Investigation of breast cancer using two-dimensional MRS

Pure-Shift-Based Proton Magnetic Resonance Spectroscopy for High-Resolution Studies of Biological Samples

Proton magnetic resonance spectroscopy (1H MRS) presents a powerful tool for revealing molecular-level metabolite information, complementary to the anatomical insight delivered by magnetic resonance imaging (MRI), thus playing a significant role in in vivo/in vitro biological studies. However, its further applications are generally confined by spectral congestion caused by numerous biological metabolites contained within the limited proton frequency range. Herein, we propose a pure-shift-based 1H localized MRS method as a proof of concept for high-resolution studies of biological samples. Benefitting from the spectral simplification from multiplets to singlet peaks, this method addresses the challenge of spectral congestion encountered in conventional MRS experiments and facilitates metabolite analysis from crowded NMR resonances. The performance of the proposed pure-shift 1H MRS method is demonstrated on different kinds of samples, including brain metabolite phantom and in vitro biological samples of intact pig brain tissue and grape tissue, using a 7.0 T animal MRI scanner. This proposed MRS method is readily implemented in common commercial NMR/MRI instruments because of its generally adopted pulse-sequence modules. Therefore, this study takes a meaningful step for MRS studies toward potential applications in metabolite analysis and disease diagnosis.

Enhanced spectral resolution for correlated spectroscopic imaging using inner-product and covariance transform: a pilot analysis of metabolites and lipids in breast cancer in vivo

Acquisition duration of correlated spectroscopy in vivo can be longer due to a large number of t1 increments along the indirect (F1) dimension. Limited number of t1 increments on the other hand leads to poor spectral resolution along F1. Covariance transformation (CT) instead of Fourier transform along t1 is an alternative way of increasing the resolution of the 2D COSY spectrum. Prospectively undersampled five-dimensional echo-planar correlated spectroscopic imaging (EP-COSI) data from ten malignant patients and ten healthy women were acquired and reconstructed using compressed sensing. The COSY spectrum at each voxel location was then generated using FFT, CT and a variant of CT called Inner Product (IP). Metabolite and lipid ratios were computed with respect to water from unsuppressed one-dimensional spectrum. The effects of t1-ridging artifacts commonly seen with FFT were not observed with CT/IP. Statistically significant differences were observed in the fat cross peaks measured with CT/IP/FFT. Spectral resolution was increased ~ 8.5 times (~ 19.53 Hz in FFT, ~ 2.32 Hz in CT/IP) without affecting the spectral width along F1 was possible with CT/IP. CT and IP enabled substantially increased F1 resolution effectively with significant gain in scan time and reliable measure of unsaturation index as a biomarker for malignant breast cancer.

In vivo assignment of methylmalonic acid in breast tissue using 2D MRS and relationship with breast density, menopausal status and cancer risk

BACKGROUND

Methylmalonic acid (MMA) is linked to progression and aggressiveness of tumours. A recent study showed that high levels of circulatory MMA directed genetic programs promoting cancer progression.

PURPOSE

To evaluate in vivo two-dimensional correlated spectroscopy (2D COSY) data from women at elevated risk of breast cancer to determine if resonances consistent with MMA are present, and if so to correlate levels with breast density, menopausal status and risk categories.

MATERIALS AND METHODS

With institutional review board approval, 106 women at elevated risk (mean age 47), including 46 participants at medium risk, 43 at high risk with no known mutation and 17 BRCA-mutation carriers, were recruited. Breast density was assessed using a T₂ sequence. A T₁ sequence was used to place the voxel for the 2D COSY data. Peak volumes were normalized to the methylene peak at (1.30, 1.30) ppm. Chi-squared and Mann-Whitney tests were used.

RESULTS

Two resonances are assigned on the diagonal at 3.15 ppm and 3.19 ppm consistent with and denoted MMA1 and MMA2 respectively. MMA1 and MMA2 increased in parallel with increased risk. BRCA-mutation carriers recorded an increase in mean MMA1 of 120% (p = 0.033) and MMA2 of 127% (p = 0.020) in comparison with participants with no known mutation. BRCA-mutation carriers with dense breasts recorded a significant increase in mean MMA1 of 137% (p = 0.002) and in mean MMA2 of 143% (p = 0.004) compared with BRCA-mutation participants with low-density breast tissue. MMA1 and MMA2 were higher in premenopausal women with dense breasts compared with those with low-density tissue. The highest values of MMA were recorded in BRCA-mutation carriers.

CONCLUSION

Two tentative assignments are made for MMA in breast tissue of women at elevated risk for cancer. BRCA-mutation carriers exhibited higher values of MMA than those with no known mutation. Premenopausal women with BRCA mutation and dense breasts recorded the highest levels of MMA compared with other categories.

Breast Tissue Chemistry Measured In Vivo In Healthy Women Correlate with Breast Density and Breast Cancer Risk

BACKGROUND

The relationship of tissue chemistry to breast density and cancer risk has not been documented despite breast density being a known risk factor.

PURPOSE

To investigate whether distinct chemical profiles associated with breast density and cancer risk are identified in healthy breast tissue using in vivo two-dimensional correlated spectroscopy (2D COSY).

STUDY TYPE

Prospective.

POPULATION

One-hundred-seven participants including 55 at low risk and 52 at high risk of developing breast cancer.

FIELD STRENGTH/SEQUENCE

3 T/ axial/ T1, T2, 2D COSY.

ASSESSMENT

Two radiologists defined breast density on T2. Interobserver variability assessed. Peak volumes normalized to methylene at (1.30, 1.30) ppm as internal shift reference.

STATISTICAL TESTS

Chi-squared/Mann-Whitney/Kappa statistics/Kruskal Wallis/pairwise analyses. Significance level 0.05.

RESULTS

Ten percentage were fatty breasts, 39% scattered fibroglandular, 35% heterogeneously dense, and 16% extremely dense. Interobserver variability was excellent (kappa = 0.817). Sixty percentage (64/107) were premenopausal. Four distinct tissue chemistry categories were identified: low-density (LD)/premenopausal, high-density (HD)/premenopausal, LD/postmenopausal, and HD/postmenopausal. Compared to LD, HD breast chemistry showed significant increases of cholesterol (235%) and lipid unsaturation (33%). In the low-risk category, postmenopausal women with dense breasts recorded the largest significant changes including cholesterol methyl 540%, lipid unsaturation 207%, glutamine/glutamate 900%, and choline/phosphocholine 800%. In the high-risk cohort, premenopausal women with HD recorded a more active chemical profile with significant increases in choline/phosphocholine 1100%, taurine/glucose 550% and cholesterol sterol 250%.

DATA CONCLUSION

Four distinct chemical profiles were identified in healthy breast tissue based on breast density and menopausal status in participants at low and high risk. Gradual increase in neutral lipid content and metabolites was noted in both risk groups across categories in different order. In low risk, the HD postmenopausal category exhibited the highest metabolic activity, while women at high risk exhibited the highest lipid content and metabolic activity in the HD premenopausal category.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 3.

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction

Objectives

The main objective of this work was to detect novel biomarkers in breast cancer by spreading the MR spectra over two dimensions in multiple spatial locations using an accelerated 5D EP-COSI technology.

Methods

The 5D EP-COSI data were non-uniformly undersampled with an acceleration factor of 8 and reconstructed using group sparsity-based compressed sensing reconstruction. Different metabolite and lipid ratios were then quantified and statistically analyzed for significance. Linear discriminant models based on the quantified metabolite and lipid ratios were generated. Spectroscopic images of the quantified metabolite and lipid ratios were also reconstructed.

Results

The 2D COSY spectra generated using the 5D EP-COSI technique showed differences among healthy, benign, and malignant tissues in terms of their mean values of metabolite and lipid ratios, especially the ratios of potential novel biomarkers based on unsaturated fatty acids, myo-inositol, and glycine. It is further shown the potential of choline and unsaturated lipid ratio maps, generated from the quantified COSY signals across multiple locations in the breast, to serve as complementary markers of malignancy that can be added to the multiparametric MR protocol. Discriminant models using metabolite and lipid ratios were found to be statistically significant for classifying benign and malignant tumor from healthy tissues.

Conclusions

Accelerated 5D EP-COSI technique demonstrates the potential to detect novel biomarkers such as glycine, myo-inositol, and unsaturated fatty acids in addition to commonly reported choline in breast cancer, and facilitates metabolite and lipid ratio maps which have the potential to play a significant role in breast cancer detection.

Advances in knowledge

This study presents the first evaluation of a multidimensional MR spectroscopic imaging technique for the detection of potentially novel biomarkers based on glycine, myo-inositol, and unsaturated fatty acids, in addition to commonly reported choline. Spatial mapping of choline and unsaturated fatty acid ratios with respect to water in malignant and benign breast masses are also shown. These metabolic characteristics may serve as additional biomarkers for improving the diagnostic and therapeutic evaluation of breast cancer.

Clinical applications of breast cancer metabolomics using high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS): systematic scoping review

INTRODUCTION

Breast cancer is a heterogeneous disease with different prognoses and responses to systemic treatment depending on its molecular characteristics, which makes it imperative to develop new biomarkers for an individualized diagnosis and personalized oncological treatment. Ex vivo high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS) is the most common technique for metabolic quantification in human surgical and biopsy tissue specimens.

OBJECTIVE

To perform a review of the current available literature on the clinical applications of HRMAS 1H MRS metabolic analysis in tissue samples of breast cancer patients.

METHODS

This systematic scoping review included original research papers published in the English language in peer-reviewed journals. Study selection was performed independently by two reviewers and preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were followed.

RESULTS

The literature search returned 159 studies and 26 papers were included as part of this systematic review. There was considerable variation regarding tissue type, aims, and statistical analysis methods across the different studies. To facilitate the interpretation of the results, the included studies were grouped according to their aims or main outcomes into: feasibility and tumor diagnosis (n = 6); tumor heterogeneity (n = 2); correlation with proteomics/transcriptomics (n = 3); correlation with prognostic factors (n = 11); and response evaluation to NAC (n = 4).

CONCLUSION

There is a lot of potential in including metabolic information of breast cancer tissue obtained with HRMAS 1H MRS. To date, studies show that metabolic concentrations quantified by this technique can be related to the diagnosis, prognosis, and treatment response in breast cancer patients.

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.

Quantitative analysis of spatial averaging effect on chemical shift imaging SNR and noise coherence with k-space sampling schemes

Spatial averaging of multiple voxels from high-resolution chemical shift imaging (hrCSI) is a common strategy for in vivo metabolic studies to achieve a better signal-to-noise ratio (SNR) for a region-of-interest. However, the mechanism about how the spatial averaging approach influences the respective spectral signal and noise and its relevance to the k-space sampling schemes remains unclear. Using three-dimension ¹⁷O CSI technique with the weighted k-space sampling method of Fourier series window, we performed quantitative SNR comparisons between a single low-resolution CSI (lrCSI) voxel (being 27 times larger than the hrCSI voxel size) and the spatially averaged hrCSI voxels with matched sampling volume and location. We demonstrated that the averaged hrCSI voxel spectrum had a large SNR loss (> 4 times) compared to the lrCSI voxel, which was resulted from unmatched increases in signal (~1.9 fold) and noise (~9.3 fold). The signal increase was caused by the spatial overlapping between the adjacent hrCSI voxels. The substantial noise increase was mainly attributed to the strong noise coherence among hrCSI voxels acquired with the weighted k-space sampling. This study presents a quantitative relation between the k-space sampling schemes to an apparent SNR penalty of the spatial averaging approach. The information could be useful for designing CSI acquisition method and determination of optimal spatial resolution for in vivo metabolic imaging studies.

1D-spectral editing and 2D multispectral in vivo1H-MRS and 1H-MRSI - Methods and applications

This article reviews the methodological aspects of detecting low-abundant J-coupled metabolites via 1D spectral editing techniques and 2D nuclear magnetic resonance (NMR) methods applied in vivo, in humans, with a focus on the brain. A brief explanation of the basics of J-evolution will be followed by an introduction to 1D spectral editing techniques (e.g., J-difference editing, multiple quantum coherence filtering) and 2D-NMR methods (e.g., correlation spectroscopy, J-resolved spectroscopy). Established and recently developed methods will be discussed and the most commonly edited J-coupled metabolites (e.g., neurotransmitters, antioxidants, onco-markers, and markers for metabolic processes) will be briefly summarized along with their most important applications in neuroscience and clinical diagnosis.

Adjacent vessel sign and breast imaging reporting and data system are valuable for diagnosis of benign and malignant breast lesions

The purpose of this study is to investigate whether an adjacent vessel sign (AVS) observed on the maximum intensity projections (MIPs) from the subtracted images can help distinguish between malignant and benign breast lesions and to test whether the combination of breast imaging reporting and data system (BI-RADS) category and AVS can increase the specificity and diagnostic accuracy of breast magnetic resonance imaging (MRI). The study included 63 histologically verified lesions which underwent dynamic breast MRI before biopsy. All magnetic resonance (MR) images were evaluated by two radiologists in consensus, who were unaware of the histopathological outcome. The MR images of all cases were analyzed according to BI-RADS-MRI assessment category. Levels of suspicion were reported as categories of I-V. The presence of vessels either entering the enhancing lesion or in contact with the lesion edge on MIP images was considered as the presence of AVS. Final analysis of 63 masses revealed 41 malignant lesions (65.1%) and 22 benign lesions (34.9%). Thirty seven out of 41 malignant lesions and 3 out of 22 benign lesions were associated with adjacent vessel, with highly significant difference between benign and malignant lesions (P < 0.001), especially for lesions smaller than 2.0 cm. The corresponding specificity, sensitivity and accuracy of contrast-enhanced 3.0-T breast were 86.4%, 82.9% and 84.1%, respectively. Based on BI-RADS-MRI category, the specificity, sensitivity and accuracy of breast MRI were 54.5%, 100% and 84.1%, respectively. After combining BI-RADS category and AVS, the specificity, sensitivity and accuracy of breast MRI were 90.9%, 82.9% and 85.7%, respectively. AVS can help differentiate malignant from benign breast lesions, especially for the lesions smaller than 2.0 cm. The combination of BI-RADS category and AVS can increase the specificity and the diagnostic accuracy of breast MRI.

Non-uniformly under-sampled multi-dimensional spectroscopic imaging in vivo: maximum entropy versus compressed sensing reconstruction

The four-dimensional (4D) echo-planar correlated spectroscopic imaging (EP-COSI) sequence allows for the simultaneous acquisition of two spatial (ky, kx) and two spectral (t2, t1) dimensions in vivo in a single recording. However, its scan time is directly proportional to the number of increments in the ky and t1 dimensions, and a single scan can take 20–40 min using typical parameters, which is too long to be used for a routine clinical protocol. The present work describes efforts to accelerate EP-COSI data acquisition by application of non-uniform under-sampling (NUS) to the ky–t1 plane of simulated and in vivo EP-COSI datasets then reconstructing missing samples using maximum entropy (MaxEnt) and compressed sensing (CS). Both reconstruction problems were solved using the Cambridge algorithm, which offers many workflow improvements over other l1-norm solvers. Reconstructions of retrospectively under-sampled simulated data demonstrate that the MaxEnt and CS reconstructions successfully restore data fidelity at signal-to-noise ratios (SNRs) from 4 to 20 and 5× to 1.25× NUS. Retrospectively and prospectively 4× under-sampled 4D EP-COSI in vivo datasets show that both reconstruction methods successfully remove NUS artifacts; however, MaxEnt provides reconstructions equal to or better than CS. Our results show that NUS combined with iterative reconstruction can reduce 4D EP-COSI scan times by 75% to a clinically viable 5 min in vivo, with MaxEnt being the preferred method.

Magnetic resonance in the detection of breast cancers of different histological types

Breast cancer incidence is increasing worldwide. Early detection is critical for long-term patient survival, as is monitoring responses to chemotherapy for management of the disease. Magnetic resonance imaging and spectroscopy (MRI/MRS) has gained in importance in the last decade for the diagnosis and monitoring of breast cancer therapy. The sensitivity of MRI/MRS for anatomical delineation is very high and the consensus is that MRI is more sensitive in detection than x-ray mammography. Advantages of MRS include delivery of biochemical information about tumor metabolism, which can potentially assist in the staging of cancers and monitoring responses to treatment. The roles of MRS and MRI in screening and monitoring responses to treatment of breast cancer are reviewed here. We rationalize how it is that different histological types of breast cancer are differentially detected and characterized by MR methods.

Quantitative mapping of total choline in healthy human breast using proton echo planar spectroscopic imaging (PEPSI) at 3 Tesla

PURPOSE

To quantitatively measure tCho levels in healthy breasts using Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI).

MATERIALS AND METHODS

The two-dimensional mapping of tCho at 3 Tesla across an entire breast slice using PEPSI and a hybrid spectral quantification method based on LCModel fitting and integration of tCho using the fitted spectrum were developed. This method was validated in 19 healthy females and compared with single voxel spectroscopy (SVS) and with PRESS prelocalized conventional Magnetic Resonance Spectroscopic Imaging (MRSI) using identical voxel size (8 cc) and similar scan times (∼7 min).

RESULTS

A tCho peak with a signal to noise ratio larger than 2 was detected in 10 subjects using both PEPSI and SVS. The average tCho concentration in these subjects was 0.45 ± 0.2 mmol/kg using PEPSI and 0.48 ± 0.3 mmol/kg using SVS. Comparable results were obtained in two subjects using conventional MRSI. High lipid content in the spectra of nine tCho negative subjects was associated with spectral line broadening of more than 26 Hz, which made tCho detection impossible. Conventional MRSI with PRESS prelocalization in glandular tissue in two of these subjects yielded tCho concentrations comparable to PEPSI.

CONCLUSION

The detection sensitivity of PEPSI is comparable to SVS and conventional PRESS-MRSI. PEPSI can be potentially used in the evaluation of tCho in breast cancer. A tCho threshold concentration value of ∼0.7 mmol/kg might be used to differentiate between cancerous and healthy (or benign) breast tissues based on this work and previous studies.

NMR metabolomics of MTLn3E breast cancer cells identifies a role for CXCR4 in lipid and choline regulation

The alpha chemokine receptor CXCR4 is up-regulated in certain types of breast cancer. Truncation of the C-terminus of this receptor alters cell morphology and increases invasiveness and metastatic potential. Here, to better understand the effects of CXCR4 expression and truncation in breast cancer cells, we have used high resolution magic angle spinning (HR-MAS) NMR studies of rat breast carcinoma MtLn3E cells to characterize the metabolite complement of cells heterologously expressing human CXCR4 or its C-terminal truncation mutant, Δ34-CXCR4. Notable reductions in choline levels were detected when either cells expressing wild-type CXCR4 or Δ34-CXCR4 were compared with cells containing an empty expression vector. Cells expressing CXCR4-Δ34 had reduced lipid content when compared with either the wild-type CXCR4 expressing cells or those containing the empty expression vector. Taken together, our results show that distinct effects on the metabolite complement can be linked to either CXCR4 expression or CXCR4 regulation. The metabolite markers for these two effects identified in the present study can, in turn, be used to further investigate the role of CXCR4 in metastasis.

An HR-MAS MR metabolomics study on breast tissues obtained with core needle biopsy

BACKGROUND

Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability.

METHODOLOGY/PRINCIPAL FINDINGS

In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients.

CONCLUSIONS/SIGNIFICANCE

HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers.

Adiabatic localized correlation spectroscopy (AL-COSY): application in muscle and brain

PURPOSE

To describe an enhanced version of a localized correlation spectroscopy (L-COSY) by introducing adiabatic radiofrequency (RF) pulses for localization in two dimensions. Adiabatic pulses will improve slice selection profile and reduce chemical shift artifacts. Optimized Mao and adiabatic hyperbolic secant pulses are tested in vivo.

MATERIALS AND METHODS

Region of interest is localized by a 90° nonselective adiabatic RF pulse followed by two pairs of adiabatic RF pulses and a terminal 90° RF sinc pulse. Slice profiles for both refocusing pulses and chemical shift artifacts are measured in a water-oil phantom for L-COSY and AL-COSY. In vivo results of both COSY sequences are shown from muscle and brain on a 3 Tesla (T) scanner.

RESULTS

Chemical shift artifacts were reduced with AL-COSY compared with L-COSY. Slice profiles of adiabatic pulses were found to be sharper and more symmetrical than those of traditional Mao pulses. One-dimensional (1D) phantom studies showed longer T2 values using AL-COSY sequence. Comparison of 2D spectra obtained revealed spectroscopic peak volume improvements in AL-COSY and less residual water. In vivo 1D comparison showed more inphase and sharper peaks in AL-COSY spectrum.

CONCLUSION

The AL-COSY sequence is an improved sequence due to sharper slice selection profiles, reduction of chemical shift artifacts, peak volume improvements in 2D techniques, and less J-modulation.

In vivo 1H MRS in the assessment of the therapeutic response of breast cancer patients

MRI and in vivo MRS have rapidly evolved as sensitive tools for diagnosis and therapeutic monitoring in cancer research. In vivo MRS provides information on tumor metabolism, which is clinically valuable in the diagnosis and assessment of tumor response to therapy for the management of women with breast diseases. Several centers complement breast MRI studies with (1)H MRS to improve the specificity of diagnosis. Malignant breast tissues show elevated water-to-fat ratio and choline-containing compounds (total choline, tCho), and any effect of therapy on tissue viability or metabolism will be manifested as changes in these levels. Sequential (1)H MRS studies have shown significantly reduced tCho levels during the course of therapy in patients who were responders. However, there are challenges in using in vivo MRS because of the relatively low sensitivity in detecting the tCho resonance with decreased lesion size or significant reduction in the tumor volume during therapy. MRS is also technically challenging because of the low signal-to-noise ratio and heterogeneous distribution of fat and glandular tissues in the breast. MRS is best utilized for the diagnosis of focal masses, most commonly seen in patients with ductal-type neoplasms; however, it has limitations in detecting nonfocal masses, such as the linear pattern of tumors seen in invasive lobular carcinoma. Further work is required to assess the clinical utility of quantitative MRS, with the goal of automation, which will reduce the subjectivity currently inherent in both qualitative and semi-quantitative MRS.

The necrosis sign in magnetic resonance-mammography: diagnostic accuracy in 1,084 histologically verified breast lesions

Necrosis sign (NS) is a new descriptor for differential diagnosis of breast lesions in magnetic resonance (MR)-mammography (MRM). This study was designed: (a) to analyze diagnostic accuracy of NS in 1,084 histologically verified breast lesions, (b) to assess performance of NS in subgroups. This study was approved by the local ethical committee. All histologically verified lesions having undergone MR-mammography at our institution over 12 years were evaluated by experienced radiologists (> 500 MRM) according to standard protocols and study design (T1w; 0.1 mmol/kg bw gadolinium diethylenetriamine penta-acetic acid; T2-turbo spin echo (TSE)). Patients with history of breast biopsy (surgically, minimal-invasive), radiation- or chemotherapy ≤ 1 year before MRM were excluded. NS was assessed on T2w-TSE sequences and was rated positive if a hyperintense center in a hypointense lesion could be visualized (chi-squared test). One thousand and eighty-four lesions were available for statistical analysis (648: malignant, 436: benign). NS was significantly associated with malignancy (p < 0.001), providing specificity and positive predictive value (PPV) of 96.1% and 78.8%. Malignant lesions > 20 mm presented significantly more often NS (p < 0.001) than neoplasias ≤ 20 mm. There was no difference regarding prevalence of NS in small versus advanced benign lesions (n.s.), leading to better performance of NS in lesions > 20 mm (PPV: 87.8%). Correlation between NS and Grading of invasive carcinomas was significant. In this study of 1,084 lesions necrosis sign was a specific and highly predictive feature for differential diagnosis in MRM (Specificity: 96.1%; PPV: 78.8%). This particularly counts for advanced lesions (PPV 87.8%). As this new descriptor correlates with Grading, it could be used as an initial estimate of patient's prognosis.

Implementing a breast MR imaging program: all things considered

The role of magnetic resonance (MR) imaging in breast imaging and evaluation has increased rapidly. MR imaging now encompasses diagnostic evaluation as well as screening for breast cancer in high-risk groups, monitoring the extent of disease and the response to chemotherapy. It is expected that the utility of breast MR imaging will continue to increase, requiring additional facilities and expertise. Establishing a breast MR imaging program requires familiarity with several unique issues pertaining to the nature of this imaging modality. This article attempts to address some of these issues, including selection of a magnet based on needs of the particular practice and magnet field strength, selection of a dedicated breast coil, magnet location and siting, advantages and challenges of higher strength magnets such as 3 Tesla, establishing a referral base, scheduling of breast MR examinations, patient safety concerns, and examination interpretation and reporting.

Metabolic profiling of human lung cancer tissue by 1H high resolution magic angle spinning (HRMAS) NMR spectroscopy

This work aims at characterizing the metabolic profile of human lung cancer, to gain new insights into tumor metabolism and to identify possible biomarkers with potential diagnostic value in the future. Paired samples of tumor and noninvolved adjacent tissues from 12 lung tumors have been directly analyzed by (1)H HRMAS NMR (500/600 MHz) enabling, for the first time to our knowledge, the identification of over 50 compounds. The effect of temperature on tissue stability during acquisition time has also been investigated, demonstrating that analysis should be performed within less than two hours at low temperature (277 K), to minimize glycerophosphocholine (GPC) and phosphocholine (PC) conversion to choline and reduce variations in some amino acids. The application of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to the standard 1D (1)H spectra resulted in good separation between tumor and control samples, showing that inherently different metabolic signatures characterize the two tissue types. On the basis of spectral integration measurements, lactate, PC, and GPC were found to be elevated in tumors, while glucose, myo-inositol, inosine/adenosine, and acetate were reduced. These results show the valuable potential of HRMAS NMR-metabonomics for investigating the metabolic phenotype of lung cancer.

The adjacent vessel sign on breast MRI: new data and a subgroup analysis for 1,084 histologically verified cases

OBJECTIVE

The adjacent vessel sign (AVS) is a descriptor for differentiating malignant from benign breast lesions on breast MRI (bMRI). This investigation was designed to verify the previous reports on the diagnostic accuracy of AVS and to assess correlation between AVS, histopathological diagnosis, lesion size and lesion grade.

MATERIALS AND METHODS

This study was approved by the local ethical committee. Experienced radiologists evaluated 1,084 lesions. The exclusion criteria were no histological verification after bMRI and breast interventions that were done up to one year before bMRI (surgery, core biopsy, chemo- or radiation therapy). The native and dynamic contrast-enhanced T1-weighted series were acquired using standardized protocols. The AVS was rated positive if a vessel leading to a lesion could be visualized. Prevalence of an AVS was correlated with the lesions' size, grade and histology using Chi-square-tests.

RESULTS

The AVS was significantly associated with malignancy (p < 0.001; sensitivity: 47%, specificity: 88%, positive-predictive-value [PPV]: 85%). Malignant lesions > 2 cm more often presented with an AVS than did those malignant lesions < 2 cm (p < 0.0001; sensitivity: 65%, PPV: 90%). There was no correlation of the AVS with the tumor grade. The prevalence of an AVS didn't significantly differ between invasive lobular carcinomas versus ductal carcinomas. In situ cancers were less frequently associated with an AVS (p < 0.001).

CONCLUSION

The adjacent vessel sign was significantly associated with malignancy. Thus, it can be used to accurately assess breast lesions on bMRI. In this study, the AVS was particularly associated with advanced and invasive carcinomas.