Fast multi‐parametric imaging in abdomen by corrected dual‐flip angle sequence with interleaved echo acquisition

2021 ◽  
Author(s):  
Hao Peng ◽  
Chuanli Cheng ◽  
Qian Wan ◽  
Sen Jia ◽  
Shuai Wang ◽  
...  
Keyword(s):  
Flip Angle ◽  
Parametric Imaging

Parametric imaging of [11C]PIB studies using spectral analysis

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S590-S590 ◽  
Author(s):  
Rainer Hinz ◽  
Gunnar Blomquist ◽  
Paul Edison ◽  
David J Brooks
Keyword(s):  
Spectral Analysis ◽  
Parametric Imaging

scholarly journals Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamidreza Taleghamar ◽  
Hadi Moghadas-Dastjerdi ◽  
Gregory J. Czarnota ◽  
Ali Sadeghi-Naini
Keyword(s):  
Breast Cancer ◽  
Treatment Response ◽  
Quantitative Ultrasound ◽  
Parametric Imaging ◽  
Term Survival ◽  
Adaptive Boosting ◽  
Tumor Margin ◽  
Parametric Images ◽  
Response To Chemotherapy ◽  
Pre Treatment

AbstractThe efficacy of quantitative ultrasound (QUS) multi-parametric imaging in conjunction with unsupervised classification algorithms was investigated for the first time in characterizing intra-tumor regions to predict breast tumor response to chemotherapy before the start of treatment. QUS multi-parametric images of breast tumors were generated using the ultrasound radiofrequency data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for neo-adjuvant chemotherapy followed by surgery. A hidden Markov random field (HMRF) expectation maximization (EM) algorithm was applied to identify distinct intra-tumor regions on QUS multi-parametric images. Several features were extracted from the segmented intra-tumor regions and tumor margin on different parametric images. A multi-step feature selection procedure was applied to construct a QUS biomarker consisting of four features for response prediction. Evaluation results on an independent test set indicated that the developed biomarker coupled with a decision tree model with adaptive boosting (AdaBoost) as the classifier could predict the treatment response of patient at pre-treatment with an accuracy of 85.4% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.89. In comparison, the biomarkers consisted of the features derived from the entire tumor core (without consideration of the intra-tumor regions), and the entire tumor core and the tumor margin could predict the treatment response of patients with an accuracy of 74.5% and 76.4%, and an AUC of 0.79 and 0.76, respectively. Standard clinical features could predict the therapy response with an accuracy of 69.1% and an AUC of 0.6. Long-term survival analyses indicated that the patients predicted by the developed model as responders had a significantly better survival compared to the non-responders. Similar findings were observed for the two response cohorts identified at post-treatment based on standard clinical and pathological criteria. The results obtained in this study demonstrated the potential of QUS multi-parametric imaging integrated with unsupervised learning methods in identifying distinct intra-tumor regions in breast cancer to characterize its responsiveness to chemotherapy prior to the start of treatment.

Accuracy of equilibrium magnetization mapping in sliced two-dimensional spoiled gradient-recalled echo pulse sequence with variable flip angle

2013 ◽  
Vol 38 (5) ◽  
pp. 1245-1250
Author(s):  
Hideto Kuribayashi ◽  
Masaki Sekino ◽  
Takuya Minowa ◽  
Yoshie Maitani ◽  
Hiroyuki Ohsaki ◽  
...  
Keyword(s):  
Pulse Sequence ◽  
Flip Angle ◽  
Two Dimensional ◽  
Variable Flip Angle ◽  
Equilibrium Magnetization ◽  
Echo Pulse

Flow Quantification with Nakagami Parametric Imaging for Suppressing Contrast Microbubbles Attenuation

2013 ◽  
Vol 39 (4) ◽  
pp. 660-669 ◽  
Author(s):  
Xiaolin Gu ◽  
Min Wei ◽  
Yujin Zong ◽  
Hujie Jiang ◽  
Mingxi Wan
Keyword(s):  
Flow Quantification ◽  
Parametric Imaging ◽  
Contrast Microbubbles

Partial flip-angle spin-echo imaging: clinical applications

1989 ◽  
Vol 153 (4) ◽  
pp. 883-884
Author(s):  
JP Laissy ◽  
P Hugonet
Keyword(s):  
Spin Echo ◽  
Clinical Applications ◽  
Flip Angle

Parametric imaging using digital subtraction angiography

1986 ◽  
Vol 59 (697) ◽  
pp. 7-11 ◽  
Author(s):  
G. J. S. Hunter ◽  
J. V. Hunter ◽  
N. J. G. Brown
Keyword(s):  
Digital Subtraction Angiography ◽  
Parametric Imaging ◽  
Digital Subtraction

A dual flip angle 3D bSSFP magnetization transfer-like method to differentiate between recent and old myocardial infarction

2018 ◽  
Vol 47 (3) ◽  
pp. spcone-spcone
Author(s):  
Philippe Germain ◽  
Soraya El Ghannudi ◽  
Aissam Labani ◽  
Mi Y. Jeung ◽  
Afshin Gangi ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Magnetization Transfer ◽  
Flip Angle ◽  
Old Myocardial Infarction
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