The need for comprehensive clinical image data and relevant information in image-guided Radiation Therapy (RT) is becoming steadily apparent. Multiple standalone systems utilizing the most technological advancements in imaging, therapeutic radiation, and computerized treatment planning systems acquire key data during the RT treatment course of a patient. One example are patients treated for brain tumors of greater sizes and irregular shapes that utilize state-of-the-art RT technology to deliver pinpoint accurate radiation doses. One such system, the Cyberknife, is a radiation treatment system that utilizes image-guided information to control a multi-jointed, six degrees of freedom, robotic arm to deliver precise and required radiation dose to the tumor site of a cancer patient. The image-guided system is capable of tracking the lesion orientations with respect to the patient’s position throughout the treatment process. This is done by correlating live radiographic images with pre-operative, CT and MR imaging information to determine relative patient and tumor position repeatedly over the course of the treatment. The disparate and complex data generated by the Cyberknife system along with related data is scattered throughout the RT department compromising an efficient clinical workflow since the data crucial for a clinical decision may be time-consuming to retrieve, temporarily missing, or even lost. To address these shortcomings, the ACR-NEMA Standards Committee extended its DICOM (Digital Imaging & Communications in Medicine) Standard from Radiology to RT by ratifying seven DICOM RT objects starting in 1997. However, they are rarely used by the RT community in daily clinical operations. In the past, the research focus of an RT department has primarily been developing new protocols and devices to improve treatment process and outcomes of cancer patients with minimal effort dedicated to integration of imaging and information systems. Our research, tightly-coupling radiology and RT information systems, represents a new frontier for medical informatics research that has never been previously considered. By combining our past experience in medical imaging informatics, DICOM-RT expertise, and system integration, we propose to test our hypothesis using a brain tumor case model that a DICOM-RT electronic patient record (ePR) system can improve clinical workflow efficiency for treatment and management of patients. This RT ePR system integrated with clinical images and RT data can impact the RT department in a similar fashion as PACS has already successfully done for Radiology. As a first step, the specific treatment case of patients with brain tumors specifically patients treated with the Cyberknife system will be the initial proof of concept for the research design, implementation, evaluation, and clinical relevance.