Human Observer Net: A Platform Tool for Human Observer Studies of Image Data.

Background Current software applications for human observer studies of images lack flexibility in study design, platform independence, multicenter use, and assessment methods and are not open source, limiting accessibility and expandability. Purpose To develop a user-friendly software platform that enables efficient human observer studies in medical imaging with flexibility of study design. Materials and Methods Software for human observer imaging studies was designed as an open-source web application to facilitate access, platform-independent usability, and multicenter studies. Different interfaces for study creation, participation, and management of results were implemented. The software was evaluated in human observer experiments between May 2019 and March 2021, in which duration of observer responses was tracked. Fourteen radiologists evaluated and graded software usability using the 100-point system usability scale. The application was tested in Chrome, Firefox, Safari, and Edge browsers. Results Software function was designed to allow visual grading analysis (VGA), multiple-alternative forced-choice (m-AFC), receiver operating characteristic (ROC), localization ROC, free-response ROC, and customized designs. The mean duration of reader responses per image or per image set was 6.2 seconds ± 4.8 (standard deviation), 5.8 seconds ± 4.7, 8.7 seconds ± 5.7, and 6.0 seconds ± 4.5 in four-AFC with 160 image quartets per reader, four-AFC with 640 image quartets per reader, localization ROC, and experimental studies, respectively. The mean system usability scale score was 83 ± 11 (out of 100). The documented code and a demonstration of the application are available online (https://github.com/genskeu/HON, https://hondemo.pythonanywhere.com/). Conclusion A user-friendly and efficient open-source application was developed for human reader experiments that enables study design versatility, as well as platform-independent and multicenter usability. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Thompson in this issue.

Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging: a phantom study.

OBJECTIVES: To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST). METHODS: Effects of image reconstruction on radiomics features were investigated using a phantom that realistically mimicked a 65-year-old patient's abdomen with hepatic metastases. The phantom was scanned at 18 doses from 0.2 to 4 mGy, with 20 repeated scans per dose. Images were reconstructed with FBP, AIDR 3D, FIRST, and AiCE. Ninety-three radiomics features were extracted from 24 regions of interest, which were evenly distributed across three tissue classes: normal liver, metastatic core, and metastatic rim. Features were analyzed in terms of their consistent characterization of tissues within the same image (intraclass correlation coefficient ≥ 0.75), discriminative power (Kruskal-Wallis test p value < 0.05), and repeatability (overall concordance correlation coefficient ≥ 0.75). RESULTS: The median fraction of consistent features across all doses was 6%, 8%, 6%, and 22% with FBP, AIDR 3D, FIRST, and AiCE, respectively. Adequate discriminative power was achieved by 48%, 82%, 84%, and 92% of features, and 52%, 20%, 17%, and 39% of features were repeatable, respectively. Only 5% of features combined consistency, discriminative power, and repeatability with FBP, AIDR 3D, and FIRST versus 13% with AiCE at doses above 1 mGy and 17% at doses ≥ 3 mGy. AiCE was the only reconstruction technique that enabled extraction of higher-order features. CONCLUSIONS: AiCE more than doubled the yield of radiomics features at doses typically used clinically. Inconsistent tissue characterization within CT images contributes significantly to the poor stability of radiomics features. KEY POINTS: • Image quality of CT images reconstructed with filtered back projection and iterative methods is inadequate for the majority of radiomics features due to inconsistent tissue characterization, low discriminative power, or low repeatability. • Deep learning reconstruction enhances image quality for radiomics and more than doubled the feature yield at doses that are typically used in clinical CT imaging. • Image reconstruction algorithms can optimize image quality for more reliable quantification of tissues in CT images.

Comparison of low-contrast detectability between uniform and anatomically realistic phantoms-influences on CT image quality assessment.

OBJECTIVES: To evaluate the effects of anatomical phantom structure on task-based image quality assessment compared with a uniform phantom background. METHODS: Two neck phantom types of identical shape were investigated: a uniform type containing 10-mm lesions with 4, 9, 18, 30, and 38 HU contrast to the surrounding area and an anatomically realistic type containing lesions of the same size and location with 10, 18, 30, and 38 HU contrast. Phantom images were acquired at two dose levels (CTDIvol of 1.4 and 5.6 mGy) and reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Detection accuracy was evaluated by seven radiologists in a 4-alternative forced choice experiment. RESULTS: Anatomical phantom structure impaired lesion detection at all lesion contrasts (p < 0.01). Detectability in the anatomical phantom at 30 HU contrast was similar to 9 HU contrast in uniform images (91.1% vs. 89.5%). Detection accuracy decreased from 83.6% at 5.6 mGy to 55.4% at 1.4 mGy in uniform FBP images (p < 0.001), whereas AIDR 3D preserved detectability at 1.4 mGy (80.7% vs. 85% at 5.6 mGy, p = 0.375) and was superior to FBP (p < 0.001). In the assessment of anatomical images, superiority of AIDR 3D was not confirmed and dose reduction moderately affected detectability (74.6% vs. 68.2%, p = 0.027 for FBP and 81.1% vs. 73%, p = 0.018 for AIDR 3D). CONCLUSIONS: A lesion contrast increase from 9 to 30 HU is necessary for similar detectability in anatomical and uniform neck phantom images. Anatomical phantom structure influences task-based assessment of iterative reconstruction and dose effects. KEY POINTS: • A lesion contrast increase from 9 to 30 HU is necessary for similar low-contrast detectability in anatomical and uniform neck phantom images. • Phantom background structure influences task-based assessment of iterative reconstruction and dose effects. • Transferability of CT assessment to clinical imaging can be expected to improve as the realism of the test environment increases.

Visualizing patterns of intervertebral disc damage with dual-energy computed tomography: assessment of diagnostic accuracy in an ex vivo spine biophantom.

BACKGROUND: Previously, dual-energy computed tomography (DECT) has been established for imaging spinal fractures as an alternative modality to magnetic resonance imaging (MRI). PURPOSE: To analyze the diagnostic accuracy of DECT in visualizing intervertebral disc (IVD) damage. MATERIAL AND METHODS: The lumbar spine of a Great Dane dog was used as an ex vivo biophantom. DECT was performed as sequential volume technique on a single-source CT scanner. IVDs were imaged before and after an injection of sodium chloride solution and after anterior discectomy in single-source sequential volume DECT technique using 80 and 135 kVp. Chondroitin/Collagen maps (cMaps) were reconstructed at 1 mm and compared with standard CT. Standardized regions of interest (ROI) were placed in the anterior anulus fibrosus, nucleus pulposus, and other sites. Three blinded readers classified all images as intact disc, nucleus lesion, or anulus lesion. Additionally, clinical examples from patients with IVD lesions were retrospectively identified from the radiological database. RESULTS: Interrater reliability was almost perfect with a Fleiss kappa of 0.833 (95% confidence interval [CI] 0.83-0.835) for DECT, compared with 0.780 (95% CI 0.778-0.782) for standard CT. For overall detection accuracy of IVD, DECT achieved 91.0% sensitivity (95% CI 83.6-95.8) and 92.0% specificity (95% CI 80.8-97.8). Standard CT showed 91.0% sensitivity (95% CI 83.6-95.8) and 78.0% specificity (95% CI 64.0-88.5). CONCLUSION: DECT reliably identified IVD damage in an ex vivo biophantom. Clinical examples of patients with different lesions illustrate the accurate depiction of IVD microstructure. These data emphasize the diagnostic potential of DECT cMaps.

Task-based assessment of neck CT protocols using patient-mimicking phantoms-effects of protocol parameters on dose and diagnostic performance.

OBJECTIVES: To assess how modifying multiple protocol parameters affects the dose and diagnostic performance of a neck CT protocol using patient-mimicking phantoms and task-based methods. METHODS: Six patient-mimicking neck phantoms containing hypodense lesions of 1 cm diameter and 30 HU contrast and one non-lesion phantom were examined with 36 CT protocols. All possible combinations of the following parameters were investigated: 100- and 120-kVp tube voltage; tube current modulation (TCM) noise levels of SD 7.5, 10, and 14; pitches of 0.637, 0.813, and 1.388; filtered back projection (FBP); and iterative reconstruction (AIDR 3D). Dose-length products (DLPs) and lesion detectability (assessed by 14 radiologists) were compared with the clinical standard protocol (120 kVp, TCM SD 7.5, 0.813 pitch, AIDR 3D). RESULTS: The DLP of the standard protocol was 25 mGy•cm; the area under the curve (AUC) was 0.839 (95%CI: 0.790-0.888). Combined effects of tube voltage reduction to 100 kVp and TCM noise level increase to SD 10 optimized protocol performance by improving dose (7.3 mGy•cm) and detectability (AUC 0.884, 95%CI: 0.844-0.924). Diagnostic performance was significantly affected by the TCM noise level at 120 kVp (AUC 0.821 at TCM SD 7.5 vs. 0.776 at TCM SD 14, p = 0.003), but not at 100-kVp tube voltage (AUC 0.839 at TCM SD 7.5 vs. 0.819 at TCM SD 14, p = 0.354), the reconstruction method at 100 kVp (AUC 0.854 for AIDR 3D vs. 0.806 for FBP, p < 0.001), but not at 120-kVp tube voltage (AUC 0.795 for AIDR 3D vs. 0.793 for FBP, p = 0.822), and the tube voltage for AIDR 3D reconstruction (p < 0.001), but not for FBP (p = 0.226). CONCLUSIONS: Combined effects of 100-kVp tube voltage, TCM noise level of SD 10, a pitch of 0.813, and AIDR 3D resulted in an optimal neck protocol in terms of dose and diagnostic performance. Protocol parameters were subject to complex interactions, which created opportunities for protocol improvement. KEY POINTS: • A task-based approach using patient-mimicking phantoms was employed to optimize a CT system for neck imaging through systematic testing of protocol parameters. • Combined effects of 100-kVp tube voltage, TCM noise level of SD 10, a pitch of 0.813, and AIDR 3D reconstruction resulted in an optimal protocol in terms of dose and diagnostic performance. • Interactions of protocol parameters affect diagnostic performance and should be considered when optimizing CT techniques.

3D printing of anatomically realistic phantoms with detection tasks to assess the diagnostic performance of CT images.

OBJECTIVES: Detectability experiments performed to assess the diagnostic performance of computed tomography (CT) images should represent the clinical situation realistically. The purpose was to develop anatomically realistic phantoms with low-contrast lesions for detectability experiments. METHODS: Low-contrast lesions were digitally inserted into a neck CT image of a patient. The original and the manipulated CT images were used to create five phantoms: four phantoms with lesions of 10, 20, 30, and 40 HU contrast and one phantom without any lesion. Radiopaque 3D printing with potassium-iodide-doped ink (600 mg/mL) was used. The phantoms were scanned with different CT settings. Lesion contrast was analyzed using HU measurement. A 2-alternative forced choice experiment was performed with seven radiologists to study the impact of lesion contrast on detection accuracy and reader confidence (1 = lowest, 5 = highest). RESULTS: The phantoms reproduced patient size, shape, and anatomy. Mean ± SD contrast values of the low-contrast lesions were 9.7 ± 1.2, 18.2 ± 2, 30.2 ± 2.7, and 37.7 ± 3.1 HU for the 10, 20, 30, and 40 HU contrast lesions, respectively. Mean ± SD detection accuracy and confidence values were not significantly different for 10 and 20 HU lesion contrast (82.1 ± 6.3% vs. 83.9 ± 9.4%, p = 0.863 and 1.7 ± 0.4 vs. 1.8 ± 0.5, p = 0.159). They increased to 95 ± 5.7% and 2.6 ± 0.7 for 30 HU lesion contrast and 99.5 ± 0.9% and 3.8 ± 0.7 for 40 HU lesion contrast (p < 0.005). CONCLUSIONS: A CT image was manipulated to produce anatomically realistic phantoms for low-contrast detectability experiments. The phantoms and our initial experiments provide a groundwork for the assessment of CT image quality in a clinical context. KEY POINTS: • Phantoms generated from manipulated CT images provide patient anatomy and can be used for detection tasks to evaluate the diagnostic performance of CT images. • Radiologists are unconfident and unreliable in detecting hypodense lesions of 20 HU contrast and less in an anatomical neck background. • Detectability experiments with anatomically realistic phantoms can assess CT image quality in a clinical context.

Scout-guided needle placement-a technical approach for dose reduction in CT-guided periradicular infiltration.

PURPOSE: To develop and evaluate a technical approach for CT-guided periradicular infiltration using quantitative needle access and guidance parameters extracted from CT scout images. METHODS: Five 3D-printed phantoms of the abdomen mimicking different patients were used to develop a technical approach for scout-guided periradicular infiltration. The needle access point, puncture depth, and needle angulation were calculated using measurements extracted from anterior-posterior and lateral CT scout images. Fifty needle placements were performed with the technique thus developed. Dose exposure and number of image acquisitions were compared with ten procedures performed using a conventional free-hand technique. Data were analyzed with the Mann-Whitney U test. RESULTS: Parameters derived solely from scout images provided adequate guidance for successful and reliable needle placement. Needle guidance was performed with the same equipment as the standard periradicular infiltration. Two scout images and 3.5 ± 2.3 (mean ± SD) single-shot images for needle positioning were acquired. Mean DLP ± SD was 3.8 ± 2.5 mGy cm. The number of single-shot acquisitions was reduced by 68% and the overall dose was reduced by 84% in comparison with the conventional free-hand technique (p < 0.0001). CONCLUSION: Scout-guided needle placement for periradicular infiltration is feasible and reduces radiation exposure significantly.

Development of a method to create uniform phantoms for task-based assessment of CT image quality.

PURPOSE: To develop a customized method to produce uniform phantoms for task-based assessment of CT image quality. METHODS: Contrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated. A phantom was produced by laser cutting PMMA slabs to the shape of a patient's neck. An opening of 10 mm diameter was cut into the left parapharyngeal space. An angioplasty balloon was inserted and filled with the fructose solutions to simulate low-contrast lesions. The phantom was scanned with six tube currents. Images were reconstructed with filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Calculated and measured contrasts were compared. The phantom was evaluated in a detectability experiment using images with 4 and 20 HU lesion contrast. RESULTS: Low-contrast lesions of 4, 9, 11, 13, 18, 20, 24, 30, 35, and 37 HU contrast were simulated. Calculated and measured contrasts correlated excellently (r = 0.998; 95% confidence interval: 0.991 to 1). The mean ± SD difference was 0.41 ± 2.32 HU (P < 0.0001). Detection accuracy and reader confidence were 62.9 ± 18.2% and 1.58 ± 0.68 for 4 HU lesion contrast and 99.6 ± 1.3% and 4.27 ± 0.92 for 20 HU lesion contrast (P < 0.0001), confirming that the method produced lesions at the threshold of detectability. CONCLUSION: A cost-effective and flexible approach was developed to create uniform phantoms with low-contrast signals. The method should facilitate access to customized phantoms for task-based image quality assessment.

Paper-based 3D printing of anthropomorphic CT phantoms: Feasibility of two construction techniques.

OBJECTIVES: To develop and evaluate methods for assembling radiopaque printed paper sheets to realistic patient phantoms for CT dose and image quality testing. METHODS: CT images of two patients were radiopaque printed with aqueous potassium iodide solution (0.6 g/ml) on paper. Two methods were developed for assembling the paper sheets to head and neck phantoms. (1) Printed sheets were fed to a paper-based 3D printer along with corresponding 3D printable STL files. (2) Paper stacks of 5-mm thickness were glued with toner, cut to the patient shape and assembled to a phantom. In a sample application study, both phantoms were examined with five different tube current settings. Images were reconstructed using filtered-back projection (FBP) and iterative reconstruction (AIDR 3D) with three strength levels. Dose length product (DLP), signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNRs) were analysed. Data were analysed using 2-way analysis of variance (ANOVA). RESULTS: Both methods achieved anthropomorphic phantoms with detailed patient anatomy. The 3D printer yielded a precise reproduction of the external patient shape, but caused visible glue artefacts. Gluing with toner avoided these artefacts and yielded more flexibility with regard to phantom size. In the sample application study, non-inferior SNR and CNR and up to 83.7% lower DLP were achieved on the phantoms with AIDR 3D compared with FBP. CONCLUSIONS: Two methods for assembling radiopaque printed paper sheets to phantoms of individual patients are presented. The sample application demonstrates potential for simulation of patient imaging and systematic CT dose and image quality assessment. KEY POINTS: • Two methods were developed to create realistic CT phantoms of individual patients from radiopaque printed paper sheets. • Analysis of five tube current and four reconstruction settings on two radiopaque 3D printed patient phantoms yielded non-inferior SNR and CNR and up to 83.7% lower dose with iterative reconstruction in comparison with filtered back projection. • Radiopaque 3D printed phantoms can simulate patients and allow systematic analysis of CT dose and image quality parameters.

A radiopaque 3D printed, anthropomorphic phantom for simulation of CT-guided procedures.

OBJECTIVES: To develop an anthropomorphic phantom closely mimicking patient anatomy and to evaluate the phantom for the simulation of computed tomography (CT)-guided procedures. METHODS: Patient CT images were printed with aqueous potassium iodide solution (1 g/mL) on paper. The printed paper sheets were stacked in alternation with 1-mm thick polyethylene foam layers, cut to the patient shape and glued together to create an anthropomorphic abdomen phantom. Ten interventional radiologists performed periradicular infiltration on the phantom and rated the phantom procedure regarding different aspects of suitability for simulating CT-guided procedures. RESULTS: Radiopaque printing in combination with polyethylene foam layers achieved a phantom with detailed patient anatomy that allowed needle placement. CT-guided periradicular infiltration on the phantom was rated highly realistic for simulation of anatomy, needle navigation and overall course of the procedure. Haptics were rated as intermediately realistic. Participants strongly agreed that the phantom was suitable for training and learning purposes. CONCLUSIONS: A radiopaque 3D printed, anthropomorphic phantom provides a realistic platform for the simulation of CT-guided procedures. Future work will focus on application for training and procedure optimisation. KEY POINTS: • Radiopaque 3D printing combined with polyethylene foam achieves patient phantoms for CT-guided procedures. • Radiopaque 3D printed, anthropomorphic phantoms allow realistic simulation of CT-guided procedures. • Realistic visual guidance is a key aspect in simulation of CT-guided procedures. • Three-dimensional printed phantoms provide a platform for training and optimisation of CT-guided procedures.

Subarachnoid blood acutely induces spreading depolarizations and early cortical infarction.

See Ghoshal and Claassen (doi:10.1093/brain/awx226) for a scientific commentary on this article. Early cortical infarcts are common in poor-grade patients after aneurysmal subarachnoid haemorrhage. There are no animal models of these lesions and mechanisms are unknown, although mass cortical spreading depolarizations are hypothesized as a requisite mechanism and clinical marker of infarct development. Here we studied acute sequelae of subarachnoid haemorrhage in the gyrencephalic brain of propofol-anaesthetized juvenile swine using subdural electrode strips (electrocorticography) and intraparenchymal neuromonitoring probes. Subarachnoid infusion of 1­2 ml of fresh blood at 200 µl/min over cortical sulci caused clusters of spreading depolarizations (count range: 12­34) in 7/17 animals in the ipsilateral but not contralateral hemisphere in 6 h of monitoring, without meaningful changes in other variables. Spreading depolarization clusters were associated with formation of sulcal clots (P < 0.01), a high likelihood of adjacent cortical infarcts (5/7 versus 2/10, P < 0.06), and upregulation of cyclooxygenase-2 in ipsilateral cortex remote from clots/infarcts. In a second cohort, infusion of 1 ml of clotted blood into a sulcus caused spreading depolarizations in 5/6 animals (count range: 4­20 in 6 h) and persistent thick clots with patchy or extensive infarction of circumscribed cortex in all animals. Infarcts were significantly larger after blood clot infusion compared to mass effect controls using fibrin clots of equal volume. Haematoxylin and eosin staining of infarcts showed well demarcated zones of oedema and hypoxic-ischaemic neuronal injury, consistent with acute infarction. The association of spreading depolarizations with early brain injury was then investigated in 23 patients [14 female; age (median, quartiles): 57 years (47, 63)] after repair of ruptured anterior communicating artery aneurysms by clip ligation (n = 14) or coiling (n = 9). Frontal electrocorticography [duration: 54 h (34, 66)] from subdural electrode strips was analysed over Days 0­3 after initial haemorrhage and magnetic resonance imaging studies were performed at ∼ 24­48 h after aneurysm treatment. Patients with frontal infarcts only and those with frontal infarcts and/or intracerebral haemorrhage were both significantly more likely to have spreading depolarizations (6/7 and 10/12, respectively) than those without frontal brain lesions (1/11, P's < 0.05). These results suggest that subarachnoid clots in sulci/fissures are sufficient to induce spreading depolarizations and acute infarction in adjacent cortex. We hypothesize that the cellular toxicity and vasoconstrictive effects of depolarizations act in synergy with direct ischaemic effects of haemorrhage as mechanisms of infarct development. Results further validate spreading depolarizations as a clinical marker of early brain injury and establish a clinically relevant model to investigate causal pathologic sequences and potential therapeutic interventions.

Radiopaque Three-dimensional Printing: A Method to Create Realistic CT Phantoms.

Purpose To develop a method to create anthropomorphic phantoms of individual patients with high precision of anatomic details and radiation attenuation properties. Materials and Methods Inkjet cartridges were filled with potassium iodide solutions (600 mg/mL) and prints were realized on plain paper (80 g/m2). Stacks of 100 prints resulted in three-dimensional phantoms of 1 cm thickness. In a first step, reproduction of patient anatomy was tested by printing computed tomographic (CT) images of a real patient abdomen scan. In a second step, gray scales, iodine deposition, and Hounsfield units were investigated by printing geometric phantoms with gray scales ranging from 0% (white) to 100% (black). On the basis of these results, a gray-scale-correction procedure was developed to achieve realistic Hounsfield units in the patient phantom. In a third step, reproduction of the real patient's Hounsfield units was verified by printing the initial patient CT scan again after application of the gray-scale-correction procedure. Data were analyzed by using Pearson correlation, linear regression, and nonlinear regression. Results The first abdomen phantom showed a detailed reproduction of the patient anatomy and demonstrated feasibility of the concept. However, individual-organ Hounsfield units deviated from the real patient CT scan. Analysis of the geometric phantoms revealed an exponential correlation between template gray scales and printer deposition. Application of a correction procedure to the template gray scales allowed for a linear correlation (r = 0.9946; 95% confidence interval: 0.9916, 0.9966). After the same correction procedure was applied to the abdomen phantom, linear correlation of phantom and patient Hounsfield units was confirmed (r = 0.9925; 95% confidence interval: 0.9635, 0.9985). Conclusion The method presented in this work can realize realistic and customizable phantoms for diagnostic and therapeutic radiology, including the reproduction of individual patients. © RSNA, 2016.

Dual-energy computed tomography of the neck-optimizing tube current settings and radiation dose using a 3D-printed patient phantom.

BACKGROUND: Dual-energy computed tomography (DECT) is increasingly used in studies and clinical practice. However, the best protocol is controversially discussed and whether it exhibits more radiation exposure compared to conventional protocols. Thus, the purpose of the study was to determine optimal tube current settings for DECT in a 3D-printed anthropomorphic phantom of the neck. METHODS: A 3D-printed iodinated ink based phantom of a contrast enhanced CT of the neck was imaged. Six dual-energy multi-detector computed tomography scans were performed with six different tube currents (80 kVp: 30-400 mAs; 135 kVp: 5-160 mAs). 120 virtual blended images (VBIs) and 66 virtual monochromatic images (VMIs) were reconstructed and 12 regions of interest (bilaterally: common carotid arteries, subcutaneous soft tissue, mandibular bone, sternocleidomastoid muscle, submandibular gland, and mid-image: vertebral body of C2 and pharyngeal space) in six consecutive slices resulting in 96 measurements per scan were performed. Hounsfield units and signal- and contrast-to-noise ratio were compared to single-energy computed tomography as standard of reference. RESULTS: VBIs overestimated the Hounsfield units (P<0.0001). Optimal dual-energy scanning parameters resulted in 120% (100 kVe: 51.2 vs. 61.7 and 65.2, for signal and contrast-to-noise ratio, respectively; 120 kVe: 60.8 vs. 72.1 vs. 128.3) of the radiation exposure with about 80% of the signal/contrast-to-noise ratio of the corresponding single-energy images. However, optimal weighting of tube currents for both voltages depended on the desired reconstruction. CONCLUSIONS: Dual-energy protocols apply an estimated 120% of the single-energy radiation exposure and result in approximately 80% of the image quality. Tube current settings should be adapted to the desired information.

Training of CT-guided Periradicular Therapy in a Realistic Simulation Environment - Evaluation and Recommendations for a Training Curriculum.

RATIONALE AND OBJECTIVES: To evaluate the training of computed tomography (CT)-guided periradicular therapy in a realistic simulation environment and to derive recommendations for a training curriculum. MATERIALS AND METHODS: A novel simulation environment including the use of a 3D printed, patient-mimicking phantom was used to train medical students to perform CT-guided periradicular therapy of the lumbar spine. Seventeen participants underwent three training sessions (day 0, day 7, and after day 28) with six procedures per session. Procedure duration and the number of fluoroscopy image acquisitions were recorded. Participants' performance was assessed by an independent investigator using a six-point checklist scale (0 = lowest, 6 = highest). In addition, participants self-evaluated their skills and the simulation training in questionnaires. RESULTS: Procedure durations and image acquisitions decreased after one training session (p < 0.001) without further improvement thereafter (p > 0.6). They also decreased within training sessions and were lowest after five procedures in all sessions. Performance scores improved after the first session to nearly perfect scores in the second session (mean 5.7; 95%CI: 5.5-6.0; p < 0.001) and decreased again in the third session (mean 4.9; 95%CI: 4.6-5.3; p = 0.008). Participants were satisfied with their training progress and felt adequately prepared to perform CT-guided periradicular therapies on patients after the training. CONCLUSION: Simulation-based training of CT-guided periradicular therapy in a realistic environment is effective and should ideally be performed with one training session consisting of five procedures shortly before treating the first patient.

Intra-scanner repeatability of quantitative imaging features in a 3D printed semi-anthropomorphic CT phantom.

OBJECTIVES: Radiomics has shown to provide novel diagnostic and predictive disease information based on quantitative image features in study settings. However, limited data yielded contradictory results and important questions regarding the validity of the methods remain to be answered. The purpose of this study was to evaluate how clinical imaging techniques affect the stability of radiomics features by using 3D printed anthropomorphic CT phantom to test for repeatability and reproducibility of quantitative parameters. METHODS: 48 PET/CT validated lymph nodes of prostate cancer patients (24 metastatic, 24 non-metastatic) were used as a template to create a customized 3D printed anthropomorphic phantom. We subsequently scanned the phantom five times with a routine abdominal CT protocol. Images were reconstructed using iterative reconstruction and two soft tissue kernels and one bone kernel. Radiomics features were extracted and assessed for repeatability and susceptibility towards image reconstruction settings using concordance correlation coefficients. RESULTS: Our analysis revealed 19 of 86 features (22 %) as highly repeatable (CCC ≥ 0.85) with low susceptibility towards image reconstruction protocols. Most features analyzed depicted critical non-repeatability with CCC's < 0.75 even under entirely consistent imaging acquisition settings. Edge enhancing kernels result in higher variances between the scans and differences in repeatability and reproducibility were detected between PSMA-positive and negative lymph nodes with overall more stable features seen in tumor positive lymph nodes. CONCLUSIONS: Both, repeatability and reproducibility play a crucial role in the validation process of radiomics features in clinical routine. This phantom study shows that most radiomics features in contrast to previous studies, including phantom and clinical, do not depict sufficient intra-scanner repeatability to serve as reliable diagnostic tools.

Characterization of office laser printers for 3-D printing of soft tissue CT phantoms.

The purpose of our study is to develop and evaluate a method for radiopaque 3-D printing (R3P) of soft tissue computed tomography (CT) phantoms with office laser printers. Five laser printers from different vendors are tested for toner CT attenuation. A liver phantom is created by printing CT images of a patient liver on office paper. One thousand eight hundred sixty paper sheets are printed with three repeated prints per page, resulting in a stack of 18.6 cm. The phantom is examined with 12 tube current settings. Images are reconstructed using filtered back projection (FBP) and iterative reconstruction [adaptive iterative dose reduction 3D (AIDR 3D)]. Seven radiologists rated image quality of all acquisitions. Toner attenuation of all investigated printers increased linearly with the print template grayscale. The liver phantom reproduced anatomic detail and attenuation values of the patient ( mean ± SD HU difference 12.68 ± 7.74 ). Image quality scores increased with dose but did not vary significantly above a threshold dose for AIDR 3D. Overall, AIDR 3D reconstructed images are rated superior to FBP reconstructions ( p < 0.001 ). In conclusion, R3P with standard office laser printers can generate soft tissue CT phantoms without hardware manipulations but with limited flexibility regarding attenuation properties of the printed toner material.

Recording, analysis, and interpretation of spreading depolarizations in neurointensive care: Review and recommendations of the COSBID research group.

Spreading depolarizations (SD) are waves of abrupt, near-complete breakdown of neuronal transmembrane ion gradients, are the largest possible pathophysiologic disruption of viable cerebral gray matter, and are a crucial mechanism of lesion development. Spreading depolarizations are increasingly recorded during multimodal neuromonitoring in neurocritical care as a causal biomarker providing a diagnostic summary measure of metabolic failure and excitotoxic injury. Focal ischemia causes spreading depolarization within minutes. Further spreading depolarizations arise for hours to days due to energy supply-demand mismatch in viable tissue. Spreading depolarizations exacerbate neuronal injury through prolonged ionic breakdown and spreading depolarization-related hypoperfusion (spreading ischemia). Local duration of the depolarization indicates local tissue energy status and risk of injury. Regional electrocorticographic monitoring affords even remote detection of injury because spreading depolarizations propagate widely from ischemic or metabolically stressed zones; characteristic patterns, including temporal clusters of spreading depolarizations and persistent depression of spontaneous cortical activity, can be recognized and quantified. Here, we describe the experimental basis for interpreting these patterns and illustrate their translation to human disease. We further provide consensus recommendations for electrocorticographic methods to record, classify, and score spreading depolarizations and associated spreading depressions. These methods offer distinct advantages over other neuromonitoring modalities and allow for future refinement through less invasive and more automated approaches.