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• Virtual calcium-only images (VCa) show good correlation with DEXA bone mineral density. • VCa might be used to estimate BMD as it is less prone to bone marrow changes. • A VCa cut-off of 126 HU can be used to identify abnormal bone mineral density. To evaluate a novel calcium-only imaging technique (VCa) with subtracted bone marrow in osteoporosis in dual-layer CT (DLCT) compared to conventional CT images (CI) and dual-energy X-ray absorptiometry (DXA). Images of a multi-energy CT phantom with calcium inserts, quantitative CT calibration phantom, and of 55 patients (mean age: 64.6 ± 11.5 years) were acquired on a DLCT to evaluate bone mineral density (BMD). CI, calcium-suppressed images, and VCa were calculated. For investigating the association of VCa and CI with DXA a subsample of 30 patients (<90 days between DXA and CT) was used. Multiple regression analysis was performed to identify further factors improving the prediction of DXA BMD. The calcium concentrations of the CT phantom inserts were significantly associated with CT numbers from VCa (R2 = 0.94) and from CI (R2 = 0.89–0.92). VCa showed significantly higher CT numbers than CI in the phantom (p ≤ 0.001) and clinical setting (p < 0.001). CT numbers from VCa were significantly associated with CI (R2 = 0.95, p < 0.001) and with DXA (R 2 = 0.31, p = 0.007), whereas no significant association between DXA and CI was found. Prediction of DXA BMD based on CT numbers derived from VCa yielded R2 = 0.76 in multiple regression analysis. ROC for the differentiation of normal from pathologic BMD in VCa yielded an AUC of 0.7, and a cut-off value of 126HU (sensitivity: 0.90; specificity: 0.47). VCa images showed better agreement with DXA and known calcium concentrations than CI, and could be used to estimate BMD. A VCa cut-off of 126 HU could be used to identify abnormal bone mineral density. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the prediction of vertebral fractures in plasma cell dyscrasias using dual-layer CT (DLCT) with quantitative assessment of conventional CT image data (CI), calcium suppressed image data (CaSupp), and calculation of virtual calcium-only (VCa) image data., Material and Methods: Patients ( n = 81) with the diagnosis of a plasma cell dyscrasia and whole-body DLCT at the time of diagnosis and follow-up were retrospectively enrolled. CI, CaSupp25, and CaSupp100 were quantitatively analyzed using regions of interest in the lumbar vertebral bodies and fractured vertebral bodies on baseline or follow-up imaging. VCa were calculated by subtraction (CaSupp100-CaSupp25), delineating bone only. Logistic regression analyses were performed to assess the possibility of imminent spine fractures., Results: In 24 patients, new vertebral fractures were observed in the follow-up imaging. The possibility of new vertebral fractures was significant for baseline assessment of CT numbers in CI, CaSupp25, and VCa ( p = 0.01, respectively), with a higher risk for new fractures in the case of lower CT numbers in CI (Odds ratio = [0.969; 0.994]) and VCa (Odds ratio = [0.978; 0.995]) and in the case of higher CT numbers in CaSupp 25 (Odds ratio 1.015 [1.006; 1.026]). Direct model comparisons implied that CT numbers in CaSupp 25 and VCa might show better fracture prediction than those in CI (R 2 = 0.18 both vs. 0.15; AICc = 91.95, 91.79 vs. 93.62), suggesting cut-off values for CI at 103 HU (sensitivity: 54.2%; specificity: 82.5; AUC: 0.69), for VCa at 129 HU (sensitivity: 41.7%; specificity: 94.7; AUC: 0.72)., Conclusions: Quantitative assessment with CaSupp and calculation of VCa is feasible to predict the vertebral fracture risk in MM patients. DLCT may prove useful in detecting imminent fractures.

Purpose: Complicated type B Aortic dissection is a severe aortic pathology that requires treatment through thoracic endovascular aortic repair (TEVAR). During TEVAR a stentgraft is deployed in the aortic lumen in order to restore blood flow. Due to the complicated pathology including an entry, a resulting dissection wall with potentially several re-entries, replicating this structure artificially has proven to be challenging thus far., Methods: We developed a 3d printed, patient-specific and perfused aortic dissection phantom with a flexible dissection flap and all major branching vessels. The model was segmented from CTA images and fabricated out of a flexible material to mimic aortic wall tissue. It was placed in a pulsatile hemodynamic flow loop. Hemodynamics were investigated through pressure and flow measurements and doppler ultrasound imaging. Surgeons performed a TEVAR intervention including stentgraft deployment under fluoroscopic guidance., Results: The flexible aortic dissection phantom was successfully incorporated in the hemodynamic flow loop, a systolic pressure of 112 mmHg and physiological flow of 4.05 L per minute was reached. Flow velocities were higher in true lumen with a up to 35.7 cm/s compared to the false lumen with a maximum of 13.3 cm/s, chaotic flow patterns were observed on main entry and reentry sights. A TEVAR procedure was successfully performed under fluoroscopy. The position of the stentgraft was confirmed using CTA imaging., Conclusions: This perfused in-vitro phantom allows for detailed investigation of the complex inner hemodynamics of aortic dissections on a patient-specific level and enables the simulation of TEVAR procedures in a real endovascular operating environment. Therefore, it could provide a dynamic platform for future surgical training and research., (© 2024. The Author(s).)

Objectives: With the introduction of clinical photon-counting detector computed tomography (PCD-CT) and its novel reconstruction techniques, a quantitative investigation of different acquisition and reconstruction settings is necessary to optimize clinical acquisition protocols for metal artifact reduction., Materials and Methods: A multienergy phantom was scanned on a clinical dual-source PCD-CT (NAEOTOM Alpha; Siemens Healthcare GmbH) with 4 different central inserts: water-equivalent plastic, aluminum, steel, and titanium. Acquisitions were performed at 120 kVp and 140 kVp (CTDI vol 10 mGy) and reconstructed as virtual monoenergetic images (VMIs; 110-150 keV), as T3D, and with the standard reconstruction "none" (70 keV VMI) using different reconstruction kernels (Br36, Br56) and with as well as without iterative metal artifact reduction (iMAR). Metal artifacts were quantified, calculating relative percentages of metal artifacts. Mean CT numbers of an adjacent water-equivalent insert and different tissue-equivalent inserts were evaluated, and eccentricity of metal rods was measured. Repeated-measures analysis of variance was performed for statistical analysis., Results: Metal artifacts were most prevalent for the steel insert (12.6% average artifacts), followed by titanium (4.2%) and aluminum (1.0%). The strongest metal artifact reduction was noted for iMAR (with iMAR: 1.4%, without iMAR: 10.5%; P < 0.001) or VMI (VMI: 110 keV 2.6% to 150 keV 3.3%, T3D: 11.0%, and none: 16.0%; P < 0.001) individually, with best results when combining iMAR and VMI at 110 keV (1.2%). Changing acquisition tube potential (120 kV: 6.6%, 140 kV: 5.2%; P = 0.33) or reconstruction kernel (Br36: 5.5%, Br56: 6.4%; P = 0.17) was less effective. Mean CT numbers and standard deviations were significantly affected by iMAR (with iMAR: -3.0 ± 21.5 HU, without iMAR: -8.5 ± 24.3 HU; P < 0.001), VMI (VMI: 110 keV -3.6 ± 21.6 HU to 150 keV -1.4 ± 21.2 HU, T3D: -11.7 ± 23.8 HU, and none: -16.9 ± 29.8 HU; P < 0.001), tube potential (120 kV: -4.7 ± 22.8 HU, 140 kV: -6.8 ± 23.0 HU; P = 0.03), and reconstruction kernel (Br36: -5.5 ± 14.2 HU, Br56: -6.8 ± 23.0 HU; P < 0.001). Both iMAR and VMI improved quantitative CT number accuracy and metal rod eccentricity for the steel rod, but iMAR was of limited effectiveness for the aluminum rod., Conclusions: For metal artifact reduction in PCD-CT, a combination of iMAR and VMI at 110 keV demonstrated the strongest artifact reduction of the evaluated options, whereas the impact of reconstruction kernel and tube potential was limited., Competing Interests: Conflicts of interest and sources of funding: The authors received institutional grants from Bayer Healthcare AG, Canon, Guerbet, and Siemens Healthcare GmbH unrelated to this specific work. In addition, André Euler and Hatem Alkadhi are part of the speaker’s bureau of Siemens Healthcare GmbH. Stephan Skornitzke has become an employee of Philips., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: This study provides a quantitative meta-analysis of pancreatic CT perfusion studies, investigating choice of study parameters, ability for quantitative discrimination of pancreatic diseases, and influence of acquisition and reconstruction parameters on reported results., Methods: Based on a PubMed search with key terms 'pancreas' or 'pancreatic,' 'dynamic' or 'perfusion,' and 'computed tomography' or 'CT,' 491 articles published between 1982 and 2020 were screened for inclusion in the study. Inclusion criteria were: reported original data, human subjects, five or more datasets, measurements of pancreas or pancreatic pathologies, and reported quantitative perfusion parameters. Study parameters and reported quantitative measurements were extracted, and heterogeneity of study parameters and trends over time are analyzed. Pooled data were tested with weighted ANOVA and ANCOVA models for differences in perfusion results between normal pancreas, pancreatitis, PDAC (pancreatic ductal adenocarcinoma), and non-PDAC (e.g., neuroendocrine tumors, insulinomas) and based on study parameters., Results: Reported acquisition parameters were heterogeneous, except for contrast agent amount and injection rate. Tube potential and slice thickness decreased, whereas tube current time product and scan coverage increased over time. Blood flow and blood volume showed significant differences between pathologies (both p < 0.001), unlike permeability (p = 0.11). Study parameters showed a significant effect on reported quantitative measurements (p < 0.05)., Conclusions: Significant differences in perfusion measurements between pathologies could be shown for pooled data despite observed heterogeneity in study parameters. Statistical analysis indicates most influential parameters for future optimization and standardization of acquisition protocols., Critical Relevance Statement: Quantitative CT perfusion enables differentiation of pancreatic pathologies despite the heterogeneity of study parameters in current clinical practice., (© 2023. The Author(s).)

For implementation, performance evaluation and timing optimization of CT perfusion first pass analysis (FPA) by correlation with maximum slope model (MSM) in pancreatic adenocarcinoma, dynamic CT perfusion acquisitions of 34 time-points were performed in 16 pancreatic adenocarcinoma patients. Regions of interest were marked in both parenchyma and carcinoma. FPA, a low radiation exposure CT perfusion technique, was implemented. Blood flow (BF) perfusion maps were calculated using FPA and MSM. Pearson's correlation between FPA and MSM was calculated at each evaluated time-point to determine optimum timing for FPA. Differences in BF between parenchyma and carcinoma were calculated. Average BF for MSM was 106.8 ± 41.5 ml/100 ml/min in parenchyma and 42.0 ± 24.8 ml/100 ml/min in carcinoma, respectively. For FPA, values ranged from 85.6 ± 37.5 ml/100 ml/min to 117.7 ± 44.5 ml/100 ml/min in parenchyma and from 27.3 ± 18.8 ml/100 ml/min to 39.5 ± 26.6 ml/100 ml/min in carcinoma, depending on acquisition timing. A significant difference (p value < 0.0001) between carcinoma and parenchyma was observed at all acquisition times based on FPA measurements. FPA shows high correlation with MSM (r > 0.90) and 94% reduction in the radiation dose compared to MSM. CT perfusion FPA, where the first scan is obtained after the arterial input function exceeds a threshold of 120 HU, followed by a second scan after 15.5-20.0 s, could be used as a potential imaging biomarker with low radiation exposure for diagnosing and evaluating pancreatic carcinoma in clinical practice, showing high correlation with MSM and the ability to differentiate between parenchyma and carcinoma., (© 2023. The Author(s).)

Introduction: By using bolus tracking with an appropriate acquisition delay dual-energy computed tomography (DECT) iodine maps might serve as a replacement of CT perfusion maps at reduced radiation exposure. This study aimed to evaluate the optimal acquisition delays of DECT for the replacement of parameter maps calculated with the Patlak model in pancreatic adenocarcinoma by corresponding iodine maps., Materials and Methods: Dual-source dynamic DECT acquisitions at 80 kV p /Sn140 kV p of 14 patients with pancreatic carcinoma were used to calculate CT perfusion maps of blood volume and permeability with the Patlak model. DECT iodine maps were generated from individual DECT acquisitions, matching acquisition times relative to prior bolus-triggered three-phase CT acquisitions for investigating different acquisition delays. Correlation between perfusion parameters and iodine concentrations was determined for acquisition delays between -6 s and 33 s., Results: Correlation between iodine concentrations and perfusion parameters ranged from -0.05 to 0.63 for blood volume and from -0.05 to 0.71 for permeability, depending on potential trigger delay. The correlation was significant for potential acquisition delays above 1.5 s for blood volume and above 9.0 s for permeability (both p < 0.05). Maximum correlation occurred at an acquisition delay of 15.0 s for blood volume (r = 0.63) and at 25.5 s for permeability (r = 0.71), with significantly lower iodine concentrations in carcinoma (15.0 s: 1.3 ± 0.5 mg/ml; 22.5 s: 1.4 ± 0.7 mg/ml) than in non-neoplastic pancreatic parenchyma (15.0 s: 2.3 ± 0.8 mg/ml; 22.5 s: 2.4 ± 0.6 mg/ml; p < 0.05)., Discussion: In the future, well-timed DECT iodine maps acquired with bolus tracking could provide an alternative to permeability and blood volume maps calculated with the Patlak model., Competing Interests: The authors declare the following conflict of interests: Stephan Skornitzke has ownership interests in investment funds containing stock of healthcare companies. Wolfram Stiller is a member of the CT Advisory Board of Philips Medical Systems. Otherwise, the authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article., (© 2023 The Authors.)

Asynchronous calibration could allow opportunistic screening based on routine CT for early osteoporosis detection. In this phantom study, a bone mineral density (BMD) calibration phantom and multi-energy CT (MECT) phantom were imaged on eight different CT scanners with multiple tube voltages (80-150 kV p ) and image reconstruction settings (e.g. soft/hard kernel). Reference values for asynchronous BMD estimation were calculated from the BMD-phantom and validated with six calcium composite inserts of the MECT-phantom with known ground truth. Relative errors/changes in estimated BMD were calculated and investigated for influence of tube voltage, CT scanner and reconstruction setting. Reference values for 282 acquisitions were determined, resulting in an average relative error between calculated BMD and ground truth of - 9.2% ± 14.0% with a strong correlation (R 2  = 0.99; p < 0.0001). Tube voltage and CT scanner had a significant effect on calculated BMD (p < 0.0001), with relative differences in BMD of 3.8% ± 28.2% when adapting reference values for tube voltage, - 5.6% ± 9.2% for CT scanner and 0.2% ± 0.2% for reconstruction setting, respectively. Differences in BMD were small when using reference values from a different CT scanner of the same model (0.0% ± 1.4%). Asynchronous phantom-based calibration is feasible for opportunistic BMD assessment based on CT images with reference values adapted for tube voltage and CT scanner model., (© 2022. The Author(s).)

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.

Objectives: To evaluate the prognostic value of fully automatic lung quantification based on spectral computed tomography (CT) and laboratory parameters for combined outcome prediction in COVID-19 pneumonia., Methods: CT images of 53 hospitalized COVID-19 patients including virtual monochromatic reconstructions at 40-140keV were analyzed using a fully automated software system. Quantitative CT (QCT) parameters including mean and percentiles of lung density, fibrosis index (FIBI-700, defined as the percentage of segmented lung voxels ≥-700 HU), quantification of ground-glass opacities and well-aerated lung areas were analyzed. QCT parameters were correlated to laboratory and patient outcome parameters (hospitalization, days on intensive care unit, invasive and non-invasive ventilation)., Results: Best correlations were found for laboratory parameters LDH (r = 0.54), CRP (r = 0.49), Procalcitonin (r = 0.37) and partial pressure of oxygen (r = 0.35) with the QCT parameter 75th percentile of lung density. LDH, Procalcitonin, 75th percentile of lung density and FIBI-700 were the strongest independent predictors of patients' outcome in terms of days of invasive ventilation. The combination of LDH and Procalcitonin with either 75th percentile of lung density or FIBI-700 achieved a r2 of 0.84 and 1.0 as well as an area under the receiver operating characteristic curve (AUC) of 0.99 and 1.0 for the prediction of the need of invasive ventilation., Conclusions: QCT parameters in combination with laboratory parameters could deliver a feasible prognostic tool for the prediction of invasive ventilation in patients with COVID-19 pneumonia., Competing Interests: Dr. Stephan Skornitzke has ownership interests in investment funds containing stock of healthcare companies. Dr. Thuy Duong Do was supported by a grant from the Medical Faculty of the University of Heidelberg. Prof. Dr. Mark O. Wielpütz receives funding from Boehringer Ingelheim and Vertex Pharma, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Purpose: Due to the difficult differentiation from non-specific postoperative soft tissue formation (PSF), early diagnosis of pancreatic carcinoma recurrence remains challenging. Thus, we investigated the diagnostic potential of dual-energy (DE) contrast-enhanced CT., Method: After potentially curative pancreatic carcinoma resection, 31 consecutive patients with PSF were examined via DE perfusion CT, acquiring 34 images (80 kV p /140 kV p ) every 1.5 s, as the initial purpose of this study was evaluating CT-Perfusion. Corresponding time points of arterial, pancreatic, and early venous phase were calculated from bolus trigger times in prior conventional CT. Iodine and 120 kV p -equivalent images were calculated. Regions of interest were placed in each soft tissue formation. Diagnosis of local recurrence was confirmed by regular follow-up or histopathology., Results: Final diagnosis was local recurrence in 17 patients and non-specific PSF in 14 patients. Iodine concentrations in early venous phase were significantly higher in recurrent carcinoma than in non-specific PSF (1.47 mg/ml vs. 0.96 mg/ml, p = 0.007). In earlier contrast phases iodine concentrations tended to be higher, but not significantly. CT numbers in recurrent carcinoma in 120 kV p -equivalent images in venous phase were significantly higher, too (74HU vs 47HU, p = 0.002). ROC-curve analysis for iodine concentrations in early venous phase suggests a cut-off value of ≥ 1.55 mg/ml for local recurrence (AUC = 0.78, specificity = 1.0, sensitivity = 0.53) and for CT numbers in 120kV p -equivalent images a cut-off value of ≥ 57HU (AUC = 0.82, specificity = 0.82, sensitivity = 0.71)., Conclusion: In difficult cases, measuring iodine concentrations or CT numbers in PSF in (early) venous phase DECT could be a valuable additional parameter for differentiating local recurrence from non-specific PSF., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Purpose:  The goal of this study was to evaluate the diagnostic accuracy of perfusion computed tomography (CT) parameters obtained by different mathematical-kinetic methods for distinguishing pancreatic adenocarcinoma from normal tissue. To determine cut-off values and to assess the interchangeability of cut-off values, which were determined by different methods., Materials and Methods:  Perfusion CT imaging of the pancreas was prospectively performed in 23 patients. 19 patients with histopathologically confirmed pancreatic adenocarcinoma were included in the study. Blood flow (BF), blood volume (BV) and permeability-surface area product (PS) were measured in pancreatic adenocarcinoma and normal tissue with the deconvolution (BF, BV, PS), maximum slope (BF), and Patlak methods (BV, PS). The interchangeability of cut-off values was examined by assessing agreement between BF, BV, and PS measured with different mathematical-kinetic methods., Results:  Bland-Altman analysis demonstrated poor agreement between perfusion parameters, measured with different mathematical-kinetic methods. According to receiver operating characteristic (ROC) analysis, PS measured with the Patlak method had the significantly lowest diagnostic accuracy (area under ROC curve = 0.748). All other parameters were of high diagnostic accuracy (area under ROC curve = 0.940-0.997), although differences in diagnostic accuracy were not statistically different. Cut-off values for BF of ≤ 91.83 ml/100 ml/min and for BV of ≤ 5.36 ml/100 ml, both measured with the deconvolution method, appear to be the most appropriate cut-off values to distinguish pancreatic adenocarcinoma from normal tissue., Conclusion:  Perfusion parameters obtained by different methods are not interchangeable. Therefore, cut-off values, which were determined using different methods, are not interchangeable either. Perfusion parameters can help to distinguish pancreatic adenocarcinoma from normal tissue with high diagnostic accuracy, except for PS measured with the Patlak method., Key Points:   · Perfusion CT parameters showed high diagnostic accuracy in differentiating between pancreatic adenocarcinoma and normal tissue.. · Only PS measured with the Patlak method showed a significantly lower diagnostic accuracy.. · Perfusion parameters measured with different mathematical-kinetic methods are not interchangeable.. · A specific cut-off value must be determined for each method and each perfusion parameter.., Citation Format: · Koell M, Klauss M, Skornitzke S et al. Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma with the Deconvolution, Maximum Slope, and Patlak Methods - Evaluation of Diagnostic Accuracy and Interchangeability of Cut-Off Values. Fortschr Röntgenstr 2021; 193: 1062 - 1073., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Objectives: To investigate the value of spectral-detector computed tomography (SDCT) parameters for the quantitative differentiation between atelectasis and pneumonia on contrast-enhanced chest CT., Material and Methods: Sixty-three patients, 22 clinically diagnosed with pneumonia and 41 with atelectasis, underwent contrast-enhanced SDCT scans during the venous phase. CT numbers (Hounsfield Units [HU]) were measured on conventional reconstructions (CON 120kVp ) and the iodine concentration (C iodine , [mg/ml]), and effective atomic number (Z eff ) on spectral reconstructions, using region-of-interest (ROI) analysis. Receiver operating characteristics (ROC) and contrast-to-noise ratios (CNRs) were calculated to assess each reconstruction's potential to differentiate between atelectasis and pneumonia., Results: On contrast-enhanced SDCT, the difference between atelectasis and pneumonia was significant on CON 120kVp , C iodine , and Z eff images (p < 0.001). On CON 120kVp images, a threshold of 81 HU achieved a sensitivity of 93 % and a specificity of 95 % for identifying pneumonia, while C iodine and Z eff images reached the same sensitivity but lower specificities of 85 % and 83 %. CON 120kVp images showed significantly higher CNRs between normal lung and atelectasis or pneumonia with 30.63 and 27.69 compared to C iodine images with 3.54 and 1.27 and Z eff images with 4.22 and 7.63 (p < 0.001). None of the parameters could differentiate atelectasis and pneumonia without contrast media., Conclusions: Contrast-enhanced SDCT can differentiate atelectasis and pneumonia based on the spectral parameters C iodine , and Z eff. However, they had no added value compared to CT number measurement on CON 120kVp images. Furthermore, contrast media is still needed for a differentiation based on quantitative SDCT parameters., Competing Interests: The authors declare the following conflict of interests: Stephan Skornitzke has ownership interests in investment funds containing stock of healthcare companies., (© 2021 The Authors.)

Purpose: To evaluate dual-energy CT (DE) and dedicated metal artifact reduction algorithms (iMAR) during CT-guided biopsy in comparison to single-energy CT (SE)., Methods: A trocar was placed in the liver of six pigs. CT acquisitions were performed with SE and dose equivalent DE at four dose levels(1.7-13.5mGy). Iterative reconstructions were performed with and without iMAR. ROIs were placed in four positions e.g. at the trocar tip(TROCAR) and liver parenchyma adjacent to the trocar tip(LIVER-1) by two independent observers for quantitative analysis using CT numbers, noise, SNR and CNR. Qualitative image analysis was performed regarding overall image quality and artifacts generated by iMAR., Results: There were no significant differences in CT numbers between DE and SE at TROCAR and LIVER-1 irrespective of iMAR. iMAR significantly reduced metal artifacts at LIVER-1 for all exposure settings for DE and SE(p = 0.02-0.04), but not at TROCAR. SNR, CNR and noise were comparable for DE and SE. SNR was best for high dose levels of 6.7/13.5mGy. Mean difference in the Blant-Altman analysis was -8.43 to 0.36. Cohen's kappa for qualitative interreader-agreement was 0.901., Conclusions: iMAR independently reduced metal artifacts more effectively and efficiently than CT acquisition in DE at any dose setting and its application is feasible during CT-guided liver biopsy., Competing Interests: The authors have declared that no competing interests exist.

Background/objectives: The aim of this study was to compare intravoxel incoherent motion (IVIM) diffusion weighted (DW) MRI and CT perfusion to assess tumor perfusion of pancreatic ductal adenocarcinoma (PDAC)., Methods: In this prospective study, DW-MRI and CT perfusion were conducted in nineteen patients with PDAC on the day before surgery. IVIM analysis of DW-MRI was performed and the parameters perfusion fraction f, pseudodiffusion coefficient D*, and diffusion coefficient D were extracted for tumors, upstream, and downstream parenchyma. With a deconvolution-based analysis, the CT perfusion parameters blood flow (BF) and blood volume (BV) were estimated for tumors, upstream, and downstream parenchyma. In ten patients, intratumoral microvessel density (MVD tumor ) and microvessel area (MVA tumor ) were analyzed microscopically in resection specimens. Correlation coefficients between IVIM parameters, CT perfusion parameters, and histological microvessel parameters in tumors were calculated. Receiver operating characteristic (ROC) analysis was performed for differentiation of tumors and upstream parenchyma., Results: f tumor significantly positively correlated with BF tumor (r = 0.668, p = 0.002) and BV tumor (r = 0.672, p = 0.002). There were significant positive correlations between f tumor and MVD tumor / MVA tumor (r ≥ 0.770, p ≤ 0.009) as well as between BF tumor and MVD tumor / MVA tumor (r ≥ 0.697, p ≤ 0.025). Correlation coefficients between f tumor and MVD tumor / MVA tumor were not significantly different from correlation coefficients between BF tumor and MVD tumor / MVA tumor (p ≥ 0.400). Moreover, f, BF, BV, and permeability values (PEM) showed excellent performance in distinguishing tumors from upstream parenchyma (area under the ROC curve ≥0.874)., Conclusions: The study shows that IVIM derived f tumor and CT perfusion derived BF tumor similarly reflect vascularity of PDAC and seem to be comparably applicable for the evaluation of tumor perfusion for tumor characterization and as potential quantitative imaging biomarker., Trial Registration: DRKS, DRKS00022227, Registered 26 June 2020, retrospectively registered. https://www.drks.de/drks&#95;web/navigate.do?navigationId=trial . HTML&TRIAL&#95;ID=DRKS00022227.

Purpose: Investigation of potential improvements in dynamic CT perfusion measurements by exploitation of improved visualization of contrast agent in virtual monoenergetic reconstructions of images acquired with dual-energy computed tomography (DECT)., Method: For 17 patients with pancreatic carcinoma, dynamic dual-source DECT acquisitions were performed at 80kV p /Sn140kV p every 1.5 s over 51 s. Virtual monoenergetic images (VMI) were reconstructed for photon energies between 40 keV and 150 keV (5 keV steps). Using the maximum-slope model, perfusion maps of blood flow were calculated from VMIs and 80kV p images and compared quantitatively with regard to blood flow measured in regions of interest in healthy tissue and carcinoma, standard deviation (SD), and absolute-difference-to-standard-deviation ratio (ADSDR) of measurements., Results: On average, blood flow calculated from VMIs increased with increasing energy levels from 114.3 ± 37.2 mL/100 mL/min (healthy tissue) and 45.6 ± 25.3 mL/100 mL/min (carcinoma) for 40 keV to 128.6 ± 58.9 mL/100 mL/min (healthy tissue) and 75.5 ± 49.8 mL/100 mL/min (carcinoma) for 150 keV, compared to 114.2 ± 37.4 mL/100 mL/min (healthy tissue) and 46.5 ± 26.6 mL/100 mL/min (carcinoma) for polyenergetic 80kV p . Differences in blood flow between tissue types were significant for all energies. Differences between perfusion maps calculated from VMIs and 80kV p images were not significant below 110 keV. SD and ADSDR were significantly better for perfusion maps calculated from VMIs at energies between 40 keV and 55 keV than for those calculated from 80kV p images. Compared to effective dose of dynamic 80kV p acquisitions (4.6 ± 2.2mSv), dose of dynamic DECT/VMI acquisitions (8.0 ± 3.7mSv) was higher., Conclusions: Perfusion maps of blood flow based on low-energy VMIs between 40 keV and 55 keV offer improved robustness and quality of quantitative measurements over those calculated from 80kV p image data (reference standard), albeit at increased patient radiation exposure., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objectives: To quantitatively and qualitatively evaluate image quality in dual-layer CT (DLCT) compared to single-layer CT (SLCT) in the thorax, abdomen, and pelvis in a reduced-dose setting., Methods: Intraindividual, retrospective comparisons were performed in 25 patients who received at least one acquisition of all three acquisition protocols SLCT low (100 kVp), DLCT high (120 kVp), and DLCT low (120 kVp), all covering the venous-phase thorax, abdomen, and pelvis with matched CTDI vol between SLCT low and DLCT low . Reconstruction parameters were identical between all scans. Image quality was assessed quantitatively at 10 measurement locations in the thorax, abdomen, and pelvis by two independent observers, and subjectively with an intraindividual forced choice test between the three acquisitions. Dose-length product (DLP) and CTDI vol were extracted for dose comparison., Results: Despite matched CTDI vol in acquisition protocols, CTDI vol and DLP were lower for SLCT low compared to DLCT low and DLCT high (DLP 408.58, 444.68, 647.08 mGy·cm, respectively; p < 0.0004), as automated tube current modulation for DLCT low reached the lower limit in the thorax (mean 66.1 mAs vs limit 65 mAs). Noise and CNR were comparable between SLCT low and DLCT low (p values, 0.29-0.51 and 0.05-0.20), but CT numbers were significantly higher for organs and vessels in the upper abdomen for SLCT low compared to DLCT low . DLCT high had significantly better image quality (Noise and CNR). Subjective image quality was superior for DLCT high , but no difference was found between SLCT low and DLCT low ., Conclusions: DLCT low showed comparable image quality to SLCT low , with the additional possibility of spectral post-processing. Further dose reduction seems possible by decreasing the lower limit of the tube current for the thorax., Key Points: • Clinical use of reduced-dose DLCT is feasible despite the required higher tube potential. • DLCT with reduced dose shows comparable objective and subjective image quality to reduced-dose SLCT. • Further dose reduction in the thorax might be possible by adjusting mAs thresholds.

Objectives: To systematically evaluate the influence of acquisition settings in conjunction with raw-data based iterative image reconstruction (IR) on lung densitometry based on multi-row detector computed tomography (CT) in an anthropomorphic chest phantom., Materials and Methods: Ten porcine heart-lung explants were mounted in an ex vivo chest phantom shell, six with highly and four with low attenuating chest wall. CT (Somatom Definition Flash, Siemens Healthineers) was performed at 120kVp and 80kVp, each combined with current-time products of 120, 60, 30, and 12mAs, and was reconstructed with filtered back projection (FBP) and IR (Safire, Siemens Healthineers). Mean lung density (LD), air density (AD) and noise were measured by semi-automated region-of interest (ROI) analysis, with 120kVp/120 mAs serving as the standard of reference., Results: Using IR, noise in lung parenchyma was reduced by ~ 31% at high attenuating chest wall and by ~ 22% at low attenuating chest wall compared to FBP, respectively (p<0.05). IR induced changes in the order of ±1 HU to mean absolute LD and AD compared to corresponding FBP reconstructions which were statistically significant (p<0.05)., Conclusions: Densitometry is influenced by acquisition parameters and reconstruction algorithms to a degree that may be clinically negligible. However, in longitudinal studies and clinical research identical protocols and potentially other measures for calibration may be required., Competing Interests: The authors have declared that no competing interest exist.

Objectives: Using dual-energy computed tomography (DECT) for quantifying iodine content after injection of contrast agent could provide a quantitative basis for dynamic computed tomography (CT) perfusion measurements by means of established mathematical models of contrast agent kinetics, thus improving results by combining the strength of both techniques, which was investigated in this study., Materials and Methods: A dynamic DECT acquisition over 51 seconds performed at 80/Sn140 kVp in 17 patients with pancreatic carcinoma was used to calculate iodine-enhancement images for each time point by means of 3-material decomposition. After motion correction, perfusion maps of blood flow were calculated using the maximum-slope model from both 80 kVp image data and iodine-enhancement images. Blood flow was measured in regions of interest placed in healthy pancreatic tissue and carcinoma for both of the derived perfusion maps. To assess image quality of input data, an adjusted contrast-to-noise ratio was calculated for 80 kVp images and iodine-enhancement images. Susceptibility of perfusion results to residual patient breathing motion during acquisition was investigated by measuring blood flow in fatty tissue surrounding the pancreas, where blood flow should be negligible compared with the pancreas., Results: For both 80 kVp and iodine-enhancement images, blood flow was significantly higher in healthy tissue (114.2 ± 37.4 mL/100 mL/min or 115.1 ± 36.2 mL/100 mL/min, respectively) than in carcinoma (46.5 ± 26.6 mL/100 mL/min or 49.7 ± 24.7 mL/100 mL/min, respectively). Differences in blood flow between 80 kVp image data and iodine-enhancement images were statistically significant in healthy tissue, but not in carcinoma. For 80 kVp images, adjusted contrast-to-noise ratio was significantly higher (1.3 ± 1.1) than for iodine-enhancement images (1.1 ± 0.9). When evaluating fatty tissue surrounding the pancreas for estimating influence of patient motion, measured blood flow was significantly lower for iodine-enhancement images (30.7 ± 12.0 mL/100 mL/min) than for 80 kVp images (39.0 ± 19.1 mL/100 mL/min). Average patient radiation exposure was 8.01 mSv for dynamic DECT acquisition, compared with 4.60 mSv for dynamic 80 kVp acquisition., Discussion: Iodine enhancement images can be used to calculate CT perfusion maps of blood flow, and compared with 80 kVp images, results showed only a small difference of 1 mL/100 mL/min in blood flow in healthy tissue, whereas patient radiation exposure was increased for dynamic DECT. Perfusion maps calculated based on iodine-enhancement images showed lower blood flow in fatty tissues surrounding the pancreas, indicating reduced susceptibility to residual patient breathing motion during the acquisition.

Objectives: The aim of this study was to establish an objective segmentation-based evaluation of metal artifact reduction algorithms in the context of percutaneous microwave ablation in a porcine model., Materials and Methods: Five computed tomography acquisitions from a previous animal study on computed tomography-guided percutaneous applicator positioning for microwave antenna were reconstructed with 6 different algorithms (30 image series total): standard filtered backprojection (B30f) and iterative reconstruction (ADMIRE-I30-1, ADMIRE-I30-3), all with and without metal artifact reduction. For artifact quantification, 3-dimensional segmentation of liver parenchyma without visible artifacts (VLiverReference) and liver volume surrounding the antenna (VLiverVOI) was performed, determining thresholds for artifact segmentation and calculating volume of voxels influenced by artifacts. Objective image analysis was based on relative volume of artifacts, and subjective image quality (ie, metal artifact extent) was evaluated by 2 independent observers. Correlation between objective and subjective evaluation was calculated., Results: Both objective and subjective evaluations showed a significant reduction in metal artifacts when using dedicated metal artifact reduction algorithms (both P < 0.05). No significant reduction in metal artifacts was found when using iterative reconstruction (both P > 0.05). A good correlation between subjective and objective image quality was found (Spearman rank correlation coefficient rs = 0.65; P < 0.05). Interreader agreement was substantial (κ = 0.67)., Conclusions: Segmentation-based objective evaluation of metal artifacts shows good agreement with conventional subjective evaluations and offers a promising quantitative and precise approach with limited time expenditure.

Objectives: To assess the influence of image noise on computed tomography (CT) perfusion studies, CT perfusion software algorithms were evaluated for susceptibility to image noise and results applied to clinical perfusion studies., Methods: Digital perfusion phantoms were generated using a published deconvolution model to create time-attenuation curves (TACs) for 16 different combinations of blood flow (BF; 30/60/90/120 ml/100 ml/min) and flow extraction product (FEP; 10/20/30/40 ml/100 ml/min) corresponding to values encountered in clinical studies. TACs were distorted with Gaussian noise at 50 different strengths to approximate image noise, performing 200 repetitions for each noise level. A total of 160,000 TACs were evaluated by measuring BF and FEP with CT perfusion software, comparing results for the maximum slope and Patlak models with those obtained with a deconvolution model. To translate results to clinical practice, data of 23 patients from a CT perfusion study were assessed for image noise, and the accuracy of reported CT perfusion measurements was estimated., Results: Perfusion measurements depend on image noise as means and standard deviations of BF and FEP over repetitions increase with increasing image noise, especially for low BF and FEP values. BF measurements derived by deconvolution show larger standard deviations than those performed with the maximum slope model. Image noise in the evaluated CT perfusion study was 26.46 ± 3.52 HU, indicating possible overestimation of BF by up to 85% in a clinical setting., Conclusions: Measurements of perfusion parameters depend heavily upon the magnitude of image noise, which has to be taken into account during selection of acquisition parameters and interpretation of results, e.g., as a quantitative imaging biomarker., Key Points: • CT perfusion results depend heavily upon the magnitude of image noise. • Different CT perfusion models react differently to the presence of image noise. • Blood flow may be overestimated by 85% in clinical CT perfusion studies.

Background: In computed tomography (CT) quality assurance, alignment of image quality phantoms is crucial for quantitative and reproducible evaluation and may be improved by alignment correction. Our goal was to develop an alignment correction algorithm to facilitate geological sampling of sediment cores taken from a cold-water coral mount., Methods: An alignment correction algorithm was developed and tested with a CT acquisition at 120 kVp and 150 mAs of an image quality phantom. Random translation (maximum 15 mm) and rotation (maximum 2.86°) were applied and ground-truth was compared to parameters determined by alignment correction. Furthermore, mean densities were evaluated in four regions of interest (ROIs) placed in the phantom low-contrast section, comparing values before and after correction to ground truth. This process was repeated 1000 times. After validation, alignment correction was applied to CT acquisitions (140 kVp, 570 mAs) of sediment core sections up to 1 m in length, and sagittal reconstructions were calculated for sampling planning., Results: In the phantom, average absolute differences between applied and detected parameters after alignment correction were 0.01 ± 0.06 mm (mean ± standard deviation) along the x-axis, 0.11 ± 0.08 mm along the y-axis, 0.15 ± 0.07° around the x-axis, and 0.02 ± 0.02° around the y-axis, respectively. For ROI analysis, differences in densities were 63.12 ± 30.57, 31.38 ± 32.10, 18.27 ± 35.57, and 9.59 ± 26.37 HU before alignment correction and 1.22 ± 1.40, 0.76 ± 0.9, 0.45 ± 0.86, and 0.36 ± 0.48 HU after alignment correction, respectively. For sediment core segments, average absolute detected parameters were 3.93 ± 2.89 mm, 7.21 ± 2.37 mm, 0.37 ± 0.33°, and 0.21 ± 0.22°, respectively., Conclusions: The alignment correction algorithm was successfully evaluated in the phantom and allowed a correct alignment of sediment core segments, thus aiding in sampling planning. Application to other tasks, like image quality analysis, seems possible.

Objective: Quantitative evaluation of different bolus tracking trigger delays for acquisition of dual energy (DE) CT iodine maps as an alternative to CT perfusion., Methods: Prior to this retrospective analysis of prospectively acquired data, DECT perfusion sequences were dynamically acquired in 22 patients with pancreatic carcinoma using dual source CT at 80/140 kV p with tin filtration. After deformable motion-correction, perfusion maps of blood flow (BF) were calculated from 80 kV p image series of DECT, and iodine maps were calculated for each of the 34 DECT acquisitions per patient. BF and iodine concentrations were measured in healthy pancreatic tissue and carcinoma. To evaluate potential DECT acquisition triggered by bolus tracking, measured iodine concentrations from the 34 DECT acquisitions per patient corresponding to different trigger delays were assessed for correlation to BF and intergroup differences between tissue types depending on acquisition time., Results: Average BF measured in healthy pancreatic tissue and carcinoma was 87.6 ± 28.4 and 38.6 ± 22.2 ml/100 ml min -1 , respectively. Correlation between iodine concentrations and BF was statistically significant for bolus tracking with trigger delay greater than 0 s (r max = 0.89; p < 0.05). Differences in iodine concentrations between healthy pancreatic tissue and carcinoma were statistically significant for DECT acquisitions corresponding to trigger delays of 15-21 s (p < 0.05)., Conclusion: An acquisition window between 15 and 21 s after exceeding bolus tracking threshold shows promising results for acquisition of DECT iodine maps as an alternative to CT perfusion measurements of BF. Advances in knowledge: After clinical validation, DECT iodine maps of pancreas acquired using bolus tracking with appropriate trigger delay as determined in this study could offer an alternative quantitative imaging biomarker providing functional information for tumor assessment at reduced patient radiation exposure compared to CT perfusion measurements of BF.

Orthopedic hardware impairs image quality in cross-sectional imaging. With an increasing number of orthopedic implants in an aging population, the need to mitigate metal artifacts in computed tomography and magnetic resonance imaging is becoming increasingly relevant. This review provides an overview of the major artifacts in CT and MRI and state-of-the-art solutions to improve image quality. All steps of image acquisition from device selection, scan preparations and parameters to image post-processing influence the magnitude of metal artifacts. Technological advances like dual-energy CT with the possibility of virtual monochromatic imaging (VMI) and new materials offer opportunities to further reduce artifacts in CT and MRI. Dedicated metal artifact reduction sequences contain algorithms to reduce artifacts and improve imaging of surrounding tissue and are essential tools in orthopedic imaging to detect postoperative complications in early stages., Key Points: · Tissues around orthopaedic hardware can still be well visualised despite metal artifacts.. · Artefact reduction in CT: acquisition parameters, iterative reconstruction, Dual-energy CT and VMI.. · Artefact reduction in MRI: choice of device, sequences, acquisition parameters and MARS., Citation Format: · Do TD, Sutter R, Skornitzke S et al. CT and MRI Techniques for Imaging Around Orthopedic Hardware. Fortschr Röntgenstr 2018; 190: 31 - 41., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (© Georg Thieme Verlag KG Stuttgart · New York.)

Purpose: To evaluate the diagnostic performance of dual energy (DE) perfusion-CT for the differentiation between postoperative soft-tissue formation and tumor recurrence in patients after potentially curative pancreatic cancer resection., Material and Methods: 24 patients with postoperative soft-tissue formation in the conventional regular follow-up CT acquisition after pancreatic cancer resection with curative intent were included prospectively. They were examined with a 64-row dual-source CT using a dynamic sequence of 34 DE acquisitions every 1.5 s (80 ml of iodinated contrast material, 370 mg/ml, flow rate 5 ml/s). Weighted average (linearly blended M0.5) 120kVp-equivalent dual-energy perfusion image data sets were evaluated with a body-perfusion CT tool (see above) for estimating blood flow, permeability, and blood volume. Diagnosis was confirmed by histological study (n = 4) and by regular follow-up., Results: Final diagnosis was local recurrence of pancreatic cancer in 15 patients and unspecific postoperative tissue formation in 9 patients. The blood-flow values for recurrence tissue trended to be lower compared to postoperative tissue formation with 16.6 ml/100 ml/min and 24.7 ml/100 ml/min, respectively for weighted average 120kVp-equivalent image data, which was not significant (n.s.) (p = 0.06, significance level 0.05). Permeability- and blood-volume values were only slightly lower in recurrence tissue (n.s.)., Conclusion: DE perfusion-CT is feasible in patients after pancreatic cancer resection and a promising functional imaging technique. As only a trend for lower perfusion values in local recurrence compared to unspecific postoperative alterations was found, the perfusion differences are not yet sufficient to differentiate between malignancy and unspecific postoperative alterations for this new technique. Further studies and technical improvements are needed to generate reliable data for this clinically highly relevant differentiation., Key Points: • DE Perfusion CT is feasible in patients after pancreatic cancer resection.• While reliable differentiation of unspecific postoperative tissue formation from recurrent malignancy cannot be achieved yet, it is within reach.• DE Perfusion CT has the potential to overcome todays limitations of pure morphological diagnosis of recurrent pancreatic cancer. Citation Format: • Fritz F, Skornitzke S, Hackert T et al. Dual-Energy Perfusion-CT in Recurrent Pancreatic Cancer - Preliminary RESULTS. Fortschr Röntgenstr 2016; 188: 559 - 565., (© Georg Thieme Verlag KG Stuttgart · New York.)

Purpose: Based on the guidelines from "Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography" of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated., Methods: The extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers., Results: Spatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment., Conclusions: The presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods., (Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Purpose: To evaluate dual-energy CT (DECT) imaging of hypodense liver lesions in patients with hepatic steatosis, having a high incidence in the general population and among cancer patients receiving chemotherapy., Methods: One hundred and five patients with hepatic steatosis (liver parenchyma <40 HU) underwent contrast-enhanced DECT with reconstruction of pure iodine (PI), optimum contrast (OC), 80 kVp, and 120 kVp-equivalent data sets. Image noise (IN), lesion to liver signal to noise (SNR) and contrast to noise (CNR) ratios were quantitatively analysed; image quality was rated on a 5-point scale (1, excellent; 2, good; 3, fair; 4, poor; 5, non-diagnostic) by two independent reviewers., Results: In 21 patients with hypodense liver lesions, IN was lowest in PI followed by 120 kVp-equivalent and OC, and highest in 80 kVp. SNR was highest in PI (1.30), followed by 120 kVp-equivalent (0.72) and 80 kVp (0.63), and lowest in OC (0.55). CNR was highest in 120 kVp-equivalent (4.95), followed by OC (4.55) and 80 kVp (4.14), and lowest in PI (3.63). The 120 kVp-equivalent series exhibited best overall qualitative image score (1.88), followed by OC (1.98), 80 kVp (3.00) and PI (3.67)., Conclusion: In our study, the 120 kVp-equivalent series was best suited for visualization of hypodense lesions within steatotic liver parenchyma, while using DECT currently seems to offer no additional diagnostic advantage., Key Points: • Hepatic steatosis has high incidence in the general population and following chemotherapy. • Hypodense liver lesions can be obscured by steatotic liver parenchyma in CT. • Low kV p -CT shows no advantage in detecting hypodense lesions in steatotic livers. • Additional DECT image information does not improve visualization of hypodense lesions in steatosis. • 120 kV p -equivalent imaging yields best quantitative and qualitative image analysis results.

Mitral valve (MV) diseases are among the most common types of heart diseases, while heart diseases are the most common cause of death worldwide. MV repair surgery is connected to higher survival rates and fewer complications than the total replacement of the MV, but MV repair requires extensive patient-specific therapy planning. The simulation of MV repair with a patient-specific model could help to optimize surgery results and make MV repair available to more patients. However, current patient-specific simulations are difficult to transfer to clinical application because of time-constraints or prohibitive requirements on the resolution of the image data. As one possible solution to the problem of patient-specific MV modeling, we present a mass-spring MV model based on 3D transesophageal echocardiographic (TEE) images already routinely acquired for MV repair therapy planning. Our novel approach to the rest-length estimation of springs allows us to model the global support of the MV leaflets through the chordae tendinae without the need for high-resolution image data. The model is used to simulate MV annuloplasty for five patients undergoing MV repair, and the simulated results are compared to post-surgical TEE images. The comparison shows that our model is able to provide a qualitative estimate of annuloplasty surgery. In addition, the data suggests that the model might also be applied to simulating the implantation of artificial chordae., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Objectives: Study objectives were the quantitative evaluation of whether conventional abdominal computed tomography (CT) perfusion measurements mathematically correlate with quantitative single-acquisition dual-energy CT (DECT) iodine concentration maps, the determination of the optimum time of acquisition for achieving maximum correlation, and the estimation of the potential for radiation exposure reduction when replacing conventional CT perfusion by single-acquisition DECT iodine concentration maps., Materials and Methods: Dual-energy CT perfusion sequences were dynamically acquired over 51 seconds (34 acquisitions every 1.5 seconds) in 24 patients with histologically verified pancreatic carcinoma using dual-source DECT at tube potentials of 80 kVp and 140 kVp. Using software developed in-house, perfusion maps were calculated from 80-kVp image series using the maximum slope model after deformable motion correction. In addition, quantitative iodine maps were calculated for each of the 34 DECT acquisitions per patient. Within a manual segmentation of the pancreas, voxel-by-voxel correlation between the perfusion map and each of the iodine maps was calculated for each patient to determine the optimum time of acquisition topt defined as the acquisition time of the iodine map with the highest correlation coefficient. Subsequently, regions of interest were placed inside the tumor and inside healthy pancreatic tissue, and correlation between mean perfusion values and mean iodine concentrations within these regions of interest at topt was calculated for the patient sample., Results: The mean (SD) topt was 31.7 (5.4) seconds after the start of contrast agent injection. The mean (SD) perfusion values for healthy pancreatic and tumor tissues were 67.8 (26.7) mL per 100 mL/min and 43.7 (32.2) mL per 100 mL/min, respectively. At topt, the mean (SD) iodine concentrations were 2.07 (0.71) mg/mL in healthy pancreatic and 1.69 (0.98) mg/mL in tumor tissue, respectively. Overall, the correlation between perfusion values and iodine concentrations was high (0.77), with correlation of 0.89 in tumor and of 0.56 in healthy pancreatic tissue at topt. Comparing radiation exposure associated with a single DECT acquisition at topt (0.18 mSv) to that of an 80 kVp CT perfusion sequence (2.96 mSv) indicates that an average reduction of Deff by 94% could be achieved by replacing conventional CT perfusion with a single-acquisition DECT iodine concentration map., Conclusions: Quantitative iodine concentration maps obtained with DECT correlate well with conventional abdominal CT perfusion measurements, suggesting that quantitative iodine maps calculated from a single DECT acquisition at an organ-specific and patient-specific optimum time of acquisition might be able to replace conventional abdominal CT perfusion measurements if the time of acquisition is carefully calibrated. This could lead to large reductions of radiation exposure to the patients while offering quantitative perfusion data for diagnosis.