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.

Development and evaluation of two open-source nnU-Net models for automatic segmentation of lung tumors on PET and CT images with and without respiratory motion compensation.

OBJECTIVES: In lung cancer, one of the main limitations for the optimal integration of the biological and anatomical information derived from Positron Emission Tomography (PET) and Computed Tomography (CT) is the time and expertise required for the evaluation of the different respiratory phases. In this study, we present two open-source models able to automatically segment lung tumors on PET and CT, with and without motion compensation. MATERIALS AND METHODS: This study involved time-bin gated (4D) and non-gated (3D) PET/CT images from two prospective lung cancer cohorts (Trials 108237 and 108472) and one retrospective. For model construction, the ground truth (GT) was defined by consensus of two experts, and the nnU-Net with 5-fold cross-validation was applied to 560 4D-images for PET and 100 3D-images for CT. The test sets included 270 4D- images and 19 3D-images for PET and 80 4D-images and 27 3D-images for CT, recruited at 10 different centres. RESULTS: In the performance evaluation with the multicentre test sets, the Dice Similarity Coefficients (DSC) obtained for our PET model were DSC(4D-PET) = 0.74 ± 0.06, improving 19% relative to the DSC between experts and DSC(3D-PET) = 0.82 ± 0.11. The performance for CT was DSC(4D-CT) = 0.61 ± 0.28 and DSC(3D-CT) = 0.63 ± 0.34, improving 4% and 15% relative to DSC between experts. CONCLUSIONS: Performance evaluation demonstrated that the automatic segmentation models have the potential to achieve accuracy comparable to manual segmentation and thus hold promise for clinical application. The resulting models can be freely downloaded and employed to support the integration of 3D- or 4D- PET/CT and to facilitate the evaluation of its impact on lung cancer clinical practice. CLINICAL RELEVANCE STATEMENT: We provide two open-source nnU-Net models for the automatic segmentation of lung tumors on PET/CT to facilitate the optimal integration of biological and anatomical information in clinical practice. The models have superior performance compared to the variability observed in manual segmentations by the different experts for images with and without motion compensation, allowing to take advantage in the clinical practice of the more accurate and robust 4D-quantification. KEY POINTS: Lung tumor segmentation on PET/CT imaging is limited by respiratory motion and manual delineation is time consuming and suffer from inter- and intra-variability. Our segmentation models had superior performance compared to the manual segmentations by different experts. Automating PET image segmentation allows for easier clinical implementation of biological information.

The contribution of brain volume to explain autonomous imbalance during recovery from acute stress in batterers.

AIM: Many authors have suggested that intimate partner violence (IPV) perpetrators present an imbalance between both branches of the autonomous nervous system when coping with acute stress. Concretely, there is a predominance of the sympathetic branches over the parasympathetic ones when recovering from stress. This imbalance can be explained by their tendency toward anger rumination, and more concretely, by their focus on thoughts of revenge during this period. Unfortunately, there is a gap in the scientific literature in terms of using magnetic resonance imaging (MRI) techniques to assess which brain structures would explain this tendency of IPV perpetrators when coping with acute stress. METHOD: The main objective of this study was to assess whether the gray matter volume (GMV) of relevant brain structures, signaled in previous scientific literature, moderates the association between thoughts of revenge and sympathetic activation during the recovery period, based on skin conductance levels (SCL) after being exposed to stress, in a group of IPV perpetrators (n = 58) and non-violent men (n = 61). RESULTS: This study highlighted that the GMV of the left nucleus accumbens, right lobules of the cerebellum, and inferior temporal gyrus in IPV perpetrators moderated the association between thoughts of revenge and SCL during the recovery period. Accordingly, the higher the thoughts of revenge, the higher the sympathetic predominance (or higher SCL levels), especially among IPV perpetrators with the lowest GMV of these brain structures. Nonetheless, those variables were unrelated in the control group. CONCLUSIONS: Our study highlights the involvement of certain brain structures and how they explain the tendency of some IPV perpetrators to ruminate anger or, more precisely, to focus on thoughts of revenge when they recover from acute stress. These results reinforce the need to incorporate neuroimaging techniques during screening processes to properly understand how IPV perpetrators deal with stress, which in turn helps target their needs and design concrete intervention modules.

Design and validation of a decision support checklist for efficient resource allocation in research projects during proposal preparation.

PURPOSE: This article presents the design and validation of evaluation criteria checklist aimed at facilitating decision-making processes regarding participation in research projects and allocation of resources before the preparation of research proposals. MATERIALS AND METHODS: A multidisciplinary team developed a comprehensive evaluation focusing on the proposal preparation phase of research projects. A Delphi survey method was used to establish a connection between the relevance of the project and the possible success of research proposals. Assessment criteria were agreed upon, each assigned specific weights. The results of the survey were applied to a database of 62 proposals for which our research group sought funding during 2020-2021. The method was validated using the funding body's outcomes (approval or rejection) of the submitted proposals as the ground truth per project type (national, European and regional). RESULTS: The results of the survey generated a checklist of 8 criteria (excellence, impact, and efficiency aspects) that effectively assess the possibility of success of research proposals during the preparatory phase. For national projects, the tool validation demonstrated a sensitivity of 100% and a specificity of 76.19%; European projects exhibited a sensitivity of 100% and a specificity of 53.84%; and regional projects showed a sensitivity of 80% and a specificity of 30%. CONCLUSIONS: By establishing an agreed set of evaluation criteria, the developed comprehensive index enables a more precise decision support tool for the participation in research proposals and the allocation of necessary resources. This control system saves valuable time and effort for research groups while enhancing the overall efficiency of available resources.

A Gadolinium(III) Complex Based on Pyridoxine Molecule with Single-Ion Magnet and Magnetic Resonance Imaging Properties.

Pyridoxine (pyr) is a versatile molecule that forms part of the family of B vitamins. It is used to treat and prevent vitamin B6 deficiency and certain types of metabolic disorders. Moreover, the pyridoxine molecule has been investigated as a suitable ligand toward metal ions. Nevertheless, the study of the magnetic properties of metal complexes containing lanthanide(III) ions and this biomolecule is unexplored. We have synthesized and characterized a novel pyridoxine-based GdIII complex of formula [GdIII(pyr)2(H2O)4]Cl3 · 2 H2O (1) [pyr = pyridoxine]. 1 crystallizes in the triclinic system and space group Pi. In its crystal packing, cationic [Gd(pyr)2(H2O)4]3+ entities are connected through H-bonding interactions involving non-coordinating water molecules and chloride anions. In addition, Hirshfeld surfaces of 1 were calculated to further investigate their intermolecular interactions in the crystal lattice. Our investigation of the magnetic properties of 1, through ac magnetic susceptibility measurements, reveals the occurrence of a slow relaxation in magnetization in this mononuclear GdIII complex, indicating an unusual single-ion magnet (SIM) behavior for this pseudo-isotropic metal ion at very low temperatures. We also studied the relaxometric properties of 1, as a potential contrast agent for high-field magnetic resonance imaging (MRI), from solutions of 1 prepared in physiological serum (0.0-3.2 mM range) and measured at 3 T on a clinical MRI scanner. The values of relaxivity obtained for 1 are larger than those of some commercial MRI contrast agents based on mononuclear GdIII systems.

The role of intimate partner violence perpetrators' resting state functional connectivity in treatment compliance and recidivism.

To expand the scientific literature on how resting state functional connectivity (rsFC) magnetic resonance imaging (MRI) (or the measurement of the strength of the coactivation of two brain regions over a sustained period of time) can be used to explain treatment compliance and recidivism among intimate partner violence (IPV) perpetrators. Therefore, our first aim was to assess whether men convicted of IPV (n = 53) presented different rsFC patterns from a control group of non-violent (n = 47) men. We also analyzed if the rsFC of IPV perpetrators before staring the intervention program could explain treatment compliance and recidivism one year after the intervention ended. The rsFC was measured by applying a whole brain analysis during a resting period, which lasted 45 min. IPV perpetrators showed higher rsFC in the occipital brain areas compared to controls. Furthermore, there was a positive association between the occipital pole (OP) and temporal lobes (ITG) and a negative association between the occipital (e.g., occipital fusiform gyrus, visual network) and both the parietal lobe regions (e.g., supramarginal gyrus, parietal operculum cortex, lingual gyrus) and the putamen in IPV perpetrators. This pattern was the opposite in the control group. The positive association between many of these occipital regions and the parietal, frontal, and temporal regions explained treatment compliance. Conversely, treatment compliance was also explained by a reduced rsFC between the rostral prefrontal cortex and the frontal gyrus and both the occipital and temporal gyrus, and between the temporal and the occipital and cerebellum areas and the sensorimotor superior networks. Last, the enhanced rsFC between the occipital regions and both the cerebellum and temporal gyrus predicted recidivism. Our results highlight that there are specific rsFC patterns that can distinguish IPV perpetrators from controls. These rsFC patterns could be useful to explain treatment compliance and recidivism among IPV perpetrators.

Translating radiological research into practice-from discovery to clinical impact.

At the European Society of Radiology (ESR), we strive to provide evidence for radiological practices that improve patient outcomes and have a societal impact. Successful translation of radiological research into clinical practice requires multiple factors including tailored methodology, a multidisciplinary approach aiming beyond technical validation, and a focus on unmet clinical needs. Low levels of evidence are a threat to radiology, resulting in low visibility and credibility. Here, we provide the background and rationale for the thematic series Translating radiological research into practice-from discovery to clinical impact, inviting authors to describe their processes of achieving clinically impactful radiological research. We describe the challenges unique to radiological research. Additionally, a survey was sent to non-radiological clinical societies. The majority of respondents (6/11) were in the field of gastrointestinal/abdominal medicine. The implementation of CT/MRI techniques for disease characterisation, detection and staging of cancer, and treatment planning and radiological interventions were mentioned as the most important radiological developments in the past years. The perception was that patients are substantially unaware of the impact of these developments. Unmet clinical needs were mostly early diagnosis and staging of cancer, microstructural/functional assessment of tissues and organs, and implant assessment. All but one respondent considered radiology important for research in their discipline, but five indicated that radiology is currently not involved in their research. Radiology research holds the potential for being transformative to medical practice. It is our responsibility to take the lead in studies including radiology and strive towards the highest levels of evidence.Critical relevance statement For radiological research to make a clinical and societal impact, radiologists should take the lead in radiological studies, go beyond the assessment of technical feasibility and diagnostic accuracy, and-in a multidisciplinary approach-address clinical unmet needs.Key points• Multiple factors are essential for radiological research to make a clinical and societal impact.• Radiological research needs to go beyond diagnostic accuracy and address unmet clinical needs.• Radiologists should take the lead in radiological studies with a multidisciplinary approach.

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII.

PURPOSE: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. METHODS: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. RESULT: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. CONCLUSION: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. CRITICAL RELEVANCE STATEMENT: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. KEY POINTS: • A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).

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.

Development and validation of an image biomarker to identify metabolic dysfunction associated steatohepatitis: MR-MASH score.

BACKGROUND AND AIMS: Diagnosis of metabolic dysfunction-associated steatohepatitis (MASH) requires histology. In this study, a magnetic resonance imaging (MRI) score was developed and validated to identify MASH in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Secondarily, a screening strategy for MASH diagnosis was investigated. METHODS: This prospective multicentre study included 317 patients with biopsy-proven MASLD and contemporaneous MRI. The discovery cohort (Spain, Portugal) included 194 patients. NAFLD activity score (NAS) and fibrosis were assessed with the NASH-CRN histologic system. MASH was defined by the presence of steatosis, lobular inflammation, and ballooning, with NAS ≥4 with or without fibrosis. An MRI-based composite biomarker of Proton Density Fat Fraction and waist circumference (MR-MASH score) was developed. Findings were afterwards validated in an independent cohort (United States, Spain) with different MRI protocols. RESULTS: In the derivation cohort, 51% (n = 99) had MASH. The MR-MASH score identified MASH with an AUC = .88 (95% CI .83-.93) and strongly correlated with NAS (r = .69). The MRI score lower cut-off corresponded to 88% sensitivity with 86% NPV, while the upper cut-off corresponded to 92% specificity with 87% PPV. MR-MASH was validated with an AUC = .86 (95% CI .77-.92), 91% sensitivity (lower cut-off) and 87% specificity (upper cut-off). A two-step screening strategy with sequential MR-MASH examination performed in patients with indeterminate-high FIB-4 or transient elastography showed an 83-84% PPV to identify MASH. The AUC of MR-MASH was significantly higher than that of the FAST score (p < .001). CONCLUSIONS: The MR-MASH score has clinical utility in the identification and management of patients with MASH at risk of progression.

Proteometabolomics of initial and recurrent glioblastoma highlights an increased immune cell signature with altered lipid metabolism.

BACKGROUND: There is an urgent need to better understand the mechanisms associated with the development, progression, and onset of recurrence after initial surgery in glioblastoma (GBM). The use of integrative phenotype-focused -omics technologies such as proteomics and lipidomics provides an unbiased approach to explore the molecular evolution of the tumor and its associated environment. METHODS: We assembled a cohort of patient-matched initial (iGBM) and recurrent (rGBM) specimens of resected GBM. Proteome and metabolome composition were determined by mass spectrometry-based techniques. We performed neutrophil-GBM cell coculture experiments to evaluate the behavior of rGBM-enriched proteins in the tumor microenvironment. ELISA-based quantitation of candidate proteins was performed to test the association of their plasma concentrations in iGBM with the onset of recurrence. RESULTS: Proteomic profiles reflect increased immune cell infiltration and extracellular matrix reorganization in rGBM. ASAH1, SYMN, and GPNMB were highly enriched proteins in rGBM. Lipidomics indicates the downregulation of ceramides in rGBM. Cell analyses suggest a role for ASAH1 in neutrophils and its localization in extracellular traps. Plasma concentrations of ASAH1 and SYNM show an association with time to recurrence. CONCLUSIONS: We describe the potential importance of ASAH1 in tumor progression and development of rGBM via metabolic rearrangement and showcase the feedback from the tumor microenvironment to plasma proteome profiles. We report the potential of ASAH1 and SYNM as plasma markers of rGBM progression. The published datasets can be considered as a resource for further functional and biomarker studies involving additional -omics technologies.

Increased femoral anteversion in females with anterior knee pain relates to both the neck and the shaft of the femur.

INTRODUCTION: Increased femoral anteversion (FAV) can have many clinical manifestations, including anterior knee pain (AKP). To our knowledge, no studies have measured the location of FAV in a cohort of female AKP patients. The objective of this research is to determine whether the increased FAV in AKP females originates above the lesser trochanter, below the lesser trochanter or at both levels. MATERIALS AND METHODS: Thrity-seven consecutive AKP female patients (n = 66 femurs) were recruited prospectively. There were 17 patients (n = 26 femurs; mean age of 28 years) in whom the suspicion for the increased FAV of the femur was based on the clinical examination (pathological group-PG). The control group (CG) consisted of 20 patients (n = 40 femurs; mean age of 29 years) in whom there was no increased FAV from the clinical standpoint. All of them underwent a torsional computed tomography of the lower limbs. FAV was measured according to Murphy´s method. A segmental analysis of FAV was performed using the lesser trochanter as a landmark. RESULTS: Significant differences in the total FAV (18.7 ± 5.52 vs. 42.46 ± 6.33; p < 0.001), the neck version (54.88 ± 9.64 vs. 64.27 ± 11.25; p = 0.0006) and the diaphysis version (- 36.17 ± 8.93 vs. - 21.81 ± 11.73; p < 0.001) were observed between the CG and the PG. The difference in the diaphyseal angle between CG and PG accounts for 60% of the total difference between healthy and pathological groups, while the difference between both groups in the angle of the neck accounts for 40%. CONCLUSION: In chronic AKP female patients with increased FAV, the two segments of the femur contribute to the total FAV, with a different pattern among patients and controls, being the compensation mechanism of the diaphysis much lower in the pathological femurs than in the controls.

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.

Brain network functional connectivity changes in patients with anterior knee pain: a resting-state fMRI exploratory study.

BACKGROUND: This study investigates the functional brain connectivity in patients with anterior knee pain (AKP). While biomechanical models are frequently employed to investigate AKP, it is important to recognize that pain can manifest even in the absence of structural abnormalities. Leveraging the capabilities of functional magnetic resonance imaging (fMRI), this research aims to investigate the brain mechanisms present in AKP patients. METHODS: Forty-five female subjects (24 AKP patients, 21 controls) underwent resting-state fMRI and T1-weighted structural MRI. Functional brain connectivity patterns were analyzed, focusing on pain network areas, and the influence of catastrophizing thoughts was evaluated. RESULTS: Comparing patients and controls, several findings emerged. First, patients with AKP exhibited increased correlation between the right supplementary motor area and cerebellum I, as well as decreased correlation between the right insula and the left rostral prefrontal cortex and superior frontal gyrus. Second, in AKP patients with catastrophizing thoughts, there was increased correlation of the left lateral parietal cortex with two regions of the right cerebellum (II and VII) and the right pallidum, and decreased correlation between the left medial frontal gyrus and the right thalamus. Furthermore, the correlation between these regions showed promising results for discriminating AKP patients from controls, achieving a cross-validation accuracy of 80.5%. CONCLUSIONS: Resting-state fMRI revealed correlation differences in AKP patients compared to controls and based on catastrophizing thoughts levels. These findings shed light on neural correlates of chronic pain in AKP, suggesting that functional brain connectivity alterations may be linked to pain experience in this population. RELEVANCE STATEMENT: Etiopathogenesis of pain in anterior knee pain patients might not be limited to the knee, but also to underlying alterations in the central nervous system: cortical changes might lead a perpetuation of pain. KEY POINTS: • Anterior knee pain patients exhibit distinct functional brain connectivity compared to controls, and among catastrophizing subgroups. • Resting-state fMRI reveals potential for discriminating anterior knee pain patients with 80.5% accuracy. • Functional brain connectivity differences improve understanding of pain pathogenesis and objective anterior knee pain identification.

Predictive value of texture analysis on lumbar MRI in patients with chronic low back pain.

PURPOSE: The aim of this study was to determine whether MRI texture analysis could predict the prognosis of patients with non-specific chronic low back pain. METHODS: A prospective observational study was conducted on 100 patients with non-specific chronic low back pain, who underwent a conventional MRI, followed by rehabilitation treatment, and revisited after 6 months. Sociodemographic variables, numeric pain scale (NPS) value, and the degree of disability as measured by the Roland-Morris disability questionnaire (RMDQ), were collected. The MRI analysis included segmentation of regions of interest (vertebral endplates and intervertebral disks from L3-L4 to L5-S1, paravertebral musculature at the L4-L5 space) to extract texture variables (PyRadiomics software). The classification random forest algorithm was applied to identify individuals who would improve less than 30% in the NPS or would score more than 4 in the RMDQ at the end of the follow-up. Sensitivity, specificity, and the area under the ROC curve were calculated. RESULTS: The final series included 94 patients. The predictive model for classifying patients whose pain did not improve by 30% or more offered a sensitivity of 0.86, specificity 0.57, and area under the ROC curve 0.71. The predictive model for classifying patients with a RMDQ score 4 or more offered a sensitivity of 0.83, specificity of 0.20, and area under the ROC curve of 0.52. CONCLUSION: The texture analysis of lumbar MRI could help identify patients who are more likely to improve their non-specific chronic low back pain through rehabilitation programs, allowing a personalized therapeutic plan to be established.

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project, as a noninvasive and reliable way to improve the diagnosis and prognosis in pediatric oncology. The PRIMAGE project is a European multi-center research initiative that focuses on developing medical imaging-derived artificial intelligence (AI) solutions designed to enhance overall management and decision-making for two types of pediatric cancer: neuroblastoma and diffuse intrinsic pontine glioma. To allow this, the PRIMAGE project has created an open-cloud platform that combines imaging, clinical, and molecular data together with AI models developed from this data, creating a comprehensive decision support environment for clinicians managing patients with these two cancers. In order to achieve this, a standardized data processing and analysis workflow was implemented to generate robust and reliable predictions for different clinical endpoints. Magnetic resonance (MR) image harmonization and registration was performed as part of the workflow. Subsequently, an automated tool for the detection and segmentation of tumors was trained and internally validated. The Dice similarity coefficient obtained for the independent validation dataset was 0.997, indicating compatibility with the manual segmentation variability. Following this, radiomics and deep features were extracted and correlated with clinical endpoints. Finally, reproducible and relevant imaging quantitative features were integrated with clinical and molecular data to enrich both the predictive models and a set of visual analytics tools, making the PRIMAGE platform a complete clinical decision aid system. In order to ensure the advancement of research in this field and to foster engagement with the wider research community, the PRIMAGE data repository and platform are currently being integrated into the European Federation for Cancer Images (EUCAIM), which is the largest European cancer imaging research infrastructure created to date.

Pancreatic steatosis and iron overload increases cardiovascular risk in non-alcoholic fatty liver disease.

Objective: To assess the prevalence of pancreatic steatosis and iron overload in non-alcoholic fatty liver disease (NAFLD) and their correlation with liver histology severity and the risk of cardiometabolic diseases. Method: A prospective, multicenter study including NAFLD patients with biopsy and paired Magnetic Resonance Imaging (MRI) was performed. Liver biopsies were evaluated according to NASH Clinical Research Network, hepatic iron storages were scored, and digital pathology quantified the tissue proportionate areas of fat and iron. MRI-biomarkers of fat fraction (PDFF) and iron accumulation (R2*) were obtained from the liver and pancreas. Different metabolic traits were evaluated, cardiovascular disease (CVD) risk was estimated with the atherosclerotic CVD score, and the severity of iron metabolism alteration was determined by grading metabolic hiperferritinemia (MHF). Associations between CVD, histology and MRI were investigated. Results: In total, 324 patients were included. MRI-determined pancreatic iron overload and moderate-to severe steatosis were present in 45% and 25%, respectively. Liver and pancreatic MRI-biomarkers showed a weak correlation (r=0.32 for PDFF, r=0.17 for R2*). Pancreatic PDFF increased with hepatic histologic steatosis grades and NASH diagnosis (p<0.001). Prevalence of pancreatic steatosis and iron overload increased with the number of metabolic traits (p<0.001). Liver R2* significantly correlated with MHF (AUC=0.77 [0.72-0.82]). MRI-determined pancreatic steatosis (OR=3.15 [1.63-6.09]), and iron overload (OR=2.39 [1.32-4.37]) were independently associated with high-risk CVD. Histologic diagnosis of NASH and advanced fibrosis were also associated with high-risk CVD. Conclusion: Pancreatic steatosis and iron overload could be of utility in clinical decision-making and prognostication of NAFLD.

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.