A Mizoguchi

Computer-aided beam arrangement based on similar cases in radiation treatment-planning databases for stereotactic lung radiation therapy

The purpose of this study was to develop a computer-aided method for determination of beam arrangements based on similar cases in a radiotherapy treatment-planning database for stereotactic lung radiation therapy. Similar-case-based beam arrangements were automatically determined based on the following two steps. First, the five most similar cases were searched, based on geometrical features related to the location, size and shape of the planning target volume, lung and spinal cord. Second, five beam arrangements of an objective case were automatically determined by registering five similar cases with the objective case, with respect to lung regions, by means of a linear registration technique. For evaluation of the beam arrangements five treatment plans were manually created by applying the beam arrangements determined in the second step to the objective case. The most usable beam arrangement was selected by sorting the five treatment plans based on eight plan evaluation indices, including the D95, mean lung dose and spinal cord maximum dose. We applied the proposed method to 10 test cases, by using an RTP database of 81 cases with lung cancer, and compared the eight plan evaluation indices between the original treatment plan and the corresponding most usable similar-case-based treatment plan. As a result, the proposed method may provide usable beam arrangements, which have no statistically significant differences from the original beam arrangements (P > 0.05) in terms of the eight plan evaluation indices. Therefore, the proposed method could be employed as an educational tool for less experienced treatment planners.

Computer-assisted radiation treatment planning system for determination of beam directions based on similar cases in a database for stereotactic body radiotherapy

Similar treatment plans or similar cases in radiotherapy treatment planning (RTP) databases of senior experienced planners could be helpful or educational for treatment planners who have few experiences of stereotactic body radiotherapy (SBRT). The aim of this study was to investigate the feasibility of beam arrangements determined using similar cases in a RTP database including plans designed by experienced treatment planners. Similar cases were automatically selected based on geometrical features and planning evaluation indices from 81 cases with lung cancer who received SBRT. First, the RTP database was searched for the five most similar cases based on geometrical features related to the location, size, and shape of the planning target volume, lung, and spinal cord. Second, the five beam arrangements of an objective case were automatically determined by registering five similar cases to the objective case with respect to lung regions by means of a linear registration technique. For evaluation of the beam arrangements, five plans were designed by applying the beam arrangements determined in the second step to the objective case. The most usable beam arrangement was selected by sorting the five plans based on 11 planning evaluation indices including tumor control probability and normal tissue complication probability. We applied the proposed two-step method to 10 test cases by using an RTP database of 81 cases with lung cancer, and compared the 11 planning evaluation indices between the original plan and the corresponding most usable similar-case-based plan. As a result, there were no statistically significant differences between the original beam arrangements and the most usable similar-case-based beam arrangements (P > 0.05) in terms of the 10 planning evaluation indices. The proposed method suggested usable beam arrangements with little difference from cases in the RTP database, and thus it could be employed as an educational tool for less experienced treatment planners.

Computational Intelligent Image Analysis for Assisting Radiation Oncologists’ Decision Making in Radiation Treatment Planning

This chapter describes the computational image analysis for assisting radiation oncologists’ decision making in radiation treatment planning for high precision radiation therapy. The radiation therapy consists of five steps, i.e., diagnosis, treatment planning, patient setup, treatment, and follow-up, in which computational intelligent image analysis and pattern recognition methods play important roles in improving the accuracy of radiation therapy and assisting radiation oncologists’ or medical physicists’ decision making. In particular, the treatment planning step is substantially important and indispensable, because the subsequent steps must be performed according to the treatment plan. This chapter introduces a number of studies on computational intelligent image analysis used for the computer-aided decision making in radiation treatment planning. Moreover, the authors also explore computer-aided treatment planning methods including automated beam arrangement based on similar cases, computerized contouring of lung tumor regions using a support vector machine (SVM) classifier, and a computerized method for determination of robust beam directions against patient setup errors in particle therapy.

Automated determination of robust beam directions against patient setup errors based on electron density spatial distribution in hadron particle therapy

The precise dose distribution fitted with a tumor shape in a beam direction tend to be more fragile if the beam’s eye view (BEV) of the three dimensional (3D) electron density (ED) map in the beam direction changed more abruptly (high frequency) with large variation (large amplitude). This could lead to significant tumor underdose, but fatal overdose in organs at risk. In this study, we developed an automated method for determination of robust beam directions against the patient setup error based on the ED-based BEV in the beam direction in the particle therapy. The basic idea of our approach was to find the robust beam directions, whose ED- based BEV has low special frequency variation with small amplitude. For evaluation of the variation in the ED-based BEV in a beam direction, we calculated power spectra of the ED-based BEVs in all directions (0 to 355 degree) with an interval of 5 degree. We assume that as the spatial frequency and amplitude of the variation in the ED-based BEV in a beam direction is lower and smaller, respectively, the gradient of the power spectrum becomes larger, which means the robust beam direction. The ED-based BEV was produced by projection of a 3D electron density map derived from the computed tomogra- phy (CT) image from a beam source to a planning target volume (PTV) distal end. The gradient of the power spectrum was obtained as the slope of a one-order polynomial with the power spectral values for all frequencies until a Nyquist frequency.The proposed methodology was applied to four head and neck cancer patients for determination of robust beam directions. As a preliminary result, radiation oncologists agreed with most beam directions, which seem to be robust against patient setup errors, suggested by the proposed method.

WE‐G‐BRCD‐04: Development of Automated Determination Method of Robust Beam Directions against Patient Setup Errors Based on Spatial Distribution of Electron Density in Particle Therapy

PURPOSE The three-dimensional (3D) dose distribution covering a tumor region tends to be more breakable if the beams eye view (BEV) of the 3D electron density (ED) map in a beam direction changes more abruptly with large fluctuations. Our aim of this study was to develop an automated determination method of robust beam directions against the patient setup error based on the ED-based BEV in the beam direction in the particle therapy. METHODS The basic idea of our proposed method was to find the robust beam directions, whose the ED-based BEV has the spatial fluctuations with low special frequency and small amplitude. For evaluation of the spatial fluctuation in the ED-based BEV in a beam direction, we obtained power spectra of the ED-based BEVs in all directions, i.e., 0 to 355 degree, with an interval of 5 degree. It was assumed that as the average spatial frequency and amplitude of the fluctuation in the ED-based BEV in a beam direction is lower and smaller, respectively, the absolute value of a gradient of the power spectrum becomes larger. Therefore the gradient of the power spectrum was calculated for determination of the robust beam direction. The ED-based BEV was produced by projecting a 3D electron density map derived from the computed tomography (CT) image from a beam source to the distal end of a planning target volume (PTV). Four cases of head and neck cancer patients were selected for evaluation of the proposed method. RESULTS As a preliminary result, radiation oncologists agreed with most beam directions, which seem to be robust against patient setup errors, suggested by the proposed method. CONCLUSIONS Our proposed method could be feasible to suggest the robust beam directions against patient setup errors in hadron particle therapy.

TU‐E‐BRB‐01: Similar‐Case‐Based Optimization of Beam Arrangements in Stereotactic Body Radiation Therapy

PURPOSE The quality of a treatment plan for stereotactic body radiotherapy (SBRT) depends on an experience of each treatment planner. Therefore, the treatment plans are subjectively determined by comparison of several treatment plans developed by time consuming iterative manners, while considering the benefit to a tumor and the risk to the surrounding normal tissues. The aim of our study was to develop an automated optimization method for beam arrangements based on similar cases in a database including plans designed by senior experienced treatment planners. METHODS Our proposed method consists of three steps. First, similar cases were automatically selected based on image features from the treatment planning point of view. We defined four types of image features relevant to planning target volume (PTV) location, PTV shape, lung size, and spinal cord positional features. Second, the beam angles of the similar case were registered to the objective case with respect to lung regions using a linear registration technique. Third, the beam direction of the objective case was locally optimized based on the cost function considering radiation absorption in normal tissues and organs at risk. The proposed method was evaluated with 10 test cases and a treatment planning database including 81 cases by using eight planning evaluation indices such as D95, lung V20, and maximum spinal cord dose. RESULTS The proposed method may provide usable beam directions, which have no statistically significant differences with the original beam directions (P > 0.05) in terms of the seven planning evaluation indices. Moreover, the mean value of D95 for 10 test cases was improved with a statistically significant difference by using the proposed method, compared with the original beam directions (P = 0.03). CONCLUSIONS The proposed method could be used as a computer-assisted treatment planning tool for determination of beam directions in SBRT.

SU‐E‐I‐91: Development of a Compact Radiographic Simulator Using Microsoft Kinect

PURPOSE Radiographic simulator system is useful for learning radiographic techniques and confirmation of positioning before x-ray irradiation. Conventional x-ray simulators have drawbacks in cost and size, and are only applicable to situations in which position of the object does not change. Therefore, we have developed a new radiographic simulator system using an infrared-ray based three-dimensional shape measurement device (Microsoft Kinect). METHODS We made a computer program using OpenCV and OpenNI for processing of depth image data obtained from Kinect, and calculated the exact distance from Kinect to the object by calibration. Theobject was measured from various directions, and positional relationship between the x-ray tube and the object was obtained. X-ray projection images were calculated by projecting x-rays onto the mathematical three-dimensional CT data of a head phantom with almost the same size. The object was rotated from 0 degree (standard position) through 90 degrees in increments of 10 degrees, and the accuracy of the measured rotation angle values was evaluated. In order to improve the computational time, the projection image size was changed (512*512, 256*256, and 128*128). RESULTS The x-ray simulation images corresponding to the radiographic images produced by using the x-ray tube were obtained. The three-dimensional position of the object was measured with good precision from 0 to 50 degrees, but above 50 degrees, measured position error increased with the increase of the rotation angle. The computational time and image size were 30, 12, and 7 seconds for 512*512, 256*256, and 128*128, respectively. CONCLUSIONS We could measure the three-dimensional position of the object using properly calibrated Kinect sensor, and obtained projection images at relatively high-speed using the three-dimensional CTdata. It was suggested that this system can be used for obtaining simulated projection x-ray images before x-ray exposure by attaching this device onto an x-ray tube.

SU‐GG‐J‐44: Estimation of Lateral Scatter Kernels in EPID and Water Equivalent Phantom for Dose Verification in Stereotactic Lung Radiotherapy

Purpose: Lateral scatter kernels (LSKs) of an electronic portal imaging device(EPID) and a water equivalent phantom are essential data for estimating the three‐dimensional dose distributions in lungcancer patients who receive stereotactic body radiotherapy. The LSKs are used for converting portal images to portal doseimages. The purpose of this study was to investigate a method of estimating LSKs of the EPID and water equivalent phantom, and then compare the LSKs between experimental measurements and the Monte Carlo(MC) method. Method and Materials: The experimental LSKs were derived from the differentiation of the signal (mean pixel value or absorbed dose) as a function of equivalent circular radius of irradiation area. Mean pixel values in a region of interest of the EPID and absorbed doses in the water equivalent phantom were measured for estimating the LSKs of the EPID and water equivalent phantom, respectively, by changing the irradiation area of 3×3 to 20×20 cm2. For evaluation of the experimental method, the theoretical LSKs were obtained based on the Monte Carlo method by simulating the same geometry of the experimental set‐up including the EPID and water equivalent phantom. Two x‐ray energies of 6 and 10 MV were employed respectively, at a medicallinear accelerator in conjunction with an EPID.Results: The experimental method overestimated the LSKs of the EPID and water equivalent phantom compared with those of the Monte Carlo simulation method. The full width half maximum values at 6 and 10 MV of the theoretical LSKs were 0.166 and 0.193 cm for the EPID, respectively, and 0.177 and 0.211 cm for the water equivalent phantom, respectively. Conclusion: We should continue to investigate the experimental and theoretical methods for estimation of LSKs of the EPID and water equivalent phantom for dose verification in stereotactic lungradiotherapy.