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

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.

A pilot study of everolimus and radiation for neuroendocrine liver metastases

Liver metastases are common in patients with neuroendocrine tumors. For patients, management must balance disease control with consideration of toxicity, given limited treatment options. Everolimus has demonstrated effectiveness in neuroendocrine neoplasms. Given emerging data of a synergistic effect with radiation therapy, we evaluated combined Everolimus and radiation for neuroendocrine liver metastases. This single-arm, single centre prospective pilot study evaluated the safety and efficacy of combined everolimus and radiotherapy for well-differentiated neuroendocrine liver metastases. Patients with unresectable liver metastases received everolimus for 30 days, followed by concurrent everolimus and liver radiotherapy, then a further 14 days of everolimus. Tolerability was evaluated using the CTCAE v.4.03. Individual metastasis response rate and local control were measured by RECIST v1.1. Overall survival, progression-free survival and freedom from change in systemic therapy were estimated by the Kaplan-Meier method. 40 metastases were treated in 14 patients. No Grade 3 or higher toxicities were identified in the concurrent treatment phase; 8 grade 2 toxicity and 1 patient develped grade 3 toxicity in the post-radiation phase. Overall response rate was 38%. One and 2-year local control was 97% and 71%. Median progression free survival was 12 months. One and 2-year overall survival were 100% and 92%. In conclusion, combined everolimus and radiation is well-tolerated for neuroendocrine liver metastases and is associated with excellent local control. The approach of selective local ablation of oligometastatic or oligoprogressive disease warrants further evaluation in this patient population.