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Inferior vena cava filters (IVCFs) constructed with poly-p-dioxanone (PPDO) are promising alternatives to metallic filters and their associated risks and complications. Incorporating high-Z nanoparticles (NPs) improves PPDO IVCFs’ radiopacity without adversely affecting their safety or performance. However, increased radiopacity from these studies are insufficient for filter visualization during fluoroscopy-guided PPDO IVCF deployment. This study focuses on the use of bismuth nanoparticles (BiNP) as radiopacifiers to render sufficient signal intensity for the fluoroscopy-guided deployment and long-term CT monitoring of PPDO IVCFs. The use of polyhydroxybutyate (PHB) as an additional layer to increase the surface adsorption of NPs resulted in a 2-fold increase in BiNP coating (BiNP-PPDO IVCFs, 3.8%, BiNP-PPDO+PHB IVCFs, 6.2%), enabling complete filter visualization during fluoroscopy-guided IVCF deployment and, 1 week later, clot deployment. The biocompatibility, clot-trapping efficacy, and mechanical strength of the control PPDO (load-at-break, 6.23±0.13 kg), BiNP-PPDO (6.10±0.09 kg), and BiNP-PPDO+PHB (6.15±0.13 kg) IVCFs did not differ significantly over a 12-week monitoring period in pigs. These results indicate that BiNP-PPDO+PHB can increase the radiodensity of a novel absorbable IVCF without compromising device strength. Visualizing the device under conventional radiographic imaging is key to allow safe and effective clinical translation of the device.

The use of absorbable inferior vena cava filters (IVCFs) constructed with poly-p-dioxanone (PPDO) eliminates risks and complications associated with the use of retrievable metallic filters. Radiopacity of radiolucent PPDO IVCFs can be improved with the incorporation of nanoparticles (NPs) made of high-atomic number materials such as gold and bismuth. In this study, we focused on incorporating tungsten NPs (WNPs), along with polyhydroxybutyrate (PHB), polycaprolactone (PCL), and polyvinylpyrrolidone (PVP) polymers to increase the surface adsorption of the WNPs. We compared the imaging properties of WNPs with single-polymer PHB (W-P) and WNPs with polymer blends consisting of PHB, PCL, and PVP (W-PB). Ourin vitroanalyses using PPDO sutures showed enhanced radiopacity with either W-P or W-PB coating, without compromising the inherent physico-mechanical properties of the PPDO sutures. We observed a more sustained release of WNPs from W-PB-coated sutures than W-P-coated sutures. We successfully deployed W-P- and W-PB-coated IVCFs into the inferior vena cava of pig models, with monitoring by fluoroscopy. At the time of deployment, W-PB-coated IVCFs showed a 2-fold increase in radiopacity compared to W-P-coated IVCFs. Longitudinal monitoring ofin vivoIVCFs over a 12-week period showed a drastic decrease in radiopacity at week 3 for both filters. Results of this study highlight the utility of NPs and polymers for enhancing radiopacity of medical devices; however, different methods of incorporating NPs and polymers can still be explored to improve the efficacy, safety, and quality of absorbable IVCFs.

To evaluate the feasibility of using dual-energy computed tomography (DECT) and theranostic cesium hydroxide (CsOH) for image guidance of thermochemical ablation (TCA) in a rabbit VX2 tumor model.In vivo experiments were performed in New Zealand white rabbits where VX2 tumor fragments (0.3mL) were inoculated into the right and left flanks (n=16 rabbits, 32 tumors). Catheters were placed in the approximate center of 1-2 cm diameter tumors under ultrasound guidance. TCA was delivered as one of three treatment groups: untreated control, 5M TCA, or 10M TCA. The TCA base reagent was doped with 250mM CsOH. Dual-energy CT (DECT) was acquired pre-and post-TCA. Material-specific images (Cs) were post-processed based on previous phantom calibrations to determine Cs concentration. Line profiles were drawn through the ablation center. 24 hours after TCA, subjects were euthanized, and the resulting damage was evaluated with histopathology.Cesium was detected in 100% of treated tumors (n = 21). Line profiles indicated the highest concentrations at the injection site and decreased concentrations at the tumor margins, with no cesium detected beyond the ablation zone. Maximum detected Cs concentration ranged from 14.39 mM to 137.33 mM. A dose-dependent trend in tissue necrosis was demonstrated between the 10 M TCA treatment group and the 5 M TCA treatment group (p=0.0005) and untreated controls (p=0.0089).DECT provided image guidance for delivery, localization, and quantification of TCA in the rabbit VX2 model.

PURPOSE Chronic susceptibility lesions in the brain can be either hemorrhagic (potentially dangerous) or calcific (usually not dangerous) but are difficult to discriminate on routine imaging. We proposed to develop quantitative diagnostic criteria for single-energy computed tomography (SECT), dual-energy computed tomography (DECT), and quantitative susceptibility mapping (QSM) to distinguish hemorrhage from calcium. MATERIALS AND METHODS Patients with positive susceptibility lesions on routine T2*-weighted magnetic resonance of the brain were recruited into this prospective imaging clinical trial, under institutional review board approval and with informed consent. The SECT, DECT, and QSM images were obtained, the lesions were identified, and the regions of interest were defined, with the mean values recorded. Criteria for quantitative interpretation were developed on the first 50 patients, and then applied to the next 45 patients. Contingency tables, scatter plots, and McNemar test were applied to compare classifiers. RESULTS There were 95 evaluable patients, divided into a training set of 50 patients (328 lesions) and a validation set of 45 patients (281 lesions). We found the following classifiers to best differentiate hemorrhagic from calcific lesions: less than 68 Hounsfield units for SECT, calcium level of less than 15 mg/mL (material decomposition value) for DECT, and greater than 38 ppb for QSM. There was general mutual agreement among the proposed criteria. The proposed criteria outperformed the current published criteria. CONCLUSIONS We provide the updated criteria for the classification of chronic positive susceptibility brain lesions as hemorrhagic versus calcific for each major clinically available imaging modality. These proposed criteria have greater internal consistency than the current criteria and should likely replace it as gold standard.

Purpose Assessment of image quality directly in clinical image data is an important quality control objective as phantom-based testing does not fully represent image quality across patient variation. Computer algorithms for automatically measuring noise in clinical computed tomography (CT) images have been introduced, but the accuracy of these algorithms is unclear. This work benchmarks the accuracy of the global noise (GN) algorithm for automatic noise measurement in contrast-enhanced abdomen CT exams in comparison to precise reference noise measurements. The GN algorithm was further optimized compared to the previous report in the literature. Methods Reference values of noise were established in a public image dataset of 82 contrast-enhanced abdomen CT exams. The reference noise values were obtained by manual regions-of-interest measurements of pixel standard deviation in the liver parenchyma according to an instruction protocol. Noise measurements taken by six observers were averaged together to improve reference noise statistical precision. The GN algorithm was used to automatically measure noise in each image set. The accuracy of the GN algorithm was determined in terms of RMS error compared to reference noise. The GN algorithm was optimized by conducting 1000 trials with random algorithm parameter values. The trial with the lowest RMS error was used to select optimum algorithm parameters. Results The range of noise across CT image sets was 8.8-28.8 HU. Reference noise measurements were made with a precision of ±0.78 HU (95% confidence interval). The RMS error of automatic noise measurement was 0.93 HU (0.77-1.19 HU 95% confidence interval). The automatic noise measurements were equally accurate across image sets of varying noise magnitude. Optimum GN algorithm parameter values were: a kernel size of 7 pixels, and soft tissue lower and upper thresholds of 0 and 170 HU, respectively. Conclusions The performance of automatic noise measurement was benchmarked in a large clinical CT dataset. The study provides a framework for thorough validation of automatic clinical image quality measurement methods. The GN algorithm was optimized and validated for automatic measurement of soft-tissue noise in abdomen CT exams.

To present recommendations for the use of imaging for evaluation and procedural guidance of brachytherapy for cervical cancer patients.An expert panel comprised of members of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease Focused Panel and the American Brachytherapy Society jointly assessed the existing literature and provide data-driven guidance on imaging protocol development, interpretation, and reporting.Image-guidance during applicator implantation reduces rates of uterine perforation by the tandem. Postimplant images may be acquired with radiography, computed tomography (CT), or magnetic resonance imaging (MRI), and CT or MRI are preferred due to a decrease in severe complications. Pre-brachytherapy T2-weighted MRI may be used as a reference for contouring the high-risk clinical target volume (HR-CTV) when CT is used for treatment planning. Reference CT and MRI protocols are provided for reference.Image-guided brachytherapy in locally advanced cervical cancer is essential for optimal patient management. Various imaging modalities, including orthogonal radiographs, ultrasound, computed tomography, and magnetic resonance imaging, remain integral to the successful execution of image-guided brachytherapy.

Absorbable inferior vena cava filters (IVCFs) offer a promising alternative to metallic retrievable filters in providing protection against pulmonary embolism (PE) for patients contraindicated for anticoagulant therapy. However, because absorbable filters are not radiopaque, monitoring of the filter using conventional X-ray imaging modalities (e.g. plain film radiographs, computed tomography [CT] and fluoroscopy) during deployment and follow-up is not possible and represents a potential obstacle to widespread clinical integration of the device. Here, we demonstrate that gold nanoparticles (AuNPs) infused into biodegradable filters made up of poly-p-dioxanone (PPDO) may improve device radiopacity without untoward effects on device efficacy and safety, as assessed in swine models for 12 weeks. The absorbable AuNP-infused filters demonstrated significantly improved visualization using CT without affecting tensile strength, in vitro degradation, in vivo resorption, or thrombus-capturing efficacy, as compared to similar non-AuNPs infused resorbable IVCFs. This study presents a significant advancement to the development of imaging enhancers for absorbable IVCFs.

Convective transport is an important phenomenon for nanomedicine delivery. We present an imaging-based approach to recover tissue properties that are significant in the accumulation of nanoparticles delivered via systemic methods. The classical pharmacokinetic analysis develops governing equations for the particle transport from a first principle mass balance. Fundamentally, the governing equations for compartmental mass balance represent a spatially invariant mass transport between compartments and do not capture spatially variant convection phenomena. Further, the parameters recovered from this approach do not necessarily have direct meaning with respect to the governing equations for convective transport. In our approach, a framework is presented for directly measuring permeability in the sense of Darcy flow through porous tissue. Measurements from our approach are compared to an extended Tofts model as a control. We demonstrate that a pixel-wise iterative clustering algorithm may be applied to reduce the parameter space of the measurements. We show that measurements obtained from our approach are correlated with measurements obtained from the extended Tofts model control. These correlations demonstrate that the proposed approach contains similar information to an established compartmental model and may be useful in providing an alternative theoretical framework for parameterizing mathematical models for treatment planning and diagnostic studies involving nanomedicine where convection dominated effects are important.

PURPOSE: Material differentiation has been made possible using dual-energy CT (DECT), in which the unique, energy-dependent attenuating characteristics of materials can provide new diagnostic information. One promising application is the clinical integration of biodegradable polymers as temporary implantable medical devices impregnated with high-atomic number (high-Z) materials. The purpose of this study was to explore the incorporation of high-atomic-number (high-Z) contrast materials in a bioresorbable inferior vena cava filter for advanced computed tomography (CT)-based monitoring of its location and differentiating from surrounding materials. MATERIALS AND METHODS: Imaging optimization and calibration studies were performed using a body phantom. The dual-energy CT (DECT) ratios for iron, zirconium, barium, gadolinium, ytterbium, tantalum, tungsten, gold, and bismuth were generated for peak kilovoltage combinations of 80/150Sn, 90/150Sn, and 100/150Sn kVp in dual-source CT via linear regression of the CT numbers at low and high energies. A secondary calibration of the material map to the nominal material concentration was generated to correct for use of materials other than iodine. CT number was calibrated to the material concentration based on single-energy CT (SECT) with additional filtration (150Sn kVp). These quantification methods were applied to monitoring of biodegradable inferior vena cava filters (IVCFs) made of braided poly(p-dioxanone) sutures infused with ultrasmall bismuth nanoparticles (BiNPs) implanted in an adult domestic pig. RESULTS: Qualitative material differentiation was optimal for high-Z (>73) contrast agents in DECT. However, quantification became nonlinear and inaccurate as the K-edge of the material increased. Using the high-energy (150Sn kVp) data component as a SECT scan, the linearity of quantification curves was maintained with lower limits of detection than with DECT. Among the materials tested, bismuth had optimal differentiation from iodine in DECT while maintaining increased contrast in high-energy SECT for quantification (11.5% error). Coating the IVCF with BiNPs resulted in markedly greater radiopacity (maximum CT number, 2028 HU) than that of an uncoated IVCF (maximum CT number, 127 HU). Using DECT imaging and processing, the BiNP-IVCF could be clearly differentiated from iodine contrast injected into the inferior vena cava of the pig. CONCLUSIONS: These findings may improve widespread integration of medical devices incorporated with high-Z materials into the clinic, where technical success, possible complications, and device integrity can be assessed intraoperatively and postoperatively via DECT imaging.

We illuminate a possible explanatory pathophysiologic mechanism for retinal cellular neuropathy by means of a novel diagnostic method using ophthalmoscopic imaging and a molecular imaging agent targeted to fast axonal transport. The retinal neuropathies are a group of diseases with damage to retinal neural elements. Retinopathies lead to blindness but are typically diagnosed late, when substantial neuronal loss and vision loss have already occurred. We devised a fluorescent imaging agent based on the non-toxic C fragment of tetanus toxin (TTc), which is taken up and transported in neurons using the highly conserved fast axonal transport mechanism. TTc serves as an imaging biomarker for normal axonal transport and demonstrates impairment of axonal transport early in the course of an N-methyl-D-aspartic acid (NMDA)-induced excitotoxic retinopathy model in rats. Transport-related imaging findings were dramatically different between normal and retinopathic eyes prior to presumed neuronal cell death. This proof-of-concept study provides justification for future clinical translation.

Purpose To determine the accuracy of dual-energy computed tomographic (CT) quantitation in a phantom system comparing fast kilovolt peak-switching, dual-source, split-filter, sequential-scanning, and dual-layer detector systems. Materials and Methods A large elliptical phantom containing iodine (2, 5, and 15 mg/mL), simulated contrast material-enhanced blood, and soft-tissue inserts with known elemental compositions was scanned three to five times with seven dual-energy CT systems and a total of 10 kilovolt peak settings. Monochromatic images (50, 70, and 140 keV) and iodine concentration images were created. Mean iodine concentration and monochromatic attenuation for each insert and reconstruction energy level were recorded. Measurement bias was assessed by using the sum of the mean signed errors measured across relevant inserts for each monochromatic energy level and iodine concentration. Iodine and monochromatic errors were assessed by using the root sum of the squared error of all measurements. Results At least one acquisition paradigm per scanner had iodine biases (range, -2.6 to 1.5 mg/mL) with significant differences from zero. There were no significant differences in iodine error (range, 0.44-1.70 mg/mL) among the top five acquisition paradigms (one fast kilovolt peak switching, three dual source, and one sequential scanning). Monochromatic bias was smallest for 70 keV (-12.7 to 15.8 HU) and largest for 50 keV (-80.6 to 35.2 HU). There were no significant differences in monochromatic error (range, 11.4-52.0 HU) among the top three acquisition paradigms (one dual source and two fast kilovolt peak switching). The lowest accuracy for both measures was with a split-filter system. Conclusion Iodine and monochromatic accuracy varies among systems, but dual-source and fast kilovolt-switching generally provided the most accurate results in a large phantom. © RSNA, 2017 Online supplemental material is available for this article.

Purpose Accurate deformable image registration is necessary for longitudinal studies. The error associated with commercial systems has been evaluated using computed tomography (CT). Several in-house algorithms have been evaluated for use with magnetic resonance imaging (MRI), but there is still relatively little information about MRI deformable image registration. This work presents an evaluation of two deformable image registration systems, one commercial (Velocity) and one in-house (demons-based algorithm), with MRI using two different metrics to quantify the registration error. Methods The registration error was analyzed first with synthetic MR images. These images were generated from inter-patient and intra-patient variation models trained on 28 patients. Four synthetic posttreatment images were generated for each of four synthetic pretreatment images, resulting in 16 image registrations for both the T1- and T2-weighted images. The synthetic post-treatment images were registered to their corresponding synthetic pre-treatment image. The registration error was calculated between the known deformation vector field and the generated deformation vector field from the image registration system. The registration error was also analyzed using a porcine phantom with ten implanted 0.35-mm diameter gold markers. The markers were visible on CT but not MRI. CT, T1-weighted MR, and T2-weighted MR images were taken in four different positions. The markers were contoured on the CT images and rigidly registered to their corresponding MR images. The MR images were deformably registered and the distance between the projected marker location and true marker location was measured as the registration error. Results The synthetic images were evaluated only on Velocity. Root mean square errors (RMSEs) of 0.76 mm in the left-right (LR) direction, 0.76 mm in the anteroposterior (AP) direction, and 0.69 mm in the superior-inferior (SI) direction were observed for the T1-weighted MR images. RMSEs of 1.1 mm in the LR direction, 0.75 mm in the AP direction, and 0.81 mm in the SI direction were observed for the T2-weighted MR images. The porcine phantom MR images, when evaluated with Velocity, had RMSEs of 1.8, 1.5, and 2.7 mm in the LR, AP, and SI directions for the T1-weighted images and 1.3, 1.2, and 1.6 mm in the LR, AP, and SI directions for the T2-weighted images. When the porcine phantom images were evaluated with the in-house demons-based algorithm, RMSEs were 1.2, 1.5, 2.1 mm in the LR, AP, and SI directions for the T1-weighted images and 0.81, 1.1, and 1.1 mm in the LR, AP, and SI directions for the T2-weighted images. Conclusions The MRI registration error was low for both Velocity and the in-house demons-based algorithm according to both image evaluation methods, with all RMSEs below 3 mm. This implies that both image registration systems can be used for longitudinal studies using MRI. This article is protected by copyright. All rights reserved.

To evaluate the quantitative attenuation and reliability of virtual non-contrast (VNC) images of the abdomen acquired from multiphasic scans with a dual-energy computed tomography (DECT) system and compare it with that of true non-enhanced images (TNC) on second- (Flash) and third- (Force) generation DECT scanners. This retrospective study was approved by the institutional review board and included 123 patients with pancreatic cancer who had undergone routine clinical multiphasic DECT examinations at our institution using Flash and Force scanners between March and August 2017. VNC images of the abdomen were reconstructed from late arterial phase images. For every patient, regions-of-interest were defined in the aorta, fluid-containing structures (gallbladder, pleural effusion, and renal cysts > 10 mm), paravertebral muscles, subcutaneous fat, spleen, pancreas, renal cortex, and liver (eight locations) on TNC and VNC images. The mean attenuation of VNC was compared with TNC by organ for each CT scanner using an equivalence test and the Bland–Altman plot. The mean attenuations for TNC or VNC were compared between the Force and Flash CT scanners using a two-sample t test. The VNC attenuation of organs on the Force scanner was lower than was that on the Flash, and the mean attenuation difference in different organs on the Force was closer to 0. The estimated means of TNC and VNC were equivalent for an equivalence margin of 10 on the Force scanner. VNC images in DECT are a promising alternative to TNC images. In clinical scenarios in which non-enhanced CT images are required but are not available for accurate diagnosis, VNC images can potentially serve as an alternative to TNC images without the radiation exposure risks.

Background Assessments of the quantitative limitations among the six commercially available dual-energy (DE) CT acquisition schemes used by major CT manufacturers could aid researchers looking to use iodine quantification as an imaging biomarker. Purpose To determine the limits of detection and quantification of DE CT in phantoms by comparing rapid peak kilovoltage switching, dual-source, split-filter, and dual-layer detector systems in six different scanners. Materials and Methods Seven 50-mL iohexol solutions were used, with concentrations of 0.03-2.0 mg iodine per milliliter. The solutions and water sample were scanned five times each in two phantoms (small, 20-cm diameter; large, 30 × 40-cm diameter) with six DE CT systems and a total of 10 peak kilovoltage settings or combinations. Iodine maps were created, and the mean iodine signal in each sample was recorded. The limit of blank (LOB) was defined as the upper limit of the 95% confidence interval of the water sample. The limit of detection (LOD) was defined as the concentration with a 95% chance of having a signal above the LOB. The limit of quantification (LOQ) was defined as the lowest concentration where the coefficient of variation was less than 20%. Results The LOD range was 0.021-0.26 mg/mL in the small phantom and 0.026-0.55 mg/mL in the large phantom. The LOQ range was 0.07-0.50 mg/mL in the small phantom and 0.20-1.0 mg/mL in the large phantom. The dual-source and rapid peak kilovoltage switching systems had the lowest LODs, and the dual-layer detector systems had the highest LODs. Conclusion The iodine limit of detection using dual-energy CT systems varied with scanner and phantom size, but all systems depicted iodine in the small and large phantoms at or below 0.3 and 0.5 mg/mL, respectively, and enabled quantification at concentrations of 0.5 and 1.0 mg/mL, respectively. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Hindman in this issue.

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

The aim of this study was to develop a diagnostic framework for distinguishing calcific from hemorrhagic cerebral lesions using dual-energy computed tomography (DECT) in an anthropomorphic phantom system.An anthropomorphic phantom was designed to mimic the CT imaging characteristics of the human head. Cylindrical lesion models containing either calcium or iron, mimicking calcification or hemorrhage, respectively, were developed to exhibit matching, and therefore indistinguishable, single-energy CT (SECT) attenuation values from 40 to 100 HU. These lesion models were fabricated at 0.5, 1, and 1.5 cm in diameter and positioned in simulated cerebrum and skull base locations within the anthropomorphic phantom. All lesion sizes were modeled in the cerebrum, while only 1.5-cm lesions were modeled in the skull base. Images were acquired using a GE 750HD CT scanner and an expansive dual-energy protocol that covered variations in dose (36.7-132.6 mGy CTDIvol, n = 12), image thickness (0.625-5 mm, n = 4), and reconstruction filter (soft, standard, detail, n = 3) for a total of 144 unique technique combinations. Images representing each technique combination were reconstructed into water and calcium material density images, as well as a monoenergetic image chosen to mimic the attenuation of a 120-kVp SECT scan. A true single-energy routine brain protocol was also included for verification of lesion SECT attenuation. Points representing the 3 dual-energy reconstructions were plotted into a 3-dimensional space (water [milligram/milliliter], calcium [milligram/milliliter], monoenergetic Hounsfield unit as x, y, and z axes, respectively), and the distribution of points analyzed using 2 approaches: support vector machines and a simple geometric bisector (GB). Each analysis yielded a plane of optimal differentiation between the calcification and hemorrhage lesion model distributions. By comparing the predicted lesion composition to the known lesion composition, we identified the optimal combination of CTDIvol, image thickness, and reconstruction filter to maximize differentiation between the lesion model types. To validate these results, a new set of hemorrhage and calcification lesion models were created, scanned in a blinded fashion, and prospectively classified using the planes of differentiation derived from support vector machine and GB methods.Accuracy of differentiation improved with increasing dose (CTDIvol) and image thickness. Reconstruction filter had no effect on the accuracy of differentiation. Using an optimized protocol consisting of the maximum CTDIvol of 132.6 mGy, 5-mm-thick images, and a standard filter, hemorrhagic and calcific lesion models with equal SECT attenuation (Hounsfield unit) were differentiated with over 90% accuracy down to 70 HU for skull base lesions of 1.5 cm, and down to 100 HU, 60 HU, and 60 HU for cerebrum lesions of 0.5, 1.0, and 1.5 cm, respectively. The analytic method that yielded the best results was a simple GB plane through the 3-dimensional DECT space. In the validation study, 96% of unknown lesions were correctly classified across all lesion sizes and locations investigated.We define the optimal scan parameters and expected limitations for the accurate classification of hemorrhagic versus calcific cerebral lesions in an anthropomorphic phantom with DECT. Although our proposed DECT protocol represents an increase in dose compared with routine brain CT, this method is intended as a specialized evaluation of potential brain hemorrhage and is thus counterbalanced by increased diagnostic benefit. This work provides justification for the application of this technique in human clinical trials.

PURPOSE: Magnetic resonance imaging (MRI) provides non-invasive evaluation of patient’s anatomy without using ionizing radiation. Due to this and the high soft-tissue contrast, MRI use has increased and has potential for use in longitudinal studies where changes in patients’ anatomy or tumors at different time points are compared. Deformable image registration can be useful for these studies. Here we describe two data sets that can be used to evaluate the registration accuracy of systems for MR images, as it cannot be assumed to be the same as that measured on CT images. ACQUISITION AND VALIDATION METHODS: Two sets of images were created to test registration accuracy. (1) A porcine phantom was created by placing ten 0.35 mm gold markers into porcine meat. The porcine phantom was immobilized in a plastic container with movable dividers. T1-weighted, T2-weighted, and CT images were acquired with the porcine phantom compressed in 4 different ways. The markers were not visible on the MR images, due to the selected voxel size, so they did not interfere with the measured registration accuracy, while the markers were visible on the CT images and were used to identify the known deformation between positions. (2) Synthetic images were created using 28 head and neck squamous cell carcinoma patients who had MR scans pre-, mid-, and post-radiotherapy treatment. An inter- and intra-patient variation model was created using these patient scans. Four synthetic pre-treatment images were created using the inter-patient model, and four synthetic post-treatment images were created for each of the pre-treatment images using the intra-patient model. DATA FORMAT AND USAGE NOTES: The T1-weighted, T2-weighted, and CT scans of the porcine phantom in the four positions are provided. Four T1-weighted synthetic pre-treatment images each with four synthetic post-treatment images, and four T2-weighted synthetic pre-treatment images each with four synthetic post-treatment images are provided. Additionally, the applied deformation vector fields to generate the synthetic post-treatment images are provided. The data is available on TCIA under the collection MRI-DIR. POTENTIAL APPLICATIONS: The proposed database provides two sets of images (one acquired and one computer generated) for use in evaluating deformable image registration accuracy. T1- and T2-weighted images are available for each technique as the different image contrast in the two types of images may impact the registration accuracy.

Multiple studies in the literature have proposed diagnostic thresholds based on Multi-Energy Computed Tomography (MECT) iodine maps. However, it is critical to determine the minimum detectable iodine concentration for MECT systems to assure the clinical accuracy for various measured concentrations for these image types. In this study, seven serial dilutions of iohexol were made with concentrations from 0.03 to 2.0 mg Iodine/mL in 50 mL centrifuge tubes. The dilutions and one blank vial were scanned five times each in two scatter conditions: within a 20.0 cm diameter (Head) phantom, and a 30.0 cm x 40.0 cm elliptical (Body) phantom. This was repeated on a total of six scanners from three vendors: fast-kVp switching, dual-source dual-energy CT, dual-layer detector CT, and split-filter CT. Scan parameters and dose were matched as closely as possible across systems, and iodine maps were reconstructed. Regions-of-Interest (ROIs) were placed on 5 consecutive images within each vial, for a total of 25 measurements per sample. The mean and standard deviation were calculated for each sample. The Limit of Detection (LOD) was defined as the concentration that had a 95% chance of having a signal above the 95% confidence interval of the measured blank samples. The range of LODs was 0.021 – 0.484 mg I/mL in the head phantom and 0.125 – 0.547 mg I/mL in the body phantom. The LOD for iodinated contrast using MECT systems changed with scatter and attenuation conditions. The limit of detection for all conditions was under 0.5 mg Iodine/mL.

The purpose of this study was to determine typical radiation dose levels to patients undergoing CT-guided interventional procedures.A total of 571 patients undergoing CT interventional procedures were included in this retrospective data analysis study. Enrolled patients underwent one of five procedures: cryoablation, aspiration, biopsy, drain, or injection. With each procedure, two scan modes were used, either intermittent (no table increment) or helical mode. Skin dose was estimated from the volumetric CT dose index (CTDI(vol)) and phantom measurements. Effective dose was calculated by multiplying dose-length product (DLP) and conversion factor (k factor) for helical mode, and using Monte Carlo organ dose coefficients for intermittent mode.The mean (± SD) skin doses were 728 ± 382, 130 ± 104, 128 ± 81, 152 ± 105, and 195 ± 147 mGy, and the mean effective doses were 119.7 ± 50.3, 20.1 ± 11.0, 13.8 ± 9.2, 25.3 ± 15.4, and 9.1 ± 5.5 mSv for each of the five procedures, respectively. The maximum skin dose was 1.95 Gy. The mean effective dose across all procedure types was 24.1 mSv, with 2.3 mSv from intermittent scans and 21.8 mSv from helical scans.Substantial dose differences were observed among the five procedures. The risk of deterministic effects appears to be very low, because the maximum observed skin dose did not exceed the threshold for transient skin erythema (2 Gy). The average risk of stochastic effects was comparable to that of 1-10 abdomen and pelvis CT examinations. Although the intermittent mode can contribute substantially to skin dose, it contributes minimally to the effective dose because of the much shorter scan range used.

Purpose: Although a major benefit of dual-energy CT is its quantitative capabilities, it is critical to understand how results vary by scanner manufacturer and/or model before making clinical patient management decisions. Each manufacturer utilizes a specific dual-energy CT approach; cross-calibration may be required for facilities with more than one dual-energy CT scanner type. Methods: A solid dual-energy quality control phantom (Gammex, Inc.; Appleton, WI) representing a large body cross-section containing three Iodine inserts (2mg/ml, 5mg/ml, 15 mg/ml) was scanned on these CT systems: GE HD-750 (80/140kVp), prototype GE Revolution CT with GSI (80/140kVp), Siemens Flash (80/140kVp and 100/140kVp), and Philips IQon (120kVp and 140kVp). Iodine content was measured in units of concentration (mg/ml) from a single 5mm-thick central image. Three to five acquisitions were performed on each scanner platform in order to compute standard deviation. Scan acquisitions were approximately dose-matched (∼25mGy CTDIvol) and image parameters were as consistent as possible (thickness, kernel, no noise reduction applied). Results: Iodine measurement error ranges were −0.24ߝ0.16 mg/ml for the 2mg/ml insert (−12.0 − 8.0%), −0.28–0.26 mg/ml for the 5mg/ml insert (−5.6 − 5.2%), and −1.16−0.99 mg/ml for the 15mg/ml insert (−7.7 − 6.6%). Standard deviations ranged from 0 to 0.19 mg/ml for the repeated acquisitions from each scanner. The average iodine measurement error and standard deviation across all systems and inserts was −0.21 ± 0.48 mg/ml (−1.5 ± 6.48%). The largest absolute measurement error was found in the 15mg/ml iodine insert. Conclusion: There was generally good agreement in Iodine quantification across 3 dual-energy CT manufacturers and 4 scanner models. This was unexpected given the widely different underlying dual-energy CT mechanisms employed. Future work will include additional scanner platforms, independent verification of the Iodine insert standard concentrations (especially the 15 mg/ml insert), and how much measurement variability can be clinically tolerated. This research has been supported by funds from Dr. William Murphy, Jr., the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging at MD Anderson Cancer Center.

Objective To compare conventional diffusion-weighted imaging (DWI) with spectral spatial excitation (cDWI) and an enhanced DWI with additional adiabatic spectral inversion recovery (eDWI) for 3-T breast magnetic resonance imaging (MRI). Methods Twenty-four patients were enrolled in the study with both cDWI and eDWI. Three breast radiologists scored cDWI and eDWI images of each patient for fat-suppression quality, geometric distortion, visibility of normal structure and biopsy-proven lesions, and overall image quality. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) for evaluable tissues were measured. Statistical tests were performed for qualitative and quantitative comparisons. Results Diffusion-weighted imaging with spectral spatial excitation yielded significantly higher CNR and SNR on a lesion basis, and higher glandular CNR and SNR and muscle SNR on a patient basis. Enhanced DWI also yielded significantly higher qualitative scores in all categories. No significant difference was found in ADC values. Conclusions Enhanced DWI provided superior image quality and higher CNR and SNR on a lesion basis. Enhanced DWI can replace cDWI for 3-T breast DWI.

Purpose: Intracranial hemorrhage and calcification with Single-Energy CT (SECT) attenuation below 100HU cannot be reliably identified using currently clinically available means. Calcification is typically benign but hemorrhage can carry a risk of intracranial bleeding and contraindicate use of anticoagulant therapies. A biologically-relevant phantom was used to investigate identification of unknown intracranial lesions using dual-energy CT (DECT) as a verification of prior lesion differentiation results. Methods: Prior phantom work investigating calcification and hemorrhage differentiation resulted in 3D-DECT raw data (water density, calcium density, 68keV) for a range of DECT protocol variations: image thicknesses (1.25, 2.5, 3.75, 5mm), CTDIvol (36.7 to 132.6mGy) and reconstruction algorithms (Soft, Standard, Detail). Acquisition-specific raw data were used to create a plane of optimal differentiation based on the geometric bisector of 3D-linear regression of the two lesion distributions. Verification hemorrhage and calcification lesions, ranging in size from 0.5 to 1.5cm, were created at varying attenuation from 50 to 100HU. Lesions were inserted into a biologically-relevant brain phantom and scanned using SECT (3.75mm images, Standard, 67mGy) and a range of DECT protocols (3.75mm images, Standard, [67, 105.6, 132.6mGy]). 3D-DECT data were collected and blinded for analysis. The 3D-DECT distribution of the lesion was then compared to the acquisition-matched geometric bisector plane and the mean lesion value’s position relative to the plane, indicating lesion identity, and the percentage of voxels on the identified side of the plane, indicating identification confidence, were derived. Results: 98% of the 120 lesions investigated were identified correctly as hemorrhage or calcification. 74% were identified with greater than 80% confidence. Increases in CTDIvol and lesion diameter were associated with increased identification confidence. Conclusion: Intracranial lesions of unknown etiology were identified with 80% confidence for 74% of lesions investigated. These phantom data suggest that the identification of intracranial lesions below 100HU is clinically feasible using DECT. This research was conducted at the MD Anderson Center for Advanced Biomedical Imaging in-part with equipment support from General Electric Healthcare

Purpose: It can be logistically quite difficult to scan patients on the same exact device for their repeat visits in multi-scanner facilities. The reliability between dual-energy CT scanners’ quantitative results is not known, nor is their individual repeatability. Therefore, we evaluated inter- and intra-scanner variability with respect to several key clinical quantitative metrics specific to dual-energy CT. Methods: Eleven identical GE HD-750 CT scanners in a busy clinical environment were used to perform dual-energy (DE) CT scans of a large elliptical quality control (QC) phantom (Gammex, Inc.; Middleton, WI) which contains many standard insert materials. The DE-QC phantom was scanned bi-weekly during 2016; 3 to 4 scans were obtained from each scanner (a total of 35 data sets were used for analysis). Iodine accuracy for the 2mg/ml, 5mg/ml and 15mg/ml rods (from the Iodine(Water) image set) and soft tissue HU (40 HU based on NIST constants) from the 50keV data set were used to assess inter- and intra-scanner variability (standard deviation). Results: Intra-scanner variability average for 2mg/ml Iodine was 0.10 mg/ml (range 0.05–0.15 mg/ml), for 5mg/ml Iodine was 0.12 mg/ml (range 0.07–0.16 mg/ml), for 15 mg/ml Iodine was 0.25 mg/ml (range 0.16–0.37 mg/ml), and for the soft tissue inserts was 2.1 HU (range 1.8–2.6 HU). Inter-scanner variability average for 2mg/ml Iodine was 0.16 mg/ml (range 0.11–0.19 mg/ml), for 5mg/ml Iodine was 0.18 mg/ml (range 0.11–0.22 mg/ml), for 15 mg/ml Iodine was 0.35 mg/ml (range 0.23–0.44 mg/ml), and for the soft tissue inserts was 3.8 HU (range 3.1–4.5 HU). Conclusion: Intra-scanner variability for the iodine and soft tissue inserts averaged 3.1% and 5.2% respectively, and inter-scanner variability for these regions analyzed averaged 5.0% and 9.5%, respectively. Future work will include determination of smallest measurable change and acceptable limits for DE-CT scanner variability over longer time intervals. This research has been supported by funds from Dr. William Murphy, Jr., the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging at MD Anderson Cancer Center.

Purpose: Although dual-energy CT provides improved sensitivity of HU for certain tissue types at lower simulated energy levels, if these values vary by scanner type they may impact clinical patient management decisions. Each manufacturer has selected a specific dual-energy CT approach (or in one case, three different approaches); understanding HU variability among low monochromatic images may be required when more than one dual-energy CT scanner type is available for use. Methods: A large elliptical dualenergy quality control phantom (Gammex Inc.; Middleton, WI) containing several standard tissue type materials was scanned at least three times on each of the following systems: GE HD750, prototype GE Revolution CT with GSI, Siemens Flash, Siemens Edge, Siemens AS 128, and Philips IQon. Images were generated at 50, 70, and 140 keV. Soft tissue and Iodine HU were measured on a single central 5mm-thick image; NIST constants were used to calculate the ideal HU for each material. Scan acquisitions were approximately dose-matched (∼25mGy CTDIvol) and image parameters were held as consistent as possible (thickness, kernel, no noise reduction). Results: Measured soft tissue (29 HU at 120 kVp) varied from 28 HU to 44 HU at 50 keV (excluding one outlier), from 21 HU to 31 HU at 70 keV, and from 19 HU to 32 HU at 140 keV. Measured iodine (5mg/ml, 106 HU at 120 kVp) varied from 246 HU to 280 HU at 50 keV, from 123 HU to 129 HU at 70 keV, and from 22 HU to 32 HU at 140 keV. Conclusion: Measured HU in standard rods across 3 dual-energy CT manufacturers and 6 scanner models varied directly with monochromatic level, with the most variability was observed at 50 keV and least variability at 70keV. Future work will include additional scanner platforms and how measurement variability impacts radiologists. This research has been supported by funds from Dr. William Murphy, Jr., the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging at MD Anderson Cancer Center.

To determine relationships among patient size, scanner radiation output, and size-specific dose estimates (SSDEs) for adults who underwent computed tomography (CT) of the torso.Informed consent was waived for this institutional review board-approved study of existing data from 545 adult patients (322 men, 223 women) who underwent clinically indicated CT of the torso between April 1, 2007, and May 13, 2007. Automatic exposure control was used to adjust scanner output for each patient according to the measured CT attenuation. The volume CT dose index (CTDI(vol)) was used with measurements of patient size (anterioposterior plus lateral dimensions) and the conversion factors from the American Association of Physicists in Medicine Report 204 to determine SSDE. Linear regression models were used to assess the dependence of CTDI(vol) and SSDE on patient size.Patient sizes ranged from 42 to 84 cm. In this range,CTDI(vol) was significantly correlated with size (slope = 0.34 mGy/cm; 95% confidence interval [CI]: 0.31, 0.37 mGy/cm; R(2) = 0.48; P.001), but SSDE was independent of size (slope = 0.02 mGy/cm; 95% CI: -0.02, 0.07 mGy/cm; R(2) = 0.003; P = .3). These R(2) values indicated that patient size explained 48% of the observed variability in CTDI(vol) but less than 1% of the observed variability in SSDE. The regression of CTDI(vol) versus patient size demonstrated that, in the 42-84-cm range, CTDI(vol) varied from 12 to 26 mGy. However, use of the evaluated automatic exposure control system to adjust scanner output for patient size resulted in SSDE values that were independent of size.For the evaluated automatic exposure control system,CTDI(vol) (scanner output) increased linearly with patient size; however, patient dose (as indicated by SSDE) was independent of size.

Dual energy computed tomography (CT) has been previously shown to be capable of quantifying iron concentration in a phantom model. In this work, a commercial three material decomposition algorithm was investigated with the aim of quantifying iron concentration in vivo with dual energy CT. Iron (III) nitrate solutions of five/seven different concentrations were placed in syringes of two different cross-sectional areas within anthropomorphic phantoms of three different sizes and scanned using various x-ray tube potentials and beam filtration levels. A commercial three material decomposition software package was used to measure iron concentration values in specified regions of interest. These data were used to assess the effects of tube potential, beam filtration, phantom size, and object size on the ability of dual energy CT to accurately quantify iron concentration. The object's cross sectional area (diameter of syringe containing the iron solution) affected the accuracy of the iron quantification, with measurements averaged over a larger region of interest having improved accuracy. In most cases, the greater spectral separation afforded by the tin filtration improved the accuracy of the iron quantification. Using the larger syringes (approximately 100 mm 2 cross sectional area) and small phantom size, dual energy CT measurements of the three highest iron concentrations (approximately 10 - 18 mg/ml) had a maximum percent difference from the known value of 21%.

Dual-source computed tomography (CT) utilizes two x-ray tubes and two detectors simultaneously for the purpose of obtaining 83 msec temporal resolution, 160 kW of x-ray power reserve, or dual-kV (dual-energy) scan capabilities. One inherent constraint of such a design is cross-scatter radiation, which occurs when x-rays from tube A are scattered by the patient and detected by detector B, or vice versa. In the evaluated dual-source CT scanner, an on-line cross-scatter correction technique is used to address this limitation. The technique, available using the 14×1.2-mm collimation, measures scattered radiation along the z axis using detector rows beyond those corresponding to the 16.8 mm nominal total beam width. These direct measurements of scattered radiation are used to correct the measured projection data (scattered and primary radiation) for cross-scatter. A semi-anthropomorphic thorax phantom was used with increasing thicknesses of tissue-equivalent material to simulate small, medium, large and extra-large patients. Phantoms were scanned using single-source and dual-source protocols at 80, 100, 120 and 140 kV, and the mean and standard deviation of the CT numbers in a water-equivalent cylinder located centrally within the phantom measured. For this comparison, images reconstructed using only tube A data from the dual-source acquisition were compared to the single-source images, also obtained using tube A. The differences in the mean and standard deviation of the measured CT numbers between the dual-source tube A images, which were corrected for cross-scatter, and the single-source images, where no cross-scatter existed, were determined for all tube energies and phantom sizes. The differences in mean CT number ranged from -5.2 to 1.3 HU, and the differences in standard deviations ranged from -4.5 to 3.0 HU. We conclude, therefore, that use of the evaluated on-line cross-scatter correction algorithm results in negligible differences in CT number and image noise between single-source and dual-source image data, independent of phantom size and tube potential.

Purpose: To evaluate the timing and shape of the kilovoltage (kV) waveform for a fast-kV switching dual-energy CT system using a non-invasive method. Methods: A kV divider with mobile filter pack was connected to a digital oscilloscope and scanned using a fast-kV switching dual-energy CT system in service mode. The tube was stationary, so exposure time was equivalent to rotation time. In this system, the generator switches quickly between two nominal voltages of 80kV and 140kV. The predicted waveform period was calculated given 1968 projections per exposure/rotation. Two Gemstone Spectral Imaging (GSI) service settings, GSI-2 and GSI-3, with exposure times of 0.8sec and 0.5sec, respectively, were analyzed. The data were binned into high (>110kV) and low (

Purpose: Absorbable IVC filters are shown to be safe and efficacious in preventing pulmonary embolism. These absorbable filters disappear from the body after their required duration, alleviating costly removal procedures and downstream complications. Monitoring the positioning and integrity of absorbable devices using dual-energy computed tomography (DECT) would improve treatment efficacy. The purpose of this study is to determine the limit of detection and the energy dependence of DECT for various contrast agents that may be infused within the IVC filters including gold nanoparticles (AuNP) having diameters of 2 and 4 nm. Methods: All imaging studies were performed on a GE Discovery CT750 system in Gemstone Spectral Imaging (GSI) mode. Plastic vials containing the contrast agent solutions of water and blood were placed in a water bath, and images were acquired with the GSI-5 preset. The images were reformatted into the coronal plane and 5mm diameter ROIs were placed within each solution on a GE Advantage Workstation. Monoenergetic reconstructions were generated from 40 – 140 keV. Results: Mass attenuation (contrast per unit density) for AuNPs was greater than iron, but less than barium and iodine. Contrast was 10.2 (± 3.6) HU for 4 nm AuNP at 0.72 mg/ml and 12.1 (± 4.2) for 2 nm AuNP at 0.31 mg/ml at 70 keV suggesting reasonable chance of visualization at these concentrations for 70 keV reconstruction. The contrast as a function of CT energy is similar in both water and blood. Iodine is most dependent, followed closely by barium and iron, and trailed by a large margin by the AuNP. This was unexpected given Au’s large atomic number and the predominance of photoelectric effect at low energy. Conclusion: Infusion of IVC filters with AuNP is feasible. Discrimination of AuNP-infused IVC filters from surrounding anatomy warrants further investigation.

Purpose: A prototype quality control (QC) phantom and analysis process has been designed specifically to monitor dual-energy CT and address the current lack of quantitative oversight of the spectral capabilities of these scanners. Methods: A prototype solid water phantom was designed with multiple material inserts, and to support both head and body protocols. Inserts included tissue equivalent and material rods (iodine, iron, calcium) at various concentrations. The oval body phantom, measuring 30cm×40cm×15cm, was scanned using four dual-energy protocols with CTDIvol ranges of 19.6–62mGy (0.516 pitch) and 10.3–32.5mGy (0.984 pitch), and rotation times ranging from 0.5-1sec. The circular head phantom, measuring 22cm in diameter by 15cm, was scanned using three dual-energy protocols with CTDIvol ranges of 67–132.6mGy (0.531 pitch) and 36.7–72.7mGy (0.969 pitch), and rotation times ranging from 0.5–0.9sec. All images were reconstructed at 50, 70, 110 and 140 keV, and using a water-iodine material basis pair. The images were evaluated for iodine quantification accuracy and stability of monoenergetic reconstructions. The phantom was scanned twice on ten GE 750HD CT scanners to evaluate inter-scanner agreement, as well as ten times on a single scanner over a oneweek period to evaluate intra-scanner repeatability. Results: Preliminary analysis revealed consistent (inter- and intra-scanner) iodinemore » quantification accuracy within 10% was only achieved for protocols in the upper half of dose levels assessed when grouped by pitch. Although all scanners undergo rigorous daily single-energy QC, iodine quantification accuracy from one scanner unexpectedly deviated from the other nine substantially. In general, inter-scanner agreement and intra-scanner repeatability varied with dose, rotation time and reconstructed keV. Conclusion: Preliminary results indicate the need for a dual-energy QC process to ensure inter-scanner agreement and intra-scanner repeatability. In particular, iodine quantification accuracy within 10% may not be achievable using lower dose techniques. Future plans include longer term dual-energy CT QC data collection. In-kind financial support was provided by GE Healthcare.« less