Magnetic Particle Imaging Is a Sensitive In Vivo Imaging Modality for the Detection of Dendritic Cell Migration

Optical-magnetic Imaging for Optimizing Lymphodepletion-TIL Combination Therapy in Breast Cancer

PURPOSE

Lymphodepletion before tumor-infiltrating lymphocytes (TIL) infusion can activate the immune system, enhance the release of homeostatic cytokines, and decrease the number of immunosuppressive cells. This process is crucial for improving the therapeutic efficacy of TIL therapy. However, the challenge of in vivo assessing TILs targeting tumors limits the optimization of lymphodepleting conditioning regimen (LDC).

PROCEDURES

This study aims to employ magnetic particle imaging (MPI) and fluorescence molecular imaging (FMI) to monitor TIL biodistribution in vivo and optimize LDC in triple-negative breast cancer TIL therapy. MPI provides quantitative imaging capabilities without depth limitations, effectively complementing the high sensitivity of FMI. The efficacy of different LDCs in enhancing TIL therapy was assessed using FMI, and MPI quantified the number of TILs accumulated in the 4T1 tumor.

RESULTS

TILs preserved viability, phenotypes, and anti-tumor efficacy after being labeled with superparamagnetic iron oxide and fluorescence dye DiR. The dual-modality imaging system effectively discerned variations in LDC treatments that enhanced TIL therapy. Compared to TIL monotherapy, lymphodepletion with TIL therapy improves tumor dual-modality imaging signal intensity, increases the expression of monocyte chemotactic protein-1 in serum and tumor tissue, and enhances the therapeutic effect of TILs.

CONCLUSION

Our results confirm the utility of optical-magnetic dual-modality imaging for tracking the biodistribution of TILs in vivo. With the help of optical-magnetic dual-modality imaging, we successfully optimize TIL combination therapy. Optical-magnetic dual-modality imaging provides a new approach to develop personalized immunotherapy strategies and mine potential therapeutic mechanisms for TIL.

On the partial volume effect in magnetic particle imaging

Objective.Magnetic particle imaging (MPI) is an emerging tomographic 'hot spot' imaging modality with potential to visualize superparamagnetic iron oxide nanoparticle tracer distributions with high sensitivity and quantitative accuracy. MPI shares many similarities with positron emission tomography (PET), where the partial volume effect (PVE) can result in signal under- and over-quantification due to spill-over of signal arising from limited resolution. While the PVE has been alluded to in the MPI literature it has not been previously studied nor characterized. The objective of this study was to systematically characterize this PVE in MPI.Approach.This contribution characterizes the PVE using models of varying size and shape filled with a uniform concentration of tracer. The effect of object size on signal distribution was analyzed after application of a new image post-processing filter.Main results.As object size increased, signal distribution increased to a maximum signal value independent of object geometry and proportional to tracer concentration. Furthermore, for small objects with characteristic dimensions below the resolution of the tracer at the scanning conditions used, signal suppression was observed. These results are consistent with foundational observations of PVE in PET, suggesting that approaches to overcome the PVE in PET may be applicable to MPI.Significance.This finding has significant impact on the MPI field by demonstrating the presence of the PVE phenomenon that can directly influence imaging results.

A Comparison of the Sensitivity and Cellular Detection Capabilities of Magnetic Particle Imaging and Bioluminescence Imaging

BACKGROUND

Preclinical cell tracking is enhanced with a multimodal imaging approach. Bioluminescence imaging (BLI) is a highly sensitive optical modality that relies on engineering cells to constitutively express a luciferase gene. Magnetic particle imaging (MPI) is a newer imaging modality that directly detects superparamagnetic iron oxide (SPIO) particles used to label cells. Here, we compare BLI and MPI for imaging cells in vitro and in vivo.

METHODS

Mouse 4T1 breast carcinoma cells were transduced to express firefly luciferase, labeled with SPIO (ProMag), and imaged as cell samples after subcutaneous injection into mice.

RESULTS

For cell samples, the BLI and MPI signals were strongly correlated with cell number. Both modalities presented limitations for imaging cells in vivo. For BLI, weak signal penetration, signal attenuation, and scattering prevented the detection of cells for mice with hair and for cells far from the tissue surface. For MPI, background signals obscured the detection of low cell numbers due to the limited dynamic range, and cell numbers could not be accurately quantified from in vivo images.

CONCLUSIONS

It is important to understand the shortcomings of these imaging modalities to develop strategies to improve cellular detection sensitivity.

Transformer for low concentration image denoising in magnetic particle imaging

Objective.Magnetic particle imaging (MPI) is an emerging tracer-basedin vivoimaging technology. The use of MPI at low superparamagnetic iron oxide nanoparticle concentrations has the potential to be a promising area of clinical application due to the inherent safety for humans. However, low tracer concentrations reduce the signal-to-noise ratio of the magnetization signal, leading to severe noise artifacts in the reconstructed MPI images. Hardware improvements have high complexity, while traditional methods lack robustness to different noise levels, making it difficult to improve the quality of low concentration MPI images.Approach.Here, we propose a novel deep learning method for MPI image denoising and quality enhancing based on a sparse lightweight transformer model. The proposed residual-local transformer structure reduces model complexity to avoid overfitting, in which an information retention block facilitates feature extraction capabilities for the image details. Besides, we design a noisy concentration dataset to train our model. Then, we evaluate our method with both simulated and real MPI image data.Main results.Simulation experiment results show that our method can achieve the best performance compared with the existing deep learning methods for MPI image denoising. More importantly, our method is effectively performed on the real MPI image of samples with an Fe concentration down to 67μgFeml-1.Significance.Our method provides great potential for obtaining high quality MPI images at low concentrations.

Accurate Concentration Recovery for Quantitative Magnetic Particle Imaging Reconstruction via Nonconvex Regularization

Magnetic particle imaging (MPI) uses nonlinear response signals to noninvasively detect magnetic nanoparticles in space, and its quantitative properties hold promise for future precise quantitative treatments. In reconstruction, the system matrix based method necessitates suitable regularization terms, such as Tikhonov or non-negative fused lasso (NFL) regularization, to stabilize the solution. While NFL regularization offers clearer edge information than Tikhonov regularization, it carries a biased estimate of the l1 penalty, leading to an underestimation of the reconstructed concentration and adversely affecting the quantitative properties. In this paper, a new nonconvex regularization method including min-max concave (MC) and total variation (TV) regularization is proposed. This method utilized MC penalty to provide nearly unbiased sparse constraints and adds the TV penalty to provide a uniform intensity distribution of images. By combining the alternating direction multiplication method (ADMM) and the two-step parameter selection method, a more accurate quantitative MPI reconstruction was realized. The performance of the proposed method was verified on the simulation data, the Open-MPI dataset, and measured data from a homemade MPI scanner. The results indicate that the proposed method achieves better image quality while maintaining the quantitative properties, thus overcoming the drawback of intensity underestimation by the NFL method while providing edge information. In particular, for the measured data, the proposed method reduced the relative error in the intensity of the reconstruction results from 28% to 8%.

Open-source device for high sensitivity magnetic particle spectroscopy, relaxometry, and hysteresis loop tracing

Magnetic nanoparticles (MNPs) are used extensively across numerous disciples, with applications including Magnetic Particle Imaging (MPI), targeted hyperthermia, deep brain stimulation, immunoassays, and thermometry. The assessment of MNPs, especially those being designed for MPI, is performed with magnetic particle spectrometers, relaxometers, loop tracers, or similar devices. Despite the many applications and the need for particle assessment, there are few consolidated resources for designing or building such a MNP assessment system. Here, we describe the design and performance of an open-source device capable of spectroscopy, relaxometry, and loop tracing. We show example measurements from the device and quantify the detection sensitivity by measuring a dilution series of Synomag-D 70 nm (from 0.5 mg Fe/ml to 7 ng Fe/ml) with a 10 mT drive field at 23.8 kHz. The device measures 260 pg Fe with SNR = 1 and 1.3 ng at SNR = 5 in spectroscopy mode in under one second of measurement time. The system has a dynamic range of 60 μg to 260 pg Fe without changing the hardware configuration. As an example application, we characterize Synomag-D's relaxation time constant for drive fields 2-18 mT and compare the magnetization responses of two commonly used MNPs.

In vivo tracking of adenoviral-transduced iron oxide-labeled bone marrow-derived dendritic cells using magnetic particle imaging

BACKGROUND

Despite widespread study of dendritic cell (DC)-based cancer immunotherapies, the in vivo postinjection fate of DC remains largely unknown. Due in part to a lack of quantifiable imaging modalities, this is troubling as the amount of DC migration to secondary lymphoid organs correlates with therapeutic efficacy. Magnetic particle imaging (MPI) has emerged as a suitable modality to quantify in vivo migration of superparamagnetic iron oxide (SPIO)-labeled DC. Herein, we describe a popliteal lymph node (pLN)-focused MPI scan to quantify DC in vivo migration accurately and consistently.

METHODS

Adenovirus (Ad)-transduced SPIO+ (Ad SPIO+) and SPIO+ C57BL/6 bone marrow-derived DC were generated and assessed for viability and phenotype, then fluorescently labeled and injected into mouse hind footpads (n = 6). Two days later, in vivo DC migration was quantified using whole animal, pLN-focused, and ex vivo pLN MPI scans.

RESULTS

No significant differences in viability, phenotype and in vivo pLN migration were noted for Ad SPIO+ and SPIO+ DC. Day 2 pLN-focused MPI quantified DC migration in all instances while whole animal MPI only quantified pLN migration in 75% of cases. Ex vivo MPI and fluorescence microscopy confirmed that pLN MPI signal was due to originally injected Ad SPIO+ and SPIO+ DC.

CONCLUSION

We overcame a reported limitation of MPI by using a pLN-focused MPI scan to quantify pLN-migrated Ad SPIO+ and SPIO+ DC in 100% of cases and detected as few as 1000 DC (4.4 ng Fe) in vivo. MPI is a suitable preclinical imaging modality to assess DC-based cancer immunotherapeutic efficacy.

RELEVANCE STATEMENT

Tracking the in vivo fate of DC using noninvasive quantifiable magnetic particle imaging can potentially serve as a surrogate marker of therapeutic effectiveness.

KEY POINTS

• Adenoviral-transduced and iron oxide-labeled dendritic cells are in vivo migration competent. • Magnetic particle imaging is a suitable modality to quantify in vivo dendritic cell migration. • Magnetic particle imaging focused field of view overcomes dynamic range limitation.

First Superferromagnetic Remanence Characterization and Scan Optimization for Super-Resolution Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a sensitive, high-contrast tracer modality that images superparamagnetic iron oxide nanoparticles, enabling radiation-free theranostic imaging. MPI resolution is currently limited by scanner and particle constraints. Recent tracers have experimentally shown 10× resolution and signal improvements with dramatically sharper M-H curves. Experiments show a dependence on interparticle interactions, conforming to literature definitions of superferromagnetism. We thus call our tracers superferromagnetic iron oxide nanoparticles (SFMIOs). While SFMIOs provide excellent signal and resolution, they exhibit hysteresis with non-negligible remanence and coercivity. We provide the first quantitative measurements of SFMIO remanence decay and reformation using a novel multiecho pulse sequence. We characterize MPI scanning with remanence decay and coercivity and describe an SNR-optimized pulse sequence for SFMIOs under human electromagnetic safety limitations. The resolution from SFMIOs could enable clinical MPI with 10× reduced scanner selection fields, reducing hardware costs by up to 100×.

Dual Magnetic Particle Imaging and Akaluc Bioluminescence Imaging for Tracking Cancer Cell Metastasis

Magnetic particle imaging (MPI) provides hotspot tracking and direct quantification of superparamagnetic iron oxide nanoparticle (SPIO)-labelled cells. Bioluminescence imaging (BLI) with the luciferase reporter gene Akaluc can provide complementary information on cell viability. Thus, we explored combining these technologies to provide a more holistic view of cancer cell fate in mice. Akaluc-expressing 4T1Br5 cells were labelled with the SPIO Synomag-D and injected into the mammary fat pads (MFP) of four nude mice. BLI was performed on days 0, 6 and 13, and MPI was performed on days 1, 8 and 14. Ex vivo histology and fluorescence microscopy of MFP and a potential metastatic site was conducted. The BLI signal in the MFP increased significantly from day 0 to day 13 (p < 0.05), mirroring tumor growth. The MPI signal significantly decreased from day 1 to day 14 (p < 0.05) due to SPIO dilution in proliferating cells. Both modalities detected secondary metastases; however, they were visualized in different anatomical regions. Akaluc BLI complemented MPI cell tracking, allowing for longitudinal measures of cell viability and sensitive detection of distant metastases at different locations. We predict this multimodal imaging approach will help to evaluate novel therapeutics and give a better understanding of metastatic mechanisms.

In Vivo Cellular Magnetic Imaging: Labeled vs. Unlabeled Cells

Superparamagnetic iron oxide (SPIO)-labeling of cells has been applied for magnetic resonance imaging (MRI) cell tracking for over 30 years, having resulted in a dozen or so clinical trials. SPIO nanoparticles are biodegradable and can be broken down into elemental iron, and hence the tolerance of cells to magnetic labeling has been overall high. Over the years, however, single reports have accumulated demonstrating that the proliferation, migration, adhesion and differentiation of magnetically labeled cells may differ from unlabeled cells, with inhibition of chondrocytic differentiation of labeled human mesenchymal stem cells (hMSCs) as a notable example. This historical perspective provides an overview of some of the drawbacks that can be encountered with magnetic labeling. Now that magnetic particle imaging (MPI) cell tracking is emerging as a new in vivo cellular imaging modality, there has been a renaissance in the formulation of SPIO nanoparticles this time optimized for MPI. Lessons learned from the occasional past pitfalls encountered with SPIO-labeling of cells for MRI may expedite possible future clinical translation of (combined) MRI/MPI cell tracking.