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Improved signal processing to detect cancer by ultrasonic molecular imaging of targeted nanoparticles
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10.1121/1.3578459
/content/asa/journal/jasa/129/6/10.1121/1.3578459
http://aip.metastore.ingenta.com/content/asa/journal/jasa/129/6/10.1121/1.3578459
View: Figures

Figures

Image of FIG. 1.
FIG. 1.

A diagram of the apparatus used to acquire backscattered RF data, in vivo, (A) a typical ultrasonic gray scale image together with (B) a histologically stained section of the tumor indicating portions where -targeted nanoparticles nanoparticles could adhere, and (C) a further enlarged section indicating more precisely the location of viable target sites (red by staining).

Image of FIG. 2.
FIG. 2.

Subsets (middle portion: ) of smoothing spline images based on unfiltered (top row) and low-pass filtered (bottom row) RF obtained from a MDA435-implanted mouse injected with -targeted nanoparticles. (A) Smoothing parameter , (B) , (C) , (D) . The RF used to construct these images was acquired immediately after injection.

Image of FIG. 3.
FIG. 3.

Subsets (middle portion: ) of smoothing spline images based on unfiltered (top row) and low-pass filtered (bottom row) RF obtained from a MDA435-implanted mouse injected with -targeted nanoparticles. (A) Smoothing parameter , (B) , (C) , (D) The RF used to construct these images was acquired immediately after injection.

Image of FIG. 4.
FIG. 4.

Effects of smoothing parameter on smoothed spline output for representative segments of unfiltered RF data.

Image of FIG. 5.
FIG. 5.

Effects of smoothing parameter on smoothed spline output for low-pass filtered versions of the same RF data shown in Fig. 4.

Image of FIG. 6.
FIG. 6.

Effects of smoothing parameter on smoothed spline output for unfiltered RF data. Left column: Comparison of log magnitude of Fourier transforms of smoothed (i.e., ) and unsmoothed (i.e., ) data from the left columns of Fig. 4. Right column: Plots of the unsmoothed log magnitude minus the smoothed log magnitude.

Image of FIG. 7.
FIG. 7.

Same comparison as Fig. 6 but applied to the low-pass filtered data of, Fig. 5.

Image of FIG. 8.
FIG. 8.

Analysis steps for images from a single mouse. Step 1: the cumulative distribution function (CDF) of all 12 images aquired from the animal are computed. Step 2: The CDF is used to segment the image into targeted (inside the blue boundaries) and non-targeted (outside) segments according to pixel value being above or below the threshold level (44% in this case). Step 3: The mean value, , of is computed for each “targeted region. Step 4: These are used to calculate for each time point in the study. This procedure is repeated for all mice in each group. An example of the resulting averages at each time point for two of the groups studied (using the 44% analysis threshold) is shown in Fig. 10, where the subscript has been suppressed in .

Image of FIG. 9.
FIG. 9.

Closeup of thresholded smoothing spline images. (Left) Image based on backscattered RF obtained from MDA435 tumor implanted mouse (same RF data used in Figs. 2–5) immediately after injection of -targeted nanoparticles. (Right) Image based on backscattered RF obtained from the same region 60 min after injection, “colorized” so that all pixels in the bottom 44% of the histogram (constructed using the 0-60 min images obtained from this mouse) are red.

Image of FIG. 10.
FIG. 10.

(Color online) Average time course of images obtained from the five MDA435-implanted (left, top) and five non-implanted mice (right, top) injected with -targeted nanoparticles, five MDA435-implanted (left, middle),and five non-implanted mice (right, middle) injected with non-targeted nanoparticles, and five MDA435-implanted (left, bottom) and five non-implanted mice (right, bottom) injected with saline. These data were obtained for the CDF threshold set to include the lower 44% of pixel values in the from each of the images in each group. Standard error bars for each group are also shown.

Image of FIG. 11.
FIG. 11.

(Color online) Average time course of images obtained from the five MDA435-implanted mice injected with -targeted nanoparticles and the corresponding confidence ratios () as a function of time post-injection. The left panel is the same panel appearing in the top right column of Fig. 10.

Image of FIG. 12.
FIG. 12.

Confidence panel for -targeted nanoparticle group processed using optimal smoothing splines applied to low-pass filtered RF data. This image is composed of data like that shown in the right side of Fig. 11.

Image of FIG. 13.
FIG. 13.

Confidence panel stack comprised of confidence panels for all groups processed using optimal smoothing splines applied to low-pass filtered RF data. This panel is comprised of confidence summary images like that shown in Fig. 12.

Image of FIG. 14.
FIG. 14.

Confidence panel summary composed of confidence panel stacks for all groups, masked at successively greater confidence levels (labels A–F defined in Fig. 13). The left most (unmasked) stack of this image is shown in Fig. 13 and presents confidence panels in the same order. Also indicated is a conservatively chosen range of analysis thresholds (44%–62%) that produce an “extensive” region of confidence ratios, , having an absolute value greater than 4 only for the tumor-implanted group injected with -targeted nanoparticles. Thus this range of analysis thresholds combined with the requirement that comprises selection criterion permitting identification of this group.

Image of FIG. 15.
FIG. 15.

Confidence, , panels from for all groups used in our study. Pixels with absolute value below are masked (colored black). Panels A–F were obtained using unfiltered RF: (A) MDA435-implanted mice injected with -targeted nanoparticles (), (B) MDA435-implanted mice injected with non-targeted nanoparticles (), (C) MDA435-implanted mice injected with saline (), (D)–,(F) same injections into tumor-free mice. Panels A′ through B′ are the corresponding panels obtained using low-pass filtered RF. The smoothing spline parameter in all cases.

Image of FIG. 16.
FIG. 16.

Confidence, , panels from for all groups used in our study. Pixels with absolute value below are masked (colored black). Panels A–F were obtained using unfiltered RF: (A) MDA435-implanted mice injected with -targeted nanoparticles (), (B) MDA435-implanted mice injected with non-targeted nanoparticles (), (C) MDA435-implanted mice injected with saline (), (D)–(F) same injections into tumor-free mice. Panels A′ through B′ are the corresponding panels obtained using low-pass filtered RF. The smoothing spline parameter in all cases.

Image of FIG. 17.
FIG. 17.

confidence panels, corresponding to those shown in Fig. 15. Both figures were made using the same RF.

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/content/asa/journal/jasa/129/6/10.1121/1.3578459
2011-06-14
2014-04-19
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Improved signal processing to detect cancer by ultrasonic molecular imaging of targeted nanoparticles
http://aip.metastore.ingenta.com/content/asa/journal/jasa/129/6/10.1121/1.3578459
10.1121/1.3578459
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