The mission of The University of Texas M. D. Anderson Cancer Center is to eliminate cancer in Texas, the nation, and the world through outstanding programs that integrate patient care, research and prevention, and through education for undergraduate and graduate students, trainees, professionals, employees and the public.
The primary function of the Clinical Data Abstractor role is to abstract and codes information from patient medical records to obtain clinical and research data and work with the Tumor Measurement Initiative (TMI). The Tumor Measurement Initiative aims to build an institutional platform to support standardized, automated, quantitative imaging-based tumor measurement across each patient's journey to advance multidisciplinary, data-driven, high precision cancer treatment. This individual be responsible for annotating images, meticulous record keeping including procedural documentation, and participating in optimization of TMI procedures and workflows to fulfil this objective. They will also have oversight and management of imaging databases associated with TMI and research projects. Scope includes regular collaboration and verbal updates with TMI and lab team members.
The ideal candidate for the Clinical Data Abstractor will have experience in contouring tumors for medical radiology images. This candidate will also have experience with data mining, analyzing it and/or working with large data sets.
The goals of our research are to curate and annotate imaging data and associated data collected at the institution to support development and validation of automate tools to facilitate future image analysis and quantitative imaging research with a longer-term goal of clinical translation and implementation.
Artificial intelligence (AI) techniques are being developed to segment (e.g. delineate the boundary) of tumors and normal tissues. The ability to efficiently and automatically perform this task will have a significant impact on image guidance techniques. The segmentation and pre-treatment analysis information will be used as input to the biomechanical model-based registration to optimize the accuracy of the algorithm.
Direct experience using RayStation for image analysis, segmentation, and annotation is required. Familiarity with DICOM standards, PACS integration, RIS, HL7 standards is highly preferred. Must be adaptable to change and able to interact with co-workers and customers in a positive manner, as well as communicate in an effective manner.
1. Generation of annotations for TMI automation
• Generating manual segmentations on images to support TMI automation algorithm training and test data
• Clearly communicate and coordinate with subject matter experts to ensure appropriate oversight and review of annotations.
• Prepare timely annotation progress updates for TMI sponsor reporting.
• Collaborate with TMI Automation team on use of tools and processes which can be leveraged for segmentation and / or XNAT IQ cohort curation.
2. Work with Engineering Data Engineering Analytics Team to:
• Identify new data sets and elements required to support TMI (e.g., genetic mutations from molecular diagnostics).
• Obtain knowledge and guidance on use of context engine tools (e.g., Foundry, Slicer Dicer, etc.) for cohort curation and development of data sets required to support TMI.
3. Record Keeping and Data Collection:
• Maintain accurate, detailed records and data and protocols.
• Prepare summary tables and graphs for data tracking and as required
• Collaborate with subject matter experts to document procedures as needed to support and / or sustain program initiatives.
4. Demonstrate and practice data governance precautions.
• Receive verbal and/or written instructions from supervisor on standards and specialized data governance procedures.
• Attend required courses/certification for human subjects research
• Have working knowledge of imaging-related platforms - with reference to procedure manuals whenever necessary.
• Monitor workflow as it pertains to the need for additional data ingress requests, alignment/coverage by IRB and material transfer agreement requirements for data collaborations.
5. Organization and performance of TMI procedures and workflows
• Expand knowledge of ongoing techniques and enhance proficiency in planning, executing, and troubleshooting these techniques.
• Participate in adopting new techniques while continuously increasing knowledge and skills to enhance research efforts.
• Maintain assertiveness and flexibility in approaching new techniques and responsibilities; utilize good work habits and time management.
6. Written and Verbal Communication to support research activities:
• Assist with writing and submitting abstracts, research project plans, grants, protocols and manuscripts
• Provide regular verbal updates on progress to the TMI team
7. Other duties as assigned by PI or supervisor.
Required: High school diploma or equivalent.
Required: Two years of experience in tumor registry, healthcare, or related field. Additional years of education may be substituted for required experience on a one to one year basis.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html