Towards applying NMR relaxometry as a diagnostic tool for bone and soft tissue sarcomas: a pilot study

Universal 1H Spin-Lattice NMR Relaxation Features of Sugar-A Step towards Quality Markers

1H fast field-cycling and time-domain nuclear magnetic resonance relaxometry studies have been performed for 15 samples of sugar of different kinds and origins (brown, white, cane, beet sugar). The extensive data set, including results for crystal sugar and sugar/water mixtures, has been thoroughly analyzed, with a focus on identifying relaxation contributions associated with the solid and liquid fractions of the systems and non-exponentiality of the relaxation processes. It has been observed that 1H spin-lattice relaxation rates for crystal sugar (solid) vary between 0.45 s-1 and 0.59 s-1, and the relaxation process shows only small deviations from exponentiality (a quantitative measure of the exponentiality has been provided). The 1H spin-lattice relaxation process for sugar/water mixtures has turned out to be bi-exponential, with the relaxation rates varying between about 13 s-1-17 s-1 (for the faster component) and about 2.1 s-1-3.5 s-1 (for the slower component), with the ratio between the amplitudes of the relaxation contributions ranging between 2.8 and 4.2. The narrow ranges in which the parameters vary make them a promising marker of the quality and authenticity of sugar.

Physics-Informed Discretization for Reproducible and Robust Radiomic Feature Extraction Using Quantitative MRI

OBJECTIVE

Given the limited repeatability and reproducibility of radiomic features derived from weighted magnetic resonance imaging (MRI), there may be significant advantages to using radiomics in conjunction with quantitative MRI. This study introduces a novel physics-informed discretization (PID) method for reproducible radiomic feature extraction and evaluates its performance using quantitative MRI sequences including magnetic resonance fingerprinting (MRF) and apparent diffusion coefficient (ADC) mapping.

MATERIALS AND METHODS

A multiscanner, scan-rescan dataset comprising whole-brain 3D quantitative (MRF T1, MRF T2, and ADC) and weighted MRI (T1w MPRAGE, T2w SPACE, and T2w FLAIR) from 5 healthy subjects was prospectively acquired. Subjects underwent 2 repeated acquisitions on 3 distinct 3 T scanners each, for a total of 6 scans per subject (30 total scans). First-order statistical (n = 23) and second-order texture (n = 74) radiomic features were extracted from 56 brain tissue regions of interest using the proposed PID method (for quantitative MRI) and conventional fixed bin number (FBN) discretization (for quantitative MRI and weighted MRI). Interscanner radiomic feature reproducibility was measured using the intraclass correlation coefficient (ICC), and the effect of image sequence (eg, MRF T1 vs T1w MPRAGE), as well as image discretization method (ie, PID vs FBN), on radiomic feature reproducibility was assessed using repeated measures analysis of variance. The robustness of PID and FBN discretization to segmentation error was evaluated by simulating segmentation differences in brainstem regions of interest. Radiomic features with ICCs greater than 0.75 following simulated segmentation were determined to be robust to segmentation.

RESULTS

First-order features demonstrated higher reproducibility in quantitative MRI than weighted MRI sequences, with 30% (n = 7/23) features being more reproducible in MRF T1 and MRF T2 than weighted MRI. Gray level co-occurrence matrix (GLCM) texture features extracted from MRF T1 and MRF T2 were significantly more reproducible using PID compared with FBN discretization; for all quantitative MRI sequences, PID yielded the highest number of texture features with excellent reproducibility (ICC > 0.9). Comparing texture reproducibility of quantitative and weighted MRI, a greater proportion of MRF T1 (n = 225/370, 61%) and MRF T2 (n = 150/370, 41%) texture features had excellent reproducibility (ICC > 0.9) compared with T1w MPRAGE (n = 148/370, 40%), ADC (n = 115/370, 32%), T2w SPACE (n = 98/370, 27%), and FLAIR (n = 102/370, 28%). Physics-informed discretization was also more robust than FBN discretization to segmentation error, as 46% (n = 103/222, 46%) of texture features extracted from quantitative MRI using PID were robust to simulated 6 mm segmentation shift compared with 19% (n = 42/222, 19%) of weighted MRI texture features extracted using FBN discretization.

CONCLUSIONS

The proposed PID method yields radiomic features extracted from quantitative MRI sequences that are more reproducible and robust than radiomic features extracted from weighted MRI using conventional (FBN) discretization approaches. Quantitative MRI sequences also demonstrated greater scan-rescan robustness and first-order feature reproducibility than weighted MRI.

Zero- to low-field relaxometry of chemical and biological fluids

Nuclear magnetic resonance (NMR) relaxometry is an analytical method that provides information about molecular environments, even for NMR "silent" molecules (spin-0), by analyzing the properties of NMR signals versus the magnitude of the longitudinal field. Conventionally, this technique is performed at fields much higher than Earth's magnetic field, but our work focuses on NMR relaxometry at zero and ultra-low magnetic fields (ZULFs). Operating under such conditions allows us to investigate slow (bio)chemical processes occurring on a timescale from milliseconds to seconds, which coincide with spin evolution. ZULFs also minimize T2 line broadening in heterogeneous samples resulting from magnetic susceptibility. Here, we use ZULF NMR relaxometry to analyze (bio)chemical compounds containing 1H-13C, 1H-15N, and 1H-31P spin pairs. We also detected high-quality ULF NMR spectra of human whole-blood at 0.8 μT, despite a shortening of spin relaxation by blood proteomes (e.g., hemoglobin). Information on proton relaxation times of blood, a potential early biomarker of inflammation, can be acquired in under a minute using inexpensive, portable/small-size NMR spectrometers based on atomic magnetometers.

Water Dynamics in Highly Concentrated Protein Systems-Insight from Nuclear Magnetic Resonance Relaxometry

¹H spin-lattice relaxation experiments have been performed for water-Bovine Serum Albumin (BSA) mixtures, including 20%wt and 40%wt of BSA. The experiments have been carried out in a frequency range encompassing three orders of magnitude, from 10 kHz to 10 MHz, versus temperature. The relaxation data have been thoroughly analyzed in terms of several relaxation models with the purpose of revealing the mechanisms of water motion. For this purpose, four relaxation models have been used: the data have been decomposed into relaxation contributions expressed in terms of Lorentzian spectral densities, then three-dimensional translation diffusion has been assumed, next two-dimensional surface diffusion has been considered, and eventually, a model of surface diffusion mediated by acts of adsorption to the surface has been employed. In this way, it has been demonstrated that the last concept is the most plausible. Parameters describing the dynamics in a quantitative manner have been determined and discussed.

On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping

Soft tissue sarcomas (STS) prognosis is disappointing, with current treatment strategies being based on a "fit for all" principle and not taking distinct sarcoma subtypes specificities and genetic/metabolic differences into consideration. The paucity of precision therapies in STS reflects the shortage of studies that seek to decipher the sarcomagenesis mechanisms. There is an urge to improve STS diagnosis precision, refine STS classification criteria, and increase the capability of identifying STS prognostic biomarkers. Single-omics and multi-omics studies may play a key role on decodifying sarcomagenesis. Metabolomics provides a singular insight, either as a single-omics approach or as part of a multi-omics strategy, into the metabolic adaptations that support sarcomagenesis. Although STS metabolome is scarcely characterized, untargeted and targeted metabolomics approaches employing different data acquisition methods such as mass spectrometry (MS), MS imaging, and nuclear magnetic resonance (NMR) spectroscopy provided important information, warranting further studies. New chromatographic, MS, NMR-based, and flow cytometry-based methods will offer opportunities to therapeutically target metabolic pathways and to monitorize the response to such metabolic targeting therapies. Here we provide a comprehensive review of STS omics applications, comprising a detailed analysis of studies focused on the metabolic landscape of these tumors.

Intracellular Water Lifetime as a Tumor Biomarker to Monitor Doxorubicin Treatment via FFC-Relaxometry in a Breast Cancer Model

This study aims to explore whether the water exchange rate constants in tumor cells can act as a hallmark of pathology status and a reporter of therapeutic outcomes. It has been shown, using 4T1 cell cultures and murine allografts, that an early assessment of the therapeutic effect of doxorubicin can be detected through changes in the cellular water efflux rate constant kio. The latter has been estimated by analyzing the magnetization recovery curve in standard NMR T1 measurements when there is a marked difference in the proton relaxation rate constants (R1) between the intra- and the extra-cellular compartments. In cellular studies, T1 measurements were carried out on a relaxometer working at 0.5 T, and the required difference in R1 between the two compartments was achieved via the addition of a paramagnetic agent into the extracellular compartment. For in-vivo experiments, the large difference in the R1 values of the two-compartments was achieved when the T1 measurements were carried out at low magnetic field strengths. This task was accomplished using a Fast Field Cycling (FFC) relaxometer that was properly modified to host a mouse in its probe head. The decrease in kio upon the administration of doxorubicin is the result of the decreased activity of Na+/K+-ATPase, as shown in an independent test on the cellular uptake of Rb ions. The results reported herein suggest that kio can be considered a non-invasive, early and predictive biomarker for the identification of responsive patients immediately from the first doxorubicin treatment.

Low-Field NMR Relaxometry for Intraoperative Tumour Margin Assessment in Breast-Conserving Surgery

Simple Summary

Breast cancer is the most diagnosed cancer for women, and clear surgical margins in breast-conserving surgery (BCS) are essential for preventing recurrence. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new tool for intraoperative margin assessment was evaluated. The technique allows the determination of the tissue proton relaxation rates as a function of the applied magnetic field on small tissue samples excised from surgical specimens, at the margins of tumour resection, prior to histopathological analysis. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved. The discriminating ability shown by the relaxometric assay relies mainly on the difference of fat/water content between healthy and tumour cells. The information obtained has the potential to support the surgeon in real-time margin assessment during BCS.

Abstract

As conserving surgery is routinely applied for the treatment of early-stage breast cancer, the need for new technology to improve intraoperative margin assessment has become increasingly important. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new diagnostic tool was evaluated. The technique allows the determination of the tissue proton relaxation rates (R₁), as a function of the applied magnetic field, which are affected by the changes in the composition of the mammary gland tissue occurring during the development of neoplasia. The study involved 104 small tissue samples obtained from surgical specimens destined for histopathology. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved by using two quantifiers, namely (i) the slope of the line joining the R₁ values measured at 0.02 and 1 MHz and (ii) the sum of the R₁ values measured at 0.39 and 1 MHz. The method is fast, and it does not rely on the expertise of a pathologist or cytologist. The obtained results suggest that a simplified, low-cost, automated instrument might compete well with the currently available tools in margin assessment.

Joint multi-field T1 quantification for fast field-cycling MRI

Purpose

Recent developments in hardware design enable the use of fast field‐cycling (FFC) techniques in MRI to exploit the different relaxation rates at very low field strength, achieving novel contrast. The method opens new avenues for in vivo characterizations of pathologies but at the expense of longer acquisition times. To mitigate this, we propose a model‐based reconstruction method that fully exploits the high information redundancy offered by FFC methods.

Methods

The proposed model‐based approach uses joint spatial information from all fields by means of a Frobenius ‐ total generalized variation regularization. The algorithm was tested on brain stroke images, both simulated and acquired from FFC patients scans using an FFC spin echo sequences. The results are compared to three non‐linear least squares fits with progressively increasing complexity.

Results

The proposed method shows excellent abilities to remove noise while maintaining sharp image features with large signal‐to‐noise ratio gains at low‐field images, clearly outperforming the reference approach. Especially patient data show huge improvements in visual appearance over all fields.

Conclusion

The proposed reconstruction technique largely improves FFC image quality, further pushing this new technology toward clinical standards.