The combination of immune checkpoint inhibitors and definitive radiotherapy is investigated for the multimodal treatment of cisplatin non-eligible locally advanced head and neck cancers (HNC). In the case of recurrent and metastatic HNC, immunotherapy has shown benefit over the EXTREME protocol, being already considered the standard treatment. One of the biggest challenges of multimodal treatment is to establish the optimal therapy sequence so that the synergistic effect is maximal. Thus, superior results were obtained for the administration of anti-CTLA4 immunotherapy followed by hypofractionated radiotherapy, but the anti-PD-L1 therapy demonstrates the maximum potential of radio-sensitization of the tumor in case of concurrent administration. The synergistic effect of radiotherapy–immunotherapy (RT–IT) has been demonstrated in clinical practice, with an overall response rate of about 18% for HNC. Given the demonstrated potential of radiotherapy to activate the immune system through already known mechanisms, it is necessary to identify biomarkers that direct the “nonresponders” of immunotherapy towards a synergistic RT–IT stimulation strategy. Stimulation of the immune system by irradiation can convert “nonresponder” to “responder”. With the development of modern techniques, re-irradiation is becoming an increasingly common option for patients who have previously been treated with higher doses of radiation. In this context, radiotherapy in combination with immunotherapy, both in the advanced local stage and in recurrent/metastatic of HNC radiotherapy, could evolve from the “first level” of knowledge (i.e., ballistic precision, dose conformity and homogeneity) to “level two” of “biological dose painting” (in which the concept of tumor heterogeneity and radio-resistance supports the need for doses escalation based on biological criteria), and finally to the “third level“ ofthe new concept of “immunological dose painting”. The peculiarity of this concept is that the radiotherapy target volumes and tumoricidal dose can be completely reevaluated, taking into account the immune-modulatory effect of irradiation. In this case, the tumor target volume can include even the tumor microenvironment or a partial volume of the primary tumor or metastasis, not all the gross and microscopic disease. Tumoricidal biologically equivalent dose (BED) may be completely different from the currently estimated values, radiotherapy treating the tumor in this case indirectly by boosting the immune response. Thus, the clinical target volume (CTV) can be replaced with a new immunological-clinical target volume (ICTV) for patients who benefit from the RT–IT association (Image 1).

Radiomics, a subdomain of artificial intelligence, consists in extracting a large volume of data from all medical imaging techniques and correlating them with clinical data in order to build predictive and prognostic models. Radiomics is related to radiogenomics that correlates genetic mutations and molecular and biological characteristics of tissues with information extracted from medical imaging. Both are state-of-the-art fields of translational biomedical research. The ability to predict early patient survival and response to treatment, but also the capacity to identify tumor subtypes non-invasively, could make radiomics a key player with an essential role in personalized oncology. In head and neck cancer radiotherapy, radiomic algorithms can predict not only the response to radiochemotherapy or induction chemotherapy but also the need for planning through adaptive radiotherapy (ART). Radiomics can also predict the risk of severe toxicities, especially that of xerostomia. Given the benefit that a de-escalation of treatment can bring in selected cases to improve the quality of life, radiomics is expected to be part of the therapeutic decision for head and neck cancers in the near future, and may help identify cases where de-escalation of multimodal therapy will not jeopardize the therapeutic benefit.

In the last decade, the analysis of the medical images has evolved significantly, applications and tools capable to extract quantitative characteristics of the images beyond the discrimination capacity of the investigator’s eye being developed. The applications of this new research field, called radiomics, presented an exponential growth with direct implications in the diagnosis and prediction of response to therapy. Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype with a severe prognosis, despite the aggressive multimodal treatments applied according to the guidelines. Radiomics has already proven the ability to differentiate TNBC from fibroadenoma. Radiomics features extracted from digital mammography may also distinguish between TNBC and non-TNBC. Recent research has identified three distinct subtypes of TNBC using IRM breast images voxel-level radiomics features (size/shape related features, texture features, sharpness). The correlation of these TNBC subtypes with the clinical response to neoadjuvant therapy may lead to the identification of biomarkers in order to guide the clinical decision. Furthermore, the variation of some radiomics features in the neoadjuvant settings provides a tool for the rapid evaluation of treatment efficacy. The association of radiomics features with already identified biomarkers can generate complex predictive and prognostic models. Standardization of image acquisition and also of radiomics feature extraction is required to validate this method in clinical practice.

Immunotherapy, the modern oncological treatment with immune checkpoint inhibitors (ICIs), has been part of the clinical practice for malignant melanoma for more than a decade. Anti-cytotoxic T-lymphocyte antigen 4 (CTLA4), anti-programmed cell death Protein 1 (PD-1), or anti programmed death-ligand 1 (PD-L1) agents are currently part of the therapeutic arsenal of metastatic or relapsed disease in numerous cancers; more recently, they have also been evaluated and validated as consolidation therapy in the advanced local stage. The combination with radiotherapy, a treatment historically considered loco-regional, changes the paradigm, offering—via synergistic effects—the potential to increase immune-mediated tumor destruction. However, the fragile balance between the tumoricidal effects through immune mechanisms and the immunosuppression induced by radiotherapy means that, in the absence of ICI, the immune-mediated potentiation effect of radiotherapy at a distance from the site of administration is rare. Through analysis of the preclinical and clinical data, especially the evidence from the PACIFIC clinical trial, we can consider that hypofractionated irradiation and reduction of the irradiated volume, in order to protect the immune-infiltrated tumor microenvironment, performed concurrently with the immunotherapy or a maximum of 2 weeks before the start of ICI treatment, could bring maximum benefits. In addition, avoiding radiation-induced lymphopenia (RILD) by protecting some anatomical lymphoid structures or large blood vessels, as well as the use of irradiation of partial tumor volumes, even in plurimetastatic disease, for the conversion of a "cold" immunological tumor into a “hot” immunological tumor are modern concepts of radiotherapy in the era of immunotherapy. Low-dose radiotherapy could also be proposed in plurimetastatic cases, the effect being different (modeling of the TME) from that of high doses per fraction irradiation (cell death with release of antigens that facilitates immune-mediated cell death).