Metabolite quantification and high-field MRS in breast cancer

Noise suppression of proton magnetic resonance spectroscopy improves paediatric brain tumour classification

Proton magnetic resonance spectroscopy (1H-MRS) is increasingly used for clinical brain tumour diagnosis, but suffers from limited spectral quality. This retrospective and comparative study aims at improving paediatric brain tumour classification by performing noise suppression on clinical 1H-MRS. Eighty-three/forty-two children with either an ependymoma (ages 4.6 ± 5.3/9.3 ± 5.4), a medulloblastoma (ages 6.9 ± 3.5/6.5 ± 4.4), or a pilocytic astrocytoma (8.0 ± 3.6/6.3 ± 5.0), recruited from four centres across England, were scanned with 1.5T/3T short-echo-time point-resolved spectroscopy. The acquired raw 1H-MRS was quantified by using Totally Automatic Robust Quantitation in NMR (TARQUIN), assessed by experienced spectroscopists, and processed with adaptive wavelet noise suppression (AWNS). Metabolite concentrations were extracted as features, selected based on multiclass receiver operating characteristics, and finally used for identifying brain tumour types with supervised machine learning. The minority class was oversampled through the synthetic minority oversampling technique for comparison purposes. Post-noise-suppression 1H-MRS showed significantly elevated signal-to-noise ratios (P < .05, Wilcoxon signed-rank test), stable full width at half-maximum (P > .05, Wilcoxon signed-rank test), and significantly higher classification accuracy (P < .05, Wilcoxon signed-rank test). Specifically, the cross-validated overall and balanced classification accuracies can be improved from 81% to 88% overall and 76% to 86% balanced for the 1.5T cohort, whilst for the 3T cohort they can be improved from 62% to 76% overall and 46% to 56%, by applying Naïve Bayes on the oversampled 1H-MRS. The study shows that fitting-based signal-to-noise ratios of clinical 1H-MRS can be significantly improved by using AWNS with insignificantly altered line width, and the post-noise-suppression 1H-MRS may have better diagnostic performance for paediatric brain tumours.

Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal-to-noise ratio and speed of MRS

BACKGROUND

While magnetic resonance imaging (MRI) provides high resolution anatomical images with sharp soft tissue contrast, magnetic resonance spectroscopy (MRS) enables non-invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal-to-noise ratio (SNR) when concentrations of metabolites are in the range of millimolar. Standard approach of using a high number of signal averaging (NSA) to achieve sufficient SNR comes at the cost of a long acquisition time.

PURPOSE

We propose to use deep-learning approaches to denoise MRS data without increasing NSA. This method has potential to reduce the acquisition time as well as improve SNR and quality of spectra, which could enhance the diagnostic value and broaden the clinical applications of MRS.

METHODS

The study was conducted using data collected from the brain spectroscopy phantom and human subjects. We utilized a stack auto-encoder (SAE) network to train deep learning models for denoising low NSA data (NSA = 1, 2, 4, 8, and 16) randomly truncated from high SNR data collected with high NSA (NSA = 192), which were also used to obtain the ground truth. We applied both self-supervised and fully-supervised training approaches and compared their performance of denoising low NSA data based on improvement in SNR. To prevent overfitting, the SAE network was trained in a patch-based manner. We then tested the denoising methods on noise-containing data collected from the phantom and human subjects, including data from brain tumor patients. We evaluated their performance by comparing the SNR levels and mean squared errors (MSEs) calculated for the whole spectra against high SNR "ground truth", as well as the value of chemical shift of N-acetyl-aspartate (NAA) before and after denoising.

RESULTS

With the SAE model, the SNR of low NSA data (NSA = 1) obtained from the phantom increased by 28.5% and the MSE decreased by 42.9%. For low NSA data of the human parietal and temporal lobes, the SNR increased by 32.9% and the MSE decreased by 63.1%. In all cases, the chemical shift of NAA in the denoised spectra closely matched with the high SNR spectra without significant distortion to the spectra after denoising. Furthermore, the denoising performance of the SAE model was more effective in denoising spectra with higher noise levels.

CONCLUSIONS

The reported SAE denoising method is a model-free approach to enhance the SNR of MRS data collected with low NSA. With the denoising capability, it is possible to acquire MRS data with a few NSA, shortening the scan time while maintaining adequate spectroscopic information for detecting and quantifying the metabolites of interest. This approach has the potential to improve the efficiency and effectiveness of clinical MRS data acquisition by reducing the scan time and increasing the quality of spectroscopic data.

A multimodal pipeline using NMR spectroscopy and MALDI-TOF mass spectrometry imaging from the same tissue sample

NMR spectroscopy and matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) are both commonly used to detect large numbers of metabolites and lipids in metabolomic and lipidomic studies. We have demonstrated a new workflow, highlighting the benefits of both techniques to obtain metabolomic and lipidomic data, which has realized for the first time the combination of these two complementary and powerful technologies. NMR spectroscopy is frequently used to obtain quantitative metabolite information from cells and tissues. Lipid detection is also possible with NMR spectroscopy, with changes being visible across entire classes of molecules. Meanwhile, MALDI MSI provides relative measures of metabolite and lipid concentrations, mapping spatial information of many specific metabolite and lipid molecules across cells or tissues. We have used these two complementary techniques in combination to obtain metabolomic and lipidomic measurements from triple-negative human breast cancer cells and tumor xenograft models. We have emphasized critical experimental procedures that ensured the success of achieving NMR spectroscopy and MALDI MSI in a combined workflow from the same sample. Our data show that several phospholipid metabolite species were differentially distributed in viable and necrotic regions of breast tumor xenografts. This study emphasizes the power of combined NMR spectroscopy-MALDI imaging to advance metabolomic and lipidomic studies.

Cortical GABA levels are reduced in young adult binge drinkers: Association with recent alcohol consumption and sex

Binge drinking refers to a pattern of alcohol intake that raises blood alcohol concentration to or above legal intoxication levels. It is common among young adults and is associated with health risks that scale up with alcohol intake. Acute intoxication depresses neural activity via complex signaling mechanisms by enhancing inhibition mediated by gamma-amino butyric acid (GABA), and by decreasing excitatory glutamatergic effects. Evidence primarily rooted in animal research indicates that the brain compensates for the acute depressant effects under the conditions of habitual heavy use. These neuroadaptive changes are reflected in neural hyperexcitability via downregulated inhibitory signaling, which becomes apparent as withdrawal symptoms. However, human evidence on the compensatory reduction in GABA signaling is scant. The neurochemical aspect of this mechanistic model was evaluated in the present study with proton magnetic resonance spectroscopy (¹H-MRS) which is sensitive to GABA plus macromolecule signal (GABA + ). Furthermore, we examined sex differences in GABA + levels as a function of a recent history of binge drinking, given interactions between endogenous neurosteroids, GABA signaling, and alcohol. The study recruited young adult women and men (22.2 ± 2.8 years of age) who were classified as binge drinkers (BDs, N = 52) if they reported ≥ 5 binge episodes in the previous six months. Light drinkers (LDs, N = 49) reported drinking regularly, but not exceeding ≤ 2 binge episodes in the past six months. GABA-edited ¹H-MR spectra were acquired from the occipital cortex at 3 T with the MEGA-PRESS sequence. GABA + signal was analyzed relative to water and total creatine (Cr) levels as a function of binge drinking history and sex. Controlling for within-voxel tissue composition, both GABA + indices showed decreased GABA + levels in BDs relative to LDs. The reduced GABA + concentration was associated with occasional high-intensity drinking in the BD group. This evidence is consistent with compensatory GABA downregulation that accompanies alcohol misuse, tipping the excitation/inhibition balance towards hyperexcitability. Analysis of the time course of GABA + neuroplasticity indicated that GABA + was lowest when measured one day after the last drinking occasion in BDs. While the BD vs LD differences were primarily driven by LD women, there was no interaction between Sex and a history of binge drinking. GABA + was higher in LD women compared to LD men. Aligned with the allostasis model, the mechanistic compensatory GABA downregulation observed in young emerging adults engaging in occasional binge drinking complements direct neural measures of hyperexcitability in BDs. Notably, these results suggest that neuroadaptation to alcohol is detectable at the levels of consumption that are within a normative range, and may contribute to adverse health outcomes.

Is Elevated Choline on Magnetic Resonance Spectroscopy a Reliable Marker of Breast Lesion Malignancy?

Background

Contemporary magnetic resonance imaging (MRI) of the breast represents a powerful diagnostic modality for cancer detection, with excellent sensitivity and high specificity. Magnetic resonance spectroscopy (MRS) is being explored as an additional tool for improving specificity in breast cancer detection, using multiparametric MRI. The aim of this study was to examine the possibility of 1H-MRS to discriminate malignant from benign breast lesions, using elevated choline (Cho) peak as an imaging biomarker.

Methods

A total of 60 patients were included in this prospective study: 30 with malignant (average age, 55.2 years; average lesion size, 35 mm) and 30 with benign breast lesions (average age, 44.8 years; average lesion size, 20 mm), who underwent multiparametric MRI with multivoxel 3D ¹H-MRS on a 1.5-T scanner in a 3-year period. Three patients with benign breast lesions were excluded from the study. All lesions were histologically verified. Peaks identified on ¹H-MRS were lipid (0.9, 2.3, 2.8, and 5.2 ppm), choline (3.2 ppm), and water peaks (4.7 ppm). Sensitivity and specificity, as well as positive and negative predictive values, were defined using ROC curves. Cohen's Kappa test of inter-test reliability was performed [testing the agreement between ¹H-MRS and histologic finding, and ¹H-MRS and MR mammography (MRM)].

Results

Choline peak was elevated in 24/30 malignant lesions and in 20/27 benign breast lesions. The sensitivity of ¹H-MRS was 0.8, specificity was 0.741, positive predictive value was 0.774, and negative predictive value was 0.769. Area under ROC was 0.77 (CI 0.640-0.871). Inter-test reliability between ¹H-MRS and histologic finding was 0.543 (moderate agreement) and that between ¹H-MRS and MRM was 0.573 (moderate agreement). False-negative findings were most frequently observed in invasive lobular cancers, while false-positive findings were most frequently observed in adenoid fibroadenomas.

Conclusion

Although elevation of the choline peak has a good sensitivity and specificity in breast cancer detection, both are significantly lower than those of multiparametric MRM. Inclusion of spectra located on tumor margins as well as analysis of lipid peaks could aid both sensitivity and specificity. An important ratio of false-positive and false-negative findings in specific types of breast lesions (lobular cancer and adenoid fibroadenoma) suggests interpreting these lesions with a caveat.

1H MR Spectroscopy of Fine-Needle Aspiration Biopsy Specimens for the Discrimination of Breast Cancer

Purpose

To determine whether MR spectroscopic assessment of fine-needle aspiration (FNA) biopsy specimens from suspicious breast lesions could be used to improve the diagnostic utility of FNA biopsies for the characterization of breast lesions.

Materials and Methods

In this prospective study, a previously reported technique using high-spatial-resolution proton MR spectroscopy was modified and used to examine the utility of FNA biopsies in the evaluation of suspicious breast lesions. Tissue samples from 115 lesions (from 102 women; average age, 54 years) were excised by using FNA and core biopsies and were collected between September 7, 2012, and April 11, 2014. Histologic results from core biopsy specimens determined the lesions to be benign (n = 55), invasive ductal carcinoma (n = 51), invasive lobular carcinoma (n = 5), or ductal carcinoma in situ (n = 4). Measures of phosphocholine (PC), glycerophosphocholine, and choline relative to each other and to total creatine (tCr) were obtained from usable spectra. Planned comparisons among lesion groups were carried out using t test contrasts, and differences of each contrast level from zero were judged significant when the two-tailed P value was less than .05.

Results

Of the 115 samples, 69 (60%) yielded no usable MR spectra. Analysis of the 46 with usable spectra found that only the difference in PC/tCr between benign and cancer lesions was statistically significant (P = .028).

Conclusion

Given that 60% of FNA biopsy specimens yielded no usable spectra and that results were largely inconclusive when derived from usable spectra, the combined MR and FNA technique, as modified and implemented in this study, is of little value for detection and diagnosis of breast cancer.Keywords: Breast, MR-Spectroscopy, Neoplasms-Primary© RSNA, 2020.

Clinical relevance of total choline (tCho) quantification in suspicious lesions on multiparametric breast MRI

Purpose

To assess the additional value of quantitative tCho evaluation to diagnose malignancy and lymph node metastases in suspicious lesions on multiparametric breast MRI (mpMRI, BI-RADS 4, and BI-RADS 5).

Methods

One hundred twenty-one patients that demonstrated suspicious multiparametric breast MRI lesions using DCE, T2w, and diffusion-weighted (DW) images were prospectively enrolled in this IRB-approved study. All underwent single-voxel proton MR spectroscopy (¹H-MRS, point-resolved spectroscopy sequence, TR 2000 ms, TE 272 ms) with and without water suppression. The total choline (tCho) amplitude was measured and normalized to millimoles/liter according to established methodology by two independent readers (R1, R2). ROC-analysis was employed to predict malignancy and lymph node status by tCho results.

Results

One hundred three patients with 74 malignant and 29 benign lesions had full ¹H-MRS data. The area under the ROC curve (AUC) for prediction of malignancy was 0.816 (R1) and 0.809 (R2). A cutoff of 0.8 mmol/l tCho could diagnose malignancy with a sensitivity of > 95%. For prediction of lymph node metastases, tCho measurements achieved an AUC of 0.760 (R1) and 0.788 (R2). At tCho levels < 2.4 mmol/l, no metastatic lymph nodes were found.

Conclusion

Quantitative tCho evaluation from ¹H-MRS allowed diagnose malignancy and lymph node status in breast lesions suspicious on multiparametric breast MRI. tCho therefore demonstrated the potential to downgrade suspicious mpMRI lesions and stratify the risk of lymph node metastases for improved patient management.

Key Points

• Quantitative tCho evaluation can distinguish benign from malignant breast lesions suspicious after multiparametric MRI assessment.

• Quantitative tCho levels are associated with lymph node status in breast cancer.

• Quantitative tCho levels are higher in hormonal receptor positive compared to hormonal receptor negative lesions.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-06678-z) contains supplementary material, which is available to authorized users.

Analyzing acoustoelastic effect of shear wave elastography data for perfused and hydrated soft tissues using a macromolecular network inspired model

Shear wave elastography (SWE) has enhanced our ability to non-invasively make in vivo measurements of tissue elastic properties of animal and human tissues. Recently, researchers have taken advantages of acoustoelasticity in SWE to extract nonlinear elastic properties from soft biological tissues. However, most investigations of the acoustoelastic effects of SWE data (AE-SWE) rely on classic hyperelastic models for rubber-like (dry) materials. In this paper, we focus solely on understanding acoustoelasticity in soft hydrated tissues using SWE data and propose a straightforward approach to modeling the constitutive behavior of soft tissue that has a direct microstructural/macromolecular interpretation. Our approach incorporates two constitutive features relevant to biological tissues into AE-SWE: static dilation of the medium associated with nonstructural components (e.g. tissue hydration and perfusion) and finite extensibility derived from an ideal network of biological filaments. We evaluated the proposed method using data from an in-house tissue-mimicking phantom experiment, and ex vivo and in vivo AE-SWE data available in the SWE literature. In conclusion, predictions made by our approach agreed well with measurements obtained from phantom, ex vivo and in vivo tissue experiments.

Application of in vivo MR methods in the study of breast cancer metabolism

In the last two decades, various in vivo MR methodologies have been evaluated for their potential in the study of cancer metabolism. During malignant transformation, metabolic alterations occur, leading to morphological and functional changes. Among various MR methods, in vivo MRS has been extensively used in breast cancer to study the metabolism of cells, tissues or whole organs. It provides biochemical information at the metabolite level. Altered choline, phospholipid and energy metabolism has been documented using proton (¹ H), phosphorus (³¹ P) and carbon (¹³ C) isotopes. Increased levels of choline-containing compounds, phosphomonoesters and phosphodiesters in breast cancer, which are indicative of altered choline and phospholipid metabolism, have been reported using in vivo, in vitro and ex vivo NMR studies. These changes are reversed on successful therapy, which depends on the treatment regimen given. Monitoring the various tumor intermediary metabolic pathways using nuclear spin hyperpolarization of ¹³ C-labeled substrates by dynamic nuclear polarization has also been recently reported. Furthermore, the utility of various methods such as diffusion, dynamic contrast and perfusion MRI have also been evaluated to study breast tumor metabolism. Parameters such as tumor volume, apparent diffusion coefficient, volume transfer coefficient and extracellular volume ratio are estimated. These parameters provide information on the changes in tumor microstructure, microenvironment, abnormal vasculature, permeability and grade of the tumor. Such changes seen during cancer progression are due to alterations in the tumor metabolism, leading to changes in cell architecture. Due to architectural changes, the tissue mechanical properties are altered; this can be studied using magnetic resonance elastography, which measures the elastic properties of tissues. Moreover, these structural MRI methods can be used to investigate the effect of therapy-induced changes in tumor characteristics. This review discusses the potential of various in vivo MR methodologies in the study of breast cancer metabolism.

In vivo MR spectroscopy for breast cancer diagnosis

Breast cancer is a significant health concern in females, worldwide. In vivo proton (1H) MR spectroscopy (MRS) has evolved as a non-invasive tool for diagnosis and for biochemical characterization of breast cancer. Water-to-fat ratio, fat and water fractions and choline containing compounds (tCho) have been identified as diagnostic biomarkers of malignancy. Detection of tCho in normal breast tissue of volunteers and in lactating females limits the use of tCho as a diagnostic marker. Technological developments like high-field scanners, multi channel coils, pulse sequences with water and fat suppression facilitated easy detection of tCho. Also, quantification of tCho and its cut-off for objective assessment of malignancy have been reported. Meta-analysis of in vivo 1H MRS studies have documented the pooled sensitivities and the specificities in the range of 71-74% and 78-88%, respectively. Inclusion of MRS has been shown to enhance the diagnostic specificity of MRI, however, detection of tCho in small sized lesions (≤1 cm) is challenging even at high magnetic fields. Potential of MRS in monitoring the effect of chemotherapy in breast cancer has also been reported. This review briefly presents the potential clinical role of in vivo 1H MRS in the diagnosis of breast cancer, its current status and future developments.

Role of diffusion weighted imaging and magnetic resonance spectroscopy in breast cancer patients with indeterminate dynamic contrast enhanced magnetic resonance imaging findings

PURPOSE

Dynamic contrast enhanced MRI (DCEMRI), diffusion weighted imaging (DWI) and in vivo proton (¹H) magnetic resonance spectroscopy (MRS) provides functional and molecular nature of breast cancer. This study evaluates the potential of the combination of three MR parameters [curve kinetics, apparent diffusion coefficient (ADC) and total choline (tCho) concentration] determined from these techniques in increasing the sensitivity of breast cancer detection.

METHODS

MR investigations were carried out at 1.5 T on 56 patients with cytologically/histologically confirmed breast carcinoma. Single-voxel MRS was used to determine the tCho concentration. 3D FLASH was used for DCEMRI while single shot EPI based DWI was used for ADC determination.

RESULTS

On DCEMRI, one patient showed type I curve, while 8 showed type II and 47 showed type III curve thus giving a sensitivity of 83.9% as detection rate of malignancy. tCho concentration was above cut-off value (2.54 mmol/kg) for 50/56 cases giving a sensitivity of 89.3%. Among 9 indeterminate DCEMRI cases, tCho showed malignancy in 6 cases with type II curve. DWI detected malignancy in 54/56 cases that included 9 cases that were false negative on DCEMRI, yielding a sensitivity of 96.4%. A total of 54 cases showed malignancy when any two of the three MR parameters was positive for malignancy yielding a sensitivity of 96.4% while it increased to 100% when any one parameters showed positive result.

CONCLUSION

DWI showed highest sensitivity of detection compared to DCEMRI and MRS. Multi-parametric approach yielded 96.4% and 100% sensitivity when any two or one of the three parameters was taken as positive for malignancy, respectively. Also the results demonstrated that addition of DWI and MRS play a significant role in establishing the final diagnosis of malignancy, especially in cases where DCEMRI is indeterminate.

Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning

Multicellular spheroids (hereinafter referred to as spheroids) are 3D biological models. The metabolomic profiles inside spheroids provide crucial information reflecting the molecular phenotypes and microenvironment of cells. To study the influence of an anticancer drug on the spatially resolved metabolites, spheroids were cultured using HCT-116 colorectal cancer cells, treated with the anticancer drug Irinotecan under a series of time- and concentration-dependent conditions. The Single-probe mass spectrometry imaging (MSI) technique was utilized to conduct the experiments. The MSI data were analyzed using advanced data analysis methods to efficiently extract metabolomic information. Multivariate curve resolution alternating least square (MCR-ALS) was used to decompose each MS image into different components with grouped species. To improve the efficiency of data analysis, both supervised (Random Forest) and unsupervised (cluster large applications (CLARA)) machine learning (ML) methods were employed to cluster MS images according to their metabolomic features. Our results indicate that anticancer drug significantly affected the abundances of a variety of metabolites in different regions of spheroids. This integrated experiment and data analysis approach can facilitate the studies of metabolites in different types of 3D tumor models and tissues and potentially benefit the drug discovery, therapeutic resistance, and other biological research fields.

Application of Imaging Technologies in Breast Cancer Detection: A Review Article

One of the techniques utilised in the management of cancer in all stages is multiple biomedical imaging. Imaging as an important part of cancer clinical protocols can provide a variety of information about morphology, structure, metabolism and functions. Application of imaging technics together with other investigative apparatus including in fluids analysis and vitro tissue would help clinical decision-making. Mixed imaging techniques can provide supplementary information used to improve staging and therapy planning. Imaging aimed to find minimally invasive therapy to make better results and reduce side effects. Probably, the most important factor in reducing mortality of certain cancers is an early diagnosis of cancer via screening based on imaging. The most common cancer in women is breast cancer. It is considered as the second major cause of cancer deaths in females, and therefore it remained as an important medical and socio-economic issue. Medical imaging has always formed part of breast cancer care and has used in all phases of cancer management from detection and staging to therapy monitoring and post-therapeutic follow-up. An essential action to be performed in the preoperative staging of breast cancer based on breast imaging. The general term of breast imaging refers to breast sonography, mammography, and magnetic resonance tomography (MRT) of the breast (magnetic resonance mammography, MRM).

Further development in technology will lead to increase imaging speed to meet physiological processes requirements. One of the issues in the diagnosis of breast cancer is sensitivity limitation. To overcome this limitation, complementary imaging examinations are utilised that traditionally includes screening ultrasound, and combined mammography and ultrasound. Development in targeted imaging and therapeutic agents calls for close cooperation among academic environment and industries such as biotechnological, IT and pharmaceutical industries.

Changes in total choline concentration in the breast of healthy fertile young women in relation to menstrual cycle or use of oral contraceptives: a 3-T 1H-MRS study

Background

To evaluate changes in total choline (tCho) absolute concentration ([tCho]) in the breast of healthy fertile women in relation to menstrual cycle (MC) or use of oral contraceptives (OC).

Methods

After institutional review board approval, we prospectively evaluated 40 healthy fertile volunteers: 20 with physiological MC, aged 28 ± 3 years (mean ± standard deviation; nOC group); 20 using OC, aged 26 ± 3 years (OC group). Hormonal assays and water-suppressed single-voxel 3-T proton magnetic resonance spectroscopy (¹H-MRS) were performed on MC days 7, 14, and 21 in the nOC group and only on MC day 14 in the OC group. [tCho] was measured versus an external phantom. Mann-Whitney U test and Spearman coefficient were used; data are given as median and interquartile interval.

Results

All spectra had good quality. In the nOC group, [tCho] (mM) did not change significantly during MC: 0.8 (0.3–2.4) on day 7, 0.9 (0.4–1.2) on day 14, and 0.4 (0.2–0.8) on day 21 (p = 0.963). In the OC group, [tCho] was 0.7 (0.2–1.7) mM. The between-groups difference was not significant on all days (p ≥ 0.411). All hormones except prolactin changed during MC (p ≤ 0.024). In the OC group, [tCho] showed a borderline correlation with estradiol (r = 0.458, p = 0.056), but no correlation with other hormones (p ≥ 0.128). In the nOC group, [tCho] negatively correlated with prolactin (r = -0.587, p = 0.006) on day 7; positive correlation was found with estradiol on day 14 (r = 0.679, p = 0.001).

Conclusions

A tCho peak can be detected in the normal mammary gland using 3-T ¹H-MRS. The [tCho] in healthy volunteers was 0.4–0.9 mM, constant over the MC and independent of OC use.

Imaging Cancer Metabolism

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

Magnetic Resonance Spectroscopy Studies of Mouse Models of Cancer

Magnetic resonance spectroscopy (MRS) or spectroscopic imaging (MRSI) enables the detection of metabolites, amino acids, and lipids, among other biomolecules, in tumors of live mouse models of cancer. Tumor-bearing mice are anesthetized by breathing isoflurane in a magnetic resonance (MR) scanner dedicated to small animal MR. Here we describe the overall setup and steps for measuring ¹H and ³¹P MRS and ¹H MRSI of orthotopic breast tumor models in mice with surface coils. This protocol can be adapted to the use of volume coils to measure ¹H and ³¹P MRS(I) of tumor models that grow inside the body. We address issues of animal handling, setting up the measurement, measurement options, and data analysis.

A Metabolic Therapy for Malignant Glioma Requires a Clinical Measure

Cancers are "reprogrammed" to use a much higher rate of glycolysis (GLY) relative to oxidative phosphorylation (OXPHOS), even in the presence of adequate amounts of oxygenation. Originally identified by Nobel Laureate Otto Warburg, this hallmark of cancer has recently been termed metabolic reprogramming and represents a way for the cancer tissue to divert carbon skeletons to produce biomass. Understanding the mechanisms that underlie this metabolic shift should lead to better strategies for cancer treatments. Malignant gliomas, cancers that are very resistant to conventional treatments, are highly glycolytic and seem particularly suited to approaches that can subvert this phenotype.

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.

Breast Tissue Metabolism by Magnetic Resonance Spectroscopy

Metabolic alterations are known to occur with oncogenesis and tumor progression. During malignant transformation, the metabolism of cells and tissues is altered. Cancer metabolism can be studied using advanced technologies that detect both metabolites and metabolic activities. Identification, characterization, and quantification of metabolites (metabolomics) are important for metabolic analysis and are usually done by nuclear magnetic resonance (NMR) or by mass spectrometry. In contrast to the magnetic resonance imaging that is used to monitor the tumor morphology during progression of the disease and during therapy, in vivo NMR spectroscopy is used to study and monitor tumor metabolism of cells/tissues by detection of various biochemicals or metabolites involved in various metabolic pathways. Several in vivo, in vitro and ex vivo NMR studies using ¹H and ³¹P magnetic resonance spectroscopy (MRS) nuclei have documented increased levels of total choline containing compounds, phosphomonoesters and phosphodiesters in human breast cancer tissues, which is indicative of altered choline and phospholipid metabolism. These levels get reversed with successful treatment. Another method that increases the sensitivity of substrate detection by using nuclear spin hyperpolarization of ¹³C-lableled substrates by dynamic nuclear polarization has revived a great interest in the study of cancer metabolism. This review discusses breast tissue metabolism studied by various NMR/MRS methods.

Metabolomic analysis of the saliva of Japanese patients with oral squamous cell carcinoma

The aim of the present study was to characterize the metabolic systems in Japanese patients with oral squamous cell carcinoma (OSCC) using capillary electrophoresis-mass spectrometry (CE-MS) metabolome analysis of saliva samples. A previous study showed variations among ethnicities and tumor sites in the saliva metabolome of patients with OSCC using CE-MS. In the present study, saliva was obtained from 22 Japanese patients with OSCC and from 21 healthy controls who visited the Department of Dentistry, Oral and Maxillofacial Surgery, Tokyo Dental Collage Ichikawa General Hospital, Tokyo, Japan, and all samples were subject to comprehensive quantitative metabolome analysis using CE-MS. A total of 499 metabolites were detected as CE-MS peaks in the saliva tested from the two groups. A total of 25 metabolites were revealed as potential markers to discriminate between patients with OSCC and healthy controls: Choline, p-hydroxyphenylacetic acid, and 2-hydroxy-4-methylvaleric acid (P<0.001); valine, 3-phenyllactic acid, leucine, hexanoic acid, octanoic acid, terephthalic acid, γ-butyrobetaine, and 3-(4-hydroxyphenyl)propionic acid (P<0.01); and isoleucine, tryptophan, 3-phenylpropionic acid, 2-hydroxyvaleric acid, butyric acid, cadaverine, 2-oxoisovaleric acid, N6,N6,N6-trimethyllysine, taurine, glycolic acid, 3-hydroxybutyric acid, heptanoic acid, alanine, and urea (P<0.05, according to the Wilcoxon rank sum test). A previous study by Sugimoto and co-workers detected 24 discriminatory metabolites, 7 of which (taurine, valine, leucine, isoleucine, choline, cadaverine, and tryptophan) were also detected in the present study. In the present study, however, choline, metabolites in the branched chain amino acids (BCAA) cycle, urea, and 3-hydroxybutyric acid were also characterized. Choline and metabolites of the BCAA cycle have previously been reported in OSCC using metabolome analysis. To the best of our knowledge, no previous reports have identified urea and 3-hydroxybuyric acid in the metabolome of patients with OSCC. These findings suggest the usefulness of metabolites as salivary biomarkers for Japanese patients with OSCC. Further studies using larger patient cohorts should be conducted to validate these results.

Proton and phosphorus magnetic resonance spectroscopy of the healthy human breast at 7 T

In vivo water- and fat-suppressed ¹ H magnetic resonance spectroscopy (MRS) and ³¹ P magnetic resonance adiabatic multi-echo spectroscopic imaging were performed at 7 T in duplicate in healthy fibroglandular breast tissue of a group of eight volunteers. The transverse relaxation times of ³¹ P metabolites were determined, and the reproducibility of ¹ H and ³¹ P MRS was investigated. The transverse relaxation times for phosphoethanolamine (PE) and phosphocholine (PC) were fitted bi-exponentially, with an added short T₂ component of 20 ms for adenosine monophosphate, resulting in values of 199 ± 8 and 239 ± 14 ms, respectively. The transverse relaxation time for glycerophosphocholine (GPC) was also fitted bi-exponentially, with an added short T₂ component of 20 ms for glycerophosphatidylethanolamine, which resonates at a similar frequency, resulting in a value of 177 ± 6 ms. Transverse relaxation times for inorganic phosphate, γ-ATP and glycerophosphatidylcholine mobile phospholipid were fitted mono-exponentially, resulting in values of 180 ± 4, 19 ± 3 and 20 ± 4 ms, respectively. Coefficients of variation for the duplicate determinations of ¹ H total choline (tChol) and the ³¹ P metabolites were calculated for the group of volunteers. The reproducibility of inorganic phosphate, the sum of phosphomonoesters and the sum of phosphodiesters with ³¹ P MRS imaging was superior to the reproducibility of ¹ H MRS for tChol. ¹ H and ³¹ P data were combined to calculate estimates of the absolute concentrations of PC, GPC and PE in healthy fibroglandular tissue, resulting in upper limits of 0.1, 0.1 and 0.2 mmol/kg of tissue, respectively.

Multiparametric MR Imaging of Breast Cancer

Breast MR imaging has increased in popularity over the past 2 decades due to evidence of its high sensitivity for cancer detection. Current clinical MR imaging approaches rely on the use of a dynamic contrast-enhanced acquisition that facilitates morphologic and semiquantitative kinetic assessments of breast lesions. The use of more functional and quantitative parameters holds promise to broaden the utility of MR imaging and improve its specificity. Because of wide variations in approaches for measuring these parameters and the considerable technical challenges, robust multicenter data supporting their routine use are not yet available, limiting current applications of many of these tools to research purposes.

Clinical Imaging of Tumor Metabolism with ¹H Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is a noninvasive functional technique to evaluate the biochemical behavior of human tissues. This property has been widely used in assessment and therapy monitoring of brain tumors. MRS studies can be implemented outside the brain, with successful and promising results in the evaluation of prostate and breast cancer, although still with limited reproducibility. As a result of technical improvements, malignancies of the musculoskeletal system and abdominopelvic organs can benefit from the molecular information that MRS provides. The technical challenges and main applications in oncology of (1)H MRS in a clinical setting are the focus of this review.

CEST-MRI detects metabolite levels altered by breast cancer cell aggressiveness and chemotherapy response

Chemical exchange saturation transfer (CEST) is an MRI contrast mechanism that detects the exchange of protons from distinct hydroxyl, amine, and amide groups to tissue water through the transfer of signal loss, with repeated exchange enhancing their effective signal. We applied CEST to detect systematically 15 common cellular metabolites in a panel of differentially aggressive human breast cancer cell lines. The highest CEST contrast was generated by creatine, myo-inositol, glutamate, and glycerophosphocholine, whose cellular concentrations decreased with increasing breast cancer aggressiveness. These decreased metabolite concentrations resulted in turn in a decreased CEST profile with increasing breast cancer aggressiveness in water-soluble extracts of breast cell lines. Treatment of both breast cancer cell lines with the chemotherapy drug doxorubicin resulted in increased metabolic CEST profiles, which correlated with significant increases in creatine, phosphocreatine, and glycerophosphocholine. CEST can detect breast cancer aggressiveness and response to chemotherapy in water-soluble extracts of breast cell lines. The presented results help shed light on possible contributions from CEST-active metabolites to the CEST contrast produced by breast cancers. The metabolic CEST profile may improve detection sensitivity over conventional MRS, and may have the potential to assess breast cancer aggressiveness and response to chemotherapy non-invasively using MRI if specialized metabolic CEST profile detection can be realized in vivo. Copyright © 2016 John Wiley & Sons, Ltd.

The state of the art in breast imaging using the Twente Photoacoustic Mammoscope: results from 31 measurements on malignancies

Objectives

Photoacoustic mammography is potentially an ideal technique, however, the amount of patient data is limited. To further our understanding of the in vivo performance of the method and to guide further research and development, we imaged 33 breast malignancies using the research system – the Twente Photoacoustic Mammoscope (PAM).

Methods

Thirty-one patients participated in this retrospective, observational study. The study and informed consent procedure were approved by the local ethics committee. PAM uses 1,064 nm light for excitation with a planar, 588-element, 1-MHz ultrasound array for detection. Photoacoustic lesion visibility and appearance were compared with conventional imaging (x-ray mammography and ultrasonography) findings, histopathology and patient demographics.

Results

Of 33 malignancies 32 were visualized with high contrast and good co-localization with conventional imaging. The contrast of the detected malignancies was independent of radiographic breast density, and size estimation was reasonably good with an average 28 % deviation from histology. However, the presence of contrast areas outside the malignant region is suggestive for low specificity of the current system. Statistical analyses did not reveal any further relationship between PAM results and patient demographics nor lesion characteristics.

Conclusions

The results confirm the high potential of photoacoustic mammography in future breast care.

Key Points

• Photoacoustic breast imaging visualizes malignancies with high imaging contrast.

• Photoacoustic lesion contrast is independent of the mammographically estimated breast density.

• No clear relationship exists between photoacoustic characteristics and lesion type, grade, etc.

• Photoacoustic specificity to breast cancer from some cases is not yet optimal.

Photoacoustic image patterns of breast carcinoma and comparisons with Magnetic Resonance Imaging and vascular stained histopathology

Photoacoustic (optoacoustic) imaging can visualize vasculature deep in tissue using the high contrast of hemoglobin to light, with the high-resolution possible with ultrasound detection. Since angiogenesis, one of the hallmarks of cancer, leads to increased vascularity, photoacoustics holds promise in imaging breast cancer as shown in proof-of-principle studies. Here for the first time, we investigate if there are specific photoacoustic appearances of breast malignancies which can be related to the tumor vascularity, using an upgraded research imaging system, the Twente Photoacoustic Mammoscope. In addition to comparisons with x-ray and ultrasound images, in subsets of cases the photoacoustic images were compared with MR images, and with vascular staining in histopathology. We were able to identify lesions in suspect breasts at the expected locations in 28 of 29 cases. We discovered generally three types of photoacoustic appearances reminiscent of contrast enhancement types reported in MR imaging of breast malignancies, and first insights were gained into the relationship with tumor vascularity.

Mapping human brain capillary water lifetime: high-resolution metabolic neuroimaging

Shutter-speed analysis of dynamic-contrast-agent (CA)-enhanced normal, multiple sclerosis (MS), and glioblastoma (GBM) human brain data gives the mean capillary water molecule lifetime (τ(b)) and blood volume fraction (v(b); capillary density-volume product (ρ(†)V)) in a high-resolution (1)H2O MRI voxel (40 μL) or ROI. The equilibrium water extravasation rate constant, k(po) (τ(b)(-1)), averages 3.2 and 2.9 s(-1) in resting-state normal white matter (NWM) and gray matter (NGM), respectively (n = 6). The results (italicized) lead to three major conclusions. (A) k(po) differences are dominated by capillary water permeability (P(W)(†)), not size, differences. NWM and NGM voxel k(po) and v(b) values are independent. Quantitative analyses of concomitant population-averaged k(po), v(b) variations in normal and normal-appearing MS brain ROIs confirm P(W)(†) dominance. (B) P(W)(†) is dominated (>95%) by a trans(endothelial)cellular pathway, not the P(CA)(†) paracellular route. In MS lesions and GBM tumors, P(CA)(†) increases but P(W)(†) decreases. (C) k(po) tracks steady-state ATP production/consumption flux per capillary. In normal, MS, and GBM brain, regional k(po) correlates with literature MRSI ATP (positively) and Na(+) (negatively) tissue concentrations. This suggests that the P(W)(†) pathway is metabolically active. Excellent agreement of the relative NGM/NWM k(po)v(b) product ratio with the literature (31)PMRSI-MT CMR(oxphos) ratio confirms the flux property. We have previously shown that the cellular water molecule efflux rate constant (k(io)) is proportional to plasma membrane P-type ATPase turnover, likely due to active trans-membrane water cycling. With synaptic proximities and synergistic metabolic cooperativities, polar brain endothelial, neuroglial, and neuronal cells form "gliovascular units." We hypothesize that a chain of water cycling processes transmits brain metabolic activity to k(po), letting it report neurogliovascular unit Na(+),K(+)-ATPase activity. Cerebral k(po) maps represent metabolic (functional) neuroimages. The NGM 2.9 s(-1) k(po) means an equilibrium unidirectional water efflux of ~10(15) H2O molecules s(-1) per capillary (in 1 μL tissue): consistent with the known ATP consumption rate and water co-transporting membrane symporter stoichiometries.

Molecular imaging using PET for breast cancer

Molecular imaging can visualize the biological processes at the molecular and cellular levels in vivo using certain tracers for specific molecular targets. Molecular imaging of breast cancer can be performed with various imaging modalities, however, positron emission tomography (PET) is a sensitive and non-invasive molecular imaging technology and this review will focus on PET molecular imaging of breast cancer, such as FDG-PET, FLT-PET, hormone receptor PET, and anti-HER2 PET.

Utilisation of MR spectroscopy and diffusion weighted imaging in predicting and monitoring of breast cancer response to chemotherapy

Neoadjuvant chemotherapy (NACT) is the standard treatment option for breast cancer as more data shows that pathologic complete response (pCR) after NACT correlates with improved prognosis. MRI is accepted as the best imaging modality for evaluating the response to NACT in many studies as compared with clinical examination and other imaging modalities. In vivo magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) studies have both emerged as potential tools to provide early response indicators based on the changes in the metabolites and the apparent diffusion coefficient (ADC) respectively. In this review article, we aim to discuss the strength and limitations of MRS and DWI in monitoring of early response breast cancer to NACT.

Interrogating a multifactorial model of breast conserving therapy with clinical data

Most women with early stage breast cancer do not require removal of the entire breast to treat their cancer; instead, up to 70% of women can be effectively and safely treated by breast conserving therapy (BCT) with surgical removal of the tumor only (lumpectomy) followed by radiation treatment of the remaining breast tissue. Unfortunately, the final contour and cosmesis of the treated breast is suboptimal in approximately 30% of patients. The ability to accurately predict breast contour after BCT for breast cancer could significantly improve patient decision-making regarding the choice of surgery for breast cancer. Our overall hypothesis is that the complex interplay among mechanical forces due to gravity, breast tissue constitutive law distribution, inflammation induced by radiotherapy and internal stress generated by the healing process play a dominant role in determining the success or failure of lumpectomy in preserving the breast contour and cosmesis. We have shown here from a first patient study that even in the idealistic situation of excellent cosmetic outcome this problem requires multiscale modeling. We propose a method to decide which component of the model works best for each phase of healing and what parameters should be considered dominant and patient specific. This patient study is part of a clinical trial registered on ClinicalTrial.gov, identifier NCT02310711.

Metabolic imaging of pancreatic ductal adenocarcinoma detects altered choline metabolism

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal disease that develops relatively symptom-free and is therefore advanced at the time of diagnosis. The absence of early symptoms and effective treatments has created a critical need for identifying and developing new noninvasive biomarkers and therapeutic targets.

EXPERIMENTAL DESIGN

We investigated the metabolism of a panel of PDAC cell lines in culture and noninvasively in vivo with (1)H magnetic resonance spectroscopic imaging (MRSI) to identify noninvasive biomarkers and uncover potential metabolic targets.

RESULTS

We observed elevated choline-containing compounds in the PDAC cell lines and tumors. These elevated choline-containing compounds were easily detected by increased total choline (tCho) in vivo, in spectroscopic images obtained from tumors. Principal component analysis of the spectral data identified additional differences in metabolites between immortalized human pancreatic cells and neoplastic PDAC cells. Molecular characterization revealed overexpression of choline kinase (Chk)-α, choline transporter 1 (CHT1), and choline transporter-like protein 1 (CTL1) in the PDAC cell lines and tumors.

CONCLUSIONS

Collectively, these data identify new metabolic characteristics of PDAC and reveal potential metabolic targets. Total choline detected with (1)H MRSI may provide an intrinsic, imaging probe-independent biomarker to complement existing techniques in detecting PDAC. The expression of Chk-α, CHT1, and CTL1 may provide additional molecular markers in aspirated cytological samples.

Optimization of 7-T chemical exchange saturation transfer parameters for validation of glycosaminoglycan and amide proton transfer of fibroglandular breast tissue

PURPOSE

To (a) implement simulation-optimized chemical exchange saturation transfer (CEST) measurements sensitive to amide proton transfer (APT) and glycosaminoglycan (GAG) hydroxyl proton transfer effects in the human breast at 7 T and (b) determine the reliability of these techniques for evaluation of fibroglandular tissue in the healthy breast as a benchmark for future studies of pathologic findings.

MATERIALS AND METHODS

All human studies were institutional review board approved, were HIPAA compliant, and included informed consent. The CEST parameters of saturation duration (25 msec) and amplitude (1 μT) were chosen on the basis of simulation-driven optimization for APT contrast enhancement with the CEST effect quantified by using residuals of a Lorentzian fit. Optimized parameters were implemented at 7 T in 10 healthy women in two separate examinations to evaluate the reliability of CEST magnetic resonance (MR) imaging measurements in the breast. CEST z-spectra were acquired over saturation offset frequencies ranging between ±40 ppm by using a quadrature unilateral breast coil. The imaging-repeat imaging reliability was assessed in terms of the intraclass correlation coefficient, which indicates the ratio of between-subject variation to total variation.

RESULTS

Simulations were performed of the Bloch equations with chemical exchange-guided selection of optimal values for pulse duration and amplitude, 25 msec and 1 μT, respectively. Reliability was evaluated by using intraclass correlation coefficients (95% confidence intervals), with acceptable results: 0.963 (95% confidence interval: 0.852, 0.991) and 0.903 (95% confidence interval: 0.609, 0.976) for APT and GAG, respectively.

CONCLUSION

Simulations were used to derive optimal CEST preparation parameters to elicit maximal CEST contrast enhancement in healthy fibroglandular breast tissue due to APT at 7 T. By using these parameters, reproducible values were obtained for both the amide and hydroxyl protons from CEST MR imaging at 7 T and are feasible in the human breast.

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.

Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes

PURPOSE

Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]).

METHODS AND MATERIALS

Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV46 and CTV60, respectively). MTVCho and MTVNAA were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue.

RESULTS

The MRSI coverage of the brain was between 70% and 76%. The MTVNAA were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTVCho was outside of the edema (median, 33%) and for some patients it was also outside of the CTV46 and CTV60. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTVCho for these patients were outside of CTV60.

CONCLUSIONS

This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on metabolic information.

1H/31P polarization transfer at 9.4 Tesla for improved specificity of detecting phosphomonoesters and phosphodiesters in breast tumor models

PURPOSE

To assess the ability of a polarization transfer (PT) magnetic resonance spectroscopy (MRS) technique to improve the detection of the individual phospholipid metabolites phosphocholine (PC), phosphoethanolamine (PE), glycerophosphocholine (GPC), and glycerophosphoethanolamine (GPE) in vivo in breast tumor xenografts.

MATERIALS AND METHODS

The adiabatic version of refocused insensitive nuclei enhanced by polarization transfer (BINEPT) MRS was tested at 9.4 Tesla in phantoms and animal models. BINEPT and pulse-acquire (PA) 31P MRS was acquired consecutively from the same orthotopic MCF-7 (n = 10) and MDA-MB-231 (n = 10) breast tumor xenografts. After in vivo MRS measurements, animals were euthanized, tumors were extracted and high resolution (HR)-MRS was performed. Signal to noise ratios (SNRs) and metabolite ratios were compared for BINEPT and PA MRS, and were also measured and compared with that from HR-MRS.

RESULTS

BINEPT exclusively detected metabolites with 1H-31P coupling such as PC, PE, GPC, and GPE, thereby creating a significantly improved, flat baseline because overlapping resonances from immobile and partly mobile phospholipids were removed without loss of sensitivity. GPE and GPC were more accurately detected by BINEPT in vivo, which enabled a reliable quantification of metabolite ratios such as PE/GPE and PC/GPC, which are important markers of tumor aggressiveness and treatment response.

CONCLUSION

BINEPT is advantageous over PA for detecting and quantifying the individual phospholipid metabolites PC, PE, GPC, and GPE in vivo at high magnetic field strength. As BINEPT can be used clinically, alterations in these phospholipid metabolites can be assessed in vivo for cancer diagnosis and treatment monitoring.

Requirements for static and dynamic higher order B0 shimming of the human breast at 7 T

The increased magnetic susceptibility effects at higher magnetic fields increase the demands for shimming of the B0 field for in vivo MRI and MRS. Both static and dynamic techniques have been developed to compensate for susceptibility-induced field inhomogeneities. In this study, we investigate the impact of and need for both static and dynamic higher order B0 shimming of magnetic field homogeneities in clinical breast MRI at 7 T. Both global and local field variations at lipid-tissue interfaces were observed in the magnetic field using TE-optimized B0 mapping at 7 T. With static B0 shimming, a field homogeneity of 39 ± 11 Hz (n = 48) was reached in a single breast using second-order shimming. Further compensation of the residual local field inhomogeneities caused by lipid-tissue interfaces does not seem to be feasible with shallow spherical harmonic fields. For bilateral shimming, the shimming quality was significantly less at 62 ± 15 Hz (n = 22) over both breasts, even after (simulated) fourth-order shimming. In addition, a substantial time-dependent field instability of 30 Hz peak to peak, with significant higher order field contributions, was observed during regular breathing. In conclusion, TE-optimized B0 field mapping reveals substantial field variations in the lipid-rich environment of the human breast, in both space and time. The static field variations could be partially minimized by third-order B0 shimming, providing sufficient lipid suppression. However, in order to fully benefit from the increased spectral dispersion at high fields, the significant magnetic field variations during breathing need to be considered.

Magnetic resonance imaging in breast cancer: A literature review and future perspectives

Early detection and diagnosis of breast cancer are essential for successful treatment. Currently mammography and ultrasound are the basic imaging techniques for the detection and localization of breast tumors. The low sensitivity and specificity of these imaging tools resulted in a demand for new imaging modalities and breast magnetic resonance imaging (MRI) has become increasingly important in the detection and delineation of breast cancer in daily practice. However, the clinical benefits of the use of pre-operative MRI in women with newly diagnosed breast cancer is still a matter of debate. The main additional diagnostic value of MRI relies on specific situations such as detecting multifocal, multicentric or contralateral disease unrecognized on conventional assessment (particularly in patients diagnosed with invasive lobular carcinoma), assessing the response to neoadjuvant chemotherapy, detection of cancer in dense breast tissue, recognition of an occult primary breast cancer in patients presenting with cancer metastasis in axillary lymph nodes, among others. Nevertheless, the development of new MRI technologies such as diffusion-weighted imaging, proton spectroscopy and higher field strength 7.0 T imaging offer a new perspective in providing additional information in breast abnormalities. We conducted an expert literature review on the value of breast MRI in diagnosing and staging breast cancer, as well as the future potentials of new MRI technologies.

Quadrature transmit coil for breast imaging at 7 tesla using forced current excitation for improved homogeneity

PURPOSE

To demonstrate the use of forced current excitation (FCE) to create homogeneous excitation of the breast at 7 tesla, insensitive to the effects of asymmetries in the electrical environment.

MATERIALS AND METHODS

FCE was implemented on two breast coils: one for quadrature (1) H imaging and one for proton-decoupled (13) C spectroscopy. Both were a Helmholtz-saddle combination, with the saddle tuned to 298 MHz for imaging and 75 MHz for spectroscopy. Bench measurements were acquired to demonstrate the ability to force equal currents on elements in the presence of asymmetric loading to improve homogeneity. Modeling and temperature measurements were conducted per safety protocol. B1 mapping, imaging, and proton-decoupled (13) C spectroscopy were demonstrated in vivo.

RESULTS

Using FCE to ensure balanced currents on elements enabled straightforward tuning and maintaining of isolation between quadrature elements of the coil. Modeling and bench measurements confirmed homogeneity of the field, which resulted in images with excellent fat suppression and in broadband proton-decoupled carbon-13 spectra.

CONCLUSION

FCE is a straightforward approach to ensure equal currents on multiple coil elements and a homogeneous excitation field, insensitive to the effects of asymmetries in the electrical environment. This enabled effective breast imaging and proton-decoupled carbon-13 spectroscopy at 7T.