Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features
• Current staging systems for hepatocellular carcinoma (HCC) are centered on treatment decisions and based on prognosis determined by a combination of imaging, laboratory, and clinical parameters; imaging provides preoperative anatomic delineation of the tumor extent. • Magnetic resonance imaging...
Saved in:
Main Authors: | , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/171404 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-171404 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1714042023-10-29T15:37:50Z Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features Low, Hsien Min Lee, Jeong Min Tan, Cher Heng Lee Kong Chian School of Medicine (LKCMedicine) Tan Tock Seng Hospital Science::Medicine Hepatocellular Carcinoma Prognosis • Current staging systems for hepatocellular carcinoma (HCC) are centered on treatment decisions and based on prognosis determined by a combination of imaging, laboratory, and clinical parameters; imaging provides preoperative anatomic delineation of the tumor extent. • Magnetic resonance imaging (MRI) imaging additionally provides multiparametric information on the cellular composition of certain variants of HCC that have prognoses ranging from better to worse compared to not otherwise specific HCC. • Hepatobiliary MRI findings of microvascular invasion and non-hypervascular hypointense nodules are promising for assessing the prognosis of tumor recurrence and patient survival. • Standardization of imaging-based classification systems could improve both the diagnosis and prognosis assessment of HCC but requires further validation. Published version 2023-10-24T03:46:23Z 2023-10-24T03:46:23Z 2023 Journal Article Low, H. M., Lee, J. M. & Tan, C. H. (2023). Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features. Korean Journal of Radiology, 24(7), 660-667. https://dx.doi.org/10.3348/kjr.2023.0168 1229-6929 https://hdl.handle.net/10356/171404 10.3348/kjr.2023.0168 37404108 2-s2.0-85163991032 7 24 660 667 en Korean Journal of Radiology © 2023 The Korean Society of Radiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Science::Medicine Hepatocellular Carcinoma Prognosis |
spellingShingle |
Science::Medicine Hepatocellular Carcinoma Prognosis Low, Hsien Min Lee, Jeong Min Tan, Cher Heng Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
description |
• Current staging systems for hepatocellular carcinoma (HCC) are centered on treatment decisions and based on prognosis determined by a combination of imaging, laboratory, and clinical parameters; imaging provides preoperative anatomic delineation of the tumor extent.
• Magnetic resonance imaging (MRI) imaging additionally provides multiparametric information on the cellular composition of certain variants of HCC that have prognoses ranging from better to worse compared to not otherwise specific HCC.
• Hepatobiliary MRI findings of microvascular invasion and non-hypervascular hypointense nodules are promising for assessing the prognosis of tumor recurrence and patient survival.
• Standardization of imaging-based classification systems could improve both the diagnosis and prognosis assessment of HCC but requires further validation. |
author2 |
Lee Kong Chian School of Medicine (LKCMedicine) |
author_facet |
Lee Kong Chian School of Medicine (LKCMedicine) Low, Hsien Min Lee, Jeong Min Tan, Cher Heng |
format |
Article |
author |
Low, Hsien Min Lee, Jeong Min Tan, Cher Heng |
author_sort |
Low, Hsien Min |
title |
Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
title_short |
Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
title_full |
Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
title_fullStr |
Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
title_full_unstemmed |
Prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
title_sort |
prognosis prediction of hepatocellular carcinoma based on magnetic resonance imaging features |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/171404 |
_version_ |
1781793742450065408 |