@article{LaquaWoznickiBleyetal.2023,
  author    = {Laqua, Fabian Christopher and Woznicki, Piotr and Bley, Thorsten A. and Sch{\"o}neck, Mirjam and Rinneburger, Miriam and Weisthoff, Mathilda and Schmidt, Matthias and Persigehl, Thorsten and Iuga, Andra-Iza and Baeßler, Bettina},
  title     = {Transfer-learning deep radiomics and hand-crafted radiomics for classifying lymph nodes from contrast-enhanced computed tomography in lung cancer},
  series = {Cancers},
  volume    = {15},
  journal   = {Cancers},
  number    = {10},
  issn      = {2072-6694},
  doi       = {10.3390/cancers15102850},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-319231},
  year      = {2023},
  abstract  = {Objectives: Positron emission tomography (PET) is currently considered the non-invasive reference standard for lymph node (N-)staging in lung cancer. However, not all patients can undergo this diagnostic procedure due to high costs, limited availability, and additional radiation exposure. The purpose of this study was to predict the PET result from traditional contrast-enhanced computed tomography (CT) and to test different feature extraction strategies. Methods: In this study, 100 lung cancer patients underwent a contrast-enhanced \(^{18}\)F-fluorodeoxyglucose (FDG) PET/CT scan between August 2012 and December 2019. We trained machine learning models to predict FDG uptake in the subsequent PET scan. Model inputs were composed of (i) traditional "hand-crafted" radiomics features from the segmented lymph nodes, (ii) deep features derived from a pretrained EfficientNet-CNN, and (iii) a hybrid approach combining (i) and (ii). Results: In total, 2734 lymph nodes [555 (20.3\%) PET-positive] from 100 patients [49\% female; mean age 65, SD: 14] with lung cancer (60\% adenocarcinoma, 21\% plate epithelial carcinoma, 8\% small-cell lung cancer) were included in this study. The area under the receiver operating characteristic curve (AUC) ranged from 0.79 to 0.87, and the scaled Brier score (SBS) ranged from 16 to 36\%. The random forest model (iii) yielded the best results [AUC 0.871 (0.865-0.878), SBS 35.8 (34.2-37.2)] and had significantly higher model performance than both approaches alone (AUC: p < 0.001, z = 8.8 and z = 22.4; SBS: p < 0.001, z = 11.4 and z = 26.6, against (i) and (ii), respectively). Conclusion: Both traditional radiomics features and transfer-learning deep radiomics features provide relevant and complementary information for non-invasive N-staging in lung cancer.},
  language  = {en}
}
@article{GuggenbergerVogtSongetal.2023,
  author    = {Guggenberger, Konstanze V. and Vogt, Marius L. and Song, Jae W. and Weng, Andreas M. and Fr{\"o}hlich, Matthias and Schmalzing, Marc and Venhoff, Nils and Hillenkamp, Jost and Pham, Mirko and Meckel, Stephan and Bley, Thorsten A.},
  title     = {Intraorbital findings in giant cell arteritis on black blood MRI},
  series = {European Radiology},
  volume    = {33},
  journal   = {European Radiology},
  number    = {4},
  doi       = {10.1007/s00330-022-09256-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324978},
  pages     = {2529-2535},
  year      = {2023},
  abstract  = {Objective Blindness is a feared complication of giant cell arteritis (GCA). However, the spectrum of pathologic orbital imaging findings on magnetic resonance imaging (MRI) in GCA is not well understood. In this study, we assess inflammatory changes of intraorbital structures on black blood MRI (BB-MRI) in patients with GCA compared to age-matched controls. Methods In this multicenter case-control study, 106 subjects underwent BB-MRI. Fifty-six patients with clinically or histologically diagnosed GCA and 50 age-matched controls without clinical or laboratory evidence of vasculitis were included. All individuals were imaged on a 3-T MR scanner with a post-contrast compressed-sensing (CS) T1-weighted sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) BB-MRI sequence. Imaging results were correlated with available clinical symptoms. Results Eighteen of 56 GCA patients (32\%) showed inflammatory changes of at least one of the intraorbital structures. The most common finding was enhancement of at least one of the optic nerve sheaths (N = 13, 72\%). Vessel wall enhancement of the ophthalmic artery was unilateral in 8 and bilateral in 3 patients. Enhancement of the optic nerve was observed in one patient. There was no significant correlation between imaging features of inflammation and clinically reported orbital symptoms (p = 0.10). None of the age-matched control patients showed any inflammatory changes of intraorbital structures. Conclusions BB-MRI revealed inflammatory findings in the orbits in up to 32\% of patients with GCA. Optic nerve sheath enhancement was the most common intraorbital inflammatory change on BB-MRI. MRI findings were independent of clinically reported orbital symptoms. Key Points • Up to 32\% of GCA patients shows signs of inflammation of intraorbital structures on BB-MRI. • Enhancement of the optic nerve sheath is the most common intraorbital finding in GCA patients on BB-MRI. • Features of inflammation of intraorbital structures are independent of clinically reported symptoms.},
  language  = {en}
}
@article{GuggenbergerBleyVogtetal.2022,
  author    = {Guggenberger, Konstanze V. and Bley, Thorsten A. and Vogt, Marius L. and Urbach, Horst and Meckel, Stephan},
  title     = {High-Resolution Black Blood Vessel Wall Imaging in COVID-19 Encephalopathy-Is it Really Endotheliitis?},
  series = {Clinical Neuroradiology},
  volume    = {32},
  journal   = {Clinical Neuroradiology},
  number    = {1},
  doi       = {10.1007/s00062-021-01109-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-264794},
  pages     = {295-296},
  year      = {2022},
  abstract  = {No abstract available.},
  language  = {en}
}
@article{HerzStefanescuLohretal.2022,
  author    = {Herz, Stefan and Stefanescu, Maria R. and Lohr, David and Vogel, Patrick and Kosmala, Aleksander and Terekhov, Maxim and Weng, Andreas M. and Grunz, Jan-Peter and Bley, Thorsten A. and Schreiber, Laura M.},
  title     = {Effects of image homogeneity on stenosis visualization at 7 T in a coronary artery phantom study: With and without B1-shimming and parallel transmission},
  series = {PloS One},
  volume    = {17},
  journal   = {PloS One},
  number    = {6},
  doi       = {10.1371/journal.pone.0270689},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300129},
  year      = {2022},
  abstract  = {Background To investigate the effects of B\(_1\)-shimming and radiofrequency (RF) parallel transmission (pTX) on the visualization and quantification of the degree of stenosis in a coronary artery phantom using 7 Tesla (7 T) magnetic resonance imaging (MRI). Methods Stenosis phantoms with different grades of stenosis (0\%, 20\%, 40\%, 60\%, 80\%, and 100\%; 5 mm inner vessel diameter) were produced using 3D printing (clear resin). Phantoms were imaged with four different concentrations of diluted Gd-DOTA representing established arterial concentrations after intravenous injection in humans. Samples were centrally positioned in a thorax phantom of 30 cm diameter filled with a custom-made liquid featuring dielectric properties of muscle tissue. MRI was performed on a 7 T whole-body system. 2D-gradient-echo sequences were acquired with an 8-channel transmit 16-channel receive (8 Tx / 16 Rx) cardiac array prototype coil with and without pTX mode. Measurements were compared to those obtained with identical scan parameters using a commercially available 1 Tx / 16 Rx single transmit coil (sTX). To assess reproducibility, measurements (n = 15) were repeated at different horizontal angles with respect to the B0-field. Results B\(_1\)-shimming and pTX markedly improved flip angle homogeneity across the thorax phantom yielding a distinctly increased signal-to-noise ratio (SNR) averaged over a whole slice relative to non-manipulated RF fields. Images without B\(_1\)-shimming showed shading artifacts due to local B\(_1\)\(^+\)-field inhomogeneities, which hampered stenosis quantification in severe cases. In contrast, B\(_1\)-shimming and pTX provided superior image homogeneity. Compared with a conventional sTX coil higher grade stenoses (60\% and 80\%) were graded significantly (p<0.01) more precise. Mild to moderate grade stenoses did not show significant differences. Overall, SNR was distinctly higher with B\(_1\)-shimming and pTX than with the conventional sTX coil (inside the stenosis phantoms 14\%, outside the phantoms 32\%). Both full and half concentration (10.2 mM and 5.1 mM) of a conventional Gd-DOTA dose for humans were equally suitable for stenosis evaluation in this phantom study. Conclusions B\(_1\)-shimming and pTX at 7 T can distinctly improve image homogeneity and therefore provide considerably more accurate MR image analysis, which is beneficial for imaging of small vessel structures.},
  language  = {en}
}
@article{MihatschBeissertPomperetal.2022,
  author    = {Mihatsch, Patrick W. and Beissert, Matthias and Pomper, Martin G. and Bley, Thorsten A. and Seitz, Anna K. and K{\"u}bler, Hubert and Buck, Andreas K. and Rowe, Steven P. and Serfling, Sebastian E. and Hartrampf, Philipp E. and Werner, Rudolf A.},
  title     = {Changing threshold-based segmentation has no relevant impact on semi-quantification in the context of structured reporting for PSMA-PET/CT},
  series = {Cancers},
  volume    = {14},
  journal   = {Cancers},
  number    = {2},
  issn      = {2072-6694},
  doi       = {10.3390/cancers14020270},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-254782},
  year      = {2022},
  abstract  = {Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA-RADS, we characterized lesions in 18 patients imaged with \(^{18}\)F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV\(_{max}\), SUV\(_{peak}\), SUV\(_{mean}\)) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50\%). SUV\(_{max}\) was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (p ≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV\(_{max}\) and SUV\(_{peak}\) compared to the entire PSMA-RADS-4 or -5 cohort (p < 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (p < 0.0001), but not to the PSMA-RADS-4 cohort (SUV\(_{max}\), p = 0.07; SUV\(_{peak}\), p = 0.08). SUV\(_{mean}\) (p = 0.30) and TL-PSMA (p = 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50\% MIT (p = 0.0066), which was driven by lymph nodes (p = 0.0239), but not bone lesions (p = 0.15). SUV\(_{max}\) was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in \(^{18}\)F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV\(_{mean}\) and TL-PSMA in contrast to PSMA-TV.},
  language  = {en}
}
@unpublished{HeidenreichGassenmaierAnkenbrandetal.2021,
  author    = {Heidenreich, Julius F. and Gassenmaier, Tobias and Ankenbrand, Markus J. and Bley, Thorsten A. and Wech, Tobias},
  title     = {Self-configuring nnU-net pipeline enables fully automatic infarct segmentation in late enhancement MRI after myocardial infarction},
  edition   = {accepted version},
  doi       = {10.1016/j.ejrad.2021.109817},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323418},
  year      = {2021},
  abstract  = {Purpose To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy. Methods In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework ("nnU-net") was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels. Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the S{\o}rensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson's r correlation and Bland-Altman analysis. Results The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network. Conclusion The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.},
  language  = {en}
}
@article{FroehlichSerflingHiguchietal.2021,
  author    = {Fr{\"o}hlich, Matthias and Serfling, Sebastian and Higuchi, Takahiro and Pomper, Martin G. and Rowe, Steven P. and Schmalzing, Marc and Tony, Hans-Peter and Gernert, Michael and Strunz, Patrick-Pascal and Portegys, Jan and Schwaneck, Eva-Christina and Gadeholt, Ottar and Weich, Alexander and Buck, Andreas K. and Bley, Thorsten A. and Guggenberger, Konstanze V. and Werner, Rudolf A.},
  title     = {Whole-Body [\(^{18}\)F]FDG PET/CT Can Alter Diagnosis in Patients with Suspected Rheumatic Disease},
  series = {Diagnostics},
  volume    = {11},
  journal   = {Diagnostics},
  number    = {11},
  issn      = {2075-4418},
  doi       = {10.3390/diagnostics11112073},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-250227},
  year      = {2021},
  abstract  = {The 2-deoxy-d-[\(^{18}\)F]fluoro-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) is widely utilized to assess the vascular and articular inflammatory burden of patients with a suspected diagnosis of rheumatic disease. We aimed to elucidate the impact of [\(^{18}\)F]FDG PET/CT on change in initially suspected diagnosis in patients at the time of the scan. Thirty-four patients, who had undergone [\(^{18}\)F]FDG PET/CT, were enrolled and the initially suspected diagnosis prior to [18F]FDG PET/CT was compared to the final diagnosis. In addition, a semi-quantitative analysis including vessel wall-to-liver (VLR) and joint-to-liver (JLR) ratios was also conducted. Prior to [\(^{18}\)F]FDG PET/CT, 22/34 (64.7\%) of patients did not have an established diagnosis, whereas in 7/34 (20.6\%), polymyalgia rheumatica (PMR) was suspected, and in 5/34 (14.7\%), giant cell arteritis (GCA) was suspected by the referring rheumatologists. After [\(^{18}\)F]FDG PET/CT, the diagnosis was GCA in 19/34 (55.9\%), combined GCA and PMR (GCA + PMR) in 9/34 (26.5\%) and PMR in the remaining 6/34 (17.6\%). As such, [\(^{18}\)F]FDG PET/CT altered suspected diagnosis in 28/34 (82.4\%), including in all unclear cases. VLR of patients whose final diagnosis was GCA tended to be significantly higher when compared to VLR in PMR (GCA, 1.01 ± 0.08 (95\%CI, 0.95-1.1) vs. PMR, 0.92 ± 0.1 (95\%CI, 0.85-0.99), p = 0.07), but not when compared to PMR + GCA (1.04 ± 0.14 (95\%CI, 0.95-1.13), p = 1). JLR of individuals finally diagnosed with PMR (0.94 ± 0.16, (95\%CI, 0.83-1.06)), however, was significantly increased relative to JLR in GCA (0.58 ± 0.04 (95\%CI, 0.55-0.61)) and GCA + PMR (0.64 ± 0.09 (95\%CI, 0.57-0.71); p < 0.0001, respectively). In individuals with a suspected diagnosis of rheumatic disease, an inflammatory-directed [\(^{18}\)F]FDG PET/CT can alter diagnosis in the majority of the cases, particularly in subjects who were referred because of diagnostic uncertainty. Semi-quantitative assessment may be helpful in establishing a final diagnosis of PMR, supporting the notion that a quantitative whole-body read-out may be useful in unclear cases.},
  language  = {en}
}
@article{WengKoestlerBleyetal.2021,
  author    = {Weng, Andreas M. and K{\"o}stler, Herbert and Bley, Thorsten A. and Ritter, Christian O.},
  title     = {Effect of short-term smoking \& L-arginine on coronary endothelial function assessed by cardiac magnetic resonance cold pressor testing: a pilot study},
  series = {BMC Cardiovascular Disorders},
  volume    = {21},
  journal   = {BMC Cardiovascular Disorders},
  doi       = {10.1186/s12872-021-02050-1},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260559},
  year      = {2021},
  abstract  = {Background The effect of smoking on coronary vasomotion has been investigated in the past with various imaging techniques in both short- and long-term smokers. Additionally, coronary vasomotion has been shown to be normalized in long-term smokers by L-Arginine acting as a substrate for NO synthase, revealing the coronary endothelium as the major site of abnormal vasomotor response. Aim of the prospective cohort study was to investigate coronary vasomotion of young healthy short-term smokers via magnetic resonance cold pressor test with and without the administration of L-Arginine and compare obtained results with the ones from nonsmokers. Methods Myocardial blood flow (MBF) was quantified with first-pass perfusion MRI on a 1.5 T scanner in healthy short-term smokers (N = 10, age: 25.0 ± 2.8 years, 5.0 ± 2.9 pack years) and nonsmokers (N = 10, age: 34.3 ± 13.6) both at rest and during cold pressor test (CPT). Smokers underwent an additional examination after administration of L-Arginine within a median of 7 days of the na{\"i}ve examination. Results MBF at rest turned out to be 0.77 ± 0.30 (smokers with no L-Arginine; mean ± standard deviation), 0.66 ± 0.21 (smokers L-Arginine) and 0.84 ± 0.08 (nonsmokers). Values under CPT were 1.21 ± 0.42 (smokers no L-Arginine), 1.09 ± 0.35 (smokers L-Arginine) and 1.63 ± 0.33 (nonsmokers). In all groups, MBF was significantly increased under CPT compared to the corresponding rest examination (p < 0.05 in all cases). Additionally, MBF under CPT was significantly different between the smokers and the nonsmokers (p = 0.002). MBF at rest was significantly different between the smokers when L-Arginine was given and the nonsmokers (p = 0.035). Conclusion Short-term smokers showed a reduced response to cold both with and without the administration of L-Arginine. However, absolute MBF values under CPT were lower compared to nonsmokers independently of L-Arginine administration.},
  language  = {en}
}
@article{WengHeidenreichMetzetal.2021,
  author    = {Weng, Andreas M. and Heidenreich, Julius F. and Metz, Corona and Veldhoen, Simon and Bley, Thorsten A. and Wech, Tobias},
  title     = {Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times},
  series = {BMC Medical Imaging},
  volume    = {21},
  journal   = {BMC Medical Imaging},
  doi       = {10.1186/s12880-021-00608-1},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260520},
  year      = {2021},
  abstract  = {Background Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentation of lung images which were scanned by a fast UTE sequence exploiting the stack-of-spirals trajectory can provide sufficiently good accuracy for the calculation of functional parameters. Methods In this study, lung images were acquired in 20 patients suffering from cystic fibrosis (CF) and 33 healthy volunteers, by a fast UTE sequence with a stack-of-spirals trajectory and a minimum echo-time of 0.05 ms. A convolutional neural network was then trained for semantic lung segmentation using 17,713 2D coronal slices, each paired with a label obtained from manual segmentation. Subsequently, the network was applied to 4920 independent 2D test images and results were compared to a manual segmentation using the S{\o}rensen-Dice similarity coefficient (DSC) and the Hausdorff distance (HD). Obtained lung volumes and fractional ventilation values calculated from both segmentations were compared using Pearson's correlation coefficient and Bland Altman analysis. To investigate generalizability to patients outside the CF collective, in particular to those exhibiting larger consolidations inside the lung, the network was additionally applied to UTE images from four patients with pneumonia and one with lung cancer. Results The overall DSC for lung tissue was 0.967 ± 0.076 (mean ± standard deviation) and HD was 4.1 ± 4.4 mm. Lung volumes derived from manual and deep learning based segmentations as well as values for fractional ventilation exhibited a high overall correlation (Pearson's correlation coefficent = 0.99 and 1.00). For the additional cohort with unseen pathologies / consolidations, mean DSC was 0.930 ± 0.083, HD = 12.9 ± 16.2 mm and the mean difference in lung volume was 0.032 ± 0.048 L. Conclusions Deep learning-based image segmentation in stack-of-spirals based lung MRI allows for accurate estimation of lung volumes and fractional ventilation values and promises to replace the time-consuming step of manual image segmentation in the future.},
  language  = {en}
}
@article{PetritschPannbeckerWengetal.2021,
  author    = {Petritsch, Bernhard and Pannbecker, Pauline and Weng, Andreas M. and Grunz, Jan-Peter and Veldhoen, Simon and Bley, Thorsten A. and Kosmala, Aleksander},
  title     = {Split-filter dual-energy CT pulmonary angiography for the diagnosis of acute pulmonary embolism: a study on image quality and radiation dose},
  series = {Quantitative Imaging in Medicine and Surgery},
  volume    = {11},
  journal   = {Quantitative Imaging in Medicine and Surgery},
  number    = {5},
  doi       = {10.21037/qims-20-740},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231456},
  pages     = {1817-1827},
  year      = {2021},
  abstract  = {Background: Computed tomography (CT) pulmonary angiography is the diagnostic reference standard in suspected pulmonary embolism (PE). Favorable results for dual-energy CT (DECT) images have been reported for this condition. Nowadays, dual-energy data acquisition is feasible with different technical options, including a single-source split-filter approach. Therefore, the aim of this retrospective study was to investigate image quality and radiation dose of thoracic split-filter DECT in comparison to conventional single-energy CT in patients with suspected PE. Methods: A total of 110 CT pulmonary angiographies were accomplished either as standard single-energy CT with automatic tube voltage selection (ATVS) (n=58), or as split-filter DECT (n=52). Objective [pulmonary artery CT attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)] and subjective image quality [four-point Likert scale; three readers (R)] were compared among the two study groups. Size-specific dose estimates (SSDE), dose-length-product (DLP) and volume CT dose index (CTDIvol) were assessed for radiation dose analysis. Results: Split-filter DECT images yielded 67.7\% higher SNR (27.0 vs. 16.1; P<0.001) and 61.9\% higher CNR (22.5 vs. 13.9; P<0.001) over conventional single-energy images, whereas CT attenuation was significantly lower (344.5 vs. 428.2 HU; P=0.013). Subjective image quality was rated good or excellent in 93.0\%/98.3\%/77.6\% (R1/R2/R3) of the single-energy CT scans, and 84.6\%/82.7\%/80.8\% (R1/R2/R3) of the split-filter DECT scans. SSDE, DLP and CTDIvol were significantly lower for conventional single-energy CT compared to split-filter DECT (all P<0.05), which was associated with 26.7\% higher SSDE. Conclusions: In the diagnostic workup of acute PE, the split-filter allows for dual-energy data acquisition from single-source single-layer CT scanners. The existing opportunity to assess pulmonary "perfusion" based on analysis of iodine distribution maps is associated with higher radiation dose in terms of increased SSDE than conventional single-energy CT with ATVS. Moreover, a proportion of up to 3.8\% non-diagnostic examinations in the current reference standard test for PE is not negligible.},
  language  = {en}
}