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BMC Cancer
Published in: BMC Cancer 1/2013

Open Access 01-12-2013 | Research article

Ultrasonic spectrum analysis for in vivo characterization of tumor microstructural changes in the evaluation of tumor response to chemotherapy using diagnostic ultrasound

Authors: Chun-yi Lin, Long-hui Cao, Jian-wei Wang, Wei Zheng, Yao Chen, Zi-zhen Feng, An-hua Li, Jian-hua Zhou

Published in: BMC Cancer | Issue 1/2013

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Abstract

Background

There is a strong need for early assessment of tumor response to chemotherapy in order to avoid the adverse effects of unnecessary chemotherapy and to allow early transition to second-line therapy. The purpose of this study was to determine the feasibility of ultrasonic spectral analysis for the in vivo characterization of changes in tumor microstructure in the evaluation of tumor response to chemotherapy using diagnostic ultrasound.

Methods

Experiments were approved by the regional animal care committee. Twenty-four MCF-7 breast cancer bearing nude mice were treated with adriamycin or sterile saline administered by intraperitoneal injection. Ultrasonic radio-frequency (RF) data was collected using a clinically available ultrasound scanner (6-MHz linear transducer). Linear regression parameters (spectral slope and midband-fit) regarding the calibrated power spectra from the RF signals were tested to monitor tumor response to treatment. The section equivalent to the ultrasound imaging plane was stained with hematoxylin and eosin to allow for assessment of the density of tumor cell nuclei.

Results

Treatment with adriamycin significantly reduced tumor growth in comparison with the control group (p = 0.003). Significant changes were observed in the ultrasonic parameters of the treated relative to the untreated tumors (p < 0.05). The spectral slope increased by 48.5%, from −10.66 ± 2.96 to −5.49 ± 2.69; the midband-fit increased by 12.8%, from −57.10 ± 7.68 to −49.81 ± 5.40. Treated tumors were associated with a significant decrease in the density of tumor cell nuclei as compared with control tumors (p < 0.001).

Conclusions

Ultrasonic spectral analysis can detect changes in tumor microstructure after chemotherapy, and this will be helpful in the early evaluation tumor response to chemotherapy.
Appendix
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Literature
1.
Groheux D, Giacchetti S, Espié M, Rubello D, Moretti JL, Hindié E: Early monitoring of response to neoadjuvant chemotherapy in breast cancer with 18F-FDG PET/CT: defining a clinical aim. Eur J Nucl Med Mol Imaging. 2011, 38: 419-425. 10.1007/s00259-010-1660-5.CrossRefPubMed
2.
Ah-See ML, Makris A, Taylor NJ, Harrison M, Richman PI, Burcombe RJ, Stirling JJ, D'Arcy JA, Collins DJ, Pittam MR, Ravichandran D, Padhani AR: Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer. Clin Cancer Res. 2008, 14: 6580-6589. 10.1158/1078-0432.CCR-07-4310.CrossRefPubMed
3.
Bellomi M, Petralia G, Sonzogni A, Zampino MG, Rocca A: CT perfusion for the monitoring of neoadjuvant chemotherapy and radiation therapy in rectal carcinoma: initial experience. Radiology. 2007, 244: 486-493. 10.1148/radiol.2442061189.CrossRefPubMed
4.
Brindle K: New approaches for imaging tumour responses to treatment. Nat Rev Cancer. 2008, 8: 94-107.CrossRefPubMed
5.
Ellis PA, Smith IE, McCarthy K, Detre S, Salter J, Dowsett M: Preoperative chemotherapy induces apoptosis in early breast cancer. Lancet. 1997, 349: 849-10.1016/S0140-6736(05)61752-7.CrossRefPubMed
6.
Chang J, Ormerod M, Powles TJ, Allred DC, Ashley SE, Dowsett M: Apoptosis and proliferation as predictors of chemotherapy response in patients with breast carcinoma. Cancer. 2000, 9: 2145-2152.CrossRef
7.
Hamstra DA, Galbán CJ, Meyer CR, Johnson TD, Sundgren PC, Tsien C, Lawrence TS, Junck L, Ross DJ, Rehemtulla A, Ross BD, Chenevert TL: Functional diffusion map as an early imaging biomarker for high-grade glioma: correlation with conventional radiologic response and overall survival. J Clin Oncol. 2008, 26: 3387-3394. 10.1200/JCO.2007.15.2363.CrossRefPubMedPubMedCentral
8.
Kyriazi S, Collins DJ, Messiou C, Pennert K, Davidson RL, Giles SL, Kaye SB, Desouza NM: Metastatic ovarian and primary peritoneal cancer: assessing chemotherapy response with diffusion-weighted MR imaging–value of histogram analysis of apparent diffusion coefficients. Radiology. 2011, 261: 182-192. 10.1148/radiol.11110577.CrossRefPubMed
9.
Liu T, Mansukhani MM, Benson MC, Ennis R, Yoshida E, Schiff PB, Zhang P, Zhou J, Kutcher GJ: A feasibility study of novel ultrasonic tissue characterization for prostate-cancer diagnosis: 2D spectrum analysis of in vivo data with histology as gold standard. Med Phys. 2009, 36: 3504-3511. 10.1118/1.3166360.CrossRefPubMedPubMedCentral
10.
Liu T, Lizzi FL, Silverman RH, Kutcher GJ: Ultrasonic tissue characterization using 2-D spectrum analysis and its application in ocular tumor diagnosis. Med Phys. 2004, 31: 1032-1039. 10.1118/1.1690196.CrossRefPubMedPubMedCentral
11.
Yang M, Krueger TM, Miller JG, Holland MR: Characterization of anisotropic myocardial backscatter using spectral slope, intercept and midband fit parameters. Ultrason Imaging. 2007, 29: 122-134. 10.1177/016173460702900204.CrossRefPubMed
12.
Kumon RE, Pollack MJ, Faulx AL, Olowe K, Farooq FT, Chen VK, Zhou Y, Wong RC, Isenberg GA, Sivak MV, Chak A, Deng CX: In vivo characterization of pancreatic and lymph node tissue by using EUS spectrum analysis: a validation study. Gastrointest Endosc. 2010, 71: 53-63. 10.1016/j.gie.2009.08.027.CrossRefPubMed
13.
Lizzi FL: Ultrasonic scatterer-property images of the eye and prostate. Proc 1997 IEEE Ultrasonics Symp. 1997, 1109-1116.
14.
Vlad RM, Brand S, Giles A, Kolios MC, Czarnota GJ: Quantitative ultrasound characterization of responses to radiotherapy in cancer mouse models. Clin Cancer Res. 2009, 15: 2067-2075. 10.1158/1078-0432.CCR-08-1970.CrossRefPubMed
15.
Banihashemi B, Vlad R, Debeljevic B, Giles A, Kolios MC, Czarnota GJ: Ultrasound imaging of apoptosis in tumor response: novel preclinical monitoring of photodynamic therapy effects. Cancer Res. 2008, 68: 8590-8596. 10.1158/0008-5472.CAN-08-0006.CrossRefPubMed
16.
Lee J, Karshafian R, Papanicolau N, Giles A, Kolios MC, Czarnota GJ: Quantitative ultrasound for the monitoring of novel microbubble and ultrasound radiosensitization. Ultrasound Med Bio. 2012, 38: 1212-1221. 10.1016/j.ultrasmedbio.2012.01.028.CrossRef
17.
Hwang JY, Park J, Kang BJ, Lubow DJ, Chu D, Farkas DL, Shung KK, Medina-Kauwe LK: Multimodality imaging in vivo for preclinical assessment of tumor-targeted doxorubicin nanoparticles. PLoS One. 2012, 7: e34463-10.1371/journal.pone.0034463.CrossRefPubMedPubMedCentral
18.
Sadeghi-Naini A, Falou O, Czarnota GJ: Quantitative ultrasound spectral parametric maps: Early surrogates of cancer treatment response. Prof. 34th Annual Intl. Conf. Proc. IEEE Eng Med Biol Soc. 2012, 2672-2675.
19.
Lizzi FL, Greenebaum M, Feleppa EJ, Elbaum M, Coleman DJ: Theoretical framework for spectrum analysis in ultrasonic tissue characterization. J Acoust Soc Am. 1983, 73: 1366-1373. 10.1121/1.389241.CrossRefPubMed
20.
Lizzi FL, Astor M, Feleppa EJ, Shao M, Kalisz A: Statistical framework for ultrasonic spectral parameter imaging. Ultrasound Med Biol. 1997, 23: 1371-1382. 10.1016/S0301-5629(97)00200-7.CrossRefPubMed
21.
Lizzi FL, Astor M, Liu T, Deng C, Coleman DJ, Silverman RH: Ultrasonic spectrum analysis for tissue assays and therapy evaluation. Int J Imaging Syst Technol. 1997, 8: 3-10. 10.1002/(SICI)1098-1098(1997)8:1<3::AID-IMA2>3.0.CO;2-E.CrossRef
22.
Hlatky L, Hahnfeldt P, Folkman J: Clinical application of antiangiogenic therapy: microvessel density, what it does and doesn’t tell us. J Natl Cancer Inst. 2002, 94: 883-893. 10.1093/jnci/94.12.883.CrossRefPubMed
23.
Rajan R, Esteva FJ, Symmans WF: Pathologic changes in breast cancer following neoadjuvant chemotherapy: implications for the assessment of response. Clin Breast Cancer. 2004, 5: 235-238. 10.3816/CBC.2004.n.028.CrossRefPubMed
24.
Rajan R, Poniecka A, Smith TL, Yang Y, Frye D, Pusztai L, Fiterman DJ, Gal-Gombos E, Whitman G, Rouzier R, Green M, Kuerer H, Buzdar AU, Hortobagyi GN, Symmans WF: Change in tumor cellularity of breast carcinoma after neoadjuvant chemotherapy as a variable in the pathologic assessment of response. Cancer. 2004, 100: 1365-1373. 10.1002/cncr.20134.CrossRefPubMed
25.
Czarnota GJ, Kolios MC, Hunt JW, Sherar MD: Ultrasound imaging of apoptosis. DNA-damage effects visualized. Methods Mol Biol. 2002, 203: 257-277.PubMed
26.
Lizzi FL, King DL, Rorke MC, Hui J, Ostromogilsky M, Yaremko MM, Feleppa EJ, Wai P: Comparison of theoretical scattering results and ultrasonic data from clinical liver examinations. Ultrasound Med Biol. 1988, 14: 377-385. 10.1016/0301-5629(88)90073-7.CrossRefPubMed
27.
Vlad RM, Saha RK, Alajez NM, Ranieri S, Czarnota GJ, Kolios MC: An increase in cellular size variance contributes to the increase in ultrasound backscatter during cell death. Ultrasound Med Biol. 2010, 36: 1546-1558. 10.1016/j.ultrasmedbio.2010.05.025.CrossRefPubMed
28.
Taggart LR, Baddour RE, Giles A, Czarnota GJ, Kolios MC: Ultrasonic characterization of whole cells and isolated nuclei. Ultrasound Med Biol. 2007, 33: 389-401. 10.1016/j.ultrasmedbio.2006.07.037.CrossRefPubMed
29.
Kolios MC, Czarnota GJ, Lee M, Hunt JW, Sherar MD: Ultrasonic spectral parameter characterization of apoptosis. Ultrasound Med Biol. 2002, 28: 589-597. 10.1016/S0301-5629(02)00492-1.CrossRefPubMed
30.
Oelze ML, Zachary JF, O'Brien WD: Parametric imaging of rat mammary tumors in vivo for the purposes of tissue characterization. J Ultrasound Med. 2002, 21: 1201-1210.PubMed
31.
Czarnota GJ, Papanicolau N, Lee J, Karshafian R, Giles A, Kolios MC: Novel low-frequency ultrasound detection of apoptosis in vitro and in vivo [abstract]. Ultrason Imaging. 2008, 29: 237-238.
32.
Zhou J, Zhang P, Osterman KS, Woodhouse SA, Schiff PB, Yoshida EJ, Lu ZF, Pile-Spellman ER, Kutcher GJ, Liu T: Implementation and validation of an ultrasonic tissue characterization technique for quantitative assessment of normal-tissue toxicity in radiation therapy. Med Phys. 2009, 36: 1643-1650. 10.1118/1.3103935.CrossRefPubMedPubMedCentral
33.
Papanicolau N, Karshafian R, Sadeghian A, Kolios M, Czarnota G: Conventional frequency evaluation of tumor cell death in response to treatment in vivo (abstract). J Acoust Soc Am. 2010, 128: 2365-
34.
Symmans WF, Peintinger F, Hatzis C, Rajan R, Kuerer H, Valero V, Assad L, Poniecka A, Hennessy B, Green M, Buzdar AU, Singletary SE, Hortobagyi GN, Pusztai L: Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy. J Clin Oncol. 2007, 25: 4414-4422. 10.1200/JCO.2007.10.6823.CrossRefPubMed
35.
Park SH, Moon WK, Cho N, Song IC, Chang JM, Park IA, Han W, Noh DY: Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Radiology. 2010, 257: 56-63. 10.1148/radiol.10092021.CrossRefPubMed
36.
Chenevert TL, Stegman LD, Taylor JM, Robertson PL, Greenberg HS, Rehemtulla A, Ross BD: Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors. J Natl Cancer Inst. 2000, 92: 2029-2036. 10.1093/jnci/92.24.2029.CrossRefPubMed
Metadata
Title
Ultrasonic spectrum analysis for in vivo characterization of tumor microstructural changes in the evaluation of tumor response to chemotherapy using diagnostic ultrasound
Authors
Chun-yi Lin
Long-hui Cao
Jian-wei Wang
Wei Zheng
Yao Chen
Zi-zhen Feng
An-hua Li
Jian-hua Zhou
Publication date
01-12-2013
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2013
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/1471-2407-13-302

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