Comparison of multiphase data from CT perfusion vs clinical 4-phase CT scans with respect to image quality, lesion detection, and LI-RADS classification in HCC patients
2022 (English) In: Heliyon, E-ISSN 2405-8440, Vol. 8, no 1, article id e08757Article in journal (Refereed) Published
Abstract [en]
Purpose: The aim of this study was to assess the image quality and diagnostic performance of reconstructed arterial (A) and portal venous (PV) phases in computed tomography perfusion (CTP) scans compared to the corresponding phases in standard 4-phase CT and to assess the utility for LI-RADS classification using CTP and 4-phase 4CT. Methods: A total of 26 scans with each method (CTP and 4-phase CT) from 19 hepatocellular carcinoma patients were analyzed and compared. Arterial and PV phases reconstructed by advanced modeled iterative reconstruction at strength 4 (ADMIRE 4) from raw CTP data were compared with image sets from arterial and PV phases of 4-phase CT (ADMIRE 3) in the same patient with respect to image quality. Results: Quantitative image analysis showed that reconstructed CTP datasets were equivalent to 4-phase CT image sets. Qualitative image analysis revealed similar lesion detection rates with the 2 methods for patients with an abdominal diameter <= 36 cm and body weight <90 kg, but lower detection rates with CTP for patients with an abdominal diameter >37 cm. There was no difference in Liver Imaging Reporting and Data System (LI-RADS) classifications between the 2 methods. Conclusion: Reconstructed CTP images can potentially replace 4-phase CT images in patients weighing <90 kg and with a body diameter <37 cm, as the 2 methods are comparable in terms of quantitative image quality and ability to detect and classify lesions based on LI-RADS criteria.
Place, publisher, year, edition, pages Elsevier Science Ltd , 2022. Vol. 8, no 1, article id e08757
Keywords [en]
Perfusion imaging; HCC; 4-Dimensional computed tomography; Image quality; CT
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers URN: urn:nbn:se:liu:diva-184110 DOI: 10.1016/j.heliyon.2022.e08757 ISI: 000767184700107 PubMedID: 35146150 OAI: oai:DiVA.org:liu-184110 DiVA, id: diva2:1651136
Note Funding Agencies|County Council of Östergötland, Sweden (LFoU)
2022-04-112022-04-112024-02-07