Advanced Oncologic Imaging

Dear Colleagues,

Imaging diagnosis can be assisted by computed analysis. Tumor-specific aspect is one of the possible representations of human cancer at imaging, while others come from the analysis of data acquired during examination. At present, new parameters can be evaluated using computer-assisted imaging analysis that would be otherwise invisible. These new parameters are inside the images but not visible during standard radiological evaluation and reporting. Therefore, new imaging analysis can be used for oncologic evaluations and response to therapy. For example, texture analysis supplies an evaluation of tumor heterogeneity by imaging and analyzing pixel or voxel gray level distributions and relationships in the image, also giving information on the tumor microenvironment. In particular, texture analysis that evaluates pixel values, variations, and distributions could predict tumor pathologic grade, features, relapse risk, response to therapy, and therefore patients’ overall survival and prognosis. In summary, the computed analysis of imaging could cover new significant roles, such as the evaluation of tumor aggressiveness and prognostic prediction.

The aim of this Special Issue is to present the most common advanced oncologic imaging on CT and MRI, from texture analysis to quantification imaging on MRI, showing examples of computer-assisted imaging analysis adding value that is useful for diagnosis and oncology patient management.

Prof. Mirko D'Onofrio
Prof. Maria Antonietta Bali
Prof. Maxime Ronot
Guest Editors

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