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Purpose: To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images. Methods: A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams were calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants. Results: IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was −1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [−2.4, −0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images. Conclusions: IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

The authors present the design and simulation of an imaging system that employs a compact multiple source x-ray tube to produce a tomosynthesisimage from a set of projections obtained at a single tube position. The electron sources within the tube are realized using cold cathodecarbon nanotube technology. The primary intended application is tomosynthesis-based 3D image guidance during external beam radiation therapy. The tube, which is attached to the gantry of a medicallinear accelerator(linac) immediately below the multileaf collimator, operates within the voltage range of 80 – 160 kVp and contains a total of 52 sources that are arranged in a rectilinear array. This configuration allows for the acquisition of tomographic projections from multiple angles without any need to rotate the linac gantry. The x-ray images are captured by the same amorphous silicon flat panel detector employed for portal imaging on contemporary linacs. The field of view (FOV) of the system corresponds to that part of the volume that is sampled by rays from all sources. The present tube and detector configuration provides an 8 × 8 cm 2 FOV in the plane of the linac isocenter when the 40.96 × 40.96 cm 2 imaging detector is placed 40 cm from the isocenter. Since this tomosynthesis application utilizes the extremities of the detector to record image detail relating to structures near the isocenter, simultaneous treatment and imaging is possible for most clinical cases, where the treated target is a small region close to the linac isocenter. The tomosynthesisimages are reconstructed using the simultaneous iterative reconstruction technique, which is accelerated using a graphic processing unit. The authors present details of the system design as well as simulated performance of the imaging system based on reprojections of patient CTimages.

We describe a focused beam-stop array (BSA) for the measurement of object scatter in imaging systems that utilize x-ray beams in the megavoltage (MV) energy range. The BSA consists of 64 doubly truncated tungsten cone elements of 0.5 cm maximum diameter that are arranged in a regular array on an acrylic slab. The BSA is placed in the accessory tray of a medical linear accelerator at a distance of approximately 50 cm from the focal spot. We derive an expression that allows us to estimate the scatter in an image taken without the array present, given image values in a second image with the array in place. The presence of the array reduces fluence incident on the imaged object. This leads to an object-dependent underestimation bias in the scatter measurements. We apply corrections in order to address this issue. We compare estimates of the flat panel detector response to scatter obtained using the BSA to those derived from Monte Carlo simulations. We find that the two estimates agree to within 10% in terms of RMS error for 30 cm x 30 cm water slabs in the thickness range of 10-30 cm. Larger errors in the scatter estimates are encountered for thinner objects, probably owing to extrafocal radiation sources. However, RMS errors in the estimates of primary images are no more than 5% for water slab thicknesses in the range of 1-30 cm. The BSA scatter estimates are also used to correct cone beam tomographic projections. Maximum deviations of central profiles of uniform water phantoms are reduced from 193 to 19 HU after application of corrections for scatter, beam hardening, and lateral truncation that are based on the BSA-derived scatter estimate. The same corrections remove the typical cupping artifact from both phantom and patient images. The BSA proves to be a useful tool for quantifying and removing image scatter, as well as for validating models of MV imaging systems.

To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images.A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams were calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants.IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was -1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [-2.4, -0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images.IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

The authors present the design and simulation of an imaging system that employs a compact multiple source x-ray tube to produce a tomosynthesis image from a set of projections obtained at a single tube position. The electron sources within the tube are realized using cold cathode carbon nanotube technology. The primary intended application is tomosynthesis-based 3D image guidance during external beam radiation therapy. The tube, which is attached to the gantry of a medical linear accelerator (linac) immediately below the multileaf collimator, operates within the voltage range of 80-160 kVp and contains a total of 52 sources that are arranged in a rectilinear array. This configuration allows for the acquisition of tomographic projections from multiple angles without any need to rotate the linac gantry. The x-ray images are captured by the same amorphous silicon flat panel detector employed for portal imaging on contemporary linacs. The field of view (FOV) of the system corresponds to that part of the volume that is sampled by rays from all sources. The present tube and detector configuration provides an 8 x 8 cm2 FOV in the plane of the linac isocenter when the 40.96 x 40.96 cm2 imaging detector is placed 40 cm from the isocenter. Since this tomosynthesis application utilizes the extremities of the detector to record image detail relating to structures near the isocenter, simultaneous treatment and imaging is possible for most clinical cases, where the treated target is a small region close to the linac isocenter. The tomosynthesis images are reconstructed using the simultaneous iterative reconstruction technique, which is accelerated using a graphic processing unit. The authors present details of the system design as well as simulated performance of the imaging system based on reprojections of patient CT images.

We describe a focused beam-stop array (BSA) for the measurement of object scatter in imaging systems that utilize x-ray beams in the megavoltage (MV) energy range. The BSA consists of 64 doubly truncated tungsten cone elements of 0.5 cm maximum diameter that are arranged in a regular array on an acrylic slab. The BSA is placed in the accessory tray of a medical linear accelerator at a distance of approximately 50 cm from the focal spot. We derive an expression that allows us to estimate the scatter in an image taken without the array present, given image values in a second image with the array in place. The presence of the array reduces fluence incident on the imaged object. This leads to an object-dependent underestimation bias in the scatter measurements. We apply corrections in order to address this issue. We compare estimates of the flat panel detector response to scatter obtained using the BSA to those derived from Monte Carlo simulations. We find that the two estimates agree to within 10% in terms of RMS error for 30 cm x 30 cm water slabs in the thickness range of 10-30 cm. Larger errors in the scatter estimates are encountered for thinner objects, probably owing to extrafocal radiation sources. However, RMS errors in the estimates of primary images are no more than 5% for water slab thicknesses in the range of 1-30 cm. The BSA scatter estimates are also used to correct cone beam tomographic projections. Maximum deviations of central profiles of uniform water phantoms are reduced from 193 to 19 HU after application of corrections for scatter, beam hardening, and lateral truncation that are based on the BSA-derived scatter estimate. The same corrections remove the typical cupping artifact from both phantom and patient images. The BSA proves to be a useful tool for quantifying and removing image scatter, as well as for validating models of MV imaging systems.

Purpose: Commercial intensity‐modulated‐arc‐therapy (IMAT) implementations rely on a 100% beam‐on duty‐cycle to achieve high efficiency. With moving targets, real‐time tracking or gating may be applied. Tracking is technically challenging and gating reduces efficiency by lowering the duty‐cycle. By combining burst‐mode rIMRT (in which all dose is administered while the gantry is within a few degrees of a beam optimization point [OP]), with a motion pre‐emption strategy and intrafractional imaging, we demonstrate an efficient implementation of motion‐adaptive rIMRT. Methods: 1. An rIMRT plan is created with 36–72 OPs. A gantry rotating at 6 degrees/s takes 3–6s to reach successive OPs. This co‐incides with the natural breathing period. 2. A Fourier‐descriptor‐based trajectory model is fitted to target features identified in pre‐treatment CBCT projections. The model predicts feature location at any combination of gantry angle and breathing phase. 3. The model sets the gantry speed to place the gantry at the next beam OP just in time as the target arrives at the planned position. In‐line projection images are acquired immediately before and during beam delivery. Treatment ensues only if the target position is correct (verification completes within 50ms, so maximum misdelivery possible at 2000MU/min is within 2MU). In cases of irregular breathing, the system gracefully defaults to gated‐IMRT. Results: For a MA‐rIMRT delivery of 750MU at 2000MU/min, treatment duration increases from 154s (regular rIMRT) to 199s (5s respiration cycle). Conclusions: With predictable patient breathing, MA‐rIMRT delivery times are competitive with conventional IMAT. High treatment accuracy is easily achieved, since there is no tracking lag and since the beam shape is static during delivery. Contemporary linacs rely on non‐realtime communication systems (typically Ethernet) to control time‐critical elements such as the MLC. Since such variable‐delay systems pose formidable problems in terms of predictive control, our approach offers a pragmatic alternative to tracking. Siemens Medical Solutions USA

Purpose: We present a novel image acquisition and reconstruction scheme for dramatically increasing the field‐of‐view (FOV) in cone beam computed tomography(CBCT) using a standard centered detector. The method enables CBCT datasets to be employed as a basis for treatment planning, since the entire extent of even very large patients can be imaged in a quantitative sense. Applications include planning for emergency cases based on CBCTimages, and at Third World facilities that lack multislice‐CT systems using megavoltage‐CBCT. Methods and Materials: The projection acquisition scheme proceeds as follows: 1) The patient couch is offset (in height and lateral position) from its intended position ( x 0) at the start of treatment by a distance related to the amount of additional FOV required. 2) Projections are acquired over a limited arc. 3) The couch is offset from x 0 by the same distance as in (1), but in the opposite direction 4) Projections are acquired over a second arc. Projections are corrected for scatter, beam‐hardening and non‐uniform beam profile, and then simultaneously reconstructed using an iterative algorithm. Evaluation: We image a pelvic anthropomorphic phantom using a Siemens ONCOR linac equipped with an amorphous‐silicon detector. Dose calculation is then performed on the resulting extended FOV megavoltage‐CBCT and a multislice‐CT of the same phantom. Results: The full cross section of the phantom is reconstructed with only minor artifacts. The dose study shows almost identical dose distributions for the reference and EFOV dataset: the central percentage depth‐dose profiles for a 10×10 cm2 field exhibits a maximum deviation of 0.8%, illustrating the insignificance of the artifacts from a dosimetric perspective. Conclusion: The method increases the FOV of an ONCOR linac by 67% to 45 cm. This exceeds the capabilities of current extended FOV implementations that are based on offset‐detector systems. The reconstructed volumes appear suitable for planning purposes.

We present the design and simulation of an imaging system that employs a compact multiple source x-ray tube to produce a tomosynthesis image from a set of projections obtained at a single tube position. The electron sources within the tube are realized using cold cathode carbon nanotube technology. The primary intended application is tomosynthesis-based 3D image guidance during external beam radiation therapy. The tube, which is attached to the gantry of a medical linear accelerator (linac) immediately below the multileaf collimator, operates within the voltage range of 80-160 kVp and contains a total of 52 sources that are arranged in a rectilinear array. This configuration allows for the acquisition of tomographic projections from multiple angles without any need to rotate the linac gantry. The x-ray images are captured by the same amorphous silicon flat panel detector employed for portal imaging on contemportary linacs. The field-of-view (FOV) of the system corresponds to that part of the volume that is sampled by rays from all sources. The present tube and detector configuration provides an 8 cm×8 cm FOV in the plane of the linac isocenter when the 40.96 cm×40.96 cm imaging detector is placed 40 cm from the isocenter. Since this tomosynthesis application utilizes the extremities of the detector to record image detail relating to structures near the isocenter, simultaneous treatment and imaging is possible for most clinical cases, where the treated target is a small region close to the linac isocenter. The tomosynthesis images are reconstructed using the simultaneous iterative reconstruction technique (SART), which is accelerated using a graphics processing unit (GPU). We present details of the system design as well as simulated performance of the imaging system based on reprojections of patient CT images.

We describe the fabrication and evaluation of a thick pixelated scintillator for megavoltage (MV) imaging composed of a ceramic containing over 99.9% gadolium oxysulfide. This sintered material offers a 59% increase in density over the Lanex Fast B (LFB) phosphor screens most commonly employed in MV imaging. The sintered pixelated array (SPA) is fabricated from a single slab of ceramic. This obviates the need to assemble over a million separate crystals in order to cover a 40.96cm × 40.96cm detector area. As a consequence, the design is amenable to fabrication using methods of mass production. Method and Materials: A 1.8mm‐thick 274 × 250 pixel SPA with 0.4mm pixel pitch is attached to the light‐sensitive surface of an amorphous silicon flat panel detector (Perkin Elmer XRD1640AN). Image quality is characterized using 1MU exposures of the 6MV beam of a Siemens Primus Linac. A QC‐3V phantom is employed to calculate the modulation transfer function(MTF) and contrast‐to‐noise ratio (CNR). The detective quantum efficiency (DQE) is computed. A LFB screen is then evaluated under identical conditions for comparative purposes. Cone beam CT(CBCT)imaging is performed with four arrays tiled side‐by‐side on the detector surface. Results: The half‐maximum value of MTF occurs at 0.32 and 0.34lp/mm for the SPA and LFB, respectively. The DQE(0.1lp/mm) of SPA is 5.8%, versus 1.0% for LFB. The SPA offers a 235% improvement in CNR over LFB. Previously undetectable low‐contrast phantom inserts are clearly visible in SPA MV‐CBCT images.Conclusions: The SPA appears to offer a practical and cost‐effective means of attaining major improvements in MV image quality. The measured MTF and DQE values underestimate the achievable performance, since the SPA and detector photodiode arrays were imperfectly aligned during these evaluations. A DQE(0) value closer to the maximum attainable 7.8% is expected. Conflict of Interest: Sponsored by Siemens.

Purpose: The iterative metal artifact reduction (IMAR) algorithm has been proposed for commercial implementation in upcoming Siemens platforms. The purpose of this study is to evaluate the performance of this algorithm in radiation oncology settings. Methods: Mean CT numbers and noise (standard‐deviation) within delineated regions of interest were compared before/after IMAR correction on standard electron‐density phantom images. Patient IMAR‐corrected images were evaluated by 4 observers and ranked based on conspicuity of structures near artifacts (0–5 scale, 5 best score). The dosimetric impact of utilizing IMAR‐corrected patient images for planning was analyzed by comparing original dose distributions and those recalculated on IMAR‐corrected images. All images were acquired on a Siemens Definition scanner. In order to reference the observations herein, all analyses were also conducted on images corrected with a second algorithm: metal deletion technique (MDT), available for public use. Results: IMAR accurately recovers CT numbers. CT number percent differences were reduced on average from 62% to 18%, while average noise percent differences were minimally reduced (146% before, 140% after). MDT performed worse retrieving mean CT numbers (62% to 27%), and better at reducing noise (146% to 24%). After visually inspecting the images, physicians agreed that IMAR‐corrected images offered better confidence at reading patient anatomy than original images. The MDT‐corrected images scored 4.3 on average while IMAR‐corrected images scored 4 with reviewing physicians (p = 0.052). Local dose differences up to ±20–30cGy were noted, but γ‐analysis (3%/3mm) did not indicate major overall differences between plans calculated on original images and those calculated on IMAR‐corrected images. Conclusion: The IMAR algorithm accurately recovered CT numbers (better than MDT), while minimally reducing noise values (worse than MDT). No clinically significant differences were detected between dose distributions calculated on original CT images and those planned on IMAR‐corrected images. Initial analysis indicates that IMAR images could be used for treatment planning. Siemens Healthcare

Purpose: To describe and evaluate a calibration procedure to compute the imaging geometry parameters (IGPs) of a stationary multiple source digital tomosynthesis (DTS) system mounted on a medicallinear accelerator(linac) equipped with a cone beam CT(CBCT)imaging system. DTS reconstructed image quality depends on the precise computation of IGPs. The novelty of the proposed method is that it employs the same calibration phantom used for calibrating the CBCTimaging system. This offers two major advantages as opposed to using different phantoms: 1) It ensures both the imaging systems (CBCT and DTS) reference a common machine isocenter. This is of critical importance for 3D image guidance during radiation therapy. 2) It ensures a seamless workflow while calibrating the medicallinac. Owing to the unconventional nature of source‐detector configuration employed by the DTS system, the DTS projections of a conventional helical bead geometry calibration phantom are characterized by bead occlusion, distortion and missing information. Therefore calibrating the multiple source DTS system with the standard CBCTcalibration phantom is a non‐trivial task Materials and methods: Projections of the calibration phantom, which contains radio‐opaque tungsten beads, are obtained using each of the individual x‐ray sources. An ideal model of the projection geometry is used to obtain reference projection images of the calibration phantom for each of the x‐ray sources. IGPs are perturbed using an optimization scheme in order to minimize the difference between acquired projection images and the model. Results: The algorithm is able to detect changes in the source and detector positions with accuracy of approximately 0.3 mm. Considerable improvements are seen in the reconstructed image quality as a result of using precise IGPs in the reconstruction algorithm. Conclusion: We have demonstrated a robust method of performing geometry calibration for both regular and irregular source geometries. Research sponsored by Siemens Healthcare

Purpose: Quantitative cone beam CT(CBCT) is essential for advanced radiation oncology (RO) applications such as portal image‐based 3D dose reconstruction. Quantitative CT requires accurate modeling of scatter, beam‐hardening and detector response. Scatter correction methods are typically semi‐empirical in nature and are designed to reduce visible artifacts while incurring low computational cost. In contrast, Monte Carlo(MC) methods are accurate but impractically slow. Convolution‐superposition (CS) scatter models offer a good balance between accuracy and computational complexity. We show how CS can be employed to implement a unified correction method that enables quantitative kV and MV imaging.Method and Materials: (1) We perform detailed MC modeling of the kV and MV cone beam imaging systems. (2) Using MC, we generate calibration data that map intensities recorded on the flat panel imagers to water‐equivalent thicknesses (WETs). (3) The MC models are used to generate pencil beam kernels for water cylinders of varying thickness. (4) Scattergrams are generated from acquired projection images via the CS method using these kernels indexed by the WET at each pixel. (5) Scattergrams are iteratively refined using a multiplicative correction formula that ensures that the estimated primary image remains non‐negative even when scatter‐to‐primary ratios are very high. (6) The FDK reconstruction algorithm is applied directly to the thickness maps corresponding to the estimated primary images.Results: The algorithm is able to reduce maximum non‐uniformity in the reconstruction of a 16cm cylindrical homogeneous tissue equivalent phantom from 11.7% to 1.5%. When applied to a challenging 35cm × 22.5cm oblong water phantom, a non‐uniformity reduction in from 36% to 2.5% is achieved. A dataset of 200 1024×1024 projections can be processed in 25 seconds. Conclusions: CS methods can be used at both kV and MV energies to enable reconstruction of quantitative CBCTimages.Conflict of Interest: Supported by Siemens.