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Accepted for/Published in: JMIR Biomedical Engineering

Date Submitted: Dec 1, 2021
Open Peer Review Period: Dec 1, 2021 - Dec 8, 2021
Date Accepted: Jan 12, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

The Cole Relaxation Frequency as a Parameter to Identify Cancer in Lung Tissue: Preliminary Animal and Ex Vivo Patient Studies

Bogdanowicz L, Fidaner O, Ceres D, Grycuk A, Demos D

The Cole Relaxation Frequency as a Parameter to Identify Cancer in Lung Tissue: Preliminary Animal and Ex Vivo Patient Studies

JMIR Biomed Eng 2022;7(1):e35346

DOI: 10.2196/35346

PMID: 38875665

PMCID: 11041438

The Cole Relaxation Frequency as a Parameter to Identify Cancer in Lung Tissue: Preliminary Animal and ex vivo Patient Studies

  • Les Bogdanowicz; 
  • Onur Fidaner; 
  • Donato Ceres; 
  • Alex Grycuk; 
  • David Demos

ABSTRACT

Background:

Lung cancer is the world’s leading cause of cancer deaths, and diagnosis remains challenging. Lung cancer starts as small nodules; early and accurate diagnosis allows timely surgical resection of malignant nodules while avoiding unnecessary surgery in patients with benign nodules.

Objective:

The Cole Relaxation Frequency (CRF) is a derived electrical bioimpedance signature, which may be utilized to distinguish cancerous tissues from normal tissues.

Methods:

Human testing ex-vivo in freshly resected lung tissue, from 30 volunteer patients undergoing resection for non-small cell lung cancer. CRF of tumor and the distant normal lung tissue relative to tumor were compared to histopathology specimens to establish a potential algorithm for point-of-care diagnosis. Animal testing in-vivo: 20 mice were implanted with xenograft human lung cancer tumor cells injected subcutaneously into the right flank of each mouse. Spectral impedance measurements were taken on the tumors on live animals transcutaneously and on the tumors after euthenasia. These CRF measurements were compared to healthy mouse lung tissue. Porcine lung testing ex-vivo: Porcine Lungs were received with trachea. After removal of the vocal box a ventilator was attached to pressurize the lung and simulate breathing. At different location of the lobes, the lungs surface was cut to produce a pocket that could accomodate tumors obtained from in-vivo animal testing. The tumors were placed in the sub-surface of the lung and the electrode was placed on top of the lung surface directly over the tumor but with lung tissue between the tumor and the electrode. Spectral impedance measurements were taken when the lungs were in the deflated state, inflated state, and also during the inflation-deflation process to simulate breathing.

Results:

Among 60 specimens evaluated in 30 patients CRF allowed ready discrimination in patients with clear separation of CRF in tumor and distant normal tissue with a high degree of sensitivity (97%) and specificity (87%.) In the 25 xenograft small animal model specimens measured, the CRF aligns with the separation observed in the Human In-vivo measurements. The CRF was successfully measured of tumors implanted into ex-vivo porcine lungs and CRF measurements align with previous tests for pressurized and unpressurized lungs.

Conclusions:

As previously shown in breast tissue, CRF in the range of 1kHz – 10MHz was able to distinguish non-small cell lung cancer versus normal tissue. Further, as evidenced by in vivo small animal studies, perfused tumors have the same CRF signature as shown in breast tissue and human ex-vivo testing. Inflation and deflation of the lung have no effect on the CRF signature. With additional development, CRF derived from spectral impedance measurements may permit point-of-care diagnosis guiding surgical resection.


 Citation

Please cite as:

Bogdanowicz L, Fidaner O, Ceres D, Grycuk A, Demos D

The Cole Relaxation Frequency as a Parameter to Identify Cancer in Lung Tissue: Preliminary Animal and Ex Vivo Patient Studies

JMIR Biomed Eng 2022;7(1):e35346

DOI: 10.2196/35346

PMID: 38875665

PMCID: 11041438

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