The framework offers clinically accurate tools for hepatobiliary toxicity prediction and automatic identification of anatomical regions that are critical to spare during SBRT.

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Automated segmentation of portal vein (PV) for liver radiotherapy planning is a challenging task due to potentially low vasculature contrast, complex PV anatomy and image artifacts originated from fiducial markers and vasculature stents. In this paper, we propose a novel framework for automated PV segmentation from computed tomography (CT) images. We apply convolutional neural networks (CNN) to learn consistent appearance patterns of PV using a training set of CT images with reference annotations and then enhance PV in previously unseen CT images. Markov Random Fields (MRF) were further used to smooth the CNN enhancement results and remove isolated mis-segmented regions. Finally, CNN-MRF-based enhancement was augmented with PV centerline detection that relied on PV anatomical properties such as tubularity and branch composition. The framework was validated on a clinical database with 72 CT images of patients scheduled to liver stereotactic body radiation therapy. The obtained segmentation accuracy was DSC = 0.83 and η = 1.08 mm in terms of the median Dice coefficient and mean symmetric surface distance, respectively, when segmentation is encompassed into the PV region of interest. The obtained results indicate that CNN and anatomy analysis can be used for accurate segmentation of PV and potentially integrated into liver radiation therapy planning.

To review our institutional experience of treating cholangiocarcinoma using stereotactic body radiation therapy (SBRT). Methods and Materials: A total of 40 patients with intrahepatic (n Z 25) or perihilar (n Z 15) cholangiocarcinoma treated with SBRT were retrospectively reviewed. SBRT was delivered in 1 to 5 fractions with median dose of 40 Gy. Competing risk analysis was used to estimate cumulative incidence of local in-field, local out-of-field, regional, and distant failure. Kaplan-Meier and log-rank tests were used to calculate overall survival (OS). Toxicity was scored using Common Terminology Criteria for Adverse Events, version 4.0. Results: The median follow-up time was 18 months. The 1-year incidence of local in-field, local out-of-field, regional, and distant failure was 8%, 23%, 13%, and 22%, respectively. Median OS was 23 months and 1-and 2-year OS rates were 69% and 39%, respectively. Patients with perihilar tumors had a 1-year incidence of regional failure of 24% and worse OS (P Z .013). Patients with regional failure were more likely to develop distant metastases, 32% versus 19% at 1 year (P Z .11). Acute grade 3 þ hepatobiliary toxicity developed in 15 patients (36%). Conclusions: In this series of cholangiocarcinoma patients treated with definitive SBRT, patterns of failure reveal that regional failures are not insignificant, particularly for perihilar tumors. Elective nodal irradiation of regional lymphatics should be considered when using SBRT. A prospective study of elective nodal irradiation in patients with perihilar tumors would further clarify whether this approach improves outcomes without increasing hepatobiliary toxicity.

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Although well described in the 1960s, liver toxicity secondary to radiation therapy, commonly known as radiation-induced liver disease (RILD), remains a major challenge. RILD encompasses two distinct clinical entities, a ‘classic’ form, composed of anicteric hepatomegaly, ascites and elevated alkaline phosphatase; and a ‘non-classic’ form, with liver transaminases elevated to more than five times the reference value, or worsening of liver metabolic function represented as an increase of 2 or more points in the Child–Pugh score classification. The risk of occurrence of RILD has historically limited the applicability of radiation for the treatment of liver malignancies. With the development of 3D conformal radiation therapy, which allowed for partial organ irradiation based on computed tomography treatment planning, there has been a resurgence of interest in the use of liver irradiation. Since then, a large body of evidence regarding the liver tolerance to conventionally fractionated radiation has been produced, but severe liver toxicities has continued to be reported. More recently, improvements in diagnostic imaging, radiation treatment planning technology and delivery systems have prompted the development of stereotactic body radiotherapy (SBRT), by which high doses of radiation can be delivered with high target accuracy and a steep dose gradient at the tumor – normal tissue interface, offering an opportunity of decreasing toxicity rates while improving tumor control. Here, we present an overview of the role SBRT has played in the management of liver tumors, addressing the challenges and opportunities to reduce the incidence of RILD, such as adaptive approaches and machine-learning–based predictive models.