Field-Cycling MRI for Identifying Minor Ischemic Stroke Below 0.2 T.

Background Field-cycling imaging (FCI) is a new technology developed at the University of Aberdeen that measures change in T1 relaxation time constant of tissues over a range of low magnetic field strengths (0.2-200 mT) by rapidly switching between different fields during the pulse sequence. This provides new sources of contrast, including some invisible to clinical MRI scanners, and may be a useful alternative imaging modality for stroke. Purpose To test whether a prototype whole-body FCI scanner can be used to identify infarct regions in patients with subacute ischemic stroke. Materials and Methods This prospective study screened consecutive adult patients admitted to a single center stroke unit from February 2018 to March 2020 and April to December 2021. Included participants with confirmed ischemic stroke underwent FCI 1-6 days after ictus. FCI scans were obtained at four to six evolution fields between 0.2 mT and 0.2 T, with five evolution times from 5 to 546 msec. T1 maps were generated. The Wilcoxon signed-rank test was used to compare infarct region and contralateral unaffected brain, and Spearman rank correlation was used to examine associations between infarct to contralateral tissue contrast ratio and field strengths. Two independent readers blinded to clinical images rated the FCI scans. Results Nine participants (mean age, 62 years ± 16 [SD]; all male) successfully completed FCI. FCI scans below 0.2 T exhibited hyperintense T1 regions corresponding to the infarct region identified at baseline imaging, visually confirmed with 86% interrater agreement (Cohen κ = 0.69). Infarct to contralateral tissue contrast ratio increased as magnetic field decreased between 0.2 mT and 0.2 T (r[24] = -0.68; P < .001). T1 dispersion slopes differed between infarct and unaffected tissues (median, 0.23 [IQR, 0.18-0.37] vs 0.35 [IQR, 0.27-0.43]; P = .03). Conclusion Whole-brain FCI can be used to identify subacute ischemic stroke by T1 relaxation mechanisms at field strengths as low as 0.2 mT. Research Registry no. 1813 Published under a CC BY 4.0 license. Supplemental material is available for this article.

Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy.

OBJECTIVES: Despite improved survival due to new treatments, the 10-year survival rate in patients with breast cancer is approximately 75%. Lymphovascular invasion (LVI), a prognostic marker independent from histological grade and stage, can only be fully determined at final histological examination. Lipid composition is deregulated in tumour via de novo lipogenesis, with alteration in lipogenic genes in LVI. We hypothesise alteration in lipid composition derived from novel non-invasive spectroscopy method is associated with LVI positivity. METHODS: Thirty female patients (age 39-78) with invasive ductal carcinoma were enrolled, with 13 LVI negative and 17 LVI positive. Saturated, monounsaturated, polyunsaturated fatty acids and triglycerides (SFA, MUFA, PUFA and TRG) were quantified from ex vivo breast tumours freshly excised from patients on a 3 T clinical MRI scanner, and proliferative activity marker Ki-67 and serotonin derived histologically. RESULTS: There were significantly lower MUFA (p = 0.0189) in LVI positive (median: 0.37, interquartile range (IQR): 0.25-0.64) than negative (0.63, 0.49-0.96). There were significantly lower TRG (p = 0.0226) in LVI positive (1.32, 0.95-2.43) than negative (2.5, 1.92-4.15). There was no significant difference in SFA (p = 0.6009) or PUFA (p = 0.1641). There was no significant correlation between lipid composition against Ki-67 or serotonin, apart from a borderline negative correlation between PUFA and serotonin (r = - 0.3616, p = 0.0496). CONCLUSION: Lipid composition might provide a biomarker to study lymphovascular invasion in breast cancer. KEY POINTS: • Monounsaturated fatty acids in lymphovascular invasion (LVI) positive invasive breast carcinoma were significantly lower than that in LVI negative. • Triglycerides in LVI positive invasive breast carcinoma were significantly lower than that in LVI negative. • Lipid composition from MR spectroscopy reflects the rate of de novo lipogenesis and provides a potential biomarker independent from histological grade and stage.

Phased-array combination of 2D MRS for lipid composition quantification in patients with breast cancer.

Lipid composition in breast cancer, a central marker of disease progression, can be non-invasively quantified using 2D MRS method of double quantum filtered correlation spectroscopy (DQF-COSY). The low signal to noise ratio (SNR), arising from signal retention of only 25% and depleted lipids within tumour, demands improvement approaches beyond signal averaging for clinically viable applications. We therefore adapted and examined combination algorithms, designed for 1D MRS, for 2D MRS with both internal and external references. Lipid composition spectra were acquired from 17 breast tumour specimens, 15 healthy female volunteers and 25 patients with breast cancer on a clinical 3 T MRI scanner. Whitened singular value decomposition (WSVD) with internal reference yielded maximal SNR with an improvement of 53.3% (40.3-106.9%) in specimens, 84.4 ± 40.6% in volunteers, 96.9 ± 54.2% in peritumoural adipose tissue and 52.4% (25.1-108.0%) in tumours in vivo. Non-uniformity, as variance of improvement across peaks, was low at 21.1% (13.7-28.1%) in specimens, 5.5% (4.2-7.2%) in volunteers, 6.1% (5.0-9.0%) in peritumoural tissue, and 20.7% (17.4-31.7%) in tumours in vivo. The bias (slope) in improvement ranged from - 1.08 to 0.21%/ppm along the diagonal directions. WSVD is therefore the optimal algorithm for lipid composition spectra with highest SNR uniformly across peaks, reducing acquisition time by up to 70% in patients, enabling clinical applications.

Optimal Phased-Array Signal Combination For Polyunsaturated Fatty Acids Measurement In Breast Cancer Using Multiple Quantum Coherence MR Spectroscopy At 3T.

Polyunsaturated fatty acid (PUFA), a key marker in breast cancer, is non-invasively quantifiable using multiple quantum coherence (MQC) magnetic resonance spectroscopy (MRS) at the expense of losing half of the signal. Signal combination for phased array coils provides potential pathways to enhance the signal to noise ratio (SNR), with current algorithms developed for conventional brain MRS. Since PUFA spectra and the biochemical environment in the breast deviate significantly from those in the brain, we set out to identify the optimal algorithm for PUFA in breast cancer. Combination algorithms were compared using PUFA spectra from 17 human breast tumour specimens, 15 healthy female volunteers, and 5 patients with breast cancer on a clinical 3 T MRI scanner. Adaptively Optimised Combination (AOC) yielded the maximum SNR improvement in specimens (median, 39.5%; interquartile range: 35.5-53.2%, p < 0.05), volunteers (82.4 ± 37.4%, p < 0.001), and patients (median, 61%; range: 34-105%, p < 0.05), while independent from voxel volume (rho = 0.125, p = 0.632), PUFA content (rho = 0.256, p = 0.320) or water/fat ratio (rho = 0.353, p = 0.165). Using AOC, acquisition in patients is 1.5 times faster compared to non-noise decorrelated algorithms. Therefore, AOC is the most suitable current algorithm to improve SNR or accelerate the acquisition of PUFA MRS from breast in a clinical setting.