Resonance Detection Research Articles

Dead Time-Free Detection of NMR Signals Using Voltage-Controlled Oscillators

In this paper, we introduce voltage-controlled oscillators (VCOs) as a new type of nuclear magnetic resonance (NMR) detector, enabling dead time-free detection of NMR signals after an excitation pulse as well as the real-time inductive detection of Rabi oscillations during the pulse. Together with the theory of operation, we present the details of a custom-designed prototype implementation of a VCO-based NMR detector with an operating frequency around 62 MHz. The proof-of-concept measurements obtained with this prototype clearly demonstrate the possibility of performing dead time-free NMR experiments with coherent spin manipulation. Moreover, we also experimentally verified the capability of VCO-based detectors for performing real-time inductive detection of Rabi oscillations during the excitation pulse.

Highly efficient Z-scheme Ag3PO4/PtNPs/g-C3N4 photocatalyst for degradation of organic pollutants in water

Organic pollutants in water cause serious waste of water resources. Therefore, it is important to design efficient photocatalysts to address the problem of waste water. Herein, solid Z-scheme heterojunction photocatalyst, Ag3PO4/PtNPs/g-C3N4, was prepared via in-situ deposition. Under xenon lamp (full wavelength) irradiation, the catalyst efficiently degraded solutions of rhodamine B and phenol within 9 min and 30 min, respectively. This shows better photodegradation performance (99.4% of Rh B, and 97.0% of phenol) than other catalysts and demonstrates that the synergistic effect of its three components results in improved photocatalytic activity. Furthermore, holes and superoxide radicals were identified as main active species during catalysis with Ag3PO4/PtNPs/g-C3N4 based on scavenging experiments of active species and electron spin resonance detection results. In proposed photocatalytic mechanism, PtNPs act as a bridge and accelerate charge transfer on ternary Ag3PO4/PtNPs/g-C3N4. This study provides ternary Z-scheme heterojunction photocatalyst construction for application in the treatment of organic pollutants.

Laser photo-acoustic methane sensor (7.7 µm) for use at unmanned aerial vehicles

A compact laser photo-acoustic (PA) methane sensor based on a quantum-cascade laser (∼7.7 μm; 1750 Hz; 25 mW), a resonant differential photo-acoustic detector (PAD), and a sealed-off gas-filled PA Ref-cell has been developed. Normalization of the absorption signals in the PAD is carried out according to the absorption signals in the gas-filled PA Ref-cell, which significantly reduces the measurement errors of the methane concentration in the case of instability of the laser emission wavelength. The minimum measured background signal of the PA sensor (using high purity nitrogen) is nmin≈(26.6 ± 8.4) ppb CH4 (at a bandwidth of 20 Hz), the value of normalized noise equivalent absorption (NNEA) = 8.22 × 10–10 cm−1·W/Hz1/2. A comparison of various research groups results with mid-IR PA gas analyzers is carried out. The developed PA methane sensor is adapted for placement on the UAV’s board. Device has dimensions of 315 × 165 × 110 mm, weight ∼3.1 kg, power supply from an external source (9…60 VDC), power consumption ∼20 VA.

Insights into the removal of fluoranthene by sodium percarbonate activation with pyrite: Performance, mechanism, and degradation pathways

Sodium percarbonate (SPC) induced advanced oxidation processes have been used for the remediation of polycyclic aromatic hydrocarbons (PAHs) contamination, however, the feasibility studies of SPC and pyrite (FeS2) process are scarce. In this work, FeS2 served as a catalyst and reductant to activate SPC for fluoranthene (FLT) removal. 100% FLT removal was obtained at an initial solution pH of 5.90 with FeS2 and SPC dosages of 0.5 g/L and 0.02 mM, respectively, and the influences of initial aqueous solution pH, dissolved oxygen, and various aqueous solution matrixes on FLT degradation were explored. Based on the results of electron paramagnetic resonance detection and scavenging experiments, it was demonstrated that HO•, 1O2, and O2−• played dominant roles in the removal of FLT, whereas CO3−• could only be involved in the ROS proliferative reaction in FeS2/SPC process due to the weak oxidizing capacity. Additionally, three FLT degradation pathways were proposed based on the detected degradation intermediates 1-phenylnaphthalene, indane, and phthalic acid. Finally, the desorption of FLT in soil was investigated by employing surfactants and organic acids, with organic acids being less effective than surfactants. Since the majority of organic acids can be utilized as advanced oxidation process promoters, their practical application is advantageous.

Three-dimensional hollow catalysts with edge-defective Fe-Nx sites and enhanced peroxymonosulfate activation performance: Preparation, applications, and mechanism

Developing heterogeneous catalysts with high level of active site exposure is crucial for the activation of peroxymonosulfate. In this study, a series of high-performance Fe-N-C catalysts were obtained through the strategy of melamine-assisted pyrolysis. The morphology, specific surface area and pore structure of the catalysts can be adjusted by controlling the amount of melamine added during the pyrolysis process. Fe1-Nx-C obtained with a melamine to Fe-ZIF ratio of 1:1 exhibited the highest specific surface area (984.2 m2·g−1), pore volume (1.79 cm3·g−1) and reaction rate constant (0.055 min−1, 5.5 times that of Fe0-Nx-C). Furthermore, Fe1-Nx-C showed high stability and reusability in multiple cycles, maintaining high catalytic activity with pH range of 3–9. The addition of melamine can cause selective cleavage of C-N bonds, converting the central Fe-Nx sites into more active edge-defective Fe-Nx sites, thereby enhancing the catalytic activity. Quenching experiments and electron paramagnetic resonance (EPR) detection confirmed the dominance of 1O2 in the degradation of Bisphenol AF (BPAF). Two possible pathways for BPAF degradation were proposed based on liquid chromatography-mass spectrometry (LC-MS) and density functional theory (DFT) calculations. This study provides a new way to design and construct Fe-N-C catalysts with ideal pore structures, and enhance the accessibility of active sites inside the catalysts.

Magnetic resonance detection of advanced atrial cardiomyopathy increases the risk for atypical atrial flutter occurrence following atrial fibrillation ablation.

Recurrence of arrhythmia after catheter ablation of atrial fibrillation (AF) in the form of atypical atrial flutter (AFL) is common among a significant number of patients and often requires redo ablation with limited success rates. Identifying patients at high risk of AFL after AF ablation could aid in patient selection and personalized ablation approach. The study aims to assess the relationship between pre-existing atrial cardiomyopathy and the occurrence of AFL following AF ablation. We analysed a cohort of 1007 consecutive AF patients who underwent catheter ablation and were included in a prospective registry. Patients who did not have baseline cardiac magnetic resonance imaging and late gadolinium enhancement (LGE-CMR) or did not experience any recurrences were excluded. A total of 166 patients were included gathering 56 patients who underwent re-ablation due to AFL recurrences and 110 patients who underwent re-ablation due to AF recurrences (P = 0.11). A multiparametric assessment of atrial cardiomyopathy was based on basal LGE-CMR, including left atrial (LA) volume, LA sphericity, and global and segmental LA fibrosis using semiautomated post-processing software. Out of the initial cohort of 1007 patients, AFL and AF occurred in 56 and 110 patients, respectively. An age higher than 65 [odds ratio (OR) = 5.6, 95% confidence interval (CI): 2.2-14.4], the number of previous ablations (OR = 3.0, 95% CI: 1.2-7.8), and the management of ablation lines in the index procedure (OR = 2.5, 95% CI: 1.0-6.3) were independently associated with AFL occurrence. Furthermore, several characteristics assessed by LGE-CMR were identified as independent predictors of AFL recurrence after the index ablation for AF, such as enhanced LA sphericity (OR = 1.3, 95% CI: 1.1-1.6), LA global fibrosis (OR = 1.03, 95% CI: 1.01-1.07), and increased fibrosis in the lateral wall (OR = 1.03, 95% CI: 1.01-1.04). Advanced atrial cardiomyopathy assessed by LGE-CMR, such as increased LA sphericity, global LA fibrosis, and fibrosis in the lateral wall, is independently associated with arrhythmia recurrence in the form of AFL following AF ablation.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract.

Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Magnetic relaxation switching biosensor for one-step detection of Vibrio parahaemolyticus based on click chemistry-mediated sol-gel system

In this study, a magnetic relaxation switching (MRS) biosensor was developed for one-step detection of pathogenic bacteria Vibrio parahaemolyticus (VP). The biosensor is based on a click chemistry-mediated sol-gel system and utilizes low-field nuclear magnetic resonance (LF NMR) detection. VP aptamer (Apt)-coated hollow mesoporous silica microspheres (HMSMs) with saturated sodium ascorbate (SAA) solution sealed inside, HMSMs@SAA&Apt, are designed as the signal unit. When the target VP is present, the Apt binds to VP and releases SAA from the signal unit. The released SAA reduces Cu2+ in the test solution to Cu+, which catalyzes the click chemistry reaction between azide-modified polyethylene glycol (PEG-Azide) and acetylene-modified polyacrylic acid (PAA-Alkyne). The sol-gel transition is triggered, a large amount of "free" water is converted into "bound" water, resulting in the decrease of transverse relaxation time (T2). Under the optimal experimental conditions, the variation of T2 (ΔT2) was linearly related to the logarithm of VP concentration in the range of 10 ∼ 1.0 × 108 CFU/mL, with a limit of detection of 5 CFU/mL. The assay demonstrated good selectivity, stability, and reproducibility. It is completed in one step, holding promising applications in the rapid field detection of pathogenic bacteria.

Resonant anomaly detection with multiple reference datasets

An important class of techniques for resonant anomaly detection in high energy physics builds models that can distinguish between reference and target datasets, where only the latter has appreciable signal. Such techniques, including Classification Without Labels (CWoLa) and Simulation Assisted Likelihood-free Anomaly Detection (SALAD) rely on a single reference dataset. They cannot take advantage of commonly-available multiple datasets and thus cannot fully exploit available information. In this work, we propose generalizations of CWoLa and SALAD for settings where multiple reference datasets are available, building on weak supervision techniques. We demonstrate improved performance in a number of settings with realistic and synthetic data. As an added benefit, our generalizations enable us to provide finite-sample guarantees, improving on existing asymptotic analyses.

Prostate cancer of magnetic resonance imaging automatic segmentation and detection of based on 3D-Mask RCNN

BackgroundProstate cancer is a widespread form of cancer that impacts men across the world. MRI plays a pivotal role in the detection and precise localization of cancerous regions, aiding medical professionals in devising effective treatment strategies for patients. As a result, MRI is often used in the diagnosis of prostate cancer. PurposeOur proposed method employs deep learning to achieve automatic segmentation and detection of prostate cancer in MRI single series, particularly T2-weighted imaging (T2WI). Materials and methodsOur study utilized data from 133 patients at a hospital, consisting of 71 cases of prostate cancer and 62 cases of benign prostatic tumors. We employed T2-weighted imaging (T2WI) MRI single series from 93 prostates as the training set for our 3D-Mask RCNN model, while the remaining data from 40 prostates were used for validation. The masks were manually delineated by an experienced radiologist, with pathology serving as the reference standard. Our approach was evaluated using several metrics, such as dice similarity coefficient (DSC), accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curve analysis. ResultsOur study produced promising results using the 3D Mask R-CNN model. The training set yielded a DSC score of 0.856, sensitivity of 0.921, and specificity of 0.961. The test set was also successful, with a DSC score of 0.849, sensitivity of 0.911, and specificity of 0.931. Furthermore, our model achieved an AUC value of 0.865 and an accuracy, sensitivity, and specificity of 0.866, 0.875, and 0.835, respectively, for the training set. The test set had an AUC value of 0.842 and an accuracy, sensitivity, and specificity of 0.836, 0.847, and 0.819, respectively. These findings demonstrate that our approach is capable of accurately detecting and segmenting prostate cancer in MRI single series - T2WI. ConclusionThe use of the 3D-Mask RCNN model in segmenting prostate tumors and detecting cancer in MRI T2WI has been shown to be highly effective and precise. This approach has the potential to greatly benefit radiologists by improving the accuracy and efficiency of diagnoses, leading to more effective treatment planning for patients with prostate cancer. By automating the segmentation process, this approach can also reduce the workload of radiologists and increase the consistency of diagnoses. The high performance of this model highlights the potential of deep learning techniques in medical imaging and demonstrates the significant impact that these approaches can have on improving patient outcomes.

Quartz-Enhanced Photoacoustic Spectroscopy in the Terahertz Spectral Range

Infrared laser photo-acoustic spectroscopy provides very high sensitivity of a gas sample analysis when high-power tunable laser radiation sources and resonant photo-acoustic detectors (PADs) are used. In the resonant PAD, the acoustic signal generated by absorbed laser radiation in a measurement chamber is amplified proportionally to a Q-factor of the acoustic resonator. But, compact tunable high-power lasers (with power above 100 mW) still are not widely spread in the terahertz spectral range. One of the ways to achieve an acceptable sensitivity of terahertz photo-acoustic spectroscopy is using PADs with a very high Q-factor. The latter can be achieved using PAD with a quartz tuning fork. The current state in this field is presented in the review.

Single-electron spin resonance detection by microwave photon counting.

Electron spin resonance spectroscopy is the method of choice for characterizing paramagnetic impurities, with applications ranging from chemistry to quantum computing1,2, but it gives access only to ensemble-averaged quantities owing to its limited signal-to-noise ratio. Single-electron spin sensitivity has, however, been reached using spin-dependent photoluminescence3-5, transport measurements6-9 and scanning-probe techniques10-12. These methods are system-specific or sensitive only in a small detection volume13,14, so that practical single-spin detection remains an open challenge. Here, we demonstrate single-electron magnetic resonance by spin fluorescence detection15, using a microwave photon counter at millikelvin temperatures16. We detect individual paramagnetic erbium ions in a scheelite crystal coupled to a high-quality-factor planar superconducting resonator to enhance their radiative decay rate17, with a signal-to-noise ratio of 1.9 in one second integration time. The fluorescence signal shows anti-bunching, proving that it comes from individual emitters. Coherence times up to 3 ms are measured, limited by the spin radiative lifetime. The method has the potential to be applied to arbitrary paramagnetic species with long enough non-radiative relaxation times, and allows single-spin detection in a volume as large as the resonator magnetic mode volume (approximately 10 μm3 in the present experiment), orders of magnitude larger than other single-spin detection techniques. As such, it may find applications in magnetic resonance and quantum computing.

Resonant THz detection by periodic multi-gate plasmonic FETs

Resonant THz detection by periodic multi-gate plasmonic FETs

MnFe2O4 nanoparticles coated on one-dimensional carbon nanowires derived from Nitrilotriacetic acid as efficient catalysts to activate peroxymonosulfate for moxifloxacin degradation

Sulfate radical-based advanced oxidation processes (AOPs) are highly reliable for the elimination of recalcitrant contaminants by increasing degradability and reducing toxicity. Here, MnFe2O4 nanowires (MnFe2O4 NWs), composed of abundant MnFe2O4 nanoparticles immobilized on one-dimensional carbon nanowires derived from annealed MnFe-Nitrilotriacetic acid (MnFe-NTA) precursor was successfully synthesized. The MnFe2O4 NWs, which could provide more active sites, were then utilized to activate peroxymonosulfate (PMS) for oxidizing the target pollutant Moxifloxacin (MOX) in an aqueous solution. The MnFe2O4 NWs/PMS system acquired 91.9% removal of MOX and achieved 55.1% chemical oxygen demand (COD) degradation efficiency in 30 min. The results exhibited that the increased catalyst doses and PMS concentration lead to ascending MOX removal rate, which decreased with the participation of co-existing ions. Besides, there is a close relationship between original pH and MOX degradation efficiency. It was found that SO4⋅–, ⋅OH, 1O2, and O2⋅– were involved in the MOX degradation by quenching experiments and electron paramagnetic resonance (EPR) detection. More importantly, the stable magnetism of MnFe2O4 NWs contributed to its convenient recycling. Finally, a reliable mechanism for activating PMS was proposed based on the aforementioned results and previous researches, which could exhibit a novel horizon in effluent treatment.

Nuclear Magnetic Resonance Detection of Hydrogen Bond Network in a Proton Pump Rhodopsin RxR and Its Alteration during the Cyclic Photoreaction.

Hydrogen bond formation and deformation are crucial for the structural construction and functional expression of biomolecules. However, direct observation of exchangeable hydrogens, especially for oxygen-bound hydrogens, relevant to hydrogen bonds is challenging for current structural analysis approaches. Using solution-state NMR spectroscopy, this study detected the functionally important exchangeable hydrogens (i.e., Y49-ηOH and Y178-ηOH) involved in the pentagonal hydrogen bond network in the active site of R. xylanophilus rhodopsin (RxR), which functions as a light-driven proton pump. Moreover, utilization of the original light-irradiation NMR approach allowed us to detect and characterize the late photointermediate state (i.e., O-state) of RxR and revealed that hydrogen bonds relevant to Y49 and Y178 are still maintained during the photointermediate state. In contrast, the hydrogen bond between W75-εNH and D205-γCOO- is strengthened and stabilizes the O-state.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct (2H) and indirect (1H) detection of deuterium labeled compounds at 7T and clinical 3T

IntroductionDeuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6′-2H2]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2H MRSI (DMI) and 1H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. MethodsFive volunteers (4 m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8 g/kg oral [6,6′-2H2]-glucose administration using time-resolved 3D 2H FID-MRSI with elliptical phase encoding at 7T and 3D 1H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. ResultsOne hour after oral tracer administration regionally averaged deuterium labeled Glx4 concentrations and the dynamics were not significantly different over all participants between 7T 2H DMI and 3T 1H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2H and 1H data points a weak to moderate negative correlation was observed for Glx4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc6 data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001). ConclusionThis study demonstrates that indirect detection of deuterium labeled compounds using 1H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

Prospects of Using Machine Learning and Diamond Nanosensing for High Sensitivity SARS-CoV-2 Diagnosis

The worldwide death toll claimed by Acute Respiratory Syndrome Coronavirus Disease 2019 (SARS-CoV), including its prevailed variants, is 6,812,785 (worldometer.com accessed on 14 March 2023). Rapid, reliable, cost-effective, and accurate diagnostic procedures are required to manage pandemics. In this regard, we bring attention to quantum spin magnetic resonance detection using fluorescent nanodiamonds for biosensing, ensuring the benefits of artificial intelligence-based biosensor design on an individual patient level for disease prediction and data interpretation. We compile the relevant literature regarding fluorescent nanodiamonds-based SARS-CoV-2 detection along with a short description of viral proliferation and incubation in the cells. We also propose a potentially effective strategy for artificial intelligence-enhanced SARS-CoV-2 biosensing. A concise overview of the implementation of artificial intelligence algorithms with diamond magnetic nanosensing is included, covering this roadmap’s benefits, challenges, and prospects. Some mutations are alpha, beta, gamma, delta, and Omicron with possible symptoms, viz. runny nose, fever, sore throat, diarrhea, and difficulty breathing accompanied by severe body pain. The recommended strategy would deliver reliable and improved diagnostics against possible threats due to SARS-CoV mutations, including possible pathogens in the future.

A field focusing butterfly stripline detects NMR at higher signal-to-noise ratio

We present a compact tuned magnetic resonance detector that merges the conductor topology of a butterfly coil with that of a stripline, thereby increasing the magnetic field intensity B1 per unit current, which increases the detection signal-to-noise ratio for mass-limited samples by a factor of 2. The s-parameter measurements further reveal improved radiofrequency shielding through the suppression of B1 outside the coil when operated within an array of similar detectors. Simulations additionally show a sharper B1 fall-off for the butterfly stripline outside the sensitive sample region. Our design is compatible with 2D planar manufacturing procedures, such as printed circuit board technology, and surface micromachining.

Degradation of 1,2,3-trichloropropane in aqueous solution by ZVI-enhanced Fenton system: Performances and mechanisms

In this research, zero-valent iron (ZVI) was chosen as a reductant in the classic Fenton system to accelerate the generation of Fe(II). The removal of 1,2,3-trichloropropane (TCP) was only 65.3% in classic Fenton system, while with the addition of ZVI its removal could be enhanced to 95.4% in 120 min. Hydroxyl radicals (HO•) was confirmed to be the major radical during TCP degradation by electron paramagnetic resonance (EPR) detection and radical quenching tests. Moreover, the mechanism of TCP degradation in H2O2/Fe(II)/ZVI system was proposed. In the presence of ZVI, Fe(III) was reduced to Fe(II), further reacted with H2O2 and produced more HO• for TCP removal. 2,3-Dichloro-1-propene and 2-chloro-2-propen-1-ol were the main intermediates in TCP degradation and two possible pathways were proposed. Finally, TCP removal in different solution matrixes and for other chlorinated contaminants removal were tested, revealing the broad-spectrum reactivity and excellent performance of ZVI-enhanced Fenton system in the remediation of chlorinated organic compounds.

Multilayer Polymer Shell Perfluoropentane Nanodroplets for Multimodal Ultrasound, Magnetic Resonance, and Optoacoustic Imaging

AbstractMultimodal imaging increases the value of stand‐alone modalities by enabling simultaneous multiparametric characterization of biological tissues in vivo. Particularly, optoacoustic (OA) tomography has enabled bringing optical imaging advantages to previously unattainable depths and is currently being hybridized with other imaging technologies for enhanced performance. The full potential of these multimodal imaging approaches can only be achieved with dedicated contrast agents ensuring simultaneous measurements and accurate co‐registration of the information provided. Herein, perfluoropentane‐filled nanodroplets are modified, providing excellent contrast in ultrasound imaging, by introducing shell‐embedded additives offering strong contrast in magnetic resonance and OA imaging. Magnetite nanoparticles and indocyanine green (ICG) dye are simultaneously deposited as a multilayer shell on the droplets with the layer‐by‐layer method. This results in sufficiently high amounts of magnetite (0.54 ± 0.08 mg mL−1) and ICG (0.30 ± 0.08 mg mL−1) for efficient magnetic resonance and OA detection, respectively. The high sensitivity achieved with the developed trimodal nanodroplets is first demonstrated in phantom experiments, after which their potential toxic effects, biodistribution, and clearance are examined in vitro and in vivo. Taken together, the obtained results indicate that the developed multilayer polymer shell nanodroplets are efficient hybrid contrast agents for multimodal biomedical imaging applications.