Calculating Patient Similarity Based on Respiration Induced Tumor Motion

Abstract

In stereotactic radiotherapy for thoracic and abdominal tumors, respiratory motion management is crucial for improving efficacy of treatment, while minimizing risk to heathy tissue and organs. Since tumor motion exhibits dynamic variation in characteristics, analyzing the behavior distribution of tumor motion can improve treatment planning. Identifying similarities among patients is an intuitive step towards patient profiling for optimal treatment strategy. This paper investigates how patients, undergoing radiotherapy, can be clustered into five treatment groups, which are identified by medical physicists. And in order to do so, we propose a combination of an adaptive segmentation technique and couple it with a setwise clustering approach for measuring similarity between patients. Our methods aim to group the patients solely based on their tumor motion traces brought about by respiration. Through a series of empirical and statistical analyses, we explore the impact of different feature sets and processing methodologies on the proposed patient grouping approach.

Developing a low dimensional patient class profile in accordance to their respiration-induced tumor motion

“…If the dataset was annotated, then even in the absence of control dataset, we could have reduced our result to a single accuracy value. Our previous works, [3], [16] and [4], are centered around this dataset. Even though [3] and [16] use very similar approaches as used in this paper, due to difference in target application, we cannot provide a comparison.…”

“…Our previous works, [3], [16] and [4], are centered around this dataset. Even though [3] and [16] use very similar approaches as used in this paper, due to difference in target application, we cannot provide a comparison. [4] provides an automatic annotation technique and explores the readiness with which learning methods can learn the patterns if a proper annotation was provided.…”

Prediction and Tracking Changes in Bio-medical Sensor Data

“…Abstract-Both our preliminary works [1], [2], on biomedical sensor signal processing, have focused on abdominal tumor motion traces. In stereotactic radiotherapy for thoracic and abdominal tumors, respiratory motion management is crucial for improving efcacy of treatment, while minimizing risk to heathy tissue and organs.…”