Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry

Thyroid volumetry is crucial in the diagnosis, treatment, and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D and tracked 3D ultrasound with an automatic thyroid segmentation based on a deep neural network regarding inter- and intraobserver variability, time, and accuracy. Volume reference was MRI. 28 healthy volunteers (24—50 a) were scanned with 2D and 3D ultrasound (and by MRI) by three physicians (MD 1, 2, 3) with different experience levels (6, 4, and 1 a). In the 2D scans, the thyroid lobe volumes were calculated with the ellipsoid formula. A convolutional deep neural network (CNN) automatically segmented the 3D thyroid lobes. 26, 6, and 6 random lobe scans were used for training, validation, and testing, respectively. On MRI (T1 VIBE sequence) the thyroid was manually segmented by an experienced MD. MRI thyroid volumes ranged from 2.8 to 16.7ml (mean 7.4, SD 3.05). The CNN was trained to obtain an average Dice score of 0.94. The interobserver variability comparing two MDs showed mean differences for 2D and 3D respectively of 0.58 to 0.52ml (MD1 vs. 2), −1.33 to −0.17ml (MD1 vs. 3) and −1.89 to −0.70ml (MD2 vs. 3). Paired samples t-tests showed significant differences for 2D (p = .140, p = .002 and p = .002) and none for 3D (p = .176, p = .722 and p = .057). Intraobsever variability was similar for 2D and 3D ultrasound. Comparison of ultrasound volumes and MRI volumes showed a significant difference for the 2D volumetry of all MDs (p = .002, p = .009, p <.001), and no significant difference for 3D ultrasound (p = .292, p = .686, p = 0.091). Acquisition time was significantly shorter for 3D ultrasound. Tracked 3D ultrasound combined with a CNN segmentation significantly reduces interobserver variability in thyroid volumetry and increases the accuracy of the measurements with shorter acquisition times

Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance

Background: Radiographs of the sacroiliac joints are commonly used for the diagnosis and classification of axial spondyloarthritis. The aim of this study was to develop and validate an artificial neural network for the detection of definite radiographic sacroiliitis as a manifestation of axial spondyloarthritis (axSpA). Methods: Conventional radiographs of the sacroiliac joints obtained in two independent studies of patients with axSpA were used. The first cohort comprised 1553 radiographs and was split into training (n = 1324) and validation (n = 229) sets. The second cohort comprised 458 radiographs and was used as an independent test dataset. All radiographs were assessed in a central reading session, and the final decision on the presence or absence of definite radiographic sacroiliitis was used as a reference. The performance of the neural network was evaluated by calculating areas under the receiver operating characteristic curves (AUCs) as well as sensitivity and specificity. Cohen's kappa and the absolute agreement were used to assess the agreement between the neural network and the human readers. Results: The neural network achieved an excellent performance in the detection of definite radiographic sacroiliitis with an AUC of 0.97 and 0.94 for the validation and test datasets, respectively. Sensitivity and specificity for the cut-off weighting both measurements equally were 88% and 95% for the validation and 92% and 81% for the test set. The Cohen's kappa between the neural network and the reference judgements were 0.79 and 0.72 for the validation and test sets with an absolute agreement of 90% and 88%, respectively. Conclusion: Deep artificial neural networks enable the accurate detection of definite radiographic sacroiliitis relevant for the diagnosis and classification of axSpA

Local erythropoietin and endothelial progenitor cells improve regional cardiac function in acute myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Expanded endothelial progenitor cells (eEPC) improve global left ventricular function in experimental myocardial infarction (MI). Erythropoietin beta (EPO) applied together with eEPC may improve regional myocardial function even further by anti-apoptotic and cardioprotective effects. Aim of this study was to evaluate intramyocardial application of eEPCs and EPO as compared to eEPCs or EPO alone in experimental MI.</p> <p>Methods and Results</p> <p>In vitro experiments revealed that EPO dosed-dependently decreased eEPC and leukocyte apoptosis. Moreover, in the presence of EPO mRNA expression in eEPC of proangiogenic and proinflammatory mediators measured by TaqMan PCR was enhanced. Experimental MI was induced by ligation and reperfusion of the left anterior descending coronary artery of nude rats (n = 8-9). After myocardial transplantation of eEPC and EPO CD68+ leukocyte count and vessel density were enhanced in the border zone of the infarct area. Moreover, apoptosis of transplanted CD31 + TUNEL + eEPC was decreased as compared to transplantation of eEPCs alone. Regional wall motion of the left ventricle was measured using Magnetic Resonance Imaging. After injection of eEPC in the presence of EPO regional wall motion significantly improved as compared to injection of eEPCs or EPO alone.</p> <p>Conclusion</p> <p>Intramyocardial transplantation of eEPC in the presence of EPO during experimental MI improves regional wall motion. This was associated with an increased local inflammation, vasculogenesis and survival of the transplanted cells. Local application of EPO in addition to cell therapy may prove beneficial in myocardial remodeling.</p

Neurologic phenotypes associated with COL4A1/2 mutations

Objective: To characterize the neurologic phenotypes associated with COL4A1/2 mutations and to seek genotype–phenotype correlation. Methods: We analyzed clinical, EEG, and neuroimaging data of 44 new and 55 previously reported patients with COL4A1/COL4A2 mutations. Results: Childhood-onset focal seizures, frequently complicated by status epilepticus and resistance to antiepileptic drugs, was the most common phenotype. EEG typically showed focal epileptiform discharges in the context of other abnormalities, including generalized sharp waves or slowing. In 46.4% of new patients with focal seizures, porencephalic cysts on brain MRI colocalized with the area of the focal epileptiform discharges. In patients with porencephalic cysts, brain MRI frequently also showed extensive white matter abnormalities, consistent with the finding of diffuse cerebral disturbance on EEG. Notably, we also identified a subgroup of patients with epilepsy as their main clinical feature, in which brain MRI showed nonspecific findings, in particular periventricular leukoencephalopathy and ventricular asymmetry. Analysis of 15 pedigrees suggested a worsening of the severity of clinical phenotype in succeeding generations, particularly when maternally inherited. Mutations associated with epilepsy were spread across COL4A1 and a clear genotype–phenotype correlation did not emerge. Conclusion: COL4A1/COL4A2 mutations typically cause a severe neurologic condition and a broader spectrum of milder phenotypes, in which epilepsy is the predominant feature. Early identification of patients carrying COL4A1/COL4A2 mutations may have important clinical consequences, while for research efforts, omission from large-scale epilepsy sequencing studies of individuals with abnormalities on brain MRI may generate misleading estimates of the genetic contribution to the epilepsies overall

Multiparametric PET and MRI of myocardial damage after myocardial infarction: correlation of integrin αvβ3 expression and myocardial blood flow

PURPOSE Increased angiogenesis after myocardial infarction is considered an important favorable prognostic parameter. The αvβ3 integrin is a key mediator of cell-cell and cell-matrix interactions and an important molecular target for imaging of neovasculature and repair processes after MI. Thus, imaging of αvβ3 expression might provide a novel biomarker for assessment of myocardial angiogenesis as a prognostic marker of left ventricular remodeling after MI. Currently, there is limited data available regarding the association of myocardial blood flow and αvβ3 integrin expression after myocardial infarction in humans. METHODS Twelve patients were examined 31 ± 14 days after MI with PET/CT using [$^{18}$F]Galacto-RGD and [$^{13}$N]NH$_{3}$ and with cardiac MRI including late enhancement on the same day. Normal myocardium (remote) and areas of infarction (lesion) were identified on the [$^{18}$F]Galacto-RGD PET/CT images by correlation with [$^{13}$N]NH$_{3}$ PET and cardiac MRI. Lesion/liver-, lesion/blood-, and lesion/remote ratios were calculated. Blood flow and [$^{18}$F]Galacto-RGD uptake were quantified and correlated for each myocardial segment (AHA 17-segment model). RESULTS In 5 patients, increased [$^{18}$F]Galacto-RGD uptake was notable within or adjacent to the infarction areas with a lesion/remote ratio of 46% (26-83%; lesion/blood 1.15 ± 0.06; lesion/liver 0.61 ± 0.18). [$^{18}$F]Galacto-RGD uptake correlated significantly with infarct size (R = 0.73; p = 0.016). Moreover, it correlated significantly with restricted blood flow for all myocardial segments (R = - 0.39; p < 0.0001) and even stronger in severely hypoperfused areas (R = - 0.75; p < 0.0001). CONCLUSION [$^{18}$F]Galacto-RGD PET/CT allows the visualization and quantification of myocardial αvβ3 expression as a key player in angiogenesis in a subset of patients after MI. αvβ3 expression was more pronounced in patients with larger infarcts and was generally more intense but not restricted to areas with more impaired blood flow, proving that tracer uptake was largely independent of unspecific perfusion effects. Based on these promising results, larger prospective studies are warranted to evaluate the potential of αvβ3 imaging for assessment of myocardial angiogenesis and prediction of ventricular remodeling

A Model for Optimizing Strategies for Controlling Ground-Level Ozone in Europe

In the preparation process for the Second Sulfur Protocol of the Convention on Longrange Transboundary Air Pollution, integrated assessment models have played an important role in identifying cost-effective strategies for reducing SO 2 emissions in Europe. Applying this effect-based approach to other environmental problems (e.g., photo-oxidants) seems appealing. In view of the timetable adopted for the current preparation of an updated Protocol on emissions of nitrogen oxides, an integrated assessment tool for ozone is required in the near future. The paper presents some core elements of an integrated assessment model for tropospheric ozone in Europe, with elements on emissions, emission control technologies and costs, ozone formation and environmental impacts. The focus of the paper is on a `reduced-form&apos; model describing the relationships between the precursor emissions and long-term concentrations of ground-level ozone. This reduced-form model has been developed from a l..