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Liver contrast-enhanced sonography: computer-assisted differentiation between focal nodular hyperplasia and inflammatory hepatocellular adenoma by reference to microbubble transport patterns

  • Imaging Informatics and Artificial Intelligence
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

A new computer tool is proposed to distinguish between focal nodular hyperplasia (FNH) and an inflammatory hepatocellular adenoma (I-HCA) using contrast-enhanced ultrasound (CEUS). The new method was compared with the usual qualitative analysis.

Methods

The proposed tool embeds an “optical flow” algorithm, designed to mimic the human visual perception of object transport in image series, to quantitatively analyse apparent microbubble transport parameters visible on CEUS. Qualitative (visual) and quantitative (computer-assisted) CEUS data were compared in a cohort of adult patients with either FNH or I-HCA based on pathological and radiological results. For quantitative analysis, several computer-assisted classification models were tested and subjected to cross-validation. The accuracies, area under the receiver-operating characteristic curve (AUROC), sensitivity and specificity, positive predictive values (PPVs), negative predictive values (NPVs), false predictive rate (FPRs) and false negative rate (FNRs) were recorded.

Results

Forty-six patients with FNH (n = 29) or I-HCA (n = 17) with 47 tumours (one patient with 2 I-HCA) were analysed. The qualitative diagnostic parameters were accuracy = 93.6%, AUROC = 0.94, sensitivity = 94.4%, specificity = 93.1%, PPV = 89.5%, NPV = 96.4%, FPR = 6.9% and FNR = 5.6%. The quantitative diagnostic parameters were accuracy = 95.9%, AUROC = 0.97, sensitivity = 93.4%, specificity = 97.6%, PPV = 95.3%, NPV = 96.7%, FPR = 2.4% and FNR = 6.6%.

Conclusions

Microbubble transport patterns evident on CEUS are valuable diagnostic indicators. Machine-learning algorithms analysing such data facilitate the diagnosis of FNH and I-HCA tumours.

Key Points

• Distinguishing between focal nodular hyperplasia and an inflammatory hepatocellular adenoma using dynamic contrast-enhanced ultrasound is sometimes difficult.

• Microbubble transport patterns evident on contrast-enhanced sonography are valuable diagnostic indicators.

• Machine-learning algorithms analysing microbubble transport patterns facilitate the diagnosis of FNH and I-HCA.

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Abbreviations

AUC:

Area under the curve

CEUS:

Contrast-enhanced ultrasound

CNIL:

National Commission on Informatics and Liberty

CT:

Computed tomography

FNH:

Focal nodular hyperplasias

GB:

Gigabit

HCA:

Hepatocellular adenomas

I-HCA:

Inflammatory hepatocellular adenoma

KNN:

k-nearest neighbour

LR:

Logistic regression

MRI:

Magnetic resonance imaging

NPV:

Negative predictive value

PPV:

Positive predictive value

RAM:

Random access memory

RF:

Random forest

ROC:

Receiver-operating characteristic

SVM:

Support vector machine

T:

Tesla

US:

Ultrasound

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Acknowledgements

Experiments presented in this paper were carried out using the PlaFRIM experimental testbed, supported by Inria, CNRS (LABRI and IMB), Université de Bordeaux, Bordeaux INP, and Conseil Régional d’Aquitaine (see www.plafrim.fr/). The authors thank the Laboratory of Excellence TRAIL ANR-10-LABX-57 for funding. This study has been carried out with the financial support of the French National Research Agency (ANR) in the frame of the “Investments for the future” Programme IdEx Bordeaux-CPU (ANR-10-IDEX-03-02).

Funding

The authors thank the Laboratory of Excellence TRAIL ANR-10-LABX-57 for funding. This study has been carried out with the financial support of the French National Research Agency (ANR) in the frame of the “Investments for the future” Programme IdEx Bordeaux-CPU (ANR-10-IDEX-03-02).

Author information

Authors and Affiliations

  1. Institut de Mathématiques de Bordeaux (IMB), UMR 5251 CNRS/Université de Bordeaux, 351 cours de la Libération, F-33405, Talence, France

    Baudouin Denis de Senneville & Luc Lafitte

  2. CHU de Bordeaux, Service d’imagerie diagnostique et Interventionnelle Magellan/Saint André, F-33000, Bordeaux, France

    Nora Frulio, Hervé Laumonier, Cécile Salut & Hervé Trillaud

  3. EA IMOTION (Imagerie moléculaire et thérapies innovantes en oncologie), Université de Bordeaux, F-33000, Bordeaux, France

    Hervé Trillaud

Authors
  1. Baudouin Denis de Senneville
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  2. Nora Frulio
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  3. Hervé Laumonier
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  4. Cécile Salut
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  5. Luc Lafitte
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Correspondence to Baudouin Denis de Senneville.

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Guarantor

The scientific guarantor of this publication is Hervé Trillaud.

Conflict of interest

Hervé Trillaud: sponsored a lecture for Bracco and congress support. The other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Patients have been informed of the use of their data anonymously.

Ethical approval

Institutional review board approval was obtained.

Study subjects or cohorts overlap

Some study subjects (10 cases) have been previously reported in Hepatology 2008 by Laumonier et al—“Hepatocellular adenomas: magnetic resonance imaging features as a function of molecular pathological classification”; AJR Am J Roentgenol 2012 by Laumonier et al—“Role of contrast-enhanced sonography in differentiation of subtypes of hepatocellular adenoma: correlation with MRI findings”; and European Radiology 2018 by Bise et al—“New MRI features improve subtype classification of hepatocellular adenoma”.

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Denis de Senneville, B., Frulio, N., Laumonier, H. et al. Liver contrast-enhanced sonography: computer-assisted differentiation between focal nodular hyperplasia and inflammatory hepatocellular adenoma by reference to microbubble transport patterns. Eur Radiol 30, 2995–3003 (2020). https://doi.org/10.1007/s00330-019-06566-1

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