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1.
Technol Cancer Res Treat ; 10(2): 121-34, 2011 Apr.
Article in English | MEDLINE | ID: mdl-21381790

ABSTRACT

Optical methods such as reflectance and fluorescence spectroscopy are being investigated for their potential to aid cancer detection in a quantitative, minimally invasive manner. Mathematical models of reflectance and fluorescence provide an important link between measured optical data and biomedically-relevant tissue parameters that can be extracted from these data to characterize the presence or absence of disease. The most commonly-used mathematical models in biomedical optics are the diffusion approximation (DA) to the radiative transfer equation, Monte Carlo (MC) computational models of light transport, and semi-empirical models. This paper presents a review of the applications of these models to reflectance and endogenous fluorescence sensing for cancer diagnostics in human tissues. Specific examples are given for cervical, breast, and pancreatic tissues. A comparison of the DA and MC methods in two biologically-relevant regimes of optical parameter space will also be discussed.


Subject(s)
Light , Models, Theoretical , Neoplasms/diagnosis , Scattering, Radiation , Spectrum Analysis/methods , Algorithms , Computer Simulation , Humans , Monte Carlo Method , Neoplasms/pathology , Photons , Spectrometry, Fluorescence/methods
2.
Article in English | MEDLINE | ID: mdl-18519220

ABSTRACT

Mechanical tissue fractionation can be achieved using successive, high-intensity ultrasound pulses in a process termed histotripsy. Histotripsy has many potential clinical applications where noninvasive tissue removal is desired. The primary mechanism for histotripsy is believed to be cavitation. Using fast-gated imaging, this paper studies the evolution of a cavitating bubble cloud induced by a histotripsy pulse (10 and 14 cycles) at peak negative pressures exceeding 21MPa. Bubble clouds are generated inside a gelatin phantom and at a tissue-water interface, representing two situations encountered clinically. In both environments, the imaging results show that the bubble clouds share the same evolutionary trend. The bubble cloud and individual bubbles in the cloud were generated by the first cycle of the pulse, grew with each cycle during the pulse, and continued to grow and collapsed several hundred microseconds after the pulse. For example, the bubbles started under 10 microm, grew to 50 microm during the pulse, and continued to grow 100 microm after the pulse. The results also suggest that the bubble clouds generated in the two environments differ in growth and collapse duration, void fraction, shape, and size. This study furthers our understanding of the dynamics of bubble clouds induced by histotripsy.


Subject(s)
Connective Tissue/anatomy & histology , Connective Tissue/radiation effects , Lithotripsy/methods , Ultrasonic Therapy/methods , Animals , Signal Processing, Computer-Assisted , Swine
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