Published June 2015 | Version v1
Journal article

WE-F-BRB-03: Inclusion of Data-Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System

Creators

  • 1. Johns Hopkins University (United States)

Description

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented

Additional details

Identifiers

Publishing Information

Journal Title
Medical Physics
Journal Volume
42
Journal Issue
6
Journal Page Range
vp.
ISSN
0094-2405
CODEN
MPHYA6

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
48016497
Subject category
S60: APPLIED LIFE SCIENCES; S61: RADIATION PROTECTION AND DOSIMETRY;
Descriptors DEI
ANATOMY; DOSIMETRY; HEALTH HAZARDS; LEARNING; PATIENTS; PLANNING; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; RADIOBIOLOGY; RADIOTHERAPY; TOXICITY
Descriptors DEC
BIOLOGY; DOSES; HAZARDS; MEDICINE; NUCLEAR MEDICINE; RADIOLOGY; THERAPY

Optional Information

Notes
(c) 2015 American Association of Physicists in Medicine