A Machine Learning-Optimized System for Pulsatile, Photo- and Chemotherapeutic Treatment Using Near-Infrared Responsive MoS2-Based Microparticles in a Breast Cancer Model.

Multimodal cancer therapies are often required for progressive cancers due to the high persistence and mortality of the disease and the negative systemic side effects of traditional therapeutic methods. Thus, the development of less invasive modalities for recurring treatment cycles is of clinical significance. Herein, a light-activatable microparticle system was developed for localized, pulsatile delivery of anticancer drugs with simultaneous thermal ablation by applying controlled ON-OFF thermal cycles using near-infrared laser irradiation. The system is composed of poly(caprolactone) microparticles of 200 µm size containing molybdenum disulfide (MoS2) nanosheets as the photothermal agent and hydrophilic doxorubicin or hydrophobic violacein, as model drugs. Upon irradiation, the nanosheets heat up to ≥50 °C leading to polymer softening and release of the drug. MoS2 nanosheets exhibit high photothermal conversion efficiency and require low-power laser irradiation. A machine learning algorithm was applied to acquire the optimal laser operation conditions. In a mouse subcutaneous model of 4T1 triple-negative breast cancer, 25 microparticles were intratumorally administered, and after 3-cycle laser treatment, the system conferred synergistic phototherapeutic and chemotherapeutic effects. Our on-demand, pulsatile synergistic treatment resulted in increased median survival up to 39 days post start of treatment compared to untreated mice, with complete eradication of the tumors at the primary site. Such a system is therapeutically relevant for patients in need of recurring cycles of treatment on small tumors, since it provides precise localization and low invasiveness and is not cross-resistant with other treatments.

Cancer tissue of origin constrains the growth and metabolism of metastases.

Metastases arise from subsets of cancer cells that disseminate from the primary tumour1,2. The ability of cancer cells to thrive in a new tissue site is influenced by genetic and epigenetic changes that are important for disease initiation and progression, but these factors alone do not predict if and where cancers metastasize3,4. Specific cancer types metastasize to consistent subsets of tissues, suggesting that primary tumour-associated factors influence where cancers can grow. We find primary and metastatic pancreatic tumours have metabolic similarities and that the tumour-initiating capacity and proliferation of both primary-derived and metastasis-derived cells is favoured in the primary site relative to the metastatic site. Moreover, propagating cells as tumours in the lung or the liver does not enhance their relative ability to form large tumours in those sites, change their preference to grow in the primary site, nor stably alter aspects of their metabolism relative to primary tumours. Primary liver and lung cancer cells also exhibit a preference to grow in their primary site relative to metastatic sites. These data suggest cancer tissue of origin influences both primary and metastatic tumour metabolism and may impact where cancer cells can metastasize.

Texaphyrin-Based Calcium Sensor for Multimodal Imaging.

The ability to monitor intracellular calcium concentrations using fluorescent probes has led to important insights into biological signaling processes at the cellular level. An important challenge is to relate such measurements to broader patterns of signaling across fields of view that are inaccessible to optical techniques. To meet this need, we synthesized molecular probes that couple calcium-binding moieties to lanthanide texaphyrins, resulting in complexes endowed with a diverse complement of magnetic and photophysical properties. We show that the probes permit intracellular calcium levels to be assessed by fluorescence, photoacoustic, and magnetic resonance imaging modalities and that they are detectable by multimodal imaging in brain tissue. This work thus establishes a route for monitoring signaling processes over a range of spatial and temporal scales.

A Machine Learning-optimized system for on demand, pulsatile, photo- and chemo-therapeutic treatment using near-infrared responsive MoS 2 -based microparticles in a breast cancer model.

Cancer therapy research is of high interest because of the persistence and mortality of the disease and the side effects of traditional therapeutic methods, while often multimodal treatments are necessary based on the patient's needs. The development of less invasive modalities for recurring treatment cycles is thus of critical significance. Herein, a light-activatable microparticle system was developed for localized, pulsatile delivery of anticancer drugs with simultaneous thermal ablation, by applying controlled ON-OFF thermal cycles using near-infrared laser irradiation. The system is composed of poly(caprolactone) microparticles of 200 µm size with incorporated molybdenum disulfide (MoS 2 ) nanosheets as the photothermal agent and hydrophilic doxorubicin or hydrophobic violacein, as model drugs. Upon irradiation the nanosheets heat up to ≥50 °C leading to polymer matrix melting and release of the drug. MoS 2 nanosheets exhibit high photothermal conversion efficiency and allow for application of low power laser irradiation for the system activation. A Machine Learning algorithm was applied to acquire optimal laser operation conditions; 0.4 W/cm 2 laser power at 808 nm, 3-cycle irradiation, for 3 cumulative minutes. In a mouse subcutaneous model of 4T1 triple-negative breast cancer, 25 microparticles were intratumorally administered and after 3-cycle laser treatment the system conferred synergistic phototherapeutic and chemotherapeutic effect. Our on-demand, pulsatile synergistic treatment resulted in increased median survival up to 40 days post start of treatment compared to untreated mice, with complete eradication of the tumors at the primary site. Such a system could have potential for patients in need of recurring cycles of treatment on subcutaneous tumors.

Maximizing response to intratumoral immunotherapy in mice by tuning local retention.

Direct injection of therapies into tumors has emerged as an administration route capable of achieving high local drug exposure and strong anti-tumor response. A diverse array of immune agonists ranging in size and target are under development as local immunotherapies. However, due to the relatively recent adoption of intratumoral administration, the pharmacokinetics of locally-injected biologics remains poorly defined, limiting rational design of tumor-localized immunotherapies. Here we define a pharmacokinetic framework for biologics injected intratumorally that can predict tumor exposure and effectiveness. We find empirically and computationally that extending the tumor exposure of locally-injected interleukin-2 by increasing molecular size and/or improving matrix-targeting affinity improves therapeutic efficacy in mice. By tracking the distribution of intratumorally-injected proteins using positron emission tomography, we observe size-dependent enhancement in tumor exposure occurs by slowing the rate of diffusive escape from the tumor and by increasing partitioning to an apparent viscous region of the tumor. In elucidating how molecular weight and matrix binding interplay to determine tumor exposure, our model can aid in the design of intratumoral therapies to exert maximal therapeutic effect.

Magnetic Retrieval of Encapsulated Beta Cell Transplants from Diabetic Mice Using Dual-Function MRI Visible and Retrievable Microcapsules.

Encapsulated beta cell transplantation offers a potential cure for a subset of diabetic patients. Once transplanted, beta cell grafts can help to restore glycemic control; however, locating and retrieving cells in the event of graft failure may pose a surgical challenge. Here, a dual-function nanoparticle-loaded hydrogel microcapsule is developed that enables graft retrieval under an applied magnetic field. Additionally, this system facilitates graft localization via magnetic resonance imaging (MRI), and graft isolation from the immune system. Iron oxide nanoparticles encapsulated within alginate hydrogel capsules containing viable islets are transplanted and the in vitro and in vivo retrieval of capsules containing nanoparticles functionalized with various ligands are compared. Capsules containing islets co-encapsulated with COOH-coated nanoparticles restore normal glycemia in immunocompetent diabetic mice for at least 6 weeks, can be visualized using MRI, and are retrievable in a magnetic field. Application of a magnetic field for 90 s via a magnetically assisted retrieval device facilitates rapid retrieval of up to 94% (±3.1%) of the transplant volume 24 h after surgical implantation. This strategy aids monitoring of cell-capsule locations in vivo, facilitates graft removal at the end of the transplant lifetime, and may be applicable to many encapsulated cell transplant systems.

Wireless resonant circuits for the minimally invasive sensing of biophysical processes in magnetic resonance imaging.

Biological electromagnetic fields arise throughout all tissue depths and types, and correlate with physiological processes and signalling in organs of the body. Most of the methods for monitoring these fields are either highly invasive or spatially coarse. Here, we show that implantable active coil-based transducers that are detectable via magnetic resonance imaging enable the remote sensing of biological fields. These devices consist of inductively coupled resonant circuits that change their properties in response to electrical or photonic cues, thereby modulating the local magnetic resonance imaging signal without the need for onboard power or wired connectivity. We discuss design parameters relevant to the construction of the transducers on millimetre and submillimetre scales, and demonstrate their in vivo functionality for measuring time-resolved bioluminescence in rodent brains. Biophysical sensing via microcircuits that leverage the capabilities of magnetic resonance imaging may enable a wide range of biological and biomedical applications.

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, whether they are unconstrained therapeutic transplants, migrating cells during tumor metastasis, or cell populations induced by an immunological response, the role of oxygen in their fate and function is known to be pivotal albeit not well understood in vivo. To address such a challenge in the case of generation of a bioartificial pancreas, we have combined fluorine magnetic resonance imaging and unsupervised machine learning to monitor over time the spatial arrangement and the oxygen content of implants encapsulating pancreatic islets that are unconstrained in the intraperitoneal (IP) space of healthy and diabetic mice. Statistically significant trends in the postimplantation temporal dependence of oxygen content between aggregates of 0.5-mm or 1.5-mm alginate microcapsules were identified in vivo by looking at their dispersity as well as arrangement in clusters of different size and estimating oxygen content on a pixel-by-pixel basis from thousands of 2D images. Ultimately, we found that this dependence is stronger for decreased implant capsule size consistent with their tendency to also induce a larger immunological response. Beyond the bioartificial pancreas, this work provides a framework for the simultaneous spatiotemporal tracking and oxygen sensing of other cell populations and biomaterials that change over time to better understand and improve therapeutic design across diverse applications such as cellular transplant therapy, treatments preventing metastatic formation, and modulators for improving immunologic response, for all of which oxygen is a major mechanistic component.

Investigation of a clinical PET detector module design that employs large-area avalanche photodetectors.

We investigated the feasibility of designing an Anger-logic PET detector module using large-area high-gain avalanche photodiodes (APDs) for a brain-dedicated PET/MRI system. Using Monte Carlo simulations, we systematically optimized the detector design with regard to the scintillation crystal, optical diffuser, surface treatment, layout of large-area APDs, and signal-to-noise ratio (SNR, defined as the 511 keV photopeak position divided by the standard deviation of noise floor in an energy spectrum) of the APD devices. A detector prototype was built comprising an 8 × 8 array of 2.75 × 3.00 × 20.0 mm3 LYSO (lutetium-yttrium-oxyorthosilicate) crystals and a 22.0 × 24.0 × 9.0 mm3 optical diffuser. From the four designs of the optical diffuser tested, two designs employing a slotted diffuser are able to resolve all 64 crystals within the block with good uniformity and peak-to-valley ratio. Good agreement was found between the simulation and experimental results. For the detector employing a slotted optical diffuser, the energy resolution of the global energy spectrum after normalization is 13.4 ± 0.4%. The energy resolution of individual crystals varies between 11.3 ± 0.3% and 17.3 ± 0.4%. The time resolution varies between 4.85 ± 0.04 (center crystal), 5.17 ± 0.06 (edge crystal), and 5.18 ± 0.07 ns (corner crystal). The generalized framework proposed in this work helps to guide the design of detector modules for selected PET system configurations, including scaling the design down to a preclinical PET system, scaling up to a whole-body clinical scanner, as well as replacing APDs with other novel photodetectors that have higher gain or SNR such as silicon photomultipliers.

Scintillation induced response in passively-quenched Si-based single photon counting avalanche diode arrays.

An optical electrical model which studies the response of Si-based single photon counting arrays, specifically silicon photomultipliers (SiPMs), to scintillation light has been developed and validated with analytically derived and experimental data. The scintillator-photodetector response in terms of relative pulse height, 10%-90% rise/decay times to light stimuli of different rise times (ranging from 0.1 to 5 ns) and decay times (ranging from 1 to 50 ns), as well as for different decay times of the photodetector are compared in theory and simulation. A measured detector response is used as a reference to further validate the model and the results show a mean deviation of simulated over measured values of 1%.

Photo-detectors for time of flight positron emission tomography (ToF-PET).

We present the most recent advances in photo-detector design employed in time of flight positron emission tomography (ToF-PET). PET is a molecular imaging modality that collects pairs of coincident (temporally correlated) annihilation photons emitted from the patient body. The annihilation photon detector typically comprises a scintillation crystal coupled to a fast photo-detector. ToF information provides better localization of the annihilation event along the line formed by each detector pair, resulting in an overall improvement in signal to noise ratio (SNR) of the reconstructed image. Apart from the demand for high luminosity and fast decay time of the scintillation crystal, proper design and selection of the photo-detector and methods for arrival time pick-off are a prerequisite for achieving excellent time resolution required for ToF-PET. We review the two types of photo-detectors used in ToF-PET: photomultiplier tubes (PMTs) and silicon photo-multipliers (SiPMs) with a special focus on SiPMs.

PET & SPECT instrumentation.

The nuclear medical imaging methods, positron emission tomography (PET) and single photon emission computed tomography (SPECT), utilize the detection of gamma rays leaving the body after a radioactive tracer has been administered. The sensitivity of PET allows the detection of picomolar tracer amounts in vivo and current technology offers millimeter (PET) or submillimeter (SPECT) spatial resolution. These techniques are used in clinical and preclinical applications. The basic principles of gamma ray detection and image generation in PET and SPECT are summarized in this chapter. Furthermore, effects causing degradation of image quality are discussed.