New advances in CT imaging of pancreas diseases: a narrative review
| Autor: | Federico Bruno, Chiara Floridi, Andrea Agostini, Marina Carotti, Andrea Giovagnoni, Raffaele Natella, Alessandra Borgheresi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Quantitative imaging Lesion detection business.industry Image contrast 030218 nuclear medicine & medical imaging Review Article on Multimodality Advanced Imaging and Intervention in Gland Disease 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Pancreas diseases 030220 oncology & carcinogenesis Medicine Surgery Narrative review Dose reduction Radiology Ct imaging business Pancreas |
| Zdroj: | Gland Surg |
| ISSN: | 2227-8575 2227-684X |
| DOI: | 10.21037/gs-20-551 |
| Popis: | Computed tomography (CT) plays a pivotal role as a diagnostic tool in many diagnostic and diffuse pancreatic diseases. One of the major limits of CT is related to the radiation exposure of young patients undergoing repeated examinations. Besides the standard CT protocol, the most recent technological advances, such as low-voltage acquisitions with high performance X-ray tubes and iterative reconstructions, allow for significant optimization of the protocol with dose reduction. The variety of CT tools are further expanded by the introduction of dual energy: the production of energy-selective images (i.e., virtual monochromatic images) improves the image contrast and lesion detection while the material-selective images (e.g., iodine maps or virtual unenhanced images) are valuable for lesion detection and dose reduction. The perfusion techniques provide diagnostic and prognostic information lesion and parenchymal vascularization and interstitium. Both dual energy and perfusion CT have the potential for pushing the limits of conventional CT from morphological evaluation to quantitative imaging applied to inflammatory and oncological diseases. Advances in post-processing of CT images, such as pancreatic volumetry, texture analysis and radiomics provide relevant information for pancreatic function but also for the diagnosis, management and prognosis of pancreatic neoplasms. Artificial intelligence is promising for optimization of the workflow in qualitative and quantitative analyses. Finally, basic concepts on the role of imaging on screening of pancreatic diseases will be provided. |
| Databáze: | OpenAIRE |
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