Many tumor-targeted strategies have been used worldwide to limit the side effects and improve the effectiveness of therapies, such as chemotherapy, radiotherapy (RT), etc. Biophotonic therapy modalities comprise very promising alternative techniques for cancer treatment with minimal invasiveness and side-effects. These modalities use light e.g., laser irradiation in an extracorporeal or intravenous mode to activate photosensitizer agents with selectivity in the target tissue. Photothermal therapy (PTT) is a minimally invasive technique for cancer treatment which uses laser-activated photoabsorbers to convert photon energy into heat sufficient to induce cells destruction via apoptosis, necroptosis and/or necrosis. During the last decade, PTT has attracted an increased interest since the therapy can be combined with customized functionalized nanoparticles (NPs). Recent advances in nanotechnology have given rise to generation of various types of NPs, like gold NPs (AuNPs), designed to act both as radiosensitizers and photothermal sensitizing agents due to their unique optical and electrical properties i.e., functioning in dual mode. Functionalized AuNPS can be employed in combination with non-ionizing and ionizing radiation to significantly improve the efficacy of cancer treatment while at the same time sparing normal tissues. Here, we first provide an overview of the use of NPs for cancer therapy. Then we review many recent advances on the use of gold NPs in PTT, RT and PTT/RT based on different types of AuNPs, irradiation conditions and protocols. We refer to the interaction mechanisms of AuNPs with cancer cells via the effects of non-ionizing and ionizing radiations and we provide recent existing experimental data as a baseline for the design of optimized protocols in PTT, RT and PTT/RT combined treatment.

Many different tumor-targeted strategies are under development worldwide to limit the side effects and improve the effectiveness of cancer therapies. One promising method is to enhance the radiosensitization of the cancer cells while reducing or maintaining the normal tissue complication probability during radiation therapy using metallic nanoparticles (NPs). Radiotherapy with MV photons is more commonly available and applied in cancer clinics than high LET particle radiotherapy, so the addition of high-Z NPs has the potential to further increase the efficacy of photon radiotherapy in terms of NP radiosensitization. Generally, when using X-rays, mainly the inner electron shells are ionized, which creates cascades of both low and high energy Auger electrons. When using high LET particles, mainly the outer shells are ionized, which give electrons with lower energies than when using X-rays. The amount of the produced low energy electrons is higher when exposing NPs to heavy charged particles than when exposing them to X-rays. Since ions traverse the material along tracks, and therefore give rise to a much more inhomogeneous dose distributions than X-rays, there might be a need to introduce a higher number of NPs when using ions compared to when using X-rays to create enough primary and secondary electrons to get the desired dose escalations. This raises the questions of toxicity. This paper provides a review of the fundamental processes controlling the outcome of metallic NP-boosted photon beam and ion beam radiation therapy and presents some experimental procedures to study the biological effects of NPs’ radiosensitization. The overview shows the need for more systematic studies of the behavior of NPs when exposed to different kinds of ionizing radiation before applying metallic-based NPs in clinical practice to improve the effect of IR therapy.

Accurate in situ diagnosis and optimal surgical removal of a malignancy constitute key elements in reducing cancer-related morbidity and mortality. In surgical oncology, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. Conventional imaging techniques have attempted to serve as adjuvant tools for in situ biopsy and surgery guidance. However, no single imaging modality has been proven sufficient in terms of specificity, sensitivity, multiplexing capacity, spatial and temporal resolution. Moreover, most techniques are unable to provide information regarding the molecular tissue composition. In this review, we highlight the potential of Raman spectroscopy as a spectroscopic technique with high detection sensitivity and spatial resolution for distinguishing healthy from malignant margins in microscopic scale and in real time. A Raman spectrum constitutes an intrinsic “molecular finger-print” of the tissue and any biochemical alteration related to inflammatory or cancerous tissue state is reflected on its Raman spectral fingerprint. Nowadays, advanced Raman systems coupled with modern instrumentation devices and machine learning methods are entering the clinical arena as adjunct tools towards personalized and optimized efficacy in surgical oncology.

Over the past few years, tremendous research concerning the possibilities of gold nanoparticles in medicine has been conducted. Gold nanoparticles (AuNPs) are considered to be unique nanostructures due to their extraordinary chemical and physical properties. This review article aims to bring into light the potential applications of gold nanoparticles for diagnostic purposes in ophthalmology. More specifically, attention will be drawn to the utilization of AuNPs as contrast agents (CAs) in optical coherence tomography (OCT) and photoacoustic imaging (PAI), which are two novel imaging modalities for the visualization of the eye. None of these techniques requires the use of an imaging adjuvant to function; however, the addition of a contrast agent has been proposed for image improvement, and AuNPs are attractive candidates for this purpose. The in vitro, ex vivo, and in vivo studies investigating and supporting this concept will be presented thoroughly to elucidate whether AuNPs are eligible for imaging enhancement owing to their optical characteristics.

Advanced Raman spectroscopy (RS) systems have gained new interest in the field of medicine as an emerging tool for in vivo tissue discrimination. The coupling of RS with artificial intelligence (AI) algorithms has given a boost to RS to analyze spectral data in real time with high specificity and sensitivity. However, limitations are still encountered due to the large amount of clinical data which are required for the pre-training process of AI algorithms. In this study, human healthy and cancerous colon specimens were surgically resected from different sites of the ascending colon and analyzed by RS. Two transfer learning models, the one-dimensional convolutional neural network (1D-CNN) and the 1D–ResNet transfer learning (1D-ResNet) network, were developed and evaluated using a Raman open database for the pre-training process which consisted of spectra of pathogen bacteria. According to the results, both models achieved high accuracy of 88% for healthy/cancerous tissue discrimination by overcoming the limitation of the collection of a large number of spectra for the pre-training process. This gives a boost to RS as an adjuvant tool for real-time biopsy and surgery guidance.