The Potential of Metabolic Imaging

Neuroimaging genetics approaches to identify new biomarkers for the early diagnosis of autism spectrum disorder

Autism-spectrum disorders (ASDs) are developmental disabilities that manifest in early childhood and are characterized by qualitative abnormalities in social behaviors, communication skills, and restrictive or repetitive behaviors. To explore the neurobiological mechanisms in ASD, extensive research has been done to identify potential diagnostic biomarkers through a neuroimaging genetics approach. Neuroimaging genetics helps to identify ASD-risk genes that contribute to structural and functional variations in brain circuitry and validate biological changes by elucidating the mechanisms and pathways that confer genetic risk. Integrating artificial intelligence models with neuroimaging data lays the groundwork for accurate diagnosis and facilitates the identification of early diagnostic biomarkers for ASD. This review discusses the significance of neuroimaging genetics approaches to gaining a better understanding of the perturbed neurochemical system and molecular pathways in ASD and how these approaches can detect structural, functional, and metabolic changes and lead to the discovery of novel biomarkers for the early diagnosis of ASD.

Restoration of metabolic functional metrics from label-free, two-photon human tissue images using multiscale deep-learning-based denoising algorithms

Significance

Label-free, two-photon excited fluorescence (TPEF) imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, noise and other artifacts present in these images severely complicate the extraction of biologically useful information.

Aim

We aim to employ deep neural architectures in the synthesis of a multiscale denoising algorithm optimized for restoring metrics of metabolic activity from low-signal-to-noise ratio (SNR), TPEF images.

Approach

TPEF images of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavoproteins (FAD) from freshly excised human cervical tissues are used to assess the impact of various denoising models, preprocessing methods, and data on metrics of image quality and the recovery of six metrics of metabolic function from the images relative to ground truth images.

Results

Optimized recovery of the redox ratio and mitochondrial organization is achieved using a novel algorithm based on deep denoising in the wavelet transform domain. This algorithm also leads to significant improvements in peak-SNR (PSNR) and structural similarity index measure (SSIM) for all images. Interestingly, other models yield even higher PSNR and SSIM improvements, but they are not optimal for recovery of metabolic function metrics.

Conclusions

Denoising algorithms can recover diagnostically useful information from low SNR label-free TPEF images and will be useful for the clinical translation of such imaging.

Parallel detection of multi-contrast MRI and Deuterium Metabolic Imaging (DMI) for time-efficient characterization of neurological diseases

Deuterium Metabolic Imaging (DMI) is a novel method that can complement traditional anatomical magnetic resonance imaging (MRI) of the brain. DMI relies on the MR detection of metabolites that become labeled with deuterium (2H) after administration of a deuterated substrate and can provide images with highly specific metabolic information. However, clinical adoption of DMI is complicated by its relatively long scan time. Here, we demonstrate a strategy to interleave DMI data acquisition with MRI that results in a comprehensive neuro-imaging protocol without adding scan time. The interleaved MRI-DMI routine includes four essential clinical MRI scan types, namely T1-weighted MP-RAGE, FLAIR, T2-weighted Imaging (T2W) and susceptibility weighted imaging (SWI), interwoven with DMI data acquisition. Phantom and in vivo human brain data show that MR image quality, DMI sensitivity, as well as information content are preserved in the MRI-DMI acquisition method. The interleaved MRI-DMI technology provides full flexibility to upgrade traditional MRI protocols with DMI, adding unique metabolic information to existing types of anatomical image contrast, without extra scan time.

Restoration of metabolic functional metrics from label-free, two-photon cervical tissue images using multiscale deep-learning-based denoising algorithms

Label-free, two-photon imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, this modality suffers from low signal arising from limitations imposed by the maximum permissible dose of illumination and the need for rapid image acquisition to avoid motion artifacts. Recently, deep learning methods have been developed to facilitate the extraction of quantitative information from such images. Here, we employ deep neural architectures in the synthesis of a multiscale denoising algorithm optimized for restoring metrics of metabolic activity from low-SNR, two-photon images. Two-photon excited fluorescence (TPEF) images of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavoproteins (FAD) from freshly excised human cervical tissues are used. We assess the impact of the specific denoising model, loss function, data transformation, and training dataset on established metrics of image restoration when comparing denoised single frame images with corresponding six frame averages, considered as the ground truth. We further assess the restoration accuracy of six metrics of metabolic function from the denoised images relative to ground truth images. Using a novel algorithm based on deep denoising in the wavelet transform domain, we demonstrate optimal recovery of metabolic function metrics. Our results highlight the promise of denoising algorithms to recover diagnostically useful information from low SNR label-free two-photon images and their potential importance in the clinical translation of such imaging.

Bioorthogonal Chemical Imaging of Cell Metabolism Regulated by Aromatic Amino Acids

Essential aromatic amino acids (AAAs) are building blocks for synthesizing new biomasses in cells and sustaining normal biological functions. For example, an abundant supply of AAAs is important for cancer cells to maintain their rapid growth and division. With this, there is a rising demand for a highly specific, noninvasive imaging approach with minimal sample preparation to directly visualize how cells harness AAAs for their metabolism in situ. Here, we develop an optical imaging platform that combines deuterium oxide (D2O) probing with stimulated Raman scattering (DO-SRS) and integrates DO-SRS with two-photon excitation fluorescence (2PEF) into a single microscope to directly visualize the metabolic activities of HeLa cells under AAA regulation. Collectively, the DO-SRS platform provides high spatial resolution and specificity of newly synthesized proteins and lipids in single HeLa cell units. In addition, the 2PEF modality can detect autofluorescence signals of nicotinamide adenine dinucleotide (NADH) and Flavin in a label-free manner. The imaging system described here is compatible with both in vitro and in vivo models, which is flexible for various experiments. The general workflow of this protocol includes cell culture, culture media preparation, cell synchronization, cell fixation, and sample imaging with DO-SRS and 2PEF modalities.

Video-rate Raman-based metabolic imaging by Airy light-sheet illumination and photon-sparse detection

Despite its massive potential, Raman imaging represents just a modest fraction of all research and clinical microscopy to date. This is due to the ultralow Raman scattering cross-sections of most biomolecules that impose low-light or photon-sparse conditions. Bioimaging under such conditions is suboptimal, as it either results in ultralow frame rates or requires increased levels of irradiance. Here, we overcome this tradeoff by introducing Raman imaging that operates at both video rates and 1,000-fold lower irradiance than state-of-the-art methods. To accomplish this, we deployed a judicially designed Airy light-sheet microscope to efficiently image large specimen regions. Further, we implemented subphoton per pixel image acquisition and reconstruction to confront issues arising from photon sparsity at just millisecond integrations. We demonstrate the versatility of our approach by imaging a variety of samples, including the three-dimensional (3D) metabolic activity of single microbial cells and the underlying cell-to-cell variability. To image such small-scale targets, we again harnessed photon sparsity to increase magnification without a field-of-view penalty, thus, overcoming another key limitation in modern light-sheet microscopy.

Imaging the Rewired Metabolism in Lung Cancer in Relation to Immune Therapy

Metabolic reprogramming is recognized as one of the hallmarks of cancer. Alterations in the micro-environmental metabolic characteristics are recognized as important tools for cancer cells to interact with the resident and infiltrating T-cells within this tumor microenvironment. Cancer-induced metabolic changes in the micro-environment also affect treatment outcomes. In particular, immune therapy efficacy might be blunted because of somatic mutation-driven metabolic determinants of lung cancer such as acidity and oxygenation status. Based on these observations, new onco-immunological treatment strategies increasingly include drugs that interfere with metabolic pathways that consequently affect the composition of the lung cancer tumor microenvironment (TME). Positron emission tomography (PET) imaging has developed a wide array of tracers targeting metabolic pathways, originally intended to improve cancer detection and staging. Paralleling the developments in understanding metabolic reprogramming in cancer cells, as well as its effects on stromal, immune, and endothelial cells, a wave of studies with additional imaging tracers has been published. These tracers are yet underexploited in the perspective of immune therapy. In this review, we provide an overview of currently available PET tracers for clinical studies and discuss their potential roles in the development of effective immune therapeutic strategies, with a focus on lung cancer. We report on ongoing efforts that include PET/CT to understand the outcomes of interactions between cancer cells and T-cells in the lung cancer microenvironment, and we identify areas of research which are yet unchartered. Thereby, we aim to provide a starting point for molecular imaging driven studies to understand and exploit metabolic features of lung cancer to optimize immune therapy.

Visualizing Cancer Cell Metabolic Dynamics Regulated With Aromatic Amino Acids Using DO-SRS and 2PEF Microscopy

Oxidative imbalance plays an essential role in the progression of many diseases that include cancer and neurodegenerative diseases. Aromatic amino acids (AAA) such as phenylalanine and tryptophan have the capability of escalating oxidative stress because of their involvement in the production of Reactive Oxygen Species (ROS). Here, we use D2O (heavy water) probed stimulated Raman scattering microscopy (DO-SRS) and two Photon Excitation Fluorescence (2PEF) microscopy as a multimodal imaging approach to visualize metabolic changes in HeLa cells under excess AAA such as phenylalanine or trytophan in culture media. The cellular spatial distribution of de novo lipogenesis, new protein synthesis, NADH, Flavin, unsaturated lipids, and saturated lipids were all imaged and quantified in this experiment. Our studies reveal ∼10% increase in de novo lipogenesis and the ratio of NADH to flavin, and ∼50% increase of the ratio of unsaturated lipids to saturated lipid in cells treated with excess phenylalanine or trytophan. In contrast, these cells exhibited a decrease in the protein synthesis rate by ∼10% under these AAA treatments. The cellular metabolic activities of these biomolecules are indicators of elevated oxidative stress and mitochondrial dysfunction. Furthermore, 3D reconstruction images of lipid droplets were acquired and quantified to observe their spatial distribution around cells’ nuceli under different AAA culture media. We observed a higher number of lipid droplets in excess AAA conditions. Our study showcases that DO-SRS imaging can be used to quantitatively study how excess AAA regulates metabolic activities of cells with subcellular resolution in situ.

Prognostic and therapeutic evaluation of nasopharyngeal carcinoma by dynamic contrast-enhanced (DCE), diffusion-weighted (DW) magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS)

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck malignancy, and radiotherapy (with or without chemotherapy) is the primary treatment modality. Reliable tumour assessment during the treatment phase, which can portend the efficacy of radiotherapy and early identification of potential treatment failure in radioresistant disease, has been implicit for better cancer management. Technological advancement in the last decade has fostered the development of functional magnetic resonance imaging (fMRI) techniques into a promising tool for diagnostic and therapeutic assessments in head and neck cancer. Apart from conventional morphological assessment, early detection of the physiological environment by fMRI allows a more thorough investigation in monitoring tumour response. This article discusses the relevant fMRI utilities in NPC as an early prognostic and monitoring tool for treatment. Challenges and future developments of fMRI in radiation oncology are also discussed.

Metabolic contrast agents produced from transported solid 13C-glucose hyperpolarized via dynamic nuclear polarization

Magnetic Resonance Imaging combined with hyperpolarized ¹³C-labelled metabolic contrast agents produced via dissolution Dynamic Nuclear Polarization can, non-invasively and in real-time, report on tissue specific aberrant metabolism. However, hyperpolarization equipment is expensive, technically demanding and needs to be installed on-site for the end-user. In this work, we provide a robust methodology that allows remote production of the hyperpolarized ¹³C-labelled metabolic contrast agents. The methodology, built on photo-induced thermally labile radicals, allows solid sample extraction from the hyperpolarization equipment and several hours' lifetime of the ¹³C-labelled metabolic contrast agents at appropriate storage/transport conditions. Exemplified with [U-¹³C, d₇]-D-glucose, we remotely produce hyperpolarized ¹³C-labelled metabolic contrast agents and generate above 10,000-fold liquid-state Magnetic Resonance signal enhancement at 9.4 T, keeping on-site only a simple dissolution device.

Hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion is rate-limited by monocarboxylate transporter-1 in the plasma membrane

Hyperpolarized [1-¹³C]pyruvate magnetic resonance spectroscopic imaging (MRSI) is a noninvasive metabolic-imaging modality that probes carbon flux in tissues and infers the state of metabolic reprograming in tumors. Prevailing models attribute elevated hyperpolarized [1-¹³C]pyruvate-to-[1-¹³C]lactate conversion rates in aggressive tumors to enhanced glycolytic flux and lactate dehydrogenase A (LDHA) activity (Warburg effect). By contrast, we find by cross-sectional analysis using genetic and pharmacological tools in mechanistic studies applied to well-defined genetically engineered cell lines and tumors that initial hyperpolarized [1-¹³C]pyruvate-to-[1-¹³C]lactate conversion rates as well as global conversion were highly dependent on and critically rate-limited by the transmembrane influx of [1-¹³C]pyruvate mediated predominately by monocarboxylate transporter-1 (MCT1). Specifically, in a cell-encapsulated alginate bead model, induced short hairpin (shRNA) knockdown or overexpression of MCT1 quantitatively inhibited or enhanced, respectively, unidirectional pyruvate influxes and [1-¹³C]pyruvate-to-[1-¹³C]lactate conversion rates, independent of glycolysis or LDHA activity. Similarly, in tumor models in vivo, hyperpolarized [1-¹³C]pyruvate-to-[1-¹³C]lactate conversion was highly dependent on and critically rate-limited by the induced transmembrane influx of [1-¹³C]pyruvate mediated by MCT1. Thus, hyperpolarized [1-¹³C]pyruvate MRSI measures primarily MCT1-mediated [1-¹³C]pyruvate transmembrane influx in vivo, not glycolytic flux or LDHA activity, driving a reinterpretation of this maturing new technology during clinical translation. Indeed, Kaplan-Meier survival analysis for patients with pancreatic, renal, lung, and cervical cancers showed that high-level expression of MCT1 correlated with poor overall survival, and only in selected tumors, coincident with LDHA expression. Thus, hyperpolarized [1-¹³C]pyruvate MRSI provides a noninvasive functional assessment primarily of MCT1 as a clinical biomarker in relevant patient populations.

Metabolic Regulation of Tissue Stem Cells

Adult tissue stem cells mediate organ homeostasis and regeneration and thus are continually making decisions about whether to remain quiescent, proliferate, or differentiate into mature cell types. These decisions often integrate external cues, such as energy balance and the nutritional status of the organism. Metabolic substrates and byproducts that regulate epigenetic and signaling pathways are now appreciated to have instructive rather than bystander roles in regulating cell fate decisions. In this review, we highlight recent literature focused on how metabolites and dietary manipulations can impact cell fate decisions, with a focus on the regulation of adult tissue stem cells.

Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer

Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.

Positron emission tomography/magnetic resonance imaging (PET/MRI): An update and initial experience at HC-FMUSP

The new technology of PET/MRI is a prototype of hybrid imaging, allowing for the combination of molecular data from PET scanning and morphofunctional information derived from MRI scanning. Recent advances regarding the technical aspects of this device, especially after the development of MRI-compatible silicon photomultipliers of PET, permitted an increase in the diagnostic performance of PET/MRI translated into dose reduction and higher imaging quality. Among several clinical applications, PET/MRI gains ground initially in oncology, where MRI per se plays an essential role in the assessment of primary tumors (which is limited in the case of PET/CT), including prostate, rectal and gynecological tumors. On the other hand, the evaluation of the lungs remains an enigma although new MRI sequences are being designed to overcome this. More clinical indications of PET/MRI are seen in the fields of neurology, cardiology and inflammatory processes, and the use of PET/MRI also opens perspectives for pediatric populations as it involves very low radiation exposure. Our review aimed to highlight the current indications of PET/MRI and discuss the challenges and perspectives of PET/MRI at HC-FMUSP.

Concealed complete response in melanoma patients under therapy with immune checkpoint inhibitors: two case reports

BACKGROUND

The assessment of tumor size by RECIST using CT scans and MRIs is considered to be standard of care for staging cancer patients. Despite radiologic evidence of widespread disease, we document for the first time that patients were completely free of viable tumor.

CASE PRESENTATION

Two patients with metastatic melanoma were treated with immune checkpoint inhibitors (ipilimumab/ nivolumab) and progressive metastases were detected on CT-scans performed shortly before histologic examinations. In both patients histologic assessment revealed a complete response with necrotic and scarred lesions free of tumor. One of the patients had started immunotherapy 20 months before with an initial partial response.

CONCLUSIONS

This phenomenon of a concealed complete response can lead to overtreatment or unnecessary change in treatment. Thus, it is essential to raise awareness for it. Correct identification of responders to immune checkpoint inhibitor therapy is crucial to spare patients immune-mediated side effects and unnecessary as well as expensive treatment. Regression of metastases without decline in size, in these cases manifesting as complete responses, are probably more common than expected and identified to date. Until such responses can be readily identified by new imaging techniques, we recommend liberal biopsies for histologic assessment of progressive metastases in patients during and/or after immune checkpoint inhibitor therapy.

Imaging Cancer Metabolism

It is widely accepted that altered metabolism contributes to cancer growth and has been described as a hallmark of cancer. Our view and understanding of cancer metabolism has expanded at a rapid pace, however, there remains a need to study metabolic dependencies of human cancer in vivo. Recent studies have sought to utilize multi-modality imaging (MMI) techniques in order to build a more detailed and comprehensive understanding of cancer metabolism. MMI combines several in vivo techniques that can provide complementary information related to cancer metabolism. We describe several non-invasive imaging techniques that provide both anatomical and functional information related to tumor metabolism. These imaging modalities include: positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS) that uses hyperpolarized probes and optical imaging utilizing bioluminescence and quantification of light emitted. We describe how these imaging modalities can be combined with mass spectrometry and quantitative immunochemistry to obtain more complete picture of cancer metabolism. In vivo studies of tumor metabolism are emerging in the field and represent an important component to our understanding of how metabolism shapes and defines cancer initiation, progression and response to treatment. In this review we describe in vivo based studies of cancer metabolism that have taken advantage of MMI in both pre-clinical and clinical studies. MMI promises to advance our understanding of cancer metabolism in both basic research and clinical settings with the ultimate goal of improving detection, diagnosis and treatment of cancer patients.

Current status and future challenges for molecular imaging

Molecular imaging (MI), used in its wider sense of biology at the molecular level, is a field that lies at the intersection of molecular biology and traditional medical imaging. As advances in medicine have exponentially expanded over the last few decades, so has our need to better understand the fundamental behaviour of living organisms in a non-invasive and timely manner. This commentary draws from topics the authors addressed in their presentations at the 2017 Royal Society Meeting 'Challenges for chemistry in molecular imaging', as well as a discussion of where MI is today and where it is heading in the future.This article is part of the themed issue 'Challenges for chemistry in molecular imaging'.

The Role of PET/MR Imaging in Precision Medicine

Fluorodeoxyglucose PET and PET/computed tomography have gained acceptance in the evaluation of disease. Nontargeted tracers have been used in the diagnosis of certain malignancies but may not be sensitive or specific enough to become standard of care. Newer targeted PET tracers have been developed that target disease-specific biomarkers, and allow accurate and sensitive detection of disease. Combined with the capabilities of MR imaging to evaluate soft tissue, precision imaging with PET/MR imaging can change the diagnosis. This article discusses specific areas in which precision imaging with nontargeted and targeted diagnostic agents can change the diagnosis and treatment.

Characterization of the Tumor Microenvironment and Tumor-Stroma Interaction by Non-invasive Preclinical Imaging

Tumors are often characterized by hypoxia, vascular abnormalities, low extracellular pH, increased interstitial fluid pressure, altered choline-phospholipid metabolism, and aerobic glycolysis (Warburg effect). The impact of these tumor characteristics has been investigated extensively in the context of tumor development, progression, and treatment response, resulting in a number of non-invasive imaging biomarkers. More recent evidence suggests that cancer cells undergo metabolic reprograming, beyond aerobic glycolysis, in the course of tumor development and progression. The resulting altered metabolic content in tumors has the ability to affect cell signaling and block cellular differentiation. Additional emerging evidence reveals that the interaction between tumor and stroma cells can alter tumor metabolism (leading to metabolic reprograming) as well as tumor growth and vascular features. This review will summarize previous and current preclinical, non-invasive, multimodal imaging efforts to characterize the tumor microenvironment, including its stromal components and understand tumor-stroma interaction in cancer development, progression, and treatment response.