Radiomics refers to a method for extracting quantitative features from images and analyzing them. Compared with classic visual image analysis, radiomics provides more comprehensive objective approach is expected provide additional information that cannot be achieved analysis. has been investigated its potential in predicting the prognosis biologic behavior of primary liver cancers. Although off...

The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development diagnostic tools to differentiate these from more aggressive forms. This study combined radiomics analysis with uptake on SPECT/CT benign neoplasms cell carcinoma. A total 57 were prospectively collected. Histopathol...

Brain tumor segmentation is the first and the most critical step in clinical applications of radiomics. However, segmenting brain images by radiologists is labor intense and prone to inter- and intraobserver variability. Stable and reproducible brain image segmentation algorithms are thus important for successful tumor detection in radiomics. In this paper, we propose a supervised brain image s...

The medical community has access to a wide range of medical tests and imaging studies. However, for diagnosis and radiation therapy treatment planning, standard tests, typically governed by outdated funding guidelines, lead to decisions in treatment approaches that are based on ‘population average’ data leading to a one-size fits all approach to diagnosis and treatment. Radiomics is a rapidly g...

Quantitative analysis of tumour characteristics based on medical imaging is an emerging field of research. In recent years, quantitative imaging features derived from CT, positron emission tomography and MR scans were shown to be of added value in the prediction of outcome parameters in oncology, in what is called the radiomics field. However, results might be difficult to compare owing to a la...

BACKGROUND AND PURPOSE In this study we investigated the interchangeability of planning CT and cone-beam CT (CBCT) extracted radiomic features. Furthermore, a previously described CT based prognostic radiomic signature for non-small cell lung cancer (NSCLC) patients using CBCT based features was validated. MATERIAL AND METHODS One training dataset of 132 and two validation datasets of 62 and ...

Radiomics (radiogenomics) characterizes tumor phenotypes based on quantitative image features derived from routine radiologic imaging to improve cancer diagnosis, prognosis, prediction and response to therapy. Although radiomic features must be reproducible to qualify as biomarkers for clinical care, little is known about how routine imaging acquisition techniques/parameters affect reproducibil...

The processes of radiomics consist of image-based personalized tumor phenotyping for precision medicine. They complement slow, costly, and invasive molecular analysis of tumoral tissue. Whereas the relevance of a large variety of quantitative imaging biomarkers has been demonstrated for various cancer types, most studies were based on 2D image analysis of relatively small patient cohorts. In th...

Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy. In this article we investigate the challenging problem of predicting a patient's response to neoadjuvant chemotherapy from a single 18F-FDG PET sc...

BACKGROUND Lung diseases (resulting from air pollution) require a widely accessible method for risk estimation and early diagnosis to ensure proper and responsive treatment. Radiomics-based fractal dimension analysis of X-ray computed tomography attenuation patterns in chest voxels of mice exposed to different air polluting agents was performed to model early stages of disease and establish dif...