Thickness and design features of clinical cranial implants-what should automated methods strive to replicate?

PURPOSE: New deep learning and statistical shape modelling approaches aim to automate the design process for patient-specific cranial implants, as highlighted by the MICCAI AutoImplant Challenges. To ensure applicability, it is important to determine if the training data used in developing these algorithms represent the geometry of implants designed for clinical use. METHODS: Calavera Surgical Design provided a dataset of 206 post-craniectomy skull geometries and their clinically used implants. The MUG500+ dataset includes 29 post-craniectomy skull geometries and implants designed for automating design. For both implant and skull shapes, the inner and outer cortical surfaces were segmented, and the thickness between them was measured. For the implants, a 'rim' was defined that transitions from the repaired defect to the surrounding skull. For unilateral defect cases, skull implants were mirrored to the contra-lateral side and thickness differences were quantified. RESULTS: The average thickness of the clinically used implants was 6.0 ± 0.5 mm, which approximates the thickness on the contra-lateral side of the skull (relative difference of -0.3 ± 1.4 mm). The average thickness of the MUG500+ implants was 2.9 ± 1.0 mm, significantly thinner than the intact skull thickness (relative difference of 2.9 ± 1.2 mm). Rim transitions in the clinical implants (average width of 8.3 ± 3.4 mm) were used to cap and create a smooth boundary with the skull. CONCLUSIONS: For implant modelers or manufacturers, this shape analysis quantified differences of cranial implants (thickness, rim width, surface area, and volume) to help guide future automated design algorithms. After skull completion, a thicker implant can be more versatile for cases involving muscle hollowing or thin skulls, and wider rims can smooth over the defect margins to provide more stability. For clinicians, the differing measurements and implant designs can help inform the options available for their patient specific treatment.

Effect of Breast Screening Regimen on Breast Cancer Outcomes: A Modeling Study.

Guidelines vary for the age at which to begin breast cancer screening and the interval between examinations. A validated computer model was used to compare estimated outcomes between various screening regimens. The OncoSim-Breast microsimulation model (Canadian Partnership Against Cancer) was used to simulate a cohort of 1.53 million Canadian women born in 1975. The effect of screening regimen on absolute breast cancer mortality rates, stage at diagnosis, number needed to be screened to avert a breast cancer death or save a life year, abnormal recall rates and negative biopsy rates was examined for unscreened women or those entering screening at age 40 or 50 and screened annually or biennially to age 74. Compared to no screening, absolute mortality reduction was 4.6 (biennial 50-74), 5.9 (biennial 40-74) and 7.9 (annual 40-74) fewer deaths per 1000 women. The absolute rate of diagnosis of advanced cancers (Stage 2, 3 and 4) falls in favor of earlier stages as the number of lifetime screens increases. Annual screening beginning at age 40 until age 74 would provide an additional reduction of 2 and 3.3 breast cancer deaths per 1000 women compared to biennial screening beginning at ages 40 and 50, respectively. There is a corresponding drop in the absolute number of Stage 2, 3 and 4 cancers diagnosed.

Audit of data from examination image headers collected for quality assurance in the ECOG-ACRIN EA1151 tomosynthesis mammographic imaging screening trial (TMIST).

PURPOSE: A comprehensive, centrally-monitored physics quality control (QC) program was developed for the Tomosynthesis Imaging Screening Trial (TMIST), a randomized controlled trial of digital breast tomosynthesis (TM) versus digital mammography (DM) for cancer screening. As part of the program, in addition to a set of phantom-based tests, de-identified data on image acquisition and processing parameters were captured from the DICOM headers of all individual patient images in the trial. These data were analyzed to assess the potential usefulness of header data from digital mammograms and tomosynthesis images of patients for quality assurance in breast imaging. METHODS: Data were automatically extracted from the headers of all de-identified patient mammograms and tomosynthesis images in the TMIST study. Image acquisition parameters and estimated radiation doses were tracked for individual sites, systems and across system types. These parameters included (among others) kV, target/filter use, number of acquired views per examination, AEC mode, compression thickness and force and detector temperature. Consistency of manually entered study data parameters (subject ID, screening time-point) from TMIST was evaluated. Preliminary observations from the program are presented. RESULTS: We report on data from 812 651 images from 135 525 examinations acquired between October, 2017 and December, 2022. Data came from 6 system models from 3 manufacturers. There was greater variability both in the number of views used and in the estimated (proxy) doses received in DM exams compared to TM. Mean proxy doses per examination varied among manufacturers from 2.76-4.54 mGy for DM and 3-4.84 mGy for the tomosynthesis component in the TM arm with maximum examination proxy doses of 20 and 26 mGy for DM and TM respectively. Mean proxy doses per examination for the combination examination in TM (tomosynthesis plus digital mammography) varied from 6.6 to 7.6 mGy among manufacturers with a maximum of 44.5 mGy. CONCLUSIONS: Overall, modern digital mammography and tomosynthesis systems used in TMIST have operated very reliably. Doses vary considerably due to variation in the number of views per examination, thickness and fibro-glandularity of the breast, and choices in the use of synthesized versus actual 2D mammography in the TM examination. These data may also be useful in predicting equipment problems. Header information is valuable not only for automated QC, but also for cross-checking accuracy and consistency of data in a clinical study.

Quality control for digital tomosynthesis in the ECOG-ACRIN EA1151 TMIST trial.

BACKGROUND: The Tomosynthesis Mammography Imaging Screening Trial (TMIST), EA1151 conducted by the Eastern Cooperative Oncology Group (ECOG)/American College of Radiology Imaging Network (ACRIN) is a randomized clinical trial designed to assess the effectiveness for breast cancer screening of digital breast tomosynthesis (TM) compared to digital mammography (DM). Equipment from multiple vendors is being used in the study. PURPOSE: For the findings of the study to be valid and capture the true capacities of the two technology types, it is important that all equipment is operated within appropriate parameters with regard to image quality and dose. A harmonized QC program was established by a core physics team. Since there are over 120 trial sites, a centralized, automated QC program was chosen as the most practical design. This report presents results of the weekly QC testing program. A companion paper will review quality monitoring based on data from the headers of the patient images. METHODS: Study images are collected centrally after de-identification using the "TRIAD" application developed by ACR. The core physics team devised and implemented a minimal set of quality control (QC) tests to evaluate the tomosynthesis and 2D mammography systems. Weekly, monthly and annual testing is performed by the site mammography technologists with images submitted directly to the physics core. The weekly physics QC tests are described: SDNR of a low-contrast mass object, artifact spread, spatial resolution, tracking of technical factors, and in-slice noise power spectra. RESULTS: As of December 31, 2022 (5 years), 145 sites with 411 machines had submitted QC data. A total of 136 742 TMIST participant screening imaging studies had been performed. The 5th and 95th percentile mean glandular doses for a single tomosynthesis exposure to a 4.0 cm thick PMMA phantom ("standard breast phantom") were 1.24 and 1.68 mGy respectively. The largest sources of QC non-conformance were: operator error, not following the QC protocol exactly, unreported software updates and preventive maintenance activities that affected QC setpoints. Noise power spectra were measured, however, standardization of performance targets across machine types and software revisions was difficult. Nevertheless, for each machine type, test measurement results were very consistent when the protocol was followed. Deviations in test results were mostly related to software and hardware changes. CONCLUSION: Most systems performed very consistently. Although this is a harmonized program using identical phantoms and testing protocols, it is not appropriate to apply universal threshold or target metrics across the machine types because the systems have different non-linear reconstruction algorithms and image display filters. It was found to be more useful to assess pass/fail criteria in terms of relative deviations from baseline values established when a system is first characterized and after equipment is changed. Generally, systems which needed repair failed suddenly, but in retrospect, for a few cases, drops in SDNR and increases in mAs were observed prior to tube failure. TMIST is registered as NCT03233191 by Clinicaltrials.gov.

Capturing the True Cost of Breast Cancer Treatment: Molecular Subtype and Stage-Specific per-Case Activity-Based Costing.

BACKGROUND: Breast cancer (BC) treatment is rapidly evolving with new and costly therapeutics. Existing costing models have a limited ability to capture current treatment costs. We used an Activity-Based Costing (ABC) method to determine a per-case cost for BC treatment by stage and molecular subtype. METHODS: ABC was used to proportionally integrate multidisciplinary evidence-based patient and provider treatment options for BC, yielding a per-case cost for the total duration of treatment by stage and molecular subtype. Diagnostic imaging, pathology, surgery, radiation therapy, systemic therapy, inpatient, emergency, home care and palliative care costs were included. RESULTS: BC treatment costs were higher than noted in previous studies and varied widely by molecular subtype. Cost increased exponentially with the stage of disease. The per-case cost for treatment (2023C$) for DCIS was C$ 14,505, and the mean costs for all subtypes were C$ 39,263, C$ 76,446, C$ 97,668 and C$ 370,398 for stage I, II, III and IV BC, respectively. Stage IV costs were as high as C$ 516,415 per case. When weighted by the proportion of molecular subtype in the population, case costs were C$ 31,749, C$ 66,758, C$ 111,368 and C$ 289,598 for stage I, II, III and IV BC, respectively. The magnitude of cost differential was up to 10.9 times for stage IV compared to stage I, 4.4 times for stage III compared to stage I and 35.6 times for stage IV compared to DCIS. CONCLUSION: The cost of BC treatment is rapidly escalating with novel therapies and increasing survival, resulting in an exponential increase in treatment costs for later-stage disease. We provide real-time, case-based costing for BC treatment which will allow for the assessment of health system economic impacts and an accurate understanding of the cost-effectiveness of screening.

Accuracy of Orbital Shape Reconstruction-Comparative Analysis of Errors in Implant Shape Versus Implant Positioning: A Cadaveric Study.

INTRODUCTION: Orbital blowout fractures are commonly reconstructed with implants shaped to repair orbital cavity defects, restore ocular position and projection, and correct diplopia. Orbital implant shaping has traditionally been performed manually by surgeons, with more recent use of computer-assisted design (CAD). Accuracy of implant placement is also key to reconstruction. This study compares the placement accuracy of orbital implants, testing the hypothesis that CAD-shaped implants indexed to patient anatomy will better restore orbit geometry compared with manually shaped implants and manually placed implants. METHODS: The placement accuracy of orbital implants was assessed within a cadaveric blowout fracture model (3 skulls, 6 orbits) via 3-dimensional CT analysis. Defects were repaired with 4 different techniques: manually placed-manually shaped composite (titanium-reinforced porous polyethylene), manually placed CAD composite, indexed placed CAD composite, and indexed placed CAD titanium mesh. RESULTS: Implant placement accuracy differed significantly with the implant preparation method ( P =0.01). Indexing significantly improved the placement accuracy ( P =0.002). Indexed placed titanium mesh CAD implants (1.42±0.33 mm) were positioned significantly closer to the intact surface versus manually placed-manually shaped composite implants (2.12±0.39 mm). DISCUSSION: Computer-assisted design implants indexed to patient geometry yielded average errors below the acceptable threshold (2 mm) for enophthalmos and diplopia. This study highlights the importance of adequately indexing CAD-designed implants to patient geometry to ensure accurate orbital reconstructions.

Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge.

Cranial implants are commonly used for surgical repair of craniectomy-induced skull defects. These implants are usually generated offline and may require days to weeks to be available. An automated implant design process combined with onsite manufacturing facilities can guarantee immediate implant availability and avoid secondary intervention. To address this need, the AutoImplant II challenge was organized in conjunction with MICCAI 2021, catering for the unmet clinical and computational requirements of automatic cranial implant design. The first edition of AutoImplant (AutoImplant I, 2020) demonstrated the general capabilities and effectiveness of data-driven approaches, including deep learning, for a skull shape completion task on synthetic defects. The second AutoImplant challenge (i.e., AutoImplant II, 2021) built upon the first by adding real clinical craniectomy cases as well as additional synthetic imaging data. The AutoImplant II challenge consisted of three tracks. Tracks 1 and 3 used skull images with synthetic defects to evaluate the ability of submitted approaches to generate implants that recreate the original skull shape. Track 3 consisted of the data from the first challenge (i.e., 100 cases for training, and 110 for evaluation), and Track 1 provided 570 training and 100 validation cases aimed at evaluating skull shape completion algorithms at diverse defect patterns. Track 2 also made progress over the first challenge by providing 11 clinically defective skulls and evaluating the submitted implant designs on these clinical cases. The submitted designs were evaluated quantitatively against imaging data from post-craniectomy as well as by an experienced neurosurgeon. Submissions to these challenge tasks made substantial progress in addressing issues such as generalizability, computational efficiency, data augmentation, and implant refinement. This paper serves as a comprehensive summary and comparison of the submissions to the AutoImplant II challenge. Codes and models are available at https://github.com/Jianningli/Autoimplant_II.

Effects of ionizing radiation exposure during pregnancy.

PURPOSE: To review the effects of ionizing radiation to the conceptus and the relationship to the timing of the exposure during pregnancy. To consider strategies that would mitigate potential harms associated with exposure to ionizing radiation during pregnancy. METHODS: Data reported in the peer-reviewed literature on entrance KERMA received from specific radiological examinations were combined with published results from experiment or Monte Carlo modeling of tissue and organ doses per entrance KERMA to estimate total doses that could be received from specific procedures. Data reported in the peer-reviewed literature on dose mitigation strategies, best practices for shielding, consent, counseling and emerging technologies were reviewed. RESULTS: For procedures utilizing ionizing radiation for which the conceptus is not included in the primary radiation beam, typical doses are well below the threshold for causing tissue reactions and the risk of induction of childhood cancer is low. For procedures that include the conceptus in the primary radiation field, longer fluoroscopic interventional procedures or multiphase/multiple exposures potentially could approach or exceed thresholds for tissue reactions and the risk of cancer induction must be weighed against the expected risk/benefit of performing (or not) the imaging examination. Gonadal shielding is no longer considered best practice. Emerging technologies such as whole-body DWI/MRI, dual-energy CT and ultralow dose studies are gaining importance for overall dose reduction strategies. CONCLUSION: The ALARA principle, considering potential benefits and risks should be followed with respect to the use of ionizing radiation. Nevertheless, as Wieseler et al. (2010) state, "no examination should be withheld when an important clinical diagnosis is under consideration." Best practices require updates on current available technologies and guidelines.

Overdetection of Breast Cancer.

Overdetection (often referred to as overdiagnosis) of cancer is the detection of disease, such as through a screening program, that would otherwise remain occult through an individual's life. In the context of screening, this could occur for cancers that were slow growing or indolent, or simply because an unscreened individual would have died from some other cause before the cancer had surfaced clinically. The main harm associated with overdetection is the subsequent overdiagnosis and overtreatment of disease. In this article, the phenomenon is reviewed, the methods of estimation of overdetection are discussed and reasons for variability in such estimates are given, with emphasis on an analysis using Canadian data. Microsimulation modeling is used to illustrate the expected time course of cancer detection that gives rise to overdetection. While overdetection exists, the actual amount is likely to be much lower than the estimate used by the Canadian Task Force on Preventive Health Care. Furthermore, the issue is of greater significance in older rather than younger women due to competing causes of death. The particular challenge associated with in situ breast cancer is considered and possible approaches to avoiding overtreatment are suggested.

Decision-Making in Adult Cranial Vault Reconstruction.

LEARNING OBJECTIVES: After studying this article, the participant should be able to: 1. Define and classify different types of cranial defects 2. Compare both autologous and alloplastic options for reconstruction 3. Develop an optimal approach for cranial vault reconstruction in various clinical scenarios. SUMMARY: Defects of the cranium result from various causes, including traumatic loss, neurosurgical intervention, skull tumors, and infection. Cranial vault reconstruction aims to restore both the structural integrity and surface morphology of the skull. To ensure a successful outcome, the choice of appropriate cranioplasty reconstruction will vary primarily based on the cause, location, and size of the defect. Other relevant factors that must be considered include adequacy of soft-tissue coverage, presence of infection, and previous or planned radiation therapy. This article presents an algorithm for the reconstruction of various cranial defects using both autologous and alloplastic techniques, with a comparison of their advantages and disadvantages.

AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design.

The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design. Based on feedback from collaborating neurosurgeons, this paper concludes by stating open issues and post-challenge requirements for intra-operative use. The codes can be found at https://github.com/Jianningli/tmi.

Technical Note: Volumetric coverage in breast tomosynthesis images - Phantom QC results from the TMIST study.

PURPOSE: In the reconstruction of volume breast images from x-ray projections in breast tomosynthesis, some tomographic systems truncate the image data presented to the radiologist such that a non-negligible amount of tissue may be missing from the breast image. QC tests were conducted to determine if this problem existed in imaging in the TMIST study. METHODS: Test tools developed for TMIST containing small objects at known heights were used in routine weekly and annual QC testing of tomosynthesis units to assess the degree to which phantom material that was irradiated in imaging was excluded from the reconstructed image. Results from 318 tests on five system types from three manufacturers are reported. RESULTS: The presence and extent of this problem varied among system types. The cause was most frequently related to machine errors in the determination of breast thickness or to deflection of components during breast compression. In particular, the problem occurred when a compression paddle other than the one calibrated for tomosynthesis was used for the tests. This was also verified to have occurred in some clinical imaging. CONCLUSIONS: Missing volume can be avoided by intentionally reconstructing additional image slices above and below the presumed locations of the breast support and compression plate. A compression paddle which has been calibrated for tomosynthesis should be used both for clinical imaging and testing. The prevalence of this phenomenon suggests that more frequent testing for volume coverage may be advisable.

The impact of episodic screening interruption: COVID-19 and population-based cancer screening in Canada.

BACKGROUND: Population-based cancer screening can reduce cancer burden but was interrupted temporarily due to the COVID-19 pandemic. We estimated the long-term clinical impact of breast and colorectal cancer screening interruptions in Canada using a validated mathematical model. METHODS: We used the OncoSim breast and colorectal cancers microsimulation models to explore scenarios of primary screening stops for 3, 6, and 12 months followed by 6-24-month transition periods of reduced screening volumes. For breast cancer, we estimated changes in cancer incidence over time, additional advanced-stage cases diagnosed, and excess cancer deaths in 2020-2029. For colorectal cancer, we estimated changes in cancer incidence over time, undiagnosed advanced adenomas and colorectal cancers in 2020, and lifetime excess cancer incidence and deaths. RESULTS: Our simulations projected a surge of cancer cases when screening resumes. For breast cancer screening, a three-month interruption could increase cases diagnosed at advanced stages (310 more) and cancer deaths (110 more) in 2020-2029. A six-month interruption could lead to 670 extra advanced cancers and 250 additional cancer deaths. For colorectal cancers, a six-month suspension of primary screening could increase cancer incidence by 2200 cases with 960 more cancer deaths over the lifetime. Longer interruptions, and reduced volumes when screening resumes, would further increase excess cancer deaths. CONCLUSIONS: Interruptions in cancer screening will lead to additional cancer deaths, additional advanced cancers diagnosed, and a surge in demand for downstream resources when screening resumes. An effective strategy is needed to minimize potential harm to people who missed their screening.

The Value of All-Cause Mortality as a Metric for Assessing Breast Cancer Screening.

Although screening mammography has been demonstrated to contribute to reducing mortality due to breast cancer, some have suggested that reduced all-cause mortality should constitute the burden of proof for effectiveness. Using a microsimulation model of the development, detection, and treatment of breast cancer, it is straightforward to demonstrate that this is an unrealistic expectation for trials of practical size and period of observation, even where the reduction of breast cancer mortality is substantial. Estimates of all-cause mortality will depend not only on the efficacy of the screening intervention but also on the alignment between the age distribution of the effect of screening on reduction of deaths and that of the other major causes of death. The size of a randomized trial required to demonstrate a reduction in all-cause mortality will, therefore, depend on the length and timing of the observation period and will typically be at least 10 times larger than the size of a trial powered to test for a reduction in deaths due to breast cancer. For breast cancer, which represents a small fraction of overall deaths, all-cause mortality is neither a practical nor informative metric for assessing the effectiveness of screening.

Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy.

PURPOSE: Medical imaging is an indispensable tool in radiotherapy for dose planning, image guidance and treatment monitoring. Cone beam CT (CBCT) is a low dose imaging technique with high spatial resolution capability as a direct by-product of using flat-panel detectors. However, certain issues such as x-ray scatter, beam hardening and other artifacts limit its utility to the verification of patient positioning using image-guided radiotherapy. METHODS AND MATERIALS: Dual-energy (DE)-CBCT has recently demonstrated promise as an improved tool for tumor visualization in benchtop applications. It has the potential to improve soft-tissue contrast and reduce artifacts caused by beam hardening and metal. In this review, the practical aspects of developing a DE-CBCT based clinical and technical workflow are presented based on existing DE-CBCT literature and concepts adapted from the well-established library of work in DE-CT. Furthermore, the potential applications of DE-CBCT on its future role in radiotherapy are discussed. RESULTS AND CONCLUSIONS: Based on current literature and an investigation of future applications, there is a clear potential for DE-CBCT technologies to be incorporated into radiotherapy. The applications of DE-CBCT include (but are not limited to): adaptive radiotherapy, brachytherapy, proton therapy, radiomics and theranostics.

Digital Breast Tomosynthesis: Technique and Common Artifacts.

Image optimization at digital breast tomosynthesis (DBT) involves a series of trade-offs between multiple variables. Wider sweep angles provide better separation of overlapping tissues, but they result in decreased in-plane resolution as well as increased scan times that may be prone to patient motion. Techniques to reduce scan time, such as continuous tube motion and pixel binning during detector readout, reduce the chances of patient motion but may degrade the in-plane resolution. Image artifacts are inherent to DBT because of the limited angular range of the acquisition. Iterative reconstruction algorithms have been shown to reduce various DBT artifacts.

Investigating the feasibility of stratified breast cancer screening using a masking risk predictor.

BACKGROUND: Women with dense breasts face a double risk for breast cancer; they are at a higher risk for development of breast cancer than those with less dense breasts, and there is a greater chance that mammography will miss detection of a cancer in dense breasts due to the masking effect of surrounding fibroglandular tissue. These women may be candidates for supplemental screening. In this study, a masking risk model that was previously developed is tested on a cohort of cancer-free women to assess potential efficiency of stratification. METHODS: Three masking risk models based on (1) BI-RADS density, (2) volumetric breast density (VBD), and (3) a combination of VBD and detectability were applied to stratify the mammograms of 1897 cancer-free women. The fraction of cancer-free women whose mammograms were deemed by the algorithm to be masked and who would be considered for supplemental imaging was computed as was the corresponding fraction in a screened population of interval (masked) cancers that would be potentially detected by supplemental imaging. RESULTS: Of the models tested, the combined VBD/detectability model offered the highest efficiency for stratification to supplemental imaging. It predicted that 725 supplemental screens would be performed per interval cancer potentially detected, at an operating point that allowed detection of 64% of the interval cancers. In comparison, stratification based on the upper two BI-RADS density categories required 1117 supplemental screenings per interval cancer detected to capture 64% of interval cancers. CONCLUSION: The combined VBD/detectability models perform better than BI-RADS and offer a continuum of operating points, suggesting that this model may be effective in guiding a stratified screening environment.

Determination of 3D PSFs from computed tomography reconstructed x-ray images of spherical objects and the effects of sphere radii.

PURPOSE: A method was developed to obtain three-dimensional (3D) point spread functions (PSFs) of reconstructed x-ray volumetric images using spheres of known diameters. The algorithm consists of a sphere localization step using template matching applied to the entire volume. Richardson Lucy (RL) deconvolution is used atypically to determine the PSF from the reconstructed x-ray image and a model of the sphere. The resulting PSF is arbitrary, that is, there are no assumptions of separability or symmetry. Oversampling is not used, and sample spacing matches the image. The effect of sphere radius on PSF estimate reproducibility is investigated. METHODS: Phantoms were constructed by suspending five polytetrafluoroethylene (PTFE) spheres having known radii equal to 4.77, 7.95, 9.52, 12.68, and 19.53 mm in an agar solution. The phantom included a 25 µm steel wire to calculate a line spread function (LSF). The phantom was imaged and reconstructed with a Medtronic surgical O-Arm 23 times and a Toshiba Aquilion One computed tomography (CT) 20 times. A sharp reconstruction kernel exhibiting a nonmonotonic PSF was used with the Toshiba CT. PSFs and LSFs were computed for all of the images and repeated estimates were used to compute mean and standard deviation values for every point of the PSFs and LSFs. The PSFs from spheres were converted to LSFs and compared to the wire LSF. RESULTS: The standard deviations of the PSF estimates exhibit a decreasing trend as the sphere radius is increased. The PSF from the smallest 4.77 mm sphere is the least reproducible. The normalized root mean square difference between the mean LSF derived from the 4.77 mm radius sphere and the mean wire LSF is 2.0% for the O-arm and 1.2% for the CT. CONCLUSION: Richardson Lucy (RL) deconvolution provides a method to estimate generalized (no separability or other simplifying assumptions) 3D PSFs from spheres. X-ray noise in images acquired with typical clinical protocols cause noticeable variations in PSF estimates which can be mitigated by selecting larger spheres and combining PSF estimates from different images.