Two-dimensional MR spectroscopy of healthy and cancerous prostates in vivo

Abstract

Implementation of the state-of-the-art 2D MRS techniques and preliminary evaluation in prostate pathologies are discussed in this review. Even though these techniques are going through developmental and early testing phases, it is evident that 2D MRS can be easily added on to any clinical Magnetic Resonance Imaging (MRI) protocol to non-invasively record the biochemical contents of the prostate.

Multiparametric MRI of prostate cancer: An update on state‐of‐the‐art techniques and their performance in detecting and localizing prostate cancer

“…Shukla‐Dave et al (75) recommended incorporating the polyamine resonance into the spectroscopic analysis along with the (Cho+Cr)/Cit ratio, although this has not been widely adopted. Nonetheless, the reported values for (Cho+Cr)/Cit ratios to date have contributions from the polyamine resonances, and further studies with multidimensional MRS sequences (76) may prove valuable in obtaining a more complete understanding of the 3.0 to 3.2 ppm spectral region. Additionally, the aforementioned issue of chronic prostatitis is also thought to be a confounder in MRSI data, as its presence lowers the citrate concentration and increases the Cho concentration inappropriately raising suspicion for cancer in benign tissue (52).…”

Two-dimensional linear-combination model fitting of magnetic resonance spectra to define the macromolecule baseline using FiTAID, a Fitting Tool for Arrays of Interrelated Datasets

“…For clinical 1D MR spectra, modeling in the form of linear combinations of model spectra has become the gold standard and several software packages have been described and are available on a commercial or non-commercial basis [1][2][3] (recently reviewed in [4]). 2D modeling methods have only been used in isolated methodological studies [5][6][7][8][9][10][11][12] and the required tools are not broadly available. Furthermore, previous work was mostly focused on a single type of 2D experiment.…”

On the use of Cramér–Rao minimum variance bounds for the design of magnetic resonance spectroscopy experiments

“…Given that metabolite signals in a proton MR spectrum usually have considerable overlap that makes the quantification difficult, generally, one of three different approaches is taken: 1) use of a single non-specific one-dimensional spectrum (e.g. a localized short echo time (TE) spectrum) followed by linear combination model fitting based on prior knowledge about the constituent metabolites and spectral parameters (Provencher, 1993;Ratiney et al, 2005;Slotboom et al, 1998;Wilson et al, 2011), or 2) use of a dedicated (socalled editing) one-dimensional experiment optimized for exclusive or selective sensitivity for a single metabolite of interest, usually followed by simple model peak fitting or signal integration (Allen et al, 1997), or 3) use of a standard localized two-dimensional MR spectrum followed by peak integration (Thomas et al, 1996;Thomas et al, 2001) or prior knowledge fitting Gonenc et al, 2010;Kiefer et al, 1998;Kreis et al, 2005;; Thomas et al, 2008;van Ormondt et al, 1990;Vanhamme et al, 1999). In cases 1 and 3, the choice of experimental parameters like TE and repetition time (TR) is most often based on general considerations about maximum signal for given relaxation times, insensitivity to changes in relaxation times or arguments about minimization of macromolecular baseline contributions, while in case 2 the signal yield of wanted and unwanted metabolites and their relative overlap is modeled based on quantum mechanical simulations or solution measurements.…”