Can Dynamic MRI Sequences Play a Key Role in Evaluating Wrist Instability?

2021 ◽  
Author(s):  
F. Messina ◽  
D. Fierro ◽  
F. Pucciarelli ◽  
A. Laghi ◽  
G. Argento
Keyword(s):  
Dynamic Mri ◽  
Wrist Instability ◽  
Mri Sequences

Fractal Reconstruction of Breast Perfusion Before and After Hyperthermia Treatments

2002 ◽  
Author(s):  
Oana I. Craciunescu ◽  
Shiva K. Das ◽  
Terrence Z. Wong ◽  
Thaddeus V. Samulski
Keyword(s):  
Dynamic Mri ◽  
Relevant Information ◽  
Fractal Interpolation ◽  
Hyperthermia Treatment ◽  
Data Set ◽  
Fractal Interpolation Functions ◽  
Before And After ◽  
Treatment Data ◽  
Mri Sequences ◽  
The Difference

Thermal modeling for hyperthermia breast patients can provide relevant information to better understand the temperatures achieved during treatment. However, human breast is much perfused, making knowledge of the perfusion crucial to the accuracy of the temperature computations. It has been shown that the perfusion of blood in tumor tissue can be approximated using the relative perfusion index (RPI) determined from dynamic contrast-enhanced magnetic resonance imaging (DE-MRI). It was also concluded that the 3D reconstruction of tumor perfusion can be performed using fractal interpolation functions (FIF). The technique used was called piecewise hidden variable fractal interpolation (PHVFI). Changes in the protocol parameters for the dynamic MRI sequences in breast patients allowed us to be able to acquire more spatial slices, hence the possibility to actually verify the accuracy of the fractal interpolation. The interpolated slices were compared to the imaged slices in the original set. The accuracy of the interpolation was tested on post-hyperthermia treatment data set. The difference between the reconstruction and the original slice varied from 2 to 5%. Significantly, the fractal dimension of the interpolated slices is within 2–3% from the original images, thus preserving the fractality of the perfusion maps. The use of such a method becomes crucial when tumor size and imaging restrictions limits the number of spatial slices, requiring interpolation to fill the data between the slices.

Segmentation of left ventricle on dynamic MRI sequences for blood flow cancellation in Thermotherapy

2017 ◽  
Vol 59 ◽  
pp. 37-49
Author(s):  
Samah Bouzidi ◽  
Aurélie Emilien ◽  
Jenny Benois-Pineau ◽  
Bruno Quesson ◽  
Chokri Ben Amar ◽  
...  
Keyword(s):  
Blood Flow ◽  
Left Ventricle ◽  
Dynamic Mri ◽  
Mri Sequences

A Framework for Fusion of T1-Weighted and Dynamic MRI Sequences

2020 ◽  
pp. 157-169
Author(s):  
João F. Teixeira ◽  
Sí­lvia Bessa ◽  
Pedro F. Gouveia ◽  
Hélder P. Oliveira
Keyword(s):  
Dynamic Mri ◽  
Mri Sequences

AB1294 Psoriatic arthritis - a follow-up study applying dynamic MRI, conventional MRI and clinical measures:

2013 ◽  
Vol 71 (Suppl 3) ◽  
pp. 711.14-711
Author(s):  
R.P. Poggenborg ◽  
P. Bøyesen ◽  
C. Wiell ◽  
S.J. Pedersen ◽  
I.J. Sørensen ◽  
...  
Keyword(s):  
Psoriatic Arthritis ◽  
Dynamic Mri ◽  
Follow Up Study ◽  
Conventional Mri ◽  
Clinical Measures

scholarly journals The Effect of Heterogenous Subregions in Glioblastomas on Survival Stratification: A Radiomics Analysis Using the Multimodality MRI

2021 ◽  
Vol 20 ◽  
pp. 153303382110330
Author(s):  
Lulu Yin ◽  
Yan Liu ◽  
Xi Zhang ◽  
Hongbing Lu ◽  
Yang Liu
Keyword(s):  
Poor Prognosis ◽  
Intratumor Heterogeneity ◽  
Short Term ◽  
Prognostic Information ◽  
Manual Delineation ◽  
Flair Sequence ◽  
The Poor ◽  
Contrast Enhanced ◽  
Mri Sequences

Intratumor heterogeneity is partly responsible for the poor prognosis of glioblastoma (GBM) patients. In this study, we aimed to assess the effect of different heterogeneous subregions of GBM on overall survival (OS) stratification. A total of 105 GBM patients were retrospectively enrolled and divided into long-term and short-term OS groups. Four MRI sequences, including contrast-enhanced T1-weighted imaging (T1C), T1, T2, and FLAIR, were collected for each patient. Then, 4 heterogeneous subregions, i.e. the region of entire abnormality (rEA), the regions of contrast-enhanced tumor (rCET), necrosis (rNec) and edema/non-contrast-enhanced tumor (rE/nCET), were manually drawn from the 4 MRI sequences. For each subregion, 50 radiomics features were extracted. The stratification performance of 4 heterogeneous subregions, as well as the performances of 4 MRI sequences, was evaluated both alone and in combination. Our results showed that rEA was superior in stratifying long-and short-term OS. For the 4 MRI sequences used in this study, the FLAIR sequence demonstrated the best performance of survival stratification based on the manual delineation of heterogeneous subregions. Our results suggest that heterogeneous subregions of GBMs contain different prognostic information, which should be considered when investigating survival stratification in patients with GBM.

Sign in / Sign up

Export Citation Format

Share Document