Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease.

Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium. Objectives: To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with ⩾10 pack-years of smoking history. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume, and mean transit time were assessed on contrast-enhanced magnetic resonance imaging, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with pulmonary microvascular blood volume measures on contrast-enhanced dual-energy computed tomography. Differential expression analyses were adjusted for age, gender, race/ethnicity, educational attainment, height, weight, smoking status, and pack-years of smoking. Results: The 79 participants in the discovery sample had a mean age of 69 ± 6 years, 44% were female, 25% were non-White, 34% were current smokers, and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with magnetic resonance imaging (n = 47) or dual-energy contrast-enhanced computed tomography (n = 157) measures. Many of the identified genes are involved in inflammatory processes, including nuclear factor-κB and chemokine signaling pathways. Conclusions: PBMC gene expression in nuclear factor-κB, inflammatory, and chemokine signaling pathways was associated with pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.

Convolutional Neural Network for Fully Automated Cerebellar Volumetry in Children in Comparison to Manual Segmentation and Developmental Trajectory of Cerebellar Volumes.

The purpose of this study was to develop a fully automated and reliable volumetry of the cerebellum of children during infancy and childhood using deep learning algorithms in comparison to manual segmentation. In addition, the clinical usefulness of measuring the cerebellar volume is shown. One hundred patients (0 to 16.3 years old) without infratentorial signal abnormalities on conventional MRI were retrospectively selected from our pool of pediatric MRI examinations. Based on a routinely acquired 3D T1-weighted magnetization prepared rapid gradient echo (MPRAGE) sequence, the cerebella were manually segmented using ITK-SNAP. The data set of all 100 cases was divided into four splits (four-fold cross-validation) to train the network (NN) to delineate the boundaries of the cerebellum. First, the accuracy of the newly created neural network was compared with the manual segmentation. Secondly, age-related volume changes were investigated. Our trained NN achieved an excellent Spearman correlation coefficient of 0.99, a Dice Coefficient of 95.0 ± 2.1%, and an intersection over union (IoU) of 90.6 ± 3.8%. Cerebellar volume increased continuously with age, showing an exponentially rapid growth within the first year of life. Using a convolutional neural network, it was possible to achieve reliable, fully automated cerebellar volume measurements in childhood and infancy, even when based on a relatively small cohort. In this preliminary study, age-dependent cerebellar volume changes could be acquired.

Regional Pulmonary Morphology and Function: Photon-counting CT Assessment.

Background Experience with functional CT in the lungs without additional equipment in clinical routine is limited. Purpose To report initial experience and evaluate the robustness of a modified chest CT protocol and photon-counting CT (PCCT) for comprehensive analysis of pulmonary vasculature, perfusion, ventilation, and morphologic structure in a single examination. Materials and Methods In this retrospective study, consecutive patients with clinically indicated CT for various known and unknown pulmonary function impairment (six subgroups) were included between November 2021 and June 2022. After administration of an intravenous contrast agent, inspiratory PCCT was followed by expiratory PCCT after a delay of 5 minutes. Advanced automated postprocessing was performed, and CT-derived functional parameters were calculated (regional ventilation, perfusion, late contrast enhancement, and CT angiography). Mean intravascular contrast enhancement in the mediastinal vessels and radiation dose were determined. Using analysis of variance, the mean values of lung volumes, attenuation, ventilation, perfusion, and late contrast enhancement were tested for differences between subgroups of patients. Results In 166 patients (mean age, 63.2 years ± 14.2 [SD]; 106 male patients), all CT-derived parameters could be acquired (84.7% success rate; 166 of 196 patients). At the inspiratory examination, mean density was 325 HU in the pulmonary trunk, 260 HU in the left atrium, and 252 HU in the ascending aorta. The mean dose-length product for inspiration and expiration was 110.32 mGy · cm and 109.47 mGy · cm, respectively; the mean CT dose index for inspiration and expiration was 3.22 mGy and 3.09 mGy, respectively (less than the mean total radiation dose of 8-12 mGy, which is diagnostic reference level). Significant differences (P < .05) between the subgroups were found for all assessed parameters. Visual inspection allowed for voxelwise assessment of morphologic structure and function. Conclusion The proposed PCCT protocol allowed for a dose-efficient and robust simultaneous evaluation of pulmonary morphologic structure, ventilation, vasculature, and parenchymal perfusion in a procedure requiring advanced software but no additional hardware. © RSNA, 2023.

Automated Classification of Free-Text Radiology Reports: Using Different Feature Extraction Methods to Identify Fractures of the Distal Fibula.

PURPOSE: Radiology reports mostly contain free-text, which makes it challenging to obtain structured data. Natural language processing (NLP) techniques transform free-text reports into machine-readable document vectors that are important for creating reliable, scalable methods for data analysis. The aim of this study is to classify unstructured radiograph reports according to fractures of the distal fibula and to find the best text mining method. MATERIALS & METHODS: We established a novel German language report dataset: a designated search engine was used to identify radiographs of the ankle and the reports were manually labeled according to fractures of the distal fibula. This data was used to establish a machine learning pipeline, which implemented the text representation methods bag-of-words (BOW), term frequency-inverse document frequency (TF-IDF), principal component analysis (PCA), non-negative matrix factorization (NMF), latent Dirichlet allocation (LDA), and document embedding (doc2vec). The extracted document vectors were used to train neural networks (NN), support vector machines (SVM), and logistic regression (LR) to recognize distal fibula fractures. The results were compared via cross-tabulations of the accuracy (acc) and area under the curve (AUC). RESULTS: In total, 3268 radiograph reports were included, of which 1076 described a fracture of the distal fibula. Comparison of the text representation methods showed that BOW achieved the best results (AUC = 0.98; acc = 0.97), followed by TF-IDF (AUC = 0.97; acc = 0.96), NMF (AUC = 0.93; acc = 0.92), PCA (AUC = 0.92; acc = 0.9), LDA (AUC = 0.91; acc = 0.89) and doc2vec (AUC = 0.9; acc = 0.88). When comparing the different classifiers, NN (AUC = 0,91) proved to be superior to SVM (AUC = 0,87) and LR (AUC = 0,85). CONCLUSION: An automated classification of unstructured reports of radiographs of the ankle can reliably detect findings of fractures of the distal fibula. A particularly suitable feature extraction method is the BOW model. KEY POINTS: · The aim was to classify unstructured radiograph reports according to distal fibula fractures.. · Our automated classification system can reliably detect fractures of the distal fibula.. · A particularly suitable feature extraction method is the BOW model.. CITATION FORMAT: · Dewald CL, Balandis A, Becker LS et al. Automated Classification of Free-Text Radiology Reports: Using Different Feature Extraction Methods to Identify Fractures of the Distal Fibula. Fortschr Röntgenstr 2023; 195: 713 - 719.

Evaluation of tissue shrinkage after CT-guided microwave ablation in patients with liver malignancies using Jacobian determinant.

PURPOSE: To assess short-term tissue shrinkage in patients with liver malignancies undergoing computed tomography (CT)-guided microwave ablation (MWA) using Jacobian determinant (JD). MATERIALS AND METHODS: Twenty-nine patients with 29 hepatic malignancies (primary n = 24; metastases n = 5; median tumor diameter 18 mm) referred to CT-guided MWA (single position; 10 min, 100 W) were included in this retrospective IRB-approved study, after exclusion of five patients. Following segmentation of livers and tumors on pre-interventional images, segmentations were registered on post-interventional images. JD mapping was applied to quantify voxelwise tissue volume changes after MWA. Percentual volume changes were evaluated in the ablated tumor, a 5-cm tumor perimeter and in the whole liver and compared in different clinical conditions (tumor entity: primary vs. secondary; tumor location: subcapsular vs. non-subcapsular; tumor volume: >/<6 ml: cirrhosis: yes vs. no; prior chemotherapy: yes vs. no using Shapiro-Wilk, χ2 and Wilcoxon rank sum tests, respectively (with p < 0.05 deemed significant). RESULTS: Tissue volume change was 0.6% in the ablated tumor, 1.6% in the 5-cm perimeter and 0.3% in the whole liver. Shrinkage in the ablated tumor was pronounced in non-subcapsular located tumors, whereas tissue expansion was noted in subcapsular tumors (median -3.5 vs. 1.1%; p = 0.0195). Shrinkage in the whole liver was higher in tumor volumes >6ml, compared with smaller tumors, in which tissue expansion was noted (median -1.0 vs. 2.5%; p = 0.002). Other clinical conditions had no significant influence on the extent of tissue shrinkage (p > 0.05). CONCLUSION: 3D Jacobian analysis shows that hepatic tissue deformation following MWA is most pronounced in a 5-cm area surrounding the treated tumor. Tumor location and tumor volume may have an impact on the extent of tissue shrinkage which may affect estimation of the safety margin.

In Vivo Comparison of Synthetic Macroporous Filamentous and Sponge-like Skin Substitute Matrices Reveals Morphometric Features of the Foreign Body Reaction According to 3D Biomaterial Designs.

Synthetic macroporous biomaterials are widely used in the field of skin tissue engineering to mimic membrane functions of the native dermis. Biomaterial designs can be subclassified with respect to their shape in fibrous designs, namely fibers, meshes or fleeces, respectively, and porous designs, such as sponges and foams. However, synthetic matrices often have limitations regarding unfavorable foreign body responses (FBRs). Severe FBRs can result in unfavorable disintegration and rejection of an implant, whereas mild FBRs can lead to an acceptable integration of a biomaterial. In this context, comparative in vivo studies of different three-dimensional (3D) matrix designs are rare. Especially, the differences regarding FBRs between synthetically derived filamentous fleeces and sponge-like constructs are unknown. In the present study, the FBRs on two 3D matrix designs were explored after 25 days of subcutaneous implantation in a porcine model. Cellular reactions were quantified histopathologically to investigate in which way the FBR is influenced by the biomaterial architecture. Our results show that FBR metrics (polymorph-nucleated cells and fibrotic reactions) were significantly affected according to the matrix designs. Our findings contribute to a better understanding of the 3D matrix tissue interactions and can be useful for future developments of synthetically derived skin substitute biomaterials.

Application of A U-Net for Map-like Segmentation and Classification of Discontinuous Fibrosis Distribution in Gd-EOB-DTPA-Enhanced Liver MRI.

We aimed to evaluate whether U-shaped convolutional neuronal networks can be used to segment liver parenchyma and indicate the degree of liver fibrosis/cirrhosis at the voxel level using contrast-enhanced magnetic resonance imaging. This retrospective study included 112 examinations with histologically determined liver fibrosis/cirrhosis grade (Ishak score) as the ground truth. The T1-weighted volume-interpolated breath-hold examination sequences of native, arterial, late arterial, portal venous, and hepatobiliary phases were semi-automatically segmented and co-registered. The segmentations were assigned the corresponding Ishak score. In a nested cross-validation procedure, five models of a convolutional neural network with U-Net architecture (nnU-Net) were trained, with the dataset being divided into stratified training/validation (n = 89/90) and holdout test datasets (n = 23/22). The trained models precisely segmented the test data (mean dice similarity coefficient = 0.938) and assigned separate fibrosis scores to each voxel, allowing localization-dependent determination of the degree of fibrosis. The per voxel results were evaluated by the histologically determined fibrosis score. The micro-average area under the receiver operating characteristic curve of this seven-class classification problem (Ishak score 0 to 6) was 0.752 for the test data. The top-three-accuracy-score was 0.750. We conclude that determining fibrosis grade or cirrhosis based on multiphase Gd-EOB-DTPA-enhanced liver MRI seems feasible using a 2D U-Net. Prospective studies with localized biopsies are needed to evaluate the reliability of this model in a clinical setting.

Semiautomated quantification of the fibrous tissue response to complex three-dimensional filamentous scaffolds using digital image analysis.

Fibrosis represents a relevant response to the implantation of biomaterials, which occurs not only at the tissue-material interface (fibrotic encapsulation) but also within the void fraction of complex three-dimensional (3D) biomaterial constructions (fibrotic ingrowth). Usual evaluation of the biocompatibility mostly depicts fibrosis at the interface of the biomaterial using semiquantitative scores. Here, the relations between encapsulation and infiltrating fibrotic growth are poorly represented. Virtual pathology and digital image analysis provide new strategies to assess fibrosis in a more differentiated way. In this study, we adopted a method previously used to quantify fibrosis in visceral organs to the quantification of fibrosis to 3D biomaterials. In a proof-of-concept study, we transferred the "Collagen Proportionate Area" (CPA) analysis from hepatology to the field of biomaterials. As one task of an experimental animal study, we used CPA analysis to quantify the fibrotic ingrowth into a filamentous scaffold after subcutaneous implantation. We were able to demonstrate that the application of the CPA analysis is well suited as an additional fibrosis evaluation strategy for new biomaterial constructions. The CPA method can contribute to a better understanding of the fibrotic interactions between 3D scaffolds and the host tissue responses.

Comparison of dual-energy computer tomography and dynamic contrast-enhanced MRI for evaluating lung perfusion defects in chronic thromboembolic pulmonary hypertension.

OBJECTIVES: To evaluate the agreement in detecting pulmonary perfusion defects in patients with chronic thromboembolic pulmonary hypertension using dual-energy CT and dynamic contrast-enhanced MRI. Second, to compare both imaging modalities in monitoring lung perfusion changes in these patients after undergoing pulmonary endarterectomy. METHODS: 20 patients were examined with CT and MRI before and/or after pulmonary endarterectomy. Estimated perfusion defect percentage from both modalities was compared in a lobe-based analysis. Spatial agreement of perfusion defect maps was also assessed. RESULTS: A significant correlation between CT and MRI based perfusion defect percentage was calculated in all lung lobes (r > 0.78; p < 0.001). In addition, a good spatial agreement between perfusion defect maps was found (mean spatial overlap for the whole lung was 68.2%; SD = 6.9). Both CT and MRI detected improvements in pulmonary perfusion after pulmonary endarterectomy: 8% and 7% decrease in whole lung perfusion defect percentage (p = 0.007 and 0.004), respectively. In a lobe-wise analysis, improvements were statistically significant only in lower lobes using both modalities (reduction in defect percentage ranged from 16-29%; p < 0.02). CONCLUSIONS: Dual-energy CT is an alternative to MRI in monitoring chronic thromboembolic pulmonary hypertension. Both imaging modalities provided comparable estimations of perfusion defects and could detect similar improvement in lung perfusion after pulmonary endarterectomy.

A 3D Deep Neural Network for Liver Volumetry in 3T Contrast-Enhanced MRI.

PURPOSE: To create a fully automated, reliable, and fast segmentation tool for Gd-EOB-DTPA-enhanced MRI scans using deep learning. MATERIALS AND METHODS: Datasets of Gd-EOB-DTPA-enhanced liver MR images of 100 patients were assembled. Ground truth segmentation of the hepatobiliary phase images was performed manually. Automatic image segmentation was achieved with a deep convolutional neural network. RESULTS: Our neural network achieves an intraclass correlation coefficient (ICC) of 0.987, a Sørensen-Dice coefficient of 96.7 ± 1.9 % (mean ±â€Šstd), an overlap of 92 ±â€Š3.5 %, and a Hausdorff distance of 24.9 ±â€Š14.7 mm compared with two expert readers who corresponded to an ICC of 0.973, a Sørensen-Dice coefficient of 95.2 ±â€Š2.8 %, and an overlap of 90.9 ±â€Š4.9 %. A second human reader achieved a Sørensen-Dice coefficient of 95 % on a subset of the test set. CONCLUSION: Our study introduces a fully automated liver volumetry scheme for Gd-EOB-DTPA-enhanced MR imaging. The neural network achieves competitive concordance with the ground truth regarding ICC, Sørensen-Dice, and overlap compared with manual segmentation. The neural network performs the task in just 60 seconds. KEY POINTS: · The proposed neural network helps to segment the liver accurately, providing detailed information about patient-specific liver anatomy and volume.. · With the help of a deep learning-based neural network, fully automatic segmentation of the liver on MRI scans can be performed in seconds.. · A fully automatic segmentation scheme makes liver segmentation on MRI a valuable tool for treatment planning.. CITATION FORMAT: · Winther H, Hundt C, Ringe KI et al. A 3D Deep Neural Network for Liver Volumetry in 3T Contrast-Enhanced MRI. Fortschr Röntgenstr 2021; 193: 305 - 314.

Fully automated detection of primary sclerosing cholangitis (PSC)-compatible bile duct changes based on 3D magnetic resonance cholangiopancreatography using machine learning.

OBJECTIVES: To develop and evaluate a deep learning algorithm for fully automated detection of primary sclerosing cholangitis (PSC)-compatible cholangiographic changes on three-dimensional magnetic resonance cholangiopancreatography (3D-MRCP) images. METHODS: The datasets of 428 patients (n = 205 with confirmed diagnosis of PSC; n = 223 non-PSC patients) referred for MRI including MRCP were included in this retrospective IRB-approved study. Datasets were randomly assigned to a training (n = 386) and a validation group (n = 42). For each case, 20 uniformly distributed axial MRCP rotations and a subsequent maximum intensity projection (MIP) were calculated, resulting in a training database of 7720 images and a validation database of 840 images. Then, a pre-trained Inception ResNet was implemented which was conclusively fine-tuned (learning rate 10-3). RESULTS: Applying an ensemble strategy (by binning of the 20 axial projections), the mean absolute error (MAE) of the developed deep learning algorithm for detection of PSC-compatible cholangiographic changes was lowered from 21 to 7.1%. Sensitivity, specificity, positive predictive (PPV), and negative predictive value (NPV) for detection of these changes were 95.0%, 90.9%, 90.5%, and 95.2% respectively. CONCLUSIONS: The results of this study demonstrate the feasibility of transfer learning in combination with extensive image augmentation to detect PSC-compatible cholangiographic changes on 3D-MRCP images with a high sensitivity and a low MAE. Further validation with more and multicentric data is now desirable, as it is known that neural networks tend to overfit the characteristics of the dataset. KEY POINTS: • The described machine learning algorithm is able to detect PSC-compatible cholangiographic changes on 3D-MRCP images with high accuracy. • The generation of 2D projections from 3D datasets enabled the implementation of an ensemble strategy to boost inference performance.

Perioperative CTEPH patient monitoring with 2D phase-contrast MRI reflects clinical, cardiac and pulmonary perfusion changes after pulmonary endarterectomy.

Magnetic resonance imaging (MRI) is an emerging tool for diagnosis and treatment monitoring of chronic thromboembolic pulmonary hypertension (CTEPH). The current study aims to identify central pulmonary arterial hemodynamic parameters that reflect clinical, cardiac and pulmonary changes after PEA. 31 CTEPH patients, who underwent PEA and received pre- and postoperative MRI, were analyzed retrospectively. Central pulmonary arterial blood flow, lung perfusion and right heart function data were derived from MRI. Mean pulmonary arterial pressure (mPAP) and 5-month follow-up six-minute walk-distance (6MWD) were assessed. After PEA, mPAP decreased significantly and patients achieved a higher 6MWD. Central pulmonary arterial blood flow velocities, pulmonary blood flow (PBF) and right ventricular function increased significantly. Two-dimensional (2D) phase-contrast (PC) MRI-derived average mean velocity, maximum mean velocity and deceleration volume changes after PEA correlated with changes of 6MWD and right heart ejection fraction (RVEF). Deceleration volume is a novel 2D PC MRI parameter showing further correlation with PBF changes. In conclusion, 2D PC MRI-derived main pulmonary hemodynamic changes reflect changes of RVEF, PBF and 5-month follow-up 6MWD and may be used for future CTEPH patient monitoring after PEA.

Work and Training Conditions of German Residents in Radiology - Results from a Nationwide Survey Conducted by the Young Radiology Forum in the German Roentgen Society. / Arbeits- und Weiterbildungsbedingungen in der Facharztweiterbildung Radiologie ­ Ergebnisse einer bundesweiten Weiterbildungsumfrage durch das Forum Junge Radiologie in der Deutschen Röntgengesellschaft.

PURPOSE: Good training is the basis for high job satisfaction and high-quality patient care in radiology. The aim of this survey was to record the current state of working conditions for residents in radiology training in Germany and to focus on the aspects of training and psychosocial workload. The description of the actual state should help to identify possible problem areas and to develop improvement approaches. MATERIALS AND METHODS: At the beginning of 2018, we sent an electronic questionnaire to the German Roentgen Society (DRG), the German Association of Chairmen in Academic Radiology (KLR), the Chief Physician Forum of the DRG (CAFRAD) and the Forum of Registered Radiologists (FUNRAD) with the request to forward it to radiology residents. With 63 questions, the questionnaire covered seven essential areas of medical working and training conditions. In order to ensure interdisciplinary comparability, most questions were identical to previous surveys among residents of other disciplines. RESULTS: 643 residents started the survey. 501 (78 %) questionnaires were fully processed and included in the final analysis. 65 % of respondents were satisfied with their current job situation. At the same time, shortcomings, especially with regard to the reconciliation of family and work as well as scientific and clinical work, became clear. Only 36 % of participants with children were satisfied with the compatibility of family and work at their workplace. Only 31 % of the researchers were satisfied with their research conditions. In addition, residents experienced a high psychosocial workload. CONCLUSION: Job satisfaction is high among radiology residents in direct comparison to other disciplines. However, based on this survey, adjustments to working conditions and training in radiology seem necessary to maintain the health of the physicians concerned, to encourage motivation for scientific work and to enhance development opportunities, especially for women, through a better compatibility of work and family life. The present survey identifies strategies and leadership tools that can help to achieve this. KEY POINTS: Residents in radiology training ... · have a relatively high job satisfaction.. · experience a high psychosocial workload.. · evaluate the compatibility of family and work as in need of improvement.. · are interested in research, but evaluate research conditions as insufficient. CITATION FORMAT: · Oechtering TH, Panagiotopoulos N, Völker M et al. Work and Training Conditions of German Residents in Radiology - Results from a Nationwide Survey Conducted by the Young Radiology Forum in the German Roentgen Society. Fortschr Röntgenstr 2020; 192: 458 - 469.

Deep semantic lung segmentation for tracking potential pulmonary perfusion biomarkers in chronic obstructive pulmonary disease (COPD): The multi-ethnic study of atherosclerosis COPD study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is associated with high morbidity and mortality. Identification of imaging biomarkers for phenotyping is necessary for future treatment and therapy monitoring. However, translation of visual analytic pipelines into clinics or their use in large-scale studies is significantly slowed by time-consuming postprocessing steps. PURPOSE: To implement an automated tool chain for regional quantification of pulmonary microvascular blood flow in order to reduce analysis time and user variability. STUDY TYPE: Prospective. POPULATION: In all, 90 MRI scans of 63 patients, of which 31 had a COPD with a mean Global Initiative for Chronic Obstructive Lung Disease status of 1.9 ± 0.64 (µ ± σ). FIELD STRENGTH/SEQUENCE: 1.5T dynamic gadolinium-enhanced MRI measurement using 4D dynamic contrast material-enhanced (DCE) time-resolved angiography acquired in a single breath-hold in inspiration. [Correction added on August 20, 2019, after first online publication: The field strength in the preceding sentence was corrected.] ASSESSMENT: We built a 3D convolutional neural network for semantic segmentation using 29 manually segmented perfusion maps. All five lobes of the lung are denoted, including the middle lobe. Evaluation was performed on 61 independent cases from two sites of the Multi-Ethnic Study of Arteriosclerosis (MESA)-COPD study. We publish our implementation of a model-free deconvolution filter according to Sourbron et al for 4D DCE MRI scans as open source. STATISTICAL TEST: Cross-validation 29/61 (# training / # testing), intraclass correlation coefficient (ICC), Spearman ρ, Pearson r, Sørensen-Dice coefficient, and overlap. RESULTS: Segmentations and derived clinical parameters were processed in ~90 seconds per case on a Xeon E5-2637v4 workstation with Tesla P40 GPUs. Clinical parameters and predicted segmentations exhibit high concordance with the ground truth regarding median perfusion for all lobes with an ICC of 0.99 and a Sørensen-Dice coefficient of 93.4 ± 2.8 (µ ± σ). DATA CONCLUSION: We present a robust end-to-end pipeline that allows for the extraction of perfusion-based biomarkers for all lung lobes in 4D DCE MRI scans by combining model-free deconvolution with deep learning. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:571-579.

Validation of Automated Perfusion-Weighted Phase-Resolved Functional Lung (PREFUL)-MRI in Patients With Pulmonary Diseases.

BACKGROUND: Perfusion-weighted (Qw) noncontrast-enhanced proton lung MRI is a promising technique for assessment of pulmonary perfusion, but still requires validation. PURPOSE: To improve perfusion-weighted phase-resolved functional lung (PREFUL)-MRI, to validate PREFUL with perfusion single photon emission computed tomography (SPECT) as a gold standard, and to compare PREFUL with dynamic contrast-enhanced (DCE)-MRI as a reference. STUDY TYPE: Retrospective. POPULATION: Twenty patients with chronic obstructive pulmonary disease (COPD), 14 patients with cystic fibrosis (CF), and 21 patients with chronic thromboembolic pulmonary hypertension (CTEPH) were included. FIELD STRENGTH/SEQUENCE: For PREFUL-MRI, a spoiled gradient echo sequence and for DCE-MRI a 3D time-resolved angiography with stochastic trajectories sequence were used at 1.5T. ASSESSMENT: PREFUL-MRI coronal slices were acquired in free-breathing. DCE-MRI was performed in breath-hold with injection of 0.03 mmol/kg bodyweight of gadoteric acid at a rate of 4 cc/s. Perfusion SPECT images were obtained for six CTEPH patients. Images were coregistered. An algorithm to define the appropriate PREFUL perfusion phase was developed using perfusion SPECT data. Perfusion defect percentages (QDP) and Qw-values were calculated for all methods. For PREFUL quantitative perfusion values (PREFULQ ) and for DCE pulmonary blood flow (PBF) was calculated. STATISTICAL TESTS: Obtained parameters were assessed using Pearson correlation and Bland-Altman analysis. RESULTS: Qw-SPECT correlated with Qw-DCE (r = 0.50, P < 0.01) and Qw-PREFUL (r = 0.47, P < 0.01). Spatial overlap of QDP maps showed an agreement ≥67.7% comparing SPECT and DCE, ≥64.1% for SPECT and PREFUL, and ≥60.2% comparing DCE and PREFUL. Significant correlations of Qw-PREFUL and Qw-DCE were found (COPD: r = 0.79, P < 0.01; CF: r = 0.77, P < 0.01; CTEPH: r = 0.73, P < 0.01). PREFULQ /PBF correlations were similar/lower (CF, CTEPH: P > 0.12; COPD: P < 0.01) compared to Qw-PREFUL/DCE correlations. PREFULQ -values were higher/similar compared to PBF-values (COPD, CF: P < 0.01; CTEPH: P = 0.026). DATA CONCLUSION: The automated PREFUL algorithm may allow for noncontrast-enhanced pulmonary perfusion assessment in COPD, CF, and CTEPH patients comparable to DCE-MRI. Level of Evidence 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2020;52:103-114.

Chemosaturation Percutaneous Hepatic Perfusion (CS-PHP) with Melphalan: Evaluation of 2D-Perfusion Angiography (2D-PA) for Leakage Detection of the Venous Double-Balloon Catheter.

PURPOSE: To evaluate the feasibility of 2D-perfusion angiography (2D-PA) for detecting leakage of the double-balloon catheter used for chemosaturation percutaneous hepatic perfusion (CS-PHP). MATERIALS AND METHODS: Overall, 112 CS-PHP (09/2015-09/2018) in 52 patients were retrospectively screened for leakage alongside the double-balloon catheter on standard venograms. Finally, 18 procedures with visually detected leakage were included. Fifteen consecutive procedures without leakage served as control. To evaluate 2D-PA for leakage detection, the acquired digital subtraction venograms were post-processed. For each balloon, two different target ROIs were evaluated to assess a possible impact of localization and shape of the ROIs. Time to peak (TTP), peak density (PD), area under the curve (AUC), and ratios of target ROI/reference ROIs (PDtROI/PDREF; AUCtROI/AUCREF; and TTPtROI/TTPREF) were calculated. RESULTS: Leakages were located as follows: 15/18 cranial and 3/18 caudal. At the cranial balloon both ROIs showed a significant decrease in PDtROI/PDREF and AUCtROI/AUCREF (ROI1: p < 0.0001; p < 0.0001; ROI2: p < 0.0001; p < 0.0001) and a significant increase in TTPtROI/TTPREF (ROI1: p = 0.0009; ROI2: p = 0.0003) after double-balloon correction. Following balloon adjustment, the 2D-PA ratios (PD and AUC) of the tested ROIs differed significantly (p < 0.05). The inter-individual comparison of the 2D-PA parameters of the group with leakage before balloon correction and the non-leakage group showed significantly different 2D-PA values for the cranial balloon in both ROIs (p < 0.05). No significant differences were found for the caudal balloon. CONCLUSION: 2D-PA provides a feasible tool for detecting leakages alongside the cranial portion of the double-balloon catheter used in CS-PHP. The shape and position of the ROIs used to assess perfusion and flow have an impact on the measurements.

C-Arm computed tomography (CACT)-guided balloon pulmonary angioplasty (BPA): Evaluation of patient safety and peri- and post-procedural complications.

AIM: To assess the frequency and severity of complications of balloon pulmonary angioplasty (BPA) using C-arm computed tomography (CACT) guidance. MATERIAL AND METHODS: 266 consecutive interventions in 67 patients (42 females, mean age 66 ± 13 years) were included. Selective CACT was acquired prior to the intervention for three-dimensional (3D) guidance and to select appropriate balloon size based on the measured vessel diameter. Complications during and after the procedure, the need for further interventions and the impact on patient safety and outcome were assessed and categorised according to the SIR Classification System to Complications by Outcome (Grade A-F). RESULTS: Overall, 237 interventions were conducted without any complications (89.1%). Minor complications not requiring additional treatment occurred during or after 25 procedures (9.4%), including recurring dry cough in four patients during a total of 11 interventions (4.1%) (Grade A), three focal dissections of the targeted pulmonary artery (1.1%), four cases of pulmonary haemorrhage (1.5%), one case of reperfusion oedema (0.4%) and six cases of post-interventional short-term hemoptysis (2.3%) (Grade B). Four cases of major complications requiring additional treatment were observed (1.5%): one case of pulmonary haemorrhage (0.4%) and two cases of post-interventional haemoptysis (0.8%), all resolved after medical therapy without requiring further intervention, and one case of atrial tachycardia induced during catheterisation, subsequently requiring pharmacological cardioversion (0.4%) (Grade C). No fatal or life-threatening peri- or post-interventional complications or mortality were observed (Grade D-F). CONCLUSION: BPA performed under CACT guidance appears to be a safe procedure with a low risk of severe complications. KEY POINTS: • CACT guidance of BPA is safe and successful. • CACT-guided BPA procedures have a low complication profile. • CACT guidance is a valuable tool to navigate BPA.

Breath-hold and free-breathing 2D phase-contrast MRI for quantification of oxygen-induced changes of pulmonary circulation dynamics in healthy volunteers.

PURPOSE: To evaluate the effect of inhaled 100% oxygen on pulmonary circulation dynamics in healthy volunteers using 2D phase-contrast magnetic resonance imaging (2D PC MRI). MATERIALS AND METHODS: Twenty-one healthy volunteers were examined at 1.5T. Through-plane 2D PC MRI measurements were performed in the main pulmonary artery during free-breathing and breath-hold. Acceleration time and volume, maximum and minimum area, area change, average and maximum mean velocity, forward volume, heart rate, as well as blood pressure were determined. At baseline, subjects breathed room air. After application of a closed-fit full face mask, three further measurements were conducted: at room air (control), directly after starting 15 L/min 100% oxygen (wash-in), and after 5 minutes during continuous oxygen supply (saturation). Data were analyzed with a mixed linear model. Skewed distributed variables were rank-transformed. Tukey contrasts with family-wise adjusted P-values were applied for pairwise comparisons. RESULTS: Inhaled oxygen affected several hemodynamic parameters. Average mean velocity (P < 0.01: breath-hold during wash-in and saturation, P = 0.03: free-breathing during saturation) and maximum mean velocity (P < 0.01: breath-hold and free-breathing during saturation) decreased. When obtained during free-breathing, acceleration volume (P = 0.02: saturation), area change (P = 0.02: saturation), and maximum area (P = 0.02: wash-in, P = 0.03: saturation) increased, while minimum area and forward volume did not change. CONCLUSION: Oxygen alters pulmonary circulation dynamics in the main pulmonary artery of healthy volunteers, which can be reliably detected using 2D phase-contrast MRI. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1698-1706.

A virtual microscope for academic medical education: the pate project.

BACKGROUND: Whole-slide imaging (WSI) has become more prominent and continues to gain in importance in student teaching. Applications with different scope have been developed. Many of these applications have either technical or design shortcomings. OBJECTIVE: To design a survey to determine student expectations of WSI applications for teaching histological and pathological diagnosis. To develop a new WSI application based on the findings of the survey. METHODS: A total of 216 students were questioned about their experiences and expectations of WSI applications, as well as favorable and undesired features. The survey included 14 multiple choice and two essay questions. Based on the survey, we developed a new WSI application called Pate utilizing open source technologies. RESULTS: The survey sample included 216 students-62.0% (134) women and 36.1% (78) men. Out of 216 students, 4 (1.9%) did not disclose their gender. The best-known preexisting WSI applications included Mainzer Histo Maps (199/216, 92.1%), Histoweb Tübingen (16/216, 7.4%), and Histonet Ulm (8/216, 3.7%). Desired features for the students were latitude in the slides (190/216, 88.0%), histological (191/216, 88.4%) and pathological (186/216, 86.1%) annotations, points of interest (181/216, 83.8%), background information (146/216, 67.6%), and auxiliary informational texts (113/216, 52.3%). By contrast, a discussion forum was far less important (9/216, 4.2%) for the students. CONCLUSIONS: The survey revealed that the students appreciate a rich feature set, including WSI functionality, points of interest, auxiliary informational texts, and annotations. The development of Pate was significantly influenced by the findings of the survey. Although Pate currently has some issues with the Zoomify file format, it could be shown that Web technologies are capable of providing a high-performance WSI experience, as well as a rich feature set.