Owing to recent advances in computing power, iterative reconstruction (IR) algorithms have become a clinically viable option in computed tomographic (CT) imaging. Substantial evidence is accumulating about the advantages of IR algorithms over established analytical methods, such as filtered back projection. IR improves image quality through cyclic image processing. Although all available solutions share the common mechanism of artifact reduction and/or potential for radiation dose savings, chiefly due to image noise suppression, the magnitude of these effects depends on the specific IR algorithm. In the first section of this contribution, the technical bases of IR are briefly reviewed and the currently available algorithms released by the major CT manufacturers are described. In the second part, the current status of their clinical implementation is surveyed. Regardless of the applied IR algorithm, the available evidence attests to the substantial potential of IR algorithms for overcoming traditional limitations in CT imaging.
Cholangiocarcinoma (CCA) is a heterogeneous group of tumours, derived from cells of the biliary tree, which represent the second most frequent primary liver tumour. According to the most recent classifications, CCA can be subdivided into intrahepatic (iCCA) and extrahepatic (eCCA) which include perihilar (pCCA) and distal (dCCA) CCA. CCA are usually identified at advanced stages, when the primary tumour grows enough to produce a large liver mass or when jaundice has developed because of biliary tree obstruction. The ongoing challenges in the identification of risk factors and definition of a specific population at higher risk of developing CCA are the main challenges for the development of screening programs. Therefore, late diagnosis remains an unresolved issue in CCA. Imaging plays an important role in the detection and characterization of CCA, helping with radiological diagnosis, guiding biopsy procedures and allowing staging of the tumour. This review focuses on clinical presentations and diagnosis and staging techniques of CCA.
Applications of DECT in clinical practice are based on two capabilities: material differentiation and material identification and quantification. The capability of obtaining different material-specific datasets (iodine map, virtual unenhanced, and monochromatic images) in the same acquisition can improve lesion detection and characterization. This approach can also affect evaluation of the response to therapy and detection of oncology-related disorders. DECT is an innovative imaging technique that can dramatically affect the care of oncologic patients.
CT should be the preferred diagnostic imaging modality for detecting peritoneal metastases because of the robustness of the data. MRI and PET/CT should be considered second choices, until more consistent information on their diagnostic yield in detecting PM are obtained.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.