Fluorescence-enhanced diffuse optical tomography is expected to be useful to the collection of functional information from small animal models. This technique is currently limited by the extent of tissue heterogeneity and management of the shape of the animals. We propose an approach based on the reconstruction of object heterogeneity, which provides an original solution to the two problems. Three evaluation campaigns are described: the first two were performed on phantoms designed to test the reconstructions in highly heterogeneous media and noncontact geometries; the third was conducted on mice with lung tumors to test fluorescence yield reconstruction feasibility in vivo.

We investigate the use of the Mellin–Laplace transform for reconstructing optical parameters from time-resolved optical tomography in diffusive media. We present here its definition, its mathematical properties, and its sensitivity to variations of optical properties. The method was validated on two-dimensional reconstructions from simulation in the reflection geometry. We conclude that reconstructions based on the Mellin–Laplace transform are more robust to noise than the methods using first moments.

Lens-free microscopy multispectral acquisitions are processed with an inverse problem approach: a multispectral total variation criterion is defined and minimized with the conjugate gradients method. Reconstruction results show that the method is efficient to recover the phase image of densely packed cells.

Diffuse optics (DO) encompasses a range of photonics tools based on the study of random photon migration in highly scattering media—biological tissues in particular. Due to its unique features, DO is emerging as a powerful means for clinical or homecare diagnostics.¹ The basic physics of DO is related to the detection of temporal or spatial alteration in photon distribution re-emitted on the tissue surface.² Due to the low power (typically few mW) of injected near-infrared light (600- to 1100-nm range), DO is inherently noninvasive. The photon temporal (or spatial) distribution carries information on the absorption—ultimately related to tissue chemical composition, such as water, lipid, collagen content, oxy- and deoxy-hemoglobin concentration, cytochrome c-oxidase³—and scattering properties—linked to tissue microstructure. Further, DO is one of the few noninvasive modalities capable of providing functional information, e.g., brain or muscle activation.⁴ It can be operated noncontact through remote light illumination and collection.⁵ It explores the tissue well below the skin at depths of up to 2 to 4 cm. It can provide quantitative operator-independent assessment of the tissue status, such as hemoglobin oxygenation level in the brain. Finally, it is highly scalable, sharing the same technology from large clinical tomographic systems down to wearable devices or homecare appliances.⁶ For all these aspects, DO is attracting more and more interest in many fields, such as monitoring vital signs like brain oxygenation in critical care or during interventions,⁷ tumor diagnostics as for breast cancer,⁸ investigating the impact of lifestyle and nutrition on our body,⁹ or other fields such as neuroscience and psychology,¹⁰ sports, and leisure.¹¹ Even further, the operator independence, the depth sensitivity, and the scalability in addition to noninvasiveness make this option attractive for telemedicine and homecare of patients remotely.

We present a compact 3D diffractive microscope that can be inserted directly in a cell incubator for long-term observation of developing organisms. Our setup is particularly simple and robust, since it does not include any moving parts and is compatible with commercial cell culture containers. It has been designed to image large specimens ( > 100 × 100 × 100 µ m 3 ) with subcellular resolution. The sample’s optical properties [refractive index (RI) and absorption] are reconstructed in 3D from intensity-only images recorded with different illumination angles produced by an LED array. The reconstruction is performed using the beam propagation method embedded inside a deep-learning network where the layers encode the optical properties of the object. This deep neural network is trained for a given multiangle intensity acquisition. After training, the weights of the neural network deliver the 3D distribution of the optical properties of the sample. The effect of spherical aberrations due to the sample holder/air interfaces are taken into account in the forward model. Using this approach, we performed time-lapse 3D imaging of preimplantation mouse embryos over six days. Images of embryos from a single cell (low-scattering regime) to the blastocyst stage (highly scattering regime) were successfully reconstructed. Due to its subcellular resolution, our system can provide quantitative information on the embryos’ development and viability. Hence, this technology opens what we believe to be novel opportunities for 3D label-free live-cell imaging of whole embryos or organoids over long observation times.

We have discovered a new 4 h ultradian rhythm that occurs during the interphase of the cell cycle in a wide range of individual mammalian cells, including both primary and transformed cells. The rhythm was detected by holographic lens-free microscopy that follows the histories of the dry mass of thousands of single live cells simultaneously, each at a resolution of five minutes. It was vital that the rhythm was observed in inherently heterogeneous cell populations, thus eliminating synchronization and labeling bias. The rhythm is independent of circadian rhythm, and is temperature-compensated. We show that the amplitude of the fundamental frequency provides a way to quantify the effects of, chemical reagents on cells, thus shedding light on its mechanism. The rhythm is suppressed by proteostasis disruptors and is detected only in proliferating cells, suggesting that it represents a massive degradation and re-synthesis of protein every 4 h in growing cells.