Radiomics in Cancer Diagnosis, Prognosis and Treatment
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".
Deadline for manuscript submissions: 30 December 2024 | Viewed by 141
Special Issue Editors
Interests: radiation oncology; MR-Linac applications; radiobiology; head and neck cancers; urological malignancies; radiotherapy networks; late effects of oncological treatments; chemotherapy/radiation interactions
Special Issues, Collections and Topics in MDPI journals
Interests: radiotherapy; radiomics; prostate cancer; MR-Linac applications
Special Issues, Collections and Topics in MDPI journals
Interests: radiation oncology; radiobiology; MR-Linac clinical applications; CNS tumors; lymphomas; urological malignancies; head and neck cancers
Special Issues, Collections and Topics in MDPI journals
Interests: radiology; radiomics; head and neck imaging; cardiovascular imaging; oncologic imaging
Special Issue Information
Dear Colleagues,
This Special Issue relating radiomics discusses innovative approaches in medical diagnostics that exploit the advanced analysis of radiological images, such as images obtained from computed tomography (CT), magnetic resonance imaging (MRI) or other sources of images (e.g., PET). Instead of simply evaluating features visible to the naked eye, radiomics uses complex algorithms to extract a wide range of quantitative and qualitative data from images, including details not perceptible to the human eye.
These data are then analyzed using machine learning and artificial intelligence techniques to identify patterns, correlations and predictions. Radiomics therefore offers the possibility of diagnosing diseases early, predicting responses to treatment and identifying subgroups of patients with specific characteristics. This promising approach has the potential to personalize medicine, optimizing clinical decisions through the use of detailed and quantitative data extracted from radiological images.
This approach is particularly useful in oncology. A special field of application of growing interest is image-guided radiotherapy, especially after the introduction of hybrid machines (MR-Linacs), among the many different oncological clinical contexts radiomics can be applied in. This is particularly true in the era of personalized medicine.
Radiomics may be used in conjunction with the genetic profiling of tumors (radiogenomics) to further personalize treatments.
Prof. Dr. Stefano Maria Magrini
Guest Editor
Prof. Dr. Filippo Alongi
Prof. Dr. Michela Buglione
Prof. Dr. Davide Farina
Dr. Luigi Spiazzi
Co-Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- radiomics
- oncology
- radiation oncology
- personalized medicine
- radiology
- nuclear medicine
- oncological diagnosis
- predictive factors in oncology
- biomarkers in cancer treatment
- radio-biomarkers in oncology
