Y-90 PET/MR imaging optimization with a Bayesian penalized likelihood reconstruction algorithm.

Positron Emission Tomography (PET) imaging after 90 Y liver radioembolization is used for both lesion identification and dosimetry. Bayesian penalized likelihood (BPL) reconstruction algorithms are an alternative to ordered subset expectation maximization (OSEM) with improved image quality and lesion detectability. The investigation of optimal parameters for 90 Y image reconstruction of Q.Clear, a commercial BPL algorithm developed by General Electric (GE), in PET/MR is a field of interest and the subject of this study. The NEMA phantom was filled at an 8:1 sphere-to-background ratio. Acquisitions were performed on a PET/MR scanner for clinically relevant activities between 0.7 and 3.3 MBq/ml. Reconstructions with Q.Clear were performed varying the ß penalty parameter between 20 and 6000, the acquisition time between 5 and 20 min and pixel size between 1.56 and 4.69 mm. OSEM reconstructions of 28 subsets with 2 and 4 iterations with and without Time-of-Flight (TOF) were compared to Q.Clear with ß = 4000. Recovery coefficients (RC), their coefficient of variation (COV), background variability (BV), contrast-to-noise ratio (CNR) and residual activity in the cold insert were evaluated. Increasing ß parameter lowered RC, COV and BV, while CNR was maximized at ß = 4000; further increase resulted in oversmoothing. For quantification purposes, ß = 1000-2000 could be more appropriate. Longer acquisition times resulted in larger CNR due to reduced image noise. Q.Clear reconstructions led to higher CNR than OSEM. A ß of 4000 was obtained for optimal image quality, although lower values could be considered for quantification purposes. An optimal acquisition time of 15 min was proposed considering its clinical use.

Amyloid brain-dedicated PET images can diagnose Alzheimer's pathology with Centiloid Scale.

PURPOSE: To evaluate whether the Centiloid Scale may be used to diagnose Alzheimer's Disease (AD) pathology effectively with the only use of amyloid PET imaging modality from a brain-dedicated PET scanner. METHODS: This study included 26 patients with amyloid PET images with 3 different radiotracers. All patients were acquired both on a PET/CT and a brain-dedicated PET scanner (CareMiBrain, CMB), from which 4 different reconstructions were implemented. A new pipeline was proposed and used for the PET image analysis based on the original Centiloid Scale processing pipeline, but with only PET images. The Youden's Index was employed to calculate the optimal cutoffs for diagnosis and evaluated by the AUC, accuracy, precision, and recall metrics. RESULTS: The Centiloid Scale (CL) processing pipeline was validated with and without the use of MR images. The CL cutoffs for AD pathology diagnosis on the PET/CT and the 4 CMB reconstructions were 34.4 ±â€¯2.2, 43.5 ±â€¯3.5, 51.9 ±â€¯12.5, 57.5 ±â€¯6.8 and 41.8 ±â€¯1.2 respectively. Overall, for these cutoffs all metrics obtained the maximum score. CONCLUSION: The Centiloid scale applied to PET images allows for AD pathology diagnosis. The CMB scanner can be used with the Centiloid scale to automatically assist in the diagnosis of AD pathology, relieving the large burden of neurodegenerative diseases on a traditional PET/CT.

Relationship between neuroimaging and emotion recognition in mild cognitive impairment patients.

OBJECTIVE: Dementia is a major public health problem with high needs for early detection, efficient treatment, and prognosis evaluation. Social cognition impairment could be an early dementia indicator and can be assessed with emotion recognition evaluation tests. The purpose of this study is to investigate the link between different brain imaging modalities and cognitive status in Mild Cognitive Impairment (MCI) patients, with the goal of uncovering potential physiopathological mechanisms based on social cognition performance. METHODS: The relationship between the Reading the Mind in the Eyes Test (RMET) and some clinical and biochemical variables ([18 F]FDG PET-CT and anatomical MR parameters, neuropsychological evaluation, and CSF biomarkers) was studied in 166 patients with MCI by using a correlational approach. RESULTS: The RMET correlated with neuropsychological variables, as well as with structural and functional brain parameters obtained from the MR and FDG-PET imaging evaluation. However, significant correlations between the RMET and CSF biomarkers were not found. DISCUSSION: Different neuroimaging parameters were found to be related to an emotion recognition task in MCI. This analysis identified potential minimally-invasive biomarkers providing some knowledge about the physiopathological mechanisms in MCI.

Free automatic software for quality assurance of computed tomography calibration, edges and radiomics metrics reproducibility.

PURPOSE: To develop a QA procedure, easy to use, reproducible and based on open-source code, to automatically evaluate the stability of different metrics extracted from CT images: Hounsfield Unit (HU) calibration, edge characterization metrics (contrast and drop range) and radiomic features. METHODS: The QA protocol was based on electron density phantom imaging. Home-made open-source Python code was developed for the automatic computation of the metrics and their reproducibility analysis. The impact on reproducibility was evaluated for different radiation therapy protocols, and phantom positions within the field of view and systems, in terms of variability (Shapiro-Wilk test for 15 repeated measurements carried out over three days) and comparability (Bland-Altman analysis and Wilcoxon Rank Sum Test or Kendall Rank Correlation Coefficient). RESULTS: Regarding intrinsic variability, most metrics followed a normal distribution (88% of HU, 63% of edge parameters and 82% of radiomic features). Regarding comparability, HU and contrast were comparable in all conditions, and drop range only in the same CT scanner and phantom position. The percentages of comparable radiomic features independent of protocol, position and system were 59%, 78% and 54%, respectively. The non-significantly differences in HU calibration curves obtained for two different institutions (7%) translated in comparable Gamma Index G (1 mm, 1%, >99%). CONCLUSIONS: An automated software to assess the reproducibility of different CT metrics was successfully created and validated. A QA routine proposal is suggested.

Objective Image Quality Comparison Between Brain-Dedicated PET and PET/CT Scanners.

As part of a clinical validation of a new brain-dedicated PET system (CMB), image quality of this scanner has been compared to that of a whole-body PET/CT scanner. To that goal, Hoffman phantom and patient data were obtined with both devices. Since CMB does not use a CT for attenuation correction (AC) which is crucial for PET images quality, this study includes the evaluation of CMB PET images using emission-based or CT-based attenuation maps. PET images were compared using 34 image quality metrics. Moreover, a neural network was used to evaluate the degree of agreement between both devices on the patients diagnosis prediction. Overall, results showed that CMB images have higher contrast and recovery coefficient but higher noise than PET/CT images. Although SUVr values presented statistically significant differences in many brain regions, relative differences were low. An asymmetry between left and right hemispheres, however, was identified. Even so, the variations between the two devices were minor. Finally, there is a greater similarity between PET/CT and CMB CT-based AC PET images than between PET/CT and the CMB emission-based AC PET images.

Same-day comparative protocol PET/CT-PET/MRI [68 Ga]Ga-DOTA-TOC in paragangliomas and pheochromocytomas: an approach to personalized medicine.

BACKGROUND: PET/MRI is an emerging imaging modality which enables the evaluation and quantification of biochemical processes in tissues, complemented with accurate anatomical information and low radiation exposure. In the framework of theragnosis, PET/MRI is of special interest due to its ability to delineate small lesions, adequately quantify them, and therefore to plan targeted therapies. The aim of this study was to validate the diagnostic performance of [68 Ga]Ga-DOTA-TOC PET/MRI compared to PET/CT in advanced disease paragangliomas and pheochromocytomas (PGGLs) to assess in which clinical settings, PET/MRI may have a greater diagnostic yield. METHODS: We performed a same-day protocol with consecutive acquisition of a PET/CT and a PET/MRI after a single [68 Ga]Ga-DOTA-TOC injection in 25 patients. Intermodality agreement, Krenning Score (KS), SUVmax (Standard Uptake Value), target-to-liver-ratio (TLR), clinical setting, location, and size were assessed. RESULTS: The diagnostic accuracy with PET/MRI increased by 14.6% compared to PET/CT especially in bone and liver locations (mean size of new lesions was 3.73 mm). PET/MRI revealed a higher overall lesion uptake than PET/CT (TLR 4.12 vs 2.44) and implied an upward elevation of the KS in up to 60% of patients. The KS changed in 30.4% of the evaluated lesions (mean size 11.89 mm), in 18.4% of the lesions it increased from KS 2 on PET/CT to a KS ≥ 3 on PET/MRI and 24.96% of the lesions per patient with multifocal disease displayed a KS ≥ 3 on PET/MR, that were not detected or showed lower KS on PET/CT. In 12% of patients, PET/MRI modified clinical management. CONCLUSIONS: PET/MRI showed minor advantages over conventional PET/CT in the detection of new lesions but increased the intensity of SSRs expression in a significant number of them, opening the door to select which patients and clinical settings can benefit from performing PET/MRI.

Comparison of protocols with respiratory-gated (4D) motion compensation in PET/CT: open-source package for quantification of phantom image quality.

BACKGROUND: Patient's breathing affects the quality of chest images acquired with positron emission tomography/computed tomography (PET/CT) studies. Movement correction is required to optimize PET quantification in clinical settings. We present a reproducible methodology to compare the impact of different movement compensation protocols on PET image quality. Static phantom images were set as reference values, and recovery coefficients (RCs) were calculated from motion compensated images for the phantoms in respiratory movement. Image quality was evaluated in terms of: (1) volume accuracy (VA) with the NEMA phantom; (2) concentration accuracy (CA) by six refillable inserts within the electron density CIRS phantom; and (3) spatial resolution (R) with the Jaszczak phantom. Three different respiratory patterns were applied to the phantoms. We developed an open-source package to automatically analyze VA, CA and R. We compared 10 different movement compensation protocols available in the Philips Gemini TF-64 PET/CT (4-, 6-, 8- and 10-time bins, 20%-, 30%-, 40%-window width in Inhale and Exhale). RESULTS: The homemade package provided RC values for VA, CA and R of 102 PET images in less than 5 min. Results of the comparison of the 10 different protocols demonstrated the feasibility of the proposed method for quantifying the variations observed qualitatively. Overall, prospective protocols showed better motion compensation than retrospective. The best performance was obtained for the protocol Exhale 30% (0.3 s after maximum Exhale position and window width of 30%) with RC[Formula: see text], RC[Formula: see text] and RC[Formula: see text]. Among retrospective protocols, 8 Phase protocol showed the best performance. CONCLUSION: We provided an open-source package able to automatically evaluate the impact of motion compensation methods on PET image quality. A setup based on commonly available experimental phantoms is recommended. Its application for the comparison of 10 time-based approaches showed that Exhale 30% protocol had the best performance. The proposed framework is not specific to the phantoms and protocols presented on this study.

Artificial Intelligence on FDG PET Images Identifies Mild Cognitive Impairment Patients with Neurodegenerative Disease.

The purpose of this project is to develop and validate a Deep Learning (DL) FDG PET imaging algorithm able to identify patients with any neurodegenerative diseases (Alzheimer's Disease (AD), Frontotemporal Degeneration (FTD) or Dementia with Lewy Bodies (DLB)) among patients with Mild Cognitive Impairment (MCI). A 3D Convolutional neural network was trained using images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI dataset used for the model training and testing consisted of 822 subjects (472 AD and 350 MCI). The validation was performed on an independent dataset from La Fe University and Polytechnic Hospital. This dataset contained 90 subjects with MCI, 71 of them developed a neurodegenerative disease (64 AD, 4 FTD and 3 DLB) while 19 did not associate any neurodegenerative disease. The model had 79% accuracy, 88% sensitivity and 71% specificity in the identification of patients with neurodegenerative diseases tested on the 10% ADNI dataset, achieving an area under the receiver operating characteristic curve (AUC) of 0.90. On the external validation, the model preserved 80% balanced accuracy, 75% sensitivity, 84% specificity and 0.86 AUC. This binary classifier model based on FDG PET images allows the early prediction of neurodegenerative diseases in MCI patients in standard clinical settings with an overall 80% classification balanced accuracy.

Assessment of the dicentric chromosome assay as a biodosimetry tool for more personalized medicine in a case of a high risk neuroblastoma 131I-mIBG treatment.

PURPOSE: The aims of this study were to estimate the whole - body absorbed - dose with the Dicentric Chromosome Assay (DCA) (biodosimetry) for 131I - metaiodobenzylguanidine (131I - mIBG) therapy for high - risk neuroblastoma, and to obtain an initial correlation with the physical dosimetry calculated as described by the Medical Internal Radiation Dosimetry formalism (MIRD). Together both objectives will aid the optimization of personalized targeted radionuclide therapies. MATERIAL AND METHODS: A 12 year-old child with relapsed high-risk neuroblastoma was treated with 131I-mIBG: a first administration with activity <444 MBq/kg was used as a tracer in order to calculate the activity needed in a second administration to achieve a whole body prescribed dose of ∼4 Gy. Blood samples were obtained before and seven days after each administration to analyze the frequency of dicentrics. Moreover, consequent estimations of retained activity were done every few hours from equivalent dose rate measurements at a fixed position, two meters away from the patient, in order to apply the MIRD procedure. Blood samples were also drawn every 2- to -3 days to assess bone marrow toxicity. RESULTS: For a total activity of 22,867 MBq administered over two phases, both biological and physical dosimetries were performed. The former estimated a whole-body cumulated dose of 3.53 (2.58-4.41) Gy and the latter a total whole-body absorbed dose of 2.32 ± 0.48 Gy. The patient developed thrombocytopenia grade 3 after both infusions and neutropenia grade 3 and grade 4 (based on CTCAE 4.0) during respective phases. CONCLUSION: The results indicate a possible correlation between biodosimetry and standard physical dosimetry in 131I-mIBG treatment for high-risk neuroblastoma. A larger cohort and refinement of the DCA for internal irradiation are needed to define the role of biodosimetry in clinical situations.

Performance of MACACO Compton telescope for ion-beam therapy monitoring: first test with proton beams.

In order to exploit the advantages of ion-beam therapy in a clinical setting, delivery verification techniques are necessary to detect deviations from the planned treatment. Efforts are currently oriented towards the development of devices for real-time range monitoring. Among the different detector concepts proposed, Compton cameras are employed to detect prompt gammas and represent a valid candidate for real-time range verification. We present the first on-beam test of MACACO, a Compton telescope (multi-layer Compton camera) based on lanthanum bromide crystals and silicon photo-multipliers. The Compton telescope was first characterized through measurements and Monte Carlo simulations. The detector linearity was measured employing (22)Na and Am-Be sources, obtaining about 10% deviation from linearity at 3.44 MeV. A spectral image reconstruction algorithm was tested on synthetic data. Point-like sources emitting gamma rays with energy between 2 and 7 MeV were reconstructed with 3-5 mm resolution. The two-layer Compton telescope was employed to measure radiation emitted from a beam of 150 MeV protons impinging on a cylindrical PMMA target. Bragg-peak shifts were achieved via adjustment of the PMMA target location and the resulting measurements used during image reconstruction. Reconstructed Bragg peak profiles proved sufficient to observe peak-location differences within 10 mm demonstrating the potential of the MACACO Compton Telescope as a monitoring device for ion-beam therapy.