1887
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
In vivo cancer diagnosis with optical spectroscopy and acoustically induced blood stasis using a murine MCa35 model
Rent:
Rent this article for
USD
10.1118/1.2198196
/content/aapm/journal/medphys/33/6/10.1118/1.2198196
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/33/6/10.1118/1.2198196

Figures

Image of FIG. 1.
FIG. 1.

Experimental setup, with the mouse leg located in the focal region of the ultrasound.

Image of FIG. 2.
FIG. 2.

Illustration of a typical ultrasound pulse sequence (US) and its corresponding “boxed” representation (BUS).

Image of FIG. 3.
FIG. 3.

The ratio signal with the trend modulated ultrasound pulse signal superimposed for a typical (a) normal leg muscle tissue and (b) tumor tissue. Notice the much larger ultrasound induced contrast in the normal leg muscle signal.

Image of FIG. 4.
FIG. 4.

Illustration of “boxed” ultrasound signal (BUS), observation “windows,” and comb signal with spikes at the positions of local minima (calculated for each “window”).

Image of FIG. 5.
FIG. 5.

Laser Doppler relative average volume velocity shown with ultrasound bursts and vertical lines for reference for normal leg muscle (a) and tumor (b) tissue samples. The normal leg muscle samples have greater blood volume flow rates.

Image of FIG. 6.
FIG. 6.

A sample of an in vivo spectra of a healthy tissue sample with a fit used to determine the oxy/deoxyhemoglobin saturations and the scattering properties of the tissue.

Image of FIG. 7.
FIG. 7.

Parameters derived using the fitting algorithm applied to the collected broadband diffuse reflectance spectra: (a) oxyhemoglobin concentration; (b) deoxyhemoglobin concentration; (c) scattering coefficient; (d) scattering exponent; and (e) total hemoglobin concentration. The vertical lines reference the beginning of the five second bursts of ultrasound.

Image of FIG. 8.
FIG. 8.

The signal which reflects the changes in oxyhemoglobin concentrations.

Image of FIG. 9.
FIG. 9.

The signal in normal leg muscle tissue is better correlated to the ultrasound than the same signal for tumor tissue, measured for the same mouse to compensate for physiological differences in mice population.

Image of FIG. 10.
FIG. 10.

ROC curve for the diagnostic algorithm. Decision threshold varied from 0.1 to 1 in 0.05 steps. Area under the curve is 0.90.

Image of FIG. 11.
FIG. 11.

Vessel staining of (a) tumor and (c) normal leg muscle tissue samples. Corresponding perfused vessel stains for the same samples are shown in (b) and (d), respectively.

Image of FIG. 12.
FIG. 12.

The ratio signal for nontumor tissue with the trend modulated ultrasound pulse superimposed. The ultrasound-induced drops are difficult to distinguish.

Tables

Generic image for table
TABLE I.

Experimental data used to calculate ROC.

Generic image for table
TABLE II.

Immunohistochemistry results.

Loading

Article metrics loading...

/content/aapm/journal/medphys/33/6/10.1118/1.2198196
2006-05-11
2014-04-16
Loading

Full text loading...

This is a required field
Please enter a valid email address
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: In vivo cancer diagnosis with optical spectroscopy and acoustically induced blood stasis using a murine MCa35 model
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/33/6/10.1118/1.2198196
10.1118/1.2198196
SEARCH_EXPAND_ITEM