Non-invasive quantification of lactate by proton MR spectroscopy and its clinical applications

Assessment of sepsis-associated encephalopathy by quantitative magnetic resonance spectroscopy in a rat model of cecal ligation and puncture

Proton magnetic resonance spectroscopy (1H-MRS) is the only non-invasive technique to quantify neurometabolic compounds in the living brain. We used 1H-MRS to evaluate the brain metabolites in a rat model of Sepsis-associated encephalopathy (SAE) established by cecal ligation and puncture (CLP). 36 male Sprague-Dawley rats were randomly divided into sham and CLP groups. Each group was further divided into three subgroups: subgroup O, subgroup M, and subgroup N. Neurological function assessments were performed on the animals in the subgroup O and subgroup N at 24 h, 48 h, and 72 h. The animals in the subgroup M were examined by magnetic resonance imaging (MRI) at 12 h after CLP. Compared with the sham group, the ratio of N-acetylaspartate (NAA) to creatine (Cr) in the hippocampus was significantly lower in the CLP group. The respective ratios of lactate (Lac), myo-inositol (mIns), glutamate and glutamine (Glx), lipid (Lip), and choline (Cho) to Cr in the CLP group were clearly higher than those in the sham group. Cytochrome c, intimately related to oxidative stress, was elevated in the CLP group. Neurofilament light (NfL) chain and glial fibrillary acidic protein (GFAP) scores in the CLP group were significantly higher than those in the sham group, while zonula occludens-1 (ZO-1) was downregulated. Compared with the sham group, the CLP group displayed higher values of oxygen extraction fraction (OEF), central venous-arterial partial pressure of carbon dioxide (P (cv-a) CO2), and central venous lactate (VLac). In contrast, jugular venous oxygen saturation (SjvO2) declined. In the present study, 1H-MRS could be used to quantitatively assess brain injury in terms of microcirculation disorder, oxidative stress, blood-brain barrier disruption, and glial cell activation through changes in metabolites within brain tissue.

Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data

Background

To investigate the contribution of machine learning decision tree models applied to perfusion and spectroscopy MRI for multiclass classification of lymphomas, glioblastomas, and metastases, and then to bring out the underlying key pathophysiological processes involved in the hierarchization of the decision-making algorithms of the models.

Methods

From 2013 to 2020, 180 consecutive patients with histopathologically proved lymphomas (n = 77), glioblastomas (n = 45), and metastases (n = 58) were included in machine learning analysis after undergoing MRI. The perfusion parameters (rCBVmax, PSRmax) and spectroscopic concentration ratios (lac/Cr, Cho/NAA, Cho/Cr, and lip/Cr) were applied to construct Classification and Regression Tree (CART) models for multiclass classification of these brain tumors. A 5-fold random cross validation was performed on the dataset.

Results

The decision tree model thus constructed successfully classified all 3 tumor types with a performance (AUC) of 0.98 for PCNSLs, 0.98 for GBM and 1.00 for METs. The model accuracy was 0.96 with a RSquare of 0.887. Five rules of classifier combinations were extracted with a predicted probability from 0.907 to 0.989 for that end nodes of the decision tree for tumor multiclass classification. In hierarchical order of importance, the root node (Cho/NAA) in the decision tree algorithm was primarily based on the proliferative, infiltrative, and neuronal destructive characteristics of the tumor, the internal node (PSRmax), on tumor tissue capillary permeability characteristics, and the end node (Lac/Cr or Cho/Cr), on tumor energy glycolytic (Warburg effect), or on membrane lipid tumor metabolism.

Conclusion

Our study shows potential implementation of machine learning decision tree model algorithms based on a hierarchical, convenient, and personalized use of perfusion and spectroscopy MRI data for multiclass classification of these brain tumors.

Computed Tomography, Magnetic Resonance Imaging, and Pathological Features of Gliosarcoma

Objective

To investigate the clinical, imaging, and pathological features of gliosarcoma.

Methods

The clinical data of 14 patients with gliosarcoma confirmed by surgery and pathology at our hospital between 2010 and 2021 were analyzed retrospectively, and the relevant literature was reviewed.

Results

In all 14 cases, the gliosarcoma was located in the supratentorial brain parenchyma and involved a single lesion. There were more male patients (64.3%) than female patients (35.7%), and 57.1% of all the patients were 40-60 years of age. The prognosis of all 14 patients was poor, and the average survival time was approximately seven months. The computed tomography findings revealed mostly mixed density lesions, and some cases were complicated with bleeding. The magnetic resonance imaging revealed irregularly shaped mass lesions of different sizes, with uneven or circular enhancement. Cystic degeneration and necrosis could be seen in all the masses, some of which showed signs of bleeding and were surrounded by different degrees of edema and space-occupying effects. The pathological examination revealed that the tumors had bidirectional differentiation of the glial and sarcoma components, while the immunohistochemistry examination revealed glial fibrillary acidic protein-positive and reticular fiber-positive staining in the sarcoma.

Conclusion

The clinical manifestations of gliosarcoma are nonspecific, but imaging reveals that the condition has certain characteristics, typically consisting of a huge supratentorial mass, with an irregular heterogeneous periphery or obvious mass-like augmentation after enhancement. The final diagnosis depends on the results of a pathological examination.

Lactate metabolism in human health and disease

The current understanding of lactate extends from its origins as a byproduct of glycolysis to its role in tumor metabolism, as identified by studies on the Warburg effect. The lactate shuttle hypothesis suggests that lactate plays an important role as a bridging signaling molecule that coordinates signaling among different cells, organs and tissues. Lactylation is a posttranslational modification initially reported by Professor Yingming Zhao’s research group in 2019. Subsequent studies confirmed that lactylation is a vital component of lactate function and is involved in tumor proliferation, neural excitation, inflammation and other biological processes. An indispensable substance for various physiological cellular functions, lactate plays a regulatory role in different aspects of energy metabolism and signal transduction. Therefore, a comprehensive review and summary of lactate is presented to clarify the role of lactate in disease and to provide a reference and direction for future research. This review offers a systematic overview of lactate homeostasis and its roles in physiological and pathological processes, as well as a comprehensive overview of the effects of lactylation in various diseases, particularly inflammation and cancer.

The oncogenic and clinical implications of lactate induced immunosuppression in the tumour microenvironment

The tumour microenvironment is of critical importance in cancer development and progression and includes the surrounding stromal and immune cells, extracellular matrix, and the milieu of metabolites and signalling molecules in the intercellular space. To support sustained mitotic activity cancer cells must reconfigure their metabolic phenotype. Lactate is the major by-product of such metabolic alterations and consequently, accumulates in the tumour. Lactate actively contributes to immune evasion, a hallmark of cancer, by directly inhibiting immune cell cytotoxicity and proliferation. Furthermore, lactate can recruit and induce immunosuppressive cell types, such as regulatory T cells, tumour-associated macrophages, and myeloid-derived suppressor cells which further suppress anti-tumour immune responses. Given its roles in oncogenesis, measuring intratumoural and systemic lactate levels has shown promise as a both predictive and prognostic biomarker in several cancer types. The efficacies of many anti-cancer therapies are limited by an immunosuppressive TME in which lactate is a major contributor, therefore, targeting lactate metabolism is a priority. Developing inhibitors of key proteins in lactate metabolism such as GLUT1, hexokinase, LDH, MCT and HIF have shown promise in preclinical studies, however there is a corresponding lack of success in human trials so far. This may be explained by a weakness of preclinical models that fail to reproduce the complexities of metabolic interactions in natura. The future of these therapies may be as an adjunct to more conventional treatments.

Lactate in the Regulation of Tumor Microenvironment and Therapeutic Approaches

Tumor cells must generate sufficient ATP and biosynthetic precursors in order to maintain cell proliferation requirements. Otto Warburg showed that tumor cells uptake high amounts of glucose producing large volumes of lactate even in the presence of oxygen, this process is known as “Warburg effect or aerobic glycolysis.” As a consequence of such amounts of lactate there is an acidification of the extracellular pH in tumor microenvironment, ranging between 6.0 and 6.5. This acidosis favors processes such as metastasis, angiogenesis and more importantly, immunosuppression, which has been associated to a worse clinical prognosis. Thus, lactate should be thought as an important oncometabolite in the metabolic reprogramming of cancer. In this review, we summarized the role of lactate in regulating metabolic microenvironment of cancer and discuss its relevance in the up-regulation of the enzymes lactate dehydrogenase (LDH) and monocarboxilate transporters (MCTs) in tumors. The goal of this review is to expose that lactate is not only a secondary product of cellular metabolic waste of tumor cells, but also a key molecule involved in carcinogenesis as well as in tumor immune evasion. Finally, the possible targeting of lactate production in cancer treatment is discussed.

Reduction of Acquisition time using Partition of the sIgnal Decay in Spectroscopic Imaging technique (RAPID-SI)

To overcome long acquisition times of Chemical Shift Imaging (CSI), a new Magnetic Resonance Spectroscopic Imaging (MRSI) technique called Reduction of Acquisition time by Partition of the sIgnal Decay in Spectroscopic Imaging (RAPID-SI) using blipped phase encoding gradients inserted during signal acquisition was developed. To validate the results using RAPID-SI and to demonstrate its usefulness in terms of acquisition time and data quantification; simulations, phantom and in vivo studies were conducted, and the results were compared to standard CSI. The method was based upon the partition of a magnetic resonance spectroscopy (MRS) signal into sequential sub-signals encoded using blipped phase encoding gradients inserted during signal acquisition at a constant time interval. The RAPID-SI technique was implemented on a clinical 3 T Siemens scanner to demonstrate its clinical utility. Acceleration of data collection was performed by inserting R (R = acceleration factor) blipped gradients along a given spatial direction during data acquisition. Compared to CSI, RAPID-SI reduced acquisition time by the acceleration factor R. For example, a 2D 16x16 data set acquired in about 17 min with CSI, was reduced to approximately 2 min with the RAPID-SI (R = 8). While the SNR of the acquired RAPID-SI signal was lower compared to CSI by approximately the factor √R, it can be improved after data pre-processing and reconstruction. Compared to CSI, RAPID-SI reduces acquisition time, while preserving metabolites information. Furthermore, the method is flexible and could be combined with other acceleration methods such as Parallel Imaging.

Added Value of Spectroscopy to Perfusion MRI in the Differential Diagnostic Performance of Common Malignant Brain Tumors

BACKGROUND AND PURPOSE

Perfusion and spectroscopic MR imaging provide noninvasive physiologic and metabolic characterization of tissues, which can help in differentiating brain tumors. We investigated the diagnostic role of perfusion and spectroscopic MR imaging using individual and combined classifiers of these modalities and assessed the added performance value that spectroscopy can provide to perfusion using optimal combined classifiers that have the highest differential diagnostic performance to discriminate lymphomas, glioblastomas, and metastases.

MATERIALS AND METHODS

From January 2013 to January 2016, fifty-five consecutive patients with histopathologically proved lymphomas, glioblastomas, and metastases were included after undergoing MR imaging. The perfusion parameters (maximum relative CBV, maximum percentage of signal intensity recovery) and spectroscopic concentration ratios (lactate/Cr, Cho/NAA, Cho/Cr, and lipids/Cr) were analyzed individually and in optimal combinations. Differences among tumor groups, differential diagnostic performance, and differences in discriminatory performance of models with quantification of the added performance value of spectroscopy to perfusion were tested using 1-way ANOVA models, receiver operating characteristic analysis, and comparisons between receiver operating characteristic analysis curves using a bivariate χ², respectively.

RESULTS

The highest differential diagnostic performance was obtained with the following combined classifiers: maximum percentage of signal intensity recovery-Cho/NAA to discriminate lymphomas from glioblastomas and metastases, significantly increasing the sensitivity from 82.1% to 95.7%; relative CBV-Cho/NAA to discriminate glioblastomas from lymphomas and metastases, significantly increasing the specificity from 92.7% to 100%; and maximum percentage of signal intensity recovery-lactate/Cr and maximum percentage of signal intensity recovery-Cho/Cr to discriminate metastases from lymphomas and glioblastomas, significantly increasing the specificity from 83.3% to 97.0% and 100%, respectively.

CONCLUSIONS

Spectroscopy yielded an added performance value to perfusion using optimal combined classifiers of these modalities, significantly increasing the differential diagnostic performances for these common brain tumors.

Mitochondrial dysfunction in myotonic dystrophy type 1

The pathophysiological mechanism linking the nucleotide expansion in the DMPK gene to the clinical manifestations of myotonic dystrophy type 1 (DM1) is still unclear. In vitro studies demonstrate DMPK involvement in the redox homeostasis of cells and the mitochondrial dysfunction in DM1, but in vivo investigations of oxidative metabolism in skeletal muscle have provided ambiguous results and have never been performed in the brain. Twenty-five DM1 patients (14M, 39 ± 11years) underwent brain proton MR spectroscopy (¹H-MRS), and sixteen cases (9M, 40 ± 13 years old) also calf muscle phosphorus MRS (³¹P-MRS). Findings were compared to those of sex- and age-matched controls. Eight DM1 patients showed pathological increase of brain lactate and, compared to those without, had larger lateral ventricles (p < 0.01), smaller gray matter volumes (p < 0.05) and higher white matter lesion load (p < 0.05). A reduction of phosphocreatine/inorganic phosphate (p < 0.001) at rest and, at first minute of exercise, a lower [phosphocreatine] (p = 0.003) and greater [ADP] (p = 0.004) were found in DM1 patients compared to controls. The post-exercise indices of muscle oxidative metabolism were all impaired in DM1, including the increase of time constant of phosphocreatine resynthesis (TC PCr, p = 0.038) and the reduction of the maximum rate of mitochondrial ATP synthesis (p = 0.033). TC PCr values correlated with the myotonic area score (ρ = 0.74, p = 0.01) indicating higher impairment of muscle oxidative metabolism in clinically more affected patients. Our findings provide clear in vivo evidence of multisystem impairment of oxidative metabolism in DM1 patients, providing a rationale for targeted treatment enhancing energy metabolism.

Validating a robust double-quantum-filtered (1) H MRS lactate measurement method in high-grade brain tumours

(1) H MRS measurements of lactate are often confounded by overlapping lipid signals. Double-quantum (DQ) filtering eliminates lipid signals and permits single-shot measurements, which avoid subtraction artefacts in moving tissues. This study evaluated a single-voxel-localized DQ filtering method qualitatively and quantitatively for measuring lactate concentrations in the presence of lipid, using high-grade brain tumours in which the results could be compared with standard acquisition as a reference. Paired standard acquisition and DQ-filtered (1) H MR spectra were acquired at 3T from patients receiving treatment for glioblastoma, using fLASER (localization by adiabatic selective refocusing using frequency offset corrected inversion pulses) single-voxel localization. Data were acquired from 2 × 2 × 2 cm(3) voxels, with a repetition time of 1 s and 128 averages (standard acquisition) or 256 averages (DQ-filtered acquisition), requiring 2.15 and 4.3 min respectively. Of 37 evaluated data pairs, 20 cases (54%) had measureable lactate (fitted Cramér-Rao lower bounds ≤ 20%) in either the DQ-filtered or the standard acquisition spectra. The measured DQ-filtered lactate signal was consistently downfield of lipid (1.33 ± 0.03 ppm vs 1.22 ± 0.08 ppm; p = 0.002), showing that it was not caused by lipid breakthrough, and that it matched the lactate signal seen in standard measurements (1.36 ± 0.02 ppm). In the absence of lipid, similar lactate concentrations were measured by the two methods (mean ratio DQ filtered/standard acquisition = 1.10 ± 0.21). In 7/20 cases with measurable lactate, signal was not measureable in the standard acquisition owing to lipid overlap but was quantified in the DQ-filtered acquisition. Conversely, lactate was undetected in seven DQ-filtered acquisitions but visible using the standard acquisition. In conclusion, the DQ filtering method has proven robust in eliminating lipid and permits uncontaminated measurement of lactate. This is important validation prior to use in tissues outside the brain, which contain large amounts of lipid and which are often susceptible to motion.

Spectral data de-noising using semi-classical signal analysis: application to localized MRS

In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrödinger operator. In this manner, the MRS spectral peaks represented as a sum of these 'shaped like' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

Single-shot single-voxel lactate measurements using FOCI-LASER and a multiple-quantum filter

Measurement of tissue lactate using (1) H MRS is often confounded by overlap with intense lipid signals at 1.3 ppm. Single-voxel localization using PRESS is also compromised by the large chemical shift displacement between voxels for the 4.1 ppm (-CH) resonance and the 1.3 ppm -CH3 resonance, leading to subvoxels with signals of opposite phase and hence partial signal cancellation. To reduce the chemical shift displacement to negligible proportions, a modified semi-LASER sequence was written ("FOCI-LASER", abbreviated as fLASER) using FOCI pulses to permit high RF bandwidth even with the limited RF amplitude characteristic of clinical MRI scanners. A further modification, MQF-fLASER, includes a selective multiple-quantum filter to detect lactate and reject lipid signals. The sequences were implemented on a Philips 3 T Achieva TX system. In a solution of brain metabolites fLASER lactate signals were 2.7 times those of PRESS. MQF-fLASER lactate was 47% of fLASER (the theoretical maximum is 50%) but still larger than PRESS lactate. In oil, the main 1.3 ppm lipid peak was suppressed to less than 1%. Enhanced suppression was possible using increased gradient durations. The minimum detectable lactate concentration was approximately 0.5 mM. Coherence selection gradients needed to be at the magic angle to avoid large water signals derived from intermolecular multiple-quantum coherences. In pilot patient measurements, lactate peaks were often observed in brain tumours, but not in cervix tumours; lipids were effectively suppressed. In summary, compared with PRESS, the fLASER sequence yields greatly superior sensitivity for direct detection of lactate (and equivalent sensitivity for other metabolites), while the single-voxel single-shot MQF-fLASER sequence surpasses PRESS for lactate detection while eliminating substantial signals from lipids. This sequence will increase the potential for in vivo lactate measurement as a biomarker in targeted anti-cancer treatments as well as in measurements of tissue hypoxia.

MEK1/2 inhibition decreases lactate in BRAF-driven human cancer cells

The RAS/BRAF/MEK/ERK signaling pathway is a central driver in cancer with many BRAF and MEK inhibitors being evaluated in clinical trials. Identifying noninvasive biomarkers of early pharmacodynamic responses is important for development of these targeted drugs. As increased aerobic glycolysis is often observed in cancer, we hypothesized that MEK1/2 (MAP2K1/MAP2K2) inhibitors may reduce lactate levels as detected by magnetic resonance spectroscopy (MRS), as a metabolic biomarker for the pharmacodynamic response. MRS was used to monitor intracellular and extracellular levels of lactate in human cancer cells in vitro and in melanoma tumors ex vivo. In addition, we used (1)H MRS and a fluorescent glucose analog to evaluate the effect of MEK inhibition on glucose uptake. MEK1/2 signaling inhibition reduced extracellular lactate levels in BRAF-dependent cells but not BRAF-independent cells. The reduction in extracellular lactate in BRAF-driven melanoma cells was time-dependent and associated with reduced expression of hexokinase-II driven by c-Myc depletion. Taken together, these results reveal how MEK1/2 inhibition affects cancer cell metabolism in the context of BRAF oncogene addiction. Furthermore, they offer a preclinical proof-of-concept for the use of MRS to measure lactate as a noninvasive metabolic biomarker for pharmacodynamic response to MEK1/2 inhibition in BRAF-driven cancers.

Preclinical molecular imaging using PET and MRI

Molecular imaging fundamentally changes the way we look at cancer. Imaging paradigms are now shifting away from classical morphological measures towards the assessment of functional, metabolic, cellular, and molecular information in vivo. Interdisciplinary driven developments of imaging methodology and probe molecules utilizing animal models of human cancers have enhanced our ability to non-invasively characterize neoplastic tissue and follow anti-cancer treatments. Preclinical molecular imaging offers a whole palette of excellent methodology to choose from. We will focus on positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques, since they provide excellent and complementary molecular imaging capabilities and bear high potential for clinical translation. Prerequisites and consequences of using animal models as surrogates of human cancers in preclinical molecular imaging are outlined. We present physical principles, values and limitations of PET and MRI as molecular imaging modalities and comment on their high potential to non-invasively assess information on hypoxia, angiogenesis, apoptosis, gene expression, metabolism, and cell trafficking in preclinical cancer research.

Glycolytic phenotype and AMP kinase modify the pathologic response of tumor xenografts to VEGF neutralization

VEGF antagonists are now widely used cancer therapeutics, but predictive biomarkers of response or toxicity remain unavailable. In this study, we analyzed the effects of anti-VEGF therapy on tumor metabolism and therapeutic response by using an integrated set of imaging techniques, including bioluminescence metabolic imaging, 18-fluorodeoxyglucose positron emission tomography, and MRI imaging and spectroscopy. Our results revealed that anti-VEGF therapy caused a dramatic depletion of glucose and an exhaustion of ATP levels in tumors, although glucose uptake was maintained. These metabolic changes selectively accompanied the presence of large necrotic areas and partial tumor regression in highly glycolytic tumors. In addition, we found that the central metabolic protein kinase AMP-activated protein kinase (AMPK)-a cellular sensor of ATP levels that supports cell viability in response to energy stress-was activated by anti-VEGF therapy in experimental tumors. AMPK-α2 attenuation increased glucose consumption, tumor cell sensitivity to glucose starvation, and tumor necrosis following anti-VEGF therapy. Taken together, our findings reveal functional links between the Warburg effect and the AMPK pathway with therapeutic responses to VEGF neutralization in tumor xenograft models.

Molecular imaging as a tool for translating breast cancer science

The ability to measure biochemical and molecular processes underlies progress in breast cancer biology and treatment. These assays have traditionally been performed by analysis of cell culture or tissue samples. More recently, functional and molecular imaging has allowed the in vivo assay of biochemistry and molecular biology, which is highly complementary to tissue-based assays. This review briefly describes different imaging modalities used in molecular imaging and then reviews applications of molecular imaging to breast cancer, with a focus on translational work. It includes sections describing work in functional and physiological tumor imaging, imaging gene product expression, imaging the tumor microenvironment, reporter gene imaging, and cell labeling. Work in both animal models and human is discussed with an eye towards studies that have relevance to breast cancer treatment in patients.

Metabolite Profile in Pyramidal Tracts after Ischemic Brain Stroke Assessed by 1H MRS. A Multicenter Study

The magnitude of the motor deficit in patients with stroke depends not only on the size and location of the destroyed brain tissue, but also on axonal injury in the descending motor pathways which appears after stroke. After cerebral ischemia, there are no visible abnormalities in conventional MRI in the intact pyramidal tracts despite the process of neuronal destruction by Wallerian degeneration. Conventional MRI is not a sensitive test for Wallerian degeneration in the acute or subacute time period as it shows no changes within the first four weeks. Magnetic resonance spectroscopy (MRS) has been used for better quantification of the extent or severity of fibre damage by evaluating metabolite alterations in normal-appearing corticospinal and corticopontal tracts. This study assessed the role of 1H MRS in the detection of changes in cerebral metabolite levels in pyramidal tracts after cortical/ subcortical infarction and to compare metabolite alterations to clinical outcome (assessed by Barthel index, Scandinavian Stroke Scale). The study included 31 patients who had suffered an ischemic cortical/subcortical stroke involving the motor cortex or the descending fibers. Ratios of NAA/Cr, Cho/Cr, lip/Cr and Lac/Cr from internal capsules and cerebral peduncles were measured and compared with clinical status assessed by Barthel index and Scandinavian Stroke Scale (SSS). The ratio of NAA/Cr was significantly decreased (p<0.001) in the normal-appearing ipsilateral internal capsule in comparison with the control group. Cho/Cr and lac/Cr ratios were increased compared to the control group (p=0.019). Decrease of NAA/Cr ratio correlated with clinical status assessed by Barthel index and there was a correlation between clinical improvement (assessed by SSS) and lac/Cr ratio. Tissue metabolite concentrations distant from the infarcted region correlated with the clinical course and had predictive value. Proton MRS is very useful tool for evaluating major changes in metabolite levels in pyramidal tracts after brain stroke.

Pathophysiology of the intervertebral disc and the challenges for MRI

Through its ability to make relatively noninvasive and repeatable measurements, MRI has a great deal to offer, not only to clinical diagnosis of intervertebral disc disorders but also as a tool for basic research into disc physiology and the etiology of disc degeneration. In this brief review we outline the structure of the disc, the composition and organization of its macromolecules, and the changes that occur during disc degeneration, attempting to summarize features that have been or could become targets of MRI characterization. It is important to recognize, however, the fundamental limitation that most of the changes so far observed in MRI are consequences of alterations in cellular metabolism that occurred months to years previously and provide little insight into the current functional status of the tissue. There is therefore a need to develop MR techniques that directly characterize cellular activity and factors such as nutrient delivery on which it is critically dependent. We therefore briefly review cellular energy metabolism and nutrient transport into the avascular disc and consider the ability of MRI to reveal information about such processes. As a corollary of this discussion we also consider the constraints that the unusual transport properties of the disc impose on the delivery of contrast agents to the disc, since an understanding of these limitations is central to interpretation of the resulting images.