Registration of clinical volumes to beams-eye-view images for real-time tracking

Super-resolution reconstruction of time-resolved four-dimensional computed tomography (TR-4DCT) with multiple breathing cycles based on TR-4DMRI

BACKGROUND

Respiratory motion irregularities in lung cancer patients are common and can be severe during multi-fractional (∼20 mins/fraction) radiotherapy. However, the current clinical standard of motion management is to use a single-breath respiratory-correlated four-dimension computed tomography (RC-4DCT or 4DCT) to estimate tumor motion to delineate the internal tumor volume (ITV), covering the trajectory of tumor motion, as a treatment target.

PURPOSE

To develop a novel multi-breath time-resolved (TR) 4DCT using the super-resolution reconstruction framework with TR 4D magnetic resonance imaging (TR-4DMRI) as guidance for patient-specific breathing irregularity assessment, overcoming the shortcomings of RC-4DCT, including binning artifacts and single-breath limitations.

METHODS

Six lung cancer patients participated in the IRB-approved protocol study to receive multiple T1w MRI scans, besides an RC-4DCT scan on the simulation day, including 80 low-resolution (lowR: 5 × 5 × 5 mm3) free-breathing (FB) 3D cine MRFB images in 40 s (2 Hz) and a high-resolution (highR: 2 × 2 × 2 mm3) 3D breath-hold (BH) MRBH image for each patient. A CT (1 × 1 × 3 mm3) image was selected from 10-bin RC-4DCT with minimal binning artifacts and a close diaphragm match (<1 cm) to the MRBH image. A mutual-information-based Freeform deformable image registration (DIR) was used to register the CT and MRBH via the opposite directions (namely F1:C T Source → MR Target BH ${\mathrm{C}}{{{\mathrm{T}}}_{{\mathrm{Source}}}} \to {\mathrm{MR}}_{{\mathrm{Target}}}^{{\mathrm{BH}}}$ and F2:C T Target ← MR Source BH ${\mathrm{C}}{{{\mathrm{T}}}_{{\mathrm{Target}}}} \leftarrow {\mathrm{MR}}_{{\mathrm{Source}}}^{{\mathrm{BH}}}$ ) to establish CT-MR voxel correspondences. An intensity-based enhanced Demons DIR was then applied forMR Source BH → MR Target FB ${\mathrm{MR}}_{{\mathrm{Source}}}^{{\mathrm{BH}}} \to {\mathrm{MR}}_{{\mathrm{Target}}}^{{\mathrm{FB}}}$ , in which the original MRBH was used in D1:C T Source → ( MR Source BH → MR Target FB ) Target ${\mathrm{C}}{{{\mathrm{T}}}_{{\mathrm{Source}}}} \to {{({\mathrm{MR}}_{{\mathrm{Source}}}^{{\mathrm{BH}}} \to {\mathrm{MR}}_{{\mathrm{Target}}}^{{\mathrm{FB}}})}_{{\mathrm{Target}}}}$ , while the deformed MRBH was used in D2:( C T Target ← MR Source BH ) Source → MR Target FB ${{( \text{C}{{\text{T}}_{\text{Target}}}\leftarrow \text{MR}_{\text{Source}}^{\text{BH}} )}_{\text{Source}}}\to \text{MR}_{\text{Target}}^{\text{FB}}$ . The deformation vector fields (DVFs) obtained from each DIR were composed to apply to the deformed CT (D1) and original CT (D2) to reconstruct TR-4DCT images. A digital 4D-XCAT phantom at the end of inhalation (EOI) and end of exhalation (EOE) with 2.5 cm diaphragmatic motion and three spherical targets (ϕ = 2, 3, 4 cm) were first tested to reconstruct TR-4DCT. For each of the six patients, TR-4DCT images at the EOI, middle (MID), and EOE were reconstructed with both D1 and D2 approaches. TR-4DCT image quality was evaluated with mean distance-to-agreement (MDA) at the diaphragm compared with MRFB, tumor volume ratio (TVR) referenced to MRBH, and tumor shape difference (DICE index) compared with the selected input CT. Additionally, differences in the tumor center of mass (|∆COMD1-D2|), together with TVR and DICE comparison, was assessed in the D1 and D2 reconstructed TR-4DCT images.

RESULTS

In the phantom, TR-4DCT quality is assessed by MDA = 2.0 ± 0.8 mm at the diaphragm, TVR = 0.8 ± 0.0 for all tumors, and DICE = 0.83 ± 0.01, 0.85 ± 0.02, 0.88 ± 0.01 for ϕ = 2, 3, 4 cm tumors, respectively. In six patients, the MDA in diaphragm match is -1.6 ± 3.1 mm (D1) and 1.0 ± 3.9 mm (D2) between the reconstructed TR-4DCT and lowR MRFB among 18 images (3 phases/patient). The tumor similarity is TVR = 1.2 ± 0.2 and DICE = 0.70 ± 0.07 for D1 and TVR = 1.4 ± 0.3 (D2) and DICE = 0.73 ± 0.07 for D2. The tumor position difference is |∆COMD1-D2| = 1.2 ± 0.8 mm between D1 and D2 reconstructions.

CONCLUSION

The feasibility of super-resolution reconstruction of multi-breathing-cycle TR-4DCT is demonstrated and image quality at the diaphragm and tumor is assessed in both the 4D-XCAT phantom and six lung cancer patients. The similarity of D1 and D2 reconstruction suggests consistent and reliable DIR results. Clinically, TR-4DCT has the potential for breathing irregularity assessment and dosimetry evaluation in radiotherapy.

Markerless motion tracking with simultaneous MV and kV imaging in spine SBRT treatment-a feasibility study

Objective. Motion tracking with simultaneous MV-kV imaging has distinct advantages over single kV systems. This research is a feasibility study of utilizing this technique for spine stereotactic body radiotherapy (SBRT) through phantom and patient studies.Approach. A clinical spine SBRT plan was developed using 6xFFF beams and nine sliding-window IMRT fields. The plan was delivered to a chest phantom on a linear accelerator. Simultaneous MV-kV image pairs were acquired during beam delivery. KV images were triggered at predefined intervals, and synthetic MV images showing enlarged MLC apertures were created by combining multiple raw MV frames with corrections for scattering and intensity variation. Digitally reconstructed radiograph (DRR) templates were generated using high-resolution CBCT reconstructions (isotropic voxel size (0.243 mm)3) as the reference for 2D-2D matching. 3D shifts were calculated from triangulation of kV-to-DRR and MV-to-DRR registrations. To evaluate tracking accuracy, detected shifts were compared to known phantom shifts as introduced before treatment. The patient study included a T-spine patient and an L-spine patient. Patient datasets were retrospectively analyzed to demonstrate the performance in clinical settings.Main results. The treatment plan was delivered to the phantom in five scenarios: no shift, 2 mm shift in one of the longitudinal, lateral and vertical directions, and 2 mm shift in all the three directions. The calculated 3D shifts agreed well with the actual couch shifts, and overall, the uncertainty of 3D detection is estimated to be 0.3 mm. The patient study revealed that with clinical patient image quality, the calculated 3D motion agreed with the post-treatment cone beam CT. It is feasible to automate both kV-to-DRR and MV-to-DRR registrations using a mutual information-based method, and the difference from manual registration is generally less than 0.3 mm.Significance. The MV-kV imaging-based markerless motion tracking technique was validated through a feasibility study. It is a step forward toward effective motion tracking and accurate delivery for spinal SBRT.

Feasibility of MR-guided radiotherapy using beam-eye-view 2D-cine with tumor-volume projection

PURPOSE

Current magnetic resonance imaging (MRI) guided radiotherapy (MRgRT) applies sagittal/coronal 2D-cine to monitor major tumor motions, however, the beam eye's view (BEV) with volumetric tumor projection would be the best measure for radiation beam conformality, independent of tumor through-plane motion. The goal is to assess the feasibility, accuracy, and performance of the BEV approach.

METHODS

Beam-specific BEV 2D-cine with volume-projected tumor contours were simulated to establish a 2D/3D tumor match against a tumor-motion library based on multi-breath time-resolved (TR) 4DMRI images. Two BEV-library-matching methods were developed: (1) fast screening with tumor center-of-mass (∆COM), in-plane area ratio, and DICE similarity, and finalizing with the highest DICE score and (2) DICE screening for top-3 candidates and finalizing with rigid registration. A 4D-XCAT digital phantom and 8 lung-cancer patients were used for assessment. For each patient, 3 sets of 40 s TR-4DMRI were acquired at 2 Hz and 6 representative BEV were created with the isocenter set at tumor COM in mid-respiration. One TR-4DMRI set (40 × 2 = 80-images) was used to simulate BEV 2D-cine and the other two (160-images) were used to create a library. The matching result was validated against the ground truth within the test set. Using a leave-one-out strategy, the success rate, accuracy, and speed of tumor matching were assessed for volume-projected tumors over 11520 time-points (=8patients•3sets•80images•6BEVs).

RESULTS

Volume-projected tumor contour area on the 6 BEVs varies by 60% ± 8% and [Formula: see text] (in-plane/volume-projected) varies by 82% ± 9%. The [Formula: see text] changes with tumor shape, orientation, and through-plane motion. Method-1 produces 96% matching success (ΔCOM = 0.7 ± 0.2 mm, [Formula: see text]=1.01 ± 0.02, Dice=0.92 ± 0.02) with the computational time of 15 ± 1 ms/match, while method-2 produces 94% ± 1% success (ΔCOM = 0.2 ± 0.1 mm, [Formula: see text]=1.00 ± 0.01, Dice = 0.94 ± 0.02) with 223 ± 13 ms/match.

CONCLUSION

This study has demonstrated the feasibility, accuracy, and benefits of BEV 2D-cine imaging with tumor-volume projection, allowing real-time tumor motion monitoring and beam conformality checking. Further clinical evaluation is necessary before MRgRT applications.

Characterization of Markerless Tumor Tracking Using the On-Board Imager of a Commercial Linear Accelerator Equipped With Fast-kV Switching Dual-Energy Imaging

PURPOSE

To describe and characterize fast-kV switching, dual-energy (DE) imaging implemented within the on-board imager of a commercial linear accelerator for markerless tumor tracking (MTT).

METHODS AND MATERIALS

Fast-kV switching, DE imaging provides for rapid switching between programmed tube voltages (ie, 60 and 120 kVp) from one image frame to the next. To characterize this system, the weighting factor used for logarithmic subtraction and signal difference-to-noise ratio were analyzed as a function of time and frame rate. MTT was evaluated using a thorax motion phantom and fast kV, DE imaging was compared versus single energy (SE) imaging over 360 degrees of rotation. A template-based matching algorithm was used to track target motion on both DE and SE sequences. Receiver operating characteristics were used to compare tracking results for both modalities.

RESULTS

The weighting factor was inversely related to frame rate and stable over time. After applying the frame rate-dependent weighting factor, the signal difference-to-noise ratio was consistent across all frame rates considered for simulated tumors ranging from 5 to 25 mm in diameter. An analysis of receiver operating characteristics curves showed improved tracking with DE versus SE imaging. The area under the curve for the 10-mm target ranged from 0.821 to 0.858 for SE imaging versus 0.968 to 0.974 for DE imaging. Moreover, the residual tracking errors for the same target size ranged from 2.02 to 2.18 mm versus 0.79 to 1.07 mm for SE and DE imaging, respectively.

CONCLUSIONS

Fast-kV switching, DE imaging was implemented on the on-board imager of a commercial linear accelerator. DE imaging resulted in improved MTT accuracy over SE imaging. Such an approach may have application for MTT of patients with lung cancer receiving stereotactic body radiation therapy, particularly for small tumors where MTT with SE imaging may fail.

An open-source software for monitoring intrafraction motion during external beam radiation therapy based on superimposition of contours of projected ROIs on cine-MV images

Purpose

To present an open‐source software (https://github.com/CHUSRadOncPhys/FluoMV) for monitoring intrafraction motion that is based on the visualization of superimposed contours of projected region‐of‐interests from DICOM RTSTRUCT files on cine‐MV images acquired and displayed in real‐time during radiation therapy delivery. Clinical use with prostate gold fiducial markers is presented.

Methods

Projections of regions of interest (ROI) in the reference frame of the electronic portal imaging device are computed offline for different gantry angles before the first treatment fraction. During treatment delivery, the contrast of portal images is automatically adjusted using a histogram equalization algorithm. The projections associated with the current gantry angle are then superimposed on the images in real time. This allows the therapist to evaluate if the imaged structures of interest remain within their respective contours during treatment delivery and to potentially interrupt the treatment if deemed necessary. The spatial accuracy of the method was evaluated by imaging a ball bearing phantom in a set‐up where the position of the projected ROI is highly sensitive to gantry angle errors. The visibility of fiducial markers during one fraction of seven different volumetric modulated arc therapy (VMAT) prostate treatments is characterized.

Results

The geometric validation showed a negligible systematic error μ < 0.1 mm for the position of the projections. The random errors associated with the time accuracy of the gantry angle readout were characterized by standard deviations σ ≤ 0.6 mm. The VMAT clinical treatments showed that the fiducial markers were frequently visible, allowing for a meaningful clinical use.

Conclusions

The results demonstrate that the method presented is sufficiently accurate to be used for intrafraction monitoring of patients. The fact that this method could be implemented on many modern linacs at little to no cost and with no additional dose delivered to the patients makes this solution very attractive for improving patient care and safety in radiation therapy.

A machine learning-based real-time tumor tracking system for fluoroscopic gating of lung radiotherapy

To improve respiratory-gated radiotherapy accuracy, we developed a machine learning approach for markerless tumor tracking and evaluated it using lung cancer patient data. Digitally reconstructed radiography (DRR) datasets were generated using planning 4DCT data. Tumor positions were selected on respective DRR images to place the GTV center of gravity in the center of each DRR. DRR subimages around the tumor regions were cropped so that the subimage size was defined by tumor size. Training data were then classified into two groups: positive (including tumor) and negative (not including tumor) samples. Machine learning parameters were optimized by the extremely randomized tree method. For the tracking stage, a machine learning algorithm was generated to provide a tumor likelihood map using fluoroscopic images. Prior probability tumor positions were also calculated using the previous two frames. Tumor position was then estimated by calculating maximum probability on the tumor likelihood map and prior probability tumor positions. We acquired treatment planning 4DCT images in eight patients. Digital fluoroscopic imaging systems on either side of the vertical irradiation port allowed fluoroscopic image acquisition during treatment delivery. Each fluoroscopic dataset was acquired at 15 frames per second. We evaluated the tracking accuracy and computation times. Tracking positional accuracy averaged over all patients was 1.03 ± 0.34 mm (mean ± standard deviation, Euclidean distance) and 1.76 ± 0.71 mm ([Formula: see text] percentile). Computation time was 28.66 ± 1.89 ms/frame averaged over all frames. Our markerless algorithm successfully estimated tumor position in real time.

The first prospective implementation of markerless lung target tracking in an experimental quality assurance procedure on a standard linear accelerator

The ability to track tumour motion without implanted markers on a standard linear accelerator (linac) could enable wide access to real-time adaptive radiotherapy for cancer patients. We previously have retrospectively validated a method for 3D markerless target tracking using intra-fractional kilovoltage (kV) projections acquired on a standard linac. This paper presents the first prospective implementation of markerless lung target tracking on a standard linac and its quality assurance (QA) procedure. The workflow and the algorithm developed to track the 3D target position during volumetric modulated arc therapy treatment delivery were optimised. The linac was operated in clinical QA mode, while kV projections were streamed to a dedicated computer using a frame-grabber software. The markerless target tracking accuracy and precision were measured in a lung phantom experiment under the following conditions: static localisation of seven distinct positions, dynamic localisation of five patient-measured motion traces, and dynamic localisation with treatment interruption. The QA guidelines were developed following the AAPM Task Group 147 report with the requirement that the tracking margin components, the margins required to account for tracking errors, did not exceed 5 mm in any direction. The mean tracking error ranged from 0.0 to 0.9 mm (left-right), -0.6 to  -0.1 mm (superior-inferior) and  -0.7 to 0.1 mm (anterior-posterior) over the three tests. Larger errors were found in cases with large left-right or anterior-posterior and small superior-inferior motion. The tracking margin components did not exceed 5 mm in any direction and ranged from 0.4 to 3.2 mm (left-right), 0.7 to 1.6 mm (superior-inferior) and 0.8 to 1.5 mm (anterior-posterior). This study presents the first prospective implementation of markerless lung target tracking on a standard linac and provides a QA procedure for its safe clinical implementation, potentially enabling real-time adaptive radiotherapy for a large population of lung cancer patients.

Markerless tumor tracking using fast-kV switching dual-energy fluoroscopy on a benchtop system

PURPOSE

To evaluate markerless tumor tracking (MTT) using fast-kV switching dual-energy (DE) fluoroscopy on a bench top system.

METHODS

Fast-kV switching DE fluoroscopy was implemented on a bench top which includes a turntable stand, flat panel detector, and x-ray tube. The customized generator firmware enables consecutive x-ray pulses that alternate between programmed high and low energies (e.g., 60 and 120 kVp) with a maximum frame rate of 15 Hz. In-house software was implemented to perform weighted DE subtraction of consecutive images to create an image sequence that removes bone and enhances soft tissues. The weighting factor was optimized based on gantry angle. To characterize this system, a phantom was used that simulates the chest anatomy and tumor motion in the lung. Five clinically relevant tumor sizes (5-25 mm diameter) were considered. The targets were programmed to move in the inferior-superior direction of the phantom, perpendicular to the x-ray beam, using a cos⁴ waveform to mimic respiratory motion. Target inserts were then tracked with MTT software using a template matching method. The optimal computed tomography (CT) slice thickness for template generation was also evaluated. Tracking success rate and accuracy were calculated in regions of the phantom where the target overlapped ribs vs spine, to compare the performance of single energy (SE) and DE imaging methods.

RESULTS

For the 5 mm target, a CT slice thickness of 0.75 mm resulted in the lowest tracking error. For the larger targets (≥10 mm) a CT slice thickness ≤2 mm resulted in comparable tracking errors for SE and DE images. Overall DE imaging improved MTT accuracy, relative to SE imaging, for all tumor targets in a rotational acquisition. Compared to SE, DE imaging increased tracking success rate of small target inserts (5 and 10 mm). For fast motion tracking, success rates improved from 23% to 64% and 74% to 90% for 5 and 10 mm targets inserts overlapping ribs, respectively. For slow moving targets success rates improved from 19% to 59% and 59% to 91% in 5 and 10 mm targets overlapping the ribs, respectively. Similar results were observed when the targets overlapped the spine. For larger targets (≥15 mm) tracking success rates were comparable using SE and DE imaging.

CONCLUSION

This work presents the first results of MTT using fast-kV switching DE fluoroscopy. Using DE imaging has improved the tracking accuracy of MTT, especially for small targets. The results of this study will guide the future implementation of fast-kV switching DE imaging using the on-board imager of a linear accelerator.

Technical Note: Combination of multiple EPID imager layers improves image quality and tracking performance of low contrast-to-noise objects

PURPOSE

We hypothesized that combining multiple amorphous silicon flat panel layers increases photon detection efficiency in an electronic portal imaging device (EPID), improving image quality and tracking accuracy of low-contrast targets during radiotherapy.

METHODS

The prototype imager evaluated in this study contained four individually programmable layers each with a copper converter layer, Gd₂ O₂ S scintillator, and active-matrix flat panel imager (AMFPI). The imager was placed on a Varian TrueBeam linac and a Las Vegas phantom programmed with sinusoidal motion (peak-to-peak amplitude = 20 mm, period = 3.5 s) was imaged at a frame rate of 10 Hz with one to four layers activated. Number of visible circles and CNR of least visible circle (depth = 0.5 mm, diameter = 7 mm) was computed to assess the image quality of single and multiple layers. A previously validated tracking algorithm was employed for auto-tracking. Tracking error was defined as the difference between the programmed and tracked positions of the circle. Pearson correlation coefficient (R) of CNR and tracking errors was computed.

RESULTS

Motion-induced blurring significantly reduced circle visibility. During four cycles of phantom motion, the number of visible circles varied from 11-23, 13-24, 15-25, and 16-26 for one-, two-, three-, and four-layer imagers, respectively. Compared with using only a single layer, combining two, three, and four layers increased the median CNR by factors of 1.19, 1.42, and 1.71, respectively and reduced the average tracking error from 3.32 mm to 1.67 mm to 1.47 mm, and 0.74 mm, respectively. Significant correlations (P~10^-9 ) were found between the tracking error and CNR.

CONCLUSION

Combination of four conventional EPID layers significantly improves the EPID image quality and tracking accuracy for a poorly visible object which is moving with a frequency and amplitude similar to respiratory motion.

Use of Eye Tracking as an Innovative Instructional Method in Surgical Human Anatomy

OBJECTIVE

Tobii glasses can record corneal infrared light reflection to track pupil position and to map gaze focusing in the video recording. Eye tracking has been proposed for use in training and coaching as a visually guided control interface. The aim of our study was to test the potential use of these glasses in various situations: explanations of anatomical structures on tablet-type electronic devices, explanations of anatomical models and dissected cadavers, and during the prosection thereof. An additional aim of the study was to test the use of the glasses during laparoscopies performed on Thiel-embalmed cadavers (that allows pneumoinsufflation and exact reproduction of the laparoscopic surgical technique). The device was also tried out in actual surgery (both laparoscopy and open surgery).

DESIGN

We performed a pilot study using the Tobii glasses.

SETTING

Dissection room at our School of Medicine and in the operating room at our Hospital.

PARTICIPANTS

To evaluate usefulness, a survey was designed for use among students, instructors, and practicing physicians.

RESULTS

The results were satisfactory, with the usefulness of this tool supported by more than 80% positive responses to most questions. There was no inconvenience for surgeons and that patient safety was ensured in the real laparoscopy.

CONCLUSION

To our knowledge, this is the first publication to demonstrate the usefulness of eye tracking in practical instruction of human anatomy, as well as in teaching clinical anatomy and surgical techniques in the dissection and operating rooms.

A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy

The ability to monitor tumor motion without implanted markers can potentially enable broad access to more accurate and precise lung radiotherapy. A major challenge is that kilovoltage (kV) imaging based methods are rarely able to continuously track the tumor due to the inferior tumor visibility on 2D kV images. Another challenge is the estimation of 3D tumor position based on only 2D imaging information. The aim of this work is to address both challenges by proposing a Bayesian approach for markerless tumor tracking for the first time. The proposed approach adopts the framework of the extended Kalman filter, which combines a prediction and measurement steps to make the optimal tumor position update. For each imaging frame, the tumor position is first predicted by a respiratory-correlated model. The 2D tumor position on the kV image is then measured by template matching. Finally, the prediction and 2D measurement are combined based on the 3D distribution of tumor positions in the past 10 s and the estimated uncertainty of template matching. To investigate the clinical feasibility of the proposed method, a total of 13 lung cancer patient datasets were used for retrospective validation, including 11 cone-beam CT scan pairs and two stereotactic ablative body radiotherapy cases. The ground truths for tumor motion were generated from the the 3D trajectories of implanted markers or beacons. The mean, standard deviation, and 95th percentile of the 3D tracking error were found to range from 1.6-2.9 mm, 0.6-1.5 mm, and 2.6-5.8 mm, respectively. Markerless tumor tracking always resulted in smaller errors compared to the standard of care. The improvement was the most pronounced in the superior-inferior (SI) direction, with up to 9.5 mm reduction in the 95th-percentile SI error for patients with  >10 mm 5th-to-95th percentile SI tumor motion. The percentage of errors with 3D magnitude  <5 mm was 96.5% for markerless tumor tracking and 84.1% for the standard of care. The feasibility of 3D markerless tumor tracking has been demonstrated on realistic clinical scenarios for the first time. The clinical implementation of the proposed method will enable more accurate and precise lung radiotherapy using existing hardware and workflow. Future work is focused on the clinical and real-time implementation of this method.

Super-resolution imaging in a multiple layer EPID

A new portal imager consisting of four vertically stacked conventional electronic portal imaging device (EPID) layers has been constructed in pursuit of improved detective quantum efficiency (DQE). We hypothesize that super-resolution (SR) imaging can also be achieved in such a system by shifting each layer laterally by half a pixel relative to the layer above. Super-resolution imaging will improve resolution and contrast-to-noise ratio (CNR) in megavoltage (MV) planar and cone beam computed tomography (MV-CBCT) applications. Simulations are carried out to test this hypothesis with digital phantoms. To assess planar resolution, 2 mm long iron rods with 0.3 × 0.3 mm² square cross-section are arranged in a grid pattern at the center of a 1 cm thick solid water. For measuring CNR in MV-CBCT, a 20 cm diameter digital phantom with 8 inserts of different electron densities is used. For measuring resolution in MV-CBCT, a digital phantom featuring a bar pattern similar to the Gammex™ phantom is used. A 6 MV beam is attenuated through each phantom and detected by each of the four detector layers. Fill factor of the detector is explicitly considered. Projections are blurred with an estimated point spread function (PSF) before super-resolution reconstruction. When projections from multiple shifted layers are used in SR reconstruction, even a simple shift-add fusion can significantly improve the resolution in reconstructed images. In the reconstructed planar image, the grid pattern becomes visually clearer. In MV-CBCT, combining projections from multiple layers results in increased CNR and resolution. The inclusion of two, three and four layers increases CNR by 40%, 70% and 99%, respectively. Shifting adjacent layers by half a pixel almost doubles resolution. In comparison, using four perfectly aligned layers does not improve resolution relative to a single layer.

Beam's-eye-view imaging during non-coplanar lung SBRT

PURPOSE

Beam's-eye-view (BEV) imaging with an electronic portal imaging device (EPID) can be performed during lung stereotactic body radiation therapy (SBRT) to monitor the tumor location in real-time. Image quality for each patient and treatment field depends on several factors including the patient anatomy and the gantry and couch angles. The authors investigated the angular dependence of automatic tumor localization during non-coplanar lung SBRT delivery.

METHODS

All images were acquired at a frame rate of 12 Hz with an amorphous silicon EPID. A previously validated markerless lung tumor localization algorithm was employed with manual localization as the reference. From ten SBRT patients, 12 987 image frames of 123 image sequences acquired at 48 different gantry-couch rotations were analyzed. δ was defined by the position difference of the automatic and manual localization.

RESULTS

Regardless of the couch angle, the best tracking performance was found in image sequences with a gantry angle within 20° of 250° (δ = 1.40 mm). Image sequences acquired with gantry angles of 150°, 210°, and 350° also led to good tracking performances with δ = 1.77-2.00 mm. Overall, the couch angle was not correlated with the tracking results. Among all the gantry-couch combinations, image sequences acquired at (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) led to the best tracking results with δ = 1.19-1.82 mm. The worst performing combinations were (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) with δ > 3.5 mm. However, 35% (17/48) of the gantry-couch rotations demonstrated substantial variability in tracking performances between patients. For example, the field angle (θ = 70°, ϕ = 10°) was acquired for five patients. While the tracking errors were ≤1.98 mm for three patients, poor performance was found for the other two patients with δ ≥ 2.18 mm, leading to average tracking error of 2.70 mm. Only one image sequence was acquired for all other gantry-couch rotations (δ = 1.18-10.29 mm).

CONCLUSIONS

Non-coplanar beams with gantry-couch rotation of (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) have the highest accuracy for BEV lung tumor localization. Additionally, gantry angles of 150°, 210°, 250°, and 350° also offer good tracking performance. The beam geometries (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) are associated with substantial automatic localization errors. Overall, lung tumor visibility and tracking performance were patient dependent for a substantial number of the gantry-couch angle combinations studied.

Tracking tumor boundary in MV-EPID images without implanted markers: A feasibility study

PURPOSE

To develop a markerless tracking algorithm to track the tumor boundary in megavoltage (MV)-electronic portal imaging device (EPID) images for image-guided radiation therapy.

METHODS

A level set method (LSM)-based algorithm is developed to track tumor boundary in EPID image sequences. Given an EPID image sequence, an initial curve is manually specified in the first frame. Driven by a region-scalable energy fitting function, the initial curve automatically evolves toward the tumor boundary and stops on the desired boundary while the energy function reaches its minimum. For the subsequent frames, the tracking algorithm updates the initial curve by using the tracking result in the previous frame and reuses the LSM to detect the tumor boundary in the subsequent frame so that the tracking processing can be continued without user intervention. The tracking algorithm is tested on three image datasets, including a 4-D phantom EPID image sequence, four digitally deformable phantom image sequences with different noise levels, and four clinical EPID image sequences acquired in lung cancer treatment. The tracking accuracy is evaluated based on two metrics: centroid localization error (CLE) and volume overlap index (VOI) between the tracking result and the ground truth.

RESULTS

For the 4-D phantom image sequence, the CLE is 0.23 ± 0.20 mm, and VOI is 95.6% ± 0.2%. For the digital phantom image sequences, the total CLE and VOI are 0.11 ± 0.08 mm and 96.7% ± 0.7%, respectively. In addition, for the clinical EPID image sequences, the proposed algorithm achieves 0.32 ± 0.77 mm in the CLE and 72.1% ± 5.5% in the VOI. These results demonstrate the effectiveness of the authors' proposed method both in tumor localization and boundary tracking in EPID images. In addition, compared with two existing tracking algorithms, the proposed method achieves a higher accuracy in tumor localization.

CONCLUSIONS

In this paper, the authors presented a feasibility study of tracking tumor boundary in EPID images by using a LSM-based algorithm. Experimental results conducted on phantom and clinical EPID images demonstrated the effectiveness of the tracking algorithm for visible tumor target. Compared with previous tracking methods, the authors' algorithm has the potential to improve the tracking accuracy in radiation therapy. In addition, real-time tumor boundary information within the irradiation field will be potentially useful for further applications, such as adaptive beam delivery, dose evaluation.

Portal imaging: Performance improvement in noise reduction by means of wavelet processing

This paper discusses the suitability, in terms of noise reduction, of various methods which can be applied to an image type often used in radiation therapy: the portal image. Among these methods, the analysis focuses on those operating in the wavelet domain. Wavelet-based methods tested on natural images--such as the thresholding of the wavelet coefficients, the minimization of the Stein unbiased risk estimator on a linear expansion of thresholds (SURE-LET), and the Bayes least-squares method using as a prior a Gaussian scale mixture (BLS-GSM method)--are compared with other methods that operate on the image domain--an adaptive Wiener filter and a nonlocal mean filter (NLM). For the assessment of the performance, the peak signal-to-noise ratio (PSNR), the structural similarity index (SSIM), the Pearson correlation coefficient, and the Spearman rank correlation (ρ) coefficient are used. The performance of the wavelet filters and the NLM method are similar, but wavelet filters outperform the Wiener filter in terms of portal image denoising. It is shown how BLS-GSM and NLM filters produce the smoothest image, while keeping soft-tissue and bone contrast. As for the computational cost, filters using a decimated wavelet transform (decimated thresholding and SURE-LET) turn out to be the most efficient, with calculation times around 1 s.

Markerless tumor tracking using short kilovoltage imaging arcs for lung image-guided radiotherapy

The ability to monitor tumor motion without implanted markers is clinically advantageous for lung image-guided radiotherapy (IGRT). Existing markerless tracking methods often suffer from overlapping structures and low visibility of tumors on kV projection images. We introduce the short arc tumor tracking (SATT) method to overcome these issues. The proposed method utilizes multiple kV projection images selected from a nine-degree imaging arc to improve tumor localization, and respiratory-correlated 4D cone-beam CT (CBCT) prior knowledge to minimize the effects of overlapping anatomies. The 3D tumor position is solved as an optimization problem with prior knowledge incorporated via regularization. We retrospectively validated SATT on 11 clinical scans from four patients with central tumors. These patients represent challenging scenarios for markerless tumor tracking due to the inferior adjacent contrast. The 3D trajectories of implanted fiducial markers were used as the ground truth for tracking accuracy evaluation. In all cases, the tumors were successfully tracked at all gantry angles. Compared to standard pre-treatment CBCT guidance alone, trajectory errors were significantly smaller with tracking in all cases, and the improvements were the most prominent in the superior-inferior direction. The mean 3D tracking error ranged from 2.2-9.9 mm, which was 0.4-2.6 mm smaller compared to pre-treatment CBCT. In conclusion, we were able to directly track tumors with inferior visibility on kV projection images using SATT. Tumor localization accuracies are significantly better with tracking compared to the current standard of care of lung IGRT. Future work involves the prospective evaluation and clinical implementation of SATT.

A Feasibility Study of Tumor Motion Estimate With Regional Deformable Registration Method for 4-Dimensional Radiation Therapy of Lung Cancer

This study aims to employ 4-dimensional computed tomography to quantify intrafractional tumor motion for patients with lung cancer to improve target localization in radiation therapy. A multistage regional deformable registration was implemented to calculate the excursion of gross tumor volume (GTV) during a breathing cycle. GTV was initially delineated on 0% phase of 4-dimensional computed tomography manually, and a subregion with 20 mm margin supplemented to GTV was generated with Eclipse treatment planning system (Varian Medical Systems, Palo Alto, California). The structures, together with the 4-dimensional computed tomography set, were exported into an in-house software, with which a 3-stage B-spline deformable registration was carried out to map the subregion and warp GTV contour to other breathing phases. The center of mass of the GTV was computed using the contours, and the tumor motion was appraised as the excursion of the center of mass between 0% phase and other phases. Application of the algorithm to the 10 patients showed that clinically satisfactory outcomes were achievable with a spatial accuracy around 2 mm for GTV contour propagation between adjacent phases and 3 mm between opposite phases. The tumor excursion was determined in the vast range of 1 mm through 1.6 cm, depending on the tumor location and tumor size. Compared to the traditional whole image-based registration, the regional method was found computationally a factor of 5 more efficient. The proposed technique has demonstrated its capability in extracting thoracic tumor motion and should find its application in 4-dimensional radiation therapy in the future to maximally utilize the available spatial-temporal information.