Editorial for “Natural Changes in Radiological and Radiomics Features on MRIs of Soft‐Tissue Sarcomas Naïve of Treatment: Correlations With Histology and Patients' Outcome”

Editorial for “Natural Changes in Radiological and Radiomics Features on MRIs of Soft-Tissue Sarcomas Naïve of Treatment: Correlations With Histology and Patients’ Outcome” Is it possible to observe in an ethical manner the natural changes of tumors over time, without any treatments? For rare tumors, unfortunately, the answer to this question may be affirmative. Rare tumors are frequently affected by a late diagnosis, and nonetheless, late presentation in specialized centers. This delay renders sometimes necessary repetition of the baseline cross-sectional imaging study, MRI or CT, before the start of treatments. Indeed, the original idea of the research paper by Crombé and colleagues, presented in the current issue of Journal of Magnetic Resonance Imaging, is to take advantage of imaging studies repetition before any treatments, obtaining unique information about the natural changes in the MRI features of a rare group of tumors: soft-tissue sarcomas (STS). Sarcomas are rare mesenchymal neoplasms that arise from soft-tissue (80% of cases) or bone (20%). In order to quantify the rarity of these neoplasms, we can simply quote that STS represent only 1% of all adult malignancies with an estimated incidence of about 4–5 per 100,000 per year in Europe. Despite their rarity, STS are a highly heterogeneous group of malignancies in terms of histology, biological behaviors, age of presentation, and nonetheless in regards to their imaging features. MRI is the most informative imaging tool to evaluate STS in every phase of the disease. Baseline MRIs are fundamental for patients’ prognosis prediction and for surgical planning. Several MRI features are well-known prognostic factors for all STS histotypes, above all: peritumoral enhancement, signs of necrosis, and signal intensity inhomogeneity. Additionally, in regards to the STS heterogeneity of features above mentioned, we can detect some specific MRI features related only to selected histotypes. The most known and recognized is the so-called “tail sign” of myxofibrosarcoma and undifferentiated pleomorphic sarcoma. The detection of this sign on MRI is crucial for surgical planning and recommends wider margins of resection to include the whole tail. Indeed, the assessment of surgical margins is a relevant problem for these neoplasms, with implications on the recurrence rate, especially for some specific histotypes affected by a very high local recurrence rate, such as myxofibrosarcoma. In this research article, Crombé et al analyze all these relevant semantic MRI features, and their naïve changes before any treatments. Moreover, the authors associated the standard qualitative evaluation and quantitative radiomics analyses, with delta-radiomics, comparing the two MRIs. In recent years, radiomics analyses are becoming one of the most important fields in diagnostic imaging research. The intrinsic and extrinsic heterogeneity typical of sarcomas makes them particularly suitable for radiomics analyses. The application of this tool to MRI of sarcomas has been performed in clinical researches for histological grading prediction, patients’ prognosis prediction, and treatment response evaluation. The number and quality of papers in this field are constantly increasing over the last years. Radiomics represents a large part of the present oncologic imaging research, and even if it is still not applied in clinical practice, the future of our diagnostic imaging activity will certainly benefit from this tool. This will hopefully lead to more personalized medicine with the aid of artificial intelligence. The length of the diagnostic interval in patients affected by sarcomas is a complex and not completely analyzed issue. An interesting recent systematic review focused on sarcomas diagnostic interval, revealed broad variations of time. In regards to STS, the authors evaluated 36 studies including 16,845 patients. The total interval varied significantly (4.3– 614.9 weeks), reflecting the high heterogeneity of STS. In detail, patient intervals varied between a median of 1.3– 17.2 weeks, the primary care interval lasted 0.1–13.3 weeks, the secondary care interval varied between 1.1 and 6.9 weeks, and the tertiary care interval was 2.1–7.9 weeks.