In vivo (1) H MR spectroscopic imaging of aggressive prostate cancer: can we detect lactate?

NMR spectroscopy for metabolomics in the living system: recent progress and future challenges

Metabolism is a fundamental process that underlies human health and diseases. Nuclear magnetic resonance (NMR) techniques offer a powerful approach to identify metabolic processes and track the flux of metabolites at the molecular level in living systems. An in vitro study through in-cell NMR tracks metabolites in real time and investigates protein structures and dynamics in a state close to their most natural environment. This technique characterizes metabolites and proteins involved in metabolic pathways in prokaryotic and eukaryotic cells. In vivo magnetic resonance spectroscopy (MRS) enables whole-organism metabolic monitoring by visualizing the spatial distribution of metabolites and targeted proteins. One limitation of these NMR techniques is the sensitivity, for which a possible improved approach is through isotopic enrichment or hyperpolarization methods, including dynamic nuclear polarization (DNP) and parahydrogen-induced polarization (PHIP). DNP involves the transfer of high polarization from electronic spins of radicals to surrounding nuclear spins for signal enhancements, allowing the detection of low-abundance metabolites and real-time monitoring of metabolic activities. PHIP enables the transfer of nuclear spin polarization from parahydrogen to other nuclei for signal enhancements, particularly in proton NMR, and has been applied in studies of enzymatic reactions and cell signaling. This review provides an overview of in-cell NMR, in vivo MRS, and hyperpolarization techniques, highlighting their applications in metabolic studies and discussing challenges and future perspectives.

A multivariate curve resolution analysis of multicenter proton spectroscopic imaging of the prostate for cancer localization and assessment of aggressiveness

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR-ALS) algorithm for analyzing three-dimensional (3D) 1 H-MRSI data of the prostate in prostate cancer (PCa) patients. MCR-ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1 H-MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR-ALS and assigned to specific tissue types. Using these components, MCR-ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t-test, p < 0.001). This result was achieved including voxels with low-quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low- and high-risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR-ALS analysis of 1 H-MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR-ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients.

Developments in proton MR spectroscopic imaging of prostate cancer

In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.

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.

Supervised risk predictor of central gland lesions in prostate cancer using 1 H MR spectroscopic imaging with gradient offset-independent adiabaticity pulses

BACKGROUND

Due to the histological heterogeneity of the central gland, accurate detection of central gland prostate cancer remains a challenge.

PURPOSE

To evaluate the efficacy of in vivo 3D ¹ H MR spectroscopic imaging (3D ¹ H MRSI) with a semi-localized adiabatic selective refocusing (sLASER) sequence and gradient-modulated offset-independent adiabatic (GOIA) pulses for detection of central gland prostate cancer. Additionally four risk models were developed to differentiate 1) normal vs. cancer, 2) low- vs. high-risk cancer, 3) low- vs. intermediate-risk cancer, and 4) intermediate- vs. high-risk cancer voxels.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-six patients with biopsy-proven central gland prostate cancer.

FIELD STRENGTH/SEQUENCE

3T MRI / 3D ¹ H MRSI using GOIA-sLASER.

ASSESSMENT

Cancer and normal regions of interest (ROIs) were selected by an experienced radiologist and ¹ H MRSI voxels were placed within the ROIs to calculate seven metabolite signal ratios. Voxels were split into two subsets, 80% for model training and 20% for testing.

STATISTICAL TESTS

Four support vector machine (SVM) models were built using the training dataset. The accuracy, sensitivity, and specificity for each model were calculated for the testing dataset.

RESULTS

High-quality MR spectra were obtained for the whole central gland of the prostate. The normal vs. cancer diagnostic model achieved the highest predictive performance with an accuracy, sensitivity, and specificity of 96.2%, 95.8%, and 93.1%, respectively. The accuracy, sensitivity, and specificity of the low- vs. high-risk cancer and low- vs. intermediate-risk cancer models were 82.5%, 89.2%, 70.2%, and 73.0%, 84.7%, 60.8%, respectively. The intermediate- vs. high-risk cancer model yielded an accuracy, sensitivity, and specificity lower than 55%.

DATA CONCLUSION

The GOIA-sLASER sequence with an external phased-array coil allows for fast assessment of central gland prostate cancer. The classification offers a promising diagnostic tool for discriminating normal vs. cancer, low- vs. high-risk cancer, and low- vs. intermediate-risk cancer.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1926-1936.

Clinical applications of in vivo magnetic resonance spectroscopy in oncology

Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.

Targeting tumor-associated acidity in cancer immunotherapy

Checkpoint inhibitors, such as cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and programmed cell death-1 (PD-1) monoclonal antibodies have changed profoundly the treatment of melanoma, renal cell carcinoma, non-small cell lung cancer, Hodgkin lymphoma, and bladder cancer. Currently, they are tested in various tumor entities as monotherapy or in combination with chemotherapies or targeted therapies. However, only a subgroup of patients benefit from checkpoint blockade (combinations). This raises the question, which all mechanisms inhibit T cell function in the tumor environment, restricting the efficacy of these immunotherapeutic approaches. Serum activity of lactate dehydrogenase, likely reflecting the glycolytic activity of the tumor cells and thus acidity within the tumor microenvironment, turned out to be one of the strongest markers predicting response to checkpoint inhibition. In this review, we discuss the impact of tumor-associated acidity on the efficacy of T cell-mediated cancer immunotherapy and possible approaches to break this barrier.

Cisplatin generates oxidative stress which is accompanied by rapid shifts in central carbon metabolism

Cisplatin is commonly utilized in the treatment of solid tumors. Its mechanism of action is complex and multiple mechanisms of resistance have been described. We sought to determine the impact of cisplatin-generated oxidative stress on head and neck squamous cell carcinoma (HNSCC) proliferation, survival and metabolic activity in order to identify a potential metabolic signature associated with cisplatin response. DNA-bound cisplatin represents a small fraction of total intra-cellular cisplatin but generates a robust oxidative stress response. Neutralization of oxidative stress reverses cisplatin toxicity independent of the mechanism of cell death and TP53 mutational status. Cisplatin-induced oxidative stress triggers rapid shifts in carbon flux in 3 commonly utilized catabolic pathways: glycolysis, pentose phosphate pathway and citric acid cycle. Among these metabolic shifts, decreased flux from pyruvate into lactate is the only metabolic effect consistently observed across multiple HNSCC cell lines of varying genomic backgrounds and may reflect differential cisplatin sensitivity. Oxidative stress is a critical component of cisplatin cytotoxicity in HNSCC and is reflected in acute changes in carbon flux from pyruvate into lactate. This suggests that lactate may contribute to a metabolic signature of acute cisplatin toxicity, and could prove useful in optimizing cisplatin-based treatment regimens in HNSCC.

Hierarchical non-negative matrix factorization applied to three-dimensional 3 T MRSI data for automatic tissue characterization of the prostate

In this study non-negative matrix factorization (NMF) was hierarchically applied to simulated and in vivo three-dimensional 3 T MRSI data of the prostate to extract patterns for tumour and benign tissue and to visualize their spatial distribution. Our studies show that the hierarchical scheme provides more reliable tissue patterns than those obtained by performing only one NMF level. We compared the performance of three different NMF implementations in terms of pattern detection accuracy and efficiency when embedded into the same kind of hierarchical scheme. The simulation and in vivo results show that the three implementations perform similarly, although one of them is more robust and better pinpoints the most aggressive tumour voxel(s) in the dataset. Furthermore, they are able to detect tumour and benign tissue patterns even in spectra with lipid artefacts. Copyright © 2016 John Wiley & Sons, Ltd.

Acute Tumor Lactate Perturbations as a Biomarker of Genotoxic Stress: Development of a Biochemical Model

Ionizing radiation is the primary nonsurgical treatment modality for solid tumors. Its effectiveness is impacted by temporal constraints such as fractionation, hypoxia, and development of radioresistant clones. Biomarkers of acute radiation response are essential to developing more effective clinical algorithms. We hypothesized that acute perturbations in tumor lactate levels act as a surrogate marker of radiation response. In vitro experiments were carried out using validated human-derived cell lines from three histologies: anaplastic thyroid carcinoma (ATC), head and neck squamous cell carcinoma (HNSCC), and papillary thyroid carcinoma (PTC). Cellular metabolic activity was measured using standard biochemical assays. In vivo validation was performed using both an orthotopic and a flank derivative of a previously established ATC xenograft murine model. Irradiation of cells and tumors triggered a rapid, dose-dependent, transient decrease in lactate levels that was reversed by free radical scavengers. Acute lactate perturbations following irradiation could identify hypoxic conditions and correlated with hypoxia-induced radioresistance. Mutant TP53 cells and cells in which p53 activity was abrogated (shRNA) demonstrated a blunted lactate response to irradiation, consistent with a radioresistant phenotype. Lactate measurements therefore rapidly detected both induced (i.e., hypoxia) and intrinsic (i.e., mutTP53-driven) radioresistance. We conclude that lactate is a quantitative biomarker of acute genotoxic stress, with a temporal resolution that can inform clinical decision making. Combined with the spatial resolution of newly developed metabolic imaging platforms, this biomarker could lead to the development of truly individualized treatment strategies.

Multiparametric-MRI in diagnosis of prostate cancer

Multiparametric-magnetic resonance imaging (mp-MRI) has shown promising results in diagnosis, localization, risk stratification and staging of clinically significant prostate cancer. It has also opened up opportunities for focal treatment of prostate cancer. Combinations of T2-weighted imaging, diffusion imaging, perfusion (dynamic contrast-enhanced imaging) and spectroscopic imaging have been used in mp-MRI assessment of prostate cancer, but T2 morphologic assessment and functional assessment by diffusion imaging remains the mainstay for prostate cancer diagnosis on mp-MRI. Because assessment on mp-MRI can be subjective, use of the newly developed standardized reporting Prostate Imaging and Reporting Archiving Data System scoring system and education of specialist radiologists are essential for accurate interpretation. This review focuses on the present status of mp-MRI in prostate cancer and its evolving role in the management of prostate cancer.

MRI methods for the evaluation of high intensity focused ultrasound tumor treatment: Current status and future needs

Thermal ablation with high intensity focused ultrasound (HIFU) is an emerging noninvasive technique for the treatment of solid tumors. HIFU treatment of malignant tumors requires accurate treatment planning, monitoring and evaluation, which can be facilitated by performing the procedure in an MR-guided HIFU system. The MR-based evaluation of HIFU treatment is most often restricted to contrast-enhanced T1 -weighted imaging, while it has been shown that the non-perfused volume may not reflect the extent of nonviable tumor tissue after HIFU treatment. There are multiple studies in which more advanced MRI methods were assessed for their suitability for the evaluation of HIFU treatment. While several of these methods seem promising regarding their sensitivity to HIFU-induced tissue changes, there is still ample room for improvement of MRI protocols for HIFU treatment evaluation. In this review article, we describe the major acute and delayed effects of HIFU treatment. For each effect, the MRI methods that have been-or could be-used to detect the associated tissue changes are described. In addition, the potential value of multiparametric MRI for the evaluation of HIFU treatment is discussed. The review ends with a discussion on future directions for the MRI-based evaluation of HIFU treatment.

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.

Impacts of MR spectroscopic imaging on glioma patient management

Magnetic resonance (MR) modalities are routine imaging tools in the diagnosis and management of gliomas. MR spectroscopic imaging (MRSI), which relies on the metabolic characteristics of tissues, has been developed to accelerate the understanding of gliomas and to aid in effective clinical decision making and development of targeted therapies. In this review, the potentials and practical challenges to frequently use this technique in clinical management of gliomas are discussed. The applications of new biomarkers detectable by MRSI in differential glioma diagnosis, pre- and post-treatment evaluations, and neurosurgery are also addressed.

Metabolite ratios in 1H MR spectroscopic imaging of the prostate

In (1)H MR spectroscopic imaging ((1)H-MRSI) of the prostate the spatial distribution of the signal levels of the metabolites choline, creatine, polyamines, and citrate are assessed. The ratio of choline (plus spermine as the main polyamine) plus creatine over citrate [(Cho+(Spm+)Cr)/Cit] is derived from these metabolites and is used as a marker for the presence of prostate cancer. In this review, the factors that are of importance for the metabolite ratio are discussed. This is relevant, because the appearance of the metabolites in the spectrum depends not only on the underlying anatomy, metabolism, and physiology of the tissue, but also on acquisition parameters. These parameters influence especially the spectral shapes of citrate and spermine resonances, and consequently, the (Cho+(Spm+)Cr)/Cit ratio. Both qualitative and quantitative approaches can be used for the evaluation of (1)H-MRSI spectra of the prostate. For the quantitative approach, the (Cho+(Spm+)Cr)/Cit ratio can be determined by integration or by a fit based on model signals. Using the latter, the influence of the acquisition parameters on citrate can be taken into account. The strong overlap between the choline, creatine, and spermine resonances complicates fitting of the individual metabolites. This overlap and (unknown, possibly tissue-related) variations in T1, T2, and J-modulation hamper the application of corrections needed for a "normalized" (Cho+(Spm+)Cr)/Cit ratio that would enable comparison of spectra measured with different prostate MR spectroscopy protocols. Quantitative (Cho+(Spm+)Cr)/Cit thresholds for the evaluation of prostate cancer are therefore commonly established per institution or per protocol. However, if the same acquisition and postprocessing protocol were used, the ratio and the thresholds would be institution-independent, promoting the clinical usability of prostate (1)H-MRSI.

Mapping of prostate cancer by 1H MRSI

In many studies, it has been demonstrated that (1)H MRSI of the human prostate has great potential to aid prostate cancer management, e.g. in the detection and localisation of cancer foci in the prostate or in the assessment of its aggressiveness. It is particularly powerful in combination with T2 -weighted MRI. Nevertheless, the technique is currently mainly used in a research setting. This review provides an overview of the state-of-the-art of three-dimensional MRSI, including the specific hardware required, dedicated data acquisition sequences and information on the spectral content with background on the MR-visible metabolites. In clinical practice, it is important that relevant MRSI results become available rapidly, reliably and in an easy digestible way. However, this functionality is currently not fully available for prostate MRSI, which is a major obstacle for routine use by inexperienced clinicians. Routine use requires more automation in the processing of raw data than is currently available. Therefore, we pay specific attention in this review on the status and prospects of the automated handling of prostate MRSI data, including quality control. The clinical potential of three-dimensional MRSI of the prostate is illustrated with literature examples on prostate cancer detection, its localisation in the prostate, its role in the assessment of cancer aggressiveness and in the selection and monitoring of therapy.