Quantification of prostate MRSI data by model‐based time domain fitting and frequency domain analysis

Abstract

This paper compares two spectral processing methods for obtaining quantitative measures from in vivo prostate spectra, evaluates their effectiveness, and discusses the necessary modifications for accurate results. A frequency domain analysis (FDA) method based on peak integration was compared with a time domain fitting (TDF) method, a model-based nonlinear least squares fitting algorithm. The accuracy of both methods at estimating the choline + creatine + polyamines to citrate ratio (CCP:C) was tested using Monte Carlo simulations, empirical phantom MRSI data and in vivo MRSI data. The paper discusses the different approaches employed to achieve the quantification of the overlapping choline, creatine and polyamine resonances. Monte Carlo simulations showed induced biases on the estimated CCP:C ratios. Both methods were successful in identifying tumor tissue, provided that the CCP:C ratio was greater than a given (normal) threshold. Both methods predicted the same voxel condition in 94% of the in vivo voxels (68 out of 72). Both TDF and FDA methods had the ability to identify malignant voxels in an artifact-free case study using the estimated CCP:C ratio. Comparing the ratios estimated by the TDF and the FDA, the methods predicted the same spectrum type in 17 out of 18 voxels of the in vivo case study (94.4%).

Quantification of non–water‐suppressed MR spectra with correction for motion‐induced signal reduction

“…Previous reports have shown that frequency-domain or time-domain parametric modeling can achieve consistent quantification for metabolites (14,15). Therefore, we expect that both frequency-domain and time-domain methods can benefit from NWS MRS because of the high SNR of water signal.…”

Clinical Stage T1c Prostate Cancer: Evaluation with Endorectal MR Imaging and MR Spectroscopic Imaging

“…Choline and creatine integration ranges may contain polyamines because the polyamine peak resides between them and cannot be completely separated. Therefore, the choline plus creatine-citrate ratio may be interpreted as the choline plus polyamine plus creatine-citrate ratio, as has been described previously (18). All endorectal MR imaging-MR spectroscopic imaging data were downloaded to the departmental picture archiving and communication system (Centricity RA 1000; GE Medical Systems).…”

“…The spectroscopist was blinded to all clinical and surgical-pathologic findings except the fact that all patients were considered to have clinical stage T1c prostate cancer. Voxels in the peripheral (14,15,18,19) and transition (20) zones of the prostate gland were judged to be suspicious on the basis of established metabolic criteria, without reference to the MR findings. Subsequently, the radiologists reviewed the MR spectroscopic imaging results and, with knowledge of the MR imaging scores, assigned new scores for the presence of tumor, extracapsular extension, seminal vesicle invasion, and adjacent organ invasion on the basis of combined endorectal MR imaging-MR spectroscopic imaging data and by using the same five-point scale.…”

A comparison of two post-processing analysis methods to quantify cerebral metabolites measuredviaproton magnetic resonance spectroscopy in HIV disease

“…11 The scope of 1 H-MRS in clinical medicine is expanding, 12 but the use of this method requires accurate post-acquisition quantification of the 1 H-MRS spectra. 13 Prior work has been undertaken to compare the sensitivity of quantification methods over a range of diseased states, 14,15 but to our knowledge, no comparisons have been made of quantification models in the analysis of cerebral metabolites in HIV disease. Although such comparisons should not differ in HIV disease compared with other disease states, data on the utility of these software packages within the specific disease area provides clinical researchers with the confidence to use such modalities within a clinical research setting.…”