Comparing Magnetic Resonance Imaging and Contrast‐Enhanced Ultrasound (<scp>CEUS</scp>) for the Characterization of Nodules Found on Hepatocellular Carcinoma Surveillance
Notice bibliographique
Résumé
Surveillance CEUS is Our Clear Choice S ince 2007, hepatologists in Calgary have had access to contrast-enhanced ultrasound (CEUS) and it has become an invaluable tool in the diagnosis of management of our patients with hepatocellular carcinoma (HCC).Global guidelines from hepatology societies endorse HCC surveillance using ultrasound (US), alone, or in combination with alpha-fetoprotein (AFP), every 6 months for patients who are high risk for HCC due to cirrhosis or chronic HBV.1,2 In at-risk patients, a diagnosis of HCC can be established with contrast-enhanced (CE) imaging, without the need for a liver biopsy.In 2011, the American Association for the Study of Liver Disease (AASLD) updated their guidelines to recommend either CEcomputerized tomography (CT) or CE-magnetic resonance imaging (MRI) as the first test to investigate nodules found on surveillance US measuring 1 cm or more (Figure 1A). 3 If the non-invasive criteria of arterial phase hyperenhancement (APHE) and portal venous washout (PVWO) was not present, they recommended obtaining the other CE-imaging study (CE-MRI or CE-CT) before considering a biopsy.Based on our local experience with CEUS, in 2017 our center suggested that CEUS should be incorporated into the AASLD diagnostic algorithm (Figure 1A). 4 Like the AASLD, the European Association for the Study of the Liver (EASL) 2018 guidelines recommend first using either CE-CT or CE-MRI (with extracellular contrast agents) or gadoxeticenhanced MRI (GE-MRI) with a specific hepatobiliary contrast agent (eg, Eovist ® /Primovist ® ; Figure 1B). 2 EASL and AASLD guidelines both highlight that MRI has higher sensitivity, and similar specificity, to multiphasic CT scan for the diagnosis of HCC.1,2 CEUS is included in the EASL diagnostic algorithm if the first CT or MRI is inconclusive, given that CEUS in this setting (utilizing the updated Liver Image Reporting and Data System [LIRADS], where LR-5 is defined as APHE with late and weak washout after 60 seconds), had comparable sensitivity and superior specificity for diagnosing lesions 1-2 cm as HCC. 5 In 2018, the AASLD updated their diagnostic algorithm to include LIRADS CT/MRI criteria (Figure 1C). 1 Although AASLD acknowledges that CEUS, with a sensitivity of 85% and a specificity of 91%, can be used for the diagnosis of HCC in expert centers, they cite a lack of "prospective studies in U.S. populations" as the reason not to include it in their diagnostic algorithm.1 A recent meta-analysis of individual patient data from of 32 studies with 1170 CT, 3341 MRI, and 853 CEUS observations, looked at the predictive value of the LIRADS components.6 They found that all CT/MRI LIRADS features, except for interval growth, were associated with HCC diagnosis and for CEUS LIRADS, APHE (OR = 7.3), late and mild washout (OR = 4.1), and size ≥2 cm (OR = 1.6), but not 1-2 cm, were associated with HCC. 6 The study by Hu et al in the Journal in Ultrasound Medicine 7 provides further real-world evidence Kelly W. Burak received honorarium from Canadian Multidisciplinary HCC meeting for organizing and speaking in 2021 and from CADTH for expert review of "Y90 for HCC" Health Technology Assessment in 2020.Lisa Doulgas has nothing to declare.Stephen E. Congly has research grants from Bristol-Myers Sqibb Canada, has received consulting fees from AstraZeneca and is on the Board of Directors for the
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».