Evidence map›Paper›PMID 38846285›Full record

ArticleQuantitative imaging in medicine and surgery2024

IDEAL-IQ measurement can distinguish dysplastic nodule from early hepatocellular carcinoma: a case-control study.

Guangping Zheng, Fangjun Wei, Puxuan Lu, Gendong Yang, Cuizu Li, Chunming Lin, Yun Zhou, Yixin Chen, Jianing Tian, Xiaolei Wang and 6 more

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Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Guangping Zheng *Department of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Fangjun Wei *Department of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Puxuan LuDepartment of Radiology, Shenzhen Center for Chronic Disease Control, Shenzhen, China.
Gendong YangDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Cuizu LiDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Chunming LinDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Yun ZhouDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Yixin ChenDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Jianing TianDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Xiaolei WangDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Linjing WangDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Wenhao LiuDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Guangfeng ZhangDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Qingxian CaiDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Hua HuangDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.
Yongxing YunDepartment of Radiology, Shenzhen Third People's Hospital, Shenzhen, China.ORCID https://orcid.org/0000-0002-6435-7661

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous studies have confirmed that malignant transformation of dysplastic nodule (DN) into hepatocellular carcinoma (HCC) is accompanied by reduction of iron content in nodules. This pathological abnormality can serve as the basis for magnetic resonance imaging (MRI). This study was designed to identify the feasibility of iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantitative (IDEAL-IQ) measurement to distinguish early hepatocellular carcinoma (eHCC) from DN. Methods: We reviewed MRI studies of 35 eHCC and 23 DN lesions (46 participants with 58 lesions total, 37 males, 9 females, 31-80 years old). The exams include IDEAL-IQ sequence and 3.0T MR conventional scan [including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and Gadopentic acid (Gd-GDPA)-enhanced]. Then, 3 readers independently diagnosed eHCC, DN, or were unable to distinguish eHCC from DN using conventional MRI (CMRI), and then assessed R2* value of nodules [R2* value represents the nodule iron content (NIC)] and R2* value of liver background [R2* value represents the liver background iron content (LBIC)] with IDEAL-IQ. Statistical analysis was conducted using the Results: This study evaluated 35 eHCC participants (17 males, 6 females, 34-81 years old, nodule size: 10.5-27.6 mm, median 18.0 mm) and 23 DN participants (20 males, 3 females, 31-76 years old, nodule size: 16.30±4.095 mm). The NIC and ratio of NIC to LIBC (NIC/LBIC) of the eHCC group (35.926±12.806 sec Conclusions: Using IDEAL-IQ measurement can distinguish DN from eHCC.

Indexed as

dysplastic nodule (DN)Early hepatocellular carcinoma (eHCC)iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantitative (IDEAL-IQ)magnetic resonance imaging (MRI)

Identifiers

PMID38846285
PMCPMC11151266

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