Autor: |
Emrullah Birgin, Heiner Nebelung, Schaima Abdelhadi, Johann S. Rink, Matthias F. Froelich, Svetlana Hetjens, Mohammad Rahbari, Patrick Téoule, Erik Rasbach, Christoph Reissfelder, Jürgen Weitz, Stefan O. Schoenberg, Carina Riediger, Verena Plodeck, Nuh N. Rahbari |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Frontiers in Oncology, Vol 14 (2024) |
Druh dokumentu: |
article |
ISSN: |
2234-943X |
DOI: |
10.3389/fonc.2024.1360936 |
Popis: |
BackgroundMicrovascular invasion is a major histopathological risk factor of postoperative recurrence in patients with hepatocellular carcinoma. This study aimed to develop and validate a digital biopsy model using imaging features to predict microvascular invasion before hepatectomy.MethodsA total of 217 consecutive patients who underwent hepatectomy for resectable hepatocellular carcinoma were enrolled at two tertiary-care reference centers. An imaging-based digital biopsy model was developed and internally validated using logistic regression analysis with adjustments for age, sex, etiology of disease, size and number of lesions.ResultsThree imaging features, i.e., non-smoothness of lesion margin (OR = 16.40), ill-defined pseudocapsula (OR = 4.93), and persistence of intratumoral internal artery (OR = 10.50), were independently associated with microvascular invasion and incorporated into a prediction model. A scoring system with 0 - 3 points was established for the prediction model. Internal validation confirmed an excellent calibration of the model. A cutoff of 2 points indicates a high risk of microvascular invasion (area under the curve 0.87). The overall survival and recurrence-free survival stratified by the risk model was significantly shorter in patients with high risk features of microvascular invasion compared to those patients with low risk of microvascular invasion (overall survival: median 35 vs. 75 months, P = 0.027; recurrence-free survival: median 17 vs. 38 months, P < 0.001)).ConclusionA preoperative assessment of microvascular invasion by digital biopsy is reliable, easily applicable, and might facilitate personalized treatment strategies. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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