Earthquake probability in engineering—Part 2: Earthquake recurrence and limitations of Gutenberg-Richter b-values for the engineering of critical structures

Abstract Purpose To compare integrated slice-specific dynamic shimming (iShim) diffusion weighted imaging (DWI) and single-shot echo-planar imaging (SS-EPI) DWI in image quality and pathological characterization of rectal cancer. Materials and methods A total of 193 consecutive rectal tumor patients were enrolled for retrospective analysis. Among them, 101 patients underwent iShim-DWI (b = 0, 800, and 1600 s/mm2) and 92 patients underwent SS-EPI-DWI (b = 0, and 1000 s/mm2). Qualitative analyses of both DWI techniques was performed by two independent readers; including adequate fat suppression, the presence of artifacts and image quality. Quantitative analysis was performed by calculating standard deviation (SD) of the gluteus maximus, signal intensity (SI) of lesion and residual normal rectal wall, apparent diffusion coefficient (ADC) values (generated by b values of 0, 800 and 1600 s/mm2 for iShim-DWI, and by b values of 0 and 1000 s/mm2 for SS-EPI-DWI) and image quality parameters, such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of primary rectal tumor. For the primary rectal cancer, two pathological groups were divided according to pathological results: Group 1 (well-differentiated) and Group 2 (poorly differentiated). Statistical analyses were performed with p < 0.05 as significant difference. Results Compared with SS-EPI-DWI, significantly higher scores of image quality were obtained in iShim-DWI cases (P < 0.001). The SDbackground was significantly reduced on b = 1600 s/mm2 images and ADC maps of iShim-DWI. Both SNR and CNR of b = 800 s/mm2 and b = 1600 s/mm2 images in iShim-DWI were higher than those of b = 1000 s/mm2 images in SS-EPI-DWI. In primary rectal cancer of iShim-DWI cohort, SIlesion was significantly higher than SIrectum in both b = 800 and 1600 s/mm2 images. ADC values were significantly lower in Group 2 (0.732 ± 0.08) × 10− 3 mm2/s) than those in Group 1 ((0.912 ± 0.21) × 10− 3 mm2/s). ROC analyses showed significance of ADC values and SIlesion between the two groups. Conclusion iShim-DWI with b values of 0, 800 and 1600 s/mm2 is a promising technique of high image quality in rectal tumor imaging, and has potential ability to differentiate rectal cancer from normal wall and predicting pathological characterization.

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Safety of Catheter Embolization of Pulmonary Arteriovenous Malformations—Evaluation of Possible Cerebrovascular Embolism after Catheter Embolization of Pulmonary Arteriovenous Malformations in Patients with Hereditary Hemorrhagic Telangiectasia/Osler Disease by Pre- and Post-Interventional DWI

Journal of Clinical Medicine ◽

10.3390/jcm10040887 ◽

2021 ◽

Vol 10 (4) ◽

pp. 887

Author(s):

Guenther Schneider ◽

Alexander Massmann ◽

Peter Fries ◽

Felix Frenzel ◽

Arno Buecker ◽

...

Keyword(s):

Arteriovenous Malformations ◽

Pulmonary Arteriovenous Malformations ◽

B Values ◽

Safe Method ◽

Embolization Therapy ◽

Catheter Embolization ◽

Contrast Enhanced ◽

Previously Treated ◽

The Brain ◽

Over Time

Background. This paper aimed to prospectively evaluate the safety of embolization therapy of pulmonary arteriovenous malformations (PAVMs) for the detection of cerebral infarctions by pre- and post-interventional MRI. Method One hundred and five patients (male/female = 44/61; mean age 48.6+/−15.8; range 5–86) with pre-diagnosed PAVMs on contrast-enhanced MRA underwent embolization therapy. The number of PAVMs treated in each patient ranged from 1–8 PAVMs. Depending on the size and localization of the feeding arteries, either Nester-Coils or Amplatzer vascular plugs were used for embolization therapy. cMRI was performed immediately before, and at the 4 h and 3-month post-embolization therapy. Detection of peri-interventional cerebral emboli was performed via T2w and DWI sequences using three different b-values, with calculation of ADC maps. Results Embolization did not show any post-/peri-interventional, newly developed ischemic lesions in the brain. Only one patient who underwent re-embolization and was previously treated with tungsten coils that corroded over time showed newly developed, small, diffuse emboli in the post-interventional DWI sequence. This patient already had several episodes of brain emboli before re-treatment due to the corroded coils, and during treatment, when passing the corroded coils, experienced additional small, clinically inconspicuous brain emboli. However, this complication was anticipated but accepted, since the vessel had to be occluded distally. Conclusion Catheter-based embolization of PAVMs is a safe method for treatment and does not result in clinically inconspicuous cerebral ischemia, which was not demonstrated previously.

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Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks

Diagnostics ◽

10.3390/diagnostics11060970 ◽

2021 ◽

Vol 11 (6) ◽

pp. 970

Author(s):

Maedeh Khalilian ◽

Kamran Kazemi ◽

Mahshid Fouladivanda ◽

Malek Makki ◽

Mohammad Sadegh Helfroush ◽

...

Keyword(s):

Human Brain ◽

Clustering Coefficient ◽

Quality Data ◽

B Values ◽

Rich Club ◽

Global Efficiency ◽

Acquisition Strategy ◽

The Rich ◽

Structural Networks ◽

Single Shell

The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.

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One-Pot Hydrothermal Synthesis of Victoria Green (Ca3Cr2Si3O12) Nanoparticles in Alkaline Fluids and Its Colour Hue Characterisation

Nanomaterials ◽

10.3390/nano11020521 ◽

2021 ◽

Vol 11 (2) ◽

pp. 521

Author(s):

Juan Carlos Rendón-Angeles ◽

Zully Matamoros-Veloza ◽

Jose Luis Rodríguez-Galicia ◽

Gimyeong Seong ◽

Kazumichi Yanagisawa ◽

...

Keyword(s):

Near Infrared ◽

Single Step ◽

Spectral Space ◽

Infrared Reflectance ◽

Hydrothermal Preparation ◽

Near Infrared Reflectance ◽

One Pot ◽

Factors Affecting ◽

B Values ◽

Alkaline Conditions

One-pot hydrothermal preparation of Ca3Cr2Si3O12 uvarovite nanoparticles under alkaline conditions was investigated for the first time. The experimental parameters selected for the study considered the concentration of the KOH solvent solution (0.01 to 5.0 M), the agitation of the autoclave (50 rpm), and the nominal content of Si4+ (2.2–3.0 mole). Fine uvarovite particles were synthesised at 200 °C after a 3 h interval in a highly concentrated 5.0 M KOH solution. The crystallisation of single-phase Ca3Cr2Si3O12 particles proceeded free of by-products via a one-pot process involving a single-step reaction. KOH solutions below 2.5 M and water hindered the crystallisation of the Ca3Cr2Si3O12 particles. The hydrothermal treatments carried out with stirring (50 rpm) and non-stirring triggered the crystallisation of irregular anhedral particles with average sizes of 8.05 and 12.25 nm, respectively. These particles spontaneously assembled into popcorn-shaped agglomerates with sizes varying from 66 to 156 nm. All the powders prepared by the present method exhibited CIE-L*a*b* values that correspond to the Victoria green colour spectral space and have a high near infrared reflectance property. The particle size and structural crystallinity are factors affecting the Victoria pigment optical properties, such as CIE-L*a*b* values, green tonality, and near-infrared reflectance.

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Precise Identification of Prostate Cancer from DWI Using Transfer Learning

Sensors ◽

10.3390/s21113664 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3664

Author(s):

Islam R. Abdelmaksoud ◽

Ahmed Shalaby ◽

Ali Mahmoud ◽

Mohammed Elmogy ◽

Ahmed Aboelfetouh ◽

...

Keyword(s):

Prostate Cancer ◽

Transfer Learning ◽

Sensitivity And Specificity ◽

Benign Tumors ◽

B Values ◽

Cad System ◽

Average Accuracy ◽

Apparent Diffusion ◽

Invasive Techniques ◽

Fine Tune

Background and Objective: The use of computer-aided detection (CAD) systems can help radiologists make objective decisions and reduce the dependence on invasive techniques. In this study, a CAD system that detects and identifies prostate cancer from diffusion-weighted imaging (DWI) is developed. Methods: The proposed system first uses non-negative matrix factorization (NMF) to integrate three different types of features for the accurate segmentation of prostate regions. Then, discriminatory features in the form of apparent diffusion coefficient (ADC) volumes are estimated from the segmented regions. The ADC maps that constitute these volumes are labeled by a radiologist to identify the ADC maps with malignant or benign tumors. Finally, transfer learning is used to fine-tune two different previously-trained convolutional neural network (CNN) models (AlexNet and VGGNet) for detecting and identifying prostate cancer. Results: Multiple experiments were conducted to evaluate the accuracy of different CNN models using DWI datasets acquired at nine distinct b-values that included both high and low b-values. The average accuracy of AlexNet at the nine b-values was 89.2±1.5% with average sensitivity and specificity of 87.5±2.3% and 90.9±1.9%. These results improved with the use of the deeper CNN model (VGGNet). The average accuracy of VGGNet was 91.2±1.3% with sensitivity and specificity of 91.7±1.7% and 90.1±2.8%. Conclusions: The results of the conducted experiments emphasize the feasibility and accuracy of the developed system and the improvement of this accuracy using the deeper CNN.

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