3-D freehand echocardiography for automatic left ventricle reconstruction and analysis based on multiple acoustic windows

A new method is proposed to reconstruct and analyze the left ventricle (LV) from multiple acoustic window three-dimensional (3-D) ultrasound acquired using a transthoracic 3-D rotational probe. Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. A more extensive clinical validation is required to establish whether these promising first results translate to a method suitable for routine clinical use.

[1]  Jérôme Declerck,et al.  Automatic registration and alignment on a template of cardiac stress and rest reoriented SPECT images , 1997, IEEE Transactions on Medical Imaging.

[2]  O Basset,et al.  Spatial compounding in ultrasonic imaging using an articulated scan arm. , 1996, Ultrasound in medicine & biology.

[3]  Jae Hyun Kim,et al.  US extended-field-of-view imaging technology. , 1997, Radiology.

[4]  Andrea Giachetti On-line analysis of echocardiographic image sequences , 1998, Medical Image Anal..

[5]  G Lutter,et al.  Improved 3-D-echocardiographic endocardial border delineation using the contrast agent FS069 (Optison) transesophageal studies in a porcine model. , 2001, Ultrasound in medicine & biology.

[6]  George D. Stetten,et al.  Medical Node Models to Identify and Measure Objects in Real-Time 3D Echocardiography , 1999, IEEE Trans. Medical Imaging.

[7]  Nicholas Ayache,et al.  Features extraction and analysis methods for sequences of ultrasound Images , 1992, Image Vis. Comput..

[8]  James S. Duncan,et al.  Estimating 3D Strain from 4D Cine-MRI and Echocardiography: In-Vivo Validation , 2000, MICCAI.

[9]  R. Martin,et al.  Three-dimensional ultrasound imaging of the rotator cuff: spatial compounding and tendon thickness measurement. , 2000, Ultrasound in medicine & biology.

[10]  M.E. Legget,et al.  System for quantitative three-dimensional echocardiography of the left ventricle based on a magnetic-field position and orientation sensing system , 1998, IEEE Transactions on Biomedical Engineering.

[11]  J. Alison Noble,et al.  2D+T Acoustic Boundary Detection in Echocardiography , 1998, MICCAI.

[12]  J. Alison Noble,et al.  Automating 3D Echocardiographic Image Analysis , 2000, MICCAI.

[13]  Kevin J. Parker,et al.  Multiple Resolution Bayesian Segmentation of Ultrasound Images , 1994, Other Conferences.

[14]  Gerald Farin,et al.  Curves and surfaces for computer aided geometric design , 1990 .

[15]  Riccardo Poli,et al.  Recovery of the 3-D shape of the left ventricle from echocardiographic images , 1995, IEEE Trans. Medical Imaging.

[16]  J. Alison Noble,et al.  Automated 3-D echocardiography analysis compared with manual delineations and SPECT MUGA , 2002, IEEE Transactions on Medical Imaging.

[17]  Robert Rohling,et al.  3D spatial compounding of ultrasound images , 1997 .

[18]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Michael Brady,et al.  Feature Enhancement in Low Quality Images with Application to Echocardiography , 2001, IPMI.

[20]  D. Atkinson,et al.  Respiratory motion compensation for 3-D freehand echocardiography. , 2001, Ultrasound in medicine & biology.

[21]  Miguel. Mulet Parada Intensity independent feature extraction and tracking in echocardiographic sequences. , 2000 .