Application Of Magnetic Resonance Spectroscopy Research Articles

17O Solid-State NMR Spectroscopy of Lipid Membranes.

Despite the limitations posed by poor sensitivity, studies have reported the unique advantages of 17O based NMR spectroscopy to study systems existing in liquid, solid, or semisolid states. 17O NMR studies have exploited the remarkable sensitivity of quadrupole coupling and chemical shift anisotropy tensors to the local environment in the characterization of a variety of intra- and intermolecular interactions and motion. Recent studies have considerably expanded the use of 17O NMR to study dynamic intermolecular interactions associated with some of the challenging biological systems under magic angle spinning (MAS) and aligned conditions. The very fast relaxing nature of 17O has been well utilized in cellular and in vivo MRS (magnetic resonance spectroscopy) and MRI (magnetic resonance imaging) applications. The main focus of this Review is to highlight the new developments in the biological solids with a detailed discussion for a few selected examples including membrane proteins and nanodiscs. In addition to the unique benefits and limitations, the remaining challenges to overcome, and the impacts of higher magnetic fields and sensitivity enhancement techniques are discussed.

CE Workshop 12: Magnetic Resonance Spectroscopy for in vivo Assessment of Neurochemistry in Neuropsychology Research

Abstract & Learning Objectives:Magnetic resonance spectroscopy (MRS) is an imaging technique closely related to magnetic resonance imaging (MRI) that allows non-invasive measurement of tissue chemistry and metabolism in vivo. One important application of MRS is in the human brain, where few alternative methods for neurochemical/metabolic measurement are available. MRS has demonstrated clinical value in several brain conditions, including the diagnosis and staging of cancers, neurodegenerative diseases, and creatine deficiency disorder. But beyond its clinical value, MRS has tremendous potential as a research tool. In the context of neuropsychological research, MRS provides an important tool to help understand how neurochemistry and metabolism are associated with everyday cognitive functions including sensory and motor function, perception, memory, decision making, and mood. In this educational workshop, I will focus on magnetic resonance spectroscopy and its use in neuropsychology research. I will begin by introducing the basics of how MRS data are collected, processed, and analyzed I will discuss the advantages of MRS as well as its limitations. Finally, I will provide a selected summary of current literature involving the use of MRS in neuropsychological research. Upon conclusion of this course, learners will be able to: 1.Describe how magnetic resonance spectroscopy experiments are conducted, including methods of data acquisition, processing, analysis and interpretation.2.List examples from recent literature of how MRS has been used in neuropsychological research.3.Apply and devise new experiments involving the use of MRS for neuropsychological research.

Magnetic Resonance Spectroscopy Deep Learning Denoising Using Few in Vivo Data

Magnetic Resonance Spectroscopy (MRS) is a noninvasive tool to reveal metabolic information. One challenge of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> H-MRS is the low Signal-Noise Ratio (SNR). To improve the SNR, a typical approach is to perform a large number of Signal Averaging (SA). The data acquisition time, however, is proportional to the number of SA accordingly. A complete clinical MRS scan takes approximately 10 minutes in a common setting with the number of SA of 128. Recently, deep learning has been introduced to improve the SNR, but mostly the simulated data were used as the training set. This may hinder the MRS applications since some potential differences, such as acquisition system imperfections, physiological and psychologic conditions may exist between the simulated and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> data. In this paper, a new scheme that purely used repeated samples of realistic data was proposed. A deep learning model, Refusion Long Short-Term Memory (ReLSTM), was designed to learn the mapping from the time domain data with low SNR (24 SA) to the one with high SNR (128 SA). Experiments on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> brain spectra of 7 healthy, 2 tumor and 1 cerebral infarction region shows that using SA of 24, only 20% of a common setting, the spectra denoised by ReLSTM can provide the estimated concentrations of metabolites with the reliability comparable to those of the high-SNR spectra obtained commonly with 128 SA. Furthermore, compared with the state-of-the-art Low-Rank (LR) denoising method, the ReLSTM achieves lower relative errors and the Cramér-Rao lower bounds in quantifying some important biomarkers. In summary, ReLSTM can perform high-fidelity spectral denoising of the spectra with the fast acquisition (24 SA), which is valuable to MRS clinical studies.

Patients With "Gray Zone" PSA Levels: Application of Prostate MRI and MRS in the Diagnosis of Prostate Cancer.

Improving the detection rates of prostate cancer (PCa) and avoiding unnecessary prostate biopsies in men with prostate-specific antigen (PSA) levels within the gray zone require urgent attention. In this context, rapid advances in MR technology in recent years may offer a promising possibility. A systematic review to evaluate the applications of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) in detecting PCa and clinically significant PCa (csPCa) in men with PSA levels within the gray zone. The study type is defined as systematic review. In July 2022, out of 229 studies identified by the database search and from other sources, 23 articles related to the selected topic of interest were included in this review. No field strength or sequence restrictions. The data including the study population, study characteristics, as well as basic MRI characteristics, from the final studies included in this review, were extracted independently by two reviewers. The major results of the original study were summarized and no additional statistical analysis was performed. Among the 23 studies included in this review, 17 focused on the applications of MRS and MRI for the prebiopsy diagnosis of PCa. Nine of these 17 articles used Prostate Imaging Reporting and Data System (PI-RADS) score to interpret MRI results, thereby confirming the practicality of the PI-RADS score in predicting PCa and csPCa. The remaining six articles evaluated the applications of MRI and MRS in guiding prostate biopsy. Although there was a variation in the biopsy modalities used in these studies, both MRI- and MRS-guided prostate biopsies were observed to improve the detection rates of PCa and csPCa in patients with PSA levels within the gray zone. MRS and MRI showed good performance in the detection of PCa and csPCa before biopsy. In addition, MRS- or MRI-guided prostate-targeted biopsies were able to improve the detection rates of PCa and csPCa. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism.

A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for illustrating physiological and molecular processes changes before anatomical manifestations on conventional MR imaging. Among these, in vivo proton (1H) MR spectroscopy (MRS) is widely used for differentiating breast malignancy from benign diseases by measuring elevated choline-containing compounds. Further, the use of hyperpolarized 13C and 31P MRS enhanced the understanding of glucose and phospholipid metabolism. The metabolic profiling of an array of biological specimens (intact tissues, tissue extracts, and various biofluids such as blood, urine, nipple aspirates, and fine needle aspirates) can also be investigated through in vitro high-resolution NMR spectroscopy and high-resolution magic angle spectroscopy (HRMAS). Such studies can provide information on more metabolites than what is seen by in vivo MRS, thus providing a deeper insight into cancer biology and metabolism. The analysis of a large number of NMR spectral data sets through multivariate statistical methods classified the tumor sub-types. It showed enormous potential in the development of new therapeutic approaches. Recently, multiparametric MRI approaches were found to be helpful in elucidating the pathophysiology of cancer by quantifying structural, vasculature, diffusion, perfusion, and metabolic abnormalities in vivo. This review focuses on the applications of NMR, MRS, and MRI methods in understanding breast cancer biology and in the diagnosis and therapeutic monitoring of breast cancer.

In Vivo 13C Magnetic Resonance Spectroscopy for Assessing Brain Biochemistry in Health and Disease.

Magnetic resonance spectroscopy (MRS) is a non-invasive technique that contributes to the elucidation of brain biochemistry. 13C MRS enables the detection of specific neurochemicals and their neuroenergetic correlation with neuronal function. The synergistic outcome of 13C MRS and the infusion of 13C-labeled substrates provide an understanding of neurometabolism and the role of glutamate/gamma-aminobutyric acid (GABA) neurotransmission in diseases, such as Alzheimer's disease, schizophrenia, and bipolar disorder. Moreover, 13C MRS provides a window into the altered flux rate of different pathways, including the tricarboxylic acid cycle (TCA) and the glutamate/glutamine/GABA cycle, in health and in various diseases. Notably, the metabolic flux rate of the TCA cycle often decreases in neurodegenerative diseases. Additionally, 13C MRS can be used to investigate several psychiatric and neurological disorders as it directly reflects the real-time production and alterations of key brain metabolites. This review aims to highlight the chronology, the technological advancements, and the applications of 13C MRS in various brain diseases.

Usefulness of magnetic resonance spectroscopy in mesial temporal sclerosis: a systematic review.

Magnetic resonance spectroscopy (MRS) provides non-invasive information about metabolic features in different regions of the brain affected by mesial temporal sclerosis (MTS). To review articles analyzing the most common alterations in biochemical parameters in MTS and the applications of MRS in presurgical assessment. We undertook a systematic literature search for MRS in MTS in PubMed, SCOPUS, and Cochrane based on the MESH terms ""Magnetic Resonance Spectroscopy", "Proton Magnetic Resonance Spectroscopy", "Carbon-13 Magnetic Resonance Spectroscopy", "1H-MRS", "31P-MRS", "mesial temporal sclerosis", "hippocampal sclerosis", "mesial temporal seizure", and "mesial temporal epilepsy". Of the initial 134 articles found, 30 were selected after the exclusion process. Of these, 13 detected a decrease in N-acetylaspartate (NAA), 9 showed a decreased in the ratio NAA/Cho+Cr, and 8 demonstrated a decreased in the ratio NAA/Cr, all of them in the ipsilateral hippocampus. Nine studies also found reduced NAA levels in extrahippocampal regions. The main findings were a decrease in NAA in the ipsilateral hippocampus. In addition, NAA levels were low outside the hippocampus so MTS could be a more extensive disease. Patients without MTS also presented a decrease in NAA in the ipsilateral hippocampus although NAA was even lower in the MTS patients. Thus, MRS could be useful in the presurgical evaluation to locate the epileptogenic focus, but not specific for the diagnosis of MTS.

Spectral Wavelet-feature Analysis and Classification Assisted Denoising for enhancing magnetic resonance spectroscopy.

Magnetic resonance spectroscopy (MRS) is capable of revealing important biochemical and metabolic information of tissues noninvasively. However, the low concentrations of metabolites often lead to poor signal-to-noise ratio (SNR) and a long acquisition time. Therefore, the applications of MRS in detection and quantitative measurements of metabolites in vivo remain limited. Reducing or even eliminating noise can improve SNR sufficiently to obtain high quality spectra in addition to increasing the number of signal averaging (NSA) or the field strength, both of which are limited in clinical applications. We present a Spectral Wavelet-feature ANalysis and Classification Assisted Denoising (SWANCAD) approach to differentiate signal and noise peaks in magnetic resonance spectra based on their respective wavelet features, followed by removing the identified noise components to improve SNR. The performance of this new denoising approach was evaluated by measuring and comparing SNRs and quantified metabolite levels of low NSA spectra (e.g. NSA = 8) before and after denoising using the SWANCAD approach or by conventional spectral fitting and denoising methods, such as LCModel and wavelet threshold methods, as well as the high NSA spectra (e.g. NSA = 192) recorded in the same sampling volumes. The results demonstrated that SWANCAD offers a more effective way to detect the signals and improve SNR by removing noise from the noisy spectra collected with low NSA or in the subminute scan time (e.g. NSA = 8 or 16 s). The potential applications of SWANCAD include using low NSA to accelerate MRS acquisition while maintaining adequate spectroscopic information for detection and quantification of the metabolites of interest when a limited time is available for an MRS examination in the clinical setting.

Brain Metastases of Non-Small Cell Lung Cancer: Magnetic Resonance Spectroscopy for Clinical Outcome Assessment in Patients with Stereotactic Radiotherapy.

BackgroundBrain metastases (BM) are severe incidents among patients with non-small cell lung cancer (NSCLC) and have been associated with significant morbidity and decreased survival; thus, new methods are required to improve clinical management. Magnetic resonance spectroscopy (MRS) allows noninvasive measurements of biochemical information from tumor tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to explore the application of MRS in the assessment of tumor prognosis after stereotactic radiotherapy in NSCLC patients with BM.Patients and MethodsMRS was performed on NSCLC patients attending Qingdao Center Hospital with suspected BM, and 68 patients were included in the survival analysis. The qualitative and quantitative parameters of MRS metabolites, such as choline (Cho), creatine (Cr), and N-acetyl-aspartate (NAA), were recorded. To select a cutoff for MRS metabolite parameters in the tumor and to distinguish patients who had recurrence, we performed an ROC curve analysis. Univariate and multivariate Cox regression analyses were used to assess the association between MRS metabolite parameters and clinical cancer prognosis.ResultsThe average age was 56 years. A total of 68 NSCLC patients underwent metabolic evaluation with single voxel proton MRS and were selected for retrospective analysis. According to the area under the curve (AUC) to predict recurrence, the MRS metabolite parameters were determined as Cho (AUC=0.550), Cr (AUC=0.415), NAA (AUC=0.524), NAA/Cr (AUC=0.600), Cho/Cr (AUC=0.723), and Cho/NAA (AUC=0.543). Cho and Cr predicted poor survival while Cho/Cr and NAA/Cr predicted improved survival (P<0.05). In the multivariate model with adjustment to establish the potential role of MRS metabolite parameters, Cho/Cr showed a significant association with OS (P=0.009) and PFS (P=0.006) after stereotactic radiotherapy.ConclusionThe positive results of this study indicate the predictive value of metabolic characteristics of BM detected with MRS for the outcome after stereotactic radiotherapy.

The Application of MR Spectroscopy and MR Perfusion in Cerebral Syphilitic Gumma: A Case Report.

Cerebral syphilitic gumma is a rare disease and can be misdiagnosed as a common brain tumor when only conventional imaging results are adopted. Differentiating between syphilitic gumma and tumors may be achieved by applying advanced magnetic resonance (MR) techniques, such as MR spectroscopy and MR perfusion. However, the MR perfusion characteristics of cerebral syphilitic gumma have not been reported yet. Here, we report a case of cerebral syphilitic gumma in a 52-year-old woman and discuss the imaging features of conventional MR, MR spectroscopy, and MR perfusion. The results suggest that the application of MR spectroscopy and MR perfusion could provide additional information that contributes to the diagnosis of cerebral syphilitic gumma.

Current Practice and New Developments in the Use of In Vivo Magnetic Resonance Spectroscopy for the Assessment of Key Metabolites Implicated in the Pathophysiology of Schizophrenia.

Magnetic Resonance Spectroscopy (MRS) has become a valuable tool for investigating the biochemical bases of both normal processes in the healthy brain and elucidating the pathophysiology of neuropsychiatric disorders. As a rapidly advancing field, new developments in pulse sequence design have seen new possibilities arise in terms of what can be done with in vivo spectroscopy. While the applications of MRS are numerous, this review has been confined to the use of single voxel spectroscopy in the assessment of five key metabolites and their roles in schizophrenia: N-acetylaspartate (NAA), glutamate (Glu) and glutamine (Gln), γ-aminobutyric acid (GABA) and glutathione (GSH). This article will briefly cover the roles they play in schizophrenia, review current methods being used in their assessment and highlight new approaches that may potentially overcome some of the limitations current methods pose.

Dephasing optimization through coherence order pathway selection (DOTCOPS) for improved crusher schemes in MR spectroscopy

To develop an algorithm which can robustly eliminate all unwanted coherence pathways for an arbitrary magnetic resonance spectroscopy experiment through the adjustment of the relative amplitudes of crusher gradients, thereby reducing the effects of spurious echoes and mislocalization. The effect of crushing gradients for all coherence pathways was modeled according to the associated physics, and a cost function was optimized which maximally crushes all unwanted coherence pathways, while unaffecting the desired coherence pathway(s). The efficacy of the method was tested versus literature schemes from 2 separate MR spectroscopy (MRS) sequences: sLASER and MEGA-sLASER with both phantom and in vivo experiments. Improved crushing power for 2 separate MRS sequences was demonstrated for 2 crushing schemes adopted from the literature in both phantom and in vivo data. A novel algorithm and associated software was developed based on rigorous treatment of all coherence pathways, which can be applied to any arbitrary magnetic resonance spectroscopic pulse sequence of interest and any arbitrary coupled spin system. This developed method solves a long-standing problem in in vivo MRS and is expected to critically improve the data quality of virtually all MRS applications.

Repeatability of Dixon magnetic resonance imaging and magnetic resonance spectroscopy for quantitative muscle fat assessments in the thigh.

BackgroundChanges in muscle fat composition as for example observed in sarcopenia or muscular dystrophy affect physical performance and muscular function, like strength and power. The purpose of the present study is to measure the repeatability of Dixon magnetic resonance imaging (MRI) for assessing muscle volume and fat in the thigh. Furthermore, repeatability of magnetic resonance spectroscopy (MRS) for assessing muscle fat is determined.MethodsA prototype 6‐point Dixon MRI method was used to measure muscle volume and muscle proton density fat fraction (PDFF) in the left thigh. PDFF was measured in musculus semitendinosus of the left thigh with a T2‐corrected multi‐echo MRS method. For the determination of short‐term repeatability (consecutive examinations), the root mean square coefficients of variation of Dixon MRI and MRS data of 23 young and healthy (29 ± 5 years) and 24 elderly men with sarcopenia (78 ± 5 years) were calculated. For the estimation of the long‐term repeatability (13 weeks between examinations), the root mean square coefficients of variation of MRI data of seven young and healthy (31 ± 7 years) and 23 elderly sarcopenic men (76 ± 5 years) were calculated. Long‐term repeatability of MRS was not determined.ResultsShort‐term errors of Dixon MRI volume measurement were between 1.2% and 1.5%, between 2.1% and 1.6% for Dixon MRI PDFF measurement, and between 9.0% and 15.3% for MRS. Because of the high short‐term repeatability errors of MRS, long‐term errors were not determined. Long‐term errors of MRI volume measurement were between 1.9% and 4.0% and of Dixon MRI PDFF measurement between 2.1% and 4.2%.ConclusionsThe high degree of repeatability of volume and PDFF Dixon MRI supports its use to predict future mobility impairment and measures the success of therapeutic interventions, for example, in sarcopenia in aging populations and muscular dystrophy. Because of possible inhomogeneity of fat infiltration in muscle tissue, the application of MRS for PDFF measurements in muscle is more problematic because this may result in high repeatability errors. In addition, the tissue composition within the MRS voxel may not be representative for the whole muscle.

Application of MRS- and ASL-guided navigation for biopsy of intracranial tumors.

The diagnosis of a tumor depends on accurate identification of the target area for biopsy. However, tumor heterogeneity and the inability of conventional structural data for identifying the most malignant areas can reduce this accuracy. To evaluate the feasibility and practicality of magnetic resonance spectroscopy (MRS)- and arterial spin labeling (ASL)-guided MRI navigation for needle biopsy of intracranial tumors. Thirty patients with intracranial tumors who underwent intraoperative stereotactic biopsy were retrospectively analyzed. Contrast-enhanced 3D-BRAVO or 3D-T2FLAIR structural data, combined with MRS and ASL data, were used to identify the target area for biopsy. High-choline or high-perfusion sites were chosen preferentially, and then the puncture trajectory was optimized to obtain specimens for histopathologic examination. Twenty-two specimens were collected from 20 glioma patients (two specimens each were collected from two patients) and ten specimens were collected from ten lymphoma patients. The diagnosis rate after the biopsy was 93.3% (28/30). Two gliomas were initially diagnosed as gliosis and subsequently diagnosed correctly after the collection of a second biopsy specimen. Combined MRS and ASL helped target selection in 23 cases (76.7%), including three cases each of low-enhancing and non-enhancing gliomas. In two cases, the target selection decision was changed because the areas initially chosen on the basis of positron emission tomography data did not match the high-perfusion areas identified with ASL. Compared with conventional MRI, combined MRS and ASL improved the accuracy of target selection for the stereotactic biopsy of intracranial tumors.

Ultra-High-Field Magnetic Resonance Spectroscopy in Psychiatry

The advantages of ultra-high-field (UHF ≥ 7T) MR have been demonstrated in a variety of MR acquisition modalities. Magnetic resonance spectroscopy (MRS) can particularly benefit from substantial gains in signal-to-noise ratio (SNR) and spectral resolution at UHF, enabling the quantification of numerous metabolites, including glutamate, glutamine, glutathione, and γ-aminobutyric acid that are relevant to psychiatric disorders. The aim of this review is to give an overview about the advantages and advances of UHF MRS and its application to psychiatric disorders. In order to provide a practical guide for potential applications of MRS at UHF, a literature review is given, surveying advantages and disadvantages of MRS at UHF. Key concepts, emerging technologies, practical considerations, and applications of UHF MRS are provided. Second, the strength of UHF MRS is demonstrated using some examples of its application in psychiatric disorders.

MRI and MRS on preserved samples as a tool in fish ecology

Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) gain increasing attention and importance as a tool in marine ecology. So far, studies were largely limited to morphological studies, e.g. for the creation of digital libraries. Here, the utility of MRI and MRS for ecologists is tested and exemplified using formalin preserved samples of the Antarctic silverfish, Pleuragramma antarctica. As this species lacks a swim bladder, buoyancy is attained by the deposition of large amounts of lipids that are mainly stored in subcutaneous and intermuscular lipid sacs. In this study MRI and MRS are not only used to study internal morphology, but additionally to investigate functional morphology and to measure parameters of high ecological interest. The data are compared with literature data obtained by means of traditional ecological methods.The results from this study show that MR scans are not only an alternative to histological sections (as shown before), but even allow the visualization of particular features in delicate soft tissues, such as Pleuragramma's lipid sacs. 3D rendering techniques proved to be a useful tool to study organ volumes and lipid content, which usually requires laborious chemical lipid extraction and analysis. Moreover, the application of MRS even allows for an analysis of lipids and fatty acids within lipid sacs, which wouldn't be possible using destructive methods. MRI and MRS, in particular when used in combination, have the capacity to provide useful data on parameters of high ecological relevance and thus have proven to be a highly valuable addition, if not alternative, to the classical methods.

In vivo MRS of Muscle, Liver, Heart and Other Organs: A Review of Techniques and Applications

As MRI has been used in biomedical research and medicine since the 1970s, Magnetic Resonance Spectroscopy (MRS) has been employed to study biochemical alterations in living animals and humans. By taking advantage of its noninvasive nature, 1H, 13C and 31P MRS are being actively utilized in clinical and biomedical studies to detect lipids, metabolites, and/or kinetic information, such as acetyl carnitine content and ATP synthesis rates in vivo. These data would be quite difficult to assess by other modalities. Furthermore, many studies have indicated that in vivo values obtained by MRS show a close correlation with important metabolic parameters (e.g., hepatic and intramyocellular lipid content by 1H-MRS correlated with insulin sensitivity), which adds value of MRS. Moreover, hepatic glycogen synthesis and breakdown can be directly detected by 13C-MRS, whereas in vivo ATP synthesis rates in mitochondria can be assessed by 31P-MRS as well. These in vivo data offer critical metabolic information in animals and humans, and often serve as useful biomarkers for the pathophysiology and state of a disease. Thus, in this review, important and frequently used modalities and applications of MRS in muscle, liver, and other organs are described.

Use of in vivo magnetic resonance spectroscopy for studying metabolic diseases.

Owing to the worldwide obesity epidemic and the sedentary lifestyle in industrialized countries, the number of people with metabolic diseases is explosively increasing. Magnetic resonance spectroscopy (MRS), which is fundamentally similar to magnetic resonance imaging, can detect metabolic changes in vivo noninvasively. With its noninvasive nature, 1H, 13C and 31P MRS are being actively utilized in clinical and biomedical metabolic studies to detect lipids and important metabolites without ionizing radiation. 1H MRS can quantify lipid content in liver and muscle and can detect other metabolites, such as 2-hydroxyglutarate, in vivo. Of interest, many studies have indicated that hepatic and intramyocellular lipid content is inversely correlated with insulin sensitivity in humans. Thus, lipid content can be utilized as an in vivo biomarker for detecting early insulin resistance. Employing 13C MRS, hepatic glycogen synthesis and breakdown can be directly detected, whereas 31P MRS provides in vivo adenosine triphosphate (ATP) synthesis rates by saturation transfer methods in addition to ATP content. These in vivo data can be very difficult to assess by other methods and offer a critical piece of metabolic information. To aid the reader in understanding these new methods, fundamentals of MRS are described in this review in addition to promising future applications of MRS and its limitations.

Optimized spectral analysis in magnetic resonance spectroscopy for early tumor diagnostics

Molecular imaging through magnetic resonance spectroscopy (MRS) can provide information about key metabolites. Conventional applications of MRS are hampered by data analysis via the fast Fourier transform (FFT). Most MRS studies for cancer detection have relied upon estimations of a mere handful or even a single composite metabolite, e.g. total choline. These have yielded incremental improvements in diagnostic accuracy. In vitro studies reveal richer metabolic information for identifying cancer, particularly in closely-overlapping resonances. Among these are phosphocholine, a marker of malignant transformation. The FFT cannot assess these congested spectral components. This can be done by the fast Pade transform (FPT), an advanced, high-resolution, quantification-equipped method, applied to MRS time signals as encoded from patients with breast cancers and other cancers, with benign pathology and with normal tissue, as illustrated herein for the latter. With realistic noise levels, the FPT accurately computes the metabolite concentrations, including phosphocholine, which completely underlies phosphoethanolamine. In sharp contrast, the FFT produces a rough envelope spectrum with only a few shortened, broadened peaks, and key metabolites altogether absent. The FPT clearly separates true metabolites from spurious resonances. The efficiency and high resolution of the FPT translates into shortened examination time of the patient. These capabilities strongly suggest that by applying the FPT to time signals encoded in vivo from breast cancer and other malignancies, MRS will fulfill its potential to become a clinically- reliable, cost-effective method for early cancer detection.

Proof-of-the-Concept Study on Mathematically Optimized Magnetic Resonance Spectroscopy for Breast Cancer Diagnostics.

Magnetic resonance (MR)-based modalities aid breast cancer detection without exposure to ionizing radiation. Magnetic resonance imaging is very sensitive but costly and insufficiently specific. Molecular imaging through magnetic resonance spectroscopy (MRS) can provide information about key metabolites. Here, the measured/encoded time signals cannot be interpreted directly, necessitating mathematics for mapping to the more manageable frequency domain. Conventional applications of MRS are hampered by data analysis via the fast Fourier transform (FFT) and postprocessing by fitting techniques. Most in vivo MRS studies on breast cancer rely upon estimations of total choline (tCHO). These have yielded only incremental improvements in diagnostic accuracy. In vitro studies reveal richer metabolic information for identifying breast cancer, particularly in closely overlapping components of tCHO. Among these are phosphocholine (PC), a marker of malignant transformation of the breast. The FFT cannot assess these congested spectral components. This can be done by the fast Padé transform (FPT), a high-resolution, quantification-equipped method, which we presently apply to noisy MRS time signals consistent with those encoded in breast cancer. The FPT unequivocally and robustly extracted the concentrations of all physical metabolites, including PC. In sharp contrast, the FFT produced a rough envelope spectrum with a few distorted peaks and key metabolites absent altogether. As such, the FFT has poor resolution for these typical MRS time signals from breast cancer. Hence, based on Fourier-estimated envelope spectra, tCHO estimates are unreliable. Using even truncated time signals, the FPT clearly distinguishes noise from true metabolites whose concentrations are accurately extracted. The high resolution of the FPT translates directly into shortened examination time of the patient. These capabilities strongly suggest that by applying the FPT to time signals encoded in vivo from the breast, MRS will, at last, fulfill its potential to become a clinically reliable, cost-effective method for breast cancer detection, including screening/surveillance.