Although the rate of severe toxicity was very low, the real impact of WLI on patients' outcomes remains unproven, probably due to the narrow dose limits that can be delivered to the whole lung parenchyma. New strategies to prevent or treat lung metastases in these patients should be tested. Ultra-fractionated radiotherapy concurrent with modern chemotherapy protocols could be tested in this setting due to the chemo-sensitizing effect and negligible radio-induced toxicity of fraction doses <0.5 Gy.

BackgroundOwing to highly conformed dose distribution, intensity modulated radiation therapy (IMRT) has the potential to improve treatment results of radiotherapy (RT). Postoperative RT is a standard adjuvant treatment in conservative treatment of breast cancer (BC). The aim of this review is to analyze available evidence from randomized controlled trials (RCTs) on IMRT in BC, particularly in terms of reduction of side effects.MethodsA literature search of the bibliographic database PubMed, from January 1990 through November 2016, was performed. Only RCTs published in English were included.ResultsTen articles reporting data from 5 RCTs fulfilled the selection criteria and were included in our review. Three out of 5 studies enrolled only selected patients in terms of increased risk of toxicity. Three studies compared IMRT with standard tangential RT. One study compared the results of IMRT in the supine versus the prone position, and one study compared standard treatment with accelerated partial breast IMRT. Three studies reported reduced acute and/or late toxicity using IMRT compared with standard RT. No study reported improved quality of life.ConclusionIMRT seems able to reduce toxicity in selected patients treated with postoperative RT for BC. Further analyses are needed to better define patients who are candidates for this treatment modality.

Between January 1979 and December 1987, 99 patients (pts.) with a diagnosis of localized soft tissue sarcoma of the extremities received preoperative radiation therapy (Preop. RT, 50 pts.) or postoperative irradiation (Postop. RT, 49 pts.). In the preop. RT group, doses ranged from 42 Gy/17 fractions to 51 Gy/17 fractions; pts. treated with RT after surgery, received a dose comprised between 46 Gy/23 fractions to 66 Gy/33 fractions. The surgical procedure consisted of making a wide resection of the mass with preservation of the affected limb, in each patient. The main cause of failure was dissemination of the disease (33.3%). The incidence of local failures was low (7.1%). Recurrences were related to the size of the disease (5 cm: 0/12; 5-10 cm: 2/45 2.3%; 10 cm: 5/42, 11.9%), as were also distant metastases. The incidence of distant failures was higher in the group treated with preop. RT (44.0% vs. 22.4%), probably because a higher percentage of patients in this group had large volume diseases. Late sequelae were evaluable in 59 pts. with a follow up longer than 24 months. The incidence of complications was low (10.1%, 6/59); it was higher in the preoperative than in the postoperative group (15.4% vs. 6.1%); this observation is probably related to the different modalities of fractionation.

In recent decades, artificial intelligence (AI) tools have been applied in many medical fields, opening the possibility of finding novel solutions for managing very complex and multifactorial problems, such as those commonly encountered in radiotherapy (RT). We conducted a PubMed and Scopus search to identify the AI application field in RT limited to the last four years. In total, 1824 original papers were identified, and 921 were analyzed by considering the phase of the RT workflow according to the applied AI approaches. AI permits the processing of large quantities of information, data, and images stored in RT oncology information systems, a process that is not manageable for individuals or groups. AI allows the iterative application of complex tasks in large datasets (e.g., delineating normal tissues or finding optimal planning solutions) and might support the entire community working in the various sectors of RT, as summarized in this overview. AI-based tools are now on the roadmap for RT and have been applied to the entire workflow, mainly for segmentation, the generation of synthetic images, and outcome prediction. Several concerns were raised, including the need for harmonization while overcoming ethical, legal, and skill barriers.