In the initial diagnosis of prostate cancer, digital rectal examination is usually the preferred method. However, due to the high subjectivity of the test, more objective and accurate tools are needed to evaluate and predict the development of prostate cancer. To address this, we propose a double-layer spring Fabry-Perot (FP) pressure sensor based on femtosecond laser two-photon polymerization 3D printing technology, which is prepared on the fiber end face for mechanical characterization of prostate cancer lesions. Unlike the traditional single-layer spring structure, the sensor adopts a double-layer spring structure, with the double-layer springs spliced together. This design ensures high sensitivity while also offering a large pressure detection range, solving the problem where the single-layer spring structure is either too long, affecting sensitivity, or too short, making it prone to breaking. The double-layer spring FP pressure sensor is compact and highly sensitive, with pressure detection resolution reaching the nN level. It can serve as a stable and reliable force sensor for the early diagnosis of prostate cancer.

The structure of the double-layer spring FP pressure sensor is designed using COMSOL software, and the parameters affecting the performance of the sensor are simulated and analyzed to achieve a balance between high sensitivity and a high development success rate. After designing the sensor structure, it is fabricated using femtosecond laser two-photon polymerization 3D printing technology. First, the fiber end face is preprocessed. The processed optical fiber is then placed in the fixture, and the fixture is fixed in the printing device. Next, the photoresist is dropped onto the center of the lens, and the micro-displacement platform is used to control the position of the optical fiber. The optical fiber core is aligned with the center of the lens through the program. After that, the processed model file is exported to NanoWrite software. Finally, the printing process is carried out. Once printing is completed, the optical fiber is removed from the printing equipment and immersed in isopropanol and propylene glycol monomethyl ether acetate to develop and clean the residual photoresist. The schematic diagram is shown in Fig. 6.

We analyze the change in the reflection spectrum under different pressures ranging from 0 to 1650 nN using a spectrometer. The fitting results show that the sensing structure exhibits good linearity in the range of 0 to 1650 nN, with a sensitivity of 2.82 nm/μN. Without changing any parameters, sample 2 is prepared, and the pressure detection experiment is carried out again. The sensitivity differs by only 0.1 nm/μN compared to that of sample 1, while maintaining good linearity, which indicates that the structure has good repeatability. To verify the stability of the sensing structure, we conduct a 4 h pressure observation experiment, and the reflection spectrum of the structure shows almost no shift. For the polymer structure, the temperature crosstalk issue could affect measurement accuracy. However, the temperature sensitivity of the sensing structure is much smaller than its pressure sensitivity. Additionally, in human prostate tissue, the temperature remains stable over a long period, so the temperature crosstalk issue can be ignored. The proposed sensor can thus be used as a stable and reliable force sensor for the early diagnosis of prostate cancer.

A double-layer spring FP microcavity pressure sensor structure is fabricated using femtosecond laser two-photon polymerization 3D printing technology. When the pressure changes from 0 to 1650 nN, the proposed structure exhibits a sensitivity of 2.82 nm/μN and a linearity of 0.997. The experimental results show that the proposed FP microcavity pressure sensor structure has good repeatability and demonstrates excellent stability when continuously monitoring pressure. This sensor has the characteristics of small size, high sensitivity, easy preparation, and low manufacturing cost. It can achieve high force resolution and, in principle, can identify sub-millimeter cancerous tissues in the early stage of prostate cancer, which provides a new possibility for the early diagnosis of prostate cancer.