Cargando…

Radiomics in Oncology, Part 2: Thoracic, Genito-Urinary, Breast, Neurological, Hematologic and Musculoskeletal Applications

SIMPLE SUMMARY: This Part II is an overview of the main applications of Radiomics in oncologic imaging with a focus on diagnosis, prognosis prediction and assessment of response to therapy in thoracic, genito-urinary, breast, neurologic, hematologic and musculoskeletal oncology. In this part II we d...

Descripción completa

Detalles Bibliográficos
Autores principales: Caruso, Damiano, Polici, Michela, Zerunian, Marta, Pucciarelli, Francesco, Guido, Gisella, Polidori, Tiziano, Landolfi, Federica, Nicolai, Matteo, Lucertini, Elena, Tarallo, Mariarita, Bracci, Benedetta, Nacci, Ilaria, Rucci, Carlotta, Eid, Marwen, Iannicelli, Elsa, Laghi, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197789/
https://www.ncbi.nlm.nih.gov/pubmed/34072366
http://dx.doi.org/10.3390/cancers13112681
Descripción
Sumario:SIMPLE SUMMARY: This Part II is an overview of the main applications of Radiomics in oncologic imaging with a focus on diagnosis, prognosis prediction and assessment of response to therapy in thoracic, genito-urinary, breast, neurologic, hematologic and musculoskeletal oncology. In this part II we describe the radiomic applications, limitations and future perspectives for each pre-eminent tumor. In the future, Radiomics could have a pivotal role in management of cancer patients as an imaging tool to support clinicians in decision making process. However, further investigations need to obtain some stable results and to standardize radiomic analysis (i.e., image acquisitions, segmentation and model building) in clinical routine. ABSTRACT: Radiomics has the potential to play a pivotal role in oncological translational imaging, particularly in cancer detection, prognosis prediction and response to therapy evaluation. To date, several studies established Radiomics as a useful tool in oncologic imaging, able to support clinicians in practicing evidence-based medicine, uniquely tailored to each patient and tumor. Mineable data, extracted from medical images could be combined with clinical and survival parameters to develop models useful for the clinicians in cancer patients’ assessment. As such, adding Radiomics to traditional subjective imaging may provide a quantitative and extensive cancer evaluation reflecting histologic architecture. In this Part II, we present an overview of radiomic applications in thoracic, genito-urinary, breast, neurological, hematologic and musculoskeletal oncologic applications.