Performance of the beta-glucan test for the diagnosis of invasive fusariosis and scedosporiosis: a meta-analysis.

The (1→3)-ß-D-glucan (BDG) is a component of the fungal cell wall that can be detected in serum and used as an adjunctive tool for the diagnosis of invasive mold infections (IMI) in patients with hematologic cancer or other immunosuppressive conditions. However, its use is limited by modest sensitivity/specificity, inability to differentiate between fungal pathogens, and lack of detection of mucormycosis. Data about BDG performance for other relevant IMI, such as invasive fusariosis (IF) and invasive scedosporiosis/lomentosporiosis (IS) are scarce. The objective of this study was to assess the sensitivity of BDG for the diagnosis of IF and IS through systematic literature review and meta-analysis. Immunosuppressed patients diagnosed with proven or probable IF and IS, with interpretable BDG data were eligible. A total of 73 IF and 27 IS cases were included. The sensitivity of BDG for IF and IS diagnosis was 76.7% and 81.5%, respectively. In comparison, the sensitivity of serum galactomannan for IF was 27%. Importantly, BDG positivity preceded the diagnosis by conventional methods (culture or histopathology) in 73% and 94% of IF and IS cases, respectively. Specificity was not assessed because of lacking data. In conclusion, BDG testing may be useful in patients with suspected IF or IS. Combining BDG and galactomannan testing may also help differentiating between the different types of IMI.

IF and IS are severe fungal infections for which diagnosis is often delayed. This meta-analysis shows that beta-glucan testing in serum had a sensitivity of about 80% for IF/IS and could detect the disease earlier compared to conventional diagnostic tests.

Multimodality imaging and 3D-printing of a thoraco-abdominal aortic aneurysm eroding into the spine.

A rare case of a previously treated thoraco-abdominal aortic aneurysm eroding into the thoracic spine is described. Initially, several follow-up CT angiography scans showed an increasing aneurysm sack, but no endoleak could be depicted. Then, a new rapidly developing erosion into the thoracic spine was noted. MRI imaging excluded any other underlying infectious or malignant process. Additional contrast-enhanced ultrasound excluded an endoleak. A 3D-printed model of the aneurysm and spine and cinematic renderings were created to improve visualization. She underwent relining of the thoracic stent graft. Follow-up imaging showed a stable aneurysm size and no progression of the vertebral erosions.

Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study.

Purpose: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. Methods: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. Results: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. Conclusions: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive.

The Swiss Approach - feasibility of a national low-dose CT lung cancer screening program.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths in Switzerland. Despite this, there is no lung cancer screening program in the country. In the United States, low-dose computed tomography (LDCT) lung cancer screening is partially established and endorsed by guidelines. Moreover, evidence is growing that screening reduces lung cancer-related mortality and this was recently shown in a large European randomized controlled trial. Implementation of a lung cancer screening program, however, is challenging and depends on many country-specific factors. The goal of this article is to outline a potential Swiss lung cancer screening program. FRAMEWORK: An exhaustive literature review on international screening models as well as interviews and site visits with international experts were initiated. Furthermore, workshops and interviews with national experts and stakeholders were conducted to share experiences and to establish the basis for a national Swiss lung cancer screening program. SCREENING APPROACH: General practitioners, pulmonologists and the media should be part of the recruitment process. Decentralisation of the screening might lead to a higher adherence rate. To reduce stigmatisation, the screening should be integrated in a "lung health check". Standardisation and a common quality level are mandatory. The PLCOm2012 risk calculation model with a threshold of 1.5% risk for developing cancer in the next six years should be used in addition to established inclusion criteria. Biennial screening is preferred. LUNG RADS and NELSON+ are applied as classification models for lung nodules. CONCLUSION: Based on data from recent studies, literature research, a health technology assessment, the information gained from this project and a pilot study the Swiss Interest Group for lung cancer screening (CH-LSIG) recommends the timely introduction of a systematic lung cancer screening program in Switzerland. The final decision is for the Swiss Cancer Screening Committee to make.

Non-invasive evaluation of new-onset atrial fibrillation after cardiac surgery: a protocol for the BigMap study.

AIMS: New-onset atrial fibrillation (NOAF) is the most common complication after cardiac surgery, occurring in 25-50% of patients. It is associated with post-operative stroke, increased mortality, prolonged hospital length of stay, and higher treatment costs. Previous small observational studies have identified the left atrium as a source of the electrical rotors and foci maintaining NOAF, but confirmation by a large prospective clinical study is still missing. The aim of the proposed study is to investigate whether the source of NOAF lies in the left atrium. The correct identification of NOAF-maintaining structures in cardiac surgical patients might offer potential therapeutic targets for prophylactic perioperative ablation strategies. METHODS AND RESULTS: This is a prospective single-centre observational study of patients developing NOAF after cardiac surgery. The primary outcome is the description of NOAF-maintaining structures within the atria. Key secondary outcomes include overall mortality, intensive care unit length of stay, hospital-ventilator-free days, and proportion of persistent NOAF. In NOAF patients, the non-invasive electrophysiological mapping will be conducted using a 252-electrode electrocardiogram vest. After mapping, a low-dose computed tomography scan of the chest will be performed to integrate the electrophysiological mapping results into a 3D picture of the heart. The study will include approximately 570 patients, of whom 30% (n = 170) are expected to develop NOAF. Sample size calculation revealed that 157 NOAF patients are necessary to assess the primary outcome. Patients will be tracked for a total of 5 years. CONCLUSIONS: This is the largest prospective study to date describing the electrophysiological mechanisms of NOAF using non-invasive mapping.

Considerations on Baseline Generation for Imaging AI Studies Illustrated on the CT-Based Prediction of Empyema and Outcome Assessment.

For AI-based classification tasks in computed tomography (CT), a reference standard for evaluating the clinical diagnostic accuracy of individual classes is essential. To enable the implementation of an AI tool in clinical practice, the raw data should be drawn from clinical routine data using state-of-the-art scanners, evaluated in a blinded manner and verified with a reference test. Three hundred and thirty-five consecutive CTs, performed between 1 January 2016 and 1 January 2021 with reported pleural effusion and pathology reports from thoracocentesis or biopsy within 7 days of the CT were retrospectively included. Two radiologists (4 and 10 PGY) blindly assessed the chest CTs for pleural CT features. If needed, consensus was achieved using an experienced radiologist's opinion (29 PGY). In addition, diagnoses were extracted from written radiological reports. We analyzed these findings for a possible correlation with the following patient outcomes: mortality and median hospital stay. For AI prediction, we used an approach consisting of nnU-Net segmentation, PyRadiomics features and a random forest model. Specificity and sensitivity for CT-based detection of empyema (n = 81 of n = 335 patients) were 90.94 (95%-CI: 86.55-94.05) and 72.84 (95%-CI: 61.63-81.85%) in all effusions, with moderate to almost perfect interrater agreement for all pleural findings associated with empyema (Cohen's kappa = 0.41-0.82). Highest accuracies were found for pleural enhancement or thickening with 87.02% and 81.49%, respectively. For empyema prediction, AI achieved a specificity and sensitivity of 74.41% (95% CI: 68.50-79.57) and 77.78% (95% CI: 66.91-85.96), respectively. Empyema was associated with a longer hospital stay (median = 20 versus 14 days), and findings consistent with pleural carcinomatosis impacted mortality.

From cold-blooded reptiles to embryological remnants: Persistent myocardial sinusoids.

In nature, basically 2 types of myocardial vascular patterns exist: the sinusoidal and the coronary type. In the sinusoidal type, the sinusoid is completely fed by blood coming directly from the ventricle through a spongy sinusoidal network. This pattern is found in cold-blooded animals and in the early embryologic development of human (warm-blooded) hearts. A 61-year-old man with atrial fibrillation developed severe tachymyopathy with a severely reduced left-ventricular ejection fraction (LVEF) of 20%. The patient had no history of prior heart surgery or other cardiac interventions. He was referred for a computed tomography (CT) scan for assessment of pulmonary vein anatomy prior to their isolation. Incidentally, a focal myocardial defect of the midventricular infero-septal wall with tail-like extension into the right ventricular cavity was detected. In a cardiac magnetic resonance (CMR) scan there was no evidence of a myocardial infarction or fibrosis. In the absence of a ventricular septal defect by CT, CMR and echocardiography the diagnosis of a persistent myocardial sinusoid was evident. In this case, we used state-of-the art methods for pathology visualization, illustrating the effectiveness of CT and CMR in the precise detection and differential diagnosis of myocardial anomalies including a multi-coloured 3D-printed model that may further enhance visuospatial appreciation of those anomalies.

Quantitative myocardial perfusion 82Rb-PET assessed by hybrid PET/coronary-CT: Normal values and diagnostic performance.

PURPOSE: We aimed to assess normal values for quantified myocardial blood flow (MBF) on a hybrid PET/coronary-CT scanner and to test their diagnostic performance in patients with suspected CAD. MATERIALS AND METHODS: Patients underwent 82Rb-PET/CT and integrated CT-based coronary angiography (CCTA) and were classified as normal (no stenosis), with non-obstructive stenosis (< 50%) and with CAD (≥ 50%). Global and regional stress MBF (sMBF), rest MBF and myocardial flow reserve (MFR) were calculated. Ischemia was defined as SDS ≥ 2, severe ischemia as SDS ≥ 7. RESULTS: 357 consecutive patients were included. Global sMBF and MFR were higher in normal patients than in patients with CAD (3.61 ± 0.71 vs 3.04 ± 0.77, P < 0.0001; 3.08 ± 0.84 vs 2.68 ± 0.79, P = 0.0001), but not different compared to patients with non-obstructive stenosis (3.61 ± 0.71 vs 3.43 ± 0.69, P = 0.052; 3.08 ± 0.84 vs 2.99 ± 0.82, P = 0.45). sMBF yielded superior accuracy over MFR in identifying both ischemia (AUC 0.74 vs 0.62, P = 0.003) and severe ischemia (AUC 0.88 vs 0.78, P = 0.012). Optimal threshold for global sMBF to rule out myocardial ischemia was 3.5 mL g-1 min-1. CONCLUSIONS: Normal quantitative values are provided. Global sMBF provided higher diagnostic accuracy than MFR. Using sMBF-threshold of 3.5 mL·g-1·min-1 on 82Rb-PET/CT yielded similar NPV (96%) as CCTA to rule out CAD. Hence, resting scan could be omitted in patients with sMBF values above reference.

Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium.

BACKGROUND: Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deploying a fully automatic black-box, we propose to incorporate the automated LA volumetry into a human-centric interactive image-analysis process. METHODS AND RESULTS: Atri-U, an automated data analysis pipeline for long-axis cardiac cine images, computes the atrial volume by: (i) detecting the end-systolic frame, (ii) outlining the endocardial borders of the LA, (iii) localizing the mitral annular hinge points and constructing the longitudinal atrial diameters, equivalent to the usual workup done by clinicians. In every step human interaction is possible, such that the results provided by the algorithm can be accepted, corrected, or re-done from scratch. Atri-U was trained and evaluated retrospectively on a sample of 300 patients and then applied to a consecutive clinical sample of 150 patients with various heart conditions. The agreement of the indexed LA volume between Atri-U and two experts was similar to the inter-rater agreement between clinicians (average overestimation of 0.8 mL/m2 with upper and lower limits of agreement of - 7.5 and 5.8 mL/m2, respectively). An expert cardiologist blinded to the origin of the annotations rated the outputs produced by Atri-U as acceptable in 97% of cases for step (i), 94% for step (ii) and 95% for step (iii), which was slightly lower than the acceptance rate of the outputs produced by a human expert radiologist in the same cases (92%, 100% and 100%, respectively). The assistance of Atri-U lead to an expected reduction in reading time of 66%-from 105 to 34 s, in our in-house clinical setting. CONCLUSIONS: Our proposal enables automated calculation of the maximum LA volume approaching human accuracy and precision. The optional user interaction is possible at each processing step. As such, the assisted process sped up the routine CMR workflow by providing accurate, precise, and validated measurement results.

Fully automated guideline-compliant diameter measurements of the thoracic aorta on ECG-gated CT angiography using deep learning.

BACKGROUND: Manually performed diameter measurements on ECG-gated CT-angiography (CTA) represent the gold standard for diagnosis of thoracic aortic dilatation. However, they are time-consuming and show high inter-reader variability. Therefore, we aimed to evaluate the accuracy of measurements of a deep learning-(DL)-algorithm in comparison to those of radiologists and evaluated measurement times (MT). METHODS: We retrospectively analyzed 405 ECG-gated CTA exams of 371 consecutive patients with suspected aortic dilatation between May 2010 and June 2019. The DL-algorithm prototype detected aortic landmarks (deep reinforcement learning) and segmented the lumen of the thoracic aorta (multi-layer convolutional neural network). It performed measurements according to AHA-guidelines and created visual outputs. Manual measurements were performed by radiologists using centerline technique. Human performance variability (HPV), MT and DL-performance were analyzed in a research setting using a linear mixed model based on 21 randomly selected, repeatedly measured cases. DL-algorithm results were then evaluated in a clinical setting using matched differences. If the differences were within 5 mm for all locations, the cases was regarded as coherent; if there was a discrepancy >5 mm at least at one location (incl. missing values), the case was completely reviewed. RESULTS: HPV ranged up to ±3.4 mm in repeated measurements under research conditions. In the clinical setting, 2,778/3,192 (87.0%) of DL-algorithm's measurements were coherent. Mean differences of paired measurements between DL-algorithm and radiologists at aortic sinus and ascending aorta were -0.45±5.52 and -0.02±3.36 mm. Detailed analysis revealed that measurements at the aortic root were over-/underestimated due to a tilted measurement plane. In total, calculated time saved by DL-algorithm was 3:10 minutes/case. CONCLUSIONS: The DL-algorithm provided coherent results to radiologists at almost 90% of measurement locations, while the majority of discrepent cases were located at the aortic root. In summary, the DL-algorithm assisted radiologists in performing AHA-compliant measurements by saving 50% of time per case.

Integration of transbronchial cryobiopsy into multidisciplinary board decision: a single center analysis of one hundred consecutive patients with interstitial lung disease.

BACKGROUND: Transbronchial cryobiopsy in the evaluation of patients with interstitial lung diseases (ILD) is expected to reduce the need for surgical lung biopsy (SLB). OBJECTIVE: To evaluate the diagnostic value of cryobiopsy in combination with bronchoalveolar lavage (BAL), radiologic and clinical data in patients with ILD. METHODS: Between 08/15 and 01/20 patients with ILD underwent cryobiopsy if they: did not have (i) an usual interstitial pneumonia (UIP)-pattern on CT, (ii) predominant ground-glass opacities suggesting alveolitis, (iii) findings suggestive of sarcoidosis on CT, or if they had (i) a CT showing UIP-pattern, but had findings suggesting alternative diagnosis than idiopathic pulmonary fibrosis (IPF), or (ii) had previous non-diagnostic conventional transbronchial forceps biopsy. Histological findings were integrated into the multidisciplinary team discussion (MDTD) and a diagnostic consensus was sought. RESULTS: One hundred patients underwent cryobiopsy. In 88/100 patients, cryobiopsy was representative with diagnostic findings in 45/88 and non-specific histological findings in 43/88 patients. In 25/43 with non-specific findings, a consensus diagnosis was reached after MDTD integrating BAL, radiologic and clinical data; eight of the remaining 18 patients with non-specific findings were referred to SLB. In 12/100 patients cryobiopsy was not representative and three of these patients were also referred to SLB. In 7/11 patients (64%) SLB was diagnostic. Complications of cryobiopsy included pneumothorax (14%) and locally controlled bleeding (24%). CONCLUSIONS: The diagnostic yield of cryobiopsy was 70%:45% of cryobiopsies were diagnostic based on histology alone and an additional 25% provided non-specific, but valuable findings allowing a consensus diagnosis after MDTD. Our data demonstrate that the diagnostic value of cryobiopsy is high if combined with BAL, radiologic and clinical data.

Acute aortic dissection with entry tear at the aortic arch: long-term outcome.

OBJECTIVES: The goal was to evaluate outcomes after conservative or surgical treatment of acute aortic arch dissections. METHODS: Between January 2009 and December 2018, patients with a diagnosis of acute aortic dissection were analysed. Aortic arch aortic dissection was defined as a dissection with an isolated entry tear at the aortic arch with no involvement of the ascending aorta. RESULTS: Aortic arch dissection was diagnosed in 31 patients (age 59 ± 11 years). Surgical intervention was performed in 13 (41.9%) cases. Overall in-hospital mortality was 3% (n = 1), and all deaths occurred in the conservative group (n = 1; 6%), whereas the overall stroke rate was 3% (n = 1), and all strokes occurred in the group treated surgically (n = 1; 8%). Surgical repair was necessary for the following conditions: end-organ malperfusion (n = 9; 69%), impending rupture (n = 3; 23%) and dilatation of the aorta with ongoing pain refractory to medical treatment (n = 1; 8%). Overall survival at the end of the follow-up period was 71%, with 77% in the surgical group and 63% in the conservative group (P = 0.91). Freedom from surgical intervention was 71%, with 82% in the surgical and 63% in the conservative group (P = 0.21), and freedom from a neurological event was 88%, with 89% versus 89% (P = 0.68) in the surgical and conservative groups, respectively. CONCLUSIONS: Aortic arch dissection is a rare pathological condition that is one of the most challenging decision-making entities. Patients manifesting an uneventful course not requiring a surgical intervention during a hospital stay were at a higher risk for aorta-related intervention during the follow-up period. The treatment modality had no impact on survival or on the incidence of a neurological event.

Impact of Modified Frozen Elephant Trunk Procedure on Downstream Aorta Remodeling in Acute Aortic Dissection: CT Scan Follow-Up.

OBJECTIVES: The aim was to evaluate the impact of a modified frozen elephant trunk procedure (mFET) on remodeling of the downstream aorta following acute aortic dissections. METHODS: Over a period of 8 years, 205 patients (mean age 62.6 ± 12.6 years) underwent a mFET (n = 69, 33.7%) or isolated ascending aorta replacement (n = 136, 66.3%) (iAoA). Aortic diameter was assessed at the aortic arch (AoA), at the mid of the thoracic aorta (mThA), at the thoracoabdominal transition (ThAbd) and at the celiac trunk level (AbdA). RESULTS: Mean follow-up was 3.3 ± 2.6 years. In-hospital mortality was 14% (n = 28), 7% in mFET and 17% in the iAoA group (p = 0.08). At the end of the follow-up, overall survival was 84% (95% CI 70-92%) and 75% (65-82%) and freedom from aorta-related reoperation was 100% and 95% (88-98%) for mFET and iAoA, respectively. At iAoA, the average difference in diameter change per year between mFET and iAoA was for total lumen 0 mm (- 0.95 to 0.94 mm, p = 0.99), and for true lumen, it was 1.23 mm (- 0.09 to 2.55 mm) per year, p = 0.067. False lumen demonstrated a decrease in diameter in mFET as compared to iAoA by - 1.43 mm (- 2.75 to - 0.11 mm), p = 0.034. In mFET, at the aortic arch level the total lumen diameter decreased from 30.7 ± 4.8 mm to 30.1 ± 2.5 mm (Δr + 2.90 ± 3.64 mm) and in iAoA it increased from 31.8 ± 4.9 to 34.6 ± 5.9 mm (Δr + 2.88 ± 4.18 mm). CONCLUSION: The mFET procedure provides satisfactory clinical outcome at short term and mid-term and has a positive impact on aorta remodeling, especially at the level of the aortic arch.

CT and MR imaging prior to transcatheter aortic valve implantation: standardisation of scanning protocols, measurements and reporting-a consensus document by the European Society of Cardiovascular Radiology (ESCR).

Transcatheter aortic valve replacement (TAVR) is a minimally invasive alternative to conventional aortic valve replacement in symptomatic patients with severe aortic stenosis and contraindications to surgery. The procedure has shown to improve patient's quality of life and prolong short- and mid-term survival in high-risk individuals, becoming a widely accepted therapeutic option which has been integrated into current clinical guidelines for the management of valvular heart disease. Nevertheless, not every patient at high-risk for surgery is a good candidate for TAVR. Besides clinical selection, which is usually established by the Heart Team, certain technical and anatomic criteria must be met as, unlike in surgical valve replacement, annular sizing is not performed under direct surgical evaluation but on the basis of non-invasive imaging findings. Present consensus document was outlined by a working group of researchers from the European Society of Cardiovascular Radiology (ESCR) and aims to provide guidance on the utilisation of CT and MR imaging prior to TAVR. Particular relevance is given to the technical requirements and standardisation of the scanning protocols which have to be tailored to the remarkable variability of the scanners currently utilised in clinical practice; recommendations regarding all required pre-procedural measurements and medical reporting standardisation have been also outlined, in order to ensure quality and consistency of reported data and terminology. KEY POINTS: • To provide a reference document for CT and MR acquisition techniques, taking into account the significant technological variation of available scanners. • To review all relevant measurements that are required and define a step-by-step guided approach for the measurements of different structures implicated in the procedure. • To propose a CT/MR reporting template to assist in consistent communication between various sites and specialists involved in the procedural planning.

Early Prediction of Treatment Response of Neuroendocrine Hepatic Metastases after Peptide Receptor Radionuclide Therapy with 90Y-DOTATOC Using Diffusion Weighted and Dynamic Contrast-Enhanced MRI.

The purpose of this study was to determine if parameters derived from diffusion-weighted (DW-) and dynamic contrast-enhanced (DCE-) magnetic resonance imaging (MRI) can help to assess early response to peptide receptor radionuclide therapy (PRRT) with 90Y-DOTATOC in neuroendocrine hepatic metastases (NET-HM). Twenty patients (10 male; 10 female; mean age: 59.2 years) with NET-HM were prospectively enrolled in this single-center imaging study. DW-MRI and DCE-MRI studies were performed just before and 48 hours after therapy with 90Y-DOTATOC. Abdominal SPECT/CT was performed 24 hours after therapy. This MRI imaging and therapy session was repeated after a mean interval of 10 weeks. Up to four lesions per patient were evaluated. Response to therapy was evaluated using metastasis sizes at the first and second therapy session as standard for comparison (regressive, stable, and progressive). DW-MRI analysis included the apparent diffusion coefficient (ADC) and parameters related to intravoxel incoherent motion (IVIM), namely, diffusion (D), perfusion fraction (f) and pseudo-diffusion (D ∗ ). DCE-MRI analysis comprised Ktrans, v e and k ep. For statistical analysis of group differences, one-way analysis of variance (ANOVA) and appropriate post hoc testing was performed. A total of 51 lesions were evaluated. Seven of 51 lesions (14%) showed size progression, 18/51 (35%) regression, and 26/51 (51%) remained stable. The lesion-to-spleen uptake ratio in SPECT showed a decrease between the two treatment sessions that was significantly stronger in regressive lesions compared with stable (p = 0.013) and progressive lesions (p = 0.021). ANOVA showed significant differences in mean ADC after 48 h (p = 0.026), with higher ADC values for regressive lesions. Regarding IVIM, highest values for D at baseline were seen in regressive lesions (p = 0.023). In DCE-MRI, a statistically significant increase in v e after 10 weeks (p = 0.046) was found in regressive lesions. No differences were observed for the transfer constants Ktrans and k ep. Diffusion restriction quantified as ADC was able to differentiate regressive from progressive NET-HMs as early as 48 hours after PRRT. DW-MRI therefore may complement scintigraphy/SPECT for early assessment of response to PRRT. Assessment of perfusion parameters using IVIM and DCE-MRI did not show an additional benefit.

Centralized expert HRCT Reading in suspected idiopathic pulmonary fibrosis: Experience from an Eurasian teleradiology program.

PURPOSE: To share experience from a large, ongoing expert reading teleradiology program in Europe and Asia aiming at supporting referring centers to interpret high-resolution computed tomography (HRCT) with respect to presence of Usual Interstitial Pneumonia (UIP)-pattern in patients with suspected Idiopathic Pulmonary Fibrosis (IPF). METHOD: We analyzed data from 01/2014 to 05/2019, including HRCTs from 239 medical centers in 12 European and Asian countries that were transmitted to our Picture Archiving and Communication System (PACS) via a secured internet connection. Structured reports were generated in consensus by a radiologist with over 20 years of experience in thoracic imaging and a pulmonologist with specific expertise in interstitial lung disease according to current guidelines on IPF. Reports were sent to referring physicians. We evaluated patient characteristics, technical issues, report turnaround times and frequency of diagnoses. We also conducted a survey to collect feedback from referring physicians. RESULTS: HRCT image data from 703 patients were transmitted (53.5% male). Mean age was 63.7 years (SD:17). In 35.1% of all cases diagnosis was "UIP"/"Typical UIP". The mean report turnaround time was 1.7 days (SD:2.9). Data transmission errors occurred in 7.1%. Overall satisfaction rate among referring physicians was high (8.4 out of 10; SD:3.2). CONCLUSIONS: This Eurasian teleradiology program demonstrates the feasibility of cross-border teleradiology for the provision of state-of-the-art reporting despite heterogeneity of referring medical centers and challenges like data transmission errors and language barriers. We also point out important factors for success like the usage of structured reporting templates.

Evaluation of an AI-Powered Lung Nodule Algorithm for Detection and 3D Segmentation of Primary Lung Tumors.

Automated detection and segmentation is a prerequisite for the deployment of image-based secondary analyses, especially for lung tumors. However, currently only applications for lung nodules ≤3 cm exist. Therefore, we tested the performance of a fully automated AI-based lung nodule algorithm for detection and 3D segmentation of primary lung tumors in the context of tumor staging using the CT component of FDG-PET/CT and including all T-categories (T1-T4). FDG-PET/CTs of 320 patients with histologically confirmed lung cancer performed between 01/2010 and 06/2016 were selected. First, the main primary lung tumor within each scan was manually segmented using the CT component of the PET/CTs as reference. Second, the CT series were transferred to a platform with AI-based algorithms trained on chest CTs for detection and segmentation of lung nodules. Detection and segmentation performance were analyzed. Factors influencing detection rates were explored with binominal logistic regression and radiomic analysis. We also processed 94 PET/CTs negative for pulmonary nodules to investigate frequency and reasons of false-positive findings. The ratio of detected tumors was best in the T1-category (90.4%) and decreased continuously: T2 (70.8%), T3 (29.4%), and T4 (8.8%). Tumor contact with the pleura was a strong predictor of misdetection. Segmentation performance was excellent for T1 tumors (r = 0.908, p < 0.001) and tumors without pleural contact (r = 0.971, p < 0.001). Volumes of larger tumors were systematically underestimated. There were 0.41 false-positive findings per exam. The algorithm tested facilitates a reliable detection and 3D segmentation of T1/T2 lung tumors on FDG-PET/CTs. The detection and segmentation of more advanced lung tumors is currently imprecise due to the conception of the algorithm for lung nodules <3 cm. Future efforts should therefore focus on this collective to facilitate segmentation of all tumor types and sizes to bridge the gap between CAD applications for screening and staging of lung cancer.

Towards More Structure: Comparing TNM Staging Completeness and Processing Time of Text-Based Reports versus Fully Segmented and Annotated PET/CT Data of Non-Small-Cell Lung Cancer.

Results of PET/CT examinations are communicated as text-based reports which are frequently not fully structured. Incomplete or missing staging information can be a significant source of staging and treatment errors. We compared standard text-based reports to a manual full 3D-segmentation-based approach with respect to TNM completeness and processing time. TNM information was extracted retrospectively from 395 reports. Moreover, the RIS time stamps of these reports were analyzed. 2995 lesions using a set of 41 classification labels (TNM features + location) were manually segmented on the corresponding image data. Information content and processing time of reports and segmentations were compared using descriptive statistics and modelling. The TNM/UICC stage was mentioned explicitly in only 6% (n=22) of the text-based reports. In 22% (n=86), information was incomplete, most frequently affecting T stage (19%, n=74), followed by N stage (6%, n=22) and M stage (2%, n=9). Full NSCLC-lesion segmentation required a median time of 13.3 min, while the median of the shortest estimator of the text-based reporting time (R1) was 18.1 min (p=0.01). Tumor stage (UICC I/II: 5.2 min, UICC III/IV: 20.3 min, p < 0.001), lesion size (p < 0.001), and lesion count (n=1: 4.4 min, n=12: 37.2 min, p < 0.001) correlated significantly with the segmentation time, but not with the estimators of text-based reporting time. Numerous text-based reports are lacking staging information. A segmentation-based reporting approach tailored to the staging task improves report quality with manageable processing time and helps to avoid erroneous therapy decisions based on incomplete reports. Furthermore, segmented data may be used for multimedia enhancement and automatization.

"Exercise induced asthma" is not always asthma.

A 25 year old woman was referred to our center for further evaluation of an exercise-induced dyspnea. Moreover, the patient suffered from hoarseness and recurrent sinusitis and otitis. After initially finding nothing suspicious, a spiro-ergometry was performed. Interestingly, we saw a relevant limitation of the inspiratory flow-volume curve under maximal exercise load. Further evaluation (in particular the bronchoscopy and the resulting biopsies) led us to the final diagnosis of a granulomatosis with polyangiitis. After 4 weeks of an established therapy regime with prednisone and rituximab the prior detected subglottic stenosis and the inspiratory flow-volume curve limitation could no longer detected. We describe a rare differential diagnosis of an exercise-induced asthma and we underline the importance of a multimodal therapy concept. We highlight the critical nature of the flow-volume curve in spiro-ergometry under maximal exercise load. We recommend frequent follow-up control visits to monitor the subglottic stenosis.