Monitoring ABC-assisted deep inspiration breath hold for left-sided breast radiotherapy with an optical tracking system.

PURPOSE: Recent knowledge on the effects of cardiac toxicity warrants greater precision for left-sided breast radiotherapy. Different breath-hold (BH) maneuvers (abdominal vs thoracic breathing) can lead to chest wall positional variations, even though the patient's tidal volume remains consistent. This study aims to investigate the feasibility of using optical tracking for real-time quality control of active breathing coordinator (ABC)-assisted deep inspiration BH (DIBH). METHODS: An in-house optical tracking system (OTS) was used to monitor ABC-assisted DIBH. The stability and localization accuracy of the OTS were assessed with a ball-bearing phantom. Seven patients with left-sided breast cancer were included. A free-breathing (FB) computed tomography (CT) scan and an ABC-assisted BH CT scan were acquired for each patient. The OTS tracked an infrared (IR) marker affixed over the patient's xiphoid process to measure the positional variation of each individual BH. Using the BH within which the CT scan was performed as the reference, the authors quantified intra- and interfraction BH variations for each patient. To estimate the dosimetric impact of BH variations, the authors studied the positional correlation between the marker and the left breast using the FB CT and BH CT scans. The positional variations of 860 BHs as measured by the OTS were retrospectively incorporated into the original treatment plans to evaluate their dosimetric impact on breast and cardiac organs [heart and left anterior descending (LAD) artery]. RESULTS: The stability and localization accuracy of the OTS was within 0.2 mm along each direction. The mean intrafraction variation among treatment BHs was less than 2.8 mm in all directions. Up to 12.6 mm anteroposterior undershoot, where the patient's chest wall displacement of a BH is less than that of a reference BH, was observed with averages of 4.4, 3.6, and 0.1 mm in the anteroposterior, craniocaudal, and mediolateral directions, respectively. A high positional correlation between the marker and the breast was found in the anteroposterior and craniocaudal directions with respective Pearson correlation values of 0.95 and 0.93, but no mediolateral correlation was found. Dosimetric impact of BH variations on breast coverage was negligible. However, the mean heart dose, mean LAD dose, and max LAD dose were estimated to increase from 1.4/7.4/18.6 Gy (planned) to 2.1/15.7/31.0 Gy (delivered), respectively. CONCLUSIONS: In ABC-assisted DIBH, large positional variation can occur in some patients, due to their different BH maneuvers. The authors' study has shown that OTS can be a valuable tool for real-time quality control of ABC-assisted DIBH.

Use of a line-pair resolution phantom for comprehensive quality assurance of electronic portal imaging devices based on fundamental imaging metrics.

Image guided radiation therapy solutions based on megavoltage computed tomography (MVCT) involve the extension of electronic portal imaging devices (EPIDs) from their traditional role of weekly localization imaging and planar dose mapping to volumetric imaging for 3D setup and dose verification. To sustain the potential advantages of MVCT, EPIDs are required to provide improved levels of portal image quality. Therefore, it is vital that the performance of EPIDs in clinical use is maintained at an optimal level through regular and rigorous quality assurance (QA). Traditionally, portal imaging QA has been carried out by imaging calibrated line-pair and contrast resolution phantoms and obtaining arbitrarily defined QA indices that are usually dependent on imaging conditions and merely indicate relative trends in imaging performance. They are not adequately sensitive to all aspects of image quality unlike fundamental imaging metrics such as the modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) that are widely used to characterize detector performance in radiographic imaging and would be ideal for QA purposes. However, due to the difficulty of performing conventional MTF measurements, they have not been used for routine clinical QA. The authors present a simple and quick QA methodology based on obtaining the MTF, NPS, and DQE of a megavoltage imager by imaging standard open fields and a bar-pattern QA phantom containing 2 mm thick tungsten line-pair bar resolution targets. Our bar-pattern based MTF measurement features a novel zero-frequency normalization scheme that eliminates normalization errors typically associated with traditional bar-pattern measurements at megavoltage x-ray energies. The bar-pattern QA phantom and open-field images are used in conjunction with an automated image analysis algorithm that quickly computes the MTF, NPS, and DQE of an EPID system. Our approach combines the fundamental advantages of linear systems metrics such as robustness, sensitivity across the full spatial frequency range of interest, and normalization to imaging conditions (magnification, system gain settings, and exposure), with the simplicity, ease, and speed of traditional phantom imaging. The algorithm was analyzed for accuracy and sensitivity by comparing with a commercial portal imaging QA method (PIPSPRO, Standard Imaging, Middleton, WI) on both first-generation lens-coupled and modern a-Si flat-panel based clinical EPID systems. The bar-pattern based QA measurements were found to be far more sensitive to even small levels of degradation in spatial resolution and noise. The bar-pattern based QA methodology offers a comprehensive image quality assessment tool suitable for both commissioning and routine EPID QA.

Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy.

PURPOSE: Rigid 2D-3D registration is an alternative to 3D-3D registration for cases where largely bony anatomy can be used for patient positioning in external beam radiation therapy. In this article, the authors evaluated seven similarity measures for use in the intensity-based rigid 2D-3D registration using a variation in Skerl's similarity measure evaluation protocol. METHODS: The seven similarity measures are partitioned intensity uniformity, normalized mutual information (NMI), normalized cross correlation (NCC), entropy of the difference image, pattern intensity (PI), gradient correlation (GC), and gradient difference (GD). In contrast to traditional evaluation methods that rely on visual inspection or registration outcomes, the similarity measure evaluation protocol probes the transform parameter space and computes a number of similarity measure properties, which is objective and optimization method independent. The variation in protocol offers an improved property in the quantification of the capture range. The authors used this protocol to investigate the effects of the downsampling ratio, the region of interest, and the method of the digitally reconstructed radiograph (DRR) calculation [i.e., the incremental ray-tracing method implemented on a central processing unit (CPU) or the 3D texture rendering method implemented on a graphics processing unit (GPU)] on the performance of the similarity measures. The studies were carried out using both the kilovoltage (kV) and the megavoltage (MV) images of an anthropomorphic cranial phantom and the MV images of a head-and-neck cancer patient. RESULTS: Both the phantom and the patient studies showed the 2D-3D registration using the GPU-based DRR calculation yielded better robustness, while providing similar accuracy compared to the CPU-based calculation. The phantom study using kV imaging suggested that NCC has the best accuracy and robustness, but its slow function value change near the global maximum requires a stricter termination condition for an optimization method. The phantom study using MV imaging indicated that PI, GD, and GC have the best accuracy, while NCC and NMI have the best robustness. The clinical study using MV imaging showed that NCC and NMI have the best robustness. CONCLUSIONS: The authors evaluated the performance of seven similarity measures for use in 2D-3D image registration using the variation in Skerl's similarity measure evaluation protocol. The generalized methodology can be used to select the best similarity measures, determine the optimal or near optimal choice of parameter, and choose the appropriate registration strategy for the end user in his specific registration applications in medical imaging.

High performance computing for deformable image registration: towards a new paradigm in adaptive radiotherapy.

The advent of readily available temporal imaging or time series volumetric (4D) imaging has become an indispensable component of treatment planning and adaptive radiotherapy (ART) at many radiotherapy centers. Deformable image registration (DIR) is also used in other areas of medical imaging, including motion corrected image reconstruction. Due to long computation time, clinical applications of DIR in radiation therapy and elsewhere have been limited and consequently relegated to offline analysis. With the recent advances in hardware and software, graphics processing unit (GPU) based computing is an emerging technology for general purpose computation, including DIR, and is suitable for highly parallelized computing. However, traditional general purpose computation on the GPU is limited because the constraints of the available programming platforms. As well, compared to CPU programming, the GPU currently has reduced dedicated processor memory, which can limit the useful working data set for parallelized processing. We present an implementation of the demons algorithm using the NVIDIA 8800 GTX GPU and the new CUDA programming language. The GPU performance will be compared with single threading and multithreading CPU implementations on an Intel dual core 2.4 GHz CPU using the C programming language. CUDA provides a C-like language programming interface, and allows for direct access to the highly parallel compute units in the GPU. Comparisons for volumetric clinical lung images acquired using 4DCT were carried out. Computation time for 100 iterations in the range of 1.8-13.5 s was observed for the GPU with image size ranging from 2.0 x 10(6) to 14.2 x 10(6) pixels. The GPU registration was 55-61 times faster than the CPU for the single threading implementation, and 34-39 times faster for the multithreading implementation. For CPU based computing, the computational time generally has a linear dependence on image size for medical imaging data. Computational efficiency is characterized in terms of time per megapixels per iteration (TPMI) with units of seconds per megapixels per iteration (or spmi). For the demons algorithm, our CPU implementation yielded largely invariant values of TPMI. The mean TPMIs were 0.527 spmi and 0.335 spmi for the single threading and multithreading cases, respectively, with <2% variation over the considered image data range. For GPU computing, we achieved TPMI =0.00916 spmi with 3.7% variation, indicating optimized memory handling under CUDA. The paradigm of GPU based real-time DIR opens up a host of clinical applications for medical imaging.

Novel image registration quality evaluator (RQE) with an implementation for automated patient positioning in cranial radiation therapy.

In external beam radiation therapy, digitally reconstructed radiographs (DRRs) and portal images are used to verify patient setup based either on a visual comparison or, less frequently, with automated registration algorithms. A registration algorithm can be trapped in local optima due to irregularity of patient anatomy, image noise and artifacts, and/or out-of-plane shifts, resulting in an incorrect solution. Thus, human observation, which is subjective, is still required to check the registration result. We propose to use a novel image registration quality evaluator (RQE) to automatically identify misregistrations as part of an algorithm-based decision-making process for verification of patient positioning. A RQE, based on an adaptive pattern classifier, is generated from a pair of reference and target images to determine the acceptability of a registration solution given an optimization process. Here we applied our RQE to patient positioning for cranial radiation therapy. We constructed two RQEs-one for the evaluation of intramodal registrations (i.e., portal-portal); the other for intermodal registrations (i.e., portal-DRR). Mutual information, because of its high discriminatory ability compared with other measures (i.e., correlation coefficient and partitioned intensity uniformity), was chosen as the test function for both RQEs. We adopted 1 mm translation and 1 degree rotation as the maximal acceptable registration errors, reflecting desirable clinical setup tolerances for cranial radiation therapy. Receiver operating characteristic analysis was used to evaluate the performance of the RQE, including computations of sensitivity and specificity. The RQEs showed very good performance for both intramodal and intermodal registrations using simulated and phantom data. The sensitivity and the specificity were 0.973 and 0.936, respectively, for the intramodal RQE using phantom data. Whereas the sensitivity and the specificity were 0.961 and 0.758, respectively, for the intermodal RQE using phantom data. Phantom experiments also indicated our RQEs detected out-of-plane deviations exceeding 2.5 mm and 2.50. A preliminary retrospective clinical study of the RQE on cranial portal imaging also yielded good sensitivity > or = 0.857) and specificity (> or = 0.987). Clinical implementation of a RQE could potentially reduce the involvement of the human observer for routine patient positioning verification, while increasing setup accuracy and reducing setup verification time.

Analysis of the kinestatic charge detection system as a high detective quantum efficiency electronic portal imaging device.

Megavoltage x-ray imaging suffers from reduced image quality due to low differential x-ray attenuation and large Compton scatter compared with kilovoltage imaging. Notwithstanding this, electronic portal imaging devices (EPIDs) are now widely used in portal verification in radiotherapy as they offer significant advantages over film, including immediate digital imaging and superior contrast range. However video-camera-based EPIDs (VEPIDs) are limited by problems of low light collection efficiency and significant light scatter, leading to reduced contrast and spatial resolution. Indirect and direct detection-based flat-panel EPIDs have been developed to overcome these limitations. While flat-panel image quality has been reported to exceed that achieved with portal film, these systems have detective quantum efficiency (DQE) limited by the thin detection medium and are sensitive to radiation damage to peripheral read-out electronics. An alternative technology for high-quality portal imaging is presented here: kinesatic charge detection (KCD). The KCD is a scanning tri-electrode ion-chamber containing high-pressure noble gas (xenon at 100 atm) used in conjunction with a strip-collimated photon beam. The chamber is scanned across the patient, and an external electric field is used to regulate the cation drift velocity. By matching the scanning velocity with that of the cation (i.e., ion) drift velocity, the cations remain static in the object frame of reference, allowing temporal integration of the signal. The KCD offers several advantages as a portal imaging system. It has a thick detector geometry with an active detection depth of 6.1 cm, compared to the sub-millimeter thickness of the phosphor layer in conventional phosphor screens, leading to an order of magnitude advantage in quantum efficiency (>0.3). The unique principle of and the use of the scanning strip-collimated x-ray beam provide further integration of charges in time, reduced scatter, and a significantly reduced imaging dose, enhancing the imaging signal-to-noise ratio (SNR) and leading to high DQE. While thick detectors usually suffer from reduced spatial resolution, the KCD provides good spatial resolution due to high gas pressure that limits the spread of scattered electrons, and a strip-collimated beam that significantly reduces the inclusion of scatter in the imaging signal. A 10 cm wide small-field-of-view (SFOV) prototype of the KCD is presented with a complete analysis of its imaging performance. Measurements of modulation transfer function (MTF), noise power spectrum (NPS), and DQE were in good agreement with Monte Carlo simulations. Imaging signal loss from recombination within the KCD chamber was measured at different gas pressures, ion drift velocities, and strip-collimation widths. Image quality for the prototype KCD was also observed with anthropomorphic phantom imaging in comparison with various commercial and research portal imaging systems, including VEPID, flat-panel imager, and conventional and high contrast film systems. KCD-based imaging provided very good contrast and good spatial resolution at very low imaging dose (0.1 cGy per image). For the prototype KCD, measurements yielded DQE(0)=0.19 and DQE(1 cy/mm)=0.004.

Study of a prototype high quantum efficiency thick scintillation crystal video-electronic portal imaging device.

Image quality in portal imaging suffers significantly from the loss in contrast and spatial resolution that results from the excessive Compton scatter associated with megavoltage x rays. In addition, portal image quality is further reduced due to the poor quantum efficiency (QE) of current electronic portal imaging devices (EPIDs). Commercial video-camera-based EPIDs or VEPIDs that utilize a thin phosphor screen in conjunction with a metal buildup plate to convert the incident x rays to light suffer from reduced light production due to low QE (<2% for Eastman Kodak Lanex Fast-B). Flat-panel EPIDs that utilize the same luminescent screen along with an a-Si:H photodiode array provide improved image quality compared to VEPIDs, but they are expensive and can be susceptible to radiation damage to the peripheral electronics. In this article, we present a prototype VEPID system for high quality portal imaging at sub-monitor-unit (subMU) exposures based on a thick scintillation crystal (TSC) that acts as a high QE luminescent screen. The prototype TSC system utilizes a 12 mm thick transparent CsI(Tl) (thallium-activated cesium iodide) scintillator for QE=0.24, resulting in significantly higher light production compared to commercial phosphor screens. The 25 X 25 cm2 CsI(Tl) screen is coupled to a high spatial and contrast resolution Video-Optics plumbicon-tube camera system (1240 X 1024 pixels, 250 microm pixel width at isocenter, 12-bit ADC). As a proof-of-principle prototype, the TSC system with user-controlled camera target integration was adapted for use in an existing clinical gantry (Siemens BEAMVIEW(PLUS)) with the capability for online intratreatment fluoroscopy. Measurements of modulation transfer function (MTF) were conducted to characterize the TSC spatial resolution. The measured MTF along with measurements of the TSC noise power spectrum (NPS) were used to determine the system detective quantum efficiency (DQE). A theoretical expression of DQE(0) was developed to be used as a predictive model to propose improvements in the optics associated with the light detection. The prototype TSC provides DQE(0)=0.02 with its current imaging geometry, which is an order of magnitude greater than that for commercial VEPID systems and comparable to flat-panel imaging systems. Following optimization in the imaging geometry and the use of a high-end, cooled charge-coupled-device (CCD) camera system, the performance of the TSC is expected to improve even further. Based on our theoretical model, the expected DQE(0)=0.12 for the TSC system with the proposed improvements, which exceeds the performance of current flat-panel EPIDs. The prototype TSC provides high quality imaging even at subMU exposures (typical imaging dose is 0.2 MU per image), which offers the potential for daily patient localization imaging without increasing the weekly dose to the patient. Currently, the TSC is capable of limited frame-rate fluoroscopy for intratreatment visualization of patient motion at approximately 3 frames/second, since the achievable frame rate is significantly reduced by the limitations of the camera-control processor. With optimized processor control, the TSC is expected to be capable of intratreatment imaging exceeding 10 frames/second to monitor patient motion.

Verification of multileaf collimator leaf positions using an electronic portal imaging device.

An automated method is presented for determining individual leaf positions of the Siemens dual focus multileaf collimator (MLC) using the Siemens BEAMVIEW(PLUS) electronic portal imaging device (EPID). Leaf positions are computed with an error of 0.6 mm at one standard deviation (sigma) using separate computations of pixel dimensions, image distortion, and radiation center. The pixel dimensions are calculated by superimposing the film image of a graticule with the corresponding EPID image. A spatial correction is used to compensate for the optical distortions of the EPID, reducing the mean distortion from 3.5 pixels (uncorrected) per localized x-ray marker to 2 pixels (1 mm) for a rigid rotation and 1 pixel for a third degree polynomial warp. A correction for a nonuniform dosimetric response across the field of view of the EPID images is not necessary due to the sharp intensity gradients across leaf edges. The radiation center, calculated from the average of the geometric centers of a square field at 0 degrees and 180 degrees collimator angles, is independent of graticule placement error. Its measured location on the EPID image was stable to within 1 pixel based on 3 weeks of repeated extensions/retractions of the EPID. The MLC leaf positions determined from the EPID images agreed to within a pixel of the corresponding values measured using film and ionization chamber. Several edge detection algorithms were tested: contour, Sobel, Roberts, Prewitt, Laplace, morphological, and Canny. These agreed with each other to within < or = 1.2 pixels for the in-air EPID images. Using a test pattern, individual MLC leaves were found to be typically within 1 mm of the corresponding record-and-verify values, with a maximum difference of 1.8 mm, and standard deviations of <0.3 mm in the daily reproducibility. This method presents a fast, automatic, and accurate alternative to using film or a light field for the verification and calibration of the MLC.