Measuring tissue elasticity for tumor detection

Surgical resection is currently the most effective treatment for patients with soft-tissue tumors, which develop within connective tissues such as muscle and fat. To minimize the removal region and reduce the chance of recurrence, it is important to delineate the boundaries of the tumor prior to resection. As tumorigenesis involves a change in tissue stiffness, probing the mechanical properties (e.g. elasticity) of soft tissues could complement structural imaging (x-ray and magnetic resonance imaging, MRI) and improve tumor detection during surgery.

Elasticity measurements based on ultrasonic imaging and MRI have achieved success in the in vivo detection of human breast tumors. However, the lack of sufficient spatial resolution limits these techniques to operate at organ level, making them unsuitable for intra-operative tumor detection. Elasticity measurements based on optical coherence tomography (OCT), on the other hand, benefit from the high spatial and temporal resolutions of this technique. Current OCT-based methods for tumor detection largely rely on a piezoelectric transducer to induce tissue deformation, a method that may cause injury or alter tissue properties when used on delicate soft tissues such as those in the brain or lung. To address this issue and enable the maximum protection of tissue structures and functions, we combined a focused air-puff device with OCT, creating a system we called AP-OCT, for non-contact intra-operative detection of soft-tissue tumors through quantifying their elasticity.¹

Figure 1. (a) Schematic of the air-puff system combined with optical coherence tomography (AP-OCT). (b) OCT 3D image indicating the excitation and measurement points across tissue surface.

Figure 1(a) shows a schematic of our system, which includes two units: excitation and measurement. The focused air-puff system is used to induce surface waves (SWs) in soft tissues and a phase-sensitive OCT system is used to capture the propagation of the SWs across the tissue surface. Figure 1(b) shows a 3D OCT image indicating the distribution of the excitation and measurement positions. The system obtains the propagation velocity of the SWs and uses it to quantify the Young's modulus of the soft tissues with a simple and direct relationship. We can then differentiate soft-tissue tumors by comparing the elastic property of normal and pathological tissues.¹

The home-built air-puff system is able to generate a short-duration and low-pressure air stream that can be used for localized excitation of SWs. Our experimental results indicate that the excitation pressure on the tissue surface follows a clear relationship with the air-source pressure, the excitation distance between the port tip and the tissue surface, and the excitation angle relative to the tissue-surface normal. As the excitation unit, the air-puff system can provide a safe and easy-to-control stimulus for delicate soft tissues.²

After excitation, the SWs show a time delay at different positions along the wave-propagation direction, which we can record using the phase-sensitive OCT system. We performed pilot experiments on ex vivo human myxoma (a type of soft-tissue tumor) and normal fat and found that SWs propagate faster on the myxoma (see Figure 2). We calculated the SWs group velocity to be 1.45±0.28m/s and 1.02±0.33m/s for myxoma and normal fat, respectively. We also quantified a higher Young's modulus of 7.6±3.0kPa for myxoma compared with 3.5±2.2kPa for normal fat (see Figure 3).

Figure 2. Surface waves recorded at different spatial locations showing time delays detected on (a) myxoma and (b) normal fat.

Figure 3. Box plots of (a) the calculated group velocity of surface waves (SWs) and (b) the quantified Young's moduli for myxoma and normal fat. The solid dots and whiskers represent the mean values and standard deviations of data, respectively. P: Two-sample Kolmogorov-Smirnov test p value.

To test the AP-OCT system with samples of known elasticity, we performed the experiments on tissue-mimicking phantoms with gelatin concentrations of 10, 12, and 14% (weight/weight). Our estimated Young's moduli for the phantoms agreed well with the results measured from the uniaxial test, a mechanical testing method to directly measure the elasticity of a sample (see Figure 4).

Figure 4. Estimated Young's moduli for tissue-mimicking phantoms using the AP-OCT system. Results are compared with measurements from a uniaxial test.

Our experiments indicated that we can successfully use our non-contact AP-OCT system to determine the elasticity of soft tissues and that these quantitative measurements can be useful to detect tumors during surgery.^{1, 2} For our future work, we are seeking to extend the application of our technique to ocular tissues (e.g. cornea and crystalline lens) through the development of advanced elasticity-quantification models.

We acknowledge the funding from National Institutes of Health grant 1R01EY022362 and Federal Target Program 'Scientific and Scientific-Pedagogical Personnel of Innovative Russia' for the 2009–2013 grant 14.B37.21.1238.