Metabolic Imaging Research Articles

18F]FDG PET integrated with structural MRI for accurate brain age prediction.

Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data. The dataset comprised participants from both the Universal Medical Imaging Diagnostic Center (UMIDC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The former recruited 395 normal control (NC) subjects, while the latter included 438 NC subjects, 51 mild cognitive impairment (MCI) subjects, and 56 Alzheimer's disease (AD) subjects. We developed a novel dual-pathway, 3D simple fully convolutional network (Dual-SFCNeXt) to estimate brain age using [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) and structural magnetic resonance imaging (sMRI) images of NC subjects as input. Several prevailing DL models were trained and tested using either MRI or PET data for comparison. Model accuracies were evaluated using mean absolute error (MAE) and Pearson's correlation coefficient (r). Brain age gap (BAG), deviations of brain age from chronologic age, was correlated with cognitive assessments in MCI and AD subjects. Both PET- and MRI-based models achieved high prediction accuracy. The leading model was the SFCNeXt (the single-pathway version) for PET (MAE = 2.92, r = 0.96) and MRI (MAE = 3.23, r = 0.95) on all samples. By integrating both PET and MRI images, the Dual-SFCNeXt demonstrated significantly improved accuracy (MAE = 2.37, r = 0.97) compared to all single-modality models. Significantly higher BAG was observed in both the AD (P < 0.0001) and MCI (P < 0.0001) groups compared to the NC group. BAG correlated significantly with Mini-Mental State Examination (MMSE) scores (r=-0.390 for AD, r=-0.436 for MCI) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) scores (r = 0.333 for AD, r = 0.372 for MCI). The integration of [18F]FDG PET with structural MRI enhances the accuracy of brain age prediction, potentially introducing a new avenue for related multimodal brain age prediction studies.

Multiarm, non-randomised, single-centre feasibility study—investigation of the differential biology between benign and malignant renal masses using advanced magnetic resonance imaging techniques (IBM-Renal): protocol

IntroductionLocalised renal masses are an increasing burden on healthcare due to the rising number of cases. However, conventional imaging cannot reliably distinguish between benign and malignant renal masses, and renal...

Multi-contrast image super-resolution with deformable attention and neighborhood-based feature aggregation (DANCE): Applications in anatomic and metabolic MRI

Multi-contrast magnetic resonance imaging (MRI) reflects information about human tissues from different perspectives and has wide clinical applications. By utilizing the auxiliary information from reference images (Refs) in the easy-to-obtain modality, multi-contrast MRI super-resolution (SR) methods can synthesize high-resolution (HR) images from their low-resolution (LR) counterparts in the hard-to-obtain modality. In this study, we systematically discussed the potential impacts caused by cross-modal misalignments between LRs and Refs and, based on this discussion, proposed a novel deep-learning-based method with Deformable Attention and Neighborhood-based feature aggregation to be Computationally Efficient (DANCE) and insensitive to misalignments. Our method has been evaluated in two public MRI datasets, i.e., IXI and FastMRI, and an in-house MR metabolic imaging dataset with amide proton transfer weighted (APTW) images. Experimental results reveal that our method consistently outperforms baselines in various scenarios, with significant superiority observed in the misaligned group of IXI dataset and the prospective study of the clinical dataset. The robustness study proves that our method is insensitive to misalignments, maintaining an average PSNR of 30.67 dB when faced with a maximum range of ±9°and ±9 pixels of rotation and translation on Refs. Given our method’s desirable comprehensive performance, good robustness, and moderate computational complexity, it possesses substantial potential for clinical applications.

Simultaneous assessment of NAD(P)H and flavins with multispectral fluorescence lifetime imaging microscopy at a single excitation wavelength of 750nm.

Autofluorescence characteristics of the reduced nicotinamide adenine dinucleotide and oxidized flavin cofactors are important for the evaluation of the metabolic status of the cells. The approaches that involve a detailed analysis of both spectral and time characteristics of the autofluorescence signals may provide additional insights into the biochemical processes in the cells and biological tissues and facilitate the transition of spectral fluorescence lifetime imaging into clinical applications. We present the experiments on multispectral fluorescence lifetime imaging with a detailed analysis of the fluorescence decays and spectral profiles of the reduced nicotinamide adenine dinucleotide and oxidized flavin under a single excitation wavelength aimed at understanding whether the use of multispectral detection is helpful for metabolic imaging of cancer cells. We use two-photon spectral fluorescence lifetime imaging microscopy. Starting from model solutions, we switched to cell cultures treated by metabolic inhibitors and then studied the metabolism of cells within tumor spheroids. The use of a multispectral detector in combination with an excitation at a single wavelength of 750nm allows the identification of fluorescence signals from three components: free and bound NAD(P)H, and flavins based on the global fitting procedure. Multispectral data make it possible to assess not only the lifetime but also the spectral shifts of emission of flavins caused by chemical perturbations. Altogether, the informative parameters of the developed approach are the ratio of free and bound NAD(P)H amplitudes, the decay time of bound NAD(P)H, the amplitude of flavin fluorescence signal, the fluorescence decay time of flavins, and the spectral shift of the emission signal of flavins. Hence, with multispectral fluorescence lifetime imaging, we get five independent parameters, of which three are related to flavins. The approach to probe the metabolic state of cells in culture and spheroids using excitation at a single wavelength of 750nm and a fluorescence time-resolved spectral detection with the consequent global analysis of the data not only simplifies image acquisition protocol but also allows to disentangle the impacts of free and bound NAD(P)H, and flavin components evaluate changes in their fluorescence parameters (emission spectra and fluorescence lifetime) upon treating cells with metabolic inhibitors and sense metabolic heterogeneity within 3D tumor spheroids.

The Use of Patient-Derived Organoids in the Study of Molecular Metabolic Adaptation in Breast Cancer

Around 13% of women will likely develop breast cancer during their lifetime. Advances in cancer metabolism research have identified a range of metabolic reprogramming events, such as altered glucose and amino acid uptake, increased reliance on glycolysis, and interactions with the tumor microenvironment (TME), all of which present new opportunities for targeted therapies. However, studying these metabolic networks is challenging in traditional 2D cell cultures, which often fail to replicate the three-dimensional architecture and dynamic interactions of real tumors. To address this, organoid models have emerged as powerful tools. Tumor organoids are 3D cultures, often derived from patient tissue, that more accurately mimic the structural and functional properties of actual tumor tissues in vivo, offering a more realistic model for investigating cancer metabolism. This review explores the unique metabolic adaptations of breast cancer and discusses how organoid models can provide deeper insights into these processes. We evaluate the most advanced tools for studying cancer metabolism in three-dimensional culture models, including optical metabolic imaging (OMI), matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), and recent advances in conventional techniques applied to 3D cultures. Finally, we explore the progress made in identifying and targeting potential therapeutic targets in breast cancer metabolism.

Merging Metabolic Modeling and Imaging for Screening Therapeutic Targets in Colorectal Cancer.

Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved a novel machine learning-based method to computationally screen, in a high-throughput manner, the effects of enzyme perturbations predicted by a computational model of CRC metabolism. This approach reveals the network-wide effects of metabolic perturbations. Our results highlighted hexokinase (HK) as the crucial target, which subsequently became our focus for experimental validation using patient-derived tumor organoids (PDTOs). Through metabolic imaging and viability assays, we found that PDTOs cultured in CAF-conditioned media exhibited increased sensitivity to HK inhibition, confirming the model predictions. Our approach emphasizes the critical role of integrating computational and experimental techniques in exploring and exploiting CRC-CAF crosstalk.

Exploring Metabolic Aberrations after Intracerebral Hemorrhage In Vivo with Deuterium Metabolic Spectroscopy Imaging.

Aberrations in metabolism after intracerebral hemorrhage (ICH), particularly lactate metabolism, play a crucial role in the pathophysiology and patient outcome. To date, the evaluation of metabolism relies heavily on invasive methods such as microdialysis, restricting a comprehensive understanding of the metabolic mechanisms associated with ICH. This study proposes a noninvasive metabolic imaging method based on 2H magnetic resonance spectroscopy and imaging (2H-MRS/MRSI) to detect metabolic changes after ICH in vivo. To overcome the low-sensitivity limitation of 2H, we designed a new 1H-2H double-resonance coil with 2H-channel active detuning and proposed chemical shift imaging based on the balanced steady-state free precession method (CSI-bSSFP). Compared with the volume coil, the signal-to-noise ratio (SNR) of the new coil was increased by 4.5 times. In addition, the SNR of CSI-bSSFP was 1.5 times higher than that of conventional CSI. These two technologies were applied to measure lactate metabolic flux at different phases of ICH. The results show a higher lactate concentration in ICH rats than in control rats, which is in line with the increased expression of lactate dehydrogenase measured via immunohistochemistry staining (AUCLac_area/Glc_area: control, 0.08 ± 0.02 vs ICH-3d, 0.39 ± 0.05 vs ICH-7d, 0.18 ± 0.02, P < 0.01; H-score: control, 126.4 ± 5.03 vs ICH-3d, 168.4 ± 5.71 vs ICH-7d,133.6 ± 7.70, P < 0.05). A higher lactate signal also appeared near the ICH region than in normal brain tissue. In conclusion, 2H-MRS/MRSI shows potential as a useful method for in vivo metabolic imaging and noninvasive assessment of ICH.

Abstract B019: Sensitivity and specificity of detecting premalignant pancreatic lesions by hyperpolarized magnetic resonance

Abstract Introduction: The high mortality rate of pancreatic cancer (PC) results from a lack of methods for early detection. The progression of PC occurs primarily via two precursor pathways, either through microscopic pancreatic intraepithelial neoplasias (PanINs) or macroscopic cystic lesions, of which intraductal papillary mucinous neoplasms (IPMNs) are the most common. The progression from either PanIns or IPMN to PC, provides an opportunity for early detection of this lethal disease. PC cells have extensively reprogrammed metabolism and we have successfully employed hyperpolarized 1-13C pyruvate metabolic imaging (HP MR) to measure non-invasively the metabolic plasticity as the disease initiates and evolves. Concurrently, the specificity of HP MR of detecting premalignant lesions will be determined by imaging pancreatitis induced mice at different timepoints and compare them to the premalignant models. Methods: HP 1-13C Pyruvate MRS was employed to study the metabolic processes in tamoxifen inducible GEM models (P48CreERT2;LSL-KrasG12D (iKC)) with pre-invasive PanIN precursor lesions, invasive PC model (P48CreERT2;LSL-KrasG12D;LSL-p53R172H (iKPC)) and control animals (P48CreERT2 (iC)). These mice were imaged at different time points, before tamoxifen induction, 10-, 20-, and 30-weeks post induction. HP MR was also employed on IPMN mouse model (p48Cre;LSL- KrasG12D;Rosa26R-LSL-rtTA-TetO-GnasR201C) that develop premalignant cystic lesions, that progresses to PC on doxycycline diet (Dox+) for 15 weeks and control mice on normal diet (Dox-). These mice were imaged after 15 weeks of (Dox±) treatment. Simultaneously, wildtype, iC and iKC mice were treated with caerulein for three weeks for the development of pancreatitis and imaged 24 hours after treatment. Results: In the PanIN model, the lactate-to-pyruvate (lac/pyr) ratio increased in the PC models compared to the control model. For the aggressive iKPC mouse model, at the 20-week post induction imaging there was a significant increase of the lac/pyr ratio (0.28±0.04) compared to the 10-week time point (0.22±0.03). At the 20-week time point, the iKPC ratio was higher than the iKC and control ratios, (0.28±0.04 compared to 0.23±0.03 and 0.22±0.02 respectively) indicating the invasive nature of the cancer. Even in the iKC model there is a slight increase of the lac/pyr ratio at 20-weeks (0.23±0.03) compared to control (0.22±0.02). Mice treated with caerulein developed pancreatitis as demonstrated by tissue histology. Surprisingly, the lac/pyr ratio remained constant in both iC and iKC mice that developed pancreatitis, around 0.15±0.03 for both groups. In the IPMN model, IPMN mice feed with doxycycline showed increase pancreatic lesions and an increased lac/pyr ratio (0.43±0.05) compared to mice on normal diet (0.24±0.05). Conclusion: HP MR can detect metabolic shift to lactate in two different models of PC premalignancy representing two different pathways of PC progression. This finding can be potentially translated to the clinic for detection of premalignant pancreatic lesions in high-risk populations. Citation Format: José S Enriquez, Rian M Howell, Olivereen Le Roux, Shivanand Pudakalakatti, Prasanta Dutta, Florencia McAllister, Pratip K Bhattacharya. Sensitivity and specificity of detecting premalignant pancreatic lesions by hyperpolarized magnetic resonance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B019.

PET/CT for the Opportunistic Screening of Osteoporosis and Fractures in Cancer Patients.

In this review, we outline the different etiologies of osteoporosis in the oncologic setting and describe the basis for using PET/CT as screening tool for osteoporosis with a focus on the radiotracers [18F]FDG and [18F]NaF. Osteoporosis is a condition commonly affecting cancer patients due to their age, cancer-specific treatment agents, and effects of cancer. In terms of the unifying mechanism, decreased ratio of osteoblast-bone formation to osteoclast-bone resorption is responsible for causing osteoporosis. PET/CT, a crucial metabolic imaging modality in the oncologic imaging, could be a useful tool for the opportunistic screening of osteoporosis. There are two approaches with which osteoporosis could be identified with PET/CT-using either the (1) CT- based or (2) PET- based approaches. While the CT-based approach has been used with [18F]FDG PET/CT, both CT- and PET-based approaches can be employed with [18F]NaF-PET/CT as [18F]NaF is a radiotracer specific for osteoblast activity.

Potential application of [18F]AlF-PSMA-11 PET/CT in radioiodine refractory thyroid carcinoma

BackgroundPatients diagnosed with radioiodine refractory (RAI-R) thyroid carcinoma (TC) have a significantly worse prognosis than patients with radiosensitive TC. These refractory malignancies are often dedifferentiated, hindering the effectiveness of iodine-based imaging. Additionally, the role of metabolic imaging using [18F]FDG PET/CT is also limited in these cases, making adequate staging of RAI-R TC challenging. Recent case series have shown promising results regarding the role of the prostate-specific membrane antigen (PSMA) in TC. In this study we explored the value of [18F]AlF-PSMA-11 PET/CT in RAI-R TC.MethodsIn this phase II study, lesions detected on [18F]AlF-PSMA-11 PET were compared to findings from [18F]FDG PET/CT. Additionally, the serologic soluble prostate-specific membrane antigen (sPSMA) was measured using ELISA. PSMA-expression on tumor tissue in any available resection specimens was analysed with an immunostainer.ResultsEight patients were included, with a total of 39 identified lesions based on PET imaging. [18F]AlF-PSMA-11 PET identified 30 of 39 lesions, and [18F]FDG PET identified 33 lesions, leading to a detection rate of 76.9% and 84.6%, respectively. Interestingly, while nine lesions were solely visualized on [18F]FDG, six were uniquely seen on [18F]AlF-PSMA-11 PET. While sPSMA was immeasurable in all female patients, no correlation was found between sPSMA in male patients and disease-related factors. In five out of eight patients immunohistology showed PSMA expression on the primary tumor.ConclusionsAlthough not all lesions could be visualized, [18F]PSMA-11 PET identified multiple lesions imperceptible on [18F]FDG PET. These results display the potential additional diagnostic role of PSMA-targeted imaging in patients with RAI-R TC.Trial registration number No. EudraCT 2021-000456-19.

Non-invasive metabolic imaging of brown adipose tissue.

Non-invasive metabolic imaging of brown adipose tissue.

Enabling SENSE accelerated 2D CSI for hyperpolarized carbon-13 imaging

As hyperpolarized (HP) carbon-13 (13C) metabolic imaging is clinically translated, there is a need for easy-to-implement, fast, and robust imaging techniques. However, achieving high temporal resolution without decreasing spatial and/or spectral resolution, whilst maintaining the usability of the imaging sequence is challenging. Therefore, this study looked to accelerate HP 13C MRI by combining a well-established and robust sequence called two-dimensional Chemical Shift Imaging (2D CSI) with prospective under sampling and SENSitivity Encoding (SENSE) reconstruction. Due to the low natural abundance of 13C, the sensitivity maps cannot be pre-acquired for the reconstruction. As such, the implementation of sodium (23Na) sensitivity maps for SENSE reconstructed 13C CSI was demonstrated in a phantom and in vivo in the pig kidney. Results showed that SENSE reconstruction using 23Na sensitivity maps corrected aliased images with a four-fold acceleration. With high temporal resolution, the kidney spectra produced a detailed metabolic arrival and decay curve, useful for further metabolite kinetic modelling or denoising. Metabolic ratio maps were produced in three pigs demonstrating the technique’s ability for repeat metabolic measurements. In cases with unknown metabolite spectra or limited HP MRI specialist knowledge, this robust acceleration method ensures comprehensive capture of metabolic signals, mitigating the risk of missing spectral data.

First-Generation Radiolabeled Cyclic Peptides for Molecular Imaging of Platelet-Derived Growth Factor Receptor α.

Occult nodal spread and metastatic disease require longstanding imaging and biochemical assessments for thyroid cancer, a disease that has a propensity for diffuse, small-volume disease. We have developed a 64Cu-labeled platelet-derived growth factor receptor α (PDGFRA) antibody for immuno-PET of PDGFRA in metastatic papillary thyroid cancer (PTC). The present work describes the discovery of small cyclic PDGFRA-targeting peptides, their binding features, and radiolabeling with positron emitter gallium-68 (68Ga) for in vitro and in vivo characterization in thyroid cancer models. Phage-display technology with two separate libraries and seven different cell lines was used through three rounds of biopanning as well as flow cytometry and comparative analysis with recombinant protein to select specific peptide sequences. Phenotypic binding analysis was completed by using phosphorylation and cell migration assays. In vitro protein binding was analyzed with thermophoresis and flow cytometry using the fluorescent-labeled PDGFRA peptide. Peptide candidates were modified with the NOTA chelator for radiolabeling with 68Ga. In vitro cell uptake was studied in various thyroid cancer cell lines. In vivo studies of 68Ga-labeled peptides included metabolic stability and PET imaging. From the original library (1013 compounds), five different peptide groups were identified based on biopanning experiments with and without the α subunit of PDGFR, leading to ∼50 peptides. Subsequent phenotypic screening revealed two core peptide sequences (CP16 and CP18) that demonstrated significant changes in the level of PDGFRA phosphorylation and cell migration. Alanine scan sublibraries were created from these two lead peptide sequences, and peptides were radiolabeled using 68Ga-GaCl3 at pH 4.5, resulting in RCP > 95% within 34-40 min, including SPE purification. Cyclic peptide CP18.5 showed the strongest effects on cell migration, flow cytometry, and binding by visual interference color assay. 68Ga-labeled PDGFRA-targeting peptides showed elevated cell and tumor uptake in models of thyroid cancer, with 68Ga-NOTA-CP18.5 being the lead candidate. However, metabolic stability in vivo was compromised for 68Ga-NOTA-CP18.5 vs 68Ga-NOTA-CP18 but without impacting tumor uptake or clearance profiles. First-generation radiolabeled cyclic peptides have been developed as novel radiotracers, particularly 68Ga-NOTA-CP18.5, for the molecular imaging of PDGFRA in thyroid cancer.

Hyperpolarized [1-13C]pyruvate Magnetic Resonance Imaging Identifies Metabolic Phenotypes in Patients with Heart Failure

BackgroundHyperpolarized [1-13C]pyruvate magnetic resonance imaging (HP MRI) visualizes key steps in myocardial metabolism. The present study aimed to examine patients with heart (HF) using HP MRI. MethodsA cross-sectional study of patients with HF and healthy controls using HP MRI. Metabolic imaging was obtained using a cardiac-gated spectral-spatial excitation with spiral read-out acquisition. The metabolite signal was analyzed for lactate, bicarbonate, and the alanine signal. Metabolite signal was normalized to the total carbon signal (TC). At the one-year follow-up, echocardiography was performed in all patients and HP MRI in two patients. ResultsWe included six patients with ischemic heart disease (IHD), six with dilated cardiomyopathy and six healthy controls. In patients, left ventricular ejection fraction (LVEF) correlated with lactate/bicarbonate (r = -0.6, p = 0.03) and lactate/TC (r = -0.7, p = 0.01). In patients with LVEF < 30%, lactate/TC was increased (p = 0.01) and bicarbonate/TC reduced (p = 0.03). Circumferential strain correlated with metabolite ratios: lactate/bicarbonate, r = 0.87 (p = 0.0002); lactate/TC, r = 0.85 (p = 0.0005); bicarbonate/TC, r = -0.82 (p = 0.001). In patients with IHD, a strong correlation was found between baseline metabolite ratios and the change in LVEF at follow-up: lactate/bicarbonate (p = 0.001); lactate/TC (p = 0.011); and bicarbonate/TC (p = 0.012). ConclusionsThis study highlighted the ability of HP MRI to detect changes in metabolism in HF. HP MRI has potential for metabolic phenotyping of patients with HF and for predicting treatment response. Trial registrationEUDRACT, 2018-003533-15. Registered 4 December 2018, https://www.clinicaltrialsregister.eu/ctr-search/search?query=2018-003533-15.

Absolute Metabolite Quantification in Individuals with Glioma and Healthy Individuals Using Whole-Brain Three-dimensional MR Spectroscopic and Echo-planar Time-resolved Imaging.

MR spectroscopic imaging (MRSI) can be used to quantify an extended brain metabolic profile but is confounded by changes in tissue water levels due to disease. To develop a fast absolute quantification method for metabolite concentrations combining whole-brain MRSI with echo-planar time-resolved imaging (EPTI) relaxometry in individuals with glioma and healthy individuals. In this prospective study performed from August 2022 to August 2023, using internal water as concentration reference, the MRSI-EPTI quantification method was compared with the conventional method using population-average literature relaxation values. Healthy participants and participants with mutant IDH1 gliomas underwent imaging at 3 T with a 32-channel coil. Real-time navigated adiabatic spiral three-dimensional MRSI scans were acquired in approximately 8 minutes and reconstructed with a super-resolution pipeline to obtain brain metabolic images at 2.4-mm isotropic resolution. High-spatial-resolution multiparametric EPTI was performed in 3 minutes, with 1-mm isotropic resolution, to correct the relaxation and proton density of the water reference signal. Bland-Altman analysis and the Wilcoxon signed rank test were used to compare absolute quantifications from the proposed and conventional methods. Six healthy participants (four male; mean age, 37 years ± 11 [SD]) and nine participants with glioma (six male; mean age, 41 years ± 15; one with wild-type IDH1 and eight with mutant IDH1) were included. In healthy participants, there was good agreement (+4% bias) between metabolic concentrations derived using the two methods, with a CI of plus or minus 26%. In participants with glioma, there was large disagreement between the two methods (+39% bias) and a CI of plus or minus 55%. The proposed quantification method improved tumor contrast-to-noise ratio (median values) for total N-acetyl-aspartate (EPTI: 0.541 [95% CI: 0.217, 0.910]; conventional: 0.484 [95% CI: 0.199, 0.823]), total choline (EPTI: 1.053 [95% CI: 0.681, 1.713]; conventional: 0.940 [95% CI: 0.617, 1.295]), and total creatine (EPTI: 0.745 [95% CI: 0.628, 0.909]; conventional: 0.553 [95% CI: 0.444, 0.828]) (P = .03 for all). The whole-brain MRSI-EPTI method provided fast absolute quantification of metabolic concentrations with individual-specific corrections at 2.4-mm isotropic resolution, yielding concentrations closer to the true value in disease than the conventional literature-based corrections. © RSNA, 2024 Supplemental material is available for this article.

Synthetic Efforts toward the Synthesis of a Fluorinated Analog of 5-Aminolevulinic Acid: Practical Synthesis of Racemic and Enantiomerically Defined 3-Fluoro-5-aminolevulinic Acid.

In 2017, the FDA authorized 5-aminolevulinic acid (5-ALA) for intraoperative optical imaging of suspected high-grade gliomas. This was the first authorized optical imaging agent for brain tumor surgery to enhance the visualization of malignant tissue. Herein we report the synthesis of a racemic and enantiopure fluorinated analog of 5-ALA, i.e., 3-fluoro-5-aminolevulinic acid (3F-5-ALA). We anticipate that these studies will provide the foundation for the future construction of a fluorine-18-labeled 5-ALA PET tracer to be used for functional and metabolic imaging of gliomas.

Metabolic Imaging of Advanced Basal Cell Carcinoma Treated with Sonidegib: A Retrospective Case Series Study.

Background: Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) is a firmly established tool in oncology and is gaining importance in dermato-oncology. However, its use in advanced basal cell carcinoma (BCC) is limited, with only a few case reports and a single study focused on vismodegib. This study evaluates the role of 18F-FDG PET/CT in advanced BCC treated with sonidegib. Methods: We retrospectively assessed the clinical data of patients with advanced BCC who underwent 18F-FDG PET/CT between January 2022 and January 2024. Inclusion criteria included histologically confirmed BCC, FDG-avid lesions on baseline PET/CT, and a minimum follow-up of 6 months. Metabolic response was assessed using the PET Response Criteria in Solid Tumors (PERCIST). Results: Four patients with advanced BCC treated with sonidegib were included, presenting with a total of 10 hypermetabolic lesions at baseline PET/CT. The mean interval between baseline and follow-up scans was 8.7 ± 1.6 months. According to PERCIST, two patients achieved a complete metabolic response (CMR), while the other two had stable metabolic disease (SMD). Low baseline-standardized uptake values (i.e., SUVmax, SUVmean) and reduced total lesion glycolysis (TLG) were associated with CMR. No relapses were observed during follow-up. Conclusions: This study suggests that 18F-FDG PET/CT may help identify advanced BCC patients who are likely to benefit from sonidegib treatment. Further research is needed to fully explore the potential of PET/CT in this specific clinical context.

Cortical networks of parkinsonian gait: a metabolic and functional connectivity study.

Locomotion is an automated voluntary movement sustained by coordinated neural synchronization across a distributed brain network. The cerebral cortex is central for adapting the locomotion pattern to the environment and alterations of cortical network dynamics can lead to gait impairments. Gait problems are a common symptom with a still unclear pathophysiology and represent an unmet therapeutical need in Parkinson's disease. Little is known about the cortical network dynamics of locomotor control in these patients. We studied the cortical basis of parkinsonian gait by combining metabolic brain imaging with high-density EEG recordings and kinematic measurements performed at rest and during unperturbed overground walking. We found significant changes in functional connectivity between frontal, sensorimotor, and visuomotor cortical areas during walking as compared to resting. Specifically, hypokinetic gait was associated with poor information flow from the supplementary motor area (SMA) to precuneus and from calcarine to lingual gyrus, as well as high information flow from calcarine to cuneus. Our findings support a role for visuomotor integration processes in PD-related hypokinetic gait and suggest that reinforcing visual information may act as a compensatory strategy to allow SMA-mediated feedforward locomotor control in PD.

Spatial-temporal dynamic evolution of lewy body dementia by metabolic PET imaging.

Lewy body dementia (LBD) is a neurodegenerative disease with high heterogeneity and complex pathogenesis. Our study aimed to use disease progression modeling to uncover spatial-temporal dynamic evolution of LBD in vivo, and to explore differential profiles of clinical features, glucose metabolism, and dopaminergic function among different evolution-related subtypes. A total of 123 participants (31 healthy controls and 92 LBD patients) who underwent 18F-FDG PET scans were retrospectively enrolled. 18F-FDG PET-based Subtype and Stage Inference (SuStaIn) model was established to illustrate spatial-temporal evolutionary patterns and categorize relevant subtypes. Then subtypes and stages were further related to clinical features, glucose metabolism, and dopaminergic function of LBD patients. This 18F-FDG PET imaging-based approach illustrated two distinct patterns of neurodegenerative evolution originating from the neocortex and basal ganglia in LBD and defined them as subtype 1 and subtype 2, respectively. There were obvious differences between subtypes. Compared with subtype 1, subtype 2 exhibited a greater proportion of male patients (P = 0.045) and positive symptoms such as visual hallucinations (P = 0.033) and fluctuating cognitions (P = 0.033). Cognitive impairment, metabolic abnormalities, dopaminergic dysfunction and progression were all more severe in subtype 2 (all P < 0.05). In addition, a strong association was observed between SuStaIn subtypes and two clinical phenotypes (Parkinson's disease dementia and dementia with Lewy bodies) (P = 0.005). Our findings based on 18F-FDG PET and data-driven model illustrated spatial-temporal dynamic evolution of LBD and categorized novel subtypes with different evolutionary patterns, clinical and imaging features in vivo. The evolution-related subtypes are associated with LBD clinical phenotypes, which supports the perspective of existence of distinct entities in LBD spectrum.

Production and Multi-Parameter Live Cell Fluorescence Lifetime Imaging Microscopy (FLIM) of Multicellular Spheroids.

Multicellular tumor spheroids are a popular 3D tissue microaggregatemodel for reproducing tumor microenvironment, testing and optimizing drug therapiesand using bio- and nanosensors in a 3D context. Their ease of production, predictable size, growth, and observed nutrient and metabolite gradients are important to recapitulate the 3D niche-likecell microenvironment. However, spheroid heterogeneity and variability of their production methods can influence overall cell metabolism, viability, and drug response. This makes it difficult to choose the most appropriatemethodology, considering the requirements in size, variability, needs of biofabrication, and use as in vitro 3D tissue models in stem and cancer cell biology. In particular, spheroid production can influence their compatibility with quantitative live microscopies, such as optical metabolic imaging, fluorescence lifetime imaging microscopy (FLIM), monitoring of spheroidhypoxia with nanosensors, or viability. Here, a number of conventional spheroid formation protocols are presented, highlighting their compatibility with the live widefield, confocal, and two-photon microscopies. The follow-up imaging to analysispipeline with multiplexed autofluorescence FLIM and, using various types of cancer and stem cell spheroids, is also presented.