A Patient-Specific correspondence model to track tumor location in thorax during radiation therapy.

Purpose: We present a patient-specific model to estimate tumor location in the thorax during radiation therapy using chest surface displacement as the surrogate signal.

Methods: Two types of data are used for model construction: Four-dimensional computed tomography (4D-CT) images of the patient and the displacement of two points on the patient's skin on the thoracic area. Principal component analysis is used to fit the correspondence model.

Comparison of visual and semi-automated kilovoltage cone beam CT image QA analysis.

Established kilovoltage cone-beam computed tomography (kV-CBCT) image quality assurance (QA) guidelines often rely on recommendations provided by the American Association of Physicists in Medicine (AAPM) task group (TG) reports with metrics that use visual analysis. This can result in measurement variations by different users, especially in visually subjective analyzes such as low contrast resolution. Consequently, there is a growing interest in more automated means of image QA analysis that can offer increased consistency, accuracy, and convenience.

A novel analytical method for computing dose from kilovoltage beams used in Image-Guided radiation therapy.

Purpose: A modified convolution/superposition algorithm is proposed to compute dose from the kilovoltage beams used in IGRT. The algorithm uses material-specific energy deposition kernels instead of water-energy deposition kernels.

Methods: Monte Carlo simulation was used to model the Elekta XVI unit and determine dose deposition characteristics of its kilovoltage beams.