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Cancers are rare pathologies in children. Improvement in survival rates has been obtained thanks to new therapeutic strategies based on the identification of risk factors. Targeted therapies in paediatric oncology are new treatments providing hope that cure is achievable without long-term sequelae.The «one size fits all» approach is seriously challenged by rapid progression of medical knowledge, especially in the field of individual genome expression. It is currently known that the anti-tumour effect of a given treatment and possible side effects at the level of healthy tissues, can at least partly be predicted and explained by individual variations of gene expression. However, most of us realize that these differences in response are also linked to a variety of other individual characteristics, such as for example the environment and socio-economic factors. Without any possible doubt, there are multiple problems (technical, administrative, financial, cultural and ethical) to be solved, before we witness the real irruption of precision medicine and its holistic individualized approach in our daily oncological practice. CRT0066101 It has to start with an international effort, disregarding borders of individual countries, in order to obtain very large amounts of data (with a high degree of variability to avoid bias). This holistic approach, at both societal and individual levels, is the entrance door for a personalized approach in care, whether this is curative, predictive or preventive.Radiotherapy (RT), both with a curative and a palliative intent, is one of the cornerstones of oncological treatments. A variety of symptoms linked to cancer can be relieved with RT (such as pain, bleeding, compression exerted by a tumour lesion…). Very often, palliative RT is proposed when other medical treatments (painkillers, morphine…) are no longer efficient, or the patient does not tolerate them anymore. Palliative RT is an integral part of the global supportive oncological care. Indeed, patients' wishes and prognosis are taken into account in each and every step of the treatment pathway. Every treatment deserves an individualized approach and benefits from the best available techniques.Cancer incidence is steadily progressing worldwide, in parallel with the aging of the population. Workload is increasing constantly, especially in the fields of oncology and radiotherapy. This is particularly worrysome, as there is a general shortage of skilled professionals in the field (for example in medical physics). Moreover, every single patient does represent an enormous amount of data issued from a wide range of sources. This is especially true as far a medical imaging is concerned. Extraction of morphological data (anatomical location and extent of the tumour) and functional data (tumour biology and metabolism in general) becomes laborious. Moreover, images contain information which cannot be discerned by the human eye. Therefore, to handle shortage of human resources and transform this enormous amount of data automatically, artificial intelligence becomes a «must have». We intend to highlight the growing importance of radiomics as a cornerstone in automation of processes in radiotherapy, especially for treatment planification and a more personalized individualized treatment approach.Radiotherapy established itself in the 20th century as an essential modality in the fight against cancer. The major technological advances of the last decades have allowed a considerable improvement in the therapeutic window. They have also paved the way for stereotactic radiotherapy and new indications. The aim of this article is to enable readers to understand external radiotherapy in 2021 and to understand the challenges of tomorrow. Three areas of improvement in the discipline will be described, the optimization of the prescribed therapeutic dose, the improvement of the distribution of this dose and, finally, the better understanding of radiobiology. For each of these axes, the current implications will be described as well as those which could/should have a major impact on the radiotherapy. FLASH radiotherapy will also be discussed.The anatomo-pathological diagnosis of tumors is based on many criteria related mainly to image analysis. Currently, in most pathology laboratories, tissues or cells are placed on glass slides and directly analyzed with an optical microscope. Because of technological evolutions, it is currently possible to digitize slides (digital pathology). The digitization of whole slides has allowed the development of computer programs of artificial intelligence (AI) for image analysis. Applied to tumour pathology, this technology allows the detection, diagnosis or evaluation of the prognosis of neoplastic lesions. There are many challenges associated with the use of AI in routine pathology. These are mainly related to the amount of data to be analyzed and to the development of reliable algorithms. Nevertheless, this technology is promising and could become a valuable aid in the field of precision medicine for which the amount of data related to a patient is constantly increasing.In current practice, the use of circulating oncological biomarkers by clinicians is almost inseparable from cancer patients management. However, the interpretation of the results is not always easy because it is more specific to laboratory medicine and involves notions of peri-analytical orders as well as analytical sensitivity and specificity. In the past, the development of new analytical techniques improved the analytical sensitivity or allowed the implementation of new biomarkers; this observation would still be true today. Mass spectrometry, microRNA assay, or Single Molecule Array (SiMoA) are recent analytical developments with very good analytical performances that could contribute to the improvement of cancer patient management.Oncological imaging is a subspecialty of medical imaging and focuses on the workup and the follow-up of cancer. Oncological imaging takes into account all the specificities of cancer diseases, which is a constantly evolving field, especially in the era of precision medicine, and plays a key role in the care of cancer patients. It permits reliable diagnosis and gives precious information concerning disease extension at diagnosis, which is essential for the treatment planning. Oncological imaging allows also followup of patients under treatment, using response evaluation scores. Interventional imaging, which provides minimally invasive procedures, is useful in order to obtain a histological diagnosis, to treat some tumour or to improve quality of life of cancer patients. Finally, numerous perspectives, among them the advent of artificial intelligence (radiomics), will further strengthen the role of oncologic imaging in the near future.

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