Flat-panel Cone-beam CT Research Articles

3D-printed large-area focused grid for scatter reduction in cone-beam CT.

Cone-beam computed tomography (CBCT) systems acquire volumetric data more efficiently than fan-beam or multislice CT, particularly when the anatomy of interest resides within the axial field-of-view of the detector and data can be acquired in one rotation. For such systems, scattered radiation remains a source of image quality degradation leading to increased noise, image artifacts, and CT number inaccuracies. Recent advances in metal additive manufacturing allow the production of highly focused antiscatter grids (2D-ASGs) that can be used to reduce scatter intensity, while preserving primary radiation transmission. We present the first implementation of a large-area, 2D-ASG for flat-panel CBCT, including grid-line artifact removal and related improvements in image quality. A 245 × 194 × 10 mm 2D-ASG was manufactured from chrome-cobalt alloy using laser powder-bed fusion (LPBF) (AM-400; Renishaw plc, New Mills Wotton-under-Edge, UK). The 2D-ASG had a square profile with a pitch of 9.09 lines/cm and 10:1 grid-ratio. The nominal 0.1mm grid septa were focused to a 732 mm x-ray source to optimize primary x-ray transmission and reduce grid-line shadowing at the detector. Powder-bed fusion ensured the structural stability of the ASG with no need for additional interseptal support. The 2D-ASG was coupled to a 0.139-mm element pitch flat-panel detector (DRX 3543, Carestream Health) and proper alignment was confirmed by consistent grid-line shadow thickness across the whole detector array. A 154-mm diameter CBCT image-quality-assurance phantom was imaged using a rotary stage and a ceiling-mounted, x-ray unit (Proteus XR/a, GE Medical Systems, 80kVp, 0.5mAs). Grid-line artifacts were removed using a combination of exposure-dependent gain correction and spatial-frequency, Fourier filtering. Projections were reconstructed using a Parker-weighted, FDK algorithm and voxels were spatially averaged to 357 × 357 × 595 µm to improve the signal-to-noise characteristics of the CBCT reconstruction. Finally, in order to compare image quality with and without scatter, the phantom was scanned again under the same CBCT conditions but with no 2D-ASG. No additional antiscatter (i.e., air-gap, bowtie filtration) strategies were used to evaluate the effects in image quality caused by the 2D-ASG alone. The large-area, 2D-ASG prototype was successfully designed and manufactured using LPBF. CBCT image-quality improvements using the 2D-ASG included: an overall 14.5% CNR increase across the volume; up to 48.8% CNR increase for low-contrast inserts inside the contrast plate of the QA phantom; and a 65% reduction of cupping artifact in axial profiles of water-filled cross sections of the phantom. Advanced image processing strategies to remove grid line artifacts did not affect the spatial resolution or geometric accuracy of the system. LPBF can be used to manufacture highly efficient, 2D-focused ASGs that can be easily coupled to clinical, flat-panel detectors. The implementation of ASGs in CBCT leads to reduced scatter-related artifacts, improved CT number accuracy, and enhanced CNR with no increased equivalent dose to the patient. Further improvements to image quality might be achieved with a combination of scatter-correction algorithms and iterative-reconstruction strategies. Finally, clinical applications where other scatter removal strategies are unfeasible might now achieve superior soft-tissue visualization and quantitative capabilities.

Flat-panel conebeam CT in the clinic: history and current state.

.Research into conebeam CT concepts began as soon as the first clinical single-slice CT scanner was conceived. Early implementations of conebeam CT in the 1980s focused on high-contrast applications where concurrent high resolution (), for visualization of small contrast-filled vessels, bones, or teeth, was an imaging requirement that could not be met by the contemporaneous CT scanners. However, the use of nonlinear imagers, e.g., x-ray image intensifiers, limited the clinical utility of the earliest diagnostic conebeam CT systems. The development of consumer-electronics large-area displays provided a technical foundation that was leveraged in the 1990s to first produce large-area digital x-ray detectors for use in radiography and then compact flat panels suitable for high-resolution and high-frame-rate conebeam CT. In this review, we show the concurrent evolution of digital flat panel (DFP) technology and clinical conebeam CT. We give a brief summary of conebeam CT reconstruction, followed by a brief review of the correction approaches for DFP-specific artifacts. The historical development and current status of flat-panel conebeam CT in four clinical areas—breast, fixed C-arm, image-guided radiation therapy, and extremity/head—is presented. Advances in DFP technology over the past two decades have led to improved visualization of high-contrast, high-resolution clinical tasks, and image quality now approaches the soft-tissue contrast resolution that is the standard in clinical CT. Future technical developments in DFPs will enable an even broader range of clinical applications; research in the arena of flat-panel CT shows no signs of slowing down.

High-resolution model-based material decomposition in dual-layer flat-panel CBCT.

Spectral CT uses energy-dependent measurements that enable material discrimination in addition to reconstruction of structural information. Flat-panel detectors (FPDs) have been widely used in dedicated and interventional systems to deliver high spatial resolution, volumetric cone-beam CT (CBCT) in compact and OR-friendly designs. In this work, we derive a model-based method that facilitates high-resolution material decomposition in a spectral CBCT system equipped with a prototype dual-layer FPD. Through high-fidelity modeling of multilayer detector, we seek to avoid resolution loss that is present in more traditional processing and decomposition approaches. A physical model for spectral measurements in dual-layer flat-panel CBCT is developed including layer-dependent differences in system geometry, spectral sensitivities, and detector blur (e.g., due to varied scintillator thicknesses). This forward model is integrated into a model-based material decomposition (MBMD) method based on minimization of a penalized weighted least-squared (PWLS) objective function. The noise and resolution performance of this approach was compared with traditional projection-domain decomposition (PDD) and image-domain decomposition (IDD) approaches as well as one-step MBMD with lower-fidelity models that use approximated geometry, projection interpolation, or an idealized system geometry without system blur model. Physical studies using high-resolution three-dimensional (3D)-printed water-iodine phantoms were conducted to demonstrate the high-resolution imaging performance of the compared decomposition methods in iodine basis images and synthetic monoenergetic images. Physical experiments demonstrate that the MBMD methods incorporating an accurate geometry model can yield higher spatial resolution iodine basis images and synthetic monoenergetic images than PDD and IDD results at the same noise level. MBMD with blur modeling can further improve the spatial-resolution compared with the decomposition results obtained with IDD, PDD, and MBMD methods with lower-fidelity models. Using the MBMD without or with blur model can increase the absolute modulation at 1.75 lp/mm by 10% and 22% compared with IDD at the same noise level. The proposed model-based material decomposition method for a dual-layer flat-panel CBCT system has demonstrated an ability to extend high-resolution performance through sophisticated detector modeling including the layer-dependent blur. The proposed work has the potential to not only facilitate high-resolution spectral CT in interventional and dedicated CBCT systems, but may also provide the opportunity to evaluate different flat-panel design trade-offs including multilayer FPDs with mismatched geometries, scintillator thicknesses, and spectral sensitivities.

Novel flat-panel cone-beam CT compared to multi-detector CT for assessment of acute ischemic stroke: A prospective study

PurposeCone beam CT (CBCT) imaging assessment of acute ischemic stroke (AIS) patients with large-vessel occlusion (LVO) in the angiosuite may improve stroke workflow and decrease time to recanalization. In order for this workflow to gain widespread acceptance, current CBCT imaging needs further development to improve image quality. Our study aimed to compare the image quality of a new CBCT protocol performed directly in the angiosuite with imaging from multidetector CT as a gold standard. MethodsAIS patients with an LVO who were candidates for endovascular treatment were prospectively included in this study. Following conventional multidetector CT (MDCT), patients underwent unenhanced cone beam CT (XperCT, Philips) imaging in the angiosuite, using two different protocols: a standard 20.8 s XperCT and/or an improved 10.4 s XperCT protocol. Images were evaluated using both qualitative and quantitative methods. ResultsWe included 65 patients in the study. Patients received CBCT imaging prior to endovascular treatment; 18 patients were assessed with a standard 20.8 s protocol scans and 47 with a newer 10.4 s scan. The quantitative analysis showed that the mean contrast-to-noise ratio (CNR) was significantly higher for the newer 10.4 s protocol compared with the 20.8 s protocol (2.08 +/- 0.64 vs. 1.15 +/- 0.27, p < 0.004) and the mean image noise was significantly lower for the 10.4 s XperCTs when compared with the 20.8 s XperCTs (6.30 +/- 1.34 vs. 7.82 +/- 2.03, p=<0.003). Qualitative analysis, including 6 measures of image quality, demonstrated that 74.1 % of the 10.4 s XperCT scans were ranked as ‘Acceptable’ for assessing parenchymal imaging in AIS patients(scoring 3–5 points on a 5-point Likert-scale), compared with 32.4 % of the standard 20.8 s XperCT and 100 % of the MDCT scans. Compared to the MDCT studies, 83 % of the 10.4 s XperCT scans were deemed sufficient image quality for a direct-to-angiosuite selection, compared to only 11 % for the standard 20.8 s scans. The largest image quality improvements included grey/white matter differentiation (59 % improvement), and reduction of image noise and artefacts (63 % & 50 % improvement, respectively). ConclusionsContinued advances in cone-beam CT allow marked improvements in image quality for the assessment of brain parenchyma, which supports a direct-to-angiosuite approach for AIS patients eligible for thrombectomy treatment.

What Is the Diagnostic Accuracy of Flat-panel Cone-beam CT Arthrography for Diagnosis of Scapholunate Ligament Tears?

Cone beam CT (CBCT) is a widely available technique with possible indications in carpal ligament injuries. The accuracy of CBCT arthrography in diagnosing traumatic tears of the scapholunate ligament has not been reported. (1) What is the diagnostic accuracy of CBCT and how does it relate to the accuracy of multislice CT arthrography and conventional arthrography in diagnosing scapholunate ligament tears? (2) What is the estimated magnitude of skin radiation doses of each method? This secondary analysis of a previous prospective study included 71 men and women with suspected scapholunate ligament tears and indications for arthroscopy. Preoperative imaging was conventional arthrography and either MSCT arthrography for the first half of patients to be included (n = 36) or flat-panel CBCT arthrography for the remaining patients (n = 35). Index tests identified therapy-relevant SLL tears with dorsal or complete SLL ruptures, and these tears were compared with relevant SLL tears which were determined through arthroscopy as Geissler Stadium III and IV by probing the instable SL joint with a microhook or arthroscope. These injuries were treated by open ligament repair and Kirschner wire fixation. Accuracy values and 95% confidence intervals were calculated. Additional estimates of the radiation skin doses of each CBCT exam and two MSCT protocols were subsequently calculated using dose area products, dose length products, and CT dose indices. The diagnostic accuracy was high for all imaging methods. 95% CIs were broadly overlapping and therefore did not indicate differences between the diagnostic groups: Sensitivity of CBCT arthrography was 100% (95% CI 77 to 100), specificity was 95% (95% CI 76 to 99.9), positive predictive value was 93% (95% CI 68 to 99.8), and negative predictive value was 100% (95% CI 83 to 100). For MSCT arthrography, the sensitivity was 92% (95% CI 64 to 99.8), specificity was 96% (95% CI 78 to 99.9), positive predictive value was 92% (95% CI 64 to 99.8), and negative predictive value was 96% (95% CI 78 to 99.9). For conventional arthrography, the sensitivity was comparably high: 96% (95% CI 81 to 99.9). Specificity was (81% [95% CI 67 to 92]); the positive predictive value was 77% (95% CI 59 to 89) and negative predictive value was 97% (95% CI 86 to 99.9). Estimated mean (range) radiation skin doses were reported in a descriptive fashion and were 12.9 mSv (4.5 to 24.9) for conventional arthrography, and 3.2 mSv (2.0 to 4.8) for CBCT arthrography. Estimated radiation skin doses were 0.2 mSv and 12 mSv for MSCT arthrography, depending on the protocol. Flat-panel CBCT arthrography can be recommended as an accurate technique to diagnose scapholunate ligament injuries after wrist trauma. Estimated skin doses are low for CBCT arthrography and adapted MSCT arthrography protocols. Level III, diagnostic study.

Reduction of beam hardening artifacts on real C-arm CT data using polychromatic statistical image reconstruction

PurposeThis work aims at the compensation of beam hardening artifacts by the means of an extended three-dimensional polychromatic statistical reconstruction to be applied for flat panel cone-beam CT. MethodsWe implemented this reconstruction technique as being introduced by Elbakri et al. (2002) [1] for a multi-GPU system, assuming the underlying object consists of several well-defined materials. Furthermore, we assume one voxel can only contain an overlap of at most two materials, depending on its density value. Given the X-ray spectrum, the procedure enables to reconstruct the energy-dependent attenuation values of the volume. ResultsWe evaluated the method by using flat-panel cone-beam CT measurements of structures containing small metal objects and clinical head scan data. In comparison with the water-corrected filtered backprojection, as well as a maximum likelihood reconstruction with a consistency-based beam hardening correction, our method features clearly reduced beam hardening artifacts and a more accurate shape of metal objects. ConclusionsOur multi-GPU implementation of the polychromatic reconstruction, which does not require any image pre-segmentation, clearly outperforms the standard reconstructions of objects, with respect to beam hardening even in the presence of metal objects inside the volume. However, remaining artifacts, caused mainly by the limited dynamic range of the detector, may have to be addressed in future work.

Predicting image properties in penalized-likelihood reconstructions of flat-panel CBCT.

Model-based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods exhibit data-dependent and shift-variant properties. Image quality predictors have been derived to prospectively estimate local noise and spatial resolution, facilitating both system hardware design and tuning of reconstruction methods. However, current MBIR image quality predictors rely on idealized system models, ignoring physical blurring effects and noise correlations found in real systems. In this work, we develop and validate a new set of predictors using a physical system model specific to flat-panel cone-beam CT (FP-CBCT). Physical models appropriate for integration with MBIR analysis are developed and parameterized to represent nonidealities in FP projection data including focal spot blur, scintillator blur, detector aperture effect, and noise correlations. Flat-panel-specific predictors for local spatial resolution and local noise properties in PL reconstructions are developed based on these realistic physical models. Estimation accuracy of conventional (idealized) and FP-specific predictors is investigated and validated against experimental CBCT measurements using specialized phantoms. Validation studies show that flat-panel-specific predictors can accurately estimate the local spatial resolution and noise properties, while conventional predictors show significant deviations in the magnitude and scale of the spatial resolution and local noise. The proposed predictors show accurate estimations over a range of imaging conditions including varying x-ray technique and regularization strength. The conventional spatial resolution prediction is sharper than ground truth. Using conventional spatial resolution predictor, the full width at half maximum (FWHM) of local point spread function (PSF) is underestimated by 0.2 mm. This mismatch is mostly eliminated in FP-specific prediction. The general shape and amplitude of local noise power spectrum (NPS) FP-specific predictions are consistent with measurement, while the conventional predictions underestimated the noise level by 70%. The proposed image quality predictors permit accurate estimation of local spatial resolution and noise properties for PL reconstruction, accounting for dependencies on the system geometry, x-ray technique, and patient-specific anatomy in real FP-CBCT. Such tools enable prospective analysis of image quality for a range of goals including novel system and acquisition design, adaptive and task-driven imaging, and tuning of MBIR for robust and reliable behavior.

Percutaneous bone biopsy using a flat-panel cone beam computed tomography virtual navigation system.

ObjectivesTo assess the clinical role of flat-panel cone beam CT (CBCT) in performing percutaneous needle biopsy (PNB) of bone lesions. Flat-panel cone beam CT systems have been used as a guidance tool for performing percutaneous biopsy. Real-time fluoroscopy and virtual navigation systems help simplify needle path planning and shorten procedure times.MethodsFrom March 2012 to March 2016, 80 patients with 80 bone lesions were retrospectively enrolled in the study in Zhengzhou city of China. Technical success, diagnostic accuracy, puncture performance, procedure time, complications, and effective radiation exposure were calculated.ResultsAll biopsies were technically successful (100%). Sufficient tissue for histopathological analysis was obtained in 75 of 80 cases. The sensitivity of PNB of bone lesions was 95.5%, the specificity was 83.3%, and accuracy was 93.7%. The mean scoring of puncture performance was 3.9 ± 1.3. The mean total procedure time was 13.20 ± 4.4 min, resulting in a mean exposure dose of 11.3 ± 5.1 mSv. The complication rate was 8.7%.ConclusionPercutaneous bone biopsy using CBCT is a safe and effective method that simplifies needle path planning and shortens procedure times.

Spatial Resolution and Noise Prediction in Flat-Panel Cone-Beam CT Penalized-likelihood Reconstruction.

Model based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods have data-dependent and shift-variant image properties. Predictors of local reconstructed noise and resolution have found application in a number of methods that seek to understand, control, and optimize CT data acquisition and reconstruction parameters in a prospective fashion (as opposed to studies based on exhaustive evaluation). However, previous MBIR prediction methods have relied on idealized system models. In this work, we develop and validate new predictors using accurate physical models specific to flat-panel CT systems. Novel predictors for estimation of local spatial resolution and noise properties are developed for PL reconstruction that include a physical model for blur and correlated noise in flat-panel cone-beam CT (CBCT) acquisitions. Prospective predictions (e.g., without reconstruction) of local point spread function and and local noise power spectrum (NPS) model are applied, compared, and validated using a flat-panel CBCT test bench. Comparisons between prediction and physical measurements show excellent agreement for both spatial resolution and noise properties. In comparison, traditional prediction methods (that ignore blur/correlation found in flat-panel data) fail to capture important data characteristics and show significant mismatch. Novel image property predictors permit prospective assessment of flat-panel CBCT using MBIR. Such predictors enable standard and task-based performance assessments, and are well-suited to evaluation, control, and optimization of the CT imaging chain (e.g., x-ray technique, reconstruction parameters, novel data acquisition methods, etc.) for improved imaging performance and/or dose utilization.

WE-FG-207A-03: Low-Dose Cone-Beam Breast CT: Physics and Technology Development

WE-FG-207A-03: Low-Dose Cone-Beam Breast CT: Physics and Technology Development

WE-FG-207A-02: Why We Need Breast CT? - Clinical Perspective

WE-FG-207A-02: Why We Need Breast CT? - Clinical Perspective

WE-FG-207A-04: Performance Characteristics of Photon-Counting Breast CT

WE-FG-207A-04: Performance Characteristics of Photon-Counting Breast CT

WE-FG-207A-00: Advances in Dedicated Breast CT

WE-FG-207A-00: Advances in Dedicated Breast CT

WE-FG-207A-01: Introduction to Dedicated Breast CT - Early Studies

WE-FG-207A-01: Introduction to Dedicated Breast CT - Early Studies

WE-FG-207A-05: Dedicated Breast CT as a Diagnostic Imaging Tool: Physics and Clinical Feasibility

WE-FG-207A-05: Dedicated Breast CT as a Diagnostic Imaging Tool: Physics and Clinical Feasibility

View-dependent geometric calibration for offset flat-panel cone beam computed tomography systems

Geometric parameters that define the geometry of imaging systems are crucial for image reconstruction and image quality in x-ray computed tomography (CT). The problem of determining geometric parameters for an offset flat-panel cone beam CT (CBCT) system, a recently introduced modality with a large field of view, with the assumption of an unstable mechanism and geometric parameters that vary in each view, is considered. To accurately and rapidly find the geometric parameters for each projection view, we use the projection matrix method and design a dedicated phantom that is partially visible in all projection views. The phantom consists of balls distributed symmetrically in a cylinder to ensure the inclusion of the phantom in all views, and a large portion of the phantom is covered in the projection image. To efficiently use calibrated geometric information in the reconstruction process and get rid of approximation errors, instead of decomposing the projection matrix into actual geometric parameters that are manually corrected before being used in reconstruction, as in conventional methods, we directly use the projection matrix and its pseudo-inverse in projection and backprojection operations of reconstruction algorithms. The experiments illustrate the efficacy of the proposed method with a real offset flat-panel CBCT system in dental imaging.

Nonlinear Statistical Reconstruction for Flat-Panel Cone-Beam CT with Blur and Correlated Noise Models.

Flat-panel cone-beam CT (FP-CBCT) is a promising imaging modality, partly due to its potential for high spatial resolution reconstructions in relatively compact scanners. Despite this potential, FP-CBCT can face difficulty resolving important fine scale structures (e.g, trabecular details in dedicated extremities scanners and microcalcifications in dedicated CBCT mammography). Model-based methods offer one opportunity to improve high-resolution performance without any hardware changes. Previous work, based on a linearized forward model, demonstrated improved performance when both system blur and spatial correlations characteristics of FP-CBCT systems are modeled. Unfortunately, the linearized model relies on a staged processing approach that complicates tuning parameter selection and can limit the finest achievable spatial resolution. In this work, we present an alternative scheme that leverages a full nonlinear forward model with both system blur and spatially correlated noise. A likelihood-based objective function is derived from this forward model and we derive an iterative optimization algorithm for its solution. The proposed approach is evaluated in simulation studies using a digital extremities phantom and resolution-noise trade-offs are quantitatively evaluated. The correlated nonlinear model outperformed both the uncorrelated nonlinear model and the staged linearized technique with up to a 86% reduction in variance at matched spatial resolution. Additionally, the nonlinear models could achieve finer spatial resolution (correlated: 0.10 mm, uncorrelated: 0.11 mm) than the linear correlated model (0.15 mm), and traditional FDK (0.40 mm). This suggests the proposed nonlinear approach may be an important tool in improving performance for high-resolution clinical applications.

Model-based iterative reconstruction for flat-panel cone-beam CT with focal spot blur, detector blur, and correlated noise

While model-based reconstruction methods have been successfully applied to flat-panel cone-beam CT (FP-CBCT) systems, typical implementations ignore both spatial correlations in the projection data as well as system blurs due to the detector and focal spot in the x-ray source. In this work, we develop a forward model for flat-panel-based systems that includes blur and noise correlation associated with finite focal spot size and an indirect detector (e.g. scintillator). This forward model is used to develop a staged reconstruction framework where projection data are deconvolved and log-transformed, followed by a generalized least-squares reconstruction that utilizes a non-diagonal statistical weighting to account for the correlation that arises from the acquisition and data processing chain. We investigate the performance of this novel reconstruction approach in both simulated data and in CBCT test-bench data. In comparison to traditional filtered backprojection and model-based methods that ignore noise correlation, the proposed approach yields a superior noise-resolution tradeoff. For example, for a system with 0.34 mm FWHM scintillator blur and 0.70 FWHM focal spot blur, using the correlated noise model instead of an uncorrelated noise model increased resolution by 42% (with variance matched at 6.9 × 10−8 mm−2). While this advantage holds across a wide range of systems with differing blur characteristics, the improvements are greatest for systems where source blur is larger than detector blur.

Dental Flat Panel Conebeam CT in the Evaluation of Patients with Inflammatory Sinonasal Disease: Diagnostic Efficacy and Radiation Dose Savings

CT is the imaging modality of choice to study the paranasal sinuses; unfortunately, it involves significant radiation dose. Our aim was to assess the diagnostic validity, image quality, and radiation-dose savings of dental conebeam CT in the evaluation of patients with suspected inflammatory disorders of the paranasal sinuses. We prospectively studied 40 patients with suspected inflammatory disorders of the sinuses with dental conebeam CT and standard CT. Two radiologists analyzed the images independently, blinded to clinical information. The image quality of both techniques and the diagnostic validity of dental conebeam CT compared with the reference standard CT were assessed by using 3 different scoring systems. Image noise, signal-to-noise ratio, and contrast-to-noise ratio were calculated for both techniques. The absorbed radiation dose to the lenses and thyroid and parotid glands was measured by using a phantom and dosimeter chips. The effective radiation dose for CT was calculated. All dental conebeam CT scans were judged of diagnostic quality. Compared with CT, the conebeam CT image noise was 37.3% higher (P < .001) and the SNR of the bone was 75% lower (P < .001). The effective dose of our conebeam CT protocol was 23 μSv. Compared with CT, the absorbed radiation dose to the lenses and parotid and thyroid glands with conebeam CT was 4%, 7.8%, and 7.3% of the dose delivered to the same organs by conventional CT (P < .001). Dental conebeam CT is a valid imaging procedure for the evaluation of patients with inflammatory sinonasal disorders.

Low-dose preview for patient-specific, task-specific technique selection in cone-beam CT.

A method is presented for generating simulated low-dose cone-beam CT (CBCT) preview images from which patient- and task-specific minimum-dose protocols can be confidently selected prospectively in clinical scenarios involving repeat scans. In clinical scenarios involving a series of CBCT images, the low-dose preview (LDP) method operates upon the first scan to create a projection dataset that accurately simulates the effects of dose reduction in subsequent scans by injecting noise of proper magnitude and correlation, including both quantum and electronic readout noise as important components of image noise in flat-panel detector CBCT. Experiments were conducted to validate the LDP method in both a head phantom and a cadaveric torso by performing CBCT acquisitions spanning a wide dose range (head: 0.8-13.2 mGy, body: 0.8-12.4 mGy) with a prototype mobile C-arm system. After injecting correlated noise to simulate dose reduction, the projections were reconstructed using both conventional filtered backprojection (FBP) and an iterative, model-based image reconstruction method (MBIR). The LDP images were then compared to real CBCT images in terms of noise magnitude, noise-power spectrum (NPS), spatial resolution, contrast, and artifacts. For both FBP and MBIR, the LDP images exhibited accurate levels of spatial resolution and contrast that were unaffected by the correlated noise injection, as expected. Furthermore, the LDP image noise magnitude and NPS were in strong agreement with real CBCT images acquired at the corresponding, reduced dose level across the entire dose range considered. The noise magnitude agreed within 7% for both the head phantom and cadaveric torso, and the NPS showed a similar level of agreement up to the Nyquist frequency. Therefore, the LDP images were highly representative of real image quality across a broad range of dose and reconstruction methods. On the other hand, naïve injection ofuncorrelated noise resulted in strong underestimation of the true noise, which would lead to overly optimistic predictions of dose reduction. Correlated noise injection is essential to accurate simulation of CBCT image quality at reduced dose. With the proposed LDP method, the user can prospectively select patient-specific, minimum-dose protocols (viz., acquisition technique and reconstruction method) suitable to a particular imaging task and to the user's own observer preferences for CBCT scans following the first acquisition. The method could provide dose reduction in common clinical scenarios involving multiple CBCT scans, such as image-guided surgery and radiotherapy.