Search

Purpose: Pancreatic stereotactic body radiation therapy (SBRT) is limited to gross tumor without elective coverage for subclinical disease. Given a better understanding of recurrence patterns, we hypothesized that the addition of elective nodal irradiation (ENI) to pancreatic SBRT would be tolerable and would decrease locoregional progression.Methods and Materials: We conducted a retrospective 1:2 propensity-matched cohort study to compare toxicity and locoregional progression among patients treated with pancreatic SBRT with or without ENI. In the SBRT + ENI cohort, an elective target volume was delineated per Radiation Therapy Oncology Group guidelines and treated to 25 Gy in 5 fractions alongside 40 Gy in 5 fractions to gross disease. The primary outcome was the cumulative incidence of locoregional progression, with death as a competing risk.Results: Among 135 candidate controls treated with SBRT alone, 100 were propensity-matched to 50 patients treated with SBRT + ENI. All patients completed SBRT. Median potential radiographic follow-up was 28 months. The incidence of late and serious acute toxicity was similar between matched cohorts. However, SBRT + ENI was associated with a statistically significant increase in acute grade 1 to 2 nausea (60% vs 20%, P < .001). The 24-month cumulative incidences of locoregional progression with and without ENI were 22.6% (95% confidence interval [CI], 10.0%-35.1%) versus 44.6% (95% CI, 34.8%-54.4%; multivariable-adjusted hazard ratio, 0.39; 95% CI, 0.18-0.87; P = .021). This was stable in sensitivity analyses of uniform prescription dose, multiagent chemotherapy, and resectability. There were fewer peripancreatic (0% vs 7%), porta hepatis (2% vs 7%), and peri-aortic/aortocaval (5% vs 12%) recurrences after SBRT + ENI, but no difference in survival.Conclusions: Pancreatic SBRT + ENI was tolerable and did not increase late or serious acute toxicity relative to a matched cohort undergoing SBRT alone, but did increase acute grade 1 to 2 nausea. The addition of ENI to SBRT was associated with decreased locoregional progression but not improved survival. Further studies are warranted to determine whether ENI offers meaningful benefit. [ABSTRACT FROM AUTHOR]

• SABR doses ≥40 Gy appear to be superior than lower doses. • Modified FOLFIRINOX use appears to be superior to gemcitabine-based regimens. • Combination of SABR ≥40 Gy and modified FOLFIRINOX demonstrated the best outcomes. • Future prospective studies should test this combination for unresectable pancreatic cancer. We aimed to report the long-term impact of modern chemotherapy and SABR dose regimens on oncologic outcomes of unresectable pancreatic adenocarcinoma (PA). We reviewed the treatment characteristics and outcomes of all patients who received multi-fraction SABR for unresectable PA between February 2007 and August 2018 at our institution. Time-to-events were calculated from date of diagnosis treating death as a competing risk. A total of 149 patients were identified. Median follow-up was 15 months (range: 5–47). Median SABR dose was 33 Gy (range: 20–45) delivered in 5 fractions in 143 patients, and 3 or 6 fractions in 6 patients. 107 patients (72%) received gemcitabine-based chemotherapy while 31 (21%) received modified FOLFIRINOX (mFFX). Median OS was 16 months (95% CI, 14–17), with a 1-year cumulative incidence of LF of 14%. The combination of SABR doses ≥40 Gy and mFFX (n = 21) showed a superior PFS and OS to the use of GEM-based chemotherapy with <40 Gy SABR doses (median PFS: 14 vs. 10 months, HR: 0.46, 95% CI: 0.29–0.71, P = 0.003; median OS: 24 vs. 14 months, HR: 0.36, 95% CI: 0.22–0.59, P = 0.002), with 1-year PFS and OS of 67% and 90% compared to 35% and 59% for those who received GEM-based chemotherapy with <40 Gy SABR doses, respectively. The use of mFFX and a SABR dose ≥40 Gy in 5 fractions may be superior compared to regimens that utilize gemcitabine-based chemotherapy or SABR doses <40 Gy. [ABSTRACT FROM AUTHOR]

To develop a framework for automated prediction of hepatobiliary (HB) toxicity after liver stereotactic body radiation therapy (SBRT). A newly recognized toxicity type, named central or HB liver toxicity, had been reported, manifestation of which strongly correlates with the dose delivered to portal vein (PV) during SBRT. We propose a novel framework for automated HB toxicity prediction by combining deep learning-based auto-segmentation, PV anatomy analysis and the previously reported HB toxicity model. For validation of the framework, an IBR approved representative database of 72 patients treated with SBRT from primary (37) and metastatic (35) liver cancer was assembled. Each case included a pre-treatment CT, manual segmentations of tumor and PV, approved treatment plan, and the record of acute and late post-treatment toxicities. Performance of the developed framework was evaluated by quantitative comparison against manual predictions of HB toxicity, as well as post-treatment toxicity follow-ups. The manual and automated predictions of HB toxicity were in agreement for 94% cases using either V BED10 30 ≥ 45 cc or V BED10 40 ≥ 37 cc dosimetric predictors. When compared to post-treatment follow-ups for primary liver cancer, the proposed automated framework made 86% and 83% correct predictions in comparison to 83% and 80% correct manual predictions using V BED10 30 ≥ 45 cc or V BED10 40 ≥ 37 cc, respectively. The proposed framework automates the HB toxicity prediction with the accuracy similar to manual analysis-based HB toxicity prediction. The strategy is quite general and extendable to the automated prediction of toxicities of other organs. [ABSTRACT FROM AUTHOR]

Purpose To further explore the correlation of central biliary tract (cHBT) radiation doses with hepatobiliary toxicity (HBT) after stereotactic body radiation therapy (SBRT) in a larger patient dataset. Methods We reviewed the treatment and outcomes of all patients who received SBRT for primary liver cancer (PLC) and metastatic liver tumors between July 2004 and November 2015 at our institution. The cHBT was defined as isotropic expansions (5, 10, 15, 20 and 25 mm) from the portal vein (PV). Doses were converted to biologically effective doses by using the standard linear quadratic model with α / β of 10 (BED 10 ). HBT was graded according to the Common Terminology Criteria for Adverse Events v4.03. Results Median follow-up was 13 months. Out of the 130 patients with complete follow-up records analyzed, 60 (46.1%) had liver metastases, 40 (30.8%) had hepatocellular carcinoma (HCC), 26 (20%) had cholangiocarcinoma (CCA) and 4 (3.1%) patients other PLC histologies. Thirty-three (25.4%) grade 2+ and 28 (21.5%) grade 3+ HBT were observed. Grade 3+ HBT was seen in 13 patients (50%) with CCA, 7 patients (17.5%) with HCC and 7 (11.7%) patients with liver metastases. SBRT doses to the cHBT were highly associated with HBT, but only for PLC patients when analyzed by histological subtype. The 15 mm expansion from the PV (cHBT 15 ) proved to be an appropriate surrogate for the cHBT. The strongest cHBT 15 dose predictors for G3+ HBT for PLC were the V BED10 40 ⩾37 cc ( p < 0.0001) and the V BED10 30 ⩾ 45 cc ( p < 0.0001). Conclusion SBRT doses to the cHBT are associated with occurrence of HBT only in PLC patients. Limiting the dose to the cHBT to V BED10 40 < 37 cc and V BED10 30 < 45 cc when treating PLC patients with SBRT may reduce the risk of HBT. [ABSTRACT FROM AUTHOR]

Purpose: Deep learning is an emerging technique that allows us to capture imaging information beyond the visually recognizable level of a human being. Because of the anatomic characteristics and location, on-board target verification for radiation delivery to pancreatic tumors is a challenging task. Our goal was to use a deep neural network to localize the pancreatic tumor target on kV x-ray images acquired using an on-board imager for image guided radiation therapy.Methods and Materials: The network is set up in such a way that the input is either a digitally reconstructed radiograph image or a monoscopic x-ray projection image acquired by the on-board imager from a given direction, and the output is the location of the planning target volume in the projection image. To produce a sufficient number of training x-ray images reflecting the vast number of possible clinical scenarios of anatomy distribution, a series of changes were introduced to the planning computed tomography images, including deformation, rotation, and translation, to simulate inter- and intrafractional variations. After model training, the accuracy of the model was evaluated by retrospectively studying patients who underwent pancreatic cancer radiation therapy. Statistical analysis using mean absolute differences (MADs) and Lin's concordance correlation coefficient were used to assess the accuracy of the predicted target positions.Results: MADs between the model-predicted and the actual positions were found to be less than 2.60 mm in anteroposterior, lateral, and oblique directions for both axes in the detector plane. For comparison studies with and without fiducials, MADs are less than 2.49 mm. For all cases, Lin's concordance correlation coefficients between the predicted and actual positions were found to be better than 93%, demonstrating the success of the proposed deep learning for image guided radiation therapy.Conclusions: We demonstrated that markerless pancreatic tumor target localization is achievable with high accuracy by using a deep learning technique approach. [ABSTRACT FROM AUTHOR]