An improved method for automated calculation of the water-equivalent diameter for estimating size-specific dose in CT.

PURPOSE: The aim of this study is to propose an algorithm for the automated calculation of water-equivalent diameter (Dw ) and size-specific dose estimation (SSDE) from clinical computed tomography (CT) images containing one or more substantial body part. METHODS: All CT datasets were retrospectively acquired by the Toshiba Aquilion 128 CT scanner. The proposed algorithm consisted of a contouring stage for the Dw calculation, carried out by taking the six largest objects in the cross-sectional image of the patient's body, followed by the removal of the CT table depending on the center position (y-axis) of each object. Validation of the proposed algorithm used images of patients who had undergone chest examination with both arms raised up, one arm placed down and both arms placed down, images of the pelvic region consisting of one substantial object, and images of the lower extremities consisting of two separated areas. RESULTS: The proposed algorithm gave the same results for Dw and SSDE as the previous algorithm when images consisted of one substantial body part. However, when images consisted of more than one substantial body part, the new algorithm was able to detect all parts of the patient within the image. The Dw values from the proposed algorithm were 9.5%, 15.4%, and 39.6% greater than the previous algorithm for the chest region with one arm placed down, both arms placed down, and images with two legs, respectively. The SSDE values from the proposed algorithm were 8.2%, 11.2%, and 20.6% lower than the previous algorithm for the same images, respectively. CONCLUSIONS: We have presented an improved algorithm for automated calculation of Dw and SSDE. The proposed algorithm is more general and gives accurate results for both Dw and SSDE whether the CT images contain one or more than one substantial body part.

EGSnrc application for IMRT planning.

The aim of this study was to describe a detailed instruction of intensity modulated radiotherapy (IMRT) planning simulation using BEAMnrc-DOSXYZnrc code system (EGSnrc package) and present a new graphical user interface based on MATLAB code (The MathWorks) to combine more than one. 3ddose file which were obtained from the IMRT plan. This study was performed in four phases: the commissioning of Varian Clinac iX6 MV, the simulation of IMRT planning in EGSnrc, the creation of in-house VDOSE GUI, and the analysis of the isodose contour and dose volume histogram (DVH) curve from several beam angles. The plan paramaters in sequence and control point files were extracted from the planning data in Tan Tock Seng Hospital Singapore (multileaf collimator (MLC) leaf positions - bank A and bank B, gantry angles, coordinate of isocenters, and MU indexes). VDOSE GUI which was created in this study can display the distribution dose curve in each slice and beam angle. Dose distributions from various MLC settings and beam angles yield different dose distributions even though they used the same number of simulated particles. This was due to the differences in the MLC leaf openings in every field. The value of the relative dose error between the two dose ditributions for "body" was 51.23 %. The Monte Carlo (MC) data was normalized with the maximum dose but the analytical anisotropic algorithm (AAA) data was normalized by the dose in the isocenter. In this study, we have presented a Monte Carlo simulation framework for IMRT dose calculation using DOSXYZnrc source 21. Further studies are needed in conducting IMRT simulations using EGSnrc to minimize the different dose error and dose volume histogram deviation.

Study of efficiency in five-field and field-by-field intensity modulated radiation therapy (IMRT) plan using DOSXYZnrc Monte Carlo code.

Implementation of a modern treatment technique, such as IMRT, has been improved. In line with that, Monte Carlo (MC) simulations of this technique require the ability of complex beam configurations modelling with respect to the patient. The source 20 DOSXYZnrc with the dynamic and step and shoot technique can be used to simulate the modality. However, they have a different process to obtain the dose distribution in a certain phantom. This study aimed to compare the simulation efficiency and isodose dose distribution in a water phantom from various beam angles and multileaf collimator (MLC) positions in an IMRT plan using source 20. The 30 × 30 × 30 cm3 phantom was irradiated by Varian Clinac iX10MV photon beam with various field sizes from 2 × 2 to 6 × 6 cm2 using some beam angles 5°, 30°, 90°, 180°, and 300° and maintaining the source to surface distance (SSD) of 100 cm. The field-by-field and five-field methods were used to obtain the 3-dimensional (3D) dose distribution. The dose distribution of these methods was compared using the gamma index, DVH analysis, and simulation efficiency. Higher efficiency is better because it implies that it takes less time to reach a given uncertainty. The implementation of source 20 has been validated, with similar results, with validated source in DOSXYZnrc. The identical 3D-dimensions dose distributions using source 20 for dynamic and step and shoot were observed. Two simulations used the same number of histories with the statistical uncertainty of less than 3%. The step and shoot technique was more efficient than the dynamic simulation.

Monte carlo model and output factors of elekta infinity™ 6 and 10 MV photon beam.

AIM: This study aimed to commission the Elekta Infinity™ working in 6 and 10 MV photon beam installed in Concord International Hospital, Singapore, and compare the OFs between MC simulation and measurement using PTW semiflex and microDiamond detector for small field sizes. MATERIAL AND METHODS: There are two main steps in this study: modelling of Linac 6 and 10 MV photon beam and analysis of the output factors for field size 2 × 2-10 × 10 cm2. The EGSnrc/BEAMnrc-DOSXYZnrc code was used to model and characterize the Linac and to calculate the dose distributions in a water phantom. The dose distribution and OFs were compared to the measurement data in the same condition. RESULTS: The commissioning process was only conducted for a 10 × 10 cm2 field size. The PDD obtained from MC simulation showed a good agreement with the measurement. The local dose difference of PDDs was less than 2% for 6 and 10 MV. The initial electron energy was 5.2 and 9.4 MeV for 6 and 10 MV photon beam, respectively. This Linac model can be used for dose calculation in other situations and different field sizes because this Linac has been commissioned and validated using Monte Carlo simulation. The 10 MV Linac produces higher electron contamination than that of 6 MV. CONCLUSIONS: The Linac model in this study was acceptable. The most important result in this work comes from OFs resulted from MC calculation. This value was more significant than the OFs from measurement using semiflex and microDiamond for all beam energy and field sizes because of the CPE phenomenon.

An evaluation of computed tomography dose index measurements using a pencil ionisation chamber and small detectors.

The aim of this study was to compare the values of the computed tomography dose index 100 (CTDI100) obtained using two small detectors (i.e. a small ionisation chamber and a small solid state detector) with those obtained from a 100 mm pencil ionisation chamber for various input CT parameters: beam width, kVp, mAs, pitch, and head-body phantom variation. The measurement of CTDI100 using the 100 mm pencil chamber was carried out in a single rotation of axial mode, while the measurement using small detectors was carried out in helical mode. The differences of CTDI100 values obtained with two small detectors were about 7% for all variations. The differences of CTDI100 values obtained with small detectors and a 100 mm pencil ionisation chamber for beam widths of more than 4 mm were within 40%. However, for the narrowest beam widths (4 mm), the difference between them was very large (about 150%).

Assessment of patient dose and noise level of clinical CT images: automated measurements.

We investigated comparisons between patient dose and noise in pelvic, abdominal, thoracic and head CT images using an automatic method. 113 patient images (37 pelvis, 34 abdominal, 25 thoracic, and 17 head examinations) were retrospectively and automatically examined in this study. Water-equivalent diameter (Dw), size-specific dose estimates (SSDE) and noise were automatically calculated from the center slice for every patient image. The Dw was calculated based on auto-contouring of the patients' edges, and the SSDE was calculated as the product of the volume CT dose index (CTDIvol) extracted from the Digital Imaging and Communications in Medicine (DICOM) header and the size conversion factor based on the Dw obtained from AAPM 204. The noise was automatically measured as a minimum standard deviation in the map of standard deviations. A square region of interest of about 1 cm2 was used in the automated noise measurement. The SSDE values for the pelvis, abdomen, thorax, and head were 21.8 ± 7.3 mGy, 22.0 ± 4.5 mGy, 21.5 ± 4.7 mGy, and 65.1 ± 1.7 mGy, respectively. The SSDEs for the pelvis, abdomen, and thorax increased linearly with increasing Dw, and for the head with constant tube current, the SSDE decreased with increasing Dw. The noise in the pelvis, abdomen, thorax, and head were 5.9 ± 1.5 HU, 5.2 ± 1.4 HU, 4.9 ± 0.8 HU and 3.9 ± 0.2 HU, respectively. The noise levels for the pelvis, abdomen, and thorax of the patients were relatively constant with Dw because of tube current modulation. The noise in the head image was also relatively constant because Dw variations in the head are very small. The automated approach provides a convenient and objective tool for dose optimizations.

An algorithm for automated modulation transfer function measurement using an edge of a PMMA phantom: Impact of field of view on spatial resolution of CT images.

PURPOSE: The purpose of this study was to introduce a new algorithm for automated measurement of the modulation transfer function (MTF) using an edge of a readily available phantom and to evaluate the effect of reconstruction filter and field of view (FOV) on the spatial resolution in the CT images. METHODS: Our automated MTF measurement consisted of several steps. The center of the image was established and an appropriate region of interest (ROI) designated. The edge spread function (ESF) was determined, and a suitably interpolated ESF curve was differentiated to obtain the line spread function (LSF). The LSF was Fourier transformed to obtain the MTF. All these steps were accomplished automatically without user intervention. The results of the automated MTF from the edge phantom were validated by comparing them with a point image, and the results of the automated calculation were validated by the standard fitting method. The automated MTF calculation was then applied to the images of two polymethyl methacrylate (PMMA) phantoms and a wire phantom which had been scanned by a Toshiba Alexion 4-slice CT scanner and reconstructed with various filter types and FOVs. RESULTS: The difference in the 50% MTF values obtained from the edge and point phantoms were within ±4%. The values from the automated and fitted methods agreed to within ±2%, indicating that the automated MTF calculation was accurate. The automated MTF calculation was able to differentiate MTF curves for various filters. The spatial resolution values were 0.37 ± 0.00, 0.71 ± 0.01, and 0.78 ± 0.01 cycles/mm for FC13, FC30 and FC52 filters, respectively. The spatial resolution of the images decrease linearly (R2  > 0.98) with increasing FOVs. CONCLUSION: An automated MTF method was successfully developed using an edge phantom, the PMMA phantom. The method is easy to implement in a clinical environment and is not influenced by user experience.

Automated Calculation of Water-equivalent Diameter (DW) Based on AAPM Task Group 220.

The purpose of this study is to accurately and effectively automate the calculation of the water-equivalent diameter (DW) from 3D CT images for estimating the size-specific dose. DW is the metric that characterizes the patient size and attenuation. In this study, DW was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated DW calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of DW based on the automated contouring for every slice (DW,all). The results of this study show that the automated calculation of DW and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of DW and the manual calculation are less than 0.5%. The results of this study also show that the estimating of DW,all using DW,n=1 (central slice along longitudinal axis) produces percentage differences of -0.92% ± 3.37% and 6.75%± 1.92%, and estimating DW,all using DW,n=9 produces percentage differences of 0.23% ± 0.16% and 0.87% ± 0.36%, for thorax and head examinations, respectively. From this study, the percentage differences between normalized size-specific dose estimate for every slice (nSSDEall) and nSSDEn=1 are 0.74% ± 2.82% and -4.35% ± 1.18% for thorax and head examinations, respectively; between nSSDEall and nSSDEn=9 are 0.00% ± 0.46% and -0.60% ± 0.24% for thorax and head examinations, respectively.

Evaluation of physical properties and image of polyvinyl chloride as breast tissue equivalence for dual-modality (mammography and ultrasound).

TMP is gradually becoming a fundamental element for quality assurance and control in ionizing and non-ionizing radiation imaging modalities as well as in the development of different techniques. This study aimed to evaluate and obtain polyvinyl chloride tissue mimicking material for dual-modality breast phantoms in mammography and ultrasound. Breast tissue equivalence was evaluated based on X-ray attenuation properties, speed of sound, attenuation, and acoustic impedance. There are six samples of PVC-plasticizer material with variations of PVC concentration and additives. The evaluation of X-ray attenuation was carried out using mammography from 23 to 35 kV, while the acoustic properties were assessed with mode A ultrasound and a transducer frequency of 5 MHz. A breast phantom was created from TMP material with tissue equivalence and was then evaluated using mammography as well as ultrasound to analyze its image quality. The results showed that samples A (PVC 5%, DOP 95%), B (PVC 7%, DOP 93%), C (PVC 10%, DOP 90%), E (PVC 7%, DOP 90%, graphite 3%), and F (PVC 7%, DOP 90%, silicone oil 3%) have the closest equivalent to the ACR breast phantom material with a different range of 0.01-1.39 in the 23-35 kV range. Based on the evaluation of the acoustic properties of ultrasound, A had high similarity to fat tissue with a difference of 0.03 (dB cm- 1 MHz- 1) and 0.07 (106 kg m- 2 s- 1), while B was close to the glandular tissue with a difference of 9.2 m s- 1. Multilayer breast phantom images' results showed gray levels in mammography and ultrasound modalities. Therefore, this study succeeded in establishing TMP material for mammography and ultrasound. It can also be used for simple quality assurance and control programs.

Investigation of Eye Lens Dose Estimate based on AAPM Report 293 in Head Computed Tomography.

BACKGROUND: Estimation of eye lens dose is important in head computed tomography (CT) examination since the eye lens is a sensitive organ to ionizing radiation. OBJECTIVE: The purpose of this study is to compare estimations of eye lens dose in head CT examinations using local size-specific dose estimate (SSDE) based on size-conversion factors of the American Association of Physicists in Medicine (AAPM) Report No. 293 with those based on size-conversion factors of the AAPM Report No. 220. MATERIAL AND METHODS: This experimental study is conducted on a group of patients who had undergone nasopharyngeal CT examination. Due to the longitudinal (z-axis) dose fluctuation, the average global SSDE and average local SSDE (i.e. particular slices where the eyes are located) were investigated. All estimates were compared to the measurement results using thermo-luminescent dosimeters (TLDs). The estimated and measured doses were implemented for 14 patients undergoing nasopharyngeal CT examination. RESULTS: It was found that the percentage differences of the volume CT dose index (CTDIvol), average global SSDE based on AAPM No. 220 (SSDEo,g), average local SSDE based on AAPM No. 220 (SSDEo,l), average global SSDE based on AAPM No. 293 (SSDEn,g) and average local SSDE based on AAPM No. 293 (SSDEn,l) against the measured TLD doses were 22.5, 21.7, 15.0, 9.3, and 2.1%, respectively. All comparisons between dose estimates and TLD measurements gave p-values less than 0.001, except for SSDEn,l (p-value = 0.566). CONCLUSION: SSDE based on AAPM Report No. 293 can be used to accurately estimate eye lens radiation doses by performing the calculations on a number of specific slices containing the eyes.

An Improved Method of Automated Noise Measurement System in CT Images.

BACKGROUND: It is necessary to have an automated noise measurement system working accurately to optimize dose in computerized tomography (CT) examinations. OBJECTIVE: This study aims to develop an algorithm to automate noise measurement that can be implemented in CT images of all body regions. MATERIALS AND METHODS: In this retrospective study, our automated noise measurement method consists of three steps as follows: the first is segmenting the image of the patient. The second is developing a standard deviation (SD) map by calculating the SD value for each pixel with a sliding window operation. The third step is estimating the noise as the smallest SD from the SD map. The proposed method was applied to the images of a homogenous phantom and a full body adult anthropomorphic phantom, and retrospectively applied to 27 abdominal images of patients. RESULTS: For a homogeneous phantom, the noises calculated using our proposed and previous algorithms have a linear correlation with R2 = 0.997. It is found that the noise magnitude closely follows the magnitude of the water equivalent diameter (Dw) in all body regions. The proposed algorithm is able to distinguish the noise magnitude due to variations in tube currents and different noise suppression techniques such as strong, standard, mild, and weak ones in a reconstructed image using the AIDR 3D algorithm. CONCLUSION: An automated noise calculation has been proposed and successfully implemented in all body regions. It is not only accurate and easy to implement but also not influenced by the subjectivity of user.

Development of a computational phantom for validation of automated noise measurement in CT images.

The purpose of this study was to develop a computational phantom for validation of automatic noise calculations applied to all parts of the body, to investigate kernel size in determining noise, and to validate the accuracy of automatic noise calculation for several noise levels. The phantom consisted of objects with a very wide range of HU values, from -1000 to +950. The incremental value for each object was 10 HU. Each object had a size of 15 × 15 pixels separated by a distance of 5 pixels. There was no dominant homogeneous part in the phantom. The image of the phantom was then degraded to mimic the real image quality of CT by convolving it with a point spread function (PSF) and by addition of Gaussian noise. The magnitude of the Gaussian noises was varied (5, 10, 25, 50, 75 and 100 HUs), and they were considered as the ground truth noise (NG). We also used a computational phantom with added actual noise from a CT scanner. The phantom was used to validate the automated noise measurement based on the average of the ten smallest standard deviations (SD) from the standard deviation map (SDM). Kernel sizes from 3 × 3 up to 27 × 27 pixels were examined in this study. A computational phantom for automated noise calculations validation has been successfully developed. It was found that the measured noise (NM) was influenced by the kernel size. For kernels of 15 × 15 pixels or smaller, the NMvalue was much smaller than the NG. For kernel sizes from 17 × 17 to 21 × 21 pixels, the NMvalue was about 90% of NG. And for kernel sizes of 23 × 23 pixels and above, NMis greater than NG. It was also found that even with small kernel sizes the relationship between NMand NGis linear with R2more than 0.995. Thus accurate noise levels can be automatically obtained even with small kernel sizes without any concern regarding the inhomogeneity of the object.

Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network.

PURPOSE: The classification of urinary stones is important prior to treatment because the treatments depend on three types of urinary stones, i.e., calcium, uric acid, and mixture stones. We have developed an automatic approach for the classification of urinary stones into the three types based on microcomputed tomography (micro-CT) images using a convolutional neural network (CNN). MATERIALS AND METHODS: Thirty urinary stones from different patients were scanned in vitro using micro-CT (pixel size: 14.96 µm; slice thickness: 15 µm); a total of 2,430 images (micro-CT slices) were produced. The slices (227 × 227 pixels) were classified into the three categories based on their energy dispersive X-ray (EDX) spectra obtained via scanning electron microscopy (SEM). The images of urinary stones from each category were divided into three parts; 66%, 17%, and 17% of the dataset were assigned to the training, validation, and test datasets, respectively. The CNN model with 15 layers was assessed based on validation accuracy for the optimization of hyperparameters such as batch size, learning rate, and number of epochs with different optimizers. Then, the model with the optimized hyperparameters was evaluated for the test dataset to obtain classification accuracy and error. RESULTS: The validation accuracy of the developed approach with CNN with optimized hyperparameters was 0.9852. The trained CNN model achieved a test accuracy of 0.9959 with a classification error of 1.2%. CONCLUSIONS: The proposed automated CNN-based approach could successfully classify urinary stones into three types, namely calcium, uric acid, and mixture stones, using micro-CT images.

A SIMPLIFIED METHOD FOR THE WATER-EQUIVALENT DIAMETER CALCULATION TO ESTIMATE PATIENT DOSE IN CT EXAMINATIONS.

We proposed and evaluated a water-equivalent diameter calculation without using a region of interest (ROI), (Dw,t) and compared it with the results of using a ROI fitted to the patient border (Dw,f). Evaluations were carried out on thoracic and head CT images. We found that the difference between Dw,t and Dw,f was within 5% for all images in the head region, and most images were within 5% (27 of the 30 patients, 90%) in the thoracic region. We also proposed a method to automatically detect and eliminate the patient table (or head support) from images and evaluated the water-equivalent diameter values after the table had been removed (Dw,nt). This method was able to recognize and remove the patient table from all images used. By removing the table, the water-equivalent diameter (Dw,nt) became more accurate and the difference from Dw,f was within 5% for all images (head and thoracic images).

A SIMPLE METHOD FOR CALIBRATING PIXEL VALUES OF THE CT LOCALIZER RADIOGRAPH FOR CALCULATING WATER-EQUIVALENT DIAMETER AND SIZE-SPECIFIC DOSE ESTIMATE.

The purpose of this study is to establish the relationship between the pixel value (I) of the CT localizer radiograph and water-equivalent thickness (tw) in a straightforward procedure. We used a body CTDI phantom, which was scanned in the AP and LAT projections. After transformation from the pixel values of the images to tw, water-equivalent diameter (Dw) and size-specific dose estimate were calculated on an anthropomorphic phantom and 30 patients retrospectively. We found a linear correlation between I and tw, with R2 ≥ 0.980. The Dw values based on the CT localizer radiograph were comparable to those calculated using axial images. The Dw difference for the anthropomorphic phantom between AP projection and axial images was 5.4 ± 4.2%, and between LAT projection and axial images was 6.7 ± 5.3%. The Dw differences for the patients between CT localizer radiograph and axial images was 2.3 ± 3.2%.

THE SIZE-SPECIFIC DOSE ESTIMATE (SSDE) FOR TRUNCATED COMPUTED TOMOGRAPHY IMAGES.

The purpose of this study is to investigate truncated axial computed tomography (CT) images in the clinical environment and to produce correction factors for abdomen, thoracic and head regions based on clinical data, in order to accurately predict the water-equivalent diameter (DW) and size-specific dose estimate (SSDE). We investigated axial images of 75 patients who underwent CT examinations. Truncated axial images were characterized by the truncation percentage (TP). Correction factors were calculated by using the value of DW for a certain TP (truncated image) divided by the value of DW for TP = 0% (the non-truncated image). Most of the thorax images acquired for this study were truncated images (86.2%), in the abdomen region about half of the images were truncated (48.1%), and in the head region only a small portion were truncated (9.1%). In the thorax region the value of TP for the truncated images varied up to 50%, in the abdomen region it varied up to 35%, and in the head region it was smaller than 10%. We have shown how to accurately estimate DW and SSDE by applying a correction factor to the truncated images. The correction factors increase exponentially with increasing TP. The corrected DW and SSDE for the truncated images were significant in the thoracic region, but were not significant in the abdomen and head regions.

The impact of patient table on size-specific dose estimate (SSDE).

The use of parameters water equivalent diameter (D W ) and size-specific dose estimate (SSDE) are becoming increasingly established as a recognised method to relate patient dose from a CT examination to the dose indicator volume CT dose index (CTDIVOL). However, the role of the attenuation due to the patient table in these estimations requires careful consideration and is the subject of this study. The aim of this study is to investigate the impact of a minimal part of the patient table when calculating the D W and SSDE. We investigated 164 patients who had undergone CT examinations for the pelvis, abdomen, thorax and head. We subsequently calculated D W and SSDE using two methods: one using a small circular region of interest (ROI) including a minimal part of the patient table and the other using a ROI fitted to the patient border alone. The results showed that the water equivalent diameter calculated with the table included in the ROI (D W,t ) is greater, compared to that without the consideration of the patient table (D W,nt ), by 1.5-6.2% depending on the anatomy being imaged. On the other hand, the SSDE calculated with inclusion of the patient table (SSDEt) is smaller than otherwise (SSDEnt) by 1.0-5.5% again depending on the anatomy being imaged. The effect of the patient table on D W and SSDE in the thorax CT examination was statistically significant, but its effect on D W and SSDE in the other examinations of head, pelvis and abdomen was relatively small and not statistically significant.

Feasibility of differential geometry-based features in detection of anatomical feature points on patient surfaces in range image-guided radiation therapy.

PURPOSE: To investigate the feasibility of differential geometry features in the detection of anatomical feature points on a patient surface in infrared-ray-based range images in image-guided radiation therapy. METHODS: The key technology was to reconstruct the patient surface in the range image, i.e., point distribution with three-dimensional coordinates, and characterize the geometrical shape at every point based on curvature features. The region of interest on the range image was extracted by using a template matching technique, and the range image was processed for reducing temporal and spatial noise. Next, a mathematical smooth surface of the patient was reconstructed from the range image by using a non-uniform rational B-splines model. The feature points were detected based on curvature features computed on the reconstructed surface. The framework was tested on range images acquired by a time-of-flight (TOF) camera and a Kinect sensor for two surface (texture) types of head phantoms A and B that had different anatomical geometries. The detection accuracy was evaluated by measuring the residual error, i.e., the mean of minimum Euclidean distances (MMED) between reference (ground truth) and detected feature points on convex and concave regions. RESULTS: The MMEDs obtained using convex feature points for range images of the translated and rotated phantom A were [Formula: see text] and [Formula: see text], respectively, using the TOF camera. For the phantom B, the MMEDs of the convex and concave feature points were [Formula: see text] and [Formula: see text] mm, respectively, using the Kinect sensor. There was a statistically significant difference in the decreased MMED for convex feature points compared with concave feature points [Formula: see text]. CONCLUSIONS: The proposed framework has demonstrated the feasibility of differential geometry features for the detection of anatomical feature points on a patient surface in range image-guided radiation therapy.

A virtual photon energy fluence model for Monte Carlo dose calculation.

The presented virtual energy fluence (VEF) model of the patient-independent part of the medical linear accelerator heads, consists of two Gaussian-shaped photon sources and one uniform electron source. The planar photon sources are located close to the bremsstrahlung target (primary source) and to the flattening filter (secondary source), respectively. The electron contamination source is located in the plane defining the lower end of the filter. The standard deviations or widths and the relative weights of each source are free parameters. Five other parameters correct for fluence variations, i.e., the horn or central depression effect. If these parameters and the field widths in the X and Y directions are given, the corresponding energy fluence distribution can be calculated analytically and compared to measured dose distributions in air. This provides a method of fitting the free parameters using the measurements for various square and rectangular fields and a fixed number of monitor units. The next step in generating the whole set of base data is to calculate monoenergetic central axis depth dose distributions in water which are used to derive the energy spectrum by deconvolving the measured depth dose curves. This spectrum is also corrected to take the off-axis softening into account. The VEF model is implemented together with geometry modules for the patient specific part of the treatment head (jaws, multileaf collimator) into the XVMC dose calculation engine. The implementation into other Monte Carlo codes is possible based on the information in this paper. Experiments are performed to verify the model by comparing measured and calculated dose distributions and output factors in water. It is demonstrated that open photon beams of linear accelerators from two different vendors are accurately simulated using the VEF model. The commissioning procedure of the VEF model is clinically feasible because it is based on standard measurements in air and water. It is also useful for IMRT applications because a full Monte Carlo simulation of the treatment head would be too time-consuming for many small fields.

Study on the tongue and groove effect of the Elekta multileaf collimator using Monte Carlo simulation and film dosimetry.

BACKGROUND: Nowadays, multileaf collimation of the treatment fields from medical linear accelerators is a common option. Due to the design of the leaf sides, the tongue and groove effect occurs for certain multileaf collimator applications such as the abutment of fields where the beam edges are defined by the sides of the leaves. MATERIAL AND METHODS: In this study, the tongue and groove effect was measured for two pairs of irregular multileaf collimator fields that were matched along leaf sides in two steps. Measurements were made at 10 cm depth in a polystyrene phantom using Kodak EDR2 films for a photon beam energy of 6 MV on an Elekta Sli-plus accelerator. To verify the measurements, full Monte Carlo simulations were done. In the simulations, the design of the leaf sides was taken into account and one component module of BEAM code was modified to correctly simulate the Elekta multileaf collimator. RESULTS AND CONCLUSION: The results of measurements and simulations are in good agreement and within the tolerance of film dosimetry.