Lucia Florescu

Objective. There is a need for patient-specific dose quantification (dosimetry) in molecular radiation therapy (MRT). Cherenkov light generated in the tissue by charged particles produced by the radioactive decay of radiopharmaceuticals offers an unprecedented opportunity for MRT dosimetry. While the intensity of the emitted Cherenkov light is proportional to the dose, the intensity of light emerging and measured at the patient surface depends on patient anatomy and tissue optical characteristics. This results in an inter-patient variability of the linear relationship between Cherenkov light intensity at the patient surface and the dose delivered to the tumour that hinders the implementation of Cherenkov light-based dosimetry. A multi-patient study of Cherenkov light emission in MRT of thyroid cancer is performed and a correction technique for the surface light intensity is introduced to reduce this inter-patient variability. Approach. Numerical experiments using clinical patient computed tomography data and Monte Carlo simulations are performed for a set of patient anatomies and a range of values of tissue optical parameters and tumour radioisotope uptakes, resulting in 135 treatment realisations. The impact of anatomy and tissue optical characteristics on the characteristics of Cherenkov light is investigated. A patient-specific factor defined as the product between the fraction of the light emitted in the tumour that emerges on the patient surface and tumour volume and mass density is introduced to correct the intensity of light emerging at the patient surface for the dependence on PA and tissue optical characteristics. Main results. There is a large inter-patient variability in the relationship between the surface light intensity and dose delivered to the tumour. The correction technique greatly reduces this variability and enables the derivation of a dosimetry calibration curve. Significance. This study provides an important step towards quantitative MRT dosimetry based on Cherenkov light emitted during treatment.

We introduce the hybrid broken-ray tomography (HBRT) for three-dimensional imaging of weakly scattering systems. The HBRT utilizes fluorescent contrast agents and combines the principles and advantages of the broken-ray tomography and the non-reciprocal broken-ray tomography introduced by us previously. The HBRT uses angularly resolved intensity measurements at the incident and fluorescence wavelengths to reconstruct the attenuation and scattering coefficients at the excitation wavelength anywhere within the sample, as well as the attenuation coefficient at the fluorescence wavelength and the contrast agent concentration in the regions of contrast agent accumulation. The principles of HBRT have been validated by Monte Carlo simulations.

External beam photon radiation therapy (EBRT) utilizes high-energy X-ray photon beams produced by a linear accelerator to deliver radiation doses to the diseased tissue. As the X-ray photons interact with biological tissue, charged particles are produced, which propagate and deposit energy as radiation dose along the way. In addition to depositing dose, the charged particles that have a high enough energy and a phase velocity exceeding the phase velocity of light in the tissue also induce the emission of Cherenkov light.¹ The ability to measure at the patient’s surface Cherenkov light produced during radiation therapy^{2 – 4} opens new avenues for applications to radiation therapy dosimetry^4,5 and tissue functional imaging.^3,6,7

The clinical translation of nanoparticle-based treatments remains limited due to the unpredictability of (nanoparticle) NP pharmacokinetics$\unicode{x2014}$how they distribute, accumulate, and clear from the body. Predicting these behaviours is challenging due to complex biological interactions and the difficulty of obtaining high-quality experimental datasets. Existing AI-driven approaches rely heavily on data-driven learning but fail to integrate crucial knowledge about NP properties and biodistribution mechanisms. We introduce a multi-view deep learning framework that enhances pharmacokinetic predictions by incorporating prior knowledge of key NP properties such as size and charge into a cross-attention mechanism, enabling context-aware feature selection and improving generalization despite small datasets. To further enhance prediction robustness, we employ an ensemble learning approach, combining deep learning with XGBoost (XGB) and Random Forest (RF), which significantly outperforms existing AI models. Our interpretability analysis reveals key physicochemical properties driving NP biodistribution, providing biologically meaningful insights into possible mechanisms governing NP behaviour in vivo rather than a black-box model. Furthermore, by bridging machine learning with physiologically based pharmacokinetic (PBPK) modelling, this work lays the foundation for data-efficient AI-driven drug discovery and precision nanomedicine.

Numerical experiments for the radiation therapy of laryngeal cancer are performed using clinical data to investigate the characteristics of Cherenkov light emitted during treatment delivery, and the origin of light within the patient emerging on certain regions on the patient surface. Intensity-Modulated Radiation Therapy (IMRT) and Volumetric-Modulated Arc Radiation Therapy (VMAT), the two main treatment modalities used clinically, are considered. It is confirmed that the emitted Cherenkov light is dominant in the ultraviolet spectral region and is concentrated in tissue in regions of high-dose delivery, with the spatial distribution depending on the treatment type. The Cherenkov light at the patient surface is dominant in the near-infrared spectral region. Light emitted within the tumour and immediately surrounding tissue emerges at the patient surface on a well-defined radiation-beam-independent region that is also the region of high surface light intensity. This suggest that surface light measurements restricted to this smaller region on the patient surface (that can be determined through simulations prior to the treatment) could enable probing the tumour, while being easier to integrate with the radiotherapy system. The spectral and spatial characteristics of the emitted light that contributes to surface light (the internal light sources) are also investigated, and the unveiled characteristics can provide guidance for the development of image reconstruction algorithms for Cherenkov light-based tomographic imaging for tumour monitoring during radiation therapy.

Numerical experiments for the radiation therapy of laryngeal cancer are performed using clinical data to investigate the characteristics of Cherenkov light emitted during treatment delivery, and the origin of light within the patient emerging on certain regions on the patient surface. Intensity-Modulated Radiation Therapy (IMRT) and Volumetric-Modulated Arc Radiation Therapy (VMAT), the two main treatment modalities used clinically, are considered. It is confirmed that the emitted Cherenkov light is dominant in the ultraviolet spectral region and is concentrated in tissue in regions of high-dose delivery, with the spatial distribution depending on the treatment type. The Cherenkov light at the patient surface is dominant in the near-infrared spectral region. Light emitted within the tumour and immediately surrounding tissue emerges at the patient surface on a well-defined radiation-beam-independent region that is also the region of high surface light intensity. This suggest that surface light measurements restricted to this smaller region on the patient surface (that can be determined through simulations prior to the treatment) could enable probing the tumour, while being easier to integrate with the radiotherapy system. The spectral and spatial characteristics of the emitted light that contributes to surface light (the internal light sources) are also investigated, and the unveiled characteristics can provide guidance for the development of image reconstruction algorithms for Cherenkov light-based tomographic imaging for tumour monitoring during radiation therapy.

We perform Monte Carlo simulations using clinical CT geometries to in-vestigate Cherenkov light emission in molecular radiation therapy of hyperthyroidism and papillary thyroid carcinoma and demonstrate that Cherenkov-light based dosimetry could be feasible.

Optical methods of biomedical tomographic imaging are of considerable interest due to their non-invasive nature and sensitivity to physiologically important markers. Similarly to other imaging modalities, optical methods can be enhanced by utilizing extrinsic contrast agents. Typically, these are fluorescent molecules, which can aggregate in regions of interest due to various mechanisms. In the current approaches to imaging, the intrinsic (related to the tissue) and extrinsic (related to the contrast agent) optical parameters are determined separately. This can result in errors, in particular, due to using simplified heuristic models for the spectral dependence of the optical parameters. Recently, we have developed the theory of non-reciprocal broken-ray tomography (NRBRT) for fluorescence imaging of weakly scattering systems. NRBRT enables simultaneous reconstruction of the fluorophore concentration as well as of the intrinsic optical attenuation coefficient at both the excitation and the emission wavelengths. Importantly, no assumption about the spectral dependence of the tissue optical properties is made in NRBRT. In this study, we perform numerical validation of NRBRT under realistic conditions using the Monte Carlo method to generate forward data. We demonstrate that NRBRT can be used for tomographic imaging of samples of up to four scattering lengths in size. The effects of physical characteristics of the detectors such as the area and the acceptance angle are also investigated.

Numerical experiments based on Monte Carlo simulations and clinical CT data are performed to investigate the spatial and spectral characteristics of Cherenkov light emission and the relationship between Cherenkov light intensity and deposited dose in molecular radiotherapy of hyperthyroidism and papillary thyroid carcinoma. It is found that Cherenkov light is emitted mostly in the treatment volume, the spatial distribution of Cherenkov light at the surface of the patient presents high-value regions at locations that depend on the symmetry and location of the treatment volume, and the surface light in the near-infrared spectral region originates from the treatment site. The effect of inter-patient variability in the tissue optical parameters and radioisotope uptake on the linear relationship between the dose absorbed by the treatment volume and Cherenkov light intensity at the surface of the patient is investigated, and measurements of surface light intensity for which this effect is minimal are identified. The use of Cherenkov light measurements at the patient surface for molecular radiation therapy dosimetry is also addressed.

Broken ray transforms (BRTs) are typically considered to be reciprocal, meaning that the transform is independent of the direction in which a photon travels along a given broken ray. However, if the photon can change its energy (or be absorbed and re-radiated at a different frequency) at the vertex of the ray, then reciprocity is lost. In optics, non-reciprocal BRTs are applicable to imaging problems with fluorescent contrast agents. In the case of x-ray imaging, problems with single Compton scattering also give rise to non-reciprocal BRTs. In this paper, we focus on tomographic optical fluorescence imaging and show that, by reversing the path of a photon and using the non-reciprocity of the data function, we can reconstruct simultaneously and independently all optical properties of the medium (the intrinsic attenuation coefficients at the excitation and the fluorescence frequency and the concentration of the contrast agent). Our results are also applicable to inverting BRTs that arise due to single Compton scattering.