scholarly journals Bayesian Reconstruction of Tissue Deformation Maps for Organ Morphogenesis

2020 ◽  
Vol 40 (159) ◽  
pp. 29-32
Author(s):  
Yoshihiro MORISHITA
2021 ◽  
Vol 10 (5) ◽  
pp. 1110
Author(s):  
Anjeza Xholli ◽  
Gianluca Simoncini ◽  
Sonja Vujosevic ◽  
Giulia Trombetta ◽  
Alessandra Chiodini ◽  
...  

Menstrual pain is consequent to intense uterine contraction aimed to expel menstrual flow through downstream uterine cervix. Herein it was evaluated whether characteristics of uterine cervix are associated with intensity of menstrual pain. Ultrasound elastography was used to analyze cervix elasticity of 75 consecutive outpatient women. Elasticity was related to intensity of menstrual pain defined by a Visual Analogue Scale (VAS). Four regions of interest (ROI) were considered: internal uterine orifice (IUO), anterior (ACC) and posterior cervical (PCC) compartment and middle cervical canal (MCC). Tissue elasticity, evaluated by color score (from 0.5 = blue/violet (low elasticity) to 3.0 = red (high elasticity), and percent tissue deformation was analyzed. Elasticity of IUO was lower (p = 0.0001) than that of MCC or ACC, and it was negatively related (R2 = 0.428; p = 0.0001) to menstrual VAS (CR −2.17; 95%CI −3.80, −0.54; p = 0.01). Presence of adenomyosis (CR 3.24; 95% CI 1.94, 4.54; p = 0.0001) and cervix tenderness at clinical examination (CR 2.74; 95% CI 1.29, 4.20; p = 0.0004), were also independently related to menstrual VAS. At post hoc analysis, women with vs. without menstrual pain had lower IUO elasticity, expressed as color score (0.72 ± 0.40 vs. 0.92 ± 0.42; p = 0.059), lower percent tissue deformation at IUO (0.09 ± 0.05 vs. 0.13 ± 0.08; p = 0.025), a higher prevalence of cervical tenderness at bimanual examination (36.2% vs. 9.5%; p = 0.022) and a higher prevalence of adenomyosis (46.5% vs. 19.9%; p = 0.04). These preliminary data indicate that IUO elasticity is associated with the presence and the intensity of menstrual pain. Mechanisms determining IUO elasticity are useful to be explored.


NeuroImage ◽  
2021 ◽  
pp. 118078
Author(s):  
Jacob-Jan Sloots ◽  
Geert Jan Biessels ◽  
Alberto de Luca ◽  
Jaco J.M. Zwanenburg

2014 ◽  
Vol 10 (1) ◽  
pp. e1003457 ◽  
Author(s):  
Thibaut Jombart ◽  
Anne Cori ◽  
Xavier Didelot ◽  
Simon Cauchemez ◽  
Christophe Fraser ◽  
...  

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