Publications by authors named "David Maintz"

235 Publications

MRI DTI and PDFF as Biomarkers for Lower Motor Neuron Degeneration in ALS.

Front Neurosci 2021 26;15:682126. Epub 2021 Aug 26.

Department of Neuroradiology, Center Hospital Luxembourg, Luxembourg City, Luxembourg.

Objective: To evaluate the utility of nerve magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and muscle MRI multi-echo Dixon for assessing lower motor neuron (LMN) degeneration in amyotrophic lateral sclerosis (ALS).

Methods: In this prospective observational cohort study, 14 patients with ALS and 13 healthy controls underwent a multiparametric MRI protocol, including DTI of the sciatic nerve and assessment of muscle proton density fat fraction of the biceps femoris and the quadriceps femoris muscles by a multi-echo Dixon sequence.

Results: In ALS patients, mean fractional anisotropy values of the sciatic nerve were significantly lower than those of healthy controls. The quadriceps femoris, but not the biceps femoris muscle, showed significantly higher intramuscular fat fractions in ALS.

Interpretation: Our study provides evidence that multiparametric MRI protocols might help estimate structural nerve damage and neurogenic muscle changes in ALS.
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http://dx.doi.org/10.3389/fnins.2021.682126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428530PMC
August 2021

Manual kidney stone size measurements in computed tomography are most accurate using multiplanar image reformatations and bone window settings.

Sci Rep 2021 Aug 12;11(1):16437. Epub 2021 Aug 12.

Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.

Computed tomography in suspected urolithiasis provides information about the presence, location and size of stones. Particularly stone size is a key parameter in treatment decision; however, data on impact of reformatation and measurement strategies is sparse. This study aimed to investigate the influence of different image reformatations, slice thicknesses and window settings on stone size measurements. Reference stone sizes of 47 kidney stones representative for clinically encountered compositions were measured manually using a digital caliper (Man-M). Afterwards stones were placed in a 3D-printed, semi-anthropomorphic phantom, and scanned using a low dose protocol (CTDI 2 mGy). Images were reconstructed using hybrid-iterative and model-based iterative reconstruction algorithms (HIR, MBIR) with different slice thicknesses. Two independent readers measured largest stone diameter on axial (2 mm and 5 mm) and multiplanar reformatations (based upon 0.67 mm reconstructions) using different window settings (soft-tissue and bone). Statistics were conducted using ANOVA ± correction for multiple comparisons. Overall stone size in CT was underestimated compared to Man-M (8.8 ± 2.9 vs. 7.7 ± 2.7 mm, p < 0.05), yet closely correlated (r = 0.70). Reconstruction algorithm and slice thickness did not significantly impact measurements (p > 0.05), while image reformatations and window settings did (p < 0.05). CT measurements using multiplanar reformatation with a bone window setting showed closest agreement with Man-M (8.7 ± 3.1 vs. 8.8 ± 2.9 mm, p < 0.05, r = 0.83). Manual CT-based stone size measurements are most accurate using multiplanar image reformatation with a bone window setting, while measurements on axial planes with different slice thicknesses underestimate true stone size. Therefore, this procedure is recommended when impacting treatment decision.
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http://dx.doi.org/10.1038/s41598-021-95962-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8361194PMC
August 2021

Current Status of Cardiovascular Imaging in Germany: Structured Data from the National Certification Program, ESCR Registry, and Survey among Radiologists.

Rofo 2021 Aug 12. Epub 2021 Aug 12.

Department for Interventional and Diagnostic Radiology, University Hospital Cologne, Germany.

Purpose:  In the light of the increasing importance of cardiovascular cross-sectional imaging in current guidelines, the goal of this study is to provide a comprehensive overview of cardiovascular imaging (CVI) offered by radiological institutions across Germany.

Materials And Methods:  Data were extracted from the national certification program database of the German Roentgen Society (DRG) from 2015-2021. A nationwide online survey among radiology institutes (university hospitals, non-university hospitals, and private practices) was conducted for 2019, and data was extracted from the European Society of Cardiovascular Radiology (ESCR) registry. The data collection's key points included the number of centers and individuals certified for CVI, the number of cardiac CT and MRI examinations performed, the reporting habits, and the participation in the ESCR registry.

Results:  71 centers and 1278 persons, both with a substantial increase since 2015, were registered and certified by the DRG to perform CVI. According to the survey, a total of 69,286 CT and 64,281 MRI examinations were performed annually. Data from the survey and the ESCR registry indicated that reporting was mostly done solely by radiologists or, to a lesser degree, in joint consensus meetings with non-radiologists. The overall participation rate in the ESCR registry was 48 % among the survey's participants.

Conclusion:  This comprehensive analysis demonstrates that high-quality CVI by radiologists is available nationwide. The current challenges are to provide the best medical and technical quality of CVI by radiology for patient care and to ensure economic sustainability in the German health care system to accommodate the predicted substantial need for CVI in the future.

Key Points:   · High-quality advanced CVI service by radiologists is available nationwide.. · Highly qualified specialist knowledge is widely represented from university to private practices.. · Certification programs successfully contribute to the dissemination & deepening of CVI expertise.. · The ESCR registry is an established international tool for the documentation of CVI..

Citation Format: · Sieren M, Maintz D, Gutberlet M et al. Current Status of Cardiovascular Imaging in Germany: Structured Data from the National Certification Program, ESCR Registry, and Survey among Radiologists. Fortschr Röntgenstr 2021; DOI: 10.1055/a-1554-9236.
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http://dx.doi.org/10.1055/a-1554-9236DOI Listing
August 2021

[Interventional Radiology in Oncology - Update 2021].

Dtsch Med Wochenschr 2021 Aug 3;146(15):966-970. Epub 2021 Aug 3.

Institut für Diagnostische und Interventionelle Radiologie des Universitätsklinikums Köln.

Interventional radiology plays a crucial role in oncology. The most common interventional treatments are transarterial embolisation as well as percutaneous thermal ablations. Transarterial embolisation, such as transarterial chemoembolization (TACE) or selective internal radiation therapy (SIRT) are well established, usually palliatively intended treatment options for primary and secondary hepatic malignancies. Embolisation is usually well tolerated under conscious sedation and can be repeated several times. Percutaneous thermoablation is a local ablative, usually curatively intended treatment for hepatic, renal and pulmonary tumors. As a minimally invasive technique, it competes against surgery and radiation therapy. There are different types of thermoablation, most commonly used are radiofrequency ablation (RFA), microwave ablation (MWA) and cryo-ablation. Ablation is usually performed in general anesthesia, less common in conscious sedation. New interventional treatments are high intensity focused ultrasound (HIFU) and irreversible electroporation (IRE). HIFU allows a non-invasive, imaging-guided thermoablation that is currently certified for uterine myoma, prostate cancer and bone tumors. IRE is a minimal invasive non-thermal ablation that is especially established for locally advanced tumors that show a close relationship to large vessels, for example pancreatic cancer.
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http://dx.doi.org/10.1055/a-1192-0690DOI Listing
August 2021

Coronary artery calcification on low-dose chest CT is an early predictor of severe progression of COVID-19-A multi-center, multi-vendor study.

PLoS One 2021 21;16(7):e0255045. Epub 2021 Jul 21.

Department of Radiology, University Hospital of Cologne, Cologne, Germany.

Purpose: Cardiovascular comorbidity anticipates severe progression of COVID-19 and becomes evident by coronary artery calcification (CAC) on low-dose chest computed tomography (LDCT). The purpose of this study was to predict a patient's obligation of intensive care treatment by evaluating the coronary calcium burden on the initial diagnostic LDCT.

Methods: Eighty-nine consecutive patients with parallel LDCT and positive RT-PCR for SARS-CoV-2 were included from three centers. The primary endpoint was admission to ICU, tracheal intubation, or death in the 22-day follow-up period. CAC burden was represented by the Agatston score. Multivariate logistic regression was modeled for prediction of the primary endpoint by the independent variables "Agatston score > 0", as well as the CT lung involvement score, patient sex, age, clinical predictors of severe COVID-19 progression (history of hypertension, diabetes, prior cardiovascular event, active smoking, or hyperlipidemia), and laboratory parameters (creatinine, C-reactive protein, leucocyte, as well as thrombocyte counts, relative lymphocyte count, d-dimer, and lactate dehydrogenase levels).

Results: After excluding multicollinearity, "Agatston score >0" was an independent regressor within multivariate analysis for prediction of the primary endpoint (p<0.01). Further independent regressors were creatinine (p = 0.02) and leucocyte count (p = 0.04). The Agatston score was significantly higher for COVID-19 cases which completed the primary endpoint (64.2 [interquartile range 1.7-409.4] vs. 0 [interquartile range 0-0]).

Conclusion: CAC scoring on LDCT might help to predict future obligation of intensive care treatment at the day of patient admission to the hospital.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255045PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294495PMC
July 2021

Possibility to discriminate benign from malignant breast lesions detected on dual-layer spectral CT-evaluation.

Eur J Radiol 2021 Sep 24;142:109832. Epub 2021 Jun 24.

Department of Radiology, Cliniques Universitaires St-Luc, Université Catholique de Louvain, Brussels, Belgium.

Objectives: Intramammary mass lesions are reportedly present in up to 5.8% of all contrast enhanced CT-examinations of the female chest. We aimed to assess whether their biological relevance can be estimated using spectral CT-datasets.

Methods: In this bicentric retrospective study patients with breast masses visualized on spectral CT-examinations from 07/2017 to 06/2019 were included. Lesions were characterized as malignant or benign based on histology and/or a stable follow-up of >2 years. Conventional CT-images, iodine density-maps, virtual monoenergetic-images (40 keV, 100 keV) and Zeffective-maps were evaluated by two independent readers. Statistical analysis derived from the Regions of interest (ROIs) was done by calculating the Areas under the Receiver operating characteristic (ROC) curve (AUC) and Youden-indices.

Results: 106 breast masses (malignant/benign: 81/25, 76.4%/23.6%) were included. The mean AUCs of the variables "iodine content" (reader 1/2:0.97;0.98), "monoenergetic curve-slope" (0.97;0.96) and "Zeffective" (0.98;0.98) measured in the target lesions (TL) showed superior results compared to those derived from the variable "density" (0.92;0.93) (p < 0.001). The ratios "TL to aorta" calculated for the variables "iodine content", "monoenergetic curve-slope" and "Zeffective" showed superior results compared to normal breast tissue and muscle (p < 0.001). The optimal cutpoint for the "iodine content" in the TL was 0.7-0.9 mg/ml (sensitivity 96.6%, specificity 91.7%). The best diagnostic results were achieved by normalizing the iodine content in the TL to that in the aorta (optimal cutpoint 0.1, sensitivity 95.5%, 98.9%, specificity 91.7%).

Conclusions: Our preliminary results suggest that spectral CT-datasets might allow to estimate the biological dignity of breast masses detected on clinically indicated chest-examinations.
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http://dx.doi.org/10.1016/j.ejrad.2021.109832DOI Listing
September 2021

Influence of aging and gadolinium exposure on T1, T2, and T2*-relaxation in healthy women with an increased risk of breast cancer with and without prior exposure to gadoterate meglumine at 3.0-T brain MR imaging.

Eur Radiol 2021 Jul 3. Epub 2021 Jul 3.

Institute of Medical Statistics and Bioinformatics, University of Cologne, Cologne, Germany.

Objectives: We examined the effects of aging and of gadolinium-based contrast agent (GBCA) exposure on MRI measurements in brain nuclei of healthy women.

Methods: This prospective, IRB-approved single-center case-control study enrolled 100 healthy participants of our high-risk screening center for hereditary breast cancer, who had received at least six doses of macrocyclic GBCA (exposed group) or were newly entering the program (GBCA-naïve group). The cutoff "at least six doses" was chosen to be able to include a sufficient number of highly exposed participants. All participants underwent unenhanced 3.0-T brain MRI including quantitative T1, T2, and R2* mapping and T1- and T2-weighted imaging. The relaxation times/signal intensities were derived from region of interest measurements in the brain nuclei performed by a radiologist and a neuroradiologist, both board certified. Statistical analysis was based on descriptive evaluations and uni-/multivariable analyses.

Results: The participants (exposed group: 49, control group: 51) were aged 42 ± 9 years. In a multivariable model, age had a clear impact on R2* (p < 0.001-0.012), T2 (p = 0.003-0.048), and T1 relaxation times/signal intensities (p < 0.004-0.046) for the majority of deep brain nuclei, mostly affecting the substantia nigra, globus pallidus (GP), nucleus ruber, thalamus, and dentate nucleus (DN). The effect of prior GBCA administration on T1 relaxation times was statistically significant for the DN, GP, and pons (p = 0.019-0.037).

Conclusions: In a homogeneous group of young to middle-aged healthy females aging had an effect on T2 and R2* relaxation times and former GBCA applications influenced the measured T1 relaxation times.

Key Points: The quantitative T1, T2, and R2* relaxation times measured in women at high risk of developing breast cancer showed characteristic bandwidth for all brain nuclei examined at 3.0-T MRI. The effect of participant age had a comparatively strong impact on R2*, T2, and T1 relaxation times for the majority of brain nuclei examined. The effect of prior GBCA administrations on T1 relaxation times rates was comparatively less pronounced, yielding statistically significant results for the dentate nucleus, globus pallidus, and pons. Healthy women with and without previous GBCA-enhanced breast MRI exhibited age-related T2* and T2 relaxation alterations at 3.0 T-brain MRI. T1 relaxation alterations due to prior GBCA administration were comparatively less pronounced.
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http://dx.doi.org/10.1007/s00330-021-08069-4DOI Listing
July 2021

Contrast-Enhanced Black Blood MRI Sequence Is Superior to Conventional T1 Sequence in Automated Detection of Brain Metastases by Convolutional Neural Networks.

Diagnostics (Basel) 2021 Jun 1;11(6). Epub 2021 Jun 1.

Institut für Radiologie Neuroradiologie und Nuklearmedizin, Ruhr-Universität Bochum, Minden University Hospital, Hans-Nolte-Strasse 1, 32429 Minden, Germany.

Background: in magnetic resonance imaging (MRI), automated detection of brain metastases with convolutional neural networks (CNN) represents an extraordinary challenge due to small lesions sometimes posing as brain vessels as well as other confounders. Literature reporting high false positive rates when using conventional contrast enhanced (CE) T1 sequences questions their usefulness in clinical routine. CE black blood (BB) sequences may overcome these limitations by suppressing contrast-enhanced structures, thus facilitating lesion detection. This study compared CNN performance in conventional CE T1 and BB sequences and tested for objective improvement of brain lesion detection.

Methods: we included a subgroup of 127 consecutive patients, receiving both CE T1 and BB sequences, referred for MRI concerning metastatic spread to the brain. A pretrained CNN was retrained with a customized monolayer classifier using either T1 or BB scans of brain lesions.

Results: CE T1 imaging-based training resulted in an internal validation accuracy of 85.5% vs. 92.3% in BB imaging ( < 0.01). In holdout validation analysis, T1 image-based prediction presented poor specificity and sensitivity with an AUC of 0.53 compared to 0.87 in BB-imaging-based prediction.

Conclusions: detection of brain lesions with CNN, BB-MRI imaging represents a highly effective input type when compared to conventional CE T1-MRI imaging. Use of BB-MRI can overcome the current limitations for automated brain lesion detection and the objectively excellent performance of our CNN suggests routine usage of BB sequences for radiological analysis.
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http://dx.doi.org/10.3390/diagnostics11061016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230135PMC
June 2021

Value of spectral detector computed tomography for the early assessment of technique efficacy after microwave ablation of hepatocellular carcinoma.

PLoS One 2021 15;16(6):e0252678. Epub 2021 Jun 15.

Faculty of Medicine and University Hospital Cologne, Department of Diagnostic and Interventional Radiology, University of Cologne, Cologne, Germany.

Objectives: To investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis.

Methods: This retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40-100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy.

Results: Attenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all p<0.05). Iodine concentration and perfusion ratio differed significantly between HR and RT (all p<0.05; e.g. iodine concentration, 1.6±0.5 vs. 2.7±1.3 mg/ml). VMI50keV improved subjective AZ-to-liver contrast, HR-to-liver contrast, visualization of AZ margin and vessels adjacent to AZ compared to CI (all p<0.05). Diagnostic accuracy for detection of incomplete ablation was slightly higher in VMI50keV compared to CI (0.92 vs. 0.89), while diagnostic confidence was significantly higher in VMI50keV (p<0.05).

Conclusions: Spectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252678PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8205161PMC
June 2021

An Innovative Approach for Preoperative Perforator Flap Planning Using Contrast-enhanced B-flow Imaging.

Plast Reconstr Surg Glob Open 2021 May 21;9(5):e3547. Epub 2021 May 21.

Division of Plastic and Aesthetic Surgery, University of Cologne, Cologne, Germany.

Precise perforator mapping of the epifascial and subcutaneous course of the perforator flaps, including the precise detection of the skin point, is mandatory for successful preoperative flap design and planning of supramicrosurgery. We investigated the effectiveness of contrast-enhanced B-flow (BCEUS) imaging for perforator mapping and preoperative perforator flap planning and compared it with B-flow ultrasound, contrast-enhanced ultrasound, and color Doppler ultrasound. Sixteen patients who received an individualized perforator flap reconstruction were included in the study. Preoperative perforator mapping includes the following structures: subfascial course of the pedicle, fascial penetration point, subcutaneous course (epifascial and subcutaneous), and perforator skin point. The precision of the preoperative perforator mapping was analyzed for color Doppler ultrasound, contrast-enhanced ultrasound, B-flow ultrasound, and BCEUS. Each technique was able to precisely display the subfascial course of the vascular pedicle, including the fascial penetration point. However, only BCEUS enabled precise mapping of the epifascial and subcutaneous (suprafascial) course, including the skin point of the perforators with a clear delineation. Precise knowledge of the suprafascial course of the perforators is mandatory for successful supermicrosurgery and perforator flap planning. BCEUS imaging facilitates full perforator mapping, which improves the safety of flap harvesting. However, BCEUS is technically demanding and requires an experienced sonographer.
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http://dx.doi.org/10.1097/GOX.0000000000003547DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140766PMC
May 2021

Automated mapping and N-Staging of thoracic lymph nodes in contrast-enhanced CT scans of the chest using a fully convolutional neural network.

Eur J Radiol 2021 Jun 20;139:109718. Epub 2021 Apr 20.

Institute for Diagnostic and Interventional Radiology, University Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Straße 62, 50937, Cologne, Germany.

Purpose: To develop a deep-learning (DL)-based approach for thoracic lymph node (LN) mapping based on their anatomical location.

Method: The training-and validation-dataset included 89 contrast-enhanced computed tomography (CT) scans of the chest. 4201 LNs were semi-automatically segmented and then assigned to LN levels according to their anatomical location. The LN level classification task was addressed by a multi-class segmentation procedure using a fully convolutional neural network. Mapping was performed by firstly determining potential level affiliation for each voxel and then performing majority voting over all voxels belonging to each LN. Mean classification accuracies on the validation data were calculated separately for each level and overall Top-1, Top-2 and Top-3 scores were determined, where a Top-X score describes how often the annotated class was within the top-X predictions. To demonstrate the clinical applicability of our model, we tested its N-staging capabilities in a simulated clinical use case scenario assuming a patient diseased with lung cancer.

Results: The artificial intelligence(AI)-based assignment revealed mean classification accuracies of 86.36 % (Top-1), 94.48 % (Top-2) and 96.10 % (Top-3). Best accuracies were achieved for LNs in the subcarinal level 7 (98.31 %) and axillary region (98.74 %). The highest misclassification rates were observed among LNs in adjacent levels. The proof-of-principle application in a simulated clinical use case scenario for automated tumor N-staging showed a mean classification accuracy of up to 96.14 % (Top-1).

Conclusions: The proposed AI approach for automatic classification of LN levels in chest CT as well as the proof-of-principle-experiment for automatic N-staging, revealed promising results, warranting large-scale validation for clinical application.
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http://dx.doi.org/10.1016/j.ejrad.2021.109718DOI Listing
June 2021

Speeding up the clinical routine: Compressed sensing for 2D imaging of lumbar spine disc herniation.

Eur J Radiol 2021 Jul 29;140:109738. Epub 2021 Apr 29.

Philips Healthcare Germany, Hamburg, Germany.

Purpose: Increasing economic pressure and patient demands for comfort require an ever-increasing acceleration of scan times without compromising diagnostic certainty. This study tested the new acceleration technique Compressed SENSE (CS-SENSE) as well as different reconstruction methods for the lumbar spine.

Methods: In this prospective study, 10 volunteers and 14 patients with lumbar disc herniation were scanned using a sagittal 2D T2 turbo spin echo (TSE) sequence applying different acceleration factors of SENSE and CS-SENSE. Gradient echo (GRE), autocalibration (CS-Auto) and TSE prescans were tested for reconstruction. Images were analysed by two readers regarding anatomical delineation, diagnostic certainty (for patients only) and image quality as well as objectively calculating the root mean square error (RMSE), structural similarity index (SSIM), SNR and CNR. The Friedman test and Chi-squared were used for ordinal, ANOVA for repeated measurements and Tukey Kramer test for continuous data. Cohen's kappawas calculated for interreader reliability.

Results: CS-SENSE outperformed SENSE and CS-Auto regarding RMSE (e.g. CS-SENSE 1.5: 43.03 ± 11.64 versus SENSE 1.5: 80.41 ± 17.66; p = 0.0038) and SSIM as well as in the subjective rating for CS-SENSE 3 TSE. In the patient setting image quality was unchanged in all subjective criteria up to CS-SENSE 3 TSE (all p > 0.05) compared to standard T2 with 43 % less scan time while the GRE prescan only allowed a reduction of 32 %.

Conclusion: Combining a TSE prescan with CS-SENSE enables significant scan time reductions with unchanged ratings for lumbar spine disc herniation making this superior to the currently used SENSE acceleration or GRE reconstructions.
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http://dx.doi.org/10.1016/j.ejrad.2021.109738DOI Listing
July 2021

Automated detection and segmentation of thoracic lymph nodes from CT using 3D foveal fully convolutional neural networks.

BMC Med Imaging 2021 Apr 13;21(1):69. Epub 2021 Apr 13.

Institute of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.

Background: In oncology, the correct determination of nodal metastatic disease is essential for patient management, as patient treatment and prognosis are closely linked to the stage of the disease. The aim of the study was to develop a tool for automatic 3D detection and segmentation of lymph nodes (LNs) in computed tomography (CT) scans of the thorax using a fully convolutional neural network based on 3D foveal patches.

Methods: The training dataset was collected from the Computed Tomography Lymph Nodes Collection of the Cancer Imaging Archive, containing 89 contrast-enhanced CT scans of the thorax. A total number of 4275 LNs was segmented semi-automatically by a radiologist, assessing the entire 3D volume of the LNs. Using this data, a fully convolutional neuronal network based on 3D foveal patches was trained with fourfold cross-validation. Testing was performed on an unseen dataset containing 15 contrast-enhanced CT scans of patients who were referred upon suspicion or for staging of bronchial carcinoma.

Results: The algorithm achieved a good overall performance with a total detection rate of 76.9% for enlarged LNs during fourfold cross-validation in the training dataset with 10.3 false-positives per volume and of 69.9% in the unseen testing dataset. In the training dataset a better detection rate was observed for enlarged LNs compared to smaller LNs, the detection rate for LNs with a short-axis diameter (SAD) ≥ 20 mm and SAD 5-10 mm being 91.6% and 62.2% (p < 0.001), respectively. Best detection rates were obtained for LNs located in Level 4R (83.6%) and Level 7 (80.4%).

Conclusions: The proposed 3D deep learning approach achieves an overall good performance in the automatic detection and segmentation of thoracic LNs and shows reasonable generalizability, yielding the potential to facilitate detection during routine clinical work and to enable radiomics research without observer-bias.
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http://dx.doi.org/10.1186/s12880-021-00599-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045346PMC
April 2021

Insights into extrinsic foot muscle activation during a 75 min run using T2 mapping.

Sci Rep 2021 Apr 1;11(1):7331. Epub 2021 Apr 1.

Institute of Biomechanics and Orthopaedics, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933, Cologne, Germany.

The extrinsic foot muscles are essentially for controlling the movement path but our knowledge of their behavior during prolonged running is still very limited. Therefore, this study analyzed the time-course of muscle activation using T2 mapping during 75 min of running. In this prospective study, 19 recreational active runners completed 75 min of treadmill running at a constant speed. Interleaved T2 mapping sequences were acquired and segmented at timepoints 0, 2.5, 5, 10, 15, 45, and 75 min. ANOVA for repeated measurements followed by a Tukey post hoc test and Pearson correlation between running speed and initial signal increase at 2.5 min were calculated. All muscles showed a significant signal increase between baseline and 2.5 min (e.g. medial gastrocnemius: + 15.48%; p < 0.01). This was followed by a plateau phase till 15 min for all but the extensor digitorum longus muscle and a significant decrease at 45 or 75 min for all muscles (all p < 0.05). Correlation between running speed and signal increase was negative for all muscles and significant for both gastrocnemii (e.g. medial: r =  - 0.57, p = 0.0104) and soleus (r =  - 0.47, p = 0.0412). The decrease of relaxation times times in the later running phases was less pronounced for faster runners (≥ 10 km/h). T2 relaxation times do not only decrease after cessation of exercise but already during prolonged running. The lesser initial increase and later decrease in faster runners may indicate training induced changes.
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http://dx.doi.org/10.1038/s41598-021-86810-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016869PMC
April 2021

Velocity quantification in 44 healthy volunteers using accelerated multi-VENC 4D flow CMR.

Eur J Radiol 2021 Apr 29;137:109570. Epub 2021 Jan 29.

Department of Radiology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany. Electronic address:

Background: To evaluate the feasibility of a k-t accelerated multi-VENC 4D phase contrast flow MRI acquisition of the main heart-surrounding vessels, its benefits over a traditional single-VENC acquisition and to present reference flow and velocity values in a large cohort of volunteers.

Methods: 44 healthy volunteers were examined on a 3 T MRI scanner (Ingenia, Philips, Best, The Netherlands). 4D flow measurements were obtained with a FOV including the aorta and the pulmonary arteries. VENC values were set to 40, 100 and 200 cm/s and unfolded based on an MRI signal model. Unfolded multi-VENC data was compared to the single-VENC with VENC 200 cm/s. Flow and velocity quantification was performed in several regions of interest (ROI) placed in the ascending aorta and in the main pulmonary artery. Conservation of mass analysis was performed for single- and multi-VENC datasets. Values for mean and maximal flow velocity and stroke volume were calculated and compared to the literature.

Results: Mean scan time was 13.8 ± 4 min. Differences between stroke volumes between the ascending aorta and the main pulmonary artery were significantly lower in multi-VENC datasets compared to single-VENC datasets (9.6 ± 7.8 mL vs. 25.4 ± 26.4 mL, p < 0.001). This was also true for differences in stroke volume between up- and downstream ROIs in the ascending aorta and pulmonary artery. Values for mean and maximal velocities and stroke volume were in-line with previous studies. To highlight potential clinical applications two exemplary 4D flow measurements in patients with different pathologies are shown and compared to single-VENC datasets.

Conclusions: k-t accelerated multi-VENC 4D phase contrast flow MRI acquisition of the great vessels is feasible in a clinically acceptable scan duration. It offers improvements over traditional single-VENC 4D flow, expectedly being valuable when vessels with different flow velocities or complex flow phenomena are evaluated.
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http://dx.doi.org/10.1016/j.ejrad.2021.109570DOI Listing
April 2021

Use and Control of Artificial Intelligence in Patients Across the Medical Workflow: Single-Center Questionnaire Study of Patient Perspectives.

J Med Internet Res 2021 02 17;23(2):e24221. Epub 2021 Feb 17.

Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.

Background: Artificial intelligence (AI) is gaining increasing importance in many medical specialties, yet data on patients' opinions on the use of AI in medicine are scarce.

Objective: This study aimed to investigate patients' opinions on the use of AI in different aspects of the medical workflow and the level of control and supervision under which they would deem the application of AI in medicine acceptable.

Methods: Patients scheduled for computed tomography or magnetic resonance imaging voluntarily participated in an anonymized questionnaire between February 10, 2020, and May 24, 2020. Patient information, confidence in physicians vs AI in different clinical tasks, opinions on the control of AI, preference in cases of disagreement between AI and physicians, and acceptance of the use of AI for diagnosing and treating diseases of different severity were recorded.

Results: In total, 229 patients participated. Patients favored physicians over AI for all clinical tasks except for treatment planning based on current scientific evidence. In case of disagreement between physicians and AI regarding diagnosis and treatment planning, most patients preferred the physician's opinion to AI (96.2% [153/159] vs 3.8% [6/159] and 94.8% [146/154] vs 5.2% [8/154], respectively; P=.001). AI supervised by a physician was considered more acceptable than AI without physician supervision at diagnosis (confidence rating 3.90 [SD 1.20] vs 1.64 [SD 1.03], respectively; P=.001) and therapy (3.77 [SD 1.18] vs 1.57 [SD 0.96], respectively; P=.001).

Conclusions: Patients favored physicians over AI in most clinical tasks and strongly preferred an application of AI with physician supervision. However, patients acknowledged that AI could help physicians integrate the most recent scientific evidence into medical care. Application of AI in medicine should be disclosed and controlled to protect patient interests and meet ethical standards.
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http://dx.doi.org/10.2196/24221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7929746PMC
February 2021

Pseudoaneurysm of an intercostal artery: endovascular treatment with PK papyrus coronary stent to prevent spinal ischemia.

CVIR Endovasc 2021 Feb 16;4(1):22. Epub 2021 Feb 16.

Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany.

Background: Endovascular treatment can be a fast and safe option in the case of acute, internal bleeding - but it requires special knowledge and technical skills. Interventionalists must consider the anatomy and potential complications. As in this case report, the anterior spinal artery, for example, can be a crucial vessel that must always be considered when embolizing intercostal or lumbar arteries. The risk of spinal ischemia has to be taken into account and should be minimized by choosing the appropriate treatment option.

Case Presentation: We report about a 77 year old, male patient with upper gastrointestinal bleeding after esophagectomy and gastric conduit reconstruction. A CT scan identified a pseudoaneurysm of an intercostal artery penetrating the gastric conduit as the bleeding source. In the DSA, a direct connection between the intercostal artery and the anterior spinal artery appeared to be likely. Due to the associated risk of spinal ischemia, an embolization of the intercostal artery was not an option. We decided to implant a stentgraft that would stop the perfusion of the pseudoaneurysm, but preserve the perfusion of the intercostal artery. Due to the small diameter of the vessel, we could not implant our commonly used stentgrafts in this case. Therefore, we chose an uncommon solution and used a stentgraft that is designed primarily for coronary arteries.

Conclusions: Whenever intercostal or lumbar arteries need to be embolized, a possible connection to the anterior spinal artery must be considered and interventionalists have to be aware of possible ischemic complications. In this case, a stentgraft designed primarily for coronary arteries offered a good endovascular treatment option for the pseudoaneurysm of an intercostal artery. The risk of spinal ischemia could be minimized by using this stentgraft.
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http://dx.doi.org/10.1186/s42155-021-00211-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887107PMC
February 2021

Long-Term Follow-Up and Clinical Relevance of Incidental Findings of Fibrin Sheath and Thrombosis on Computed Tomography Scans of Cancer Patients with Port Catheters.

Ther Clin Risk Manag 2021 27;17:111-118. Epub 2021 Jan 27.

Department of Radiology, University Hospital of Cologne, Cologne, Germany.

Purpose: This retrospective study examined the incidence, progression, and clinical relevance of catheter-related thrombosis (CRT) and/or fibrin sheaths presenting as incidental findings on routine staging computed tomography (CT) scans performed in cancer patients.

Patients And Methods: Patients who underwent central venous port catheter (CVC) placement in a tertiary care hospital between September 2010 and August 2013 were followed up for up to five years. Two radiologists assessed the presence of fibrin sheath and thrombosis in consensus in staging CT scan. Patient demographics, type of cancer, preoperative comorbidities, date of CVC placement and CTs, preexisting anticoagulation, as well as the type and treatment of catheter-related complications were determined from the electronic medical record.

Results: A total of 194 patients with 530 CT scans and a mean follow-up time of 394 days were included. Fibrin sheaths and thromboses were seen on 46 scans (8.7%) in 30 patients and 80 scans (15.1%) in 35 patients. The incidence of fibrin sheaths and thromboses was found to be 15.5% and 18%, respectively. The comparison to initial CT reports results indicated that fibrin sheaths or thromboses were missed in 106 examinations (20%). Catheter-associated complications were reported in 14 patients (21.5%) without specific therapy.

Conclusion: Fibrin sheaths and CRTs are often overlooked on routine CT scans when patients are asymptomatic. The subsequent high complication rate demonstrates the clinical relevance of the initial incidental finding on CT scan. Further studies should elucidate the effect of thrombolytic agents and interventional radiologic treatment in asymptomatic patients.
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http://dx.doi.org/10.2147/TCRM.S287544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850422PMC
January 2021

Texture analysis of iodine maps and conventional images for k-nearest neighbor classification of benign and metastatic lung nodules.

Cancer Imaging 2021 Jan 26;21(1):17. Epub 2021 Jan 26.

Department of Diagnostic and Interventional Radiology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Straße 62, 50937, Cologne, Germany.

Background: The purpose of this study was to analyze if the use of texture analysis on spectral detector CT (SDCT)-derived iodine maps (IM) in addition to conventional images (CI) improves lung nodule differentiation, when being applied to a k-nearest neighbor (KNN) classifier.

Methods: 183 cancer patients who underwent contrast-enhanced, venous phase SDCT of the chest were included: 85 patients with 146 benign lung nodules (BLN) confirmed by either prior/follow-up CT or histopathology and 98 patients with 425 lung metastases (LM) verified by histopathology, F-FDG-PET-CT or unequivocal change during treatment. Semi-automatic 3D segmentation of BLN/LM was performed, and volumetric HU attenuation and iodine concentration were acquired. For conventional images and iodine maps, average, standard deviation, entropy, kurtosis, mean of the positive pixels (MPP), skewness, uniformity and uniformity of the positive pixels (UPP) within the volumes of interests were calculated. All acquired parameters were transferred to a KNN classifier.

Results: Differentiation between BLN and LM was most accurate, when using all CI-derived features combined with the most significant IM-derived feature, entropy (Accuracy:0.87; F1/Dice:0.92). However, differentiation accuracy based on the 4 most powerful CI-derived features performed only slightly inferior (Accuracy:0.84; F1/Dice:0.89, p=0.125). Mono-parametric lung nodule differentiation based on either feature alone (i.e. attenuation or iodine concentration) was poor (AUC=0.65, 0.58, respectively).

Conclusions: First-order texture feature analysis of contrast-enhanced staging SDCT scans of the chest yield accurate differentiation between benign and metastatic lung nodules. In our study cohort, the most powerful iodine map-derived feature slightly, yet insignificantly increased classification accuracy  compared to classification based on conventional image features only.
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http://dx.doi.org/10.1186/s40644-020-00374-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836145PMC
January 2021

Lymph Node Assessment in Prostate Cancer: Evaluation of Iodine Quantification With Spectral Detector CT in Correlation to PSMA PET/CT.

Clin Nucl Med 2021 04;46(4):303-309

From the Institute for Diagnostic and Interventional Radiology, Faculty of Medicine, University Cologne and University Hospital Cologne, Cologne, Germany.

Purpose: The aims of this study were to evaluate spectral detector CT (SDCT)-derived iodine concentration (IC) of lymph nodes diagnosed as metastatic and benign in prostate-specific membrane antigen (PSMA) PET/CT and to assess its potential use for lymph node assessment in prostate cancer.

Patients And Methods: Thirty-four prostate cancer patients were retrospectively included: 16 patients with and 18 without lymph node metastases as determined by PSMA PET/CT. Patients underwent PSMA PET/CT as well as portal venous phase abdominal SDCT for clinical cancer follow-up. Only scan pairs with a stable nodal status indicated by constant size as well as comparable prostate-specific antigen (PSA) levels were included. One hundred benign and 96 suspected metastatic lymph nodes were annotated and correlated between SDCT and PSMA PET/CT. Iodine concentration in SDCT-derived iodine maps and SUVmax in ultra-high definition reconstructions from PSMA PET/CT were acquired based on the region of interest.

Results: Metastatic lymph nodes as per PSMA PET/CT showed higher IC than nonmetastatic nodes (1.9 ± 0.6 mg/mL vs 1.5 ± 0.5 mg/mL, P < 0.05) resulting in an AUC of 0.72 and sensitivity/specificity of 81.3%/58.5%. The mean short axis diameter of metastatic lymph nodes was larger than that of nonmetastatic nodes (6.9 ± 3.6 mm vs 5.3 ± 1.3 mm; P < 0.05); a size threshold of 1 cm short axis diameter resulted in a sensitivity/specificity of 12.8%/99.0%. There was a significant yet weak positive correlation between SUVmax and IC (rs = 0.25; P < 0.001).

Conclusions: Spectral detector CT-derived IC was increased in lymph nodes diagnosed as metastatic in PSMA PET/CT yet showed considerable data overlap. The correlation between IC and SUVmax was weak, highlighting the role of PSMA PET/CT as important reference imaging modality for detection of lymph node metastases in prostate cancer patients.
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http://dx.doi.org/10.1097/RLU.0000000000003496DOI Listing
April 2021

Virtual calcium-suppression in dual energy computed tomography predicts metabolic activity of focal MM lesions as determined by fluorodeoxyglucose positron-emission-tomography.

Eur J Radiol 2021 Feb 25;135:109502. Epub 2020 Dec 25.

Ruhr University Bochum, Johannes Wesling University Hospital, Department of Radiology, Neuroradiology and Nuclear Medicine, Hans-Nolte-Straße 1, 32429, Minden, Germany.

Purpose: Recent studies showed that dual energy CT (DECT) allows for detection of bone marrow infiltration in multiple myeloma (MM) by obtaining virtual non-calcium (VNCa) images. This feasibility study investigated, if VNCa imaging might discriminate metabolically active, focal lesions in MM against avital lesions in MM patients, considering fluorodeoxyglucose positron-emission-tomography CT (FDG PET/CT) as the standard of reference.

Method: The study included 60 osteolytic lesions in 10 consecutive low-dose whole body CT scans of patients with MM, who underwent both FDG PET/CT and DECT at a tertiary care university hospital. Circular ROI measurements were performed in predefined lesions on the monoenergetic CT (MECT) and VNCa images by three blinded radiologists. Each lesion was rated vital or avital by a blinded specialist of nuclear medicine, based on their FDG metabolism.

Results: Each of the three readers could separate FDG PET/CT negative and positive MM lesions when analyzing the VNCa images, while MECT did not show a significant difference. Best results were yielded by high calcium suppression with excellent inter-rater reliability (average sensitivity 0.91, specificity 0.88, cutoff -46.9 HU), followed by medium and low calcium suppression.

Conclusions: In contrast to MECT imaging, VNCa imaging in DECT appears to be feasible to assess metabolic activity of focal MM lesions as defined by the standard of reference, FDG PET/CT. Considering the higher cost and radiation exposure of FDG PET/CT, DECT VNCa imaging might develop to be the modality of choice to assess metabolic activity of focal MM lesions.
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http://dx.doi.org/10.1016/j.ejrad.2020.109502DOI Listing
February 2021

Calcification of the thoracic aorta on low-dose chest CT predicts severe COVID-19.

PLoS One 2020 23;15(12):e0244267. Epub 2020 Dec 23.

Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.

Background: Cardiovascular comorbidity anticipates poor prognosis of SARS-CoV-2 disease (COVID-19) and correlates with the systemic atherosclerotic transformation of the arterial vessels. The amount of aortic wall calcification (AWC) can be estimated on low-dose chest CT. We suggest quantification of AWC on the low-dose chest CT, which is initially performed for the diagnosis of COVID-19, to screen for patients at risk of severe COVID-19.

Methods: Seventy consecutive patients (46 in center 1, 24 in center 2) with parallel low-dose chest CT and positive RT-PCR for SARS-CoV-2 were included in our multi-center, multi-vendor study. The outcome was rated moderate (no hospitalization, hospitalization) and severe (ICU, tracheal intubation, death), the latter implying a requirement for intensive care treatment. The amount of AWC was quantified with the CT vendor's software.

Results: Of 70 included patients, 38 developed a moderate, and 32 a severe COVID-19. The average volume of AWC was significantly higher throughout the subgroup with severe COVID-19, when compared to moderate cases (771.7 mm3 (Q1 = 49.8 mm3, Q3 = 3065.5 mm3) vs. 0 mm3 (Q1 = 0 mm3, Q3 = 57.3 mm3)). Within multivariate regression analysis, including AWC, patient age and sex, as well as a cardiovascular comorbidity score, the volume of AWC was the only significant regressor for severe COVID-19 (p = 0.004). For AWC > 3000 mm3, the logistic regression predicts risk for a severe progression of 0.78. If there are no visually detectable AWC risk for severe progression is 0.13, only.

Conclusion: AWC seems to be an independent biomarker for the prediction of severe progression and intensive care treatment of COVID-19 already at the time of patient admission to the hospital; verification in a larger multi-center, multi-vendor study is desired.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244267PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7757863PMC
January 2021

Clinical application of free-breathing 3D whole heart late gadolinium enhancement cardiovascular magnetic resonance with high isotropic spatial resolution using Compressed SENSE.

J Cardiovasc Magn Reson 2020 12 17;22(1):89. Epub 2020 Dec 17.

Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany.

Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) represents the gold standard for assessment of myocardial viability. The purpose of this study was to investigate the clinical potential of Compressed SENSE (factor 5) accelerated free-breathing three-dimensional (3D) whole heart LGE with high isotropic spatial resolution (1.4 mm acquired voxel size) compared to standard breath-hold LGE imaging.

Methods: This was a retrospective, single-center study of 70 consecutive patients (45.8 ± 18.1 years, 27 females; February-November 2019), who were referred for assessment of left ventricular myocardial viability and received free-breathing and breath-hold LGE sequences at 1.5 T in clinical routine. Two radiologists independently evaluated global and segmental LGE in terms of localization and transmural extent. Readers scored scans regarding image quality (IQ), artifacts, and diagnostic confidence (DC) using 5-point scales (1 non-diagnostic-5 excellent/none). Effects of heart rate and body mass index (BMI) on IQ, artifacts, and DC were evaluated with ordinal logistic regression analysis.

Results: Global LGE (n = 33) was identical for both techniques. Using free-breathing LGE (average scan time: 04:33 ± 01:17 min), readers detected more hyperenhanced lesions (28.2% vs. 23.5%, P < .05) compared to breath-hold LGE (05:15 ± 01:23 min, P = .0104), pronounced at subepicardial localization and for 1-50% of transmural extent. For free-breathing LGE, readers graded scans with good/excellent IQ in 80.0%, with low-impact/no artifacts in 78.6%, and with good/high DC in 82.1% of cases. Elevated BMI was associated with increased artifacts (P = .0012) and decreased IQ (P = .0237). Increased heart rate negatively influenced artifacts (P = .0013) and DC (P = .0479) whereas IQ (P = .3025) was unimpaired.

Conclusions: In a clinical setting, free-breathing Compressed SENSE accelerated 3D high isotropic spatial resolution whole heart LGE provides good to excellent image quality in 80% of scans independent of heart rate while enabling improved depiction of small and particularly non-ischemic hyperenhanced lesions in a shorter scan time than standard breath-hold LGE.
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http://dx.doi.org/10.1186/s12968-020-00673-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7745391PMC
December 2020

Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning.

Sci Rep 2020 12 11;10(1):21799. Epub 2020 Dec 11.

Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.

In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subsequent treatment to prevent rebleeding. However, aneurysm detection proves to be challenging and time-consuming. The purpose of this study was to develop and evaluate a deep learning model (DLM) to automatically detect and segment aneurysms in patients with aSAH on computed tomography angiography. In this retrospective single-center study, three different DLMs were trained on 68 patients with 79 aneurysms treated for aSAH (2016-2017) using five-fold-cross-validation. Their outputs were combined to a single DLM via ensemble-learning. The DLM was evaluated on an independent test set consisting of 185 patients with 215 aneurysms (2010-2015). Independent manual segmentations of aneurysms in a 3D voxel-wise manner by two readers (neurosurgeon, radiologist) provided the reference standard. For aneurysms > 30 mm (mean diameter of ~ 4 mm) on the test set, the DLM provided a detection sensitivity of 87% with false positives (FPs)/scan of 0.42. Automatic segmentations achieved a median dice similarity coefficient (DSC) of 0.80 compared to the reference standard. Aneurysm location (anterior vs. posterior circulation; P = .07) and bleeding severity (Fisher grade ≤ 3 vs. 4; P = .33) did not impede detection sensitivity or segmentation performance. For aneurysms > 100 mm (mean diameter of ~ 6 mm), a sensitivity of 96% with DSC of 0.87 and FPs/scan of 0.14 were obtained. In the present study, we demonstrate that the proposed DLM detects and segments aneurysms > 30 mm in patients with aSAH with high sensitivity independent of cerebral circulation and bleeding severity while producing FP findings of less than one per scan. Hence, the DLM can potentially assist treating physicians in aSAH by providing automated detection and segmentations of aneurysms.
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http://dx.doi.org/10.1038/s41598-020-78384-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733480PMC
December 2020

Value of spectral detector CT for pretherapeutic, locoregional assessment of esophageal cancer.

Eur J Radiol 2021 Jan 21;134:109423. Epub 2020 Nov 21.

University Cologne, Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Kerpener Straße 62, 50937, Cologne, Germany; Department of Radiology, Division of Abdominal Imaging and Intervention, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, White 270, Boston, MA, 02114, USA. Electronic address:

Purpose: To investigate the diagnostic value of spectral detector dual-energy CT-derived low-keV virtual monoenergetic images (VMI) and iodine overlays (IO) for locoregional, pretherapeutic assessment of esophageal cancer.

Method: 74 patients with biopsy-proven esophageal cancer who underwent pre-therapeutic, portal-venous-phase staging examinations of the chest and abdomen were retrospectively included. Quantitative image analysis was performed ROI-based within the tumor, healthy esophageal wall, peri-esophageal lymph nodes, azygos vein, aorta, liver, diaphragm, and mediastinal fat. Two radiologists evaluated delineation of the primary tumor and locoregional lymph nodes, assessment of the celiac trunk and diagnostic certainty regarding tumor infiltration in conventional images (CI), VMI from 40 to 70 keV and IO. Moreover, presence/absence of advanced tumor infiltration (T3/T4) was determined binary using all available images.

Results: VMI showed significantly higher attenuation and signal-to-noise ratio compared to CI for all assessed ROIs, peaking at VMI (p < 0.05). Contrast-to-noise ratio of tumor/esophagus (VMI/CI: 7.7 ± 4.7 vs. 2.3 ± 1.5), tumor/diaphragm (VMI/CI: 9.0 ± 5.5 vs. 2.2 ± 1.7) and tumor/liver (4.3 ± 5.5 vs. 1.9 ± 2.1) were all significantly higher compared to CI (p < 0.05). Qualitatively, lymph node delineation and diagnostic certainty regarding tumor infiltration received highest ratings both in IO and VMI, whereas vascular assessment was rated highest in VMI and primary tumor delineation in IO. Sensitivity/Specificity/Accuracy for detecting advanced tumor infiltration using the combination of CI, VMI and IO was 42.4 %/82.0 %/56.3 %.

Conclusions: IO and VMI improve qualitative assessment of the primary tumor and depiction of lymph nodes and vessels at pretherapeutic SDCT of esophageal cancer patients yet do not mitigate the limitations of CT in determining tumor infiltration.
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http://dx.doi.org/10.1016/j.ejrad.2020.109423DOI Listing
January 2021

Early extrapulmonary prognostic features in chest computed tomography in COVID-19 pneumonia: Bone mineral density is a relevant predictor for the clinical outcome - A multicenter feasibility study.

Bone 2021 03 7;144:115790. Epub 2020 Dec 7.

Institute of Diagnostic and Interventional Radiology, University Hospital of Cologne, Germany. Electronic address:

Background: Besides throat-nose swab polymerase chain reaction (PCR), unenhanced chest computed tomography (CT) is a recommended diagnostic tool for early detection and quantification of pulmonary changes in COVID-19 pneumonia caused by the novel corona virus. Demographic factors, especially age and comorbidities, are major determinants of the outcome in COVID-19 infection. This study examines the extra pulmonary parameter of bone mineral density (BMD) from an initial chest computed tomography as an associated variable of pre-existing comorbidities like chronic lung disease or demographic factors to determine the later patient's outcome, in particular whether treatment on an intensive care unit (ICU) was necessary in infected patients.

Methods: We analyzed 58 PCR-confirmed COVID-19 infections that received an unenhanced CT at admission at one of the included centers. In addition to the extent of pulmonary involvement, we performed a phantomless assessment of bone mineral density of thoracic vertebra 9-12.

Results: In a univariate regression analysis BMD was found to be a significant predictor of the necessity for intensive care unit treatment of COVID-19 patients. In the subgroup requiring intensive care treatment within the follow-up period a significantly lower BMD was found. In a multivariate logistic regression model considering gender, age and CT measurements of bone mineral density, BMD was eliminated from the regression analysis as a significant predictor.

Conclusion: Phantomless assessed BMD provides prognostic information on the necessity for ICU treatment in course of COVID-19 pneumonia. We recommend using the measurement of BMD in an initial CT image to facilitate a potentially better prediction of severe patient outcomes within the 22 days after an initial CT scan. Consequently, in the present sample, additional bone density analysis did not result in a prognostic advantage over simply considering age. Significantly larger patient cohorts with a more homogenous patient age should be performed in the future to illustrate potential effects.

Clinical Relevance: While clinical capacities such as ICU beds and ventilators are more crucial than ever to help manage the current global corona pandemic, this work introduces an approach that can be used in a cost-effective way to help determine the amount of these rare clinical resources required in the near future.
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http://dx.doi.org/10.1016/j.bone.2020.115790DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720732PMC
March 2021

Quantitative accuracy of virtual non-contrast images derived from spectral detector computed tomography: an abdominal phantom study.

Sci Rep 2020 12 9;10(1):21575. Epub 2020 Dec 9.

Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Strasse 62, 50937, Cologne, Germany.

Dual-energy CT allows for the reconstruction of virtual non-contrast (VNC) images. VNC images have the potential to replace true non-contrast scans in various clinical applications. This study investigated the quantitative accuracy of VNC attenuation images considering different parameters for acquisition and reconstruction. An abdomen phantom with 7 different tissue types (different combinations of 3 base materials and 5 iodine concentrations) was scanned using a spectral detector CT (SDCT). Different phantom sizes (S, M, L), volume computed tomography dose indices (CTDIvol 10, 15, 20 mGy), kernel settings (soft, standard, sharp), and denoising levels (low, medium, high) were tested. Conventional and VNC images were reconstructed and analyzed based on regions of interest (ROI). Mean and standard deviation were recorded and differences in attenuation between corresponding base materials and VNC was calculated (VNCerror). Statistic analysis included ANOVA, Wilcoxon test and multivariate regression analysis. Overall, the VNC was - 1.4 ± 6.1 HU. While radiation dose, kernel setting, and denoising level did not influence VNC significantly, phantom size, iodine content and base material had a significant effect (e.g. S vs. M: - 1.2 ± 4.9 HU vs. - 2.1 ± 6.0 HU; 0.0 mg/ml vs. 5.0 mg/ml: - 4.0 ± 3.5 HU vs. 5.1 ± 5.0 HU and 35-HU-base vs. 54-HU-base: - 3.5 ± 4.4 HU vs. 0.7 ± 6.5; all p ≤ 0.05). The overall accuracy of VNC images from SDCT is high and independent from dose, kernel, and denoising settings; however, shows a dependency on patient size, base material, and iodine content; particularly the latter results in small, yet, noticeable differences in VNC attenuation.
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http://dx.doi.org/10.1038/s41598-020-78518-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725817PMC
December 2020

A Multicentric Comparison of Apparent Diffusion Coefficient Mapping and the Kaiser Score in the Assessment of Breast Lesions.

Invest Radiol 2021 May;56(5):274-282

Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.

Materials And Methods: In this multicentric study, individual patient data from 3 different centers were analyzed. Consecutive patients receiving standardized multiparametric breast magnetic resonance imaging for standard nonscreening indications were included. At each center, 2 experienced radiologists with more than 5 years of experience retrospectively interpreted the examinations in consensus and applied the KS to every histologically verified lesion. The corresponding mean ADC of each lesion was measured using a Wielema type 4 region of interest. According to established methods, the KS and ADC were combined, yielding the KS+ score. Diagnostic accuracy was evaluated by the area under the receiver operating characteristics curve (AUROC) and compared between the KS, ADC, and KS+ (DeLong test). Likewise, the potential to help avoid unnecessary biopsies was compared between the KS, ADC, and KS+ based on established high sensitivity thresholds (McNemar test).

Results: A total of 450 lesions in 414 patients (mean age, 51.5 years; interquartile range, 42-60.8 years) were included, with 219 lesions being malignant (48.7%; 95% confidence interval [CI], 44%-53.4%). The performance of the KS (AUROC, 0.915; CI, 0.886-0.939) was significantly better than that of the ADC (AUROC, 0.848; CI, 0.811-0.880; P < 0.001). The largest difference between these parameters was observed when assessing subcentimeter lesions (AUROC, 0.909 for KS; CI, 0.849-0.950 vs 0.811 for ADC; CI, 0.737-0.871; P = 0.02).The use of the KS+ (AUROC, 0.918; CI, 0.889-0.942) improved the performance slightly, but without any significant difference relative to a single KS or ADC reading (P = 0.64).When applying high sensitivity thresholds for avoiding unnecessary biopsies, the KS and ADC achieved equal sensitivity (97.7% for both; cutoff values, >4 for KS and ≤1.4 × 10-3 mm2/s for ADC). However, the rate of potentially avoidable biopsies was higher when using the KS (specificity: 65.4% for KS vs 32.9% for ADC; P < 0.0001). The KS was superior to the KS+ in avoiding unnecessary biopsies.

Conclusions: Both the KS and ADC may be used to distinguish benign from malignant breast lesions. However, KS proved superior in this task including, most of all, when assessing small lesions less than 1 cm. Using the KS may avoid twice as many unnecessary biopsies, and the combination of both the KS and ADS does not improve diagnostic performance.
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http://dx.doi.org/10.1097/RLI.0000000000000739DOI Listing
May 2021

Quantitative distribution of iodinated contrast media in body computed tomography: data from a large reference cohort.

Eur Radiol 2021 Apr 30;31(4):2340-2348. Epub 2020 Sep 30.

University Cologne, Faculty of Medicine and University Hospital Cologne, Department of Diagnostic and Interventional Radiology, Cologne, Germany.

Objectives: Dual-energy computed tomography allows for an accurate and reliable quantification of iodine. However, data on physiological distribution of iodine concentration (IC) is still sparse. This study aims to establish guidance for IC in abdominal organs and important anatomical landmarks using a large cohort of individuals without radiological tumor burden.

Methods: Five hundred seventy-one oncologic, portal venous phase dual-layer spectral detector CT studies of the chest and abdomen without tumor burden at time point of imaging confirmed by > 3-month follow-up were included. ROI were placed in parenchymatous organs (n = 25), lymph nodes (n = 6), and vessels (n = 3) with a minimum of two measurements per landmark. ROI were placed on conventional images and pasted to iodine maps to retrieve absolute IC. Normalization to the abdominal aorta was conducted to obtain iodine perfusion ratios. Bivariate regression analysis, t tests, and ANOVA with Tukey-Kramer post hoc test were used for statistical analysis.

Results: Absolute IC showed a broad scatter and varied with body mass index, between different age groups and between the sexes in parenchymatous organs, lymph nodes, and vessels (range 0.0 ± 0.0 mg/ml-6.6 ± 1.3 mg/ml). Unlike absolute IC, iodine perfusion ratios did not show dependency on body mass index; however, significant differences between the sexes and age groups persisted, showing a tendency towards decreased perfusion ratios in elderly patients (e.g., liver 18-44 years/≥ 64 years: 0.50 ± 0.11/0.43 ± 0.10, p ≤ 0.05).

Conclusions: Distribution of IC obtained from a large-scale cohort is provided. As significant differences between sexes and age groups were found, this should be taken into account when obtaining quantitative iodine concentrations and applying iodine thresholds.

Key Points: • Absolute iodine concentration showed a broad variation and differed between body mass index, age groups, and between the sexes in parenchymatous organs, lymph nodes, and vessels. • The iodine perfusion ratios did not show dependency on body mass index while significant differences between sexes and age groups persisted. • Provided guidance values may serve as reference when aiming to differentiate healthy and abnormal tissue based on iodine perfusion ratios.
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http://dx.doi.org/10.1007/s00330-020-07298-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7979665PMC
April 2021

Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network.

Eur Radiol 2021 Apr 28;31(4):1812-1818. Epub 2020 Sep 28.

Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.

Objectives: The goal of the present study was to classify the most common types of plain radiographs using a neural network and to validate the network's performance on internal and external data. Such a network could help improve various radiological workflows.

Methods: All radiographs from the year 2017 (n = 71,274) acquired at our institution were retrieved from the PACS. The 30 largest categories (n = 58,219, 81.7% of all radiographs performed in 2017) were used to develop and validate a neural network (MobileNet v1.0) using transfer learning. Image categories were extracted from DICOM metadata (study and image description) and mapped to the WHO manual of diagnostic imaging. As an independent, external validation set, we used images from other institutions that had been stored in our PACS (n = 5324).

Results: In the internal validation, the overall accuracy of the model was 90.3% (95%CI: 89.2-91.3%), whereas, for the external validation set, the overall accuracy was 94.0% (95%CI: 93.3-94.6%).

Conclusions: Using data from one single institution, we were able to classify the most common categories of radiographs with a neural network. The network showed good generalizability on the external validation set and could be used to automatically organize a PACS, preselect radiographs so that they can be routed to more specialized networks for abnormality detection or help with other parts of the radiological workflow (e.g., automated hanging protocols; check if ordered image and performed image are the same). The final AI algorithm is publicly available for evaluation and extension.

Key Points: • Data from one single institution can be used to train a neural network for the correct detection of the 30 most common categories of plain radiographs. • The trained model achieved a high accuracy for the majority of categories and showed good generalizability to images from other institutions. • The neural network is made publicly available and can be used to automatically organize a PACS or to preselect radiographs so that they can be routed to more specialized neural networks for abnormality detection.
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http://dx.doi.org/10.1007/s00330-020-07241-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7979627PMC
April 2021
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