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Mapping light distribution in tissue by using MRI-detectable photosensitive liposomes


Characterizing sources and targets of illumination in living tissue is challenging. Here we show that spatial distributions of light in tissue can be mapped by using magnetic resonance imaging (MRI) in the presence of photosensitive nanoparticle probes. Each probe consists of a reservoir of paramagnetic molecules enclosed by a liposomal membrane incorporating photosensitive lipids. Incident light causes the photoisomerization of the lipids and alters hydrodynamic exchange across the membrane, thereby affecting longitudinal relaxation-weighted contrast in MRI. We injected the nanoparticles into the brains of live rats and used MRI to map responses to illumination profiles characteristic of widely used applications of photostimulation, photometry and phototherapy. The responses deviated from simple photon propagation models and revealed signatures of light scattering and nonlinear responsiveness. Paramagnetic liposomal nanoparticles may enable MRI to map a broad range of optical phenomena in deep tissue and other opaque environments.

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Fig. 1: Principle of liposomal nanoparticle reporters.
Fig. 2: Formation and in vitro characterization of Light-LisNRs.
Fig. 3: Assessment of Light-LisNR performance in vivo.
Fig. 4: Light mapping using LisNRs.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw data generated in this study are available from the corresponding author on reasonable request. Source data for the figures are provided with this paper.


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This research was funded by NIH grants R21 DA044748 and R01 NS120592 and a grant from the G. Harold and Leila Y. Mathers Foundation to A.J. J.S. was supported by a Friends of the McGovern Fellowship from the McGovern Institute for Brain Research and by the MIT Neurobiological Engineering Training Program (NIH T32 EB019940). M.S. was the recipient of a Marie Curie Individual Fellowship from the European Commission. We thank G. Yona and S. Shoham for advice about light modelling and for sharing code for computing beam-spreading profiles.

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Authors and Affiliations



J.S. and A.J. developed the LisNR concept. J.S., M.S. and A.J. designed the research. J.S. performed and analysed the in vitro experiments. M.S. performed the in vivo experiments. M.S. and A.J. analysed the in vivo data. J.M. and D.T. synthesized and characterized AzoPC and advised on the in vitro light-response experiments. J.S., M.S. and A.J. wrote the paper.

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Correspondence to Alan Jasanoff.

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Nature Biomedical Engineering thanks Jeff Bulte and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Light-LisNR response as a function of stimulus duration.

a, MRI signal in response to UV irradiation of Light-LisNRs (orange) over varying durations: 0.5 min (left), 2 min (middle), and 6 min (right). Corresponding unilluminated control data shown in black. Shaded margins denote s.e.m. of n = 3 animals. b, Equivalent time course data for blue illumination. c, Signal differences observed following UV irradiation (orange) or control treatment (black) of LisNRs over the durations indicated. Error bars denote s.e.m. of n = 3 animals. d, Equivalent signal difference data for blue illumination.

Source data

Extended Data Fig. 2 Dissociation between light response rates and amplitudes.

a, Top: Light-LisNR response amplitudes to blue and UV light are highly correlated over a 25 ×25 voxel region around fibre optic tips in six animals (R = 0.89, p < 10−5). Bottom: in contrast, blue light response amplitudes and response rates are statistically independent over the same voxels (R = –0.013, p = 0.66), indicating that the LisNR response rates are not strongly affected by variations in probe concentration, which largely determine the signal change amplitude distribution. b, Response amplitudes and rates can also be dissociated from one another as a function of distance from the fibre tip: amplitudes decrease monotonically (top), while response rates peak and then diminish (bottom). Error bars denote SEM over 6 (top) or 3 to 6 (bottom) biological replicates. c, Histograms of blue light response amplitudes (top) and response rates (bottom) over three cycles of illumination (B1-B3), showing stability over time (n = 2 animals). d, Box plots corresponding to the distributions in panel c. Central line = median, box limits = first and third quartiles, whiskers = limiting values. Consistency of the distributions indicates that diffusion and convection over the ~1 hour experimental time period do not strongly affect the results.

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Simon, J., Schwalm, M., Morstein, J. et al. Mapping light distribution in tissue by using MRI-detectable photosensitive liposomes. Nat. Biomed. Eng 7, 313–322 (2023).

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