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

Frulio, Nora; Laumonier, H.; Salut, Cécile; Lafitte, Luc; Trillaud, Hervé

doi:10.1007/s00330-019-06566-1

Cited by 16 publications

(11 citation statements)

References 29 publications

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“…In the DEGUM study, CEUS correctly diagnosed 57.9% of the adenomas [13]. Computer-assisted diagnosis can also be used to improve the accuracy of differential diagnosis by CEUS between FNH and adenoma [30].…”

Section: Discussionmentioning

confidence: 98%

Contrast-enhanced ultrasound for the assessment of focal nodular hyperplasia – results of a multicentre study

et al. 2021

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Aim: Contrast-enhanced ultrasound (CEUS) has become a relevant imaging method for the evaluation of focal liver le-sions (FLL). The aim of this study was to evaluate the performance of CEUS for the assessment of focal nodular hyperplasia (FNH) in a large study group. Material and methods: We performed a multicentre prospective observational study, which included successive CEUS examinations from fourteen Romanian centres. CEUS examinations were performed in de novo FLL, using low mechanical index ultrasound, following an intravenous bolus of 2.4 ml SonoVue. CEUS was considered conclusive for FNH if a typical pattern was present following contrast (rapid “spoke-wheel” enhancement during the arterial phase, hyperenhanced lesion during venous phase, hyper- or isoenhanced in the late phase). In all cases a reference method was available (contrast enhanced CT or MRI or biopsy). The trial was registered in clinicaltrials.gov (Identifier NCT01329458). Results: During the 6 years study, 2062 “de novo” FLL were evaluated by CEUS. From this cohort, 94/2062 (4.5%) had a typical enhancing pattern for FNH as described in the EFSUMB guidelines. Contrast enhanced CT/MRI and biopsy diagnosed additional 15 FNH. From the 94 cases diagnosed as FNH by CEUS, in nine the final diagnosis was different (five of them adenomas). CEUS had 85% sensitivity, 99.5% specificity, 90.4% positive predictive value, 99.2% negative predictive value and 98.8% diagnostic accuracy for the diagnosis of FNH. Conclusions: CEUS is a sensitive and very specific method for the diagnosis of FNH.

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Section: Discussionmentioning

confidence: 98%

Contrast-enhanced ultrasound for the assessment of focal nodular hyperplasia – results of a multicentre study

et al. 2021

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“…The used tool embeds an “optical flow” algorithm [ 13 , 14 ] designed to mimic the human visual perception of object transport in image series. We quantify divergence (sources and sinks) and amplitudes in obtained dense transport fields, which provided very simple indicators of displacement vector orientations and magnitudes [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

Voluntary Wheel Running Does Not Enhance Radiotherapy Efficiency in a Preclinical Model of Prostate Cancer: The Importance of Physical Activity Modalities?

Dufresne

Richard

Dieumegard

et al. 2021

Cancers

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Physical activity is increasingly recognized as a strategy able to improve cancer patient outcome, and its potential to enhance treatment response is promising, despite being unclear. In our study we used a preclinical model of prostate cancer to investigate whether voluntary wheel running (VWR) could improve tumor perfusion and enhance radiotherapy (RT) efficiency. Nude athymic mice were injected with PC-3 cancer cells and either remained inactive or were housed with running wheels. Apparent microbubble transport was enhanced with VWR, which we hypothesized could improve the RT response. When repeating the experiments and adding RT, however, we observed that VWR did not influence RT efficiency. These findings contrasted with previous results and prompted us to evaluate if the lack of effects observed on tumor growth could be attributable to the physical activity modality used. Using PC-3 and PPC-1 xenografts, we randomized mice to either inactive controls, VWR, or treadmill running (TR). In both models, TR (but not VWR) slowed down tumor growth, suggesting that the anti-cancer effects of physical activity are dependent on its modalities. Providing a better understanding of which activity type should be recommended to cancer patients thus appears essential to improve treatment outcomes.

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“…Thirteen studies evaluated AI-based classification of different FLL entities with CEUS-data [48][49][50][51][52][53][54][55][56][57][58][59][60]. The number of cases ranged from 37 to 527, the majority of studies (9/ 13) included more than 100.…”

Section: Artificial Intelligence For the Differentiation Of Specific ...mentioning

confidence: 99%

Artificial intelligence for the classification of focal liver lesions in ultrasound – a systematic review

et al. 2023

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Focal liver lesions are detected in about 15 % of abdominal ultrasound examinations. The diagnosis of frequent benign lesions can be determined reliably based on the characteristic B-mode appearance of cysts, hemangiomas or typical focal fatty changes. In case of focal liver lesions which remain unclear in B-mode ultrasound, contrast enhanced ultrasound (CEUS) increases diagnostic accuracy for the distinction of benign from malignant liver lesions. Artificial intelligence describes applications which try to emulate human intelligence, at least in subfields such as the classification of images. Since ultrasound is considered to be a particularly examiner-dependent technique, the application of artificial intelligence could be an interesting approach for an objective and accurate diagnosis. In this systematic review we analyzed how artificial intelligence can be used to classify the dignity and entity of focal liver lesions on the basis of B-mode or CEUS data. Based on a structured search on Scopus, Web of Science, PubMed and IEEE we found 52 studies, which met the inclusion criteria. Studies showed good diagnostic performance for both the classification of dignity and the differentiation of individual tumor entities. The results could be improved by inclusion of clinical parameters and were comparable to those of experienced investigators in terms of diagnostic accuracy. However, due to the limited spectrum of lesions included in the studies and a lack of independent validation cohorts, the transfer of the results into clinical practice is limited. Raumforderungen der Leber finden sich in ca. 15 % abdominaler Ultraschalluntersuchungen. Die Diagnose der meisten benignen Läsionen kann bei charakteristischem Befund, z.B. bei Zysten, Hämangiomen und typischen fokalen Fettverteilungsvarianten oft bereits in der B-Bild-Sonographie zuverlässig gestellt werden. Bei unklaren Befunden erhöht der Einsatz der Kontrastmittelsonographie (CEUS) die diagnostische Treffsicherheit bezüglich der Unterscheidung von benignen und malignen Leberläsionen. Künstliche Intelligenz beschreibt Anwendungen, die versuchen in Bereichen wie der Klassifikation von Bildern humane Intelligenz nachzubilden. Da die Sonographie als besonders untersucherabhängig gilt, könnte die Anwendung künstlicher Intelligenz ein interessanter Ansatz für eine objektive und treffsichere Diagnose sein. Im Rahmen dieser systematischen Übersichtsarbeit haben wir analysiert, wie gut künstliche Intelligenz die Dignität und Entität von Leberläsionen auf Basis von B-Bild- oder CEUS-Daten bestimmen kann. Basierend auf einer strukturierten Recherche in Scopus, Web of Science, PubMed und IEEE fanden wir 52 Studien, welche die Einschlusskriterien erfüllten. Es zeigte sich eine gute diagnostische Genauigkeit sowohl für die Differenzierung der Dignität als auch der verschiedener Tumorentitäten. Die Ergebnisse ließen sich durch die zusätzliche Berücksichtigung klinischer Parameter verbessern und waren bezüglich der diagnostischen Genauigkeit mit der erfahrener Untersucher vergleichbar. Aufgrund des begrenzten Spektrums untersuchter Läsionen und häufig fehlender unabhängiger Validierungskohorten sind die Ergebnisse jedoch nur begrenzt auf die klinische Anwendung übertragbar.

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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

Cited by 16 publications

References 29 publications

Contrast-enhanced ultrasound for the assessment of focal nodular hyperplasia – results of a multicentre study

Contrast-enhanced ultrasound for the assessment of focal nodular hyperplasia – results of a multicentre study

Voluntary Wheel Running Does Not Enhance Radiotherapy Efficiency in a Preclinical Model of Prostate Cancer: The Importance of Physical Activity Modalities?

Artificial intelligence for the classification of focal liver lesions in ultrasound – a systematic review

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