title: Perfusion estimation using contrast-enhanced 3-dimensional subharmonic ultrasound imaging: an in vivo study.
abstract: OBJECTIVE
  The ability to estimate tissue perfusion (in milliliter per minute per gram) in vivo using contrast-enhanced 3-dimensional (3D) harmonic and subharmonic ultrasound imaging was investigated.
  
  
  METHODS
  A LOGIQ™ 9 scanner (GE Healthcare, Milwaukee, WI) equipped with a 4D10L probe was modified to perform 3D harmonic imaging (HI; f(transmit), 5 MHz and f(receive), 10 MHz) and subharmonic imaging (SHI; f(transmit), 5.8 MHz and f(receive), 2.9 MHz). In vivo imaging was performed in the lower pole of both kidneys in 5 open-abdomen canines after injection of the ultrasound contrast agent (UCA) Definity (Lantheus Medical Imaging, N Billerica, MA). The canines received a 5-μL/kg bolus injection of Definity for HI and a 20-μL/kg bolus for SHI in triplicate for each kidney. Ultrasound data acquisition was started just before the injection of UCA (to capture the wash-in) and continued until washout. A microvascular staining technique based on stable (nonradioactive) isotope-labeled microspheres (Biophysics Assay Laboratory, Inc, Worcester, MA) was used to quantify the degree of perfusion in each kidney (the reference standard). Ligating a surgically exposed branch of the renal arteries induced lower perfusion rates. This was followed by additional contrast-enhanced imaging and microsphere injections to measure post-ligation perfusion. Slice data were extracted from the 3D ultrasound volumes and used to generate time-intensity curves offline in the regions corresponding to the tissue samples used for microvascular staining. The midline plane was also selected from the 3D volume (as a quasi-2-dimensional [2D] image) and compared with the 3D imaging modes. Perfusion was estimated from the initial slope of the fractional blood volume uptake (for both HI and SHI) and compared with the reference standard using linear regression analysis.
  
  
  RESULTS
  Both 3D HI and SHI were able to provide visualization of flow and, thus, perfusion in the kidneys. However, SHI provided near-complete tissue suppression and improved visualization of the UCA flow. Microsphere perfusion data were available for 4 canines (1 was excluded because of an error with the reference blood sample) and showed a mean (SD) perfusion of 9.30 (6.60) and 5.15 (3.42) mL/min per gram before and after the ligation, respectively. The reference standard showed significant correlation with the overall 3D HI perfusion estimates (r = 0.38; P = 0.007), but it correlated more strongly with 3D SHI (r = 0.62; P < 0.001). In addition, these results showed an improvement over the quasi-2D HI and SHI perfusion estimates (r = -0.05 and r = 0.14) and 2D SHI perfusion estimates previously reported by our group (r = 0.57).
  
  
  CONCLUSIONS
  In this preliminary study, 3D contrast-enhanced nonlinear ultrasound was able to quantify perfusion in vivo. Three-dimensional SHI resulted in better overall agreement with the reference standard than 3D HI did and was superior to previously reported 2D SHI results. Three-dimensional SHI outperforms the other methods for estimating blood perfusion because of the improved visualization of the complete perfused vascular networks.
authors.affiliation: Department of Radiology, Thomas Jefferson University, Philadelphia, PA 19107, USA.
authors.forename: Anush
authors.initials: A
authors.lastname: Sridharan
authors.forename: John R
authors.initials: JR
authors.lastname: Eisenbrey
authors.forename: Ji-Bin
authors.initials: JB
authors.lastname: Liu
authors.forename: Priscilla
authors.initials: P
authors.lastname: Machado
authors.forename: Valgerdur G
authors.initials: VG
authors.lastname: Halldorsdottir
authors.forename: Jaydev K
authors.initials: JK
authors.lastname: Dave
authors.forename: Hongjia
authors.initials: H
authors.lastname: Zhao
authors.forename: Yu
authors.initials: Y
authors.lastname: He
authors.forename: Suhyun
authors.initials: S
authors.lastname: Park
authors.forename: Scott
authors.initials: S
authors.lastname: Dianis
authors.forename: Kirk
authors.initials: K
authors.lastname: Wallace
authors.forename: Kai E
authors.initials: KE
authors.lastname: Thomenius
authors.forename: Flemming
authors.initials: F
authors.lastname: Forsberg
mesh_terms: D000465:Algorithms; D000818:Animals; D001783:Blood Flow Velocity / Q000502:physiology*; D003287:Contrast Media; D004285:Dogs; D005466:Fluorocarbons; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D055420:Perfusion Imaging / Q000379:methods*; D012077:Renal Artery / Q000000981:diagnostic imaging* / Q000502:physiology*; D012079:Renal Circulation / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000379:methods*
chemical_list: D003287:Contrast Media; D005466:Fluorocarbons; C042852:perflutren