Mayo, Charles S.

Background & Aims: Early-stage HCC can be treated with thermal ablation or stereotactic body radiation therapy (SBRT). We retrospectively compared local progression, mortality, and toxicity among patients with HCC treated with ablation or SBRT in a multicenter, US cohort. Approach & Results: We included adult patients with treatment-naïve HCC lesions without vascular invasion treated with thermal ablation or SBRT per individual physician or institutional preference from January 2012 to December 2018. Outcomes included local progression after a 3-month landmark period assessed at the lesion level and overall survival at the patient level. Inverse probability of treatment weighting was used to account for imbalances in treatment groups. The Cox proportional hazard modeling was used to compare progression and overall survival, and logistic regression was used for toxicity. There were 642 patients with 786 lesions (median size: 2.1 cm) treated with ablation or SBRT. In adjusted analyses, SBRT was associated with a reduced risk of local progression compared to ablation (aHR 0.30, 95% CI: 0.15–0.60). However, SBRT-treated patients had an increased risk of liver dysfunction at 3 months (absolute difference 5.5%, aOR 2.31, 95% CI: 1.13–4.73) and death (aHR 2.04, 95% CI: 1.44–2.88, p < 0.0001). Conclusions: In this multicenter study of patients with HCC, SBRT was associated with a lower risk of local progression compared to thermal ablation but higher all-cause mortality. Survival differences may be attributable to residual confounding, patient selection, or downstream treatments. These retrospective real-world data help guide treatment decisions while demonstrating the need for a prospective clinical trial.

It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision‐making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.

The term Big Data has come to encompass a number of concepts and uses within medicine. This paper lays out the relevance and application of large collections of data in the radiation oncology community. We describe the potential importance and uses in clinical practice. The important concepts are then described and how they have been or could be implemented are discussed. Impediments to progress in the collection and use of sufficient quantities of data are also described. Finally, recommendations for how the community can move forward to achieve the potential of big data in radiation oncology are provided.

In this work we used 4D dose calculations, which include the effects of shape deformations, to investigate an alternative approach to creating the ITV. We hypothesized that instead of needing images from all the breathing phases in the 4D CT dataset to create the outer envelope used for treatment planning, it is possible to exclude images from the phases closest to the inhale phase. We used 4D CT images from 10 patients with lung cancer. For each patient, we drew a gross tumor volume on the exhale‐phase image and propagated this to the images from other phases in the 4D CT dataset using commercial image registration software. We created four different ITVs using the N phases closest to the exhale phase (where , 8, 7, 6). For each ITV contour, we created a volume‐modulated arc therapy plan on the exhale‐phase CT and normalized it so that the prescribed dose covered at least 95% of the ITV. Each plan was applied to CT images from each CT phase (phases 1–10), and the calculated doses were then mapped to the exhale phase using deformable registration. The effect of the motion was quantified using the dose to 95% of the target on the exhale phase and tumor control probability. For the three‐dimensional and 4D dose calculations of the plan where , differences in the value varied from 3% to 14%, with an average difference of 7%. For 9 of the 10 patients, the reduction in was less than 5% if eight phases were used to create the ITV. For three of the 10 patients, the reduction in the was less than 5% if seven phases were used to create the ITV. We were unsuccessful in creating a general rule that could be used to create the ITV. Some reduction (8/10 phases) was possible for most, but not all, of the patients, and the ITV reduction was small.PACS number: 87.55.D‐

300 Background: The National Radiation Oncology Registry (NROR) is developing an IT infrastructure to support the efficient collection, aggregation, and analysis of data concerning cancer patients treated with radiotherapy across the United States. Methods: Detailed requirements were developed to emphasize the following distinguishing goals for the system: 1) streamline the process of data collection by minimizing manual data entry; 2) support the collection of patient-reported outcomes (PROs) and their linkage with clinician-observed outcomes; 3) facilitate data integration within the NROR and between the NROR and other registries; 4) allow for evolution of the system in response to new learning; and 5) promote sustainability and ongoing improvement through an open standard of interoperability. Results: An innovative technical architecture has been designed to meet the goals described. The system maximizes efficiency through automated extraction and electronic transfer of data from radiation oncology information systems. PROs are collected directly from patients via a web-based portal and linked to data submitted from participating institutions. A data dictionary has been developed based on national standards and controlled vocabularies to facilitate data integration. Contemporary forms-based database technology is used in combination with traditional relational technology to permit both flexible evolution of the system and efficient data analysis. A unique “gateway” architecture and open transmission standard makes it possible for commercial products to interoperate with the registry in the future. Conclusions: The NROR prototype system will be launched later this year to collect data for a pilot registry of prostate cancer patients. Its performance and usability will be important factors in the success of the pilot. If effective, the platform will support the expansion of the NROR to benefit patients, clinicians, researchers, payors, device manufacturers, and policy-makers by capturing reliable, population-based information on radiation treatment delivery and health outcomes.