| Title |
Added value of ancillary imaging features for differentiating scirrhous hepatocellular carcinoma from intrahepatic cholangiocarcinoma on gadoxetic acid-enhanced MR imaging
|
|---|---|
| Published in |
European Radiology, January 2018
|
| DOI | 10.1007/s00330-017-5196-y |
| Pubmed ID | |
| Authors |
Seo-Youn Choi, Young Kon Kim, Ji Hye Min, Tae Wook Kang, Woo Kyoung Jeong, Soohyun Ahn, Hojeong Won |
| Abstract |
To determine ancillary features that help distinguish between scirrhous hepatocellular carcinoma (S-HCC) and intrahepatic cholangiocarcinoma (ICC) and investigate added value of ancillary features to enhancement pattern-based diagnosis on gadoxetic acid-enhanced MRI. This retrospective study included 96 patients with S-HCCs and 120 patients with ICCs who underwent gadoxetic acid MRI before surgical resection. Two observers reviewed MRIs of the tumours. After determining ancillary features for differentiating tumour types, we measured the diagnostic performance of adding ancillary features to enhancement pattern-based diagnosis. T2 central darkness, capsule and septum were significant and independent features differentiating S-HCC from ICC (p ≤ .06). Adding ancillary features to enhancement pattern led to increased accuracy (observer 1, 78.9 vs. 93.8 %; observer 2, 80.3 vs. 92.8 %; p < .001), sensitivity (observer 1, 74.5 vs. 96.4 %; observer 2, 77.1 vs. 93.2 %; p < .001 and .001), and specificity (observer 1, 82.5 vs. 91.7 %; observer 2, 82.9 vs. 92.5 %; p = .006 and .005) for diagnosis of S-HCC by differentiation from ICC. Adding ancillary features capsule, septum and T2 central darkness to conventional enhancement patterns on gadoxetic acid-enhanced MRI improved accuracy, sensitivity and specificity for S-HCC diagnosis with differentiation from ICC. • Capsule, septum, and T2 central darkness were ancillary features for S-HCC. • A typical HCC enhancement was seen in 31.3% of S-HCCs. • Ancillary MRI features were useful in differentiation between S-HCC and ICC. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 36% |
| Professor > Associate Professor | 2 | 14% |
| Student > Ph. D. Student | 1 | 7% |
| Other | 1 | 7% |
| Student > Master | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 3 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 36% |
| Mathematics | 1 | 7% |
| Computer Science | 1 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Unknown | 6 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 June 2018.
All research outputs
#15,536,861
of 23,090,520 outputs
Outputs from European Radiology
#2,490
of 4,183 outputs
Outputs of similar age
#290,194
of 473,977 outputs
Outputs of similar age from European Radiology
#51
of 80 outputs
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