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Cancer Technologies

Cancer Technologies - Poster Session B

Poster H7 - Development of a noninvasive device for the quantitative characterization of melanoma in situ

Thursday, October 24, 2024
2:45 PM – 3:45 PM EST
Location: Exhibit Hall E, F & G

Introduction:  Melanoma, the deadliest form of skin cancer that arises in pigment-producing melanocytes and presents as pigmented lesions, will affect over 100,000 Americans in 2024. [1] Suspicious moles are typically visually assessed by dermatologists to determine whether they should be biopsied for histological analysis. [2] Unfortunately, for every 27.8 skin biopsies taken, only one results in a positive diagnosis, illustrating the subjective and morphological nature of a dermatologist’s assessment. [3,4] Tissue stiffness of melanomas may offer a numerical property by which to quantitatively assess lesions; however, mechanical properties of lesions are not factored into the melanoma screening process. The lack of established quantitative characteristics describing these properties, specifically for melanoma lesions, serves as a barrier to clinical usage of the information (Dr. Elise Ng, oral communication, July 2023).

Existing methods to quantify tissue mechanics are ex vivo, invasive, or lack the spatial and/or depth resolution necessary to assess melanoma lesions. Here is reported the first results of tests with a new device, which yields a numerical output that is subsequently converted to a measure of tissue elasticity. This device presents a noninvasive, maneuverable, and portable alternative to conventional tissue mechanics measurement approaches. Tests on three polymers of varying stiffnesses demonstrate the ability of the device to reliably differentiate between these materials. These results encourage further testing on murine/human tissue samples and are a promising first step in the path towards in situ characterization of melanoma tissue mechanics.

Materials and

Methods:  The prototype was designed and tested on three polymers with comparable elasticity to skin: Ecoflex™ 00-10, Dragon Skin™ 10, and Mold Star™ 16 (Smooth-On, Inc, Easton, Pennsylvania) (Table 1). Five trials per polymer were performed in a stabilized bench-top setup. A commercial tensile tester was used on all polymers as a control for reference, also with five trials per polymer. Results were analyzed using R Statistical Software.

Results, Conclusions, and Discussions: While significant differences (confirmed by two sample t-tests) were observed between the mechanical measurements of the three polymers determined using the prototype as compared to the commercial tensile tester, the relative magnitudes of the output produced for each polymer were successfully replicated and in accordance with the relative stiffnesses of the materials upon tactile inspection (Figure 1A).

Testing results from the high range modulus silicone (Mold Star) had the greatest amount of variation and the low range modulus silicone (Ecoflex) had the smallest. Variation was quantified using the standard deviation across the five trials, as well as with the percent error of the readout for each replicate with respect to the average readout of that polymer. One sample t-tests confirmed the average percent error across replicates for characterization of Mold Star was significant, but insignificant for the other two polymers (Figure 1B). It is worthwhile to note that higher variation in Mold Star measurements may be attributed to increased levels of uncontrolled system compliance when collecting measurements on stiffer materials.

The device was able to successfully differentiate between the polymers based on elasticity. While variance between trials was present and the difference between experimental and control readout was significant for all trials, the device was still able to correctly detect the relative levels of stiffness between the polymers. With future optimization of the device through use of more precise components and rigorous mathematical modeling, error between the device and control mechanical readouts can be reduced. Future testing on murine and human melanoma models is necessary to determine the extent of the device’s capabilities for melanoma detection in a biological context. These results validate the ability of the device to distinguish between stiffnesses comparable to melanoma and healthy tissue, confirming the potential for its application on tissues and eventually in situ within clinical practices. This suggests future potential for a non-invasive and objective approach to melanoma diagnosis that complements traditional visual assessments, improving detection rates while reducing unnecessary biopsies.

Acknowledgements (Optional):  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69(1):7-34. doi:10.3322/caac.21551
2. Garbe C, Amaral T, Peris K, et al. European consensus-based interdisciplinary guideline for melanoma. part 1: Diagnostics - update 2019. European journal of cancer (1990). 2020;126:141-158. https://pubmed.ncbi.nlm.nih.gov/31928887/. doi: 10.1016/j.ejca.2019.11.014.
3. Matsumoto M, Secrest A, Anderson A, Saul MI, Ho J, Kirkwood JM, Ferris LK. Estimating the cost of skin cancer detection by dermatology providers in a large healthcare system. Journal of the American Academy of Dermatology. 2017;78(4):701-709.e1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963718/. doi: 10.1016/j.jaad.2017.11.033.
4. Zhang Y, Moy AJ, Feng X, et al. Assessment of raman spectroscopy for reducing unnecessary biopsies for melanoma screening. Molecules (Basel, Switzerland). 2020;25(12):2852. https://www.ncbi.nlm.nih.gov/pubmed/32575717. doi: 10.3390/molecules25122852.