Search

Abstract The prognosis of pancreatic cancer (PDAC) after tumor resection remains poor, mostly due to a high but variable risk of recurrence. A promising tool for improved prognostication is the quantification of CT tumor enhancement. For this, various enhancement formulas have been used in previous studies. However, a systematic comparison of these formulas is lacking. In the present study, we applied twenty-three previously published CT enhancement formulas to our cohort of 92 PDAC patients who underwent upfront surgery. We identified seven formulas that could reliably predict tumor recurrence. Using these formulas, weak tumor enhancement was associated with tumor recurrence at one and two years after surgery (p ≤ 0.030). Enhancement was inversely associated with adverse clinicopathological features. Low enhancement values were predictive of a high recurrence risk (Hazard Ratio ≥ 1.659, p ≤ 0.028, Cox regression) and a short time to recurrence (TTR) (p ≤ 0.027, log-rank test). Some formulas were independent predictors of TTR in multivariate models. Strikingly, almost all of the best-performing formulas measure solely tumor tissue, suggesting that normalization to non-tumor structures might be unnecessary. Among the top performers were also the absolute arterial/portal venous tumor attenuation values. These can be easily implemented in clinical practice for better recurrence prediction, thus potentially improving patient management.

Abstract Objective Investigate the feasibility of detecting early treatment-induced tumor tissue changes in patients with advanced lung adenocarcinoma using diffusion-weighted MRI-derived radiomics features. Methods This prospective observational study included 144 patients receiving either tyrosine kinase inhibitors (TKI, n = 64) or platinum-based chemotherapy (PBC, n = 80) for the treatment of pulmonary adenocarcinoma. Patients underwent diffusion-weighted MRI the day prior to therapy (baseline, all patients), as well as either + 1 (PBC) or + 7 and + 14 (TKI) days after treatment initiation. One hundred ninety-seven radiomics features were extracted from manually delineated tumor volumes. Feature changes over time were analyzed for correlation with treatment response (TR) according to CT-derived RECIST after 2 months and progression-free survival (PFS). Results Out of 14 selected delta-radiomics features, 6 showed significant correlations with PFS or TR. Most significant correlations were found after 14 days. Features quantifying ROI heterogeneity, such as short-run emphasis (p = 0.04(pfs)/0.005(tr)), gradient short-run emphasis (p = 0.06(pfs)/0.01(tr)), and zone percentage (p = 0.02(pfs)/0.01(tr)) increased in patients with overall better TR whereas patients with worse overall response showed an increase in features quantifying ROI homogeneity, such as normalized inverse difference (p = 0.01(pfs)/0.04(tr)). Clustering of these features allows stratification of patients into groups of longer and shorter survival. Conclusion Two weeks after initiation of treatment, diffusion MRI of lung adenocarcinoma reveals quantifiable tissue-level insights that correlate well with future treatment (non-)response. Diffusion MRI-derived radiomics thus shows promise as an early, radiation-free decision-support to predict efficacy and potentially alter the treatment course early. Critical relevance statement Delta-Radiomics texture features derived from diffusion-weighted MRI of lung adenocarcinoma, acquired as early as 2 weeks after initiation of treatment, are significantly correlated with RECIST TR and PFS as obtained through later morphological imaging. Key Points Morphological imaging takes time to detect TR in lung cancer, diffusion-weighted MRI might identify response earlier. Several radiomics features are significantly correlated with TR and PFS. Radiomics of diffusion-weighted MRI may facilitate patient stratification and management. Graphical Abstract

Abstract Objectives To evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations. Materials and methods Inspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56–69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised learning (SL) vs. three self-supervised learning (SSL) methods. Distribution shifts across ethnicity were further assessed for the top-performing methods. Results The learning strategy significantly influenced model performance, with SSL methods achieving higher performances compared to SL methods (p

Abstract Background Patients with COPD are often affected by loss of bone mineral density (BMD) and osteoporotic fractures. Natriuretic peptides (NP) are known as cardiac markers, but have also been linked to fragility-associated fractures in the elderly. As their functions include regulation of fluid and mineral balance, they also might affect bone metabolism, particularly in systemic disorders such as COPD. Research question We investigated the association between NP serum levels, vertebral fractures and BMD assessed by chest computed tomography (CT) in patients with COPD. Methods Participants of the COSYCONET cohort with CT scans were included. Mean vertebral bone density on CT (BMD-CT) as a risk factor for osteoporosis was assessed at the level of TH12 (AI-Rad Companion), and vertebral compression fractures were visually quantified by two readers. Their relationship with N-terminal pro-B-type natriuretic peptide (NT-proBNP), Mid-regional pro-atrial natriuretic peptide (MRproANP) and Midregional pro-adrenomedullin (MRproADM) was determined using group comparisons and multivariable analyses. Results Among 418 participants (58% male, median age 64 years, FEV1 59.6% predicted), vertebral fractures in TH12 were found in 76 patients (18.1%). Compared to patients without fractures, these had elevated serum levels (p ≤ 0.005) of MRproANP and MRproADM. Using optimal cut-off values in multiple logistic regression analyses, MRproANP levels ≥ 65 nmol/l (OR 2.34; p = 0.011) and age (p = 0.009) were the only significant predictors of fractures after adjustment for sex, BMI, smoking status, FEV1% predicted, SGRQ Activity score, daily physical activity, oral corticosteroids, the diagnosis of cardiac disease, and renal impairment. Correspondingly, MRproANP (p

Abstract Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.

IntroductionValidation of functional free-breathing MRI involves a comparison to more established or more direct measurements. This procedure is cost-intensive, as it requires access to patient cohorts, lengthy protocols, expenses for consumables, and binds working time. Therefore, the purpose of this study is to introduce a synthetic lung model (ASYLUM), which mimics dynamic MRI acquisition and includes predefined lung abnormalities for an alternative validation approach. The model is evaluated with different registration and quantification methods and compared with real data.MethodsA combination of trigonometric functions, deformation fields, and signal combinations were used to create 20 synthetic image time series. Lung voxels were assigned either to normal or one of six abnormality classes. The images were registered with three registration algorithms. The registered images were further analyzed with three quantification methods: deformation-based or signal-based regional ventilation (JVent/RVent) analysis and perfusion amplitude (QA). The registration results were compared with predefined deformations. Quantification methods were evaluated regarding predefined amplitudes and with respect to sensitivity, specificity, and spatial overlap of defects. In addition, 36 patients with chronic obstructive pulmonary disease were included for verification of model interpretations using CT as the gold standard.ResultsOne registration method showed considerably lower quality results (76% correlation vs. 92/97%, p ≤ 0.0001). Most ventilation defects were correctly detected with RVent and QA (e.g., one registration variant with sensitivity ≥78%, specificity ≥88). Contrary to this, JVent showed very low sensitivity for lower lung quadrants (0–16%) and also very low specificity (1–29%) for upper lung quadrants. Similar patterns of defect detection differences between RVent and JVent were also observable in patient data: Firstly, RVent was more aligned with CT than JVent for all quadrants (p ≤ 0.01) except for one registration variant in the lower left region. Secondly, stronger differences in overlap were observed for the upper quadrants, suggesting a defect bias in the JVent measurements in the upper lung regions.ConclusionThe feasibility of a validation framework for free-breathing functional lung imaging using synthetic time series was demonstrated. Evaluating different ventilation measurements, important differences were detected in synthetic and real data, with signal-based regional ventilation assessment being a more reliable method in the investigated setting.

Abstract Background Randomized controlled trials described beneficial effects of inhaled triple therapy (LABA/LAMA/ICS) in patients with chronic obstructive pulmonary disease (COPD) and high risk of exacerbations. We studied whether such effects were also detectable under continuous treatment in a retrospective observational setting. Methods Data from baseline and 18-month follow-up of the COPD cohort COSYCONET were used, including patients categorized as GOLD groups C/D at both visits (n = 258). Therapy groups were defined as triple therapy at both visits (triple always, TA) versus its complement (triple not always, TNA). Comparisons were performed via multiple regression analysis, propensity score matching and inverse probability weighting to adjust for differences between groups. For this purpose, variables were divided into predictors of therapy and outcomes. Results In total, 258 patients were eligible (TA: n = 162, TNA: n = 96). Without adjustments, TA patients showed significant (p

Purpose: The present study aimed to compare the computed tomography (CT) and magnetic resonance imaging (MRI) features of solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine neoplasms (pNENs). Method: Lesion imaging features of 39 patients with SPNs and 127 patients with pNENs were retrospectively extracted from 104 CT and 91 MRI scans. Results: Compared to pNEN patients, SPN patients were significantly younger (mean age 51.8 yrs versus 32.7 yrs) and more often female (female: male ratio, 5.50:1 versus 1.19:1). Most SPNs and pNENs presented as well-defined lesions with an expansive growth pattern. SPNs more often appeared as round or ovoid lesions, compared to pNENs which showed a lobulated or irregular shape in more than half of cases (p

ObjectivesThe presence of occult nodal metastases in patients with oral tongue squamous cell carcinomas (OTSCCs) has implications for treatment. More than 30% of patients will have occult nodal metastases, yet a considerable number of patients undergo unnecessary invasive neck dissection to confirm nodal status. In this work, we propose a probabilistic model for lymphatic metastatic spread that can quantify the risk of microscopic involvement at the lymph node level (LNL) given the location of macroscopic metastases and the tumor stage using the MRI method.Materials and methodsA total of 108 patients of OTSCCs were included in the study. A hidden Markov model (HMM) was used to compute the probabilities of transitions between states over time based on MRI. Learning of the transition probabilities was performed via Markov chain Monte Carlo sampling and was based on a dataset of OTSCC patients for whom involvement of individual LNLs was reported.ResultsOur model found that the most common involvement was that of level I and level II, corresponding to a high probability of 𝑝b1 = 0.39 ± 0.05, 𝑝b2 = 0.53 ± 0.09; lymph node level I had metastasis, and the probability of metastasis in lymph node II was high (93.79%); lymph node level II had metastasis, and the probability of metastasis in lymph node III was small (7.88%). Lymph nodes progress faster in the early stage and slower in the late stage.ConclusionAn HMM can produce an algorithm that is able to predict nodal metastasis evolution in patients with OTSCCs by analyzing the macroscopic metastases observed in the upstream levels, and tumor category.

Abstract In magnetic resonance imaging (MRI), the perception of substandard image quality may prompt repetition of the respective image acquisition protocol. Subsequently selecting the preferred high-quality image data from a series of acquisitions can be challenging. An automated workflow may facilitate and improve this selection. We therefore aimed to investigate the applicability of an automated image quality assessment for the prediction of the subjectively preferred image acquisition. Our analysis included data from 11,347 participants with whole-body MRI examinations performed as part of the ongoing prospective multi-center German National Cohort (NAKO) study. Trained radiologic technologists repeated any of the twelve examination protocols due to induced setup errors and/or subjectively unsatisfactory image quality and chose a preferred acquisition from the resultant series. Up to 11 quantitative image quality parameters were automatically derived from all acquisitions. Regularized regression and standard estimates of diagnostic accuracy were calculated. Controlling for setup variations in 2342 series of two or more acquisitions, technologists preferred the repetition over the initial acquisition in 1116 of 1396 series in which the initial setup was retained (79.9%, range across protocols: 73–100%). Image quality parameters then commonly showed statistically significant differences between chosen and discarded acquisitions. In regularized regression across all protocols, ‘structured noise maximum’ was the strongest predictor for the technologists’ choice, followed by ‘N/2 ghosting average’. Combinations of the automatically derived parameters provided an area under the ROC curve between 0.51 and 0.74 for the prediction of the technologists’ choice. It is concluded that automated image quality assessment can, despite considerable performance differences between protocols and anatomical regions, contribute substantially to identifying the subjective preference in a series of MRI acquisitions and thus provide effective decision support to readers.

We assessed the effects of structured reporting (SR) of lower extremity CT angiography (CTA) on report quality and workflow efficiency compared with conventional reports (CR). Surveys were conducted at an academic radiology department before and after the introduction of an SR template. Participants (n = 39, 21) rated report quality and report creation effort (1: very dissatisfied/low to 10: very satisfied/high) and whether SR represents an improvement over CR (1: completely disagree to 5: completely agree). Four residents and two supervising radiologists created both CR and SR of 40 CTA examinations. Report creation time was measured and the factual accuracy of residents’ reports was judged. Report completeness (median 8.0 vs. 7.0, p = 0.016) and clinical usefulness (7.0 vs. 4.0, p = 0.029) were rated higher for SR. Supervising radiologists found report clarity improved by SR (8.0 vs. 4.5, p = 0.029). Report creation effort was unchanged (7.0 vs. 6.0, p > 0.05). SR was considered an improvement over CR (median 4.0, IQR,3.0–5.0). Report supervision was shortened by SR (6.2 ± 2.0 min vs. 10.6 ± 3.5 min, p < 0.001) but total time for report creation remained unchanged (36.6 ± 12.8 min vs. 36.4 ± 11.0 min, p > 0.05). Factual accuracy of residents’ SR was deemed higher (8.0/9.5 vs. 7.0/7.0, p = 0.006/ < 0.001). In conclusion, SR has the potential to improve report quality and workflow efficiency for lower extremity CTA.

BackgroundChronic obstructive pulmonary disease (COPD) poses a substantial global health burden, demanding advanced diagnostic tools for early detection and accurate phenotyping. In this line, this study seeks to enhance COPD characterization on chest computed tomography (CT) by comparing the spatial and quantitative relationships between traditional parametric response mapping (PRM) and a novel self-supervised anomaly detection approach, and to unveil potential additional insights into the dynamic transitional stages of COPD.MethodsNon-contrast inspiratory and expiratory CT of 1,310 never-smoker and GOLD 0 individuals and COPD patients (GOLD 1–4) from the COPDGene dataset were retrospectively evaluated. A novel self-supervised anomaly detection approach was applied to quantify lung abnormalities associated with COPD, as regional deviations. These regional anomaly scores were qualitatively and quantitatively compared, per GOLD class, to PRM volumes (emphysema: PRMEmph, functional small-airway disease: PRMfSAD) and to a Principal Component Analysis (PCA) and Clustering, applied on the self-supervised latent space. Its relationships to pulmonary function tests (PFTs) were also evaluated.ResultsInitial t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the self-supervised latent space highlighted distinct spatial patterns, revealing clear separations between regions with and without emphysema and air trapping. Four stable clusters were identified among this latent space by the PCA and Cluster Analysis. As the GOLD stage increased, PRMEmph, PRMfSAD, anomaly score, and Cluster 3 volumes exhibited escalating trends, contrasting with a decline in Cluster 2. The patient-wise anomaly scores significantly differed across GOLD stages (p

This study evaluates how far T2 mapping can identify arthroscopically confirmed pathologies in the long biceps tendon (LBT) and quantify the T2 values in healthy and pathological tendon substance. This study comprised eighteen patients experiencing serious shoulder discomfort, all of whom underwent magnetic resonance imaging, including T2 mapping sequences, followed by shoulder joint arthroscopy. Regions of interest were meticulously positioned on their respective T2 maps, capturing the sulcal portion of the LBT and allowing for the quantification of the average T2 values. Subsequent analyses included the calculation of diagnostic cut-off values, sensitivities, and specificities for the detection of tendon pathologies, and the calculation of inter-reader correlation coefficients (ICCs) involving two independent radiologists. The average T2 value for healthy subjects was measured at 23.3 ± 4.6 ms, while patients with tendinopathy displayed a markedly higher value, at 47.9 ± 7.8 ms. Of note, the maximum T2 value identified in healthy tendons (29.6 ms) proved to be lower than the minimal value measured in pathological tendons (33.8 ms), resulting in a sensitivity and specificity of 100% (95% confidence interval 63.1–100) across all cut-off values ranging from 29.6 to 33.8 ms. The ICCs were found to range from 0.93 to 0.99. In conclusion, T2 mapping is able to assess and quantify healthy LBTs and can distinguish them from tendon pathology. T2 mapping may provide information on the (ultra-)structural integrity of tendinous tissue, facilitating early diagnosis, prompt therapeutic intervention, and quantitative monitoring after conservative or surgical treatments of LBT.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28–83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Purpose: To assess the feasibility and diagnostic accuracy of MRI-derived 3D volumetry of lower lumbar vertebrae and dural sac segments using shape-based machine learning for the detection of Marfan syndrome (MFS) compared with dural sac diameter ratios (the current clinical standard). Materials and methods: The final study sample was 144 patients being evaluated for MFS from 01/2012 to 12/2016, of whom 81 were non-MFS patients (46 [67%] female, 36 ± 16 years) and 63 were MFS patients (36 [57%] female, 35 ± 11 years) according to the 2010 Revised Ghent Nosology. All patients underwent 1.5T MRI with isotropic 1 × 1 × 1 mm3 3D T2-weighted acquisition of the lumbosacral spine. Segmentation and quantification of vertebral bodies L3-L5 and dural sac segments L3-S1 were performed using a shape-based machine learning algorithm. For comparison with the current clinical standard, anteroposterior diameters of vertebral bodies and dural sac were measured. Ratios between dural sac volume/diameter at the respective level and vertebral body volume/diameter were calculated. Results: Three-dimensional volumetry revealed larger dural sac volumes (p < 0.001) and volume ratios (p < 0.001) at L3-S1 levels in MFS patients compared with non-MFS patients. For the detection of MFS, 3D volumetry achieved higher AUCs at L3-S1 levels (0.743, 0.752, 0.808, and 0.824) compared with dural sac diameter ratios (0.673, 0.707, 0.791, and 0.848); a significant difference was observed only for L3 (p < 0.001). Conclusion: MRI-derived 3D volumetry of the lumbosacral dural sac and vertebral bodies is a feasible method for quantifying dural ectasia using shape-based machine learning. Non-inferior diagnostic accuracy was observed compared with dural sac diameter ratio (the current clinical standard for MFS detection).

Abstract Background This study provides a quantitative meta-analysis of pancreatic CT perfusion studies, investigating choice of study parameters, ability for quantitative discrimination of pancreatic diseases, and influence of acquisition and reconstruction parameters on reported results. Methods Based on a PubMed search with key terms ‘pancreas’ or ‘pancreatic,’ ‘dynamic’ or ‘perfusion,’ and ‘computed tomography’ or ‘CT,’ 491 articles published between 1982 and 2020 were screened for inclusion in the study. Inclusion criteria were: reported original data, human subjects, five or more datasets, measurements of pancreas or pancreatic pathologies, and reported quantitative perfusion parameters. Study parameters and reported quantitative measurements were extracted, and heterogeneity of study parameters and trends over time are analyzed. Pooled data were tested with weighted ANOVA and ANCOVA models for differences in perfusion results between normal pancreas, pancreatitis, PDAC (pancreatic ductal adenocarcinoma), and non-PDAC (e.g., neuroendocrine tumors, insulinomas) and based on study parameters. Results Reported acquisition parameters were heterogeneous, except for contrast agent amount and injection rate. Tube potential and slice thickness decreased, whereas tube current time product and scan coverage increased over time. Blood flow and blood volume showed significant differences between pathologies (both p

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

IntroductionDue to hypoxic vasoconstriction, perfusion is interesting in the lungs. Magnetic Resonance Imaging (MRI) perfusion imaging based on Dynamic Contrast Enhancement (DCE) has been demonstrated in patients with Chronic Obstructive Pulmonary Diseases (COPD) using visual scores, and quantification methods were recently developed further. Inter-patient correlations of echo time-dependent observed T1 [T1(TE)] have been shown with perfusion scores, pulmonary function testing, and quantitative computed tomography. Here, we examined T1(TE) quantification and quantitative perfusion MRI together and investigated both inter-patient and local correlations between T1(TE) and quantitative perfusion.Methods22 patients (age 68.0 ± 6.2) with COPD were examined using morphological MRI, inversion recovery multi-echo 2D ultra-short TE (UTE) in 1–2 slices for T1(TE) mapping, and 4D Time-resolved angiography With Stochastic Trajectories (TWIST) for DCE. T1(TE) maps were calculated from 2D UTE at five TEs from 70 to 2,300 μs. Pulmonary Blood Flow (PBF) and perfusion defect (QDP) maps were produced from DCE measurements. Lungs were automatically segmented on UTE images and morphological MRI and these segmentations registered to DCE images. DCE images were separately registered to UTE in corresponding slices and divided into corresponding subdivisions. Spearman’s correlation coefficients were calculated for inter-patient correlations using the entire segmented slices and for local correlations separately using registered images and subdivisions for each TE. Median T1(TE) in normal and defect areas according to QDP maps were compared.ResultsInter-patient correlations were strongest on average at TE2 = 500 μs, reaching up to |ρ| = 0.64 for T1 with PBF and |ρ| = 0.76 with QDP. Generally, local correlations of T1 with PBF were weaker at TE2 than at TE1 or TE3 and with maximum values of |ρ| = 0.66 (from registration) and |ρ| = 0.69 (from subdivision). In 18 patients, T1 was shorter in defect areas than in normal areas, with the relative difference smallest at TE2.DiscussionThe inter-patient correlations of T1 with PBF and QDP found show similar strength and TE-dependence as those previously reported for visual perfusion scores and quantitative computed tomography. The local correlations and median T1 suggest that not only base T1 but also the TE-dependence of observed T1 in normal areas is closer to that found previously in healthy volunteers than in defect areas.

Abstract Absorption-based clinical computed tomography (CT) is the current imaging method of choice in the diagnosis of lung diseases. Many pulmonary diseases are affecting microscopic structures of the lung, such as terminal bronchi, alveolar spaces, sublobular blood vessels or the pulmonary interstitial tissue. As spatial resolution in CT is limited by the clinically acceptable applied X-ray dose, a comprehensive diagnosis of conditions such as interstitial lung disease, idiopathic pulmonary fibrosis or the characterization of small pulmonary nodules is limited and may require additional validation by invasive lung biopsies. Propagation-based imaging (PBI) is a phase sensitive X-ray imaging technique capable of reaching high spatial resolutions at relatively low applied radiation dose levels. In this publication, we present technical refinements of PBI for the characterization of different artificial lung pathologies, mimicking clinically relevant patterns in ventilated fresh porcine lungs in a human-scale chest phantom. The combination of a very large propagation distance of 10.7 m and a photon counting detector with $$100\,\upmu \hbox {m}$$ 100 μ m pixel size enabled high resolution PBI CT with significantly improved dose efficiency, measured by thermoluminescence detectors. Image quality was directly compared with state-of-the-art clinical CT. PBI with increased propagation distance was found to provide improved image quality at the same or even lower X-ray dose levels than clinical CT. By combining PBI with iodine k-edge subtraction imaging we further demonstrate that, the high quality of the calculated iodine concentration maps might be a potential tool for the analysis of lung perfusion in great detail. Our results indicate PBI to be of great value for accurate diagnosis of lung disease in patients as it allows to depict pathological lesions non-invasively at high resolution in 3D. This will especially benefit patients at high risk of complications from invasive lung biopsies such as in the setting of suspected idiopathic pulmonary fibrosis (IPF).

Reduced iodine loads for computed tomography (CT)-based vascular assessment prior to transcatheter aortic valve implantation (TAVI) may be feasible in conjunction with a spectral detector CT scanner. This prospective single-center study considered 100 consecutive patients clinically referred for pre-TAVI CT. They were examined on a dual-layer detector CT scanner to obtain an ECG-gated cardiac scan and a non-ECG-gated aortoiliofemoral scan. Either a standard contrast media (SCM) protocol using 80 mL Iohexol 350 mgI/mL (iodine load: 28 gI) or a body-mass-index adjusted reduced contrast media (RCM) protocol using 40–70 mL Iohexol 350 mgI/mL (iodine load: 14–24.5 gI) were employed. Conventional images and virtual monoenergetic images at 40–80 keV were reconstructed. A threshold of 250 HU was set for sufficient attenuation along the arterial access pathway. A qualitative assessment used a five-point Likert scale. Sufficient attenuation in the thoracic aorta was observed for all patients in both groups using conventional images. In the abdominal, iliac, and femoral segments, sufficient attenuation was observed for the majority of patients when using virtual monoenergetic images (SCM: 96–100% of patients, RCM: 88–94%) without statistical difference between both groups. Segments with attenuation measurements below the threshold remained qualitatively assessable as well. Likert scores were ‘excellent’ for virtual monoenergetic images 50 keV and 55 keV in both groups (RCM: 1.2–1.4, SCM: 1.2–1.3). With diagnostic image quality maintained, it can be concluded that reduced iodine loads of 14–24.5 gI are feasible for pre-TAVI vascular assessment on a spectral detector CT scanner.

Abstract Background To explore the prognostic value of serial dynamic contrast-enhanced (DCE) MRI in patients with advanced pulmonary adenocarcinoma undergoing first-line therapy with either tyrosine-kinase inhibitors (TKI) or platinum-based chemotherapy (PBC). Methods Patients underwent baseline (day 0, n = 98), and post-therapeutic DCE MRI (PBC: day + 1, n = 52); TKI: day + 7, n = 46) at 1.5T. Perfusion curves were acquired at 10, 40, and 70 s after contrast application and analysed semiquantitatively. Treatment response was evaluated at 6 weeks by CT (RECIST 1.1); progression-free survival (PFS) and overall survival were analysed with respect to clinical and perfusion parameters. Relative uptake was defined as signal difference between contrast and non-contrast images, divided by the non-contrast signal. Predictors of survival were selected using Cox regression analysis. Median follow-up was 825 days. Results In pre-therapeutic and early post-therapeutic MRI, treatment responders (n = 27) showed significantly higher relative contrast uptake within the tumor at 70 s after application as compared to non-responders (n = 71, p ≤ 0.02), response defined as PR by RECIST 1.1 at 6 weeks. There was no significant change of perfusion at early MRI after treatment. In multivariate regression analysis of selected parameters, the strongest association with PFS were relative uptake at 40 s in the early post-treatment MRI and pre-treatment clinical data (presence of liver metastases, ECOG performance status). Conclusion Higher contrast uptake within the tumor at pre-treatment and early post-treatment MRI was associated with treatment response and better prognosis. DCE MRI of pulmonary adenocarcinoma may provide important prognostic information.

Abstract Asynchronous calibration could allow opportunistic screening based on routine CT for early osteoporosis detection. In this phantom study, a bone mineral density (BMD) calibration phantom and multi-energy CT (MECT) phantom were imaged on eight different CT scanners with multiple tube voltages (80–150 kVp) and image reconstruction settings (e.g. soft/hard kernel). Reference values for asynchronous BMD estimation were calculated from the BMD-phantom and validated with six calcium composite inserts of the MECT-phantom with known ground truth. Relative errors/changes in estimated BMD were calculated and investigated for influence of tube voltage, CT scanner and reconstruction setting. Reference values for 282 acquisitions were determined, resulting in an average relative error between calculated BMD and ground truth of − 9.2% ± 14.0% with a strong correlation (R 2 = 0.99; p

Abstract Large epidemiological studies such as the UK Biobank (UKBB) or German National Cohort (NAKO) provide unprecedented health-related data of the general population aiming to better understand determinants of health and disease. As part of these studies, Magnetic Resonance Imaging (MRI) is performed in a subset of participants allowing for phenotypical and functional characterization of different organ systems. Due to the large amount of imaging data, automated image analysis is required, which can be performed using deep learning methods, e. g. for automated organ segmentation. In this paper we describe a computational pipeline for automated segmentation of abdominal organs on MRI data from 20,000 participants of UKBB and NAKO and provide results of the quality control process. We found that approx. 90% of data sets showed no relevant segmentation errors while relevant errors occurred in a varying proportion of data sets depending on the organ of interest. Image-derived features based on automated organ segmentations showed relevant deviations of varying degree in the presence of segmentation errors. These results show that large-scale, deep learning-based abdominal organ segmentation on MRI data is feasible with overall high accuracy, but visual quality control remains an important step ensuring the validity of down-stream analyses in large epidemiological imaging studies.

Abstract Intraductal tubulopapillary neoplasms (ITPN) are rare pancreatic tumors (

BackgroundIn chronic obstructive pulmonary disease (COPD) abnormal lung function is related to emphysema and airway obstruction, but their relative contribution in each GOLD-stage is not fully understood. In this study, we used quantitative computed tomography (QCT) parameters for phenotyping of emphysema and airway abnormalities, and to investigate the relative contribution of QCT emphysema and airway parameters to airflow limitation specifically in each GOLD stage.MethodsNon-contrast computed tomography (CT) of 492 patients with COPD former GOLD 0 COPD and COPD stages GOLD 1–4 were evaluated using fully automated software for quantitative CT. Total lung volume (TLV), emphysema index (EI), mean lung density (MLD), and airway wall thickness (WT), total diameter (TD), lumen area (LA), and wall percentage (WP) were calculated for the entire lung, as well as for all lung lobes separately. Results from the 3rd-8th airway generation were aggregated (WT3-8, TD3-8, LA3-8, WP3-8). All subjects underwent whole-body plethysmography (FEV1%pred, VC, RV, TLC).ResultsEI was higher with increasing GOLD stages with 1.0 ± 1.8% in GOLD 0, 4.5 ± 9.9% in GOLD 1, 19.4 ± 15.8% in GOLD 2, 32.7 ± 13.4% in GOLD 3 and 41.4 ± 10.0% in GOLD 4 subjects (p

Purpose: To assess the diagnostic accuracy of BMI-adapted, low-radiation and low-iodine dose, dual-source aortic CT for endoleak detection in non-obese and obese patients following endovascular aortic repair. Methods: In this prospective single-center study, patients referred for follow-up CT after endovascular repair with a history of at least one standard triphasic (native, arterial and delayed phase) routine CT protocol were enrolled. Patients were divided into two groups and allocated to a BMI-adapted (group A, BMI < 30 kg/m2; group B, BMI ≥ 30 kg/m2) double low-dose CT (DLCT) protocol comprising single-energy arterial and dual-energy delayed phase series with virtual non-contrast (VNC) reconstructions. An in-patient comparison of the DLCT and routine CT protocol as reference standard was performed regarding differences in diagnostic accuracy, radiation dose, and image quality. Results: Seventy-five patients were included in the study (mean age 73 ± 8 years, 63 (84%) male). Endoleaks were diagnosed in 20 (26.7%) patients, 11 of 53 (20.8%) in group A and 9 of 22 (40.9%) in group B. Two radiologists achieved an overall diagnostic accuracy of 98.7% and 97.3% for endoleak detection, with 100% in group A and 95.5% and 90.9% in group B. All examinations were diagnostic. The DLCT protocol reduced the effective dose from 10.0 ± 3.6 mSv to 6.1 ± 1.5 mSv (p < 0.001) and the total iodine dose from 31.5 g to 14.5 g in group A and to 17.4 g in group B. Conclusion: Optimized double low-dose dual-source aortic CT with VNC, arterial and delayed phase images demonstrated high diagnostic accuracy for endoleak detection and significant radiation and iodine dose reductions in both obese and non-obese patients compared to the reference standard of triple phase, standard radiation and iodine dose aortic CT.

Abstract In patients with COPD, it has not been comprehensively assessed whether the predictive value of comorbidities for mortality differs between men and women. We therefore aimed to examine sex differences of COPD comorbidities in regard with prognosis by classifying comorbidities into a comorbidome related to extrapulmonary disorders and a pulmorbidome, referring to pulmonary disorders. The study population comprised 1044 women and 1531 men with the diagnosis of COPD from COSYCONET, among them 2175 of GOLD grades 1–4 and 400 at risk. Associations of comorbidities with mortality were studied using Cox regression analysis for men and women separately. During the follow-up (median 3.7 years) 59 women and 159 men died. In men, obesity, hypertension, coronary artery disease, liver cirrhosis, osteoporosis, kidney disease, anaemia and increased heart rate (HR) predict mortality, in women heart failure, hyperuricemia, mental disorders, kidney disease and increased HR (p

Introduction: Chronic rhinosinusitis (CRS) usually presents with nasal congestion, rhinorrhea and anosmia impacts quality of life in cystic fibrosis (CF). Especially mucopyoceles pathognomonic for CRS in CF may cause complications such as spread of infection. Previous studies using magnetic resonance imaging (MRI) demonstrated early onset and progression of CRS from infancy to school age in patients with CF, and mid-term improvements of CRS in preschool and school-age children with CF treated with lumacaftor/ivacaftor for at least 2 months. However, long-term data on treatment effects on paranasal sinus abnomalities in preschool and school-age children with CF are lacking.Methods: 39 children with CF homozygous for F508del (mean age at baseline MRI 5.9 ± 3.0 years, range 1-12 years) underwent MRI before (MRI1) and about 7 months after starting lumacaftor/ivacaftor and then annually (median 3 follow-up MRI, range 1–4) (MRI2-4). MRI were evaluated using the previously evaluated CRS-MRI score with excellent inter-reader agreement. For intraindividual analysis ANOVA mixed-effects analysis including Geisser-Greenhouse correction and Fisher’s exact test, and for interindividual group analysis Mann-Whitney test were used.Results: The CRS-MRI sum score at baseline was similar in children starting lumacaftor/ivacaftor in school age and children starting therapy at preschool age (34.6 ± 5.2 vs.32.9 ± 7.8, p = 0.847). Mucopyoceles were the dominant abnormality in both, especially in maxillary sinus (65% and 55%, respectively). In children starting therapy in school age the CRS-MRI sum score decreased longitudinally from MRI1 to MRI2 (−2.1 ± 3.5, p < 0.05), MRI3 (−3.0 ± 3.7, p < 0.01) and MRI4 (−3.6 ± 4.7, p < 0.01), mainly due to a decrease in the mucopyoceles subscore (−1.0 ± 1.5, p = 0.059; −1.2 ± 2.0, p < 0.05; −1.6 ± 1.8, p < 0.01; and −2.6 ± 2.8, p = 0.417, respectively). In children starting lumacaftor/ivacaftor in preschool age, the CRS-MRI sum score remained stable under therapy over all three follow-up MRI (0.6 ± 3.3, p = 0.520; 2.4 ± 7.6, p = 0.994; 2.1 ± 10.5, p > 0.999 and −0.5 ± 0.5, p = 0.740; respectively).Conclusion: Longitudinal paranasal sinus MRI shows improvements in paranasal sinus abnormalities in children with CF starting lumacaftor/ivacaftor therapy at school age. Further, MRI detects a prevention of an increase in paranasal sinus abnormalities in children with CF starting lumacaftor/ivacaftor therapy at preschool age. Our data support the role of MRI for comprehensive non-invasive therapy and disease monitoring of paranasal sinus abnormalities in children with CF.

Introduction: By using bolus tracking with an appropriate acquisition delay dual-energy computed tomography (DECT) iodine maps might serve as a replacement of CT perfusion maps at reduced radiation exposure. This study aimed to evaluate the optimal acquisition delays of DECT for the replacement of parameter maps calculated with the Patlak model in pancreatic adenocarcinoma by corresponding iodine maps. Materials and methods: Dual-source dynamic DECT acquisitions at 80 kVp/Sn140 kVp of 14 patients with pancreatic carcinoma were used to calculate CT perfusion maps of blood volume and permeability with the Patlak model. DECT iodine maps were generated from individual DECT acquisitions, matching acquisition times relative to prior bolus-triggered three-phase CT acquisitions for investigating different acquisition delays. Correlation between perfusion parameters and iodine concentrations was determined for acquisition delays between −6 s and 33 s. Results: Correlation between iodine concentrations and perfusion parameters ranged from −0.05 to 0.63 for blood volume and from −0.05 to 0.71 for permeability, depending on potential trigger delay. The correlation was significant for potential acquisition delays above 1.5 s for blood volume and above 9.0 s for permeability (both p

Background Bronchial artery dilatation (BAD) is associated with haemoptysis in advanced cystic fibrosis (CF) lung disease. Our aim was to evaluate BAD onset and its association with disease severity by magnetic resonance imaging (MRI). Methods 188 CF patients (mean±sd age 13.8±10.6 years, range 1.1–55.2 years) underwent annual chest MRI (median three exams, range one to six exams), contributing a total of 485 MRI exams including perfusion MRI. Presence of BAD was evaluated by two radiologists in consensus. Disease severity was assessed using the validated MRI scoring system and spirometry (forced expiratory volume in 1 s (FEV1) % pred). Results MRI demonstrated BAD in 71 (37.8%) CF patients consistently from the first available exam and a further 10 (5.3%) patients first developed BAD during surveillance. Mean MRI global score in patients with BAD was 24.5±8.3 compared with 11.8±7.0 in patients without BAD (p

ObjectivesQuantitative computed tomography (QCT) offers some promising markers to quantify cystic fibrosis (CF)-lung disease. Air trapping may precede irreversible bronchiectasis; therefore, the temporal interdependencies of functional and structural lung disease need to be further investigated. We aim to quantify airway dimensions and air trapping on chest CT of school-age children with mild CF-lung disease over two years.MethodsFully-automatic software analyzed 144 serial spirometer-controlled chest CT scans of 36 children (median 12.1 (10.2–13.8) years) with mild CF-lung disease (median ppFEV1 98.5 (90.8–103.3) %) at baseline, 3, 12 and 24 months. The airway wall percentage (WP5–10), bronchiectasis index (BEI), as well as severe air trapping (A3) were calculated for the total lung and separately for all lobes. Mixed linear models were calculated, considering the lobar distribution of WP5–10, BEI and A3 cross-sectionally and longitudinally.ResultsWP5–10 remained stable (P = 0.248), and BEI changed from 0.41 (0.28–0.7) to 0.54 (0.36–0.88) (P = 0.156) and A3 from 2.26% to 4.35% (P = 0.086) showing variability over two years. ppFEV1 was also stable (P = 0.276). A robust mixed linear model showed a cross-sectional, regional association between WP5–10 and A3 at each timepoint (P

Background: Detecting bone marrow edema (BME) as a sign of acute fractures is challenging on conventional computed tomography (CT). This study evaluated the diagnostic performance of a three-material decomposition (TMD) approach for detecting traumatic BME of the extremities on spectral computed tomography (SCT). Methods: This retrospective diagnostic study included 81 bone compartments with and 80 without BME. A TMD application to visualize BME was developed in collaboration with Philips Healthcare. The following bone compartments were included: distal radius, proximal femur, proximal tibia, distal tibia and fibula, and long bone diaphysis. Two blinded radiologists reviewed each case independently in random order for the presence or absence of BME. Results: The interrater reliability was 0.84 (p < 0.001). The different bone compartments showed sensitivities of 86.7% to 93.8%, specificities of 84.2% to 94.1%, positive predictive values of 82.4% to 94.7%, negative predictive values of 87.5% to 93.3%, and area under the curve (AUC) values of 85.7% to 93.1%. The distal radius showed the highest sensitivity and the proximal femur showed the lowest sensitivity, while the proximal femur presented the highest specificity and the distal tibia presented the lowest specificity. Conclusions: Our TMD approach provides high diagnostic performance for detecting BME of the extremities. Therefore, this approach could be used routinely in the emergency setting.

Purpose: The combined testing for coronary artery and pulmonary diseases is of clinical interest as risk factors are shared. In this study, a novel ECG-gated tin-filtered ultra-low dose chest CT protocol (GCCT) for integrated heart and lung acquisition and the applicability of artificial intelligence (AI)-based coronary artery calcium scoring were assessed. Methods: In a clinical registry of 10481 patients undergoing heart and lung CT, GCCT was applied in 44 patients on a dual-source CT. Coronary calcium scans (CCS) with 120 kVp, 100 kVp, and tin-filtered 100 kVp (Sn100) of controls, matched with regard to age, sex, and body-mass index, were retrieved from the registry (ntotal=176, 66.5 (59.4–74.0) years, 52 men). Automatic tube current modulation was used in all scans. In 20 patients undergoing GCCT and Sn100 CCS, Agatston scores were measured both semi-automatically by experts and by AI, and classified into six groups (0,

Background: Chest computed tomography (CT) is increasingly used for phenotyping and monitoring of patients with COPD. The aim of this work was to evaluate the association of Pi10 as a measure of standardized airway wall thickness on CT with exacerbations, mortality, and response to triple therapy. Methods: Patients of GOLD grades 1–4 of the COSYCONET cohort with prospective CT scans were included. Pi10 was automatically computed and analyzed for its relationship to COPD severity, comorbidities, lung function, respiratory therapy, and mortality over a 6-year period, using univariate and multivariate comparisons. Results: We included n = 433 patients (61%male). Pi10 was dependent on both GOLD grades 1–4 ( p = 0.009) and GOLD groups A–D ( p = 0.008); it was particularly elevated in group D, and ROC analysis yielded a cut-off of 0.26 cm. Higher Pi10 was associated to lower FEV 1 % predicted and higher RV/TLC, moreover the annual changes of lung function parameters ( p

The “bullseye” sign has been exclusively reported in patients suffering from coronavirus disease 2019 (COVID-19) pneumonia. It is theorized that this newly recognized computed tomography (CT) feature represents a sign of organizing pneumonia. Well established signs of organizing pneumonia also reported in COVID-19 patients include linear opacities, the “reversed halo” sign (or “atoll” sign), and a perilobular distribution of abnormalities. These findings are usually present on imaging in the intermediate and late stage of the disease. This is a case of simultaneous presence of the “bullseye” and the “reversed halo” sign on chest CT images of a COVID-19 patient examined 22 days after symptom onset.

Abstract Background Lung emphysema is an important phenotype of chronic obstructive pulmonary disease (COPD), and CT scanning is strongly recommended to establish the diagnosis. This study aimed to identify criteria by which physicians with limited technical resources can improve the diagnosis of emphysema. Methods We studied 436 COPD patients with prospective CT scans from the COSYCONET cohort. All items of the COPD Assessment Test (CAT) and the St George’s Respiratory Questionnaire (SGRQ), the modified Medical Research Council (mMRC) scale, as well as data from spirometry and CO diffusing capacity, were used to construct binary decision trees. The importance of parameters was checked by the Random Forest and AdaBoost machine learning algorithms. Results When relying on questionnaires only, items CAT 1 & 7 and SGRQ 8 & 12 sub-item 3 were most important for the emphysema- versus airway-dominated phenotype, and among the spirometric measures FEV1/FVC. The combination of CAT item 1 (≤ 2) with mMRC (> 1) and FEV1/FVC, could raise the odds for emphysema by factor 7.7. About 50% of patients showed combinations of values that did not markedly alter the likelihood for the phenotypes, and these could be easily identified in the trees. Inclusion of CO diffusing capacity revealed the transfer coefficient as dominant measure. The results of machine learning were consistent with those of the single trees. Conclusions Selected items (cough, sleep, breathlessness, chest condition, slow walking) from comprehensive COPD questionnaires in combination with FEV1/FVC could raise or lower the likelihood for lung emphysema in patients with COPD. The simple, parsimonious approach proposed by us might help if diagnostic resources regarding respiratory diseases are limited. Trial registration ClinicalTrials.gov, Identifier: NCT01245933, registered 18 November 2010, https://clinicaltrials.gov/ct2/show/record/NCT01245933 .

Abstract Background Cancer-associated fibroblasts are found in the stroma of epithelial tumors. They are characterized by overexpression of the fibroblast activation protein (FAP), a serine protease which was already proven as attractive target for chelator-based theranostics. Unfortunately, the value of gallium-68 labeled tracers is limited by their batch size and the short nuclide half-life. To overcome this drawback, radiolabeling with aluminum fluoride complexes and 6-fluoronicotinamide derivatives of the longer-lived nuclide fluorine-18 was established. The novel compounds were tested for their FAP-specific binding affinity. Uptake and binding competition were studied in vitro using FAP expressing HT-1080 cells. HEK cells transfected with the closely related dipeptidyl peptidase-4 (HEK-CD26) were used as negative control. Small animal positron emission tomography imaging and biodistribution experiments were performed in HT-1080-FAP xenografted nude mice. [18F]AlF-FAPI-74 was selected for PET/CT imaging in a non-small cell lung cancer (NSCLC) patient. Results In vitro, 18F-labeled FAPI-derivatives demonstrated high affinity (EC50 =

Abstract To evaluate the relationship of cardiac function, including time-volume-curves, with lung volumes derived from pulmonary function tests (PFT) and MRI in subjects without cardiovascular diseases. 216 subjects underwent whole-body MRI and spirometry as part of the KORA-FF4 cohort study. Lung volumes derived semi-automatically using an in-house algorithm. Forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and residual volume were measured. Cardiac parameters derived from Cine-SSFP-sequence using cvi42, while left ventricle (LV) time-volume-curves were evaluated using pyHeart. Linear regression analyses assessed the relationships of cardiac parameters with PFT and MRI-based lung volumes. Mean age was 56.3 ± 9.2 years (57% males). LV and right ventricular (RV) end-diastolic-, end-systolic-, stroke volume, LV peak ejection- and early/late diastolic filling rate were associated with FEV1, FVC, and residual volume (excluding late diastolic filling rate with FEV1, LV end-systolic/stroke volume and RV end-diastolic/end-systolic volumes with residual volume). In contrast, LV end-diastolic volume (ß = − 0.14, p = 0.01), early diastolic filling rate (ß = − 0.11, p = 0.04), and LV/RV stroke volume (ß = − 0.14, p = 0.01; ß = − 0.11, p = 0.01) were inversely associated with MRI-based lung volume. Subclinical cardiac impairment was associated with reduced FEV1, FVC, and residual volume. Cardiac parameters decreased with increasing MRI-based lung volume contrasting the results of PFT.

BackgroundDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows the assessment of pulmonary perfusion, which may play a key role in the development of muco-obstructive lung disease. One problem with quantifying pulmonary perfusion is the high variability of metrics. Quantifying the extent of abnormalities using unsupervised clustering algorithms in residue function maps leads to intrinsic normalization and could reduce variability.PurposeWe investigated the reproducibility of perfusion defects in percent (QDP) in clinically stable patients with cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD).Methods15 CF (29.3 ± 9.3y, FEV1%predicted = 66.6 ± 15.8%) and 20 COPD (66.5 ± 8.9y, FEV1%predicted = 42.0 ± 13.3%) patients underwent DCE-MRI twice 1 month apart. QDP, pulmonary blood flow (PBF), and pulmonary blood volume (PBV) were computed from residue function maps using an in-house quantification pipeline. A previously validated MRI perfusion score was visually assessed by an expert reader.ResultsOverall, mean QDP, PBF, and PBV did not change within 1 month, except for QDP in COPD (p < 0.05). We observed smaller limits of agreement (± 1.96 SD) related to the median for QDP (CF: ± 38%, COPD: ± 37%) compared to PBF (CF: ± 89%, COPD: ± 55%) and PBV (CF: ± 55%, COPD: ± 51%). QDP correlated moderately with the MRI perfusion score in CF (r = 0.46, p < 0.05) and COPD (r = 0.66, p < 0.001). PBF and PBV correlated poorly with the MRI perfusion score in CF (r =−0.29, p = 0.132 and r =−0.35, p = 0.067, respectively) and moderately in COPD (r =−0.57 and r =−0.57, p < 0.001, respectively).ConclusionIn patients with muco-obstructive lung diseases, QDP was more robust and showed a higher correlation with the MRI perfusion score compared to the traditionally used perfusion metrics PBF and PBV.

Obesity-related metabolic disorders such as hypertension, hyperlipidemia and chronic inflammation have been associated with aortic dilatation and resulting in aortic aneurysms in many cases. Whether weight loss may reduce the risk of aortic dilatation is not clear. In this study, the diameter of the descending thoracic aorta, infrarenal abdominal aorta and aortic bifurcation of 144 overweight or obese non-smoking adults were measured by MR-imaging, at baseline, and 12 and 50 weeks after weight loss by calorie restriction. Changes in aortic diameter, anthropometric measures and body composition and metabolic markers were evaluated using linear mixed models. The association of the aortic diameters with the aforementioned clinical parameters was analyzed using Spearman`s correlation. Weight loss was associated with a reduction in the thoracic and abdominal aortic diameters 12 weeks after weight loss (predicted relative differences for Quartile 4: 2.5% ± 0.5 and -2.2% ± 0.8, p < 0.031; respectively). Furthermore, there was a nominal reduction in aortic diameters during the 50-weeks follow-up period. Aortic diameters were positively associated with weight, visceral adipose tissue, glucose, HbA1c and with both systolic and diastolic blood pressure. Weight loss induced by calorie restriction may reduce aortic diameters. Future studies are needed to investigate, whether the reduction of aortic diameters via calorie restriction may help to prevent aortic aneurysms.

Abstract The COVID-19 pandemic has worldwide individual and socioeconomic consequences. Chest computed tomography has been found to support diagnostics and disease monitoring. A standardized approach to generate, collect, analyze, and share clinical and imaging information in the highest quality possible is urgently needed. We developed systematic, computer-assisted and context-guided electronic data capture on the FDA-approved mint LesionTM software platform to enable cloud-based data collection and real-time analysis. The acquisition and annotation include radiological findings and radiomics performed directly on primary imaging data together with information from the patient history and clinical data. As proof of concept, anonymized data of 283 patients with either suspected or confirmed SARS-CoV-2 infection from eight European medical centers were aggregated in data analysis dashboards. Aggregated data were compared to key findings of landmark research literature. This concept has been chosen for use in the national COVID-19 response of the radiological departments of all university hospitals in Germany.

Background and Aim. Assessment of appropriateness of CT pulmonary angiograms (CTPA) in patients with suspected pulmonary embolism (PE) is based on risk stratification algorithms such as simplified the Geneva Score (sGS) in combination with D-dimer blood tests. The aim of this study was to validate the diagnostic yield and appropriateness of CTPA examinations in accordance with 2014 European Society of Cardiology (ESC) guidelines. Materials and Methods. Data from 155 outpatients who underwent CTPA for clinical suspicion of PE were gathered from the radiology information system (RIS) and the clinical information system (CIS). We assessed the presence of sGS items and D-dimer blood test results in RIS from CTPA request forms and from clinical documentation in CIS. Results. Based on the RIS, there were 2.6% patients with high (sGS≥3) and 97.4% patients with low pre-test PE probability (sGS

Abstract Background Despite synchronization to respiration, respiration-navigated (RN) 3D turbo-spin-echo MRCP is limited by susceptibility to motion artifacts. The aim of this study was to assess the quality of pancreaticobiliary duct visualization of a non-RN MRCP alternative based on balanced steady-state free precession imaging (BSSFP) with overlapping slices compared with RN-MRCP. Methods This is a retrospective study on 50 patients without pancreaticobiliary duct disease receiving MRCP at 1.5 T. We performed an intraindividual comparison of coronal RN-MRCP with combined coronal and transverse BSSFP-MRCP. Image quality was scored by 3 readers for 6 pancreaticobiliary duct segments (3 pancreatic, 3 biliary) using a 6-point scale. A segment score of 3 or lower as assessed by at least 2 of 3 readers was defined as insufficient segment visualization. Nonparametric tests and interrater reliability testing were used for statistical analysis. Results Overall duct visualization averaged over all readers was scored with 4.5 ± 1.1 for RN-MRCP (pancreatic, 4.1 ± 0.5; biliary, 5.0 ± 0.4) and 4.9 ± 0.9 for combined coronal and transverse BSSFP-MRCP (pancreatic, 4.6 ± 0.6; biliary, 5.1 ± 0.6), respectively (p

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

Abstract Irreversible electroporation (IRE) is an ablation procedure in which cell death is induced by ultrashort electrical pulses. In this unicentric retrospective study we investigated the influence of needle positioning on ablation success. 15 IREs with residual tumor after ablation, detected in the first follow-up MRI, were included, and compared with 30 successful ablations. Evaluation of needle geometry revealed significantly higher values for needle divergence (NDiv, 7.0° vs. 3.7°, p = 0.02), tumor-center-to-ablation-center distance (TACD, 11.6 vs. 3.2 mm, p

Abstract Objectives Our aim was to develop a structured reporting concept (structured oncology report, SOR) for general follow-up assessment of cancer patients in clinical routine. Furthermore, we analysed the report quality of SOR compared to conventional reports (CR) as assessed by referring oncologists. Methods SOR was designed to provide standardised layout, tabulated tumour burden documentation and standardised conclusion using uniform terminology. A software application for reporting was programmed to ensure consistency of layout and vocabulary and to facilitate utilisation of SOR. Report quality was analysed for 25 SOR and 25 CR retrospectively by 6 medical oncologists using a 7-point scale (score 1 representing the best score) for 6 questionnaire items addressing different elements of report quality and overall satisfaction. A score of ≤ 3 was defined as a positive rating. Results In the first year after full implementation, 7471 imaging examinations were reported using SOR. The proportion of SOR in relation to all oncology reports increased from 49 to 95% within a few months. Report quality scores were better for SOR for each questionnaire item (p < 0.001 each). Averaged over all questionnaire item scores were 1.98 ± 1.22 for SOR and 3.05 ± 1.93 for CR (p < 0.001). The overall satisfaction score was 2.15 ± 1.32 for SOR and 3.39 ± 2.08 for CR (p < 0.001). The proportion of positive ratings was higher for SOR (89% versus 67%; p < 0.001). Conclusions Department-wide structured reporting for follow-up imaging performed for assessment of anticancer treatment efficacy is feasible using a dedicated software application. Satisfaction of referring oncologist with report quality is superior for structured reports.

Purpose To explore the typical magnetic resonance imaging (MRI) pattern of osteoblastoma (OB) after radiofrequency ablation (RFA) treatment and to identify signs indicating treatment success or relapse. Materials and methods Forty-four follow-up MRI examinations of 15 patients with OB who had undergone 19 RFA procedures were analyzed retrospectively. An early follow-up group (1–4 months after RFA) and a late follow-up group (8–131 months after RFA) were established. The groups were further subdivided according to treatment success. Images were analyzed for the presence of central nidus enhancement (CNE), peripheral nidus enhancement (PNE), perifocal bone marrow edema (PBME) and fatty nidus conversion (FNC). Results The early follow-up MRI image from every patient in the treatment success group exhibited a target-like appearance with negative CNE and positive PNE or PBME. PNE and PBME were observed in 93% and 71% of the early follow-up images, respectively. A target-like appearance was observed in 25% of the late follow-up images, and PNE and PBME were each observed in 20% of these images. FNC was not observed in the early follow-up images, but was seen in 55% of the late follow-up images. All three MRI images of the patients exhibiting clinical recurrence demonstrated strong CNE, PNE and extensive PMBE, which was in contrast to the images of the patients exhibiting treatment success. Conclusion A target-like appearance of OB in early follow-up MRI examination indicates treatment success. PNE and PBME typically reduce over time and can lead to FNC in successfully treated patients. CNE recurrence, PNE and extensive PBME are signs of relapse.

ObjectivesTo evaluate the prognostic value of fully automatic lung quantification based on spectral computed tomography (CT) and laboratory parameters for combined outcome prediction in COVID-19 pneumonia.MethodsCT images of 53 hospitalized COVID-19 patients including virtual monochromatic reconstructions at 40-140keV were analyzed using a fully automated software system. Quantitative CT (QCT) parameters including mean and percentiles of lung density, fibrosis index (FIBI-700, defined as the percentage of segmented lung voxels ≥-700 HU), quantification of ground-glass opacities and well-aerated lung areas were analyzed. QCT parameters were correlated to laboratory and patient outcome parameters (hospitalization, days on intensive care unit, invasive and non-invasive ventilation).ResultsBest correlations were found for laboratory parameters LDH (r = 0.54), CRP (r = 0.49), Procalcitonin (r = 0.37) and partial pressure of oxygen (r = 0.35) with the QCT parameter 75th percentile of lung density. LDH, Procalcitonin, 75th percentile of lung density and FIBI-700 were the strongest independent predictors of patients' outcome in terms of days of invasive ventilation. The combination of LDH and Procalcitonin with either 75th percentile of lung density or FIBI-700 achieved a r2 of 0.84 and 1.0 as well as an area under the receiver operating characteristic curve (AUC) of 0.99 and 1.0 for the prediction of the need of invasive ventilation.ConclusionsQCT parameters in combination with laboratory parameters could deliver a feasible prognostic tool for the prediction of invasive ventilation in patients with COVID-19 pneumonia.