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<p>The mechanical properties of tumor tissue differ from those of healthy tissue. Therefore, surgeons palpate accessible surgical sites to determine tumor boundaries prior to resection. However, palpation is not possible during minimally invasive surgery, so instrumented palpation is required instead. This study investigates the suitability of an engineering method that combines mechanical object scanning and indentation to determine Young’s modulus of soft, tissue-like materials. To establish a defined reference, we tested our concept on silicone phantoms containing stiff tumor-like inclusions. We used a sensor consisting of a load cell connected to a rigid probe with a spherical indenter tip. Young’s modulus was calculated by measured force, indentation depth, and indenter geometry. These results were compared with those of a palpation experiment on the same specimens, conducted with surgeons. Validation results reflect the accuracy of the method. Error in estimation of Young’s modulus is: soft material 6.7%, stiff material 44.9%. Repeatability is high, with a standard deviation &lt; 7%. By scanning a phantom and creating a stiffness image, we were able to identify the location and shape of the inclusion more clearly than experienced surgeons could using manual palpation. Looking ahead, the prospect of miniaturizing the presented technique for localizing tumor boundaries during surgery seems promising.</p>

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Proof of concept of a static approach to determine mechanical tissue properties during tumor surgery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月3日

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  • Max Jäger,
  • Katja Uhrhan,
  • Christine Mucha,
  • María Alejandra Guzmán Alfaro,
  • Hartmut Witte

摘要

The mechanical properties of tumor tissue differ from those of healthy tissue. Therefore, surgeons palpate accessible surgical sites to determine tumor boundaries prior to resection. However, palpation is not possible during minimally invasive surgery, so instrumented palpation is required instead. This study investigates the suitability of an engineering method that combines mechanical object scanning and indentation to determine Young’s modulus of soft, tissue-like materials. To establish a defined reference, we tested our concept on silicone phantoms containing stiff tumor-like inclusions. We used a sensor consisting of a load cell connected to a rigid probe with a spherical indenter tip. Young’s modulus was calculated by measured force, indentation depth, and indenter geometry. These results were compared with those of a palpation experiment on the same specimens, conducted with surgeons. Validation results reflect the accuracy of the method. Error in estimation of Young’s modulus is: soft material 6.7%, stiff material 44.9%. Repeatability is high, with a standard deviation < 7%. By scanning a phantom and creating a stiffness image, we were able to identify the location and shape of the inclusion more clearly than experienced surgeons could using manual palpation. Looking ahead, the prospect of miniaturizing the presented technique for localizing tumor boundaries during surgery seems promising.