Incorporating Case-Based Reasoning for Radiation Therapy Knowledge Modeling: A Pelvic Case Study.

Sheng, Yang

Zhang, Jiahan

Wang, Chunhao

Yin, Fang-Fang

Wu, Q Jackie

Ge, Yaorong

2019-10-01T13:54:12Z

2019-10-01T13:54:12Z

2019-01

2019-10-01T13:54:11Z

Knowledge models in radiotherapy capture the relation between patient anatomy and dosimetry to provide treatment planning guidance. When treatment schemes evolve, existing models struggle to predict accurately. We propose a case-based reasoning framework designed to handle novel anatomies that are of same type but vary beyond original training samples. A total of 105 pelvic intensity-modulated radiotherapy cases were analyzed. Eighty cases were prostate cases while the other 25 were prostate-plus-lymph-node cases. We simulated 4 scenarios: Scarce scenario, Semiscarce scenario, Semiample scenario, and Ample scenario. For the Scarce scenario, a multiple stepwise regression model was trained using 85 cases (80 prostate, 5 prostate-plus-lymph-node). The proposed workflow started with evaluating the feature novelty of new cases against 5 training prostate-plus-lymph-node cases using leverage statistic. The case database was composed of a 5-case dose atlas. Case-based dose prediction was compared against the regression model prediction using sum of squared residual. Mean sum of squared residual of case-based and regression predictions for the bladder of 13 identified outliers were 0.174 ± 0.166 and 0.459 ± 0.508, respectively (P = .0326). For the rectum, the respective mean sum of squared residuals were 0.103 ± 0.120 and 0.150 ± 0.171 for case-based and regression prediction (P = .1972). By retaining novel cases, under the Ample scenario, significant statistical improvement was observed over the Scarce scenario (P = .0398) for the bladder model. We expect that the incorporation of case-based reasoning that judiciously applies appropriate predictive models could improve overall prediction accuracy and robustness in clinical practice.

1533-0346

1533-0338

https://hdl.handle.net/10161/19363

eng

SAGE Publications

Technology in cancer research & treatment

10.1177/1533033819874788

case-based reasoning

knowledge modeling

prostate cancer

radiation therapy

Incorporating Case-Based Reasoning for Radiation Therapy Knowledge Modeling: A Pelvic Case Study.

Journal article

Sheng, Yang|0000-0003-3380-1966

Yin, Fang-Fang|0000-0002-2025-4740|0000-0003-1064-2149

1533033819874788

School of Medicine

Duke

Duke Kunshan University Faculty

Duke Kunshan University

Duke Cancer Institute

Institutes and Centers

Radiation Oncology

Clinical Science Departments

Published

18