scholarly journals Applications of Continuous Wave Free Precession Sequences in Low-Field, Time-Domain NMR

2019 ◽  
Vol 9 (7) ◽  
pp. 1312 ◽  
Author(s):  
Tiago Bueno Moraes ◽  
Tatiana Monaretto ◽  
Luiz Colnago

This review discusses the theory and applications of the Continuous Wave Free Precession (CWFP) sequence in low-field, time-domain nuclear magnetic resonance (TD-NMR). CWFP is a special case of the Steady State Free Precession (SSFP) regime that is obtained when a train of radiofrequency pulses, separated by a time interval Tp shorter than the effective transverse relaxation time (T2*), is applied to a sample. Unlike regular pulsed experiments, in the CWFP regime, the amplitude is not dependent on T1. Therefore, Tp should be as short as possible (limited by hardware). For Tp < 0.5 ms, thousands of scans can be performed per second, and the signal to noise ratio can be enhanced by more than one order of magnitude. The amplitude of the CWFP signal is dependent on T1/T2; therefore, it can be used in quantitative analyses for samples with a similar relaxation ratio. The time constant to reach the CWFP regime (T*) is also dependent on relaxation times and flip angle (θ). Therefore, T* has been used as a single shot experiment to measure T1 using a low flip angle (5°) or T2, using θ = 180°. For measuring T1 and T2 simultaneously in a single experiment, it is necessary to use θ = 90°, the values of T* and M0, and the magnitude of CWFP signal |Mss|. Therefore, CWFP is an important sequence for TD-NMR, being an alternative to the Carr-Purcell-Meiboom-Gill sequence, which depends only on T2. The use of CWFP for the improvement of the signal to noise ratio in quantitative and qualitative analyses and in relaxation measurements are presented and discussed.

2018 ◽  
Vol 57 (9) ◽  
pp. 616-625 ◽  
Author(s):  
Tatiana Monaretto ◽  
Andre Souza ◽  
Tiago Bueno Moraes ◽  
Victor Bertucci-Neto ◽  
Corinne Rondeau-Mouro ◽  
...  

2021 ◽  
pp. 20210465
Author(s):  
Tsutomu Tamada ◽  
Ayumu Kido ◽  
Yu Ueda ◽  
Mitsuru Takeuchi ◽  
Takeshi Fukunaga ◽  
...  

Objective: High b-value diffusion-weighted imaging (hDWI) with a b-value of 2000 s/mm2 provides insufficient image contrast between benign and malignant tissues and an overlap of apparent diffusion coefficient (ADC) between Gleason grades (GG) in prostate cancer (PC). We compared image quality, PC detectability, and discrimination ability for PC aggressiveness between ultra-high b-value DWI (uhDWI) of 3000 s/mm2 and hDWI. Methods: The subjects were 49 patients with PC who underwent 3T multiparametric MRI. Single-shot echo-planar DWI was acquired with b-values of 0, 2000, and 3000 s/mm2. Anatomical distortion of prostate (AD), signal intensity of benign prostate (PSI), and lesion conspicuity score (LCS) were assessed using a 4-point scale; and signal-to-noise ratio, contrast-to-noise ratio, and mean ADC (×10–3 mm2/s) of lesion (lADC) and surrounding benign region (bADC) were measured. Results: PSI was significantly lower in uhDWI than in hDWI (p < 0.001). AD, LCS, signal-to-noise ratio, and contrast-to-noise ratio were comparable between uhDWI and hDWI (all p > 0.05). In contrast, lADC was significantly lower than bADC in both uhDWI and hDWI (both p < 0.001). In comparison of lADC between tumors of ≤GG2 and those of ≥GG3, both uhDWI and hDWI showed significant difference (p = 0.007 and p = 0.021, respectively). AUC for separating tumors of ≤GG2 from those of ≥GG3 was 0.731 in hDWI and 0.699 in uhDWI (p = 0.161). Conclusion: uhDWI suppressed background signal better than hDWI, but did not contribute to increased diagnostic performance in PC. Advances in knowledge: Compared with hDWI, uhDWI could not contribute to increased diagnostic performance in PC.


2013 ◽  
Vol 38 (20) ◽  
pp. 4197 ◽  
Author(s):  
Thorsten Göbel ◽  
Dennis Stanze ◽  
Björn Globisch ◽  
Roman J. B. Dietz ◽  
Helmut Roehle ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1445 ◽  
Author(s):  
Bronisław Stec ◽  
Waldemar Susek

2014 ◽  
Vol 20 (6) ◽  
pp. 284-290 ◽  
Author(s):  
Gabriele Adamo ◽  
Antonino Parisi ◽  
Salvatore Stivala ◽  
Alessandro Tomasino ◽  
Diego Agro ◽  
...  

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