Metabolic Imaging Research Articles

CCRG-05. A UNIFYING AND SELF-REINFORCING MECHANISM OF TUMOR IMMORTALITY IN TERT PROMOTER MUTANT CANCERS

Abstract Telomerase Reverse Transcriptase promoter mutations enable tumor cell immortality in millions of cancer patients annually. While prior therapies targeting telomerase lacked tumor selectivity and were poorly tolerated, TERT promoter mutations and their regulation present a unique opportunity for tumor specific reversal of cellular immortality. The two hotspot mutations, G228A and G250A, generate identical de novo E26 transformation specific (ETS) transcription factor binding sites. However, the 28 ETS factors share a similar binding site preference, raising the question of whether all ETS factors can reactivate TERT. In glioblastoma and a few other cancers, we have shown the de novo ETS site along with a nearby native ETS site (ETS-195/200) recruit one ETS factor, the GA-binding protein (GABP) tetramer, to reactivate TERT. This GABP-mediated mechanism may be restricted to specific cancer types and the two hotspot mutations or could be widely relevant to any cancer with a de novo ETS TERT promoter mutation. We have found that the GABP tetramer activates 6 distinct mutant TERT promoters across 16 different cancer types. However, TERT expression is maintained in most tetramer depleted tumor cells as the tetramer is serially replaced by GABP dimers and weakly by a paralogous tetramer complex that increase following disengagement of GABP tetramer-mediated negative feedback loops. Elimination of both the tetramer and dimer reinstates epigenetic repression of TERT, shortens telomeres, and prevents cancer cell division. However, some knockout cancer cells avoid this fate through weak activation of TERT by the paralogous GABP tetramer complex. The compensatory maintenance of TERT expression can be overcome with a dominant negative GABPB1, leading to TERT silencing, evidenced by gene expression and non-invasive metabolic imaging correlates, and telomere shortening in TERT promoter mutant glioblastoma. We are currently investigating the delivery of this dominant negative to tumor cells via clinically approved retroviral replicating vectors.

Neural network mapping of gelastic behavior in children with hypothalamus hamartoma

BackgroundHypothalamus hamartomas (HHs) are rare, congenital, tumor-like, and nonprogressive malformations resulting in drug-resistant epilepsy, mainly affecting children. Gelastic seizures (GS) are an early hallmark of epilepsy with HH. The aim of this study was to explore the disease progression and the underlying physiopathological mechanisms of pathological laughter in HH.MethodsWe obtained clinical information and metabolic images of 56 HH patients and utilized ictal semiology evaluation to stratify the specimens into GS-only, GS-plus, and no-GS subgroups and then applied contrasted trajectories inference (cTI) to calculate the pseudotime value and evaluate GS progression. Ordinal logistic regression was performed to identify neuroimaging-clinical predictors of GS, and then voxelwise lesion network-symptom mapping (LNSM) was applied to explore GS-associated brain regions.ResultscTI inferred the specific metabolism trajectories of GS progression and revealed increased complexity from GS to other seizure types. This was further validated via actual disease duration (Pearson R = 0.532, P = 0.028). Male sex [odds ratio (OR) = 2.611, P = 0.013], low age at seizure onset (OR = 0.361, P = 0.005), high normalized HH metabolism (OR = − 1.971, P = 0.037) and severe seizure burden (OR = − 0.006, P = 0.032) were significant neuroimaging clinical predictors. LNSM revealed that the dysfunctional cortico-subcortico-cerebellar network of GS and the somatosensory cortex (S1) represented a negative correlation.ConclusionsThis study sheds light on the clinical characteristics and progression of GS in children with HH. We identified distinct subtypes of GS and demonstrated the involvement of specific brain regions at the cortical–subcortical–cerebellar level. These valuable results contribute to our understanding of the neural correlates of GS.

Abstract 13712: Imaging Short-Chain Fatty Acid Metabolism and Transport in the Failing Heart by PET

Introduction: Heart failure compromises the transport and oxidation of long chain fatty acids. Cardiomyocytes can compensate by using short-chain fatty acids (SCFA) which rely on other transport mechanisms. Based on this principle, we used 2-[ 18 F]fluoropropionic acid ([ 18 F]FPA), a radiolabeled SCFA analog, to assess these metabolic changes and image them by positron emission tomography (PET) in a doxorubicin-induced mouse model of cardiotoxicity. Hypothesis: We hypothesize that the increased demand for SCFA by the failing heart promotes cardiac accumulation of [ 18 F]FPA which can be imaged by PET. Methods: [ 18 F]FPA was injected intravenously into male C57BL/6J mice 10 weeks following intraperitoneal injections of 8 x 3 mg/kg doxorubicin (DOX). Dynamic PET acquisitions were performed from 60-120 min post injection of 9.25-11 MBq [ 18 F]FPA. These images were acquired in the presence or absence of 5 mg/kg AZD3965, an inhibitor of monocarboxylate transporters. Heart uptake of [ 18 F]FPA was determined by image-based quantitation and confirmed by a biodistribution study. Mechanistic [ 18 F]FPA uptake studies were also conducted in primary human cardiomyocyte (HCM) cultures. Results: Mice experiencing DOX-induced cardiotoxicity exhibited statistically significant increases in cardiac [ 18 F]FPA. AZD3965 did not significantly alter cardiac uptake but reduced uptake in all other tissues except the kidneys, the route of excretion. Additionally, [ 18 F]FPA uptake is lost in HCM for which mitochondrial acyl-CoA synthetase (ACSS) 1, but not cytosolic ACSS2, is inhibited. Conclusions: Our findings present both mechanistic and translational applications for [ 18 F]FPA. AZD3965 effectively reduced [ 18 F]FPA uptake in other tissues except for the heart and can therefore be co-administered to enhance the heart-to-background ratio. Altogether, our results indicate that [ 18 F]FPA may enter cardiac tissues by diffusion and become metabolically trapped in mitochondria.

Important Role for Glutamine in Human and Mouse TME Models of CLL ; Towards Development of a PET Tracer As a Novel Diagnostic Tool

The amino acid transporter ASCT2, encoded by the gene SLC1A5, is the main glutamine importer in proliferating human and mouse cells. We recently showed that glutamine is the main fuel of the tricarboxylic acid (TCA) cycle in cells from chronic lymphocytic leukemia (CLL) patients, and that blocking its import attenuated CD40/BCR-induced venetoclax (VEN) resistance 1. In the current study, we have investigated the role of ASCT2 and the consequences of its inhibition in human and mouse CLL cells and in healthy lymphocytes by flow cytometry, gene expression analysis, extracellular flux analysis, metabolomics, CRISPR/Cas9 gene editing and adoptive-cell transfer experiments. To enable in vivo assessment of ASCT2 in the future with Positron Emission Tomography (PET), we have explored the potential use of 18F-labelelled ( 2S,2R)-4-fluoroglutamine (4- 18F]FGln) 2 as PET tracer. Increased expression of ASCT2 upon PMA/ionomycin stimulation was observed in healthy B and T cells. In BCR/CD40-stimulated CLL cells, the increased expression was irrespective of IGHV status. We dissected the main routes of glutamine usage in CD40- and BCR-stimulated CLL cells and found that in addition to its role in the TCA cycle, glutamine import is linked to mTOR signaling. The ASCT2 inhibitor V9302 impaired mTOR signaling and decreased translation of new proteins, including the anti-apoptotic proteins Bcl-XL and Mcl-1. Of relevance for therapeutic approaches, the effector and proliferative capacity of human T cells was preserved upon V9302 treatment. This suggests that blocking ASCT2 will not affect immune responses. The SLC1A5 gene was deleted by CRISPR/Cas9 technique in murine TCL1 cells 3. Adoptive cell transfer experiments of SLC1A5-KO and WT TCL1 cells injected at 50-50% ratio in recipient mice showed selective outgrowth of SLC1A5-WT cells, with no detection of the SLC1A5-KO in the spleen of overt leukemic mice. This indicates that TCL1 leukemic cells rely on SLC1A5/ASCT2 for growth. Finally, we explored the high expression of ASCT2 and glutamine addiction in CLL from the diagnostic perspective. With the aim of improving the currently suboptimal [ 18F]FDG PET for imaging of CLL LN sites 4, we successfully synthesized 4-[ 18F]FGln. We observed uptake in CD40-stimulated CLL cells, which was decreased in the presence of V9302. Experiments to perform PET with 4-[ 18F]FGln in TCL1 mice to demonstrate an in vivo proof of concept are ongoing. Overall, these data support a crucial role for ASCT2 and glutamine in leukemia development and VEN resistance in CLL. This provides a basis for targeting the transporter for therapeutic options and/or taking advantage of its function for diagnostic approaches using 4-[ 18F]FGln as PET tracer. 1. Chen, Z. et al. Characterization of metabolic alterations of chronic lymphocytic leukemia in the lymph node microenvironment. Blood140, 630-643, doi:10.1182/blood.2021013990 (2022). 2. Qu, W. et al. Synthesis of optically pure 4-fluoro-glutamines as potential metabolic imaging agents for tumors. J Am Chem Soc133, 1122-1133, doi:10.1021/ja109203d (2011). 3. Nardi, F. et al. Assessing gene function in human B cells: CRISPR/Cas9-based gene editing and mRNA-based gene expression in healthy and tumor cells. Eur J Immunol52, 1362-1365, doi:10.1002/eji.202149784 (2022). 4. Rhodes, J. M. & Mato, A. R. PET/Computed Tomography in Chronic Lymphocytic Leukemia and Richter Transformation. PET Clin14, 405-410, doi:10.1016/j.cpet.2019.03.007 (2019).

Choline metabolism and its implications in cancer.

Choline, a quintessential quaternary ammonium compound, plays a cardinal role in several pivotal biological mechanisms, chiefly in safeguarding cell membrane integrity, orchestrating methylation reactions, and synthesizing vital neurotransmitters. This systematic review meticulously dissects the complex interplay between choline metabolism and its profound implications in oncology. The exposition is stratified into three salient dimensions: Initially, we delve into the intricacies of choline metabolism, accentuating its indispensability in cellular physiology, the enzymatic labyrinth governing its flux, and the pivotal cellular import mechanisms. Subsequently, we elucidate the contemporary comprehension of choline metabolism in the cancer paradigm, traversing its influence from inception to the intricate metamorphosis during oncogenic progression, further compounded by dysregulated enzyme activities and aberrant signaling cascades. Conclusively, we illuminate the burgeoning potential of choline-centric metabolic imaging modalities, notably magnetic resonance spectroscopy (MRS) and positron emission tomography (PET), as avant-garde tools for cancer diagnostics and therapeutic trajectory monitoring. Synoptically, the nuanced perturbations in choline metabolism in neoplastic entities unfurl critical insights, potentially heralding paradigm shifts in diagnostic and therapeutic oncological stratagems. A deeper foray into this realm is anticipated to fortify our molecular understanding and refine intervention modalities in cancer theranostics.

Left and right corticobasal syndrome: comparison of cognitive profiles between metabolic imaging - matched groups

BackgroundCorticobasal syndrome (CBS) is typically asymmetric. Case reports suggest that left-hemisphere CBS (lhCBS) is associated with major language impairment, and right-hemisphere CBS (rhCBS) is associated with major visuospatial deficits, but no group study has ever verified these observations. In our study, we enrolled 49 patients with CBS, classified them as lhCBS or rhCBS based on asymmetry of hypometabolism on brain FDG-PET and compared their cognitive and behavioural profiles.MethodsWe defined asymmetry of hypometabolism upon visual inspection of qualitative PET images and confirmed it through paired comparison of left- and right-hemisphere FDG uptake values. The two groups were also matched for severity of hypometabolism within the more affected and more preserved hemispheres, to unravel differences in the cognitive profiles ascribable specifically to each hemisphere’s functional specializations. All patients were assessed for memory, language, executive and visuospatial deficits, apraxia, neglect, dyscalculia, agraphia and behavioural disturbances.ResultsLhCBS (n. 26) and rhCBS (n. 23) patients did not differ for demographics, disease duration and severity of global cognitive impairment. The two cognitive profiles were largely overlapping, with two exceptions: Digit span forward was poorer in lhCBS, and visual neglect was more frequent in rhCBS.ConclusionsAfter balancing out patients for hemispheric hypometabolism, we did not confirm worse language or visuospatial deficits in, respectively, lhCBS and rhCBS. However, verbal short-term memory was more impaired in lhCBS, and spatial attention was more impaired in rhCBS. Both of these functions reflect the functional specialization of the left and right fronto-parietal pathways, i.e. of the main loci of neurodegeneration in CBS.

Exceptionally Mild and High-Yielding Synthesis of Vinyl Esters of Alpha-Ketocarboxylic Acids, Including Vinyl Pyruvate, for Parahydrogen-Enhanced Metabolic Spectroscopy and Imaging.

Metabolic changes often occur long before pathologies manifest and treatment becomes challenging. As key elements of energy metabolism, α-ketocarboxylic acids (α-KCA) are particularly interesting, e.g., as the upregulation of pyruvate to lactate conversion is a hallmark of cancer (Warburg effect). Magnetic resonance imaging with hyperpolarized metabolites has enabled imaging of this effect non-invasively and in vivo, allowing the early detection of cancerous tissue and its treatment. Hyperpolarization by means of dynamic nuclear polarization, however, is complex, slow, and expensive, while available precursors often limit parahydrogen-based alternatives. Here, we report the synthesis for novel 13C, deuterated ketocarboxylic acids, and a much-improved synthesis of 1-13C-vinyl pruvate-d6, arguably the most promising tracer for hyperpolarizing pyruvate using parahydrogen-induced hyperpolarization by side arm hydrogenation. The new synthesis is scalable and provides a high yield of 52%. We elucidated the mechanism of our Pd-catalyzed trans-vinylation reaction. Hydrogenation with parahydrogen allowed us to monitor the addition, which was found to depend on the electron demand of the vinyl ester. Electron-poor α-keto vinyl esters react slower than "normal" alkyl vinyl esters. This synthesis of 13C, deuterated α-ketocarboxylic acids opens up an entirely new class of biomolecules for fast and cost-efficient hyperpolarization with parahydrogen and their use for metabolic imaging.

Simultaneous high-resolution whole-brain MR spectroscopy and [18F]FDG PET for temporal lobe epilepsy.

Precise lateralizing the epileptogenic zone in patients with drug-resistant mesial temporal lobe epilepsy (mTLE) remains challenging, particularly when routine MRI scans are inconclusive (MRI-negative). This study aimed to investigate the synergy of fast, high-resolution, whole-brain MRSI in conjunction with simultaneous [18F]FDG PET for the lateralization of mTLE. Forty-eight drug-resistant mTLE patients (M/F 31/17, age 12-58) underwent MRSI and [18F]FDG PET on a hybrid PET/MR scanner. Lateralization of mTLE was evaluated by visual inspection and statistical classifiers of metabolic mappings against routine MRI. Additionally, this study explored how disease status influences the associations between altered N-acetyl aspartate (NAA) and FDG uptake using hierarchical moderated multiple regression. The high-resolution whole-brain MRSI data offers metabolite maps at comparable resolution to [18F]FDG PET. Visual examinations of combined MRSI and [18F]FDG PET showed an mTLE lateralization accuracy rate of 91.7% in a 48-patient cohort, surpassing routine MRI (52.1%). Notably, out of 23 MRI-negative mTLE, combined MRSI and [18F]FDG PET helped detect 19 cases. Logistical regression models combining hippocampal NAA level and FDG uptake improved lateralization performance (AUC=0.856), while further incorporating extrahippocampal regions such as amygdala, thalamus, and superior temporal gyrus increased the AUC to 0.939. Concurrent MRSI/PET revealed a moderating influence of disease duration and hippocampal atrophy on the association between hippocampal NAA and glucose uptake, providing significant new insights into the disease's trajectory. This paper reports the first metabolic imaging study using simultaneous high-resolution MRSI and [18F]FDG PET, which help visualize MRI-unidentifiable lesions and may thus advance diagnostic tools and management strategies for drug-resistant mTLE.

Metabolic interactions between organs in overweight and obesity using total-body positron emission tomography.

Overweight and obesity is a complex condition resulting from unbalanced energy homeostasis among various organs. However, systemic abnormalities in overweight and obese people are seldom explored in vivo by metabolic imaging techniques. The aim of this study was to determine metabolic abnormities throughout the body in overweight and obese adults using total-body positron emission tomography (PET) glucose uptake imaging. Thirty normal weight subjects [body mass index (BMI) < 25 kg/m2, 55.47 ± 13.94 years, 16 men and 14 women], and 26 overweight and obese subjects [BMI ≥ 25 kg/m2, 52.38 ± 9.52 years, 21 men and 5 women] received whole-body 18F-fluorodeoxyglucose PET imaging using the uEXPLORER. Whole-body standardized uptake value normalized by lean body mass (SUL) images were calculated. Metabolic networks were constructed based on the whole-body SUL images using covariance network approach. Both group-level and individual-level network differences between normal weight and overweight/obese subjects were evaluated. Correlation analysis was conducted between network properties and BMI for the overweight/obese subjects. Compared with normal weight subjects, overweight/obese subjects exhibited altered network connectivity strength in four network nodes, namely the pancreas (p = 0.033), spleen (p = 0.021), visceral adipose tissue (VAT) (p = 1.12 × 10-5) and bone (p = 0.021). Network deviations of overweight/obese subjects from the normal weight were positively correlated with BMI (r = 0.718, p = 3.64 × 10-5). In addition, overweight/obese subjects experienced altered connections between organs, and some of the altered connections, including pancreas-right lung and VAT-bilateral lung connections were significantly correlated with BMI. Overweight/obese individuals exhibit metabolic alterations in organ level, and altered metabolic interactions at the systemic level. The proposed approach using total-body PET imaging can reveal individual metabolic variability and metabolic deviations between organs, which would open up a new path for understanding metabolic alterations in overweight and obesity.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Deuterium metabolic imaging for 3D mapping of glucose metabolism in humans with central nervous system lesionsat 3T.

To explore the potential of 3T deuterium metabolic imaging (DMI) using a birdcage 2 H radiofrequency (RF) coil in both healthy volunteers and patients with central nervous system (CNS) lesions. A modified gradient filter, home-built 2 H volume RF coil, and spherical k-space sampling were employed in a three-dimensional chemical shift imaging acquisition to obtain high-quality whole-brain metabolic images of 2 H-labeled water and glucose metabolic products. These images were acquired in a healthy volunteer and three subjects with CNS lesions of varying pathologies. Hardware and pulse sequence experiments were also conducted to improve the signal-to-noise ratio of DMI at 3T. The ability to quantify local glucose metabolism in correspondence to anatomical landmarks across patients with varying CNS lesions is demonstrated, and increased lactate is observed in one patient with the most active disease. DMI offers the potential to examine metabolic activity in human subjects with CNS lesions with DMI at 3T, promising for the potential of the future clinical translation of this metabolic imaging technique.

THU608 Evaluation Of Incidental Adrenal Masses After Initial Radiographic Diagnosis

Abstract Disclosure: V. Williams: None. N. Wazzan: None. M. Abu Limon: None. J.O. Abdelkarim: None. M.G. Jakoby: None. G. Sydney: None. A. Gagen: None. H. O'neil: None. U. Tarabichi: None. Background. Incidental adrenal masses (IAM’s) are masses of the adrenal glands ≥ 1 cm in diameter discovered during imaging for an indication other than adrenal pathology. Diagnosis of IAM’s has increased with improved resolution of computed tomography (CT), but little is published on how often IAM’s are appropriately evaluated and factors that predict if assessment will occur. This study was conducted to determine the frequency with which IAM’s are evaluated according to American Association of Clinical Endocrinologists (AACE) guidelines when diagnosed on CT scans ordered by providers at the Southern Illinois University (SIU) School of Medicine, an academic medical center in rural Central Illinois. Methods. A retrospective single cohort study was performed. Patients age ≥ 18 years undergoing CT from January 1 - December 31, 2017 were eligible. Potential cases were screened by searching for “adrenal mass,” “adrenal nodule,” “adrenal lesion,” or “adrenal adenoma.” Cases were excluded if the mass had been noted before January 1, 2017, imaging was ordered for an adrenal disorder or cancer staging, or the adrenal mass was &amp;lt; 1 cm in largest diameter. Cases were reviewed to determine if recommended metabolic screening and imaging was conducted. Demographic data, insurance status, reason for imaging, type of CT scan, clinical setting, radiology description of the adrenal mass, selected comorbidities (hypertension, hypokalemia, type 2 diabetes mellitus, obesity, and osteoporosis), and referral to an endocrinologist were included as potential predictors of guideline compliant evaluation. Results. A total of 86 IAM’s were identified among 801 CT scans for a prevalence of 10.7%. Only 10 patients (11.6%) underwent metabolic evaluation, 22 had imaging follow-up (25.6%), and only 6 received both (7.0%). All patients with metabolic evaluation were referred to an endocrinologist (P &amp;lt; 0.001). Patients who underwent evaluation were more likely to have CT scans of the abdomen or abdomen and pelvis (P = 0.004) and be diagnosed with hypertension (P = 0.01). Notably, there was no difference in IAM size (evaluated 2.2 ± 1.1 cm, unevaluated 2.0 ± 1.2), and the descriptors “benign” or “benign adenoma” were included in the radiology reports of 88.9% and 88.1% of evaluated and unevaluated patients, respectively. Imaging follow-up was more likely in patients with an endocrine referral (p=0.03), on public insurance (p=0.02), and who were obese (p=0.02). Conclusion. The rate at patient’s with IAM’s were evaluated in accordance with AACE guidelines in this study was very low and may have been strongly influenced by inclusion of the descriptors “benign” or “benign adenoma” in nearly 90% of radiology reports. Providers at SIU who order CT scans need education and guidance on evaluation of IAM’s for metabolic activity and monitoring for changes in size that could indicate adrenocortical carcinoma. Presentation: Thursday, June 15, 2023

Parahydrogen‐Polarized [1‐13C]Pyruvate for Reliable and Fast Preclinical Metabolic Magnetic Resonance Imaging (Adv. Sci. 30/2023)

Parahydrogen‐Polarized [1‐¹³C]Pyruvate for Reliable and Fast Preclinical Metabolic Magnetic Resonance Imaging (Adv. Sci. 30/2023)

A Simulation of the Effects of Diffusion on Hyperpolarized [1-13C]-Pyruvate Signal Evolution.

Hyperpolarized [1-13C]-pyruvate magnetic resonance imaging is an emerging metabolic imaging method that offers unprecedented spatiotemporal resolution for monitoring tumor metabolism in vivo. To establish robust imaging biomarkers of metabolism, we must characterize phenomena that may modulate the apparent pyruvate-to-lactate conversion rate (kPL). Here, we investigate the potential effect of diffusion on pyruvate-to-lactate conversion, as failure to account for diffusion in pharmacokinetic analysis may obscure true intracellular chemical conversion rates. Changes in hyperpolarized pyruvate and lactate signal were calculated using a finite-difference time domain simulation of a two-dimensional tissue model. Signal evolution curves with intracellular kPL values from 0.02 to 1.00 s-1 were analyzed using spatially invariant one-compartment and two-compartment pharmacokinetic models. A second spatially variant simulation incorporating compartmental instantaneous mixing was fit with the same one-compartment model. When fitting with the one-compartment model, apparent kPL underestimated intracellular kPL by approximately 50% at an intracellular kPL of 0.02 s-1. This underestimation increased for larger kPL values. However, fitting the instantaneous mixing curves showed that diffusion accounted for only a small part of this underestimation. Fitting with the two-compartment model yielded more accurate intracellular kPL values. This work suggests diffusion is not a significant rate-limiting factor in pyruvate-to-lactate conversion given that our model assumptions hold true. In higher order models, diffusion effects may be accounted for by a term characterizing metabolite transport. Pharmacokinetic models used to analyze hyperpolarized pyruvate signal evolution should focus on carefully selecting the analytical model for fitting rather than accounting for diffusion effects.

Conv-eRVFL: Convolutional Neural Network Based Ensemble RVFL Classifier for Alzheimer's Disease Diagnosis.

As per the latest statistics, Alzheimer's disease (AD) has become a global burden over the following decades. Identifying AD at the intermediate stage became challenging, with mild cognitive impairment (MCI) utilizing credible biomarkers and robust learning approaches. Neuroimaging techniques like magnetic resonance imaging (MRI) and positron emission tomography (PET) are practical research approaches that provide structural atrophies and metabolic variations. With the help of MRI and PET scans, metabolic and structural changes in AD patients can be visible even ten years before the disease's onset. This paper proposes a novel wavelet packet transform-based structural and metabolic image fusion approach using MRI and PET scans. An eight-layer trained CNN extracts features from multiple layers and these features are fed to an ensemble of non-iterative random vector functional link (RVFL) models. The RVFL network incorporates the s-membership fuzzy function as an activation function that helps overcome outliers. Lastly, outputs of all the customized RVFL classifiers are averaged and fed to the RVFL classifier to make the final decision. Experiments are performed over Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and classification is made over CN vs. AD vs. MCI. The model performance obtained is decent enough to prove the effectiveness of the fusion-based ensemble approach.

Perspectives thérapeutiques dans la prise en charge des CBNPC de stade III non résécables: Therapeutic advances for the management of unresectable stage III Non-Small Cell Lung Cancer

Until 2017, the standard of care for unresectable stage III Non-Small Cell Lung Cancer (NSCLC) was a combination of radiotherapy and chemotherapy, ideally concomitantly. The main advance in recent years has been the addition of consolidation immunotherapy with durvalumab, following chemoradiotherapy, allowing to achieve an unprecedentedly 5-year survival rate of more than 40%. This now well-established standard still needs to be improved. The current therapeutic perspectives relate to the optimization of the technical modalities of radiotherapy, and especially dose escalation strategies and the integration of metabolic imaging as part of an adaptive approach. These advances have not yet translated into clear clinical benefit, and must be refined in order to benefit patients. On the other hand, the optimization of strategies for combining radiotherapy and systemic treatments, and particularly immunotherapy, is a major challenge for the future. The combination of the different approaches could be necessary in order to improve the outcome of these patients.1877-1203/© 2023 SPLF. Published by Elsevier Masson SAS. All rights reserved.

Early Assessment of Radiation Treatment at Clinical Field Strength by D2O Administration and Deuterium MRI

An accurate and non-invasive assessment of tumor response following treatment is essential. Traditional anatomical imaging techniques are insufficient before a significant morphological change can be observed. Metabolic imaging of molecular processes in the living body is also used. In recent years, deuterium magnetic resonance spectroscopic (MRS) imaging has been demonstrated as an alternative for cancer metabolic imaging by high-field (4-11T) MRI using deuterium-labeled molecules as a contrast agent. The study aim was to evaluate the feasibility of using deuterium MRI 1.5T for tumor visualization and early assessment of the efficacy of three anticancer treatment strategies (radiation and anticancer drugs) in pancreatic cancer model mice given heavy water (D2O) to induce deuterium (2H)-tissue labeling. A MIA PaCa-2 pancreatic cancer model of six BALB/c-nu mice was prepared, and repeated deuterium MRI was performed during the first 10 days after starting free drinking of 30% D2O. We also evaluated 2H accumulation in the tumor after irradiation, bevacizumab administration, or gemcitabine administration of other 20 mice. Additional confirmatory proton MRI, ex vivo metabolic hyperpolarization 13C-MRS and histopathology were performed. The mouse's whole-body distribution of 2H was visible 1 day after drinking, and the signal intensity increased daily. Although the tumor size did not change 1 and 3 days after irradiation, the amount of 2H in the tumor decreased significantly. The 2H image intensity of the tumor also significantly decreased after the administration of bevacizumab or gemcitabine. Metabolic hyperpolarization 13C-MRS, proton MRI and 2H-NMR spectroscopy confirmed the efficacy of the anticancer treatments. Deuterium MRI at 1.5T proved feasibility to track 2H distribution throughout mouse tissues during D2O administration and revealed a higher 2H accumulation in the tumor xenografts. This research demonstrated a promising successful method for early assessment of radiotherapy and chemotherapy of pancreatic cancer.

Pancreatic Cancer Derived 3-D Organoids as Clinical Tool to Predict Response to Radiation and Chemo-Radiation Therapy

Pancreatic cancer (PC) is the fourth leading cause of cancer death in both men and women. The standard of care for patients with locally advanced PC of chemotherapy, stereotactic radiotherapy (RT) or chemo-radiation-therapy has shown highly variable and limited success rates. However, three-dimensional (3D) Pancreatic tumor organoids (PTOs) have shown promise to study tumor response to drugs, and emerging treatments under in vitro conditions. We investigated the potential for using 3D organoids to evaluate the precise radiation and drug dose responses of in vivo PC tumors. PTOs were created from mouse pancreatic tumor tissues, and their microenvironment was compared to that of in vivo tumors using immunohistochemical staining. The organoids and in vivo PC tumors were treated with fractionated X-ray RT, 3-bromopyruvate (3BP) anti-tumor drug, and with a combination of 3BP + fractionated RT. We quantified treatment response by metabolic imaging and immunofluorescence of αSMA and vimentin markers. Pancreatic tumor organoids (PTOs) exhibited a similar fibrotic microenvironment and molecular response (as seen by apoptosis biomarker expression) as in vivo tumors. Untreated tumor organoids and in vivo tumor both exhibited proliferative growth of 6 folds the original size after 10 days, whereas no growth was seen for organoids and in vivo tumors treated with 8 (Gray) Gy of fractionated RT. Tumor organoids showed reduced growth rates of 3.2x and 1.8x when treated with 4 and 6 Gy fractionated RT, respectively. Interestingly, combination of 100 µM of 3BP + 4 Gy of RT showed pronounced growth inhibition as compared to 3-BP alone or 4 Gy of radiation alone. Further, we observed overexpression of OCT-4, SOX2, Nanog cancer stem cell markers (CSC) indicated presence of cancer stem cells in tumor organoids which might have some role in resistance to therapies and recurrence in pancreatic cancer. PTOs produced a similar microenvironment and exhibited similar growth characteristics as in vivo tumors following treatment, indicating their potential for predicting in vivo tumor sensitivity and response to RT and combined chemo-RT treatments. Cancer stem cells in pancreatic cancer could be playing a role in resistance to therapies and recurrence in pancreatic cancer.

Image-Guided Precision Medicine in the Diagnosis and Treatment of Pheochromocytomas and Paragangliomas.

In this comprehensive review, we aimed to discuss the current state-of-the-art medical imaging for pheochromocytomas and paragangliomas (PPGLs) diagnosis and treatment. Despite major medical improvements, PPGLs, as with other neuroendocrine tumors (NETs), leave clinicians facing several challenges; their inherent particularities and their diagnosis and treatment pose several challenges for clinicians due to their inherent complexity, and they require management by multidisciplinary teams. The conventional concepts of medical imaging are currently undergoing a paradigm shift, thanks to developments in radiomic and metabolic imaging. However, despite active research, clinical relevance of these new parameters remains unclear, and further multicentric studies are needed in order to validate and increase widespread use and integration in clinical routine. Use of AI in PPGLs may detect changes in tumor phenotype that precede classical medical imaging biomarkers, such as shape, texture, and size. Since PPGLs are rare, slow-growing, and heterogeneous, multicentric collaboration will be necessary to have enough data in order to develop new PPGL biomarkers. In this nonsystematic review, our aim is to present an exhaustive pedagogical tool based on real-world cases, dedicated to physicians dealing with PPGLs, augmented by perspectives of artificial intelligence and big data.

Nonfluent Variant Primary Progressive Aphasia on FDG, 11 C-PIB, and 18 F-APN-1607 PET Imaging.

A 61-year-old right-handed man presented with decreased cognitive function, short-term memory, fluent speech disorders, and grammatical errors for 1 year. The patient underwent PET imaging with 11 C-PIB, 18 F-FDG, and 18 F-APN-1607. The 11 C-PIB PET showed no amyloid accumulation; the 18 F-FDG PET showed hypometabolism in the bilateral frontal lobe, temporal lobe, and midbrain; and the 18 F-APN-1607 PET showed tau accumulation in the brainstem, basal ganglia, and left inferior frontal gyrus. These findings suggested a diagnosis of nonfluent variant primary progressive aphasia. This case emphasizes the value of combined imaging of glucose metabolism, Aβ, and tau PET in the diagnosis of nonfluent variant primary progressive aphasia.