Fan-beam CT Research Articles

MARGANVAC: metal artifact reduction method based on generative adversarial network with variable constraints

Objective. Metal artifact reduction (MAR) has been a key issue in CT imaging. Recently, MAR methods based on deep learning have achieved promising results. However, when deploying deep learning-based MAR in real-world clinical scenarios, two prominent challenges arise. One limitation is the lack of paired training data in real applications, which limits the practicality of supervised methods. Another limitation is that image-domain methods suitable for more application scenarios are inadequate in performance while end-to-end approaches with better performance are only applicable to fan-beam CT due to large memory consumption. Approach. We propose a novel image-domain MAR method based on the generative adversarial network with variable constraints (MARGANVAC) to improve MAR performance. The proposed variable constraint is a kind of time-varying cost function that can relax the fidelity constraint at the beginning and gradually strengthen the fidelity constraint as the training progresses. To better deploy our image-domain supervised method into practical scenarios, we develop a transfer method to mimic the real metal artifacts by first extracting the real metal traces and then adding them to artifact-free images to generate paired training data. Main results. The effectiveness of the proposed method is validated in simulated fan-beam experiments and real cone-beam experiments. All quantitative and qualitative results demonstrate that the proposed method achieves superior performance compared with the competing methods. Significance. The MARGANVAC model proposed in this paper is an image-domain model that can be conveniently applied to various scenarios such as fan beam and cone beam CT. At the same time, its performance is on par with the cutting-edge dual-domain MAR approaches. In addition, the metal artifact transfer method proposed in this paper can easily generate paired data with real artifact features, which can be better used for model training in real scenarios.

Gradient-based geometry learning for fan-beam CT reconstruction

Objective. Incorporating computed tomography (CT) reconstruction operators into differentiable pipelines has proven beneficial in many applications. Such approaches usually focus on the projection data and keep the acquisition geometry fixed. However, precise knowledge of the acquisition geometry is essential for high quality reconstruction results. In this paper, the differentiable formulation of fan-beam CT reconstruction is extended to the acquisition geometry. Approach. The CT fan-beam reconstruction is analytically derived with respect to the acquisition geometry. This allows to propagate gradient information from a loss function on the reconstructed image into the geometry parameters. As a proof-of-concept experiment, this idea is applied to rigid motion compensation. The cost function is parameterized by a trained neural network which regresses an image quality metric from the motion-affected reconstruction alone. Main results. The algorithm improves the structural similarity index measure (SSIM) from 0.848 for the initial motion-affected reconstruction to 0.946 after compensation. It also generalizes to real fan-beam sinograms which are rebinned from a helical trajectory where the SSIM increases from 0.639 to 0.742. Significance. Using the proposed method, we are the first to optimize an autofocus-inspired algorithm based on analytical gradients. Next to motion compensation, we see further use cases of our differentiable method for scanner calibration or hybrid techniques employing deep models.

A Feasible Study for Auto Planning and Auto Re-Planning for Nasopharyngeal Carcinoma (NPC) Adaptive Radiation Therapy (ART)

To explore the necessity of Image Guided Radiation Therapy (IGRT) for Nasopharyngeal Carcinoma (NPC) adaptive radiation therapy (ART), and evaluate the consistency and robustness of auto re-planning during ART. Eleven NPC patients were enrolled in this study at one institution. We used a CT-integrated linear accelerator, which integrates a 16-slice helical CT to acquire diagnostic-grade fan-beam CT (FBCT) for IGRT. Electron density accuracy from FBCT provides a solid foundation for accurate radiation dose calculation. PGTVp, PTV1 and PTV2 prescription dose are 69.96 Gy, 60.06 Gy and 54.12 Gy with 33 fractions. All ROIs, including Targets and OARs, were auto delineated via a treatment planning system (TPS), and modified by a senior physician with more than 15-year experience to confirm that they follow the clinical requirement. An initial plan (Plan A) was automatically generated based on the first CT-Sim images on the TPS. Another adjusted re-plan (Plan B) was also automatically generated based on the second CT-Sim images after 20 fractions of treatment for ART implementation. During the whole course of the 33 fractions delivery, there are 20 fractions Plan A (with 4 weekly IGRTi, i = 1∼4) and 13 fractions Plan B (with 3 weekly IGRTj, j = 5∼7). After carefully rigid registration between the CT-Sim images and their following weekly FBCT images, we copied Plan A and Plan B to IGRTi and IGRTj, respectively. Plan_IGRT would be re-calculated for dose evaluation. In addition, the Plan A was copied to the second CT-Sim (Plan A_2nd CT-Sim) after first CT-Sim and second CT-Sim rigid images registration. There is a significant target volume change of -5%±4%, -3%±3%, and -5%±3% from Plan A to Plan B, for PGTVp, PTV1 and PTV2 (p<0.05), respectively. All the Plan A and Plan B could be generated within 210.2s±1.4s, which is more time-saving than manual planning greatly, and there is no statistical difference between Plan A and Plan B of the plan quality index (p>0.05). The plans for IGRT7 are inferior to the plans for IGRT5 with higher V110% for PGTVp (4.40%±8.60% for Plan A, 2.37%±8.91% for Plan B). PlanA_2nd CT-Sim for each patient is inferior to Plan B, with higher V110% for PGTVp (19.12%±18.91%), lower V100% for PTV2 (-2.84%±2.89%) and higher Dmax for Brainstem (315.88 cGy ± 190.39 cGy) statistically. Furthermore, all the Plan B_IGRTj are superior to Plan A_IGRTj, with the dose index difference of -17.50% ± 23.15%/-15.47% ± 14.85%, 2.45% ± 3.23%/2.31% ± 3.09% and -194.03 cGy ± 221.91 cGy/-170.07 cGy ± 168.41 cGy for V110% of PGTVp, V100% for PTV2 and Dmax of Brainstem for j = 5/7 (p<0.05), respectively. The world's first integrated CT-Linac platform, equipped with FBCT, can provide a diagnostic-quality FBCT for achieve offline ART. It is necessary for NPC patients to have the IGRT, ART and re-planning after 20 fractions treatment, for the target volumes change sharply. Auto planning and auto re-planning for NPC ART are able to maintain the plan consistency and robustness while shorten the planning time.

First Implementation of Full-Workflow Automation for Online Adaptive Radiotherapy of Nasopharyngeal Carcinoma

The aim of this work is to established the technical characteristics and implementation procedures of an artificial intelligence (AI)-powered radiotherapy workflow that enables full-process automation for online adaptive radiotherapy (ART); and evaluate its feasibility and performance implemented for ART of nasopharyngeal carcinoma (NPC). This single center, prospective study has been approved by the ethical committee of the institution. The online ART workflow was developed based on a CT-integrated linear accelerator. During the course of radiotherapy, the patient underwent daily pre-treatment fan-beam CT (FBCT) scan. Then the FBCT was automatically registered to the original planning CT and used to assess the need for the patient to implement ART according to radiation oncologist's discretionary. The online ART workflow incorporates critical radiotherapy procedures from re-simulation, auto-segmentation by integrating image fusion and deep learning method, auto-replanning, beam delivery, and in vivo quality assurance (QA) into one scheme, while the patient is on the treatment couch during the whole process. From 2th April 2022 to 5th January 2023, 20 patients with newly-diagnosed, non-metastatic NPC were enrolled in this study. Only one-time online ART was performed for each patient, because that the appropriate timing for triggering online ART was explored in parallel with this study. According to radiation oncologists' discretionary, the median fraction for performing online ART was at 21 fractions (interquartile range, 19-24 fractions). All patients were well tolerated and successfully completed the treatment. For tumor targets contouring, minor revisions were required for automated contours of the primary gross tumor volume (GTVp) and clinical target volumes (CTVs, including CTV1 and CTV2), with the mean DSC between before and after revision of 0.91±0.042, 0.94 ± 0.042 and 0.91 ± 0.061, respectively; and much more revisions for the automated contours of cervical lymph nodes GTV (GTVn), with the mean DSC of 0.74 ± 0.28. The automated contours of normal tissues were clinically acceptable with little modifications. Median time consuming for auto-segmentation and revision was 9.5 minutes (min). For treatment planning, 18 automated plans (90%) were passed at their first auto-optimization and two plans (10%) were passed after further optimization of the dose coverage of CTVs by physicist; and the median time consuming for auto-planning was 6.2 min. Time consuming for other procedures were as follows: re-simulation, 2.3 min; plan evaluation, 3.3 min; beam delivery, 4.6 min; and the duration of the entire process was 25.9 min, range from 19.4 min to 32.5 min. We successfully established an AI-powered online ART workflow for adaptive radiotherapy of NPC, and confirmed that current auto-segmentation and auto-replanning methods are powered enough to support the clinical application of its online ART.

All-in-One Online Radiotherapy for Nasopharyngeal Carcinoma: Preliminary Results of Treatment Time, Contouring Accuracy, Treatment Plan Quality and Patient Compliance

To explore the feasibility of Fan-beam CT (FBCT)-based all in one (AIO) online workflow for nasopharyngeal carcinoma (NPC) in radical radiotherapy setting, and to preliminarily describe the timing of different steps in the process, contouring accuracy of regions of interest (ROIs), target coverage, organs at risk (OARs) dose and patient compliance. From March 16, 2022 to January 04, 2023, 25 NPC patients (22/25 diagnosed as phase III/IV disease according to 8th edition of the AJCC/UICC staging system) consecutively treated with AIO radiotherapy were prospectively enrolled. All patients received mask fixation and MRI simulation scan in advance. Primary gross tumor volume (GTVp) of nasopharynx was automatically delineated by AI and edited manually on MRI images. AIO online workflow started with an integrated KV-level CT in a CT-integrated linear accelerator. After that GTVp was registrated to CT images and other ROIs was contoured automatically and then modified manually as needed. Subsequently automatic treatment plan was calculated and optimized until the dose of target and OARs was evaluated satisfactory by physicians and physicists. Finally, treatment was delivered using volumetric modulated arc treatment (VMAT), with prescribed dose of 6996 cGy/ 33 fractions to the GTVp. Twenty-four patients (24/25, 96%) completed the AIO radiotherapy workflow successfully, with average treatment time of 28.3 min (range: 19.9-42.4 min). the AI-assisted ROIs automatically contouring took 1.55 min in average (range: 1.32-1.77 min), with an average DICE of 97.7% compared with modified contouring, and the average DICE was 95.7% for clinical tumor volume 1 (CTV1), 88.6% for CTV2, 73.6% for GTVn (cervical lymph node), 99.3% for 30 OARs. The automatic treatment plan averagely needed 3.5 min, and the pass rate of radiotherapy planning was 91.7% (22/24). The target coverage for PTVs for GTVp, CTV1, and CTV2 was 99.3%, 99.8%, 98.0% respectively. As for the dose of OARs, the average Dmax of brainstem was 5,583cGy; the Dmax of spinal cord was 3,467cGy; the Dmean of parotid was 3,285 cGy. The average monitor units of all patients was 643 MU and the delivery took 2.93 min. Patient compliance with respect to AIO workflow and total treatment time was excellent. The AIO online radiotherapy was promising for NPC patients, with clinically acceptable AI assisted ROIs contouring and treatment planning, as well as favorable patient compliance to the AIO online workflow.

Comparison of AI-Based Auto-Segmentation Quality with Different Daily IGRT Imaging Modalities for Adaptive Radiotherapy Treatment Planning

Modern AI-based auto-segmentation tools may be applied on daily computed tomography (CT) images in an image-guided radiotherapy course to facilitate evaluation of anatomical variations and adaptive treatment planning. However, most AI auto-segmentation models are trained with high-quality diagnostic or planning CT image data. This study aims to evaluate and compare auto-segmentation quality by an AI-based auto-segmentation system with different daily CT imaging modalities. We retrospectively retrieved daily IGRT images for sixty patients. Among them, twenty patients were treated on helical tomotherapy with daily megavoltage CT (MVCT) scans, twenty patients were treated on conventional Linacs with daily cone-beam CT (CBCT) scans, and twenty patients were treated on a biology-guided radiotherapy (BgRT)-capable machine with daily fan-beam kilovoltage CT (kVCT) scans. With each treatment modality, ten patients received daily CT scans in the pelvic region while the other ten received daily CT scans in the thoracic region. An auto-segmentation system using a convolutional neural network algorithm was trained in-house with historical treatment planning CT and contouring data to generate auto-segmentation models for the pelvic and thoracic regions, respectively. Normal organs were first delineated the auto-segmentation system on the daily CT images and then drawn by an experienced planner. A set of metrics including the dice similarity coefficient (DSC), Jaccard similarity index, and Hausdorff distance were used to evaluate the quality of the auto segmentation results compared with manual contours. The auto-segmentation contours on the kVCT images showed higher average DSC compared to those on the MVCT and CBCT images for all the major organs in both the pelvic and thoracic regions including the bladder, rectum, bowel, left and right femurs, esophagus, heart, left and right lung, and spinal cord. With the kVCT images, the average DSC ranged from 0.52±0.22 to 0.996±0.005. In the pelvic region, the largest absolute difference in DSC was observed for the bowel volume with an average DSC of 0.69±0.16, 0.49±0.27, and 0.32±0.25 for the kVCT, MVCT, and CBCT images, respectively (p-value < 0.05 with unpaired t-tests between kVCT and the other two imaging modalities); in the thoracic region, the largest absolute difference in DSC was observed for the esophagus with an average DSC of 0.63±0.16, 0.22±0.08, and 0.15±0.18 for the kVCT, MVCT, and CBCT images, respectively (p-value < 0.05 with unpaired t-tests between kVCT and the other two imaging modalities). Similar results were observed with other metrics. The AI-based auto segmentation system showed improved agreement with manual contouring when using kVCT images from the BgRT capable machine compared to MVCT or CBCT images. However, manual correction is necessary on auto-segmentation results from all imaging modalities especially for organs with limited contrast from surrounding tissues.

Reproducibility and Repeatability of Pelvic Radiomics Features with Daily Imaging on a Novel Biology-Guided Radiotherapy Machine Compared to Daily Imaging on Other Radiotherapy Delivery Systems

Radiomics features extracted from computed tomography (CT) images have the potential of being used as imaging biomarkers in diagnostic and prognostic models for prostate cancer. This study aims to evaluate reproducibility and repeatability of radiomics features using daily CT images from a novel biology-guided radiotherapy (BgRT)-capable machine compared to other daily CT imaging modalities from other radiotherapy delivery systems. We retrospectively selected thirty male patients treated to the pelvic region at our institution. Among the thirty patients, ten patients were treated on a BgRT-capable machine with daily fan-beam kilovoltage CT (kVCT) scans, ten patients were treated on a conventional Linac with daily cone-beam CT (CBCT) scans, and ten patients were treated on helical tomotherapy with daily megavoltage CT (MVCT) scans. The prostate gland and femoral heads were delineated on planning CT images and on CT images at the first treatment fraction. After all the CT images were resampled to have an identical voxel size, 107 radiomics features were calculated for the prostate and femoral heads on both the planning CT images and daily CT images. Concordance correlation coefficient (CCC) and Pearson's correlation coefficient (r) were calculated to evaluate radiomics feature reproducibility between the planning CT images and pre-treatment CT scans at the first treatment fraction. To evaluate radiomics feature repeatability with kVCT images on the BgRT-capable machine, a total of ten treatment sessions with repeat kVCT scans on the BgRT-capable machine were retrieved and radiomics features were compared between the first and the second kVCT scans. For the prostate gland volume, high concordance (CCC > 0.8) was found for 8, 6, and 0 radiomics features with the first-fraction kVCT, CBCT, and MVCT images, respectively, in relation to the planning CT images, while there was strong correlation (r > 0.8) in 38, 22, and 5 radiomics features in the kVCT, CBCT, and MVCT images, respectively, in relation to the planning CT images. For the left and right femoral heads, high concordance (CCC > 0.8) was found in no more than two radiomics features with the kVCT, CBCT, or MVCT images in relation to the planning CT images. Based on repeat kVCT scan data, 97 (90.7%) radiomics features showed high concordance (CCC > 0.8) in repeat kVCT scans with 98 (91.6%) features showing high correlation (Pearson's correlation coefficient > 0.8) for the prostate gland volume. A small number of radiomics features were found to show strong reproducibility between daily CT images on the first fraction and the planning CT images with the three IGRT CT modalities in this study. On the other hand, our results indicated that strong reproducibility was found with more radiomics features with daily kVCT images from the BgRT-capable machine compared to daily CBCT and MVCT images for the prostate gland. Strong repeatability was also found with most radiomics features in daily kVCT images.

The Feasibility of Adaptive CT Simulation-Free Radiation Therapy

To investigate the feasibility of a novel, streamlined radiotherapy treatment workflow in which simulation and treatment occur in a single on-table session. The efficiency, dosimetric accuracy, plan quality, and resource requirements were metrics used to evaluate the clinical potential of CT simulation-free radiotherapy. An adaptive radiotherapy treatment platform was upgraded to include a novel CBCT system reporting image quality and Hounsfield unit accuracy specifications comparable to standard fan-beam CT. An in-house workflow was designed to allow the CBCT data to be used as reference image sets for planning. Two test cases were completed on anthropomorphic phantoms equipped with small volume ion chambers (cross-calibrated to an ADCL traceable dose standard) to evaluate the feasibility and accuracy of the workflows. A spine was planned for palliative treatment with 8 Gy in 1 fraction, and an intact prostate was planned for definitive treatment with 60 Gy in 20 fractions. The CBCTs were acquired using default thorax and pelvis imaging protocols and reconstructed using an iterative algorithm with scatter removal. CBCTs were used for contouring and planning, and treatment was delivered via an online adaptive workflow. An extended-field CBCT acquisition can be acquired in 12 s of acquisition time and reconstructed in approximately 1 min. The superior-inferior extent for the CBCT planning images was 42 cm, which captured the full extent of relevant anatomy; an audit of recent single-site palliative CT simulation scans had an average length of 44.9 cm. The contouring and treatment planning for the spine and prostate were completed in 30 min and 23 min, respectively. The dosimetric agreement with the treatment plan agreed to within a range of -1.17 to 1.64%, and a mean and standard deviation of 0.41 ± 1.16%. Using an in-house workflow, CT simulation-free radiation therapy was shown to be feasible with acceptable workflow efficiency and dosimetric accuracy. This approach may be particularly applicable for urgent palliative treatments. With the availability of software to enable this workflow, and the continued advancement of on-treatment adaptation, single-visit radiation therapy may replace current practice for some clinical indications.

Development of the Independent Dose Verification Method for the Ring Gantry PET/CT Linac

The RefleXion Xi is a new external beam radiotherapy delivery modality combining kilovoltage fan-beam CT and on-board PET for Biology-guided Radiotherapy. Although the machine shares similar components with the Tomotherapy machine, it has unique hardware features such as stationary beam delivery system with couch increments. The goal of this study is to develop an in-house independent secondary dose calculation method for this ring gantry PET/CT Linac. The method aggregates the beam intensities at each discrete firing gantry angle and couch moving position. The non-uniform intensity map is decomposed into a series of segments of uniform beam intensities, and then coordinates of beam segments were modified based on the relative distance from the dose calculation point to keep the calculation point in the same spot along the gantry rotation. The dose to the calculation point of each segment is determined by using measured tissue-maximum-ratio, output factors, and off-axis ratio by independent binary collimators. Two-dimensional convolution method is applied to integrate all dose contribution components in segment areas for efficient calculation. The final dose is obtained by summing all dose to the calculation point of segments for all firing gantry angle and couch position. Twenty patients with different treatment sites including head and neck, prostate, and lung regions were analyzed. Comparison of the point dose calculated by the independent program to that calculated by the planning system has shown reasonable agreement within ±5%. The independent dose verification program has been developed as an initial patient specific QA for improving patient safety. Further study will be performed to enhance the accuracy and reliability by including additional leakage and scatter models.

Evaluation of a Novel Metal Artifact Reduction Algorithm for Reconstruction of Cone Beam CT (CBCT) Images Acquired on a New Imaging System

The presence of metal implants, dental work or prosthetics can produce image artifacts and distort Hounsfield units (HU) in patient CBCT images. The purpose of this work was to characterize a novel metal artifact reduction (MAR) algorithm for reconstruction of CBCT images obtained by a new imaging system and compare improvements in image quality with a conventional iterative reconstruction algorithm. Preliminary analyses show that the novel reconstruction algorithm implemented on the new imaging system produces image quality and HU comparable to standard fan-beam CT MATERIALS/METHODS: A 30 cm (length) x 30 cm (width) x 11 cm (depth) solid water phantom was fitted with a central cavity measuring 5.5 cm x 5.5 cm x 0.5 cm. Metal inserts of copper, aluminum, stainless steel, and titanium (5.5 cm x 5.5 cm x 1 - 5 mm in thickness) and sample dental implant materials (Amalgam, Au, Co-Cr, and Ti 6Al-Yv) were sequentially used to fill the cavity. CBCT images were acquired and reconstructed using the novel MAR and conventional iterative algorithms both on the on the new system. Images were also taken with the cavity filled with solid water for comparison. Eight image quality metrics were measured in six volumes of interest (VOIs) surrounding the cavity and compared to baseline VOI metrics for solid water-only images: HU mean, signal-to-noise ratio, contrast-to-noise ratio, artifact index, standard deviation, range, skewness, and kurtosis. The mean and standard deviation of HU within a shell-structure surrounding the cavity were calculated to evaluate the dependence of these values on distance from the center of the cavity. The artifact volume of the phantom (excluding the cavity) was estimated by calculating the 5th and 95th percentiles of HU in the CBCT of the phantom with the solid water insert, then summing the volume of all voxels with HU values outside this range. The eight image quality metrics extracted from the chosen VOIs were closer to baseline when using the novel MAR compared to conventional iterative reconstruction. It was also determined that mean HU returned to expected solid water background at a shorter distance from metal sample in the novel MAR images, and the standard deviation remained lower for the novel MAR images at all distances from the insert. These experimental outcomes were obtained for all high-density material inserts except for aluminum. The artifact volume was decreased using the novel MAR algorithm for all metal inserts excluding aluminum (p = 0.00013), and all dental implants (p = 0.00028). The novel MAR reconstruction algorithm shows a much lower sensitivity to metal artifacts, and significant improvement in image quality for all metal samples except for aluminum. These results justify the use of the novel MAR reconstruction for patients with metal implants and highlight advantages of the new CBCT imaging system for more accurate imaging and targeted treatment.

Three-Dimensional Imaging and Histopathological Features of Third Metacarpal/Tarsal Parasagittal Groove and Proximal Phalanx Sagittal Groove Fissures in Thoroughbred Horses.

Fissure in the third metacarpal/tarsal parasagittal groove and proximal phalanx sagittal groove is a potential prodromal pathology of fracture; therefore, early identification and characterisation of fissures using non-invasive imaging could be of clinical value. Thirty-three equine cadaver limbs underwent standing cone-beam (CB) computed tomography (CT), fan-beam (FB) CT, low-field magnetic resonance imaging (MRI), and macro/histo-pathological examination. Imaging diagnoses of fissures were compared to microscopic examination. Imaging features of fissures were described. Histopathological findings were scored and compared between locations with and without fissures on CT. Microscopic examination identified 114/291 locations with fissures. The diagnostic sensitivity and specificity were 88.5% and 61.3% for CBCT, 84.1% and 72.3% for FBCT, and 43.6% and 85.2% for MRI. Four types of imaging features of fissures were characterised on CT: (1) CBCT/FBCT hypoattenuating linear defects, (2) CBCT/FBCT striated hypoattenuated lines, (3) CBCT/FBCT subchondral irregularity, and (4) CBCT striated hypoattenuating lines and FBCT subchondral irregularity. Fissures on MRI appeared as subchondral bone hypo-/hyperintense defects. Microscopic scores of subchondral bone sclerosis, microcracks, and collapse were significantly higher in locations with CT-identified fissures. All imaging modalities were able to identify fissures. Fissures identified on CT were associated with histopathology of fatigue injuries.

2DeteCT - A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning

Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images. However, suitable experimental datasets for X-ray Computed Tomography (CT) are scarce, and methods are often developed and evaluated only on simulated data. We fill this gap by providing the community with a versatile, open 2D fan-beam CT dataset suitable for developing ML techniques for a range of image reconstruction tasks. To acquire it, we designed a sophisticated, semi-automatic scan procedure that utilizes a highly-flexible laboratory X-ray CT setup. A diverse mix of samples with high natural variability in shape and density was scanned slice-by-slice (5,000 slices in total) with high angular and spatial resolution and three different beam characteristics: A high-fidelity, a low-dose and a beam-hardening-inflicted mode. In addition, 750 out-of-distribution slices were scanned with sample and beam variations to accommodate robustness and segmentation tasks. We provide raw projection data, reference reconstructions and segmentations based on an open-source data processing pipeline.

Commissioning of a solid tank design for fan-beam optical CT based 3D radiation dosimetry.

Objective.Optical computed tomography (CT) is one of the leading modalities for imaging gel dosimeters used in the verification of complex radiotherapy treatments. In previous work, a novel fan-beam optical CT scanner design was proposed that could significantly reduce the volume of the refractive index baths that are commonly found in optical CT systems. Here, the proposed scanner has been manufactured and commissioned.Approach.Image reconstruction is performed through algebraic reconstruction technique and iterated using the fast iterative shrinkage-thresholding algorithm (FISTA) algorithm. Ray tracing for algebraic reconstruction was performed using an in-house developed ray tracing simulator. A set of Sylgard® 184 phantoms were created to commission spatial resolution, geometric deformity, contrast-to-noise ratio (CNR), and scan settings.Main Results.The scanner is capable of a 0.929 mm-1spatial resolution, observed at 200 iterations, although the spatial resolution is highly dependent on the number of iterations. The geometric distortion, measured by scanning a needle phantom with the prototype scanner as well as a conventional x-ray CT was found to be within <0.25 mm. The CNR was found to peak between 65 and 190 occurring between 50 and 100 iterations and was highly dependent on the region chosen for background noise calculation. The proposed scanner is capable of scanning and reading out slices in less than 1 min per slice.Significance.This work displays the viability of a fan-beam optical CT scanner with minimal index matching using ray-traced algebraic reconstruction.

Comparison of cone-beam and fan-beam computed tomography and low-field magnetic resonance imaging for detection of proximal phalanx dorsoproximal osteochondral defects.

Dorsoproximal osteochondral defects commonly affect the proximal phalanx, but information about diagnosis on computed tomography (CT) and magnetic resonance imaging (MRI) is limited. To assess CT and MRI diagnoses of osteochondral defects, describe the lesions and compare sensitivity and specificity of the modalities using macroscopic pathology as gold standard. Cross-sectional study. Thirty-five equine cadaver limbs underwent standing cone-beam CT (CBCT), fan-beam CT (FBCT), low-field MRI and pathological examination. CT and MR images were examined for proximal phalanx dorsomedial and dorsolateral eminence osteochondral defects. Defect dimensions were measured. Imaging diagnoses and measurements were compared with macroscopic examination. Fifty-six defects were seen over 70 potential locations. On CBCT and FBCT, osteochondral defects appeared as subchondral irregularity/saucer-shaped defects. On MRI, osteochondral defects were a combination of articular cartilage defect on dorsal images and subchondral flattening/irregularity on sagittal images. Subchondral thickening and osseous short tau inversion recovery hyperintensity were found concurrent with osteochondral defects. Compared with pathological examination, the sensitivity and specificity of diagnosis were 86% (95% confidence interval [95% CI] 75%-93%) and 64% (95% CI 38%-85%) for FBCT; 64% (95% CI 51%-76%) and 71% (95% CI 46%-90%) for CBCT; and 52% (95% CI 39%-65%) and 71% (95% CI 46%-90%) for MRI. Sensitivity of all modalities increased with defect size. Macroscopic defect dimensions were strongly correlated with CBCT (r = 0.76, p < 0.001) and moderately correlated with FBCT and MRI (r = 0.65, p < 0.001). Macroscopic measurements were significantly greater than all imaging modality dimensions (p < 0.001), potentially because macroscopy included articular cartilage pathology. Influence of motion artefact could not be assessed. Osteochondral defects could be visualised using both CT and MRI with sensitivity increasing with defect size. Diagnostic performance was best using FBCT, followed by CBCT then MRI, but CBCT-measured defect size best correlated with macroscopic examination. MRI provided useful information on fluid signal associated with defects, which could represent active pathology.

Iterative image reconstruction with polar coordinate discretized system matrix for optical CT radiochromic gel dosimetry.

Gel dosimeters are a potential tool for measuring the complex dose distributions that characterize modern radiotherapy. A prototype tabletop solid-tank fan-beam optical CT scanner for readout of gel dosimeters was recently developed. This scanner does not have a straight raypath from source to detector, thus images cannot be reconstructed using filtered backprojection (FBP) and iterative techniques are required. Iterative image reconstruction requires a system matrix that describes the geometry of the imaging system. Stored system matrices can become immensely large, making them impractical for storage on a typical desktopcomputer. Here we develop a method to reduce the storage size of optical CT system matrices through use of polar coordinate discretization while accounting for the refraction in optical CTsystems. A ray tracing simulator was developed to track the path of light rays as they traverse the different mediums of the optical CT scanner. Cartesian coordinate discretized system matrices (CCDSMs) and polar coordinate discretized system matrices (PCDSMs) were generated by discretizing the reconstruction area of the optical CT scanner into a Cartesian pixel grid and a polar coordinate pixel grid, respectively. The length of each ray through each pixel was calculated and used to populate the system matrices. To ensure equal weighting during iterative reconstruction, the radial rings of PCDSMs were asymmetrically spaced such that the area of each polar pixel was constant. Two clinical phantoms and several synthetic phantoms were produced and used to evaluate the reconstruction techniques under known conditions. Reconstructed images were analyzed in terms of spatial resolution, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), signal nonuniformity (SNU), and Gamma map passpercentage. A storage size reduction of 99.72% was found when comparing a PCDSM to a CCDSM with the same total number of pixels. Images reconstructed with a PCDSM were found to have superior SNR, CNR, SNU, and Gamma (1mm, 1%) pass percentage compared to those reconstructed with a CCDSM. Increasing spatial resolution in the radial direction with increasing radial distance was found in both PCDSM and CCDSM reconstructions due to the outer regions refracting light more severely. Images reconstructed with a PCDSM showed a decrease in spatial resolution in the azimuthal directions as radial distance increases, due to the widening of the polar pixels. However, this can be mitigated with only a slight increase in storage size by increasing the number of projections. A loss of spatial resolution in the radial direction within 5mm radially from center was found when reconstructing with a PCDSM, due to the large innermost pixels. However, this was remedied by increasing the number of radial rings within the PCDSM, yielding radial spatial resolution on par with images reconstructed with a CCDSM and a storage size reduction of 99.26%. Discretizing the image pixel elements in polar coordinates achieved a system matrix storage size reduction of 99.26% with only minimal reduction in the imagequality.

Cone beam computed tomography enhancement using feature‐embedded variational autoencoder with a perceptual loss function

AbstractImage‐Guided Radiation Therapy (IGRT) is a cancer treatment method. IGRT usually follows a fragmented treatment track. The weight loss of a patient causes the first treatment plan to be flawed. Medical experts can avert retaking Fan Beam Computed Tomography (FBCT) images before each session of the therapy if the Cone Beam Computed Tomography (CBCT), which is mounted on a Medical Linear Accelerator (LINAC), gives high‐quality images. Rather than improvising the CBCT machine, deep‐learning techniques can be used to enhance the CBCT images. This paper proposes a Feature‐Embedded Variational AutoEncoder (FE‐VAE) for CBCT image enhancement. A feature embedding is incorporated using a MultiResUNet‐based feature extractor to preserve structural information in the input image. A perceptual loss function, which is the product of Mean Absolute Error (MAE) and inverse Structural Similarity Index Measure (SSIM), is proposed in this work. The model is trained using Head‐and‐Neck (H&amp;N) CBCT‐FBCT pairs of 59 cancer patients. Our proposed architecture successfully generates images much closer to the ground truth FBCT images. The model gives an average peak signal‐to‐noise ratio of 32.89 dB, mean squared error of 297.36, MAE of 32.37 HU, and SSIM of 0.99. The trained model gave the least deviated SSIM and MAE, implying that the model is well‐optimised. The experimentation with different losses proves the prominence of the proposed loss function. The visual quality of the results obtained is also comparable with the ground truth. The results indicate that the model produces enhanced CBCT images. Hence, the proposed FE‐VAE is useful in fractionated radiotherapy to minimise the number of scanning sessions for replanning the dosimetry.

Investigation of the usability of cone-beam computed tomography images using digital radiography equipment for boron neutron capture therapy treatment planning in the sitting position

In boron neutron capture therapy (BNCT), treatment planning images are acquired in the recumbent position. However, treatment is occasionally performed in the sitting position. For BNCT treatment planning, we investigated the usability of cone-beam computed tomography (CBCT) images using digital radiography equipment that allows imaging in the sitting position. The dose calculation results in both CBCT and fan beam CT were in good agreement. This method will eliminate the posture difference between planning and treatment.

Fan beam CT image synthesis from cone beam CT image using nested residual UNet based conditional generative adversarial network.

A radiotherapy technique called Image-Guided Radiation Therapy adopts frequent imaging throughout a treatment session. Fan Beam Computed Tomography (FBCT) based planning followed by Cone Beam Computed Tomography (CBCT) based radiation delivery drastically improved the treatment accuracy. Furtherance in terms of radiation exposure and cost can be achieved if FBCT could be replaced with CBCT. This paper proposes a Conditional Generative Adversarial Network (CGAN) for CBCT-to-FBCT synthesis. Specifically, a new architecture called Nested Residual UNet (NR-UNet) is introduced as the generator of the CGAN. A composite loss function, which comprises adversarial loss, Mean Squared Error (MSE), and Gradient Difference Loss (GDL), is used with the generator. The CGAN utilises the inter-slice dependency in the input by taking three consecutive CBCT slices to generate an FBCT slice. The model is trained using Head-and-Neck(H&N) FBCT-CBCT images of 53 cancer patients. The synthetic images exhibited a Peak Signal-to-Noise Ratio of 34.04±0.93 dB, Structural Similarity Index Measure of 0.9751±0.001 and a Mean Absolute Error of 14.81±4.70 HU. On average, the proposed model guarantees an improvement in Contrast-to-Noise Ratio four times better than the input CBCT images. The model also minimised the MSE and alleviated blurriness. Compared to the CBCT-based plan, the synthetic image results in a treatment plan closer to the FBCT-based plan. The three-slice to single-slice translation captures the three-dimensional contextual information in the input. Besides, it withstands the computational complexity associated with a three-dimensional image synthesis model. Furthermore, the results demonstrate that the proposed model is superior to the state-of-the-art methods.

4DCT is long overdue for improvement.

4DCT is long overdue for improvement.

Identification of Heterotopic Mineralization and Adjacent Pathology in the Equine Fetlock Region by Low-Field Magnetic Resonance Imaging, Cone-Beam and Fan-Beam Computed Tomography

Heterotopic mineralization in equine distal limbs has been considered an incidental finding and little is known about its imaging features. The study aimed to identify heterotopic mineralization and adjacent pathology in the fetlock region with cone-beam (CB) computed tomography (CT), fan-beam (FB) CT, and low-field magnetic resonance imaging (MRI). Images from 12 equine cadaver limbs were examined for heterotopic mineralization and adjacent pathology and verified by macro-examination. Retrospective review of the CBCT/MR images from 2 standing horses was also included. CBCT and FBCT identified twelve mineralization's with homogeneous hyperattenuation: oblique-sesamoidean-ligament (5) without macroscopic abnormality; deep-digital-flexor-tendon (1) and suspensory-branch (6) with macroscopic abnormalities. MRI failed to identify all mineralization's, but detected suspensory branch splitting, and T2 and STIR hyperintensity in 4 suspensory-branches and 3 oblique-sesamoidean-ligaments. Macro-examination found corresponding disruption/splitting and discoloration. All modalities identified 7 ossified fragments showing cortical/trabecular pattern: capsular (1), palmar sagittal ridge (1), proximal phalanx (2) without macroscopic abnormality, and proximal sesamoid bones (3). On MRI, fragments were most identifiable on T1 images. All abaxial avulsions had suspensory-branch splitting on T1 images with T2 and STIR hyperintensity. Macro-examination showed ligament disruption/splitting and discoloration. Suspensory-branch/intersesamoidean ligament mineralization's were identified by CBCT in standing cases; 1 had associated T2 hyperintensity. Both CT systems were generally superior in identifying heterotopic mineralization's than MRI, while MRI provided information on soft tissue pathology related to the lesions, which may be important for management.