Pulse Sequence Research Articles

A digital twin for parallel liquid-state nuclear magnetic resonance spectroscopy

One approach to increasing nuclear magnetic resonance measurement sample throughput is to implement multiple, independent detection sites. However, the presence of radio frequency interference poses a challenge in multi-detector systems, particularly in unshielded coil arrays lacking sufficient electrical isolation. This issue can lead to unwanted coupling of inductive coils, resulting in excitation pulse interference and signal transfer among multiple detection sites. Here we propose a theoretical framework that combines electromagnetic simulation with spin-dynamic calculations. This framework enables the evaluation of coil coupling effects, the design of parallel pulse sequences to mitigate inter-channel coupling, and the separation of composite free induction decays obtained from multiple detectors. The parallel pulse compensation scheme was validated by a 2-channel parallel spectroscopy experiment. These results provide valuable insights for the design of parallel nuclear magnetic resonance hardware and for exploring the limits of parallelization capacity within a fixed magnet system.

Assessment of traumatic mandibular nerve using MR neurography sequence: a preliminary study

BackgroundIatrogenic mandibular nerve damage resulting from oral surgeries and dental procedures is painful and a formidable challenge for patients and oral surgeons alike, mainly because the absence of objective and quantitative methods for diagnosing nerve damage renders treatment and compensation ambiguous while often leading to medico-legal disputes. The aim of this study was to examine discriminating factors of traumatic mandibular nerve within a specific magnetic resonance imaging (MRI) protocol and to suggest tangible diagnostic criteria for peripheral trigeminal nerve injury.MethodsTwenty-six patients with ipsilateral mandibular nerve trauma underwent T2 Flex water, 3D short tau inversion recovery (STIR), and diffusion-weighted imaging (DWI) acquired by periodically rotating overlapping parallel lines with enhanced reconstruction (PROPELLER) pulse sequences; 26 injured nerves were thus compared with contra-lateral healthy nerves at anatomically corresponding sites. T2 Flex apparent signal to noise ratio (FSNR), T2 Flex apparent nerve-muscle contrast to noise ratio (FNMCNR) 3D STIR apparent signal to noise ratio (SSNR), 3D STIR apparent nerve-muscle contrast to noise ratio (SNMCNR), apparent diffusion coefficient (ADC) and area of cross-sectional nerve (Area) were evaluated.ResultsMixed model analysis revealed FSNR and FNMCNR to be the dual discriminators for traumatized mandibular nerve (p < 0.05). Diagnostic performance of both parameters was also determined with area under the receiver operating characteristic curve (AUC for FSNR = 0.712; 95% confidence interval [CI]: 0.5660, 0.8571 / AUC for FNMCNR = 0.7056; 95% confidence interval [CI]: 1.011, 1.112).ConclusionsAn increase in FSNR and FNMCNR within our MRI sequence seems to be accurate indicators of the presence of traumatic nerve. This prospective study may serve as a foundation for sophisticated model diagnosing trigeminal nerve trauma within large patient cohorts.

Generation and autocorrelation traces investigation of Nyquist pulse sequences

We propose a novel approach for generating Nyquist pulse sequences using a dual parallel Mach-Zehnder modulator (DPMZM) and a phase modulator (PM). The generated Nyquist pulse sequence achieves a repetition frequency of 10 GHz and a full width at half maximum (FWHM) of 4.22 ps. The time-domain waveforms of these sequences are retrieved using the phase and intensity from cross-correlation and spectrum only (PICASO) method. Further investigation into the autocorrelation traces reveals a pulse width conversion factor of approximately 0.75 between the Nyquist pulse sequences and their autocorrelation traces. Our work offers an alternative approach to generating and measuring Nyquist pulse sequences.

Preparation, characterization of violet phosphorus and its application in fiber laser

Violet phosphorus (VP) is a new type of two-dimensional nanomaterial that has unique electronic and optoelectronic properties, and has gained wide attention in the fields of physics, chemistry, and materials science. However, only a few instances of the use of VP in fiber lasers have been demonstrated. For instance, VP films have been utilized as saturable absorbers in Q-switched ytterbium-doped fiber lasers (YDFL) and erbium-doped fiber lasers (EDFL), operating at central wavelengths of 1033 nm and 1560 nm, respectively. Herein, VP films are prepared using a liquid phase exfoliation method and introduced in the ring cavity of a YDFL. Increasing the pump power from 113 mW to 245 mW, and repetition rates from 32.33 kHz to 107.12 kHz, resulted in a stable sequence of Q-switched pulses. A pulse width of 2.9 µs is obtained at a pump power of 245 mW. At a pump power of 230 mW, the pulse energy is 31.02 nJ. In the case of EDFL, stable Q-switched pulses are obtained at a maximum pump power of 150 mW, with the repetition rate, pulse width and pulse energy being 63.51 kHz, 6.4 µs, and 102.19 nJ, respectively. These results indicate that VP may be a promising broadband SA suitable for fiber lasers with wavelengths of 1 µm and 1.5 µm.

Cross polarization stability in multidimensional NMR spectroscopy of biological solids

Magic-angle spinning (MAS) solid-state nuclear magnetic resonance (SSNMR) spectroscopy is a powerful and versatile technique for probing structure and dynamics in large, insoluble biological systems at atomic resolution. With many recent advances in instrumentation and polarization methods, technology development in SSNMR remains an active area of research and presents opportunities to further improve data collection, processing, and analysis of samples with low sensitivity and complex tertiary and quaternary structures. SSNMR spectra are often collected as multidimensional data, requiring stable experimental conditions to minimize signal fluctuations (t1 noise). In this work, we examine the factors adversely affecting signal stability as well as strategies used to mitigate them, considering laboratory environmental requirements, configuration of amplifiers, and pulse sequence parameter selection. We show that Thermopad® temperature variable attenuators (TVAs) can partially compensate for the changes in amplifier output power as a function of temperature and thereby ameliorate one significant source of instability for some spectrometers and pulse sequences. We also consider the selection of tangent ramped cross polarization (CP) waveform shapes, to balance the requirements of sensitivity and instrumental stability. These findings collectively enable improved stability and overall performance for CP-based multidimensional spectra of microcrystalline, membrane, and fibrous proteins performed at multiple magnetic field strengths.

Simulating multipulse NMR spectra of polycrystalline solids in the frequency domain.

An approach is presented for simulating multipulse nuclear magnetic resonance (NMR) spectra of polycrystalline solids directly in the frequency domain. The approach integrates the symmetry pathway concept for multipulse NMR with efficient algorithms for calculating spinning sideband amplitudes and performing interpolated finite-element numerical integration over all crystallite orientations in a polycrystalline sample. The numerical efficiency is achieved through a set of assumptions used to approximate the evolution of a sparse density matrix through a pulse sequence as a set of individual transition pathway signals. The utility of this approach for simulating the spectra of complex materials, such as glasses and other structurally disordered materials, is demonstrated.

Artificial intelligence in musculoskeletal imaging: realistic clinical applications in the next decade.

This article will provide a perspective review of the most extensively investigated deep learning (DL) applications for musculoskeletal disease detection that have the best potential to translate into routine clinical practice over the next decade. Deep learning methods for detecting fractures, estimating pediatric bone age, calculating bone measurements such as lower extremity alignment and Cobb angle, and grading osteoarthritis on radiographs have been shown to have high diagnostic performance with many of these applications now commercially available for use in clinical practice. Many studies have also documented the feasibility of using DL methods for detecting joint pathology and characterizing bone tumors on magnetic resonance imaging (MRI). However, musculoskeletal disease detection on MRI is difficult as it requires multi-task, multi-class detection of complex abnormalities on multiple image slices with different tissue contrasts. The generalizability of DL methods for musculoskeletal disease detection on MRI is also challenging due to fluctuations in image quality caused by the wide variety of scanners and pulse sequences used in routine MRI protocols. The diagnostic performance of current DL methods for musculoskeletal disease detection must be further evaluated in well-designed prospective studies using large image datasets acquired at different institutions with different imaging parameters and imaging hardware before they can be fully implemented in clinical practice. Future studies must also investigate the true clinical benefits of current DL methods and determine whether they could enhance quality, reduce error rates, improve workflow, and decrease radiologist fatigue and burnout with all of this weighed against the costs.

Deconvoluting Monomer- and Dimer-Specific Distance Distributions between Spin Labels in a Monomer/Dimer Mixture Using T1-Edited DEER EPR Spectroscopy.

Double electron-electron resonance (DEER) EPR is a powerful tool in structural biology, providing distances between pairs of spin labels. When the sample consists of a mixture of oligomeric species (e.g., monomer and dimer), the question arises as to how to assign the peaks in the DEER-derived probability distance distribution to the individual species. Here, we propose incorporating an EPR longitudinal electron relaxation (T1) inversion recovery experiment within a DEER pulse sequence to resolve this problem. The apparent T1 between dipolar coupled electron spins measured from the inversion recovery time (τinv) dependence of the peak intensities in the T1-edited DEER-derived probability P(r) distance distribution will be affected by the number of nitroxide labels attached to the biomolecule of interest, for example, two for a monomer and four for a dimer. We show that global fitting of all the T1-edited DEER echo curves, recorded over a range of τinv values, permits the deconvolution of distances between spin labels originating from monomeric (longer T1) and dimeric (shorter T1) species. This is especially useful when the trapping of spin labels in different conformational states during freezing gives rise to complex P(r) distance distributions. The utility of this approach is demonstrated for two systems, the β1 adrenergic receptor and a construct of the huntingtin exon-1 protein fused to the immunoglobulin domain of protein G, both of which exist in a monomer-dimer equilibrium.

A Strategy for Preparing Quantum Squeezed States Using Reinforcement Learning

AbstractA scheme leveraging reinforcement learning to engineer control fields for generating non‐classical states is proposed. It is exemplified by the application to prepare spin‐squeezed states for an open collective spin model where a linear control field is designed to govern the dynamics. The reinforcement learning agent determines the temporal sequence of control pulses, commencing from a coherent spin state in an environment characterized by dissipation and dephasing. Compared to the constant control scenario, this approach provides various control sequences maintaining collective spin squeezing and entanglement. It is observed that denser application of the control pulses enhances the performance of the outcomes. However, there is a minor enhancement in the performance by adding control actions. The proposed strategy demonstrates increased effectiveness for larger systems. Thermal excitations of the reservoir are detrimental to the control outcomes. Feasible experiments are suggested to implement this control proposal based on the comparison with the others. The extensions to continuous control problems and another quantum system are discussed. The replaceability of the reinforcement learning module is also emphasized. This research paves the way for its application in manipulating other quantum systems.

Contrast-Enhanced Magnetic Resonance Imaging Based T1 Mapping and Extracellular Volume Fractions Are Associated with Peripheral Artery Disease.

Extracellular volume fraction (ECV), measured with contrast-enhanced magnetic resonance imaging (CE-MRI), has been utilized to study myocardial fibrosis, but its role in peripheral artery disease (PAD) remains unknown. We hypothesized that T1 mapping and ECV differ between PAD patients and matched controls. A total of 37 individuals (18 PAD patients and 19 matched controls) underwent 3.0T CE-MRI. Skeletal calf muscle T1 mapping was performed before and after gadolinium contrast with a motion-corrected modified look-locker inversion recovery (MOLLI) pulse sequence. T1 values were calculated with a three-parameter Levenberg-Marquardt curve fitting algorithm. ECV and T1 maps were quantified in five calf muscle compartments (anterior [AM], lateral [LM], and deep posterior [DM] muscle groups; soleus [SM] and gastrocnemius [GM] muscles). Averaged peak blood pool T1 values were obtained from the posterior and anterior tibialis and peroneal arteries. T1 values and ECV are heterogeneous across calf muscle compartments. Native peak T1 values of the AM, LM, and DM were significantly higher in PAD patients compared to controls (all p < 0.028). ECVs of the AM and SM were significantly higher in PAD patients compared to controls (AM: 26.4% (21.2, 31.6) vs. 17.3% (10.2, 25.1), p = 0.046; SM: 22.7% (19.5, 27.8) vs. 13.8% (10.2, 19.1), p = 0.020). Native peak T1 values across all five calf muscle compartments, and ECV fractions of the anterior muscle group and the soleus muscle were significantly elevated in PAD patients compared with matched controls. Non-invasive T1 mapping and ECV quantification may be of interest for the study of PAD.

Individualization of petrol sources by high field nuclear magnetic resonance spectroscopy

In the forensic science context petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has been proven to be a challenge in the investigation of fire related incidents. This research explored the possibility of identification and classification of petrol sources using high field NMR spectroscopy. In this study, 1H NMR profiling, using specific pulse sequences to analyse neat aliquot petrol samples of different brands collected at different times across the UK and Ireland is shown, for the first time, to provide a diagnostic ‘fingerprint’ with specific chemical compounds that can be used for identification and classification of petrol samples. This enables linkage of unknown petrol samples to a source and in addition provides a tool which allows exclusion of potential petrol sources. A new, innovative method using 1H selTOCSY is described for the individualization and classification of petrol samples through the identification of olefinic markers in the samples. Those markers were identified as (i) 3-methyl-1-butene, (ii) a mixture of 1-pentene and 3-methyl-1-butene, (iii) 2-methyl-2-butene and (iv) a mixture of cis and trans-2-pentene.

Quantum double lock-in amplifier

Quantum lock-in amplifiers have been proposed to extract an alternating signal from a strong noise background. However, due to the typical target signal has unknown initial phase, it is challenging to extract complete information about the signal’s amplitude, frequency, and initial phase. Here, we present a general protocol for achieving a quantum double lock-in amplifier by employing two quantum mixers operating under orthogonal pulse sequences. To demonstrate the practical implementation, we discuss the experimental feasibility using a five-level double-Λ coherent population trapping system with Rb atoms. Here, each Λ structure acts as a quantum mixer, and two applied dynamical decoupling sequences serve as orthogonal reference signals. Notably, the system significantly reduces the total measurement time by nearly half and mitigates time-dependent systematic errors compared to conventional two-level systems. Furthermore, our quantum double lock-in amplifier is robust against experimental imperfections. This study establishes a pathway to alternating signal measurement, thereby facilitating the development of practical quantum sensing technologies.

Evaluating the motional timescales contributing to averaged anisotropic interactions in MAS solid-state NMR

Abstract. Dynamic processes in molecules can occur on a wide range of timescales, and it is important to understand which timescales of motion contribute to different parameters used in dynamics measurements. For spin relaxation, this can easily be understood from the sampling frequencies of the spectral-density function by different relaxation-rate constants. In addition to data from relaxation measurements, determining dynamically averaged anisotropic interactions in magic-angle spinning (MAS) solid-state NMR allows for better quantification of the amplitude of molecular motion. For partially averaged anisotropic interactions, the relevant timescales of motion are not so clearly defined. Whether the averaging depends on the experimental methods (e.g., pulse sequences) or conditions (e.g., MAS frequency, magnitude of anisotropic interaction, radio-frequency field amplitudes) is not fully understood. To investigate these questions, we performed numerical simulations of dynamic systems based on the stochastic Liouville equation using several experiments for recoupling the dipolar coupling, chemical-shift anisotropy or quadrupolar coupling. As described in the literature, the transition between slow motion, where parameters characterizing the anisotropic interaction are not averaged, and fast motion, where the tensors are averaged leading to a scaled anisotropic quantity, occurs over a window of motional rate constants that depends mainly on the strength of the interaction. This transition region can span 2 orders of magnitude in exchange-rate constants (typically in the microsecond range) but depends only marginally on the employed recoupling scheme or sample spinning frequency. The transition region often coincides with a fast relaxation of coherences, making precise quantitative measurements difficult. Residual couplings in off-magic-angle experiments, however, average over longer timescales of motion. While in principle one may gain information on the timescales of motion from the transition area, extracting such information is hampered by low signal-to-noise ratio in experimental spectra due to fast relaxation that occurs in the same region.

Study on the partial discharge characteristics induced by the motion of cellulose particles in transformer oil

AbstractCellulose particles present a significant concern within the oil‐paper insulation of transformers, posing potential risks to insulation performance. Under the influence of the electric field, the movement of cellulose particles can compromise the transformer's insulation, leading to potential failure. An experimental platform was established to synchronously record particle motion images, partial discharge (PD) pulses, and electric voltage waveforms in oil, aiming to observe the PD characteristics resulting from particle motion under alternating current (AC) voltage and investigate the relationship between different particle motion modes, motion positions, and PD signals. The findings reveal that the phase distribution of PD signals is correlated with the particle motion mode. Specifically, the phase distribution of PD pulses during the back‐and‐forth motion mode is between 4°–94° and 182°–275°. In the suspended oscillation motion mode, the PD pulses phase is concentrated between 20°–84° and 203°–268°. The generation of PD pulses is closely linked to the particle's motion position. PD pulses occur when the particle remains on the electrode during the back‐and‐forth motion mode, generally, PD pulses rarely occur during the jumping process between the two electrodes. In the suspended oscillation motion mode, PD pulses occur when the particle moves upward, but generally do not occur during downward movement. Furthermore, the Pulse Sequence Analysis technique was used to employ the PD characteristics caused by particle motion in transformer oil. The simulation calculations of the electric field distribution for two different particle motion modes show that the particle's motion can cause distortion of the electric field distribution, leading to the generation of PD. The study of the PD characteristics at different particle motion modes and positions obtained contributes to a deeper understanding of the PD induced by cellulose particle motion under AC voltage and provides a reference for the insulation evaluation of transformers.

Comparison of methods for the NMR measurement of motionally averaged dipolar couplings

Motionally averaged dipolar couplings are an important tool for understanding the complex dynamics of catalysts, polymers, and biomolecules. While there is a plethora of solid-state NMR pulse sequences available for their measurement, in can be difficult to gauge the methods’ strengths and weaknesses. In particular, there has not been a comprehensive comparison of their performance in natural abundance samples, where 1H homonuclear dipolar couplings are important and the use of large MAS rotors may be required for sensitivity reasons. In this work, we directly compared some of the more common methods for measuring C–H dipolar couplings in natural abundance samples using L-alanine (L-Ala) and the N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLF) tripeptide as model systems. We evaluated their performance in terms of accuracy, resolution, sensitivity, and ease of implementation. We found that, despite the presence of 1H homonuclear dipolar interactions, all methods, with the exception of REDOR, were able to yield the reasonable dipolar coupling strengths for both mobile and static moieties. Of these methods, PDLF provides the most convenient workflow and precision at the expense of low sensitivity. In low-sensitivity cases, MAS-PISEMA and DIPSHIFT appear to be the better options.

Generation of Bright–Dark Pulse Pairs in the Er-Doped Mode-Locked Fiber Laser Based on Doped Fiber Saturable Absorber

This study reports new types of passive mode-locked Er-doped fiber laser (EDFL) based on a segment of doped fiber saturable absorber (DFSA) with Tm/Ho-doped fiber (THDF), Yb-doped fiber (YDF), and Er-doped fiber (EDF). By employing THDF-SA, a bright pulse sequence with a fundamental repetition rate of 17.86 MHz was obtained. In addition, various mode-locked output states, including dark pulses, dark–bright pulse pairs, bright–dark pulse pairs, and second-harmonic pulses, were obtained through polarization modulation and gain modulation, and the orthogonality of dark–bright pulses in both polarization directions was verified. Furthermore, using EDF-SA and YDF-SA, dark pulses and dark–bright pulses were obtained. A comparison of the three experiments revealed that THDF-SA effectively reduces the mode-locked threshold and improves the average output power. Compared with bright pulses, dark pulses offer several advantages such as resisting noise, increasing propagation speed, and suppressing nonlinear scattering (such as pulse-intrinsic Raman scattering); thus, the EDFL can find broad application in long-distance transmission, precision measurement, and other fields.

Determine Oil and Water Saturations in Preserved Source Rocks From 2D T1-T2 NMR

Two-dimensional (2D) T1-T2 NMR has been widely proposed as a method to determine the fluids present in unconventional source rocks. However, the assignment of the components in the 2D T1- T2 NMR spectra has so far been based on conceptual consideration and lacks rigorous experimental verification. Many assignment variations appeared in the literature and can be misleading. For example, large T1/T2 peaks in the 2D T1-T2 NMR were suggested to be fluid in small pores coupled with kerogen solid through dipolar relaxation. Our recent 500-MHz NMR relaxation experiments found that the dipolar relaxation between nanoconfined fluids and solid matrix is not big enough to support that large T1/T2 interpretation. The objective of this paper is to determine what quantitative data can be obtained using 2D T1-T2 NMR from source rocks with high confidence. We found the oil and water saturation can be accurately measured in preserved source rock plugs. Two-dimensional T1-T2 NMR data were collected on preserved core plugs from five wells of a source rock reservoir using an inversion-recovery Carr-Purcell-Meiboom-Gill (CMPG) pulse sequence on a 12-MHz NMR instrument. The acquired 2D data were inverted using an optimized inversion software, MUPen2D. We then obtain oil and water content in the plug from the 2D T1-T2 NMR using an in-house-developed NMR MATLAB app. The porosity of all the plugs was measured using a combined NMR and gas porosimetry (CNG) method. Oil and water saturation were also obtained using an industry-standard method developed by the Gas Research Institute (GRI) on the rock material close to where the plug was drilled. The oil and water saturations measured on the preserved plugs using 2D T1-T2 NMR and CNG are consistent with those from the GRI method using crushed rocks and an invasive cleaning procedure. The results show that oil and water saturations were accurately determined from 2D T1-T2 NMR on preserved source rock samples with high confidence. The NMR method is nondestructive and noninvasive and takes less than 4 hours on a preserved source rock plug, while GRI is destructive and invasive and can take several weeks for an accurate measurement on one sample. The measured results can be further used to determine the production potential of a source rock well in combination with log data.

Reinforcement learning pulses for transmon qubit entangling gates

The utility of a quantum computer is highly dependent on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular interest to explore model-free approaches, since their quality is not constrained by the limited accuracy of theoretical models for the quantum processor—in contrast to many established gate implementation strategies. In this work, we utilize a continuous control reinforcement learning algorithm to design entangling two-qubit gates for superconducting qubits; specifically, our agent constructs cross-resonance and CNOT gates without any prior information about the physical system. Using a simulated environment of fixed-frequency fixed-coupling transmon qubits, we demonstrate the capability to generate novel pulse sequences that outperform the standard cross-resonance gates in both fidelity and gate duration, while maintaining a comparable susceptibility to stochastic unitary noise. We further showcase an augmentation in training and input information that allows our agent to adapt its pulse design abilities to drifting hardware characteristics, importantly, with little to no additional optimization. Our results exhibit clearly the advantages of unbiased adaptive-feedback learning-based optimization methods for transmon gate design.

Deep brain stimulation pulse sequences to optimally modulate frequency-specific neural activity

Objective. Precise neuromodulation systems are needed to identify the role of neural oscillatory dynamics in brain function and to advance the development of brain stimulation therapies tailored to each patient’s signature of brain dysfunction. Low-frequency, local field potentials (LFPs) are of increasing interest for the development of these systems because they can reflect the synaptic inputs to a recorded neuronal population and can be chronically recorded in humans. In this computational study, we aim to identify stimulation pulse patterns needed to optimally maximize the suppression or amplification of frequency-specific neural activity. Approach. We derived DBS pulse patterns to minimize or maximize the 2-norm of frequency-specific neural oscillations using a generalized mathematical model of spontaneous and stimulation-evoked LFP activity, and a subject-specific model of neural dynamics in the pallidum of a Parkinson’s disease patient. We leveraged convex and mixed-integer optimization tools to identify these pulse patterns, and employed constraints on the pulse frequency and amplitude that are required to keep electrical stimulation within its safety envelope. Main results. Our analysis revealed that a combination of phase, amplitude, and frequency pulse modulation is needed to attain optimal suppression or amplification of the targeted oscillations. Phase modulation is sufficient to modulate oscillations with a constant amplitude envelope. To attain optimal modulation for oscillations with a time-varying envelope, a trade-off between frequency and amplitude pulse modulation is needed. The optimized pulse sequences were invariant to changes in the dynamics of stimulation-evoked neural activity, including changes in damping and natural frequency or complexity (i.e. generalized vs. patient-specific model). Significance. Our results provide insight into the structure of pulse patterns for future closed-loop brain stimulation strategies aimed at controlling neural activity precisely and in real-time.

Yet more evidence that non-aqueous myelin lipids can be directly imaged with ultrashort echo time (UTE) MRI on a clinical 3T scanner: a lyophilized red blood cell membrane lipid study

Direct imaging of semi-solid lipids, such as myelin, is of great interest as a noninvasive biomarker of neurodegenerative diseases. Yet, the short T2 relaxation times of semi-solid lipid protons hamper direct detection through conventional magnetic resonance imaging (MRI) pulse sequences. In this study, we examined whether a three-dimensional ultrashort echo time (3D UTE) sequence can directly acquire signals from membrane lipids. Membrane lipids from red blood cells (RBC) were collected from commercially available blood as a general model of the myelin lipid bilayer and subjected to D2O exchange and freeze-drying for complete water removal. Sufficiently high MR signals were detected with the 3D UTE sequence, which showed an ultrashort T2* of ∼77–271 µs and a short T1 of ∼189 ms for semi-solid RBC membrane lipids. These measurements can guide designing UTE-based sequences for direct in vivo imaging of membrane lipids.