CBCT Reconstruction Using Single X-Ray Projection With Cycle-Domain Geometry-Integrated Denoising Diffusion Probabilistic Models.

This study assesses whether variations to cone-beam computed tomography (CBCT) slice thickness (ST) effect the detection accuracy and volume assessment of periapical lesions. Forty periapical lesions were assessed on CBCT reconstructions with 0.125-mm, 0.25-mm, 0.50-mm, 1.00-mm, 1.50-mm, and 2.00-mm ST. Mimics Research was used to perform the semi-automatic segmentation technique to determine periapical lesion volume and CBCT periapical volume index (CBCTPAVI) score on each CBCT reconstruction. Diagnostic accuracy was assessed by determining the percentage of lesions detected on each reconstruction, and the Friedman test was conducted to assess for significant differences in lesion volume between the different CBCT reconstructions. Differences among CBCTPAVI scores were also assessed. Periapical lesion volume was significantly underestimated on CBCT reconstructions with ST above 1.00 mm. Variations in periapical lesion volume were the greatest among smaller lesions resulting in false negative diagnoses with the utilization of CBCTs with ST above 0.50 mm. Variations in CBCT ST can significantly influence measured periapical lesion volume, and failure to account for this may lead to misinterpretation of lesion progression or healing. A minimum ST of 0.50 mm was required for the reliable detection of all periapical lesions, and this threshold serves as a benchmark for optimizing CBCT acquisition protocols to preserve diagnostic accuracy while minimizing radiation exposure.

The cone beam computed tomography (CBCT) guided small animal radiation research platform (SARRP) has been developed for focal tumor irradiation, allowing laboratory researchers to test basic biological hypotheses that can modify radiotherapy outcomes in ways that were not feasible previously. CBCT provides excellent bone to soft tissue contrast, but is incapable of differentiating tumors from surrounding soft tissue. Bioluminescence tomography (BLT), in contrast, allows direct visualization of even subpalpable tumors and quantitative evaluation of tumor response. Integration of BLT with CBCT offers complementary image information, with CBCT delineating anatomic structures and BLT differentiating luminescent tumors. This study is to develop a systematic method to calibrate an integrated CBCT and BLT imaging system which can be adopted onboard the SARRP to guide focal tumor irradiation. The integrated imaging system consists of CBCT, diffuse optical tomography (DOT), and BLT. The anatomy acquired from CBCT and optical properties acquired from DOT serve as a priori information for the subsequent BLT reconstruction. Phantoms were designed and procedures were developed to calibrate the CBCT, DOT/BLT, and the entire integrated system. Geometrical calibration was performed to calibrate the CBCT system. Flat field correction was performed to correct the nonuniform response of the optical imaging system. Absolute emittance calibration was performed to convert the camera readout to the emittance at the phantom or animal surface, which enabled the direct reconstruction of the bioluminescence source strength. Phantom and mouse imaging were performed to validate the calibration. All calibration procedures were successfully performed. Both CBCT of a thin wire and a euthanized mouse revealed no spatial artifact, validating the accuracy of the CBCT calibration. The absolute emittance calibration was validated with a 650 nm laser source, resulting in a 3.0% difference between simulated and measured signal. The calibration of the entire system was confirmed through the CBCT and BLT reconstruction of a bioluminescence source placed inside a tissue-simulating optical phantom. Using a spatial region constraint, the source position was reconstructed with less than 1 mm error and the source strength reconstructed with less than 24% error. A practical and systematic method has been developed to calibrate an integrated x-ray and optical tomography imaging system, including the respective CBCT and optical tomography system calibration and the geometrical calibration of the entire system. The method can be modified and adopted to calibrate CBCT and optical tomography systems that are operated independently or hybrid x-ray and optical tomography imaging systems.

Cone‐beam CT (CBCT) has been widely used in image guided radiation therapy (IGRT) to acquire updated volumetric anatomical information before treatment fractions for accurate patient alignment purpose. However the excessive x‐ray imaging doses (a few cGy per scan) delivered to patients from serial CBCT scans raise a clinical concern in most IGRT procedures. This fact has greatly limited exploitation of IGRT's maximal potential. The imaging dose can be effectively reduced by reducing the number of x‐ray projections and/or lowering mAs levels in a CBCT scan. The image quality reconstructed from conventional FDK‐type algorithms however will be highly degraded. Recently total variation (TV) method has demonstrated its ability to reconstruct CBCT images from a few number of noisy x‐ray projections. Nonetheless such a method can hardly be applied in real clinical environments due to its long computational time (a few hours). It is highly desirable to develop a fast reconstruction scheme to obtain high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose.Utilizing GPU to speed up the computationally intensive tasks in CBCT reconstruction problems has drawn a lot of attention recently. In this talk GPU‐based CBCT reconstruction algorithms will be reviewed with an emphasis on an iterative CBCT reconstruction algorithm via TV regularization. We have recently developed a GPU‐friendly version of the forward‐backward splitting algorithm to solve the TV‐based reconstruction problem. Multi‐grid technique is also employed. It is found that 40 x‐ray projections are sufficient to reconstruct CBCT images with satisfactory quality for IGRT patient alignment purpose. Phantom studies indicate that CBCT images can be successfully reconstructed with our algorithm under as low as 0.1 mAs/projection level. Comparing with currently widely used full‐fan head‐and‐neck scanning protocol of about 360 projections with 0.4 mAs/projection it is estimated that an overall 36 times dose reduction has been achieved. Moreover the reconstruction time is about 130 sec on an NVIDIA Tesla C1060 GPU card which is estimated ∼100 times faster than similar iterative reconstruction approaches. The high computational efficiency and satisfactory image quality make the iterative low dose CBCT reconstruction approach feasible in real clinical environments.Learning Objectives:1. Understand basic concepts of GPU‐based CBCT reconstruction.2. Understand main challenges in GPU‐based iterative CBCT reconstruction approach and how an iterative CBCT reconstruction problem is solved on GPU.Conflict of Interest: The research presented here is partially supported by NVIDIA.

On-line cone-beam computed tomography (CBCT) may be used to reconstruct the dose for geometric changes of patients and tumors during radiotherapy course. This study is to establish a practical method to modify the CBCT for accurate dose calculation in head and neck cancer. Fan-beam CT (FBCT) and Elekta's CBCT were used to acquire images. The CT numbers for different materials on CBCT were mathematically modified to match them with FBCT. Three phantoms were scanned by FBCT and CBCT for image uniformity, spatial resolution, and CT numbers, and to compare the dose distribution from orthogonal beams. A Rando phantom was scanned and planned with intensity-modulated radiation therapy (IMRT). Finally, two nasopharyngeal cancer patients treated with IMRT had their CBCT image sets calculated for dose comparison. With 360° acquisition of CBCT and high-resolution reconstruction, the uniformity of CT number distribution was improved and the otherwise large variations for background and high-density materials were reduced significantly. The dose difference between FBCT and CBCT was < 2% in phantoms. In the Rando phantom and the patients, the dose-volume histograms were similar. The corresponding isodose curves covering ≥ 90% of prescribed dose on FBCT and CBCT were close to each other (within 2 mm). Most dosimetric differences were from the setup errors related to the interval changes in body shape and tumor response. The specific CBCT acquisition, reconstruction, and CT number modification can generate accurate dose calculation for the potential use in adaptive radiotherapy.

Cone beam CT (CBCT) with planning software is used in intra-arterial liver-directed therapies. Software accuracy relies on high CBCT image quality, which can be impaired by breathing motion. We assessed the impact of a specific MCT on software performance for procedure planning and navigation. Institutional Review Board (IRB)-approved retrospective evaluation of liver-directed therapies from July 2015 to April 2018 was performed. CBCTs with at least one well-defined tumor and noticeable breathing motion were included. Each CBCT was reconstructed with and without breathing MCT (Motion Freeze, GE Healthcare). Automatic tumor-supplying vessel detection was performed on up to 4 tumors in each CBCT reconstruction (Liver ASSIST V.I., GE Healthcare). Vessel detection sensitivity and positive predictive value (PPV) were measured with and without MCT using Digital Subtracted Angiography (DSA) as reference. Preprocedural contrast-enhanced CT was also utilized in some cases to rule out the possibility of extrahepatic supplying vessels. MCT was applied retrospectively to 18 CBCTs with a total of 30 tumors. At least one supplying vessel was detected for 28/30 (93%) tumors with MCT versus 20/30 (66%) without. On the subgroup of 10 CBCTs (22 tumors, 76 feeders) in which the automatic vessel detection initially worked in both reconstructions, the average sensitivity and PPV increased from 63% (48/76) and 57% (48/84) before MCT to 83% (63/76) and 79% (63/80) after (p = 0.002 and p < 0.001). Breathing MCT improves planning software performance in CBCT impaired by breathing motion.

Sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization.

Objective. Dynamic cone-beam computed tomography (CBCT) can capture high-spatial-resolution, time-varying images for motion monitoring, patient setup, and adaptive planning of radiotherapy. However, dynamic CBCT reconstruction is an extremely ill-posed spatiotemporal inverse problem, as each CBCT volume in the dynamic sequence is only captured by one or a few x-ray projections, due to the slow gantry rotation speed and the fast anatomical motion (e.g. breathing). Approach. We developed a machine learning-based technique, prior-model-free spatiotemporal implicit neural representation (PMF-STINR), to reconstruct dynamic CBCTs from sequentially acquired x-ray projections. PMF-STINR employs a joint image reconstruction and registration approach to address the under-sampling challenge, enabling dynamic CBCT reconstruction from singular x-ray projections. Specifically, PMF-STINR uses spatial implicit neural representations to reconstruct a reference CBCT volume, and it applies temporal INR to represent the intra-scan dynamic motion of the reference CBCT to yield dynamic CBCTs. PMF-STINR couples the temporal INR with a learning-based B-spline motion model to capture time-varying deformable motion during the reconstruction. Compared with the previous methods, the spatial INR, the temporal INR, and the B-spline model of PMF-STINR are all learned on the fly during reconstruction in a one-shot fashion, without using any patient-specific prior knowledge or motion sorting/binning. Main results. PMF-STINR was evaluated via digital phantom simulations, physical phantom measurements, and a multi-institutional patient dataset featuring various imaging protocols (half-fan/full-fan, full sampling/sparse sampling, different energy and mAs settings, etc). The results showed that the one-shot learning-based PMF-STINR can accurately and robustly reconstruct dynamic CBCTs and capture highly irregular motion with high temporal (∼ 0.1 s) resolution and sub-millimeter accuracy. Significance. PMF-STINR can reconstruct dynamic CBCTs and solve the intra-scan motion from conventional 3D CBCT scans without using any prior anatomical/motion model or motion sorting/binning. It can be a promising tool for motion management by offering richer motion information than traditional 4D-CBCTs.

New technique and application of truncated CBCT processing in adaptive radiotherapy for breast cancer

Purpose: To combine total variation (TV) and Hessian penalty in a structure adaptive way for cone-beam CT (CBCT) reconstruction. Methods: TV is a widely used first order penalty with good ability in suppressing noise and preserving edges but leads to the staircase effect in regions with smooth intensity transition. The second order Hessian penalty can effectively suppress the staircase effect with extra cost of blurring object edges. To take the best of both penalties we proposed a novel method to combine both for CBCT reconstruction in a structure adaptive way. The proposed method adaptively determined the weight of each penalty according to the geometry of local regions. An specially-designed exponent term with image gradient involved was used to characterize the local geometry such that the weights for Hessian and TV were 1 and 0 respectively at uniform local regions and 0 and 1 at edge regions. For other local regions the weights varied from 0 to 1. The objective functional was minimized using the majorzationminimization approach. We evaluated the proposed method on a modified 3D shepp-logan and a CatPhan 600 phantom. The full-width-at-halfmaximum (FWHM) and contrast-to-noise (CNR) were calculated. Results: For 3D shepp-logan the reconstructed images using TV had an obvious staircase effect while those using the proposed method and Hessian preserved the smooth transition regions well. FWHMs of the proposed method TV and Hessian penalty were 1.75 1.61 and 3.16 respectively, indicating that both TV and the proposed method is able to preserve edges. For CatPhan 600 CNR values of the proposed method were similar to those of TV and Hessian. Conclusion: The proposed method retains favorable properties of TV like preserving edges and also has the ability in better preserving gradual transition structure as Hessian does. All methods performs similarly in suppressing noise. This work was supported in part by National Natural Science Foundation of China (NNSFC) under Grant Nos.60971112 and 61375018 grants from the Cancer Prevention and Research Institute of Texas (RP130109 and RP110562-P2) National Institute of Biomedical Imaging and Bioengineering (R01 EB020366) and a grant from the American Cancer Society (RSG-13-326-01-CCE).

246 Background: Cone Beam Computed Tomography(CBCT) is the cornerstone of image guided radiotherapy(IGRT) which is an integral part of pelvic cancers like prostate cancer. Each pelvic radiotherapy (RT) session is preceded by a planned CBCT to ensure target localisation and organ at risk avoidance. When these criteria are not met, an unplanned CBCT is performed until the CBCT is satisfactory. Possible reasons for an unsatisfactory CBCT include an under filled bladder, distended rectum or prostate gland movement. Repeated unplanned CBCT results in unnecessary excess radiation for patients. We aimed to reduce the incidence of unplanned CBCT from a baseline of 21% to 9% over 5 months. Methods: We conducted the project using both conventional quality improvement methodology and the design thinking methodology. In the diagnostic phase up to March 2017, the baseline incidence of CBCT in patients receiving pelvic RT was 21%. We hypothesized that there were reversible factors leading to a higher incidence of unplanned CBCT and sought to identify and rectify these reversible factors to reduce the incidence of unplanned CBCT. Using human centred design, we designed a new process of performing a bladder ultrasound prior to CBCT to ensure a full bladder prior to RT using the steps empathy, define, ideation, prototype, testing, sharing. Results: A total of 97 patients that underwent pelvic radiotherapy were included in this study, 40 patients were pre intervention and 61 patients received the bladder ultrasound intervention implemented from April 2017 onwards. After intervention, incidence of unplanned decreased from 21% to 5.8%. A 2 sample t test was used to compare the unplanned CBCT pre and post intervention. We found the mean pre and post intervention difference in pooled mean incidence of unplanned CBCT to be significantly different by 13.3%. The reduction in unplanned CBCT translated to saving each patient on average equivalent to 3000 chest x rays worth of unnecessary radiation. Conclusions: Design Thinking is a feasible strategy in quality improvement. We report the first design thinking project in radiation oncology quality improvement. An automated ultrasound bladder is a feasible strategy to screen for bladder filling prior to each CBCT to reduce reliance on CBCT and also patient exposure to radiation in IGRT of pelvic cancers.

Cone beam computed tomography (CBCT) plays an important role in many medical fields nowadays. Unfortunately, the potential of this imaging modality is hampered by lower image quality compared to the conventional CT, and producing accurate reconstructions remains challenging. A lot of recent research has been directed towards reconstruction methods relying on deep learning, which have shown great promise for various imaging modalities. However, practical application of deep learning to CBCT reconstruction is complicated by several issues, such as exceedingly high memory costs of deep learning methods when working with fully 3D data. Additionally, deep learning methods proposed in the literature are often trained and evaluated only on data from a specific region of interest, thus raising concerns about possible lack of generalization to other regions. In this work, we aim to address these limitations and propose LIRE: a learned invertible primal-dual iterative scheme for CBCTreconstruction. LIRE is a learned invertible primal-dual iterative scheme for CBCT reconstruction, wherein we employ a U-Net architecture in each primal block and a residual convolutional neural network (CNN) architecture in each dual block. Memory requirements of the network are substantially reduced while preserving its expressive power through a combination of invertible residual primal-dual blocks and patch-wise computations inside each of the blocks during both forward and backward pass. These techniques enable us to train on data with isotropic 2 mm voxel spacing, clinically-relevant projection count and detector panel resolution on current hardware with 24 GBvideo random access memory (VRAM). Two LIRE models for small and for large field-of-view (FoV)setting were trained and validated on a set of 260 + 22 thorax CT scans and tested using a set of 142 thorax CT scans plus an out-of-distribution dataset of 79 head and neck CT scans. For both settings, our method surpasses the classical methods and the deep learning baselines on both test sets. On the thorax CT set, our method achieves peak signal-to-noise ratio (PSNR) of 33.84 ± 2.28 for the small FoV setting and 35.14 ± 2.69 for the large FoV setting; U-Net baseline achieves PSNR of 33.08 ± 1.75 and 34.29 ± 2.71 respectively. On the head and neck CT set, our method achieves PSNR of 39.35 ± 1.75 for the small FoV setting and 41.21 ± 1.41 for the large FoV setting; U-Net baseline achieves PSNR of 33.08 ± 1.75 and 34.29 ± 2.71 respectively. Additionally, we demonstrate that LIRE can be finetuned to reconstruct high-resolution CBCT data with the same geometry but 1 mm voxel spacing and higher detector panel resolution, where it outperforms the U-Net baseline aswell. Learned invertible primal-dual schemes with additional memory optimizations can be trained to reconstruct CBCT volumes directly from the projection data with clinically-relevant geometry and resolution. Such methods can offer better reconstruction quality and generalization compared to classical deep learning baselines.

ABSTRACTBackground. Radiotherapy based on MRI only (MRI-only RT) shows a promising potential for the brain. Much research focuses on creating a pseudo computed tomography (pCT) from MRI for treatment planning while little attention is often paid to the treatment delivery. Here, we investigate if cone beam CT (CBCT) can be used for MRI-only image-guided radiotherapy (IGRT) and for verifying the correctness of the corresponding pCT.Material and methods. Six patients receiving palliative cranial RT were included in the study. Each patient had three-dimensional (3D) T1W MRI, a CBCT and a CT for reference. Further, a pCT was generated using a patch-based approach. MRI, pCT and CT were placed in the same frame of reference, matched to CBCT and the differences noted. Paired pCT-CT and pCT-CBCT data were created in bins of 10 HU and the absolute difference calculated. The data were converted to relative electron densities (RED) using the CT or a CBCT calibration curve. The latter was either based on a CBCT phantom (phan) or a paired CT-CBCT population (pop) of the five other patients.Results. Non-significant (NS) differences in the pooled CT-CBCT, MRI-CBCT and pCT-CBCT transformations were noted. The largest deviations from the CT-CBCT reference were < 1 mm and 1°. The average median absolute error (MeAE) in HU was 184 ± 34 and 299 ± 34 on average for pCT-CT and pCT-CBCT, respectively, and was significantly different (p < 0.01) in each patient. The average MeAE in RED was 0.108 ± 0.025, 0.104 ± 0.011 and 0.099 ± 0.017 for pCT-CT, pCT-CBCT phan (p < 0.01 on 2 patients) and pCT-CBCT pop (NS), respectively.Conclusions. CBCT can be used for patient setup with either MRI or pCT as reference. The correctness of pCT can be verified from CBCT using a population-based calibration curve in the treatment geometry.

PurposeThe purpose of this study is to evaluate inter- and intra-fraction organ motion as well as to quantify clinical target volume (CTV) to planning target volume (PTV) margins to be adopted in the stereotactic treatment of early stage glottic cancer.Methods and materialsStereotactic body radiotherapy (SBRT) to 36 Gy in 3 fractions was administered to 23 patients with early glottic cancer T1N0M0. Patients were irradiated with a volumetric intensity modulated arc technique delivered with 6 MV FFF energy. Each patient underwent a pre-treatment cone beam computed tomography (CBCT) to correct the setup based on the thyroid cartilage position. Imaging was repeated if displacement exceeded 2 mm in any direction. CBCT imaging was also performed after each treatment arc as well as at the end of the delivery. Swallowing was allowed only during the beam-off time between arcs. CBCT images were reviewed to evaluate inter- and intra-fraction organ motion. The relationships between selected treatment characteristics, both beam-on and delivery times as well as organ motion were investigated.ResultsFor the population systematic (Ʃ) and random (σ) inter-fraction errors were 0.9, 1.3 and 0.6 mm and 1.1, 1.3 and 0.7 mm in the left-right (X), cranio-caudal (Y) and antero-posterior (Z) directions, respectively. From the analysis of CBCT images acquired after treatment, systematic (Ʃ) and random (σ) intra-fraction errors resulted 0.7, 1.6 and 0.7 mm and 1.0, 1.5 and 0.6 mm in the X, Y and Z directions, respectively. Margins calculated from the intra-fraction errors were 2.4, 5.1 and 2.2 mm in the X, Y and Z directions respectively. A statistically significant difference was found for the displacement in the Z direction between patients irradiated with > 2 arcs versus ≤ 2 arcs, (MW test, p = 0.038). When analyzing mean data from CBCT images for the whole treatment, a significant correlation was found between the time of delivery and the three dimensional displacement vector (r = 0.489, p = 0.055), the displacement in the Y direction (r = 0.553, p = 0.026) and the subsequent margins to be adopted (r = 0.626, p = 0.009). Finally, displacements and the subsequent margins to be adopted in Y direction were significantly greater for treatments with more than 2 arcs (MW test p = 0.037 and p = 0.019, respectively).ConclusionsIn the setting of controlled swallowing during treatment delivery, intra-fraction motion still needs to be taken into account when planning with estimated CTV to PTV margins of 3, 5 and 3 mm in the X, Y and Z directions, respectively. Selected treatments may require additional margins.

Intra-operative Cone Beam Computed Tomography can Help Avoid Reinterventions and Reduce CT Follow up after Infrarenal EVAR

Characterization of a Novel Radiopaque Perirectal Hydrogel Spacer for Prostate Cancer Radiotherapy