Editorial: Transplant Oncology of Liver Malignancies

Hepatocellular carcinoma (HCC) and biliary tract cancers (BTC) exhibit a poor prognosis with 5-year overall survival rates around 15%, all stages combined. Most of these primary liver malignancies are metastatic at diagnostic, with only limited therapeutic options, relying mainly on systemic therapies. Treatment modalities are different yet partially overlapping between HCC and BTC. The complex molecular profile of BTC yields to several actionable therapeutic targets, contrary to HCC that remains the field of antiangiogenic drugs in non-molecularly selected patients. Immunotherapy is now validated in the first line in HCC in combination with bevacizumab, while clinical activity of single agent immunotherapy appears limited to a subset of patients in BTC, still poorly characterized, and combinations are currently under investigation. In this review, we provide a critical evaluation and grading of clinical relevance on (i) the main prognostic biomarkers in HCC and BTC, (ii) the main theragnostic biomarkers in both tumors, and lastly (iii) what is recommended in clinical practice.

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Minimally invasive versus open right anterior sectionectomy and central hepatectomy for central liver malignancies: a propensity‐score‐matched analysis

ANZ Journal of Surgery ◽

10.1111/ans.16719 ◽

2021 ◽

Vol 91 (4) ◽

Author(s):

Ken Min Chin ◽

Yun‐Le Linn ◽

Chin Kai Cheong ◽

Ye‐Xin Koh ◽

Jin‐Yao Teo ◽

...

Keyword(s):

Propensity Score ◽

Minimally Invasive ◽

Liver Malignancies ◽

Central Hepatectomy

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Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making

Cancers ◽

10.3390/cancers13112726 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2726

Author(s):

Uli Fehrenbach ◽

Siyi Xin ◽

Alexander Hartenstein ◽

Timo Alexander Auer ◽

Franziska Dräger ◽

...

Keyword(s):

Liver Metastases ◽

External Validation ◽

High Accuracy ◽

Hepatic Tumor ◽

Liver Malignancies ◽

Internal Validation ◽

Matthew’S Correlation Coefficient ◽

Therapy Success ◽

Neuroendocrine Liver Metastases

Background: Rapid quantification of liver metastasis for diagnosis and follow-up is an unmet medical need in patients with secondary liver malignancies. We present a 3D-quantification model of neuroendocrine liver metastases (NELM) using gadoxetic-acid (Gd-EOB)-enhanced MRI as a useful tool for multidisciplinary cancer conferences (MCC). Methods: Manual 3D-segmentations of NELM and livers (149 patients in 278 Gd-EOB MRI scans) were used to train a neural network (U-Net architecture). Clinical usefulness was evaluated in another 33 patients who were discussed in our MCC and received a Gd-EOB MRI both at baseline and follow-up examination (n = 66) over 12 months. Model measurements (NELM volume; hepatic tumor load (HTL)) with corresponding absolute (ΔabsNELM; ΔabsHTL) and relative changes (ΔrelNELM; ΔrelHTL) between baseline and follow-up were compared to MCC decisions (therapy success/failure). Results: Internal validation of the model’s accuracy showed a high overlap for NELM and livers (Matthew’s correlation coefficient (φ): 0.76/0.95, respectively) with higher φ in larger NELM volume (φ = 0.80 vs. 0.71; p = 0.003). External validation confirmed the high accuracy for NELM (φ = 0.86) and livers (φ = 0.96). MCC decisions were significantly differentiated by all response variables (ΔabsNELM; ΔabsHTL; ΔrelNELM; ΔrelHTL) (p < 0.001). ΔrelNELM and ΔrelHTL showed optimal discrimination between therapy success or failure (AUC: 1.000; p < 0.001). Conclusion: The model shows high accuracy in 3D-quantification of NELM and HTL in Gd-EOB-MRI. The model’s measurements correlated well with MCC’s evaluation of therapeutic response.

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