Microvascular invasion in hepatocellular carcinoma: is it predictable with a new, preoperative application of diffusion-weighted imaging?

Yang, Chun; Wang, Heqing; Sheng, Ruofan; Ji, Yuan; Rao, Shengxiang; Zeng, Mengsu

doi:10.1016/j.clinimag.2016.10.004

Cited by 21 publications

(22 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…14 2016 Japan 79(79) 70 CT/MR 38 13 17 2 47 9 Yang et al . 18 2016 China 136(136) 56 MR 39 24 29 20 63 7 Patients (Tumors) (n): TP, FP, FN and TN referred to tumor number. Number outside the bracket was that of patients, and inside the bracket was that of tumor number; MR: Magnetic Resonance Imaging; CT: Computed Tomography; P (non-smooth) (%): percentage of patients with a non-smooth tumor margin on preoperative imaging test; TP: true-positive, FP: false-positive, FN: false-negative, TN: true-negative.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis

Zheng

Huang

et al. 2017

Sci Rep

View full text Add to dashboard Cite

Microvascular invasion (MVI) is rarely diagnosed preoperatively in hepatocellular carcinoma (HCC). The aim of this meta-analysis is to assess the diagnostic power of a non-smooth tumor margin on preoperative imaging for MVI. We performed a literature search using the PubMed, Embase and Cochrane Library databases, and 11 studies were included involving 618 MVI-positive cases and 1030 MVI-negative cases. Considerable heterogeneity was found, and was indicated to be attributable to the mean patient ages in the included studies. In subgroups of studies with a mean patient age older than 60 years and studies with computed tomography (CT) as the imaging method (as opposed to magnetic resonance imaging (MRI)), heterogeneity was low, and the diagnostic odds ratio (DOR) of the single two-dimensional imaging feature for MVI was 21.30 (95% CI [12.52, 36.23]) and 28.78 (95% CI [13.92, 59.36]), respectively; this power was equivalent to or greater than that of certain multivariable-based scoring systems. In conclusion, a non-smooth tumor margin on preoperative imaging is of great value for MVI assessment and should be considered for inclusion in future scoring systems.

show abstract

Section: Resultsmentioning

confidence: 99%

“… 13 included patients of recurrent HCC with a history of hepatectomy; and Yang et al . 18 excluded patients with interval between MRI and surgery longer than 14 days). This risk bias may indirectly impact on the mean age and patient percentage with a positive imaging parameter.…”

Section: Resultsmentioning

confidence: 99%

A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis

Zheng

Huang

et al. 2017

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Imaging techniques including computed tomography (CT) and magnetic resonance (MR) imaging may help to predict the presence of MVI of HCC based on the morphologic features (8,9) and quantitative parameters derived by using perfusion CT (10) or diffusion-weighted imaging (DWI) (11). As a functional MR imaging technique, DWI seems to be a promising tool for predicting MVI of HCC without the use of ionizing radiation or contrast medium.…”

Section: Advances In Knowledgementioning

confidence: 99%

“…Several potential risk factors such as incomplete radiologic capsule, nonsmooth tumor margins, and size were also reported to be related to MVI of HCC. These results of the different studies were inconsistent in varying degrees (8,9,(26)(27)(28)(29)(30). Selection bias of case-control study designs or surgical candidates might be the cause of disagreements among different studies.…”

Section: Gastrointestinal Imaging: Microvascular Invasion Of Hepatocementioning

confidence: 99%

Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging

et al. 2018

View full text Add to dashboard Cite

Purpose To evaluate the potential role of diffusion kurtosis imaging and conventional magnetic resonance (MR) imaging findings including standard monoexponential model of diffusion-weighted imaging and morphologic features for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Materials and Methods Institutional review board approval and written informed consent were obtained. Between September 2015 and November 2016, 84 patients (median age, 54 years; range, 29-79 years) with 92 histopathologically confirmed HCCs (40 MVI-positive lesions and 52 MVI-negative lesions) were analyzed. Preoperative MR imaging examinations including diffusion kurtosis imaging (b values: 0, 200, 500, 1000, 1500, and 2000 sec/mm) were performed and kurtosis, diffusivity, and apparent diffusion coefficient maps were calculated. Morphologic features of conventional MR images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of these parameters as potential predictors of MVI. Results Features significantly related to MVI of HCC at univariate analysis were increased mean kurtosis value (P < .001), decreased mean diffusivity value (P = .033) and apparent diffusion coefficient value (P = .011), and presence of infiltrative border with irregular shape (P = .005) and irregular circumferential enhancement (P = .026). At multivariate analysis, mean kurtosis value (odds ratio, 6.25; P = .001), as well as irregular circumferential enhancement (odds ratio, 6.92; P = .046), were independent risk factors for MVI of HCC. The mean kurtosis value for MVI of HCC showed an area under the receiver operating characteristic curve of 0.784 (optimal cutoff value was 0.917). Conclusion Higher mean kurtosis values in combination with irregular circumferential enhancement are potential predictive biomarkers for MVI of HCC. RSNA, 2017.

show abstract

“…With the development of magnetic resonance image (MRI), some researchers turn to find radiomics paraments to predict MVI. Their studies use statistical method to show that tumor sharp and margin, tumor multifocality and DWI/T2 mismatch in MR image are associated to MVI prediction [6,7]. Though these methods are noninvasive, they seldom use the information from features of MVI itself.…”

Section: Introductionmentioning

confidence: 99%

Predicting Microvascular Invasion of Hepatocellular Carcinoma by texture analysis of multi-phase MR image

Yu¹,

Chen²,

et al.

EPiC Series in Computing

View full text Add to dashboard Cite

Microvascular invasion (MVI) diagnosis is of vital importance in the curative treatment of hepatocellular carcinoma patients due to its close relationship with prognostic analysis. Currently, MVI detection often bases on surgical specimen, which is invasive for patients. This study, we extracted texture features of multi-phase MR image to predict the presence of MVI. Feature extraction employed neighboring gray level dependency emphasis (NGLDM) method, which is a common texture feature analysis method. Next, we built a SVM classifier to predict the presence of MVI using extracted features. Especially, multi-phase features were designed to enhance the precision of prediction. Enhanced MR images of pre-contrast phase and portal vein phase were used to extracting features. The method was tested by 5-fold cross- validation on the dataset. The precision of prediction was 91.31%, compared with the baseline method of 70.71%. To make the prediction more interpretable, the relationship between NGLDM texture features and the presence of MVI was discussed in the end.

show abstract

Microvascular invasion in hepatocellular carcinoma: is it predictable with a new, preoperative application of diffusion-weighted imaging?

Cited by 21 publications

References 21 publications

A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis

A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis

Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging

Predicting Microvascular Invasion of Hepatocellular Carcinoma by texture analysis of multi-phase MR image

Contact Info

Product

Resources

About