Abdominal parametric perfusion imaging with respiratory motion-compensation based on contrast-enhanced ultrasound: In-vivo validation. (April 2018)

• Record Type: Journal Article
• Authors: Wang, Diya; Xiao, Mengnan; Zhang, Yu; Wan, Mingxi
• Is Part Of: Computerized medical imaging and graphics. Volume 65(2018)
• Page Start: 11
• Page End: 21
• Publication Date: 2018-04
• Subjects: PPI parametric perfusion imaging -- DCEUS dynamic contrast-enhanced ultrasound -- TIC time-intensity curve -- rMoCo respiratory motion-compensation -- ICA independent component analysis -- PCA principal components analysis -- NMF non-negative matrix factorization -- FS full search -- TSS three step search -- FSS four step search -- SES simple and efficient search -- ARPS adaptive rood pattern search -- MSE mean square error -- SNPP peak signal-to-noise ratio -- SCR signal-to-clutter ratio -- WIT wash-in time -- WOT wash-out time -- PV peak value -- AUC area under curve; Contrast-enhanced ultrasound -- Parametric perfusion imaging -- Respiratory kinetics -- Non-negative matrix factorization; Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnosis, Radioscopic -- Data processing -- Periodicals; Diagnostic Imaging -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Diagnostic imaging; Periodicals; Electronic journals; Electronic journals; 616.0754
• DOI: 10.1016/j.compmedimag.2017.06.005
• Languages: English
• ISSNs: 0895-6111

Abstract

Highlights: Abdominal parametric perfusion imaging with non-negative respiratory motion-compensation. Non-negative matrix factorization combined with fast block matching algorithm. Validated through in-vivo liver and spleen perfusion experiments. Improved the quantized performance of calculation efficiency and accuracy. Enhanced continuity and visualization of abdominal arterioles and characterized perfusion details. Abstract: Parametric perfusion imaging (PPI) based on dynamic contrast-enhanced ultrasound (DCEUS) is a multi-parametric functional method that is increasingly used to characterize the hemodynamic features of abdominal tumors. Periodic respiratory kinetics adversely affects the signal-to-clutter ratio (SCR) and accuracy of abdominal PPI. This study proposed respiratory motion-compensation (rMoCo) employing non-negative matrix factorization combined with fast block matching algorithm to effectively remove these disturbances on abdominal PPI, which was validated through in-vivo perfusion experiments. The mean calculation efficiency of rMoCo was improved by 83.6% when the algorithm was accelerated in a unique matching sequence, which was formed from dozens of DCEUS subsequences at the same respiratory phase. The horizontal and vertical displacements induced by respiratory kinetics were estimated to correct the extraction of time-intensity curves and the peak SNR remained at 22.58 ± 2.90 dB. Finally, the abdominal PPIs of four perfusion parameters were formed with non-negative rMoCo, and their SCR was improved by 3.99 ± 0.49 dB (p < 0.05). Compared with the results without rMoCo, the continuity and visualization of abdominal arterioles were clearly enhanced, and their perfusion details were accurately characterized by PPIs with non-negative rMoCo. The proposed method benefits clinicians in providing accurate diagnoses and in developing appropriate therapeutic strategies for abdominal diseases.