1H MR spectroscopy of brain tumours and masses

Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm

Magnetic resonance spectroscopy offers information about metabolite changes in the organism, which can be used in diagnosis. While short echo time proton spectra exhibit more distinguishable metabolites compared with proton spectra acquired with long echo times, their quantification (and providing estimates of metabolite concentrations) is more challenging. They are hampered by a background signal, which originates mainly from macromolecules (MM) and mobile lipids. An improved version of the quantification algorithm QUantitation based on quantum ESTimation (QUEST), with MM prior knowledge (QUEST-MM), dedicated to proton signals and invoking appropriate prior knowledge on MM, is proposed and tested. From a single acquisition, it enables better metabolite quantification, automatic estimation of the background, and additional automatic quantification of MM components, thus improving its applicability in the clinic. The proposed algorithm may facilitate studies that involve patients with pathological MM in the brain. QUEST-MM and three QUEST-based strategies for quantifying short echo time signals are compared in terms of bias-variance trade-off and Cramér-Rao lower bound estimates. The performances of the methods are evaluated through extensive Monte Carlo studies. In particular, the histograms of the metabolite and MM amplitude distributions demonstrate the performances of the estimators. They showed that QUEST-MM works better than QUEST (Subtract approach) and is a good alternative to QUEST when measured MM signal is unavailable or unsuitable. Quantification with QUEST-MM is shown for 1 H in vivo rat brain signals obtained with the SPECIAL pulse sequence at 9.4 T, and human brain signals obtained, respectively, with STEAM at 4 T and PRESS at 3 T. QUEST-MM is implemented in jMRUI and will be available for public use from version 7.1.

In-phase simultaneous spectral editing of lactate and alanine with suppression of J-coupled lipids by the modified selective multiple quantum coherence sequences

¹H magnetic resonance spectroscopy (MRS) with the multiple quantum coherence (MQC) technique allows for the detection of lactate, an end product of glycolysis, in the environment of lipids. The method can also be used to detect alanine, a byproduct of glutaminolysis. An issue is that when both lactate and alanine are detected together by the MQC technique, a phase mismatch arises between lactate and alanine signals due to off-resonance rotations and the difference in double quantum coherence frequencies between the two molecules. Such phase mismatch can cause errors in spectral fitting and metabolite quantification. In this study, we designed two pulse sequences that eliminate such phase differences of lactate and alanine while suppressing lipid signals by modifications of the Selective Multiple Quantum Coherence (Sel-MQC) sequence, a well-known MQC technique. Using the product operator formalism and the off-resonance rotation matrices, the phase evolutions of lactate and alanine during the spectrally selective pulses and the free precession times of the sequence at the single quantum, double quantum and zero quantum coherence states of these molecules were calculated. The multiple quantum (MQ) evolution time t₁ that can remove the phase difference of lactate and alanine at the echo was calculated and fine-tuned with experiments. The lactate and alanine signal intensities and the editing efficiencies from the two modified Sel-MQC sequences were theoretically predicted by using the product operator evolutions and compared with the experimental data. The J-coupled lipid signals were successfully suppressed by both sequences. One of the two developed sequences was applied to a human body with a phantom of lactate and alanine, which resulted in successful in-phase editing of lactate and alanine and suppression of the lipid signals from the body. The study sets an important foundation for the noninvasive detection of lactate and alanine from tumors of cancer patients.

Evaluation of Proton MR Spectroscopy for the Study of the Tongue Tissue in Healthy Subjects and Patients With Tongue Squamous Cell Carcinoma: Preliminary Findings

Purpose

To noninvasively assess spectroscopic and metabolic profiles of healthy tongue tissue and in an exploratory objective in nontreated and treated patients with tongue squamous cell carcinoma (SCC).

Methods

Fourteen healthy subjects (HSs), one patient with nontreated tongue SCC (NT-SCC), and two patients with treated tongue SCC (T-SCC) underwent MRI and single-voxel proton magnetic resonance spectroscopy (1H-MRS) evaluations (3 and 1.5T). Multi-echo-times 1H-MRS was performed at the medial superior part (MSP) and the anterior inferior part (AIP) of the tongue in HS, while 1H-MRS voxel was placed at the most aggressive part of the tumor for patients with tongue SCC. 1H-MRS data analysis yielded spectroscopic metabolite ratios quantified to total creatine.

Results

In HS, compared to MSP and AIP, 1H-MRS spectra revealed higher levels of creatine, a more prominent and well-identified trimethylamine-choline (TMA-Cho) peak. However, larger prominent lipid peaks were better differentiated in the tongue MSP. Compared to HS, patients with NT-SCC exhibited very high levels of lipids and relatively higher values of TMA-Cho peak. Interestingly, patients with T-SCC showed almost nonproliferation activity. However, high lipids levels were measured, although they were relatively lower than lipids levels measured in patients with NT-SCC.

Conclusion

The present study demonstrated the potential use of in-vivo1H-MRS to noninvasively assess spectroscopic and metabolic profiles of the healthy tongue tissue in a spatial location-dependent manner. Preliminary results revealed differences between HS and patients with tongue NT-SCC as well as tongue T-SCC, which should be confirmed with more patients. 1H-MRS could be included, in the future, in the arsenal of tools for treatment response evaluation and noninvasive monitoring of patients with tongue SCC.

Structure-guided design enables development of a hyperpolarized molecular probe for the detection of aminopeptidase N activity in vivo

Dynamic nuclear polarization (DNP) is a cutting-edge technique that markedly enhances the detection sensitivity of molecules using nuclear magnetic resonance (NMR)/magnetic resonance imaging (MRI). This methodology enables real-time imaging of dynamic metabolic status in vivo using MRI. To expand the targetable metabolic reactions, there is a demand for developing exogenous, i.e., artificially designed, DNP-NMR molecular probes; however, complying with the requirements of practical DNP-NMR molecular probes is challenging because of the lack of established design guidelines. Here, we report Ala-[1-¹³C]Gly-d₂-NMe₂ as a DNP-NMR molecular probe for in vivo detection of aminopeptidase N activity. We developed this probe rationally through precise structural investigation, calculation, biochemical assessment, and advanced molecular design to achieve rapid and detectable responses to enzyme activity in vivo. With the fabricated probe, we successfully detected enzymatic activity in vivo. This report presents a comprehensive approach for the development of artificially derived, practical DNP-NMR molecular probes through structure-guided molecular design.

Coherence pathway analysis of J-coupled lipids and lactate and effective suppression of lipids upon the selective multiple quantum coherence lactate editing sequence

Objective:The selective multiple quantum coherence (Sel-MQC) sequence is a magnetic resonance spectroscopy (MRS) technique used to detect lactate and suppress co-resonant lipid signalsin vivo. The coherence pathways of J-coupled lipids upon the sequence, however, have not been studied, hindering a logical design of the sequence to fully attenuate lipid signals. The objective of this study is to elucidate the coherence pathways of J-coupled lipids upon the Sel-MQC sequence and find a strategy to effectively suppress lipid signals from these pathways while keeping the lactate signal.Approach:The product operator formalism was used to express the evolutions of the J-coupled spins of lipids and lactate. The transformations of the product operators by the spectrally selective pulses of the sequence were calculated by using the off-resonance rotation matrices. The coherence pathways and the conversion rates of the individual pathways were derived from them. Experiments were performed on phantoms and two human subjects at 3T.Main results:The coherence pathways contributing to the various lipid resonance signals by the Sel-MQC sequence depending on the gradient ratios and RF pulse lengths were identified. Theoretical calculations of the signals from the determined coherence pathways and signal attenuations by gradients matched the experimental data very well. Lipid signals from fatty tissues of the subjects were successfully suppressed to the noise level by using the gradient ratio -0.8:-1:2 or 1:0.8:2. The new gradient ratios kept the lactate signal the same as with the previously used gradient ratio 0:-1:2.Significance:The study has elucidated the coherence pathways of J-coupled lipids upon the Sel-MQC sequence and demonstrated how lipid signals can be effectively suppressed while keeping lactate signals by using information from the coherence pathway analysis. The findings enable applying the Sel-MQC sequence to lactate detection in an environment of high concentrations of lipids.

Water-suppression cycling 3-T cardiac 1 H-MRS detects altered creatine and choline in patients with aortic or mitral stenosis

Cardiac proton spectroscopy (1 H-MRS) is widely used to quantify lipids. Other metabolites (e.g. creatine and choline) are clinically relevant but more challenging to quantify because of their low concentrations (approximately 10 mmol/L) and because of cardiac motion. To quantify cardiac creatine and choline, we added water-suppression cycling (WSC) to two single-voxel spectroscopy sequences (STEAM and PRESS). WSC introduces controlled residual water signals that alternate between positive and negative phases from transient to transient, enabling robust phase and frequency correction. Moreover, a particular weighted sum of transients eliminates residual water signals without baseline distortion. We compared WSC and the vendor's standard 'WET' water suppression in phantoms. Next, we tested repeatability in 10 volunteers (seven males, three females; age 29.3 ± 4.0 years; body mass index [BMI] 23.7 ± 4.1 kg/m2 ). Fat fraction, creatine concentration and choline concentration when quantified by STEAM-WET were 0.30% ± 0.11%, 29.6 ± 7.0 μmol/g and 7.9 ± 6.7 μmol/g, respectively; and when quantified by PRESS-WSC they were 0.30% ± 0.15%, 31.5 ± 3.1 μmol/g and 8.3 ± 4.4 μmol/g, respectively. Compared with STEAM-WET, PRESS-WSC gave spectra whose fitting quality expressed by Cramér-Rao lower bounds improved by 26% for creatine and 32% for choline. Repeatability of metabolite concentration measurements improved by 72% for creatine and 40% for choline. We also compared STEAM-WET and PRESS-WSC in 13 patients with severe symptomatic aortic or mitral stenosis indicated for valve replacement surgery (10 males, three females; age 75.9 ± 6.3 years; BMI 27.4 ± 4.3 kg/m2 ). Spectra were of analysable quality in eight patients for STEAM-WET, and in nine for PRESS-WSC. We observed comparable lipid concentrations with those in healthy volunteers, significantly reduced creatine concentrations, and a trend towards decreased choline concentrations. We conclude that PRESS-WSC offers improved performance and reproducibility for the quantification of cardiac lipids, creatine and choline concentrations in healthy volunteers at 3 T. It also offers improved performance compared with STEAM-WET for detecting altered creatine and choline concentrations in patients with valve disease.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Design of Nuclear Magnetic Resonance Molecular Probes for Hyperpolarized Bioimaging

Nuclear hyperpolarization has emerged as a method to dramatically enhance the sensitivity of NMR spectroscopy. By application of this powerful tool, small molecules with stable isotopes have been used for highly sensitive biomedical molecular imaging. The recent development of molecular probes for hyperpolarized in vivo analysis has demonstrated the ability of this technique to provide unique metabolic and physiological information. This review presents a brief introduction of hyperpolarization technology, approaches to the rational design of molecular probes for hyperpolarized analysis, and examples of molecules that have met with success in vitro or in vivo.

Accumulation of Macromolecules in Idiopathic Normal Pressure Hydrocephalus

The clearance system in the brain is not completely understood. The aim of this study was to prove the presence of the “glymphatic system” in the human brain using magnetic resonance spectroscopy (MRS). Spectral data of the brain white matter were obtained from healthy volunteers and patients with hydrocephalic dementia and used to measure intracerebral metabolites, including macromolecules (MMs) and lipids. Data were transferred from the MRS scanners to a workstation, and metabolites were quantified with the spectrogram-based eddy current method and water scaling. MM levels were significantly higher in patients with a slow gait and executive dysfunction due to normal pressure hydrocephalus (NPH) than in asymptomatic volunteers (p <0.01). In contrast, the N-acetyl aspartate (NAA) level was significantly lower in patients with executive dysfunction than in asymptomatic volunteers (p <0.01). There were no statistically significant differences in metabolites, including alanine, aspartate, creatine, γ-amino butyric acid, D-glucose, glutamine, glutamate, glycerophosphorylcholine, phosphorylcholine, lactate, myoinositol, N-acetyl-aspartyl-glutamate, scyllo-inositol, taurine, creatine methylene, and guanine, in the centrum semiovale between patients with NPH and asymptomatic volunteers. We quantitatively evaluated cerebral metabolites, particularly in the centrum semiovale, with MRS. In the brain of patients with a slow gait and executive dysfunction due to NPH, MRS revealed significantly higher MM levels and lower NAA levels compared to healthy volunteers. Therefore, it may be concluded that the patients have a dysfunctional glymphatic system in the brain.

Radioresistance in Glioblastoma and the Development of Radiosensitizers

Ionizing radiation is a common and effective therapeutic option for the treatment of glioblastoma (GBM). Unfortunately, some GBMs are relatively radioresistant and patients have worse outcomes after radiation treatment. The mechanisms underlying intrinsic radioresistance in GBM has been rigorously investigated over the past several years, but the complex interaction of the cellular molecules and signaling pathways involved in radioresistance remains incompletely defined. A clinically effective radiosensitizer that overcomes radioresistance has yet to be identified. In this review, we discuss the current status of radiation treatment in GBM, including advances in imaging techniques that have facilitated more accurate diagnosis, and the identified mechanisms of GBM radioresistance. In addition, we provide a summary of the candidate GBM radiosensitizers being investigated, including an update of subjects enrolled in clinical trials. Overall, this review highlights the importance of understanding the mechanisms of GBM radioresistance to facilitate the development of effective radiosensitizers.

Robust Conditional Independence maps of single-voxel Magnetic Resonance Spectra to elucidate associations between brain tumours and metabolites

The aim of the paper is two-fold. First, we show that structure finding with the PC algorithm can be inherently unstable and requires further operational constraints in order to consistently obtain models that are faithful to the data. We propose a methodology to stabilise the structure finding process, minimising both false positive and false negative error rates. This is demonstrated with synthetic data. Second, to apply the proposed structure finding methodology to a data set comprising single-voxel Magnetic Resonance Spectra of normal brain and three classes of brain tumours, to elucidate the associations between brain tumour types and a range of observed metabolites that are known to be relevant for their characterisation. The data set is bootstrapped in order to maximise the robustness of feature selection for nominated target variables. Specifically, Conditional Independence maps (CI-maps) built from the data and their derived Bayesian networks have been used. A Directed Acyclic Graph (DAG) is built from CI-maps, being a major challenge the minimization of errors in the graph structure. This work presents empirical evidence on how to reduce false positive errors via the False Discovery Rate, and how to identify appropriate parameter settings to improve the False Negative Reduction. In addition, several node ordering policies are investigated that transform the graph into a DAG. The obtained results show that ordering nodes by strength of mutual information can recover a representative DAG in a reasonable time, although a more accurate graph can be recovered using a random order of samples at the expense of increasing the computation time.

2-D magnetic resonance spectroscopic imaging of the pediatric brain using compressed sensing

BACKGROUND

Magnetic resonance spectroscopic imaging helps to determine abnormal brain tissue conditions by evaluating metabolite concentrations. Although a powerful technique, it is underutilized in routine clinical studies because of its long scan times.

OBJECTIVE

In this study, we evaluated the feasibility of scan time reduction in metabolic imaging using compressed-sensing-based MR spectroscopic imaging in pediatric patients undergoing routine brain exams.

MATERIALS AND METHODS

We retrospectively evaluated compressed-sensing reconstructions in MR spectroscopic imaging datasets from 20 pediatric patients (11 males, 9 females; average age: 5.4±4.5 years; age range: 3 days to 16 years). We performed retrospective under-sampling of the MR spectroscopic imaging datasets to simulate accelerations of 2-, 3-, 4-, 5-, 7- and 10-fold, with subsequent reconstructions in MATLAB. Metabolite maps of N-acetylaspartate, creatine, choline and lactate (where applicable) were quantitatively evaluated in terms of the root-mean-square error (RMSE), peak amplitudes and total scan time. We used the two-tailed paired t-test along with linear regression analysis to statistically compare the compressed-sensing reconstructions at each acceleration with the fully sampled reference dataset.

RESULTS

High fidelity was maintained in the compressed-sensing MR spectroscopic imaging reconstructions from 50% to 80% under-sampling, with the RMSE not exceeding 3% in any dataset. Metabolite intensities and ratios evaluated on a voxel-by-voxel basis showed no statistically significant differences and mean metabolite intensities showed high correlation compared to the fully sampled reference dataset up to an acceleration factor of 5.

CONCLUSION

Compressed-sensing MR spectroscopic imaging has the potential to reduce MR spectroscopic imaging scan times for pediatric patients, with negligible information loss.

Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T₁ -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.

MR Spectroscopy of the Cervical Spinal Cord in Chronic Spinal Cord Injury

Purpose To investigate metabolic changes in chronic spinal cord injury (SCI) by applying MR spectroscopy in the cervical spinal cord. Materials and Methods Single-voxel short-echo spectroscopic data in study participants with chronic SCI and healthy control subjects were prospectively acquired in the cervical spinal cord at C2 above the level of injury between March 2016 and January 2017 and were compared between groups. Concentrations of total N-acetylaspartate (tNAA), myo-inositol (mI), total choline-containing compounds (tCho), creatine, and glutamine and glutamate complex were estimated from the acquired spectra. Participants were assessed with a comprehensive clinical evaluation investigating sensory and motor deficits. Correlation analysis was applied to investigate relationships between observed metabolic differences, lesion severity, and clinical outcome. Results There were 18 male study participants with chronic SCI (median age, 51 years; range, 30-68 years) and 11 male healthy control subjects (median age, 45 years; range, 30-67 years). At cervical level C2, tNAA/mI and tCho/mI ratios were lower in participants with SCI (tNAA/mI: -26%, P = .003; tCho/mI: -18%; P = .04) than in healthy control subjects. The magnitude of difference was greater with the severity of cord atrophy (tNAA/mI: R² = 0.44, P = .003; tCho/mI: R² = 0.166, P = .09). Smaller tissue bridges at the lesion site correlated with lower ratios of tNAA/mI (R² = 0.69, P = .006) and tCho/mI (R² = 0.51, P = .03) at the C2 level. Lower tNAA/mI and tCho/mI ratios were associated with worse sensory and motor outcomes (P < .05). Conclusion Supralesional metabolic alterations are observed in chronic spinal cord injury, likely reflecting neurodegeneration, demyelination, and astrocytic gliosis in the injured cervical cord. Lesion severity and greater clinical impairment are both linked to the biochemical changes in the atrophied cervical cord after spinal cord injury. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Lin in this issue.

Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumours

BACKGROUND

A tool for diagnosing childhood cerebellar tumours using magnetic resonance (MR) spectroscopy peak height measurement has been developed based on retrospective analysis of single-centre data.

OBJECTIVE

To determine the diagnostic accuracy of the peak height measurement tool in a multicentre prospective study, and optimise it by adding new prospective data to the original dataset.

MATERIALS AND METHODS

Magnetic resonance imaging (MRI) and single-voxel MR spectroscopy were performed on children with cerebellar tumours at three centres. Spectra were processed using standard scanner software and peak heights for N-acetyl aspartate, creatine, total choline and myo-inositol were measured. The original diagnostic tool was used to classify 26 new tumours as pilocytic astrocytoma, medulloblastoma or ependymoma. These spectra were subsequently combined with the original dataset to develop an optimised scheme from 53 tumours in total.

RESULTS

Of the pilocytic astrocytomas, medulloblastomas and ependymomas, 65.4% were correctly assigned using the original tool. An optimized scheme was produced from the combined dataset correctly assigning 90.6%. Rare tumour types showed distinctive MR spectroscopy features.

CONCLUSION

The original diagnostic tool gave modest accuracy when tested prospectively on multicentre data. Increasing the dataset provided a diagnostic tool based on MR spectroscopy peak height measurement with high levels of accuracy for multicentre data.

Amid proton transfer (APT) and magnetization transfer (MT) MRI contrasts provide complimentary assessment of brain tumors similarly to proton magnetic resonance spectroscopy imaging (MRSI)

OBJECTIVES

Using MRSI as comparison, we aimed to explore the difference between amide proton transfer (APT) MRI and conventional semi-solid magnetization transfer ratio (MTR) MRI, and to investigate if molecular APT and structural MTR can provide complimentary information in assessing brain tumors.

METHODS

Seventeen brain tumor patients and 17 age- and gender-matched volunteers were included and scanned with anatomical MRI, APT and MT-weighted MRI, and MRSI. Multi-voxel choline (Cho) and N-acetylaspartic acid (NAA) signals were quantified from MRSI and compared with MTR and MTR_asym(3.5ppm) contrasts averaged from corresponding voxels. Correlations between contrasts were explored voxel-by-voxel by pooling values from all voxels into Pearson's correlation analysis. Differences in correlation coefficients were tested with the Z-test (set at p<0.05).

RESULTS

APT and MT provide good contrast and quantitative parameters in tumor imaging, as do the metabolite (Cho and NAA) maps. MTR_asym(3.5ppm) significantly correlated with MTR (R=-0.61, p<0.0001), Cho (R=0.568, p<0.0001) and NAA (R=-0.619, p<0.0001) in tumors, and MTR also significantly correlated with Cho (R=-0.346, p<0.0001) and NAA (R=0.624, p<0.0001). In healthy volunteers, MTR_asym(3.5ppm) was non-significantly correlated with MTR (R=-0.049, p=0.239), Cho (R=0.030, p=0.478) and NAA (R=-0.083, p=0.046). Significant correlations were found among MTR with Cho (R=0.199, p<0.0001) and NAA (R=0.263, p<0.0001) in the group of healthy volunteers with lower correlation R values than those in tumor patients.

CONCLUSIONS

APT and MT could provide independent and supplementary information for the comprehensive assessment of molecular and structural changes due to brain tumor cancerogenesis.

KEY POINTS

• MTR _asym(3.5ppm) positively correlated with Cho while negatively with NAA in tumors. • MTR positively correlated with NAA while negatively with Cho in tumors. • Combining APT/MT provides molecular and structural information similarly to MRSI.

Conventional and advanced magnetic resonance imaging in patients with high-grade glioma

Magnetic resonance imaging is integral to the care of patients with high-grade gliomas. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic and molecular characteristics of central nervous system neoplasms. These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumor burden and therapy response. The following is an overview of current strategies based on advanced magnetic resonance imaging that are used in the assessment of high-grade glioma patients with an emphasis on how novel imaging biomarkers can potentially advance patient care.

Magnetic Resonance Spectroscopy and its Clinical Applications: A Review

In vivo NMR spectroscopy is known as magnetic resonance spectroscopy (MRS). MRS has been applied as both a research and a clinical tool in order to detect visible or nonvisible abnormalities. The adaptability of MRS allows a technique that can probe a wide variety of metabolic uses across different tissues. Although MRS is mostly applied for brain tissue, it can be used for detection, localization, staging, tumour aggressiveness evaluation, and tumour response assessment of breast, prostate, hepatic, and other cancers. In this article, the medical applications of MRS in the brain, including tumours, neural and psychiatric disorder studies, breast, prostate, hepatic, gastrointestinal, and genitourinary investigations have been reviewed.

Echo-planar spectroscopic imaging with dual-readout alternated gradients (DRAG-EPSI) at 7 T: Application for 2-hydroxyglutarate imaging in glioma patients

PURPOSE

To develop echo-planar spectroscopic imaging (EPSI) with large spectral width and accomplish high-resolution imaging of 2-hydroxyglutarate (2HG) at 7 T.

METHODS

We designed a new EPSI readout scheme at 7 T. Data were recorded with dual-readout alternated gradients and combined according to the gradient polarity. Following validation of its performance in phantoms, the new readout scheme, together with previously reported 2HG-optimized magnetic resonance spectroscopy (point-resolved spectroscopy echo time of 78 ms), was used for time-efficient and high-resolution imaging of 2HG and other metabolites in five glioma patients before treatment. Unsuppressed water, acquired with EPSI, was used as reference for multichannel combination, eddy-current compensation, and metabolite quantification. Spectral fitting was conducted with the LCModel using in-house calculated basis sets.

RESULTS

Using a readout gradient strength of 9.5 mT/m and slew rate of 90 mT/m/ms, dual-readout alternated gradients EPSI permitted 1638-Hz spectral width with 6 × 6 mm² in-plane resolution at 7 T. Phantom data indicated that dual-readout alternated gradients EPSI provides proper metabolite signals and induces much less frequency drifts than conventional EPSI. For a spatial resolution of 0.5 mL, 2HG was detected in tumors with precision (Cramer-Rao lower bound < 10%). The 2HG was estimated to be 2.3 to 3.3 mM in tumors of three patients with biopsy-proven isocitrate dehydrogenase (IDH) mutant gliomas. The 2HG was undetectable in an IDH wild-type glioblastoma. For a radiographically suggested glioma, the estimated 2HG of 2.3 ± 0.2 mM (Cramer-Rao lower bound < 10%) indicated that the lesion may be an IDH mutant glioma.

CONCLUSIONS

The data indicated that the dual-readout alternated gradients EPSI can provide reliable high-resolution imaging of 2HG in glioma patients at 7 T in vivo. Magn Reson Med 79:1851-1861, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Amide Proton Transfer Imaging Allows Detection of Glioma Grades and Tumor Proliferation: Comparison with Ki-67 Expression and Proton MR Spectroscopy Imaging

BACKGROUND AND PURPOSE

Prognosis in glioma depends strongly on tumor grade and proliferation. In this prospective study of patients with untreated primary cerebral gliomas, we investigated whether amide proton transfer-weighted imaging could reveal tumor proliferation and reliably distinguish low-grade from high-grade gliomas compared with Ki-67 expression and proton MR spectroscopy imaging.

MATERIALS AND METHODS

This study included 42 patients with low-grade (n = 28) or high-grade (n = 14) glioma, all of whom underwent conventional MR imaging, proton MR spectroscopy imaging, and amide proton transfer-weighted imaging on the same 3T scanner within 2 weeks before surgery. We assessed metabolites of choline and N-acetylaspartate from proton MR spectroscopy imaging and the asymmetric magnetization transfer ratio at 3.5 ppm from amide proton transfer-weighted imaging and compared them with histopathologic grade and immunohistochemical expression of the proliferation marker Ki-67 in the resected specimens.

RESULTS

The asymmetric magnetization transfer ratio at 3.5 ppm values measured by different readers showed good concordance and were significantly higher in high-grade gliomas than in low-grade gliomas (3.61% ± 0.155 versus 2.64% ± 0.185, P = .0016), with sensitivity and specificity values of 92.9% and 71.4%, respectively, at a cutoff value of 2.93%. The asymmetric magnetization transfer ratio at 3.5 ppm values correlated with tumor grade (r = 0.506, P = .0006) and Ki-67 labeling index (r = 0.502, P = .002). For all patients, the asymmetric magnetization transfer ratio at 3.5 ppm correlated positively with choline (r = 0.43, P = .009) and choline/N-acetylaspartate ratio (r = 0.42, P = .01) and negatively with N-acetylaspartate (r = -0.455, P = .005). These correlations held for patients with low-grade gliomas versus those with high-grade gliomas, but the correlation coefficients were higher in high-grade gliomas (choline: r = 0.547, P = .053; N-acetylaspartate: r = -0.644, P = .017; choline/N-acetylaspartate: r = 0.583, P = .036).

CONCLUSIONS

The asymmetric magnetization transfer ratio at 3.5 ppm may serve as a potential biomarker not only for assessing proliferation, but also for predicting histopathologic grades in gliomas.

Anaplastic astrocytoma mimicking progressive multifocal leucoencephalopathy: a case report and review of the overlapping syndromes

Background

Co-occurrence of multiple sclerosis (MS) and glial tumours (GT) is uncommon although occasionally reported in medical literature. Interpreting the overlapping radiologic and clinical characteristics of glial tumours, MS lesions, and progressive multifocal leukoencephalopathy (PML) can be a significant diagnostic challenge.

Case presentation

We report a case of anaplastic astrocytoma mimicking PML in a 27-year-old patient with a 15-year history of MS. She was treated with interferon, natalizumab and finally fingolimod due to active MS. Follow-up MRI, blood and cerebrospinal fluid examinations, and biopsy were conducted, but only the latter was able to reveal the cause of progressive worsening of patient’s disease.

Conclusions

Anaplastic astrocytoma misdiagnosed as PML has not yet been described. We suppose that the astrocytoma could have evolved from a low grade glioma to anaplastic astrocytoma over time, as the tumour developed adjacent to typical MS plaques. The role of the immunomodulatory treatment as well as other immunological factors in the malignant transformation can only be hypothesised. We discuss clinical, laboratory and diagnostic aspects of a malignant GT, MS lesions and PML. The diagnosis of malignant GT must be kept in mind when an atypical lesion develops in a patient with MS.

Edited 1 H magnetic resonance spectroscopy in vivo: Methods and metabolites

The Proton magnetic resonance (1 H-MRS) spectrum contains information about the concentration of tissue metabolites within a predefined region of interest (a voxel). The conventional spectrum in some cases obscures information about less abundant metabolites due to limited separation and complex splitting of the metabolite peaks. One method to detect these metabolites is to reduce the complexity of the spectrum using editing. This review provides an overview of the one-dimensional editing methods available to interrogate these obscured metabolite peaks. These methods include sequence optimizations, echo-time averaging, J-difference editing methods (single BASING, dual BASING, and MEGA-PRESS), constant-time PRESS, and multiple quantum filtering. It then provides an overview of the brain metabolites whose detection can benefit from one or more of these editing approaches, including ascorbic acid, γ-aminobutyric acid, lactate, aspartate, N-acetyl aspartyl glutamate, 2-hydroxyglutarate, glutathione, glutamate, glycine, and serine. Magn Reson Med 77:1377-1389, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Diagnostic value of 3.0T (1)H MRS with choline-containing compounds ratio (∆CCC) in primary malignant hepatic tumors

Background

The purpose of this study was to investigate the diagnostic value of 3.0-T ¹H magnetic resonance spectroscopy (¹H MRS) in primary malignant hepatic tumors and to compare the effects of ¹H MRS on the diagnostic accuracy of liver-occupying lesions between junior and experienced radiologists.

Methods

This study included 50 healthy volunteers and 40 consecutive patients (50 lesions). Informed consent was obtained from each subject. Images were obtained on clinical whole-body 3.0-T MR system. Point -Resolved Spectroscopy was used to obtain the spectroscopy image. All conventional images were reviewed blindly by junior radiologist and experienced radiologist, respectively. The choline-containing compounds peak area (CCC-A) was measured with SAGE software, and the choline-containing compound ratio (∆CCC) was calculated. The efficacy of CCC-A and ∆CCC in the diagnosis of primary malignant hepatic tumors was determined by plotting receiver operating characteristic (ROC) curves. We also compared the effects of MRS on the diagnostic accuracy of liver-occupying lesions with junior and experienced radiologist.

Results

A significant increase in mean CCC-A was observed in malignant tumors compared with benign tumors. The ROC curve showed ∆CCC had a high discriminatory ability in diagnosing primary malignant hepatic tumors with a sensitivity and specificity of 94.3 and 93.3 %, respectively. The ∆CCC area under the curve (AUC) was 0.97 that was larger than that of both junior and experienced radiologist, while the significantly statistical difference was only obtained between ∆CCC and junior radiologist (P = 0.01).

Conclusion

¹H MRS with ∆CCC demonstrates good efficacy in diagnosing primary malignant hepatic tumors. The technique improves the accuracy of diagnosing liver-occupying lesions, particularly for junior radiologists.

Detection of 2-hydroxyglutarate in brain tumors by triple-refocusing MR spectroscopy at 3T in vivo

PURPOSE

To test the efficacy of triple-refocusing MR spectroscopy (MRS) for improved detection of 2-hydroxyglutarate (2HG) in brain tumors at 3T in vivo.

METHODS

The triple-refocusing sequence parameters were tailored at 3T, with density-matrix simulations and phantom validation, for enhancing the 2HG 2.25-ppm signal selectivity with respect to the adjacent resonances of glutamate (Glu), glutamine (Gln), and gamma-aminobutyric acid (GABA). In vivo MRS data were acquired from 15 glioma patients and analyzed with LCModel using calculated basis spectra. Metabolites were quantified with reference to water.

RESULTS

A triple-refocusing sequence (echo time = 137 ms) was obtained for 2HG detection. The 2HG 2.25-ppm signal was large and narrow while the Glu and Gln signals between 2.2 and 2.3 ppm were minimal. The optimized triple refocusing offered improved separation of 2HG from Glu, Gln and GABA when compared with published MRS methods. 2HG was detected in all 15 patients, the estimated 2HG concentrations ranging from 2.4 to 15.0 mM, with Cramer-Rao lower bounds of 2%-11%. The 2HG estimates did not show significant correlation with total choline.

CONCLUSION

The optimized triple refocusing provides excellent 2HG signal discrimination from adjacent resonances and may confer reliable in vivo measurement of 2HG at relatively low concentrations. Magn Reson Med 78:40-48, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

The Use of Magnetic Resonance Spectroscopy in the Evaluation of Pediatric Patients With Seizures

BACKGROUND

The objective was to determine if it is useful to routinely add magnetic resonance spectroscopy (MRS) to magnetic resonance imaging (MRI) in the evaluation of seizure in the pediatric patient. Specifically, how often does MRS contribute information to conventional MRI?

METHODS

A retrospective search, over a period of 3 years, of patients <18 years of age who underwent both MRI and MRS as part of the evaluation of seizures yielded a total of 233 cases in 216 patients. The medical records were reviewed to determine how many patients carried a diagnosis relevant to seizures. The MRIs and MRSs were reviewed by two neuroradiologists and an MR physicist/spectroscopist who determined by consensus in how many cases MRS contributed information regarding management, diagnosis, or prognosis, in addition to the findings on MRI alone.

RESULTS

In 100 of 233 cases (43%), MRS contributed information additional to MRI. In 40 cases, MRS contributed information relevant to patient management by prompting an evaluation for an underlying inborn error of metabolism. MRS contributed information relevant to diagnosis in 24 of 100 cases (e.g., neoplasm versus dysplasia). MRS contributed information relevant to prognosis in 36 cases (e.g., hypoxic-ischemic injury). MRS added more information in cases where the patients had a diagnosis relevant to seizure before imaging. Interestingly, in 25 cases where the MRI was normal, MRS was found to be abnormal, which prompted evaluation for an inborn error of metabolism.

CONCLUSIONS

These results suggest that MRS is a useful evaluation tool in addition to MRI for children undergoing imaging for the evaluation of seizures.

Influence of macromolecule baseline on 1 H MR spectroscopic imaging reproducibility

Purpose

Poorly characterized macromolecular (MM) and baseline artefacts are known to reduce metabolite quantitation accuracy in ¹H MR spectroscopic imaging (MRSI). Increasing echo time (TE) and improvements in MM analysis schemes have both been proposed as strategies to improve metabolite measurement reliability. In this study, the influence of TE and two MM analysis schemes on MRSI reproducibility are investigated.

Methods

An experimentally acquired baseline was collected using an inversion recovery sequence (TI = 750 ms) and incorporated into the analysis method. Intrasubject reproducibility of MRSI scans, acquired at 3 Tesla, was assessed using metabolite coefficients of variance (COVs) for both experimentally acquired and simulated MM analysis schemes. In addition, the reproducibility of TE = 35 ms, 80 ms, and 144 ms was evaluated.

Results

TE = 80 ms was the most reproducible for singlet metabolites with COVs < 6% for total N‐acetyl‐aspartate, total creatine, and total choline; however, moderate multiplet dephasing was observed. Analysis incorporating the experimental baseline achieved higher Glu and Glx reproducibility at TE = 35 ms, and showed improvements over the simulated baseline, with higher efficacy for poorer data.

Conclusion

Overall, TE = 80 ms yielded the most reproducible singlet metabolite estimates. However, combined use of a short TE sequence and the experimental baseline may be preferred as a compromise between accuracy, multiplet dephasing, and T2 bias on metabolite estimates. Magn Reson Med 77:34–43, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Neuroimaging

Imaging is integral to the management of patients with brain tumors. Conventional structural imaging provides exquisite anatomic detail but remains limited in the evaluation of molecular characteristics of intracranial neoplasms. Quantitative and physiologic biomarkers derived from advanced imaging techniques have been increasingly utilized as problem-solving tools to identify glioma grade and assess response to therapy. This chapter provides a comprehensive overview of the imaging strategies used in the clinical assessment of patients with gliomas and describes how novel imaging biomarkers have the potential to improve patient management.

Magnetic resonance spectroscopy and imaging on fresh human brain tumor biopsies at microscopic resolution

The metabolic composition and concentration knowledge provided by magnetic resonance spectroscopy (MRS) liquid and high-resolution magic angle spinning spectroscopy (HR-MAS) has a relevant impact in clinical practice during magnetic resonance imaging (MRI) monitoring of human tumors. In addition, the combination of morphological and chemical information by MRI and MRS has been particularly useful for diagnosis and prognosis of tumor evolution. MRI spatial resolution reachable in human beings is limited for safety reasons and the demanding necessary conditions are only applicable on experimental model animals. Nevertheless, MRS and MRI can be performed on human biopsies at high spatial resolution, enough to allow a direct correlation between the chemical information and the histological features observed in such biopsies. Although HR-MAS is nowadays a well-established technique for spectroscopic analysis of tumor biopsies, with this approach just a mean metabolic profile of the whole sample can be obtained and thus the high histological heterogeneity of some important tumors is mostly neglected. The value of metabolic HR-MAS data strongly depends on a wide statistical analysis and usually the microanatomical rationale for the correlation between histology and spectroscopy is lost. We present here a different approach for the combined use of MRI and MRS on fresh human brain tumor biopsies with native contrast. This approach has been designed to achieve high spatial (18 × 18 × 50 μm) and spectral (0.031 μL) resolution in order to obtain as much spatially detailed morphological and metabolical information as possible without any previous treatment that can alter the sample. The preservation of native tissue conditions can provide information that can be translated to in vivo studies and additionally opens the possibility of performing other techniques to obtain complementary information from the same sample.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

Multidimensional texture characterization: on analysis for brain tumor tissues using MRS and MRI

This paper investigates the efficacy of automated pattern recognition methods on magnetic resonance data with the objective of assisting radiologists in the clinical diagnosis of brain tissue tumors. In this paper, the sciences of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) are combined to improve the accuracy of the classifier, based on the multidimensional co-occurrence matrices to assess the detection of pathological tissues (tumor and edema), normal tissues (white matter - WM and gray matter - GM), and fluid (cerebrospinal fluid - CSF). The results show the ability of the classifier with iterative training to automatically and simultaneously recover tissue-specific spectral and structural patterns and achieve segmentation of tumor and edema and grading of high and low glioma tumor. Here, extreme learning machine - improved particle swarm optimization (ELM-IPSO) neural network classifier is trained with the feature descriptions in brain magnetic resonance (MR) spectra. This has the characteristics of varying the normal spectral pattern associated with tumor patterns along with imaging features. Validation was performed considering 35 clinical studies. The volumetric features extracted from the vectors of this matrix articulate some important elementary structures, which along with spectroscopic metabolite ratios discriminate the tumor grades and tissue classes. The quantitative 3D analysis reveals significant improvement in terms of global accuracy rate for automatic classification in brain tissues and discriminating pathological tumor tissue from structural healthy brain tissue.

In situ drug and metabolite analysis [corrected] in biological and clinical research by MALDI MS imaging

In recent years the analysis in mass spectrometry (MS) [corrected] imaging has been expanded to detect a wide variety of low molecular weight compounds (LMWC), including exogenous and endogenous compounds. The high sensitivity and selectivity of MS imaging combined with visualization of molecular spatial distribution in tissues, makes it a valuable [corrected] platform in targeted drug and untargeted metabolomic analysis [corrected] in biological and clinical research. Here, we review the current and potential applications of MALDI MS imaging in these areas. The aim of advancing MALDI MS imaging in the field of LMWC is to support clinical applications by understanding drug and drug-metabolite distribution, investigating toxicity and discovering [corrected] new biomarkers.

Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering

PURPOSE

To investigate whether nonlinear dimensionality reduction improves unsupervised classification of (1) H MRS brain tumor data compared with a linear method.

METHODS

In vivo single-voxel (1) H magnetic resonance spectroscopy (55 patients) and (1) H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data.

RESULTS

An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With (1) H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC.

CONCLUSION

The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of (1) H MRSI data after cluster analysis.

Sensitivity encoding for fast (1) H MR spectroscopic imaging water reference acquisition

PURPOSE

Accurate and fast (1) H MR spectroscopic imaging (MRSI) water reference scans are important for absolute quantification of metabolites. However, the additional acquisition time required often precludes the water reference quantitation method for MRSI studies. Sensitivity encoding (SENSE) is a successful MR technique developed to reduce scan time. This study quantitatively assesses the accuracy of SENSE for water reference MRSI data acquisition, compared with the more commonly used reduced resolution technique.

METHODS

2D MRSI water reference data were collected from a phantom and three volunteers at 3 Tesla for full acquisition (306 s); 2× reduced resolution (64 s) and SENSE R = 3 (56 s) scans. Water amplitudes were extracted using MRS quantitation software (TARQUIN). Intensity maps and Bland-Altman statistics were generated to assess the accuracy of the fast-MRSI techniques.

RESULTS

The average mean and standard deviation of differences from the full acquisition were 2.1 ± 3.2% for SENSE and 10.3 ± 10.7% for the reduced resolution technique, demonstrating that SENSE acquisition is approximately three times more accurate than the reduced resolution technique.

CONCLUSION

SENSE was shown to accurately reconstruct water reference data for the purposes of in vivo absolute metabolite quantification, offering significant improvement over the more commonly used reduced resolution technique.

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.

Relative metabolite concentrations and ratios determined by use of 3-T region-specific proton magnetic resonance spectroscopy of the brain of healthy Beagles

OBJECTIVE

To determine relative concentrations of selected major brain tissue metabolites and their ratios and lobar variations by use of 3-T proton (hydrogen 1 [(1)H]) magnetic resonance spectroscopy (MRS) of the brain of healthy dogs.

ANIMALS

10 healthy Beagles.

PROCEDURES

3-T (1)H MRS at echo times of 144 and 35 milliseconds was performed on 5 transverse slices and 1 sagittal slice of representative brain lobe regions. Intravoxel parenchyma was classified as white matter, gray matter, or mixed (gray and white) and analyzed for relative concentrations (in arbitrary units) of N-acetylaspartate (NAA), choline, and creatine (ie, height at position of peak on MRS graph) as well as their ratios (NAA-to-choline, NAA-to-creatine, and choline-to-creatine ratios). Peak heights for metabolites were compared between echo times. Peak heights for metabolites and their ratios were correlated and evaluated among matter types. Yield was calculated as interpretable voxels divided by available lobar voxels.

RESULTS

Reference ranges of the metabolite concentration ratios were determined at an echo time of 35 milliseconds (NAA-to-choline ratio, 1.055 to 2.224; NAA-to-creatine ratio, 1.103 to 2.161; choline-to-creatine ratio, 0.759 to 1.332) and 144 milliseconds (NAA-to-choline ratio, 0.687 to 1.788; NAA-to-creatine ratio, 0.984 to 2.044; choline-to-creatine ratio, 0.828 to 1.853). Metabolite concentration ratios were greater in white matter than in gray matter. Voxel yields ranged from 43% for the temporal lobe to 100% for the thalamus.

CONCLUSIONS AND CLINICAL RELEVANCE

Metabolite concentrations and concentration ratios determined with 3-T (1)H MRS were not identical to those in humans and were determined for clinical and research investigations of canine brain disease.

An introduction to molecular imaging in radiation oncology: a report by the AAPM Working Group on Molecular Imaging in Radiation Oncology (WGMIR)

Molecular imaging is the direct or indirect noninvasive monitoring and recording of the spatial and temporal distribution of in vivo molecular, genetic, and/or cellular processes for biochemical, biological, diagnostic, or therapeutic applications. Molecular images that indicate the presence of malignancy can be acquired using optical, ultrasonic, radiologic, radionuclide, and magnetic resonance techniques. For the radiation oncology physicist in particular, these methods and their roles in molecular imaging of oncologic processes are reviewed with respect to their physical bases and imaging characteristics, including signal intensity, spatial scale, and spatial resolution. Relevant molecular terminology is defined as an educational assist. Current and future clinical applications in oncologic diagnosis and treatment are discussed. National initiatives for the development of basic science and clinical molecular imaging techniques and expertise are reviewed, illustrating research opportunities in as well as the importance of this growing field.

A novel semi-supervised methodology for extracting tumor type-specific MRS sources in human brain data

Background

The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal.

Methodology/Principal Findings

Non-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification.

Conclusions/Significance

We show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing.

Randomized pilot study and qualitative evaluation of a clinical decision support system for brain tumour diagnosis based on SV ¹H MRS: evaluation as an additional information procedure for novice radiologists

The results of a randomized pilot study and qualitative evaluation of the clinical decision support system Curiam BT are reported. We evaluated the system's feasibility and potential value as a radiological information procedure complementary to magnetic resonance (MR) imaging to assist novice radiologists in diagnosing brain tumours using MR spectroscopy (1.5 and 3.0T). Fifty-five cases were analysed at three hospitals according to four non-exclusive diagnostic questions. Our results show that Curiam BT improved the diagnostic accuracy in all the four questions. Additionally, we discuss the findings of the users' feedback about the system, and the further work to optimize it for real environments and to conduct a large clinical trial.

Differentiating diffuse World Health Organization grade II and IV astrocytomas with ex vivo magnetic resonance spectroscopy

BACKGROUND

The prognosis and treatment of astrocytomas, which are primary brain tumors, vary depending on the grade of the tumor, necessitating a precise preoperative classification. Magnetic resonance spectroscopy (MRS) provides information about metabolites in tissues and is an emerging noninvasive tool to improve diagnostic accuracy in patients with intracranial neoplasia.

OBJECTIVE

To investigate whether ex vivo MRS could differentiate World Health Organization grade II (A-II) and IV astrocytomas (glioblastomas; GBM) and to correlate MR spectral profiles with clinical parameters.

METHODS

Patients with A-II and GBM (n = 58) scheduled for surgical resection were enrolled. Tumor specimens were collected during surgery and stored in liquid nitrogen before being analyzed with high-resolution magic angle spinning MRS. The tumors were histopathologically classified according to World Health Organization criteria as GBM (n = 48) and A-II (n = 10).

RESULTS

Multivariate analysis of ex vivo proton high-resolution magic angle spinning spectra MRS showed differences in the metabolic profiles of different grades of astrocytomas. A-II had higher levels of glycerophosphocholine and myo-inositol than GBM. The latter had more phosphocholine, glycine, and lipids. We observed a significant metabolic difference between recurrent and nonrecurrent GBM (P < .001). Primary GBM had more phosphocholine than recurrent GBM. A significant correlation (P < .001) between lipid and lactate signals and histologically estimated percentage of necrosis was observed in GBM. Spectral profiles were not correlated with age, survival, or magnetic resonance imaging-defined tumor volume.

CONCLUSION

Ex vivo MRS can differentiate astrocytomas based on their metabolic profiles.

Metabolic profiles of brain metastases

Metastasis to the brain is a feared complication of systemic cancer, associated with significant morbidity and poor prognosis. A better understanding of the tumor metabolism might help us meet the challenges in controlling brain metastases. The study aims to characterize the metabolic profile of brain metastases of different origin using high resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) to correlate the metabolic profiles to clinical and pathological information. Biopsy samples of human brain metastases (n = 49) were investigated. A significant correlation between lipid signals and necrosis in brain metastases was observed (p < 0.01), irrespective of their primary origin. The principal component analysis (PCA) showed that brain metastases from malignant melanomas cluster together, while lung carcinomas were metabolically heterogeneous and overlap with other subtypes. Metastatic melanomas have higher amounts of glycerophosphocholine than other brain metastases. A significant correlation between microscopically visible lipid droplets estimated by Nile Red staining and MR visible lipid signals was observed in metastatic lung carcinomas (p = 0.01), indicating that the proton MR visible lipid signals arise from cytoplasmic lipid droplets. MRS-based metabolomic profiling is a useful tool for exploring the metabolic profiles of metastatic brain tumors.