Increasing demand response (DR) from households, industry and tertiary sector may provide substantial flexibility in renewable-based energy systems, but the deployment of DR is currently limited. ...This study examines the future economic potential DR in the renewable rich northern European region, and also analyses power markets impacts of large-scale DR deployment in the region. For the quantifications, the energy system model BALMOREL is used, modified to include a detailed temporal modelling of available DR potentials. Results show that among the DR options analysed, space heating and water heating provide the highest shares of loads shifted. The overall demand response potential is particularly high in Norway and Sweden, due to wide-spread electric space- and water heating. Low variable costs make these DR applications economically feasible for deployment, despite high supply-side flexibility provided by regulated hydro power. DR may contribute to peak shaving of up to 18.6% of total peak load in 2050. Revenues from DR-application yield very different results depending on techno-economic parameters, potentials and the price volatility in the various analysed market areas. Results show an insignificant change in CO2 emissions between scenarios with and without demand response.
•Economics of demand response and effect on peak load for the Nordics are analysed.•Demand response in water and space heating is economically feasible in the Nordics.•Demand response can decrease peak load by up to 18.6% in 2050.•Demand response decreases investments into peak generation and battery storage.
Due to the low permeability of many shale reservoirs, multi-stage hydraulic fracturing in horizontal wells is used to increase the productive, stimulated reservoir volume. However, each created ...hydraulic fracture alters the stress field around it, and subsequent fractures are affected by the stress field from previous fractures. The results of a numerical evaluation of the effect of stress field changes (stress shadowing), as a function of natural fracture and geomechanical properties, are presented, including a detailed evaluation of natural fracture shear failure (and, by analogy, the generated microseismicity) due to a created hydraulic fracture. The numerical simulations were performed using continuum and discrete element modeling approaches in both mechanical-only and fully coupled, hydro-mechanical modes. The results show the critical impacts that the stress field changes from a created hydraulic fracture have on the shear of the natural fracture system, which in-turn, significantly affects the success of the hydraulic fracture stimulation. Furthermore, the results provide important insight into: the role of completion design (stage spacing) and operational parameters (rate, viscosity, etc.) on the possibility of enhancing the stimulation of the natural fracture network (‘complexity’); the mechanisms that generate the microseismicity that occurs during a hydraulic fracture stimulation; and the interpretation of the generated microseismicity in relation to the volume of stimulated reservoir formation.
This study evaluates inter-site and intra-site reproducibility at ten different 7 T sites for quantitative brain imaging.
Two subjects – termed the “traveling heads” – were imaged at ten different 7 ...T sites with a harmonized quantitative brain MR imaging protocol. In conjunction with the system calibration, MP2RAGE, QSM, CEST and multi-parametric mapping/relaxometry were examined.
Quantitative measurements with MP2RAGE showed very high reproducibility across sites and subjects, and errors were in concordance with previous results and other field strengths. QSM had high inter-site reproducibility for relevant subcortical volumes. CEST imaging revealed systematic differences between the sites, but reproducibility was comparable to results in the literature. Relaxometry had also very high agreement between sites, but due to the high sensitivity, differences caused by different applications of the B1 calibration of the two RF coil types used were observed.
Our results show that quantitative brain imaging can be performed with high reproducibility at 7 T and with similar reliability as found at 3 T for multicenter studies of the supratentorial brain.
18F-FDG-PET/CT is standard to assess response in Hodgkin lymphoma by quantifying metabolic activity with the Deauville score. PET/CT, however, is time-consuming, cost-extensive, linked to high ...radiation and has a low availability. As an alternative, we investigated radiomics from non-contrast-enhanced computed tomography (NECT) scans. 75 PET/CT examinations of 43 patients on two different scanners were included. Target lesions were classified as Deauville score 4 positive (DS4+) or negative (DS4-) based on their SUVpeak and then segmented in NECT images. From these segmentations, 107 features were extracted with PyRadiomics. All further statistical analyses were then performed scanner-wise: differences between DS4+ and DS4- manifestations were assessed with the Mann-Whitney-U-test and single feature performances with the ROC-analysis. To further verify the reliability of the results, the number of features was reduced using different techniques. The feature median showed a high sensitivity for DS4+ manifestations on both scanners (scanner A: 0.91, scanner B: 0.85). It furthermore was the only feature that remained in both datasets after applying different feature reduction techniques. The feature median from NECT concordantly has a high sensitivity for DS4+ Hodgkin manifestations on two different scanners and thus could provide a surrogate for increased metabolic activity in PET/CT.
We aimed to evaluate radiomic features’ stability across different region of interest (ROI) sizes in CT and MR images. We chose a phantom with a homogenous internal structure so no differences for a ...feature extracted from ROIs of different sizes would be expected. For this, we scanned a plastic cup filled with sodium chloride solution ten times in CT and per MR sequence (T1-weighted-gradient-echo and T2-weighted-turbo-inversion-recovery-magnitude). We placed sphere-shaped ROIs of different diameters (4, 8, and 16 mm, and 4, 8, and 16 pixels) into the phantom’s center. Features were extracted using PyRadiomics. We assessed feature stability across ROI sizes with overall concordance correlation coefficients (OCCCs). Differences were tested for significance with the Mann–Whitney U-test. Of 93 features, 87 T1w-derived, 87 TIRM-derived, and 70 CT-derived features were significantly different between ROI sizes. Among MR-derived features, OCCCs showed excellent (>0.90) agreement for mean, median, and root mean squared for ROI sizes between 4 and 16 mm and pixels. We further observed excellent agreement for 10th and 90th percentile in T1w and 10th percentile in T2w TIRM images. There was no excellent agreement among the OCCCs of CT-derived features. In summary, many features indicated significant differences and only few showed excellent agreement across varying ROI sizes, although we examined a homogenous phantom. Since we considered a small phantom in an experimental setting, further studies to investigate this size effect would be necessary for a generalization. Nevertheless, we believe knowledge about this effect is crucial in interpreting radiomics studies, as features that supposedly discriminate disease entities may only indicate a systematic difference in ROI size.
Splenomegaly is a common cross-sectional imaging finding with a variety of differential diagnoses. This study aimed to evaluate whether a deep learning model could automatically segment the spleen ...and identify the cause of splenomegaly in patients with cirrhotic portal hypertension versus patients with lymphoma disease. This retrospective study included 149 patients with splenomegaly on computed tomography (CT) images (77 patients with cirrhotic portal hypertension, 72 patients with lymphoma) who underwent a CT scan between October 2020 and July 2021. The dataset was divided into a training (
= 99), a validation (
= 25) and a test cohort (
= 25). In the first stage, the spleen was automatically segmented using a modified U-Net architecture. In the second stage, the CT images were classified into two groups using a 3D DenseNet to discriminate between the causes of splenomegaly, first using the whole abdominal CT, and second using only the spleen segmentation mask. The classification performances were evaluated using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Occlusion sensitivity maps were applied to the whole abdominal CT images, to illustrate which regions were important for the prediction. When trained on the whole abdominal CT volume, the DenseNet was able to differentiate between the lymphoma and liver cirrhosis in the test cohort with an AUC of 0.88 and an ACC of 0.88. When the model was trained on the spleen segmentation mask, the performance decreased (AUC = 0.81, ACC = 0.76). Our model was able to accurately segment splenomegaly and recognize the underlying cause. Training on whole abdomen scans outperformed training using the segmentation mask. Nonetheless, considering the performance, a broader and more general application to differentiate other causes for splenomegaly is also conceivable.
Abstract Advances in timing detector technology require new specialized readout electronics. Applications demand below 10 ps time of arrival resolution and low power for a low repetition rate. A ...possible path to achieve O(10 ps) time resolution is an integrated chip using Silicon Germanium (SiGe) technology. Using DoE SBIR funding, Anadyne, Inc., in collaboration with UC Santa Cruz, has developed a prototype SiGe front-end readout chip optimized for low power and timing resolution. Two versions of the chip were produced with performance in simulation: a more power version with 10 ps resolution at 5 fC with 1.1 mW/channel, and a less power version with 10 ps resolution at 8 fC with 0.6 mW/channel. The chip was produced at Tower Semiconductor with 350 nm technology. The ASIC from the prototype run shows good performance: a rise time of 0.7–1 ns and 25 mV per fC response with RMS noise <1 mV. Simulation and results from the prototype will be reported in this paper.
Background
In radiomics studies, differences in the volume of interest (VOI) are often inevitable and may confound the extracted features. We aimed to correct this confounding effect of VOI ...variability by applying parametric maps with a fixed voxel size.
Methods
Ten scans of a cup filled with sodium chloride solution were scanned using a multislice computed tomography (CT) unit. Sphere-shaped VOIs with different diameters (4, 8, or 16 mm) were drawn centrally into the phantom. A total of 93 features were extracted conventionally from the original images using PyRadiomics. Using a self-designed and pretested software tool, parametric maps for the same 93 features with a fixed voxel size of 4 mm
3
were created. To retrieve the feature values from the maps, VOIs were copied from the original images to preserve the position. Differences in feature quantities between the VOI sizes were tested with the Mann-Whitney
U
-test and agreement with overall concordance correlation coefficients (OCCC).
Results
Fifty-five conventionally extracted features were significantly different between the VOI sizes, and none of the features showed excellent agreement in terms of OCCCs. When read from the parametric maps, only 8 features showed significant differences, and 3 features showed an excellent OCCC (≥ 0.85). The OCCCs for 89 features substantially increased using the parametric maps.
Conclusions
This phantom study shows that converting CT images into parametric maps resolves the confounding effect of VOI variability and increases feature reproducibility across VOI sizes.
The aim of this study was to develop a deep learning-based algorithm for fully automated spleen segmentation using CT images and to evaluate the performance in conditions directly or indirectly ...affecting the spleen (e.g., splenomegaly, ascites). For this, a 3D U-Net was trained on an in-house dataset (n = 61) including diseases with and without splenic involvement (in-house U-Net), and an open-source dataset from the Medical Segmentation Decathlon (open dataset, n = 61) without splenic abnormalities (open U-Net). Both datasets were split into a training (n = 32.52%), a validation (n = 9.15%) and a testing dataset (n = 20.33%). The segmentation performances of the two models were measured using four established metrics, including the Dice Similarity Coefficient (DSC). On the open test dataset, the in-house and open U-Net achieved a mean DSC of 0.906 and 0.897 respectively (
= 0.526). On the in-house test dataset, the in-house U-Net achieved a mean DSC of 0.941, whereas the open U-Net obtained a mean DSC of 0.648 (
< 0.001), showing very poor segmentation results in patients with abnormalities in or surrounding the spleen. Thus, for reliable, fully automated spleen segmentation in clinical routine, the training dataset of a deep learning-based algorithm should include conditions that directly or indirectly affect the spleen.
We aimed to evaluate the stability of radiomic features in the liver of healthy individuals across different three-dimensional regions of interest (3D ROI) sizes in T1-weighted (T1w) and T2-weighted ...(T2w) images from different MR scanners. We retrospectively included 66 examinations of patients without known diseases or pathological imaging findings acquired on three MRI scanners (3 Tesla I: 25 patients, 3 Tesla II: 19 patients, 1.5 Tesla: 22 patients). 3D ROIs of different diameters (10, 20, 30 mm) were drawn on T1w GRE and T2w TSE images into the liver parenchyma (segment V-VIII). We extracted 93 radiomic features from the different ROIs and tested features for significant differences with the Mann-Whitney-U (MWU)-test. The MWU-test revealed significant differences for most second- and higher-order features, indicating a systematic difference dependent on the ROI size. The features mean, median, root mean squared (RMS), 10th percentile, and 90th percentile were not significantly different. We also assessed feature robustness to ROI size variation with overall concordance correlation coefficients (OCCCs). OCCCs across the different ROI-sizes for mean, median, and RMS were excellent (>0.90) in both sequences on all three scanners. These features, therefore, seem robust to ROI-size variation and suitable for radiomic studies of liver MRI.
PDF
