Characterization of gradient echo signal decays in healthy and cancerous prostate at 3T improves with a Gaussian augmentation of the mono-exponential (GAME) model

Abstract

A biomarker of cancer aggressiveness, such as hypoxia, could substantially impact treatment decisions in the prostate, especially radiation therapy, by balancing treatment morbidity (urinary incontinence, erectile dysfunction, etc.) against mortality. R2* mapping with Mono-Exponential (ME) decay modeling has shown potential for identifying areas of prostate cancer hypoxia at 1.5T. However, Gaussian deviations from ME decay have been observed in other tissues at 3T. The purpose of this study is to assess whether gradient-echo signal decays are better characterized by a standard ME decay model, or a Gaussian Augmentation of the Mono-Exponential (GAME) decay model, in the prostate at 3T. Multi-gradient-echo signals were acquired on 20 consecutive patients with a clinical suspicion of prostate cancer undergoing MR-guided prostate biopsies. Data were fitted with both ME and GAME models. The information content of these models were compared using Akaike’s Information Criterion (second-order, AICC), in skeletal muscle, the prostate central gland (CG), and peripheral zone (PZ) regions-of-interest (ROIs). The GAME model had higher information content in 30% of the prostate on average (across all patients and ROIs), covering up to 67% of cancerous PZ ROIs, and up to 100% of cancerous CG ROIs (in individual patients). The higher information content of GAME became more prominent in regions that would be assumed hypoxic using ME alone, reaching 50% of the PZ and 70% of the CG as ME R2* approached 40 s−1. R2* mapping may have important applications in MRI; however, information lost due to modeling could mask differences in parameters due to underlying tissue anatomy or physiology. The GAME model improves characterization of signal behavior in the prostate at 3T, and may increase the potential for determining correlates of fit parameters with biomarkers, such as of oxygenation status.

A new concept for improved quantitative analysis of reversible transverse relaxation in tissues with variable microscopic field distribution

“…As mentioned previously, it was recently reported that the microscopic frequency distribution in biological tissue is sometimes found to be more similar to Gaussian than to Lorentzian shape. 13,14 Based on this finding, one may ask whether there is a tendency to just one of these two distributions for each pixel, or whether a more generalized model allowing further distributions in between Gaussian and Lorentzian shape would be preferable. To examine this issue, it is beneficial to unify the different models (Lorentzian vs Gaussian distribution) in a new more general approach: For further analysis, three distribution types were considered: namely, the Lorentzian distribution, the Gaussian distribution, and the so-called "symmetric alphastable" distribution.…”

“…[9][10][11][12] More recent works by Mulkern et al have shown clear deviations of the susceptibility-related signal decay from mono-exponential characteristics in brain 13 and prostate tissue. 14 It was demonstrated that those tissues often show a more Gaussian frequency distribution inside areas contributing to single pixels, reflecting a nearly Gaussian microscopic field distribution. The typical nearly Gaussian lineshape characteristics of signals in volumeselective spectra recorded in vivo support this assumption.…”

In vivo measurements of irreversible and reversible transverse relaxation rates in human basal ganglia at 7 T: making inferences about the microscopic and mesoscopic structure of iron and calcification deposits

“…Finally, a remark on our use of the Gaussian model rather than the Lorentzian to fit GESSE data, leading to reversible transverse relaxation rates being characterized by σ rather than R 2 ´: while we recognize that the assumption of a Lorentzian distribution of intra‐voxel precession frequencies (with width parameter R 2 ´) is likely to be more familiar to the reader, we note that, in addition to the data presented here, a number of recent studies have shown experimental support for the idea that this distribution is sometimes better modeled as a Gaussian (with width parameter σ ). These include studies of a variety of organs, such as brain, tooth, lung, prostate and uterus . It remains unclear, however, exactly when and why Gaussian rather than Lorentzian intra‐voxel frequency distributions might arise—a topic worthy of further investigation, whether by experiment or by theory …”

Visualization of calcium phosphate cement in teeth by zero echo time 1H MRI at high field

“…This model assumes that the intra‐voxel frequency distribution responsible for the reversible relaxation component is Gaussian rather than Lorentzian in shape, which is particularly relevant at higher field when this component becomes more prominent in T 2 * relaxation. It has been successfully used for T 2 * determinations from gradient‐echo measurements of human brain and prostate and gynecologic cancers at 3 T . In this study it was applied for the first time to estimate the T 2 * values of teeth and engineered tissue.…”

“…With the multi‐TE UTE data, the T 2 * values of fresh CPC, i.e. restored in human teeth and goat teeth at TP1, as well as the corresponding dental components (enamel and dentin), were estimated using the mono‐exponential (ME) model: and the GAME model: where S 0 is the pseudo‐spin density and ~2.35 σ represents the full width at half‐maximum (FWHM) of the Gaussian frequency distribution responsible for the reversible transverse relaxation rate …”