Metabolic profiling of human brain metastases using in vivo proton MR spectroscopy at 3T

Abstract

BackgroundMetastases to the central nervous system from different primary cancers are an oncologic challenge as the overall prognosis for these patients is generally poor. The incidence of brain metastases varies with type of primary cancer and is probably increasing due to improved therapies of extracranial metastases prolonging patient's overall survival and thereby time for brain metastases to develop. In addition, the greater access to improved neuroimaging techniques can provide earlier diagnosis. The aim of this study was to investigate the feasibility of using proton magnetic resonance spectroscopy (MRS) and multivariate analyses to characterize brain metastases originating from different primary cancers, to assess changes in spectra during radiation treatment and to correlate the spectra to clinical outcome after treatment.MethodsPatients (n = 26) with brain metastases were examined using single voxel MRS at a 3T clinical MR system. Five patients were excluded due to poor spectral quality. The spectra were obtained before start (n = 21 patients), immediately after (n = 6 patients) and two months after end of treatment (n = 4 patients). Principal component analysis (PCA) and partial least square regression analysis (PLS) were applied in order to identify clustering of spectra due to origin of metastases and to relate clinical outcome (survival) of the patients to spectral data from the first MR examination.ResultsThe PCA results indicated that brain metastases from primary lung and breast cancer were separated into two clusters, while the metastases from malignant melanomas showed no uniformity. The PLS analysis showed a significant correlation between MR spectral data and survival five months after MRS before start of treatment.ConclusionMRS determined metabolic profiles analysed by PCA and PLS might give valuable clinical information when planning and evaluating the treatment of brain metastases, and also when deciding to terminate further therapies.

Proton MR Spectroscopy of Neural Stem Cells: Does the Proton-NMR Peak at 1.28 ppm Function As a Biomarker for Cell Type or State?

“…16 The link of the signal has been best established for apoptosis and has found entry into clinical diagnostic procedures, such as the evaluation of tumor regression or type. [38][39][40] The two tumor cell types studied in the present report, mouse melanoma and glioma cells, were also prone to the induction of apoptosis and depicted a concomitant high peak intensity.…”

Proton Magnetic Resonance Spectroscopy of the Central Nervous System

“…They also observed significantly higher Lip+Lac/Cr ratio in the peritumoral area of PCNSLs when compared with that of GBMs, suggesting the presence of infiltrative active lymphocytes and macrophages in areas beyond lymphoma boundaries. Using a threshold value of 7.09 for Lip+Lac/Cr ratio they differentiated PCNSLs from GBMs with 84.6% sensitivity and 75% specificity [107]. Therefore, in the absence of obvious necrosis, increased lipid concentration together with a markedly elevated Cho/Cr ratio for both intratumoral and peritumoral areas can provide important metabolic information which may improve the distinction between PCNSLs and other brain tumors.…”

“…The results presented in their study, demonstrated that lipid signals on both short and long TE spectra are important for metastases characterization. Although non-statistically significant, lung metastases tended to differentiated from breast metastases in respect to their lipid signals, while the melanoma showed no trend [107]. Chernov et al retrospectively studied 25 metastatic brain tumors from lungs, colon, breast, kidney, prostate and cardiac muscle, using 1 H-MRS on long TE.…”

“…The most specific finding for PCNSL on MRS is an increase in lipid and Cho resonances ( Figure 9). Sometimes, lipid peaks in PCNSL may be more prominent than in high grade gliomas and can help differentiate between the two tumor types [107].…”

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

“…Several studies have been conducted to assess the metabolic patterns of brain tumors in an attempt to correlate them with the histology of the tumor, aggressiveness, and clinical outcome (4)(5)(6)(7)(8)(9)(10)(11)(12). Some studies have compared different kinds of spectral fitting methods, either in the time (13) or frequency domain (14).…”