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Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.

Optical spectroscopy is studied to contribute to skin cancer diagnosis. Indeed, optical spectra are modified along cancer progression and provide complementary information (e.g., on metabolism and tissue structure) to clinical examination for surgical guidance [1,2]. The current original dataset is made of autofluorescence and diffuse reflectance spectra acquired in vivo on 131 patients’ skin with the SpectroLive device [3,4]. Spatially-resolved spectroscopy measurements were performed using a multi-fiber optic probe featuring 4 distances (0.4–1 mm) between excitation and collection optical fibers: spatial resolution allows spectra acquired at different distances to carry information from different depths in skin tissues. Five types of autofluorescence spectra were acquired using five different wavelength excitations (on the 365–415 nm spectral range) in order to collect information on several skin endogenous fluorophores (e.g., flavins, collagen). A sixth light source (white broadband) was used to acquire diffuse reflectance spectra carrying information about skin scattering properties and skin endogenous absorbers such as melanin and hemoglobin. Patients were proposed to be included into the clinical trial if they were suspected of suffering from actinic keratoses (precancerous skin lesions) or from basal or squamous cell carcinomas: in all cases, complete diagnostics is provided in the dataset. To increase the interest of the dataset and evaluate the dependence of optical spectra (intensity, shape) not only on pathological states but also on healthy skin features (civil age, skin age, gender, phototype, anatomical site), spectra were acquired for all 131 patients on two so-called “reference” skin sites known to rarely suffer from skin cancer: palm of the hand (featuring a thick skin type) and inner wrist (featuring thin skin). Spectra are available in .tab files: first column displays the spectral range on which intensity spectra were recorded (317–788 nm) and each following column provides an intensity spectrum acquired by each spectrometer for a given combination of light source excitation and distance. Each of the 131 folders corresponding to each of the 131 patients contains a .json file providing patients clinical features: gender, civil age, skin age, phototype score and class. All .tab files names include anatomical site and anatomopathological diagnostics of the skin site on which spectra were acquired: codes were defined to match a letter or an acronym to each diagnostic and anatomical site. To ensure quality control, a spectrum was acquired on the same calibration standard before starting spectra acquisition on each patient. It is therefore possible to follow the impact of the acquisition optical chain ageing during the 4.5 years that the patients were included. This dataset can be used by epidemiologists for the characterization of populations affected by skin cancers (gender ratio, mean age, anatomical sites typically affected, etc.); it may also be used by researchers in artificial intelligence to develop innovative methods to process such data and contribute to non-invasive diagnostics of skin cancers whose incidence is steadily increasing.