Clinical application and research progress of rapid intraoperative diagnostic techniques for lung nodules_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

LIN Nengke ¹ , YUAN Xinyu ¹ , XU Jiansong ¹ , LU Xiansheng ² , ZHOU Hu ¹ , CHEN Boming ¹ , CHEN Zhiming ¹ , WANG Zhizhi ¹ , LI Shaobin ¹ , FENG Siyang ¹ ,  LU Di ¹ ,  CAI Kaican ¹

1. Department of Thoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, P. R. China;
2. Department of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, P. R. China;

Corresponding?author：

LU Di, Email: ludi1989@smu.edu.cn; CAI Kaican, Email: caican@smu.edu.cn

Keywords：

Lung nodules; lung cancer; intraoperative rapid diagnosis; mass spectrometry; spectroscopy; bioelectrical impedance; dielectric properties; review

DOI：

10.7507/1007-4848.202605006

Video：

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Abstract Full text Figures/Tables Video References Cited by

Intraoperative rapid and accurate pathological diagnosis of lung nodules is crucial for formulating individualized surgical strategies. Frozen section remains the most widely used intraoperative diagnostic method. However, its diagnostic performance may be compromised by structural alterations of lung tissue and difficulties in distinguishing early-stage lung adenocarcinoma subtypes. Modified frozen section techniques and rapid immunohistochemistry have improved diagnostic accuracy to some extent through optimized specimen preparation and the incorporation of molecular marker detection. In recent years, emerging diagnostic technologies based on physical and chemical signals, including mass spectrometry, spectroscopy, and bioelectrical impedance spectroscopy, have developed rapidly. By analyzing the molecular composition, optical characteristics, or dielectric properties of tissues, these techniques enable rapid identification of lung nodules and have shown promising potential for tumor discrimination and histological classification. This article reviews the current advances in intraoperative rapid diagnostic techniques for lung nodules.

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2.	Riely GJ, Wood DE, Ettinger DS, et al. Non-small cell lung cancer, version 4. 2024, NCCN clinical practice guidelines in oncology[J]. J Natl Compr Canc Netw, 2024, 22(4): 249-274.
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4.	Laakman JM, Chen SJ, Lake KS, et al. Frozen section quality assurance: using separate frozen section slide preparation times and interpretative time measurements to improve process[J]. Am J Clin Pathol, 2021, 156(3): 461-470.
5.	Dehan LM, Lewis JS, Mehrad M, et al. Patterns of major frozen section interpretation error: an in-depth analysis from a complex academic surgical pathology practice[J]. Am J Clin Pathol, 2023, 160(3): 247-254.
6.	Dong J, Chen Y, Qian W, et al. Sub-lobar resection versus lobectomy for challenging intraoperative frozen sections in lung adenocarcinoma within 3 cm[J]. Asian J Surg, 2024, 47(12): 5113-5117.
7.	Eguchi T, Kameda K, Lu S, et al. Lobectomy is associated with better outcomes than sublobar resection in spread through air spaces (STAS)-positive T1 lung adenocarcinoma: a propensity score-matched analysis[J]. J Thorac Oncol, 2019, 14(1): 87-98.
8.	Myung JK, Choe G, Chung DH, et al. A simple inflation method for frozen section diagnosis of minute precancerous lesions of the lung[J]. Lung Cancer, 2008, 59(2): 198-202.
9.	Xu X, Chung J, Jheon S, et al. The accuracy of frozen section diagnosis of pulmonary nodules: evaluation of inflation method during intraoperative pathology consultation with cryosection[J]. J Thorac Oncol, 2010, 5(1): 39-44.
10.	Xiang Z, Zhang J, Zhao J, et al. An effective inflation treatment for frozen section diagnosis of small-sized lesions of the lung[J]. J Thorac Dis, 2020, 12(4): 1488-1495.
11.	Liu S, Wang R, Zhang Y, et al. Precise diagnosis of intraoperative frozen section is an effective method to guide resection strategy for peripheral small-sized lung adenocarcinoma[J]. J Clin Oncol, 2016, 34(4): 307-313.
12.	Raman V, Jawitz OK, Voigt SL, et al. The effect of tumor size and histologic findings on outcomes after segmentectomy vs lobectomy for clinically node-negative non-small cell lung cancer[J]. Chest, 2021, 159(1): 390-400.
13.	Toda H, Minamiya Y, Kagaya M, et al. A novel immunohistochemical staining method allows ultrarapid detection of lymph node micrometastases while conserving antibody[J]. Acta Histochem Cytochem, 2011, 44(3): 133-139.
14.	Imai K, Nanjo H, Takashima S, et al. Intraoperative diagnosis of lymph node metastasis during segmentectomy for non-small cell lung cancer by rapid immunohistochemistry using noncontact alternating current electric field mixing[J]. Thorac Cancer, 2020, 11(12): 3547-3554.
15.	Kuriyama S, Imai K, Nanjo H, et al. Multiplex intraoperative rapid immunohistochemistry with noncontact antibody mixing for distinguishing the histologic phenotype of lung cancer[J]. Pathobiology, 2024, 91(6): 383-392.
16.	Perez CJ, Bagga AK, Prova SS, et al. Review and perspectives on the applications of mass spectrometry imaging under ambient conditions[J]. Rapid Commun Mass Spectrom, 2019, 33 Suppl 3: 27-53.
17.	Norris JL, Caprioli RM. Analysis of tissue specimens by matrix-assisted laser desorption/ionization imaging mass spectrometry in biological and clinical research[J]. Chem Rev, 2013, 113(4): 2309-2342.
18.	Brégeon F, Brioude G, De Dominicis F, et al. MALDI-TOF mass spectrometry for the rapid diagnosis of cancerous lung nodules[J/OL]. PLoS One, 2014, 9(5): e97511. DOI: 10.1371/journal.pone.0097511.
19.	Brioude G, Brégeon F, Trousse D, et al. Rapid diagnosis of lung tumors, a feasibility study using MALDI-TOF mass spectrometry[J/OL]. PLoS One, 2016, 11(5): e155449. DOI: 10.1371/journal.pone.0155449.
20.	Djambazova KV, van Ardenne JM, Spraggins JM. Advances in imaging mass spectrometry for biomedical and clinical research[J/OL]. TrAC Trends Anal Chem, 2023, 169: 117344. DOI: 10.1016/j.trac.2023.117344.
21.	Marien E, Meister M, Muley T, et al. Non-small cell lung cancer is characterized by dramatic changes in phospholipid profiles[J]. Int J Cancer, 2015, 137(7): 1539-1548.
22.	Neumann JM, Freitag H, Hartmann JS, et al. Subtyping non-small cell lung cancer by histology-guided spatial metabolomics[J]. J Cancer Res Clin Oncol, 2022, 148(2): 351-360.
23.	Thirukumaran M, Singh V, Arao Y, et al. Solid-phase microextraction-probe electrospray ionization devices for screening and quantitating drugs of abuse in small amounts of biofluids[J/OL]. Talanta, 2021, 231: 122317. DOI: 10.1016/j.talanta.2021.122317.
24.	Shigeeda W, Yoshimura R, Fujita Y, et al. Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor[J]. Thorac Cancer, 2022, 13(2): 202-209.
25.	Soudah T, Zoabi A, Margulis K. Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies[J]. Mass Spectrom Rev, 2023, 42(2): 751-778.
26.	Bensussan AV, Lin J, Guo C, et al. Distinguishing non-small cell lung cancer subtypes in fine needle aspiration biopsies by desorption electrospray ionization mass spectrometry imaging[J]. Clin Chem, 2020, 66(11): 1424-1433.
27.	Sch?fer K, Dénes J, Albrecht K, et al. In vivo, in situ tissue analysis using rapid evaporative ionization mass spectrometry[J]. Angew Chem Int Ed Engl, 2009, 48(44): 8240-8242.
28.	Balog J, Sasi-Szabó L, Kinross J, et al. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry[J/OL]. Sci Transl Med, 2013, 5(194): 194ra93. DOI: 10.1126/scitranslmed.3005623.
29.	Basu SS, Regan MS, Randall EC, et al. Rapid MALDI mass spectrometry imaging for surgical pathology[J/OL]. NPJ Precis Oncol, 2019, 3: 17. DOI: 10.1038/s41698-019-0089-y.
30.	Di L, Eichberg DG, Huang K, et al. Stimulated Raman histology for rapid intraoperative diagnosis of gliomas[J/OL]. World Neurosurg, 2021, 150: e135-e143. DOI: 10.1016/j.wneu.2021.02.122.
31.	Conti F, D'Acunto M, Caudai C, et al. Raman spectroscopy and topological machine learning for cancer grading[J/OL]. Sci Rep, 2023, 13(1): 7282. DOI: 10.1038/s41598-023-34457-5.
32.	Ko?ciński M, Markiewicz R, Jagielski J. Size-dependent cellular fate of polystyrene particles in human fibroblasts: a label-free Raman imaging study[J/OL]. Spectrochim Acta A Mol Biomol Spectrosc, 2026, 358: 127883. DOI: 10.1016/j.saa.2026.127883.
33.	Bourbousson M, Soomro I, Baldwin D, et al. Ex vivo Raman spectroscopy mapping of lung tissue: label-free molecular characterization of nontumorous and cancerous tissues[J/OL]. J Med Imaging (Bellingham), 2019, 6(3): 36001. DOI: 10.1117/1.jmi.6.3.036001.
34.	Qi Y, Yang L, Liu B, et al. Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning[J/OL]. Spectrochim Acta A Mol Biomol Spectrosc, 2022, 265: 120400. DOI: 10.1016/j.saa.2021.120400.
35.	Dai B, Han D, Miao Y, et al. Accurate categorization and rapid pathological diagnosis correction with micro-Raman technique in human lung adenocarcinoma infiltration level[J]. Transl Lung Cancer Res, 2024, 13(4): 885-900.
36.	Cucureanu V, Matei A, Avram AM. FTIR spectroscopy for carbon family study[J]. Crit Rev Anal Chem, 2016, 46(6): 502-520.
37.	Akalin A, Ergin A, Remiszewski S, et al. Resolving interobserver discrepancies in lung cancer diagnoses by spectral histopathology[J]. Arch Pathol Lab Med, 2019, 143(2): 157-173.
38.	Gro?erueschkamp F, Kallenbach-Thieltges A, Behrens T, et al. Marker-free automated histopathological annotation of lung tumour subtypes by FTIR imaging[J]. Analyst, 2015, 140(7): 2114-2120.
39.	Herrando AI, Castillo-Martin M, Galzerano A, et al. Dual excitation spectral autofluorescence lifetime and reflectance imaging for fast macroscopic characterization of tissues[J]. Biomed Opt Express, 2024, 15(6): 3507-3522.
40.	Yang X, Chen A, U K, et al. Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy[J/OL]. Thorac Cancer, 2025, 16(1): e15476. DOI: 10.1111/1759-7714.15476.
41.	Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography[J]. Science, 1991, 254(5035): 1178-1181.
42.	Liu H, Lin M, Chang W, et al. Rapid on-site AI-assisted grading for lung surgery based on optical coherence tomography[J/OL]. Cancers (Basel), 2023, 15(22): 5388. DOI: 10.3390/cancers15225388.
43.	Song CL, Kazarian SG. Effect of controlled humidity and tissue hydration on colon cancer diagnostic via FTIR spectroscopic imaging[J]. Anal Chem, 2020, 92(14): 9691-9698.
44.	Abasi S, Aggas JR, Garayar-Leyva GG, et al. Bioelectrical impedance spectroscopy for monitoring mammalian cells and tissues under different frequency domains: a review[J]. ACS Meas Sci Au, 2022, 2(6): 495-516.
45.	Sasaki K, Porter E, Rashed EA, et al. Measurement and image-based estimation of dielectric properties of biological tissues-past, present, and future[J/OL]. Phys Med Biol, 2022, 67(14): 145901. DOI: 10.1088/1361-6560/ac7b64.
46.	Wang S, Zhang J, Gharbi O, et al. Electrochemical impedance spectroscopy[J/OL]. Nat Rev Methods Primers, 2021, 1(1): 41. DOI: 10.1038/s43586-021-00039-w.
47.	Sun C, Zhu X, Ma C, et al. Electrical properties of human lung nodules in vitro from 100 Hz to 100 MHz[J]. IEEE Trans Biomed Eng, 2024, 71(4): 1355-1369.
48.	Bogdanowicz L, Fidaner O, Ceres D, et al. The Cole relaxation frequency as a parameter to identify cancer in lung tissue: preliminary animal andi patient studies[J/OL]. JMIR Biomed Eng, 2022, 7(1): e35346. DOI: 10.2196/35346.
49.	Farina L, Ruvio G, Shatwan R, et al. Histology-validated dielectric characterisation of lung carcinoma tissue for microwave thermal ablation applications[J/OL]. Cancers (Basel), 2023, 15(14): 3738. DOI: 10.3390/cancers15143738.
50.	Lu D, Peng J, Wang Z, et al. Dielectric property measurements for the rapid differentiation of thoracic lymph nodes using XGBoost in patients with non-small cell lung cancer: a self-control clinical trial[J]. Transl Lung Cancer Res, 2022, 11(3): 342-356.
51.	Montoya-Villada S, Reyes-Vera E, Orozco J. Microwave technologies for biomedical diagnosis and therapy: advances, challenges, and perspectives[J/OL]. Mikrochim Acta, 2026, 193(4): 303. DOI: 10.1007/s00604-025-07826-2.
52.	Gurjar N, Bailey K, El-Shenawee M. Polarimetry terahertz imaging of human breast cancer surgical specimens[J/OL]. J Med Imaging (Bellingham), 2024, 11(6): 65503. DOI: 10.1117/1.jmi.11.6.065503.

1. Church TR, Black WC, Aberle DR, et al. Results of initial low-dose computed tomographic screening for lung cancer[J]. N Engl J Med, 2013, 368(21): 1980-1991.
2. Riely GJ, Wood DE, Ettinger DS, et al. Non-small cell lung cancer, version 4. 2024, NCCN clinical practice guidelines in oncology[J]. J Natl Compr Canc Netw, 2024, 22(4): 249-274.
3. Ak?am TO, K?se E, Kahraman Ayd?n S, et al. Diagnostic efficacy of intraoperative histopathological examination of lesions with unknown diagnosis suspicious for malignancy[J/OL]. Heliyon, 2023, 9(12): e22405. DOI: 10.1016/j.heliyon.2023.e22405.
4. Laakman JM, Chen SJ, Lake KS, et al. Frozen section quality assurance: using separate frozen section slide preparation times and interpretative time measurements to improve process[J]. Am J Clin Pathol, 2021, 156(3): 461-470.
5. Dehan LM, Lewis JS, Mehrad M, et al. Patterns of major frozen section interpretation error: an in-depth analysis from a complex academic surgical pathology practice[J]. Am J Clin Pathol, 2023, 160(3): 247-254.
6. Dong J, Chen Y, Qian W, et al. Sub-lobar resection versus lobectomy for challenging intraoperative frozen sections in lung adenocarcinoma within 3 cm[J]. Asian J Surg, 2024, 47(12): 5113-5117.
7. Eguchi T, Kameda K, Lu S, et al. Lobectomy is associated with better outcomes than sublobar resection in spread through air spaces (STAS)-positive T1 lung adenocarcinoma: a propensity score-matched analysis[J]. J Thorac Oncol, 2019, 14(1): 87-98.
8. Myung JK, Choe G, Chung DH, et al. A simple inflation method for frozen section diagnosis of minute precancerous lesions of the lung[J]. Lung Cancer, 2008, 59(2): 198-202.
9. Xu X, Chung J, Jheon S, et al. The accuracy of frozen section diagnosis of pulmonary nodules: evaluation of inflation method during intraoperative pathology consultation with cryosection[J]. J Thorac Oncol, 2010, 5(1): 39-44.
10. Xiang Z, Zhang J, Zhao J, et al. An effective inflation treatment for frozen section diagnosis of small-sized lesions of the lung[J]. J Thorac Dis, 2020, 12(4): 1488-1495.
11. Liu S, Wang R, Zhang Y, et al. Precise diagnosis of intraoperative frozen section is an effective method to guide resection strategy for peripheral small-sized lung adenocarcinoma[J]. J Clin Oncol, 2016, 34(4): 307-313.
12. Raman V, Jawitz OK, Voigt SL, et al. The effect of tumor size and histologic findings on outcomes after segmentectomy vs lobectomy for clinically node-negative non-small cell lung cancer[J]. Chest, 2021, 159(1): 390-400.
13. Toda H, Minamiya Y, Kagaya M, et al. A novel immunohistochemical staining method allows ultrarapid detection of lymph node micrometastases while conserving antibody[J]. Acta Histochem Cytochem, 2011, 44(3): 133-139.
14. Imai K, Nanjo H, Takashima S, et al. Intraoperative diagnosis of lymph node metastasis during segmentectomy for non-small cell lung cancer by rapid immunohistochemistry using noncontact alternating current electric field mixing[J]. Thorac Cancer, 2020, 11(12): 3547-3554.
15. Kuriyama S, Imai K, Nanjo H, et al. Multiplex intraoperative rapid immunohistochemistry with noncontact antibody mixing for distinguishing the histologic phenotype of lung cancer[J]. Pathobiology, 2024, 91(6): 383-392.
16. Perez CJ, Bagga AK, Prova SS, et al. Review and perspectives on the applications of mass spectrometry imaging under ambient conditions[J]. Rapid Commun Mass Spectrom, 2019, 33 Suppl 3: 27-53.
17. Norris JL, Caprioli RM. Analysis of tissue specimens by matrix-assisted laser desorption/ionization imaging mass spectrometry in biological and clinical research[J]. Chem Rev, 2013, 113(4): 2309-2342.
18. Brégeon F, Brioude G, De Dominicis F, et al. MALDI-TOF mass spectrometry for the rapid diagnosis of cancerous lung nodules[J/OL]. PLoS One, 2014, 9(5): e97511. DOI: 10.1371/journal.pone.0097511.
19. Brioude G, Brégeon F, Trousse D, et al. Rapid diagnosis of lung tumors, a feasibility study using MALDI-TOF mass spectrometry[J/OL]. PLoS One, 2016, 11(5): e155449. DOI: 10.1371/journal.pone.0155449.
20. Djambazova KV, van Ardenne JM, Spraggins JM. Advances in imaging mass spectrometry for biomedical and clinical research[J/OL]. TrAC Trends Anal Chem, 2023, 169: 117344. DOI: 10.1016/j.trac.2023.117344.
21. Marien E, Meister M, Muley T, et al. Non-small cell lung cancer is characterized by dramatic changes in phospholipid profiles[J]. Int J Cancer, 2015, 137(7): 1539-1548.
22. Neumann JM, Freitag H, Hartmann JS, et al. Subtyping non-small cell lung cancer by histology-guided spatial metabolomics[J]. J Cancer Res Clin Oncol, 2022, 148(2): 351-360.
23. Thirukumaran M, Singh V, Arao Y, et al. Solid-phase microextraction-probe electrospray ionization devices for screening and quantitating drugs of abuse in small amounts of biofluids[J/OL]. Talanta, 2021, 231: 122317. DOI: 10.1016/j.talanta.2021.122317.
24. Shigeeda W, Yoshimura R, Fujita Y, et al. Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor[J]. Thorac Cancer, 2022, 13(2): 202-209.
25. Soudah T, Zoabi A, Margulis K. Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies[J]. Mass Spectrom Rev, 2023, 42(2): 751-778.
26. Bensussan AV, Lin J, Guo C, et al. Distinguishing non-small cell lung cancer subtypes in fine needle aspiration biopsies by desorption electrospray ionization mass spectrometry imaging[J]. Clin Chem, 2020, 66(11): 1424-1433.
27. Sch?fer K, Dénes J, Albrecht K, et al. In vivo, in situ tissue analysis using rapid evaporative ionization mass spectrometry[J]. Angew Chem Int Ed Engl, 2009, 48(44): 8240-8242.
28. Balog J, Sasi-Szabó L, Kinross J, et al. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry[J/OL]. Sci Transl Med, 2013, 5(194): 194ra93. DOI: 10.1126/scitranslmed.3005623.
29. Basu SS, Regan MS, Randall EC, et al. Rapid MALDI mass spectrometry imaging for surgical pathology[J/OL]. NPJ Precis Oncol, 2019, 3: 17. DOI: 10.1038/s41698-019-0089-y.
30. Di L, Eichberg DG, Huang K, et al. Stimulated Raman histology for rapid intraoperative diagnosis of gliomas[J/OL]. World Neurosurg, 2021, 150: e135-e143. DOI: 10.1016/j.wneu.2021.02.122.
31. Conti F, D'Acunto M, Caudai C, et al. Raman spectroscopy and topological machine learning for cancer grading[J/OL]. Sci Rep, 2023, 13(1): 7282. DOI: 10.1038/s41598-023-34457-5.
32. Ko?ciński M, Markiewicz R, Jagielski J. Size-dependent cellular fate of polystyrene particles in human fibroblasts: a label-free Raman imaging study[J/OL]. Spectrochim Acta A Mol Biomol Spectrosc, 2026, 358: 127883. DOI: 10.1016/j.saa.2026.127883.
33. Bourbousson M, Soomro I, Baldwin D, et al. Ex vivo Raman spectroscopy mapping of lung tissue: label-free molecular characterization of nontumorous and cancerous tissues[J/OL]. J Med Imaging (Bellingham), 2019, 6(3): 36001. DOI: 10.1117/1.jmi.6.3.036001.
34. Qi Y, Yang L, Liu B, et al. Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning[J/OL]. Spectrochim Acta A Mol Biomol Spectrosc, 2022, 265: 120400. DOI: 10.1016/j.saa.2021.120400.
35. Dai B, Han D, Miao Y, et al. Accurate categorization and rapid pathological diagnosis correction with micro-Raman technique in human lung adenocarcinoma infiltration level[J]. Transl Lung Cancer Res, 2024, 13(4): 885-900.
36. Cucureanu V, Matei A, Avram AM. FTIR spectroscopy for carbon family study[J]. Crit Rev Anal Chem, 2016, 46(6): 502-520.
37. Akalin A, Ergin A, Remiszewski S, et al. Resolving interobserver discrepancies in lung cancer diagnoses by spectral histopathology[J]. Arch Pathol Lab Med, 2019, 143(2): 157-173.
38. Gro?erueschkamp F, Kallenbach-Thieltges A, Behrens T, et al. Marker-free automated histopathological annotation of lung tumour subtypes by FTIR imaging[J]. Analyst, 2015, 140(7): 2114-2120.
39. Herrando AI, Castillo-Martin M, Galzerano A, et al. Dual excitation spectral autofluorescence lifetime and reflectance imaging for fast macroscopic characterization of tissues[J]. Biomed Opt Express, 2024, 15(6): 3507-3522.
40. Yang X, Chen A, U K, et al. Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy[J/OL]. Thorac Cancer, 2025, 16(1): e15476. DOI: 10.1111/1759-7714.15476.
41. Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography[J]. Science, 1991, 254(5035): 1178-1181.
42. Liu H, Lin M, Chang W, et al. Rapid on-site AI-assisted grading for lung surgery based on optical coherence tomography[J/OL]. Cancers (Basel), 2023, 15(22): 5388. DOI: 10.3390/cancers15225388.
43. Song CL, Kazarian SG. Effect of controlled humidity and tissue hydration on colon cancer diagnostic via FTIR spectroscopic imaging[J]. Anal Chem, 2020, 92(14): 9691-9698.
44. Abasi S, Aggas JR, Garayar-Leyva GG, et al. Bioelectrical impedance spectroscopy for monitoring mammalian cells and tissues under different frequency domains: a review[J]. ACS Meas Sci Au, 2022, 2(6): 495-516.
45. Sasaki K, Porter E, Rashed EA, et al. Measurement and image-based estimation of dielectric properties of biological tissues-past, present, and future[J/OL]. Phys Med Biol, 2022, 67(14): 145901. DOI: 10.1088/1361-6560/ac7b64.
46. Wang S, Zhang J, Gharbi O, et al. Electrochemical impedance spectroscopy[J/OL]. Nat Rev Methods Primers, 2021, 1(1): 41. DOI: 10.1038/s43586-021-00039-w.
47. Sun C, Zhu X, Ma C, et al. Electrical properties of human lung nodules in vitro from 100 Hz to 100 MHz[J]. IEEE Trans Biomed Eng, 2024, 71(4): 1355-1369.
48. Bogdanowicz L, Fidaner O, Ceres D, et al. The Cole relaxation frequency as a parameter to identify cancer in lung tissue: preliminary animal andi patient studies[J/OL]. JMIR Biomed Eng, 2022, 7(1): e35346. DOI: 10.2196/35346.
49. Farina L, Ruvio G, Shatwan R, et al. Histology-validated dielectric characterisation of lung carcinoma tissue for microwave thermal ablation applications[J/OL]. Cancers (Basel), 2023, 15(14): 3738. DOI: 10.3390/cancers15143738.
50. Lu D, Peng J, Wang Z, et al. Dielectric property measurements for the rapid differentiation of thoracic lymph nodes using XGBoost in patients with non-small cell lung cancer: a self-control clinical trial[J]. Transl Lung Cancer Res, 2022, 11(3): 342-356.
51. Montoya-Villada S, Reyes-Vera E, Orozco J. Microwave technologies for biomedical diagnosis and therapy: advances, challenges, and perspectives[J/OL]. Mikrochim Acta, 2026, 193(4): 303. DOI: 10.1007/s00604-025-07826-2.
52. Gurjar N, Bailey K, El-Shenawee M. Polarimetry terahertz imaging of human breast cancer surgical specimens[J/OL]. J Med Imaging (Bellingham), 2024, 11(6): 65503. DOI: 10.1117/1.jmi.11.6.065503.

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Latest ArticlesClinical application and research progress of rapid intraoperative diagnostic techniques for lung nodules

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