A simulation study of irregular respiratory motion and its dosimetric impact on lung tumors

Abstract

This study is aimed at providing a dosimetric evaluation of the irregular motion of lung tumors due to variations in patients' respiration. Twenty-three lung cancer patients are retrospectively enrolled in this study. The motion of the patient clinical target volume is simulated and two types of irregularities are defined: characteristic and uncharacteristic motions. Characteristic irregularities are representative of random fluctuations in the observed target motion. Uncharacteristic irregular motion is classified as systematic errors in determination of the target motion during the planning session. Respiratory traces from measurement of patient abdominal motion are also used for the target motion simulations. Characteristic irregular motion was observed to cause minimal changes in target dosimetry with the largest effect of 2.5% ± 0.9% (1σ) reduction in the minimum target dose (D(min)) observed for targets that move 2 cm on average and exhibiting 50% amplitude variations within a session. However, uncharacteristic irregular motion introduced more drastic changes in the clinical target volume (CTV) dose; 4.1% ± 1.7% reduction for 1 cm motion and 9.6% ± 1.7% drop for 2 cm. In simulations with patients' abdominal motion, corresponding changes in target dosimetry were observed to be negligible (<0.1%). Only uncharacteristic irregular motion was identified as a clinically significant source of dosimetric uncertainty.

Irregular Breathing Classification From Multiple Patient Datasets Using Neural Networks

“…The proposed methodology for irregular breathing classification can impact the dose calculation for patient treatments [9], [10]. The highly irregularly breathing patient may be expected to have a much bigger internal target volume (ITV) than a regular one, where ITV contains the macroscopic cancer and an internal margin to take into account the variations due to organ motions [9].…”

“…The highly irregularly breathing patient may be expected to have a much bigger internal target volume (ITV) than a regular one, where ITV contains the macroscopic cancer and an internal margin to take into account the variations due to organ motions [9]. Thus, the detection of irregular breathing motion before and during the external beam radiotherapy is desired for minimizing the safety margin [10]. Only a few clinical studies, however, have shown a deteriorated outcome with increased irregularity of breathing patterns [1], [8], [10], probably due to the lack of technical development in this topic.…”

“…Thus, the detection of irregular breathing motion before and during the external beam radiotherapy is desired for minimizing the safety margin [10]. Only a few clinical studies, however, have shown a deteriorated outcome with increased irregularity of breathing patterns [1], [8], [10], probably due to the lack of technical development in this topic. Other reasons confounding the clinical effect of irregular motion such as variations in target volumes or positioning uncertainties also influence the classification outcomes [8]- [11].…”

“…An expected usage of the irregularity detection is to adapt the margin value, i.e., the patients classified with regular breathing patterns would be treated with tight margins to minimize the target volume. For patients classified with irregular breathing patterns, safety margins may need to be adjusted based on the irregularity to cope with baseline shifts or highly fluctuating amplitudes that are not covered by standard safety margins [9], [10].…”

“…However, the decision boundary to distinguish the irregular patterns from diverse respirations is not clear yet [11], [16]. For example, some studies defined only two (characteristic and uncharacteristic [10]) or three (small, middle, and large [9]) types of irregular breathing motions based on the breathing amplitude to access the target dosimetry [9], [10]. Our purpose is to classify irregular patterns, given symptoms that fit into neither the regular pattern nor the regular compression pattern categorizations [17].…”