Dose robustness of deep learning models for anatomic segmentation of computed tomography images.

Purpose: The trend towards lower radiation doses and advances in computed tomography (CT) reconstruction may impair the operation of pretrained segmentation models, giving rise to the problem of estimating the dose robustness of existing segmentation models. Previous studies addressing the issue suffer either from a lack of registered low- and full-dose CT images or from simplified simulations. Approach: We employed raw data from full-dose acquisitions to simulate low-dose CT scans, avoiding the need to rescan a patient. The accuracy of the simulation is validated using a real CT scan of a phantom. We consider down to 20% reduction of radiation dose, for which we measure deviations of several pretrained segmentation models from the full-dose prediction. In addition, compatibility with existing denoising methods is considered. Results: The results reveal the surprising robustness of the TotalSegmentator approach, showing minimal differences at the pixel level even without denoising. Less robust models show good compatibility with the denoising methods, which help to improve robustness in almost all cases. With denoising based on a convolutional neural network (CNN), the median Dice between low- and full-dose data does not fall below 0.9 (12 for the Hausdorff distance) for all but one model. We observe volatile results for labels with effective radii less than 19 mm and improved results for contrasted CT acquisitions. Conclusion: The proposed approach facilitates clinically relevant analysis of dose robustness for human organ segmentation models. The results outline the robustness properties of a diverse set of models. Further studies are needed to identify the robustness of approaches for lesion segmentation and to rank the factors contributing to dose robustness.

The influence of motion-compensated reconstruction on coronary artery analysis for a dual-layer detector CT system: a dynamic phantom study.

OBJECTIVES: Cardiac motion artifacts hinder the assessment of coronary arteries in coronary computed tomography angiography (CCTA). We investigated the impact of motion compensation reconstruction (MCR) on motion artifacts in CCTA at various heart rates (HR) using a dynamic phantom. MATERIALS AND METHODS: An artificial hollow coronary artery (5-mm diameter lumen) filled with iodinated contrast agent (400 HU at 120 kVp), positioned centrally in an anthropomorphic chest phantom, was scanned using a dual-layer spectral detector CT. The artery was translated at constant horizontal velocities (0-80 mm/s, increment of 10 mm/s). For each velocity, five CCTA scans were repeated using a clinical protocol. Motion artifacts were quantified using the in-plane motion area. Regression analysis was performed to calculate the reduction in motion artifacts provided by MCR, by division of the slopes of non-MCR and MCR fitted lines. RESULTS: Reference mean (95% confidence interval) motion artifact area was 24.9 mm2 (23.8, 26.0). Without MCR, motion artifact areas for velocities exceeding 20 mm/s were significantly larger (up to 57.2 mm2 (40.1, 74.2)) than the reference. With MCR, no significant differences compared to the reference were shown for all velocities, except for 70 mm/s (29.0 mm2 (27.0, 31.0)). The slopes of the fitted data were 0.44 and 0.04 for standard and MCR reconstructions, respectively, resulting in an 11-time motion artifact reduction. CONCLUSION: MCR may improve CCTA assessment in patients by reducing coronary artery motion artifacts, especially in those with elevated HR who cannot receive beta blockers or do not attain the targeted HR. CLINICAL RELEVANCE STATEMENT: This vendor-specific motion compensation reconstruction may improve coronary computed tomography angiography assessment in patients by reduction of coronary artery motion artifacts, especially in those with elevated various heart rates (HR) who cannot receive beta blockers or do not attain the targeted HR. KEY POINTS: • Motion artifacts are known to hinder the assessment of coronary arteries on coronary CT angiography (CCTA), leading to more non-diagnostic scans. • This dynamic phantom study shows that motion compensation reconstruction (MCR) reduces motion artifacts at various velocities, which may help to decrease the number of non-diagnostic scans. • MCR in this study showed to reduce motion artifacts 11-fold.

Correction: Adam et al. Acetic Acid as Processing Aid Dramatically Improves Organic Solvent Solubility of Weakly Basic Drugs for Spray Dried Dispersion Manufacture. Pharmaceutics 2022, 14, 555.

Figure Legend [...].

A Critical Overview of the Biological Effects of Excipients (Part II): Scientific Considerations and Tools for Oral Product Development.

It is now recognized that a number of excipients previously considered to be "inert" have the capacity to alter drug oral bioavailability through a range of in vivo effects. The various mechanisms through which an excipient can affect in vivo gastrointestinal physiology and drug absorption characteristics were explored in "A Critical Overview of The Biological Effects of Excipients (Part I): Impact on Gastrointestinal Absorption." The next critical issue that needs to be discussed is how these biological effects are evaluated. Therefore, in Part 2 of this critical overview, the in vitro, in vivo, and in silico methods for evaluating excipient effects are considered. Examples are provided to illustrate how such studies employing these various procedures have been used to promote formulation understanding and optimization. Finally, a discussion of how the Center for Drug Evaluation and Research applies these tools to support biowaivers is provided.

Cascaded learning in intravascular ultrasound: coronary stent delineation in manual pullbacks.

Purpose: Implanting stents to re-open stenotic lesions during percutaneous coronary interventions is considered a standard treatment for acute or chronic coronary syndrome. Intravascular ultrasound (IVUS) can be used to guide and assess the technical success of these interventions. Automatically segmenting stent struts in IVUS sequences improves workflow efficiency but is non-trivial due to a challenging image appearance entailing manifold ambiguities with other structures. Manual, ungated IVUS pullbacks constitute a challenge in this context. We propose a fully data-driven strategy to first longitudinally detect and subsequently segment stent struts in IVUS frames. Approach: A cascaded deep learning approach is presented. It first trains an encoder model to classify frames as "stent," "no stent," or "no use." A segmentation model then delineates stent struts on a pixel level only in frames with a stent label. The first stage of the cascade acts as a gateway to reduce the risk for false positives in the second stage, the segmentation, which is trained on a smaller and difficult-to-annotate dataset. Training of the classification and segmentation model was based on 49,888 and 1826 frames of 74 sequences from 35 patients, respectively. Results: The longitudinal classification yielded Dice scores of 92.96%, 82.35%, and 94.03% for the classes stent, no stent, and no use, respectively. The segmentation achieved a Dice score of 65.1% on the stent ground truth (intra-observer performance: 75.5%) and 43.5% on all frames (including frames without stent, with guidewires, calcium, or without clinical use). The latter improved to 49.5% when gating the frames by the classification decision and further increased to 57.4% with a heuristic on the plausible stent strut area. Conclusions: A data-driven strategy for segmenting stents in ungated, manual pullbacks was presented-the most common and practical scenario in the time-critical clinical workflow. We demonstrated a mitigated risk for ambiguities and false positive predictions.

Observation of Potential-Induced Hydration on the Surface of Ceramic Proton Conductors Using In Situ Near-Ambient Pressure X-ray Photoelectron Spectroscopy.

Interactions of ceramic proton conductors with the environment under operating conditions play an essential role on material properties and device performance. It remains unclear how the chemical environment of material, as modulated by the operating condition, affects the proton conductivity. Combining near-ambient pressure X-ray photoelectron spectroscopy and impedance spectroscopy, we investigate the chemical environment changes of oxygen and the conductivity of BaZr0.9Y0.1O3-δ under operating condition. Changes in O 1s core level spectra indicate that adding water vapor pressure increases both hydroxyl groups and active proton sites at undercoordinated oxygen. Applying external potential further promotes this hydration effect, in particular, by increasing the amount of undercoordinated oxygen. The enhanced hydration is accompanied by improved proton conductivity. This work highlights the effects of undercoordinated oxygen for improving the proton conductivity in ceramics.

Acetic Acid as Processing Aid Dramatically Improves Organic Solvent Solubility of Weakly Basic Drugs for Spray Dried Dispersion Manufacture.

Many active pharmaceutical ingredients (APIs) in the pharmaceutical pipeline require bioavailability enhancing formulations due to very low aqueous solubility. Although spray dried dispersions (SDDs) have demonstrated broad utility in enhancing the bioavailability of such APIs by trapping them in a high-energy amorphous form, many new chemical entities (NCEs) are poorly soluble not just in water, but in preferred organic spray drying solvents, e.g., methanol (MeOH) and acetone. Spraying poorly solvent soluble APIs from dilute solutions leads to low process throughput and small particles that challenge downstream processing. For APIs with basic pKa values, spray solvent solubility can be dramatically increased by using an acid to ionize the API. Specifically, we show that acetic acid can increase API solubility in MeOH:H2O by 10-fold for a weakly basic drug, gefitinib (GEF, pKa 7.2), by ionizing GEF to form the transient acetate salt. The acetic acid is removed during drying, resulting in a SDD of the original GEF free base having performance similar to SDDs sprayed from solvents without acetic acid. The increase in solvent solubility enables large scale manufacturing for these challenging APIs by significantly increasing the throughput and reducing the amount of solvent required.

Comment on Bernard et al. Association between Urinary Metabolites and the Exposure of Intensive Care Newborns to Plasticizers of Medical Devices Used for Their Care Management. Metabolites 2021, 11, 252.

The recent publication "Association between Urinary Metabolites and the Exposure of Intensive Care Newborns to Plasticizers of Medical Devices Used for Their Care Management" by L. Bernard et al. (2021) [...].

A prospective multicenter validation study for a novel angiography-derived physiological assessment software: Rationale and design of the radiographic imaging validation and evaluation for Angio-iFR (ReVEAL iFR) study.

Angiography-derived physiological assessment of coronary lesions has emerged as an alternative to wire-based assessment aiming at less-invasiveness and shorter procedural time as well as cost effectiveness in physiology-guided decision making. However, current available image-derived physiology software have limitations including the requirement of multiple projections and are time consuming. METHODS/DESIGN: The ReVEAL iFR (Radiographic imaging Validation and EvALuation for Angio-iFR) trial is a multicenter, multicontinental, validation study which aims to validate the diagnostic accuracy of the Angio-iFR medical software device (Philips, San Diego, US) in patients undergoing angiography for Chronic Coronary Syndrome (CCS). The Angio-iFR will enable operators to predict both the iFR and FFR value within a few seconds from a single projection of cine angiography by using a lumped parameter fluid dynamics model. Approximately 440 patients with at least one de-novo 40% to 90% stenosis by visual angiographic assessment will be enrolled in the study. The primary endpoint is the sensitivity and specificity of the iFR and FFR for a given lesion compared to the corresponding invasive measures. The enrollment started in August 2019, and was completed in March 2021. SUMMARY: The Angio-iFR system has the potential of simplifying physiological evaluation of coronary stenosis compared with available systems, providing estimates of both FFR and iFR. The ReVEAL iFR study will investigate the predictive performance of the novel Angio-iFR software in CCS patients. Ultimately, based on its unique characteristics, the Angio-iFR system may contribute to improve adoption of functional coronary assessment and the workflow in the catheter laboratory.

Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation.

OBJECTIVE: The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI-resulting in an extremely and dangerously long RTAT, as CXRs are sorted to the end of the worklist. METHODS: We developed a simulation framework that models the current workflow at a university hospital by incorporating hospital-specific CXR generation rates and reporting rates and pathology distribution. Using this, we simulated the standard worklist processing "first-in, first-out" (FIFO) and compared it with a worklist prioritization based on urgency. Examination prioritization was performed by the AI, classifying eight different pathological findings ranked in descending order of urgency: pneumothorax, pleural effusion, infiltrate, congestion, atelectasis, cardiomegaly, mass, and foreign object. Furthermore, we introduced an upper limit for the maximum waiting time, after which the highest urgency is assigned to the examination. RESULTS: The average RTAT for all critical findings was significantly reduced in all prioritization simulations compared to the FIFO simulation (e.g., pneumothorax: 35.6 min vs. 80.1 min; p < 0.0001), while the maximum RTAT for most findings increased at the same time (e.g., pneumothorax: 1293 min vs 890 min; p < 0.0001). Our "upper limit" substantially reduced the maximum RTAT in all classes (e.g., pneumothorax: 979 min vs. 1293 min/1178 min; p < 0.0001). CONCLUSION: Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO. KEY POINTS: • Development of a realistic clinical workflow simulator based on empirical data from a hospital allowed precise assessment of smart worklist prioritization using artificial intelligence. • Employing a smart worklist prioritization without a threshold for maximum waiting time runs the risk of false negative predictions of the artificial intelligence greatly increasing the report turnaround time. • Use of a state-of-the-art convolution neural network can reduce the average report turnaround time almost to the upper limit of a perfect classification algorithm (e.g., pneumothorax: 35.6 min vs. 30.4 min).

Practical Approach to Modeling the Impact of Amorphous Drug Nanoparticles on the Oral Absorption of Poorly Soluble Drugs.

Recently published studies have proposed that amorphous drug nanoparticles in gastrointestinal fluids may be beneficial for the absorption of poorly soluble compounds. Nanosized drug particles are known to provide rapid dissolution rates and, in some instances, a slight increase in solubility. However, in recent studies, the differences observed in vivo could not be explained solely by these attributes. Given the high dose and very low aqueous solubility of the study compounds, rapid equilibration to the drug-saturated solubility in gastrointestinal fluid would occur independent of the presence of nanoparticles. Alternatively, it has been proposed that drug nanoparticles (ca. ≤ 200 to 300 nm) may provide a "shuttle" for drug across the unstirred water layer (UWL) adjacent to the intestinal epithelium, particularly for low solubility/lipophilic compounds where absorption may be largely UWL-limited. This transport mechanism would result in a higher unbound drug concentration at the surface of the epithelium for absorption. This study evaluates this mechanism using a simple modification of the effective permeability to account for the effect of drug nanoparticles diffusing across the UWL. The modification can be made using inputs for solubility and nanoparticle size. The permeability modification was evaluated using three published case studies for amorphous formulations of itraconazole, anacetrapib, and enzalutamide, where the formation of amorphous drug nanoparticles upon dissolution resulted in improved drug absorption. Absorption modeling was performed using GastroPlus to assess the impact of the nanomodified permeability method on the accuracy of model prediction compared to in vivo data. Simulation results were compared to those for baseline simulations using an unmodified effective permeability. The results show good agreement using the nanomodified permeability, which described the data better than the standard baseline predictions. The nanomodified permeability method can be a suitable, fit-for-purpose in silico approach for evaluating or predicting oral absorption of poorly soluble, UWL-limited drugs from formulations that produce a significant number of amorphous drug nanoparticles.

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

The increased availability of labeled X-ray image archives (e.g. ChestX-ray14 dataset) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classification, we investigate a powerful network architecture in detail: the ResNet-50. Building on prior work in this domain, we consider transfer learning with and without fine-tuning as well as the training of a dedicated X-ray network from scratch. To leverage the high spatial resolution of X-ray data, we also include an extended ResNet-50 architecture, and a network integrating non-image data (patient age, gender and acquisition type) in the classification process. In a concluding experiment, we also investigate multiple ResNet depths (i.e. ResNet-38 and ResNet-101). In a systematic evaluation, using 5-fold re-sampling and a multi-label loss function, we compare the performance of the different approaches for pathology classification by ROC statistics and analyze differences between the classifiers using rank correlation. Overall, we observe a considerable spread in the achieved performance and conclude that the X-ray-specific ResNet-38, integrating non-image data yields the best overall results. Furthermore, class activation maps are used to understand the classification process, and a detailed analysis of the impact of non-image features is provided.

Improved visualization of the coronary arteries using motion correction during vasodilator stress CT myocardial perfusion imaging.

BACKGROUND: Vasodilator stress computed tomography perfusion (sCTP) imaging is complementary to coronary CT angiography (CCTA), used to determine the hemodynamic significance of coronary artery disease. However, it requires a separate image acquisition due to motion artifacts caused by higher heart rates during stress, resulting in increased iodine contrast dose and radiation. We sought to determine whether a novel motion correction algorithm applied to stress images would improve the visualization of the coronary arteries to potentially allow CCTA + sCTP evaluation in a single scan. METHODS: 28 patients referred for clinically indicated CCTA (iCT, Philips) underwent sCTP imaging (retrospective-gating with dose modulation; 100 kVp and 250 mA; 5.2 ± 4.3 mSv) after regadenoson (0.4 mg, Astellas). Stress images were reconstructed using standard filtered back-projection (FBP) and also processed to generate interaction-free coronary motion-compensated back-projection reconstructions (MCR). Each coronary artery from standard FBP and MCR images was viewed side-by-side by a reader blinded to the reconstruction technique, who graded severity of motion artifact by segment (scale 0-5, with 3 as the threshold for diagnostic quality) and to measure signal-to-noise and contrast-to-noise ratios (SNR, CNR). RESULTS: Visualization scores were higher with MCR for all coronary segments, including 14/86 (16%) segments deemed as non-diagnostic on FBP images. SNR (7 ± 2) and CNR (15 ± 8) were unchanged by motion-correction (7 ± 3, p = 0.88 and 15 ± 5, p = 0.94, respectively). CONCLUSIONS: MCR improves the visualization of coronary anatomy on sCTP images without degrading image characteristics. This algorithm is an important step towards the combined assessment of coronary anatomy and myocardial perfusion in a single scan, which will reduce study time, radiation exposure and contrast dose.

Machine learning for automated 3-dimensional segmentation of the spine and suggested placement of pedicle screws based on intraoperative cone-beam computer tomography.

OBJECTIVE: The goal of this study was to develop and validate a system for automatic segmentation of the spine, pedicle identification, and screw path suggestion for use with an intraoperative 3D surgical navigation system. METHODS: Cone-beam CT (CBCT) images of the spines of 21 cadavers were obtained. An automated model-based approach was used for segmentation. Using machine learning methodology, the algorithm was trained and validated on the image data sets. For measuring accuracy, surface area errors of the automatic segmentation were compared to the manually outlined reference surface on CBCT. To further test both technical and clinical accuracy, the algorithm was applied to a set of 20 clinical cases. The authors evaluated the system's accuracy in pedicle identification by measuring the distance between the user-defined midpoint of each pedicle and the automatically segmented midpoint. Finally, 2 independent surgeons performed a qualitative evaluation of the segmentation to judge whether it was adequate to guide surgical navigation and whether it would have resulted in a clinically acceptable pedicle screw placement. RESULTS: The clinically relevant pedicle identification and automatic pedicle screw planning accuracy was 86.1%. By excluding patients with severe spinal deformities (i.e., Cobb angle > 75° and severe spinal degeneration) and previous surgeries, a success rate of 95.4% was achieved. The mean time (± SD) for automatic segmentation and screw planning in 5 vertebrae was 11 ± 4 seconds. CONCLUSIONS: The technology investigated has the potential to aid surgeons in navigational planning and improve surgical navigation workflow while maintaining patient safety.

Millisecond Self-Assembly of Stable Nanodispersed Drug Formulations.

We report the development of a new spray-drying and nanoparticle assembly process (SNAP) that enables the formation of stable, yet rapidly dissolving, sub-200 nm nanocrystalline particles within a high Tg glassy matrix. SNAP expands the class of drugs that spray-dried dispersion (SDD) processing can address to encompass highly crystalline, but modestly hydrophobic, drugs that are difficult to process by conventional SDD. The process integrates rapid precipitation and spray-drying within a custom designed nozzle to produce high supersaturations and precipitation of the drug and high Tg glassy polymer. Keeping the time between precipitation and drying to tens of milliseconds allows for kinetic trapping of drug nanocrystals in the polymer matrix. Powder X-ray diffraction, solid state 2D NMR, and SEM imaging shows that adding an amphiphilic block copolymer (BCP) to the solvent gives essentially complete crystallization of the active pharmaceutical ingredient (API) with sub-200 nm domains. In contrast, the absence of the block copolymer results in the API being partially dispersed in the matrix as an amorphous phase, which can be sensitive to changes in bioavailability over time. Quantification of the API-excipient interactions by 2D 13C-1H NMR correlation spectroscopy shows that the mechanism of enhanced nanocrystal formation is not due to interactions between the drug and the BCP, but rather the BCP masks interactions between the drug and hydrophobic regions of the matrix polymers. BCP-facilitated SNAP samples show improved stability during aging studies and rapid dissolution and release of API in vitro.

Impact of Drug-Rich Colloids of Itraconazole and HPMCAS on Membrane Flux in Vitro and Oral Bioavailability in Rats.

Improving the oral absorption of compounds with low aqueous solubility is a common challenge that often requires an enabling technology. Frequently, oral absorption can be improved by formulating the compound as an amorphous solid dispersion (ASD). Upon dissolution, an ASD can reach a higher concentration of unbound drug than the crystalline form, and often generates a large number of sub-micrometer, rapidly dissolving drug-rich colloids. These drug-rich colloids have the potential to decrease the diffusional resistance across the unstirred water layer of the intestinal tract (UWL) by acting as rapidly diffusing shuttles for unbound drug. In a prior study utilizing a membrane flux assay, we demonstrated that, for itraconazole, increasing the concentration of drug-rich colloids increased membrane flux in vitro. In this study, we evaluate spray-dried amorphous solid dispersions (SDDs) of itraconazole with hydroxypropyl methylcellulose acetate succinate (HPMCAS) to study the impact of varying concentrations of drug-rich colloids on the oral absorption of itraconazole in rats, and to quantify their impact on in vitro flux as a function of bile salt concentration. When Sporanox and itraconazole/AFFINISOL High Productivity HPMCAS SDDs were dosed in rats, the maximum absorption rate for each formulation rank-ordered with membrane flux in vitro. The relative maximum absorption rate in vivo correlated well with the in vitro flux measured in 2% SIF (26.8 mM bile acid concentration), a representative bile acid concentration for rats. In vitro it was found that as the bile salt concentration increases, the importance of colloids for improving UWL permeability is diminished. We demonstrate that drug-containing micelles and colloids both contribute to aqueous boundary layer diffusion in proportion to their diffusion coefficient and drug loading. These data suggest that, for compounds with very low aqueous solubility and high epithelial permeability, designing amorphous formulations that produce colloids on dissolution may be a viable approach to improve oral bioavailability.

Development of a Biorelevant, Material-Sparing Membrane Flux Test for Rapid Screening of Bioavailability-Enhancing Drug Product Formulations.

Bioavailability-enhancing formulations are often used to overcome challenges of poor gastrointestinal solubility for drug substances developed for oral administration. Conventional in vitro dissolution tests often do not properly compare such formulations due to the many different drug species that may exist in solution. To overcome these limitations, we have designed a practical in vitro membrane flux test, that requires minimal active pharmaceutical ingredient (API) and is capable of rapidly screening many drug product intermediates. This test can be used to quickly compare performance of bioavailability-enhancing formulations with fundamental knowledge of the rate-limiting step(s) to membrane flux. Using this system, we demonstrate that the flux of amorphous itraconazole (logD = 5.7) is limited by aqueous boundary layer (ABL) diffusion and can be increased by adding drug-solubilizing micelles or drug-rich colloids. Conversely, the flux of crystalline ketoconazole at pH 5 (logD = 2.2) is membrane-limited, and adding solubilizing micelles does not increase flux. Under certain circumstances, the flux of ketoconazole may also be limited by dissolution rate. These cases highlight how a well-designed in vitro assay can provide critical insight for oral formulation development. Knowing whether flux is limited by membrane diffusion, ABL diffusion, or dissolution rate can help drive formulation development decisions. It may also be useful in predicting in vivo performance, dose linearity, food effects, and regional-dependent flux along the length of the gastrointestinal tract.

Reconstruction of coronary arteries from X-ray angiography: A review.

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research.

Automatic bone removal for 3D TACE planning with C-arm CBCT: Evaluation of technical feasibility.

PURPOSE: To evaluate the technical feasibility of automatically removing the ribs and spine from C-arm cone-beam computed tomography (CBCT) images acquired during transcatheter arterial chemoembolization (TACE). MATERIAL AND METHODS: Fifty-eight patients (45.8 ± 5.0 years) with unresectable hepatocellular carcinoma (HCC) underwent transcatheter arterial chemoembolization and had intraprocedural CBCT imaging. Automatic bone removal was performed using model-based segmentation of the ventral cavity. Two interventional radiologists independently evaluated the performance of bone removal, remaining soft tissue retention, and general usability (where both the bone is appropriately removed while retaining soft tissue) for 3D TACE planning on a four-level (complete/excellent, adequate/good, incomplete/questionable, insufficient/bad) score. The proportion of inter-reader agreement was calculated. RESULTS: For ribs and spine removal, 98.3-100% and 100% of cases showed complete or adequate performance, respectively. In 96.6% of the cases, soft tissue was at least adequately retained. 91.3-93.1% of the cases demonstrated good or excellent general usability for TACE planning. Satisfactory inter-reader agreement proportion was achieved in ribs (93.1%) and spine removal (89.7%), soft tissue retention (84.5%), and general usability for TACE planning (72.4%). CONCLUSION: Intraprocedural automatic bone removal on CBCT images is technically feasible and offers good removal of ribs and spine while preserving soft tissue. Its clinical value needs further assessment.

Multimodality Imaging of Ethiodized Oil-loaded Radiopaque Microspheres during Transarterial Embolization of Rabbits with VX2 Liver Tumors.

Purpose To assess the visibility of radiopaque microspheres during transarterial embolization (TAE) in the VX2 rabbit liver tumor model by using multimodality imaging, including single-snapshot radiography, cone-beam computed tomography (CT), multidetector CT, and micro-CT. Materials and Methods The study was approved by the institutional animal care and use committee. Fifteen VX2-tumor-bearing rabbits were assigned to three groups depending on the type of embolic agent injected: 70-150-µm radiopaque microspheres in saline (radiopaque microsphere group), 70-150-µm radiopaque microspheres in contrast material (radiopaque microsphere plus contrast material group), and 70-150-µm radiolucent microspheres in contrast material (nonradiopaque microsphere plus contrast material group). Rabbits were imaged with single-snapshot radiography, cone-beam CT, and multidetector CT. Three to 5 weeks after sacrifice, excised livers were imaged with micro-CT and histologic analysis was performed. The visibility of the embolic agent was assessed with all modalities before and after embolization by using a qualitative three-point scale score reading study and a quantitative assessment of the signal-to-noise ratio (SNR) change in various regions of interest, including the tumor and its feeding arteries. The Kruskal-Wallis test was used to compare the rabbit characteristics across groups, and the Wilcoxon signed rank test was used to compare SNR measurements before and after embolization. Results Radiopaque microspheres were qualitatively visualized within tumor feeding arteries and targeted tissue with all imaging modalities (P < .05), and their presence was confirmed with histologic examination. SNRs of radiopaque microsphere deposition increased after TAE on multidetector CT, cone-beam CT, and micro-CT images (P < .05). Similar results were obtained when contrast material was added to radiopaque microspheres, except for additional image attenuation due to tumor enhancement. For the group with nonradiopaque microspheres and contrast material, retained tumoral contrast remained qualitatively visible with all modalities except for micro-CT, which demonstrated soluble contrast material washout over time. Conclusion Radiopaque microspheres were visible with all imaging modalities and helped increase conspicuity of the tumor as well as its feeding arteries after TAE in a rabbit VX2 liver tumor model. (©) RSNA, 2015.