) receptor encephalitis using 18 F-fluorodeoxy-glucose positron emission tomography (18 F-FDG-PET). METHODS: Twenty-one patients diagnosed anti-GABAB receptor encephalitis who underwent 18 F-FDG-PET at first hospitalization were retrospectively reviewed. 18 F-FDG-PET images were analyzed in comparison with controls. Further group comparisons of 18 F-FDG-PET data were carried out between prognostic subgroups. RESULTS: 18 F-FDG-PET was abnormal in 81% patients with anti-GABAB receptor encephalitis and was more sensitive than MRI (81% vs. 42.9%, p = 0.025). Alter limbic lobe glucose metabolism (mostly hypermetabolism) was observed in 14 patients (66.7%), of whom 10 (10/14, 71.4%) demonstrated hypermetabolism in the medial temporal lobe (MTL). Group analysis also confirmed MTL hypermetabolism in association with relative frontal and parietal hypometabolism was a general metabolic pattern. After a median follow-up of 33 months, the group comparisons revealed that patients with poor outcome demonstrated increased metabolism in the MTL compared to those with good outcome. CONCLUSION: 18 F-FDG-PET may be more sensitive than MRI in the early diagnosis of anti-GABAB receptor encephalitis. MTL hypermetabolism was associated with relative frontal or parietal hypometabolism and may serve as a prognostic biomarker in anti-GABAB receptor encephalitis.

11C-acetate positron emission tomography is more precise than 18F-fluorodeoxyglucose positron emission tomography in evaluating tumor burden and predicting disease risk of multiple myeloma.

The optimal method of tumor burden evaluation in newly diagnosed multiple myeloma (NDMM) is yet to be determined. This study aimed to compare the value of 11C-acetate positron-emission tomography (PET)/computed tomography (CT) (AC-PET and 18F-fluorodeoxyglucose PET/CT (FDG-PET) in the assessment of tumor burden in NDMM. This study evaluated 64 NDMM patients between February 2015 and July 2018. AC-PET and FDG-PET were used to assess myeloma lesions. The clinical data, imaging results, and their correlations were analyzed. Diffuse bone marrow uptake in AC-PET was significantly correlated with biomarkers for tumor burden, including serum hemoglobin (P = 0.020), M protein (P = 0.054), the percentage of bone marrow plasma cells (P < 0.001), and the Durie-Salmon stage of the disease (P = 0.007). The maximum standard uptake value (SUVmax) of focal lesions and high diffuse bone marrow uptake in AC-PET showed stronger correlations with high-risk disease (P = 0.017, P = 0.013) than those in FDG-PET. Moreover, the presence of diffuse bone marrow uptake, more than ten focal lesions, and an SUVmax of focal lesions of > 6.0 in AC-PET, but not in FDG-PET, predicted a higher probability of disease progression and shorter progression-free survival (P < 0.05). AC-PET outperformed FDG-PET in tumor burden evaluation and disease progression prediction in NDMM.

Validation technique and improvements introduced in a new dedicated brain positron emission tomograph (CareMiBrain).

The goal of developing a PET dedicated to the brain (CareMiBrain) has evolved from its initial approach to diagnosis and monitoring of dementias, to the more ambitious of creating a revolutionary clinical pathway for the knowledge and personalized treatment of multiple neurological diseases. The main innovative feature of CareMiBrain is the use of detectors with continuous crystals, which allow a high resolution determination of the depth of annihilation photons interaction within the thickness of the scintillation crystal. The technical validation phase of the equipment consisted of a pilot, prospective and observational study whose objective was to obtain the first images (40 patients), analyze them and make adjustments in the acquisition, reconstruction and correction parameters, comparing the image quality of the CareMiBrain equipment with that of the whole-body PET/CT. Thanks to the team meetings and the joint analysis of the images, it was possible to detect its weak points and some of its causes. The calibration, acquisition and processing processes, as well as the reconstruction, were optimized, the number of iterations was set to achieve the best signal-to-noise ratio, the random correction was optimized and a post-processing algorithm was included in the reconstruction algorithm. The main technical improvements implemented in this phase of technical validation carried out through collaboration of the Services of Nuclear Medicine and Neurology of the Hospital Clínico San Carlos with the Spanish company Oncovision will be exposed in a project financed with funds from the European Union (Horizon 2020 innovation program, 713323).

A transfer learning approach to facilitate ComBat-based harmonization of multicentre radiomic features in new datasets.

PURPOSE: To facilitate the demonstration of the prognostic value of radiomics, multicenter radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis is however challenging, as they are sensitive to the variability in scanner models, acquisition protocols and reconstruction settings, which is often unavoidable in a multicentre retrospective analysis. A statistical harmonization strategy called ComBat was utilized in radiomics studies to deal with the "center-effect". The goal of the present work was to integrate a transfer learning (TL) technique within ComBat-and recently developed alternate versions of ComBat with improved flexibility (M-ComBat) and robustness (B-ComBat)-to allow the use of a previously determined harmonization transform to the radiomic feature values of new patients from an already known center. MATERIAL AND METHODS: The proposed TL approach were incorporated in the four versions of ComBat (standard, B, M, and B-M ComBat). The proposed approach was evaluated using a dataset of 189 locally advanced cervical cancer patients from 3 centers, with magnetic resonance imaging (MRI) and positron emission tomography (PET) images, with the clinical endpoint of predicting local failure. The impact performance of the TL approach was evaluated by comparing the harmonization achieved using only parts of the data to the reference (harmonization achieved using all the available data). It was performed through three different machine learning pipelines. RESULTS: The proposed TL technique was successful in harmonizing features of new patients from a known center in all versions of ComBat, leading to predictive models reaching similar performance as the ones developed using the features harmonized with all the data available. CONCLUSION: The proposed TL approach enables applying a previously determined ComBat transform to new, previously unseen data.

Modeling [11C]yohimbine PET human brain kinetics with test-retest reliability, competition sensitivity studies and search for a suitable reference region.

Previous work introduced the [11C]yohimbine as a suitable ligand of central α2-adrenoreceptors (α2-ARs) for PET imaging. However, reproducibility of [11C]yohimbine PET measurements in healthy humans estimated with a simplified modeling method with reference region, as well as sensitivity of [11C]yohimbine to noradrenergic competition were not evaluated. The objectives of the present study were therefore to fill this gap. METHODS: Thirteen healthy humans underwent two [11C]yohimbine 90-minute dynamic scans performed on a PET-MRI scanner. Seven had arterial blood sampling with metabolite assessment and plasmatic yohimbine free fraction evaluation at the first scan to have arterial input function and test appropriate kinetic modeling. The second scan was a simple retest for 6 subjects to evaluate the test-retest reproducibility. For the remaining 7 subjects the second scan was a challenge study with the administration of a single oral dose of 150 µg of clonidine 90 min before the PET scan. Parametric images of α2-ARs distribution volume ratios (DVR) were generated with two non-invasive models: Logan graphical analysis with Reference (LREF) and Simplified Reference Tissue Method (SRTM). Three reference regions (cerebellum white matter (CERWM), frontal white matter (FLWM), and corpus callosum (CC)) were tested. RESULTS: We showed high test-retest reproducibility of DVR estimation with LREF and SRTM regardless of reference region (CC, CERWM, FLWM). The best fit was obtained with SRTMCC (r2=0.94). Test-retest showed that the SRTMCC is highly reproducible (mean ICC>0.7), with a slight bias (-1.8%), whereas SRTMCERWM had lower bias (-0.1%), and excellent ICC (mean>0.8). Using SRTMCC, regional changes have been observed after clonidine administration with a significant increase reported in the amygdala and striatum as well as in several posterior cortical areas as revealed with the voxel-based analysis. CONCLUSION: The results add experimental support for the suitability of [11C]yohimbine PET in the quantitative assessment of α2-ARs occupancy in vivo in the human brain. Trial registration EudraCT 2018-000380-82.

Validation of a combined image derived input function and venous sampling approach for the quantification of [18F]GE-179 PET binding in the brain.

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<0.001), PWB ratio (r = 0.93, p<0.001), and the PIF (r = 0.92, p<0.001) as well as total distribution volume (VT) in 11 regions across the brain (r = 0.95, p<0.001). IDIF+venous VT had a mean bias of -1.7% and a comparable regional coefficient of variation (arterial: 21.3 ± 2.5%, IDIF+venous: 21.5 ± 2.0%). Simplification of the IDIF+venous method to use only one venous sample provided less accurate VT estimates (mean bias 9.9%; r = 0.71, p<0.001). A version of the method that avoids the need for blood sampling by combining the IDIF with population-based PF and PWB ratio estimates systematically underestimated VT (mean bias -20.9%), and produced VT estimates with a poor correlation to those obtained using arterial data (r = 0.45, p<0.001). Arterial and venous blood data from 7 TBI patients showed high correlations for PF (r = 0.92, p = 0.003) and PWB ratio (r = 0.93, p = 0.003). In conclusion, the IDIF+venous method with five venous samples provides a viable alternative to arterial sampling for quantification of [18F]GE-179 VT.

Identifying brain networks in synaptic density PET (11C-UCB-J) with independent component analysis.

BACKGROUND: The human brain is inherently organized into distinct networks, as reported widely by resting-state functional magnetic resonance imaging (rs-fMRI), which are based on blood-oxygen-level-dependent (BOLD) signal fluctuations. 11C-UCB-J PET maps synaptic density via synaptic vesicle protein 2A, which is a more direct structural measure underlying brain networks than BOLD rs-fMRI. METHODS: The aim of this study was to identify maximally independent brain source networks, i.e., "spatial patterns with common covariance across subjects", in 11C-UCB-J data using independent component analysis (ICA), a data-driven analysis method. Using a population of 80 healthy controls, we applied ICA to two 40-sample subsets and compared source network replication across samples. We examined the identified source networks at multiple model orders, as the ideal number of maximally independent components (IC) is unknown. In addition, we investigated the relationship between the strength of the loading weights for each source network and age and sex. RESULTS: Thirteen source networks replicated across both samples. We determined that a model order of 18 components provided stable, replicable components, whereas estimations above 18 were not stable. Effects of sex were found in two ICs. Nine ICs showed age-related change, with 4 remaining significant after correction for multiple comparison. CONCLUSION: This study provides the first evidence that human brain synaptic density can be characterized into organized covariance patterns. Furthermore, we demonstrated that multiple synaptic density source networks are associated with age, which supports the potential utility of ICA to identify biologically relevant synaptic density source networks.

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology.

PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level.