In vivo characterization of tumor vasculature using iodine and gold nanoparticles and dual energy micro-CT

Darin P. Clark1, Ketan Ghaghada2, Everett J. Moding3, David G. Kirsch3, Cristian T. Badea1

1Center for In Vivo Microscopy, Department of Radiology, Box 3302 Duke University Medical Center, Durham, NC 27710
2The Edward B. Singleton Department of Pediatric Radiology, Texas Children's Hospital, Houston, TX
3Departments of Pharmacology & Cancer Biology and Radiation Oncology, Duke Medical Center, Durham, NC 27710

Physics in Medicine and Biology - 58(6):1683-1704, 2013 Mar 21. NIHMSID#449989 PMCID: PMC3746324

Tumor blood volume and vascular permeability are well established indicators of tumor angiogenesis and important predictors in cancer diagnosis, planning, and treatment. In this work, we establish a novel preclinical imaging protocol which allows quantitative measurement of both metrics simultaneously. First, gold nanoparticles are injected and allowed to extravasate into the tumor, and then liposomal iodine nanoparticles are injected. Combining a previously optimized dual energy micro-CT scan using high-flux polychromatic x-ray sources (energies: 40 kVp, 80 kVp) with a novel post-reconstruction spectral filtration scheme, we are able to decompose the results into 3D iodine and gold maps, allowing simultaneous measurement of extravasated gold and intravascular iodine concentrations. Using a digital resolution phantom, the mean limits of detectability (mean CNR = 5) for each element are determined to be 2.3 mg/mL (18 mM) for iodine and 1.0 mg/mL (5.1 mM) for gold, well within the observed in vivo concentrations of each element (I: 0-24 mg/mL, Au: 0-9 mg/mL) and a factor of 10 improvement over the limits without post-reconstruction spectral filtration. Using a calibration phantom, these limits are validated and an optimal sensitivity matrix for performing decomposition using our micro-CT system is derived. Finally, using a primary mouse model of soft-tissue sarcoma, we demonstrate the in vivo application of the protocol to measure fractional blood volume and vascular permeability over the course of five days of active tumor growth. >

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Figure 2: DE decomposition of a 3D digital bar phantom. (A) The central slice through the digital bar phantom with 15 mg/mL iodine in odd rows and 4 mg/mL gold in even rows, a relevant case for in vivo studies. (B) The slice from (A) with 70 HU of zero-mean, white Gaussian noise. (C) Part (B) denoised with classic BF before decomposition. Edges are well preserved at all frequencies, but substantial noise remains. (D) Part (B) denoised with independent BF before decomposition. Denoising performance is better than Part (C), but edges in the 40 kVp data are noticeably blurred. (E) Denoising of part (B) with the proposed joint BF scheme before decomposition. The results maintain the superior denoising performance of (D) without noticeably blurring the edges in the 40 kVp data. Calibration bars on the far right denote window widths and levels for each row (row 1, 2: HU; row 3, 4: mg/mL). The bar width is 128 voxels (11.3 mm).

Line profiles through the central column of each slice:

Figure 7: Application of joint BF to in vivo data acquired immediately after the injection of Lip-I on day 4. (A) Matching coronal slices through the reconstructed 80 and 40 kVp data sets (noise SD: ~70 HU). Note the visual ambiguity between iodine and gold contrast. (B) The slices from (A) after joint BF (σw = 70 HU, m = 2). (C) The difference before and after filtration: (A)-(B). Black arrows indicate bones which are noticeably compromised by the denoising process. White arrows indicate the location of the primary sarcoma. (D) DE decomposition using the noisy slices from (A). (E) Identical DE decomposition using the filtered slices from (B). Note that the bones (shown in white) where segmented and excluded from the decomposition. The scale bar at the bottom right of (E) applies to all images. The two calibration bars at the bottom left denote the window widths and levels in HU for columns (A) and (B) and for column (C), respectively. The calibration bars at the bottom right denote the window widths and levels in mg/mL for I and Au, respectively, in (D) and (E).

The filtered data sets shown in Column B:

Link to 80 kVp Data (HU):

Link to 40 kVp Data (HU):

The filtered data sets overlaid in Panel E:

Link to Iodine Map (scaled in mg/mL I):

Link to Gold Map (scaled in mg/mL Au):

Link to Calcium_ Map (scaled in mg/mL Ca):

Figure 8: In vivo characterization of a primary soft-tissue sarcoma using DE micro-CT. This matrix provides a visual representation of the data acquired on day 1 (AuNp injection), day 2, day 3, day 4 (pre Lip-I injection), day 4 (post Lip-I injection), and on day 6 and illustrates the ability to simultaneously decompose I and Au in vivo. The columns represent the 40 kVp data, the 80 kVp data, the I map, the Au map, and the superposition of the I and Au maps. Each panel is a MIP through the segmented tumor at the designated day. White arrows denote an apparent increase in Au concentration within the vasculature after the injection of Lip-I on day 4. Calibration bars at the upper right denote the window widths and levels in HU for the 40 kVp and 80 kVp data and in mg/mL for I and Au maps. The scale bar at the bottom right applies to all panels.


Key (animations only):
# Calcium (Green): 0 to 175 mg/mL
# Iodine (Red): 4 to 10 mg/mL
# Gold (Yellow): 1.5 to 9 mg/mL


Day 1 (Post Au) Animation:

Day 4 (Post I) Animation:


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All work was performed at the Duke Center for In Vivo Microscopy, an NIH/NIBIB National Biomedical Technology Resource Center (P41 EB015897). We thank Sally Zimney for editorial assistance, Lucy Upchurch for assistance in preparing the supplemental material, and Yi Qi for help with animal support.