Clinical trial NCT06497686: The Application of Rapid Fresh Digital Pathology on the Diagnosis and Biomarker Testing of Lung Cancer
Official title: The Application of Rapid Fresh Digital Pathology on the Diagnosis and Biomarker Testing of Lung Cancer
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Lung Cancer
Intraoperative Pathology
3D Pathology
Immunochemistry Staining
Lead sponsor: National Taiwan University Hospital
Sponsor class: OTHER
First posted: 2024-07-12
Enrollment: 300
Sex: ALL
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Following standard surgical procedures for lung cancer tumor resection, the investigators will directly obtain tissue from the post-operative specimens. Without affecting pathological diagnosis, staging, or the assessment of surgical safety margins, the investigators will collect tissue samples measuring approximately 0.5-2.0 cm x 0.5-2.0 cm x 0.3-2.0 cm from the lung cancer/tumor and the surrounding normal tissue or the junction between the tumor and its surrounding normal tissue. These samples will be used for microscopic imaging system detection of lung cancer/tumor tissue. This process, being different from the tissue sent for intraoperative pathological examination, will not affect subsequent diagnosis and treatment.

Brief summary: Through this project, the rapid staining process will be optimized for ex-vivo human lung specimens and integrate advanced ex-vivo mesoscale nonlinear optical gigascope. Initially, this will provide rapid digital pathological diagnosis during lung cancer surgeries. This will help achieve the dual goals of precise and efficient complete resection of lung cancer tissues while preserving tissue functionality. The application of this technology aims to provide higher-quality medical services for patients suffered from lung cancers.

Detailed description: Frozen section can provide rapid diagnosis during the operation, and its information is very important for surgeons to make decisions for the operative methods, especially for patients whose clinical conditions or lesions sites are inappropriate for biopsy. The frozen section procedure requires a pathological laboratory, a skilled technician, and an experienced pathologist. Not all pathological laboratories can perform the frozen section procedure. The frozen section can also cause frozen artifacts and tissue loss especially for small biopsy samples. In this study rapid fresh digital pathology combining the rapid whole-mount hematoxylin-eosin (H\&E) tissue staining (the-RTS) method and optical imaging via mesoscale nonlinear optical gigascope (mNLOG) will be used to obtain digital images with ultra-high resolution of resected lung specimens. These images will be analyzed by experienced pathologists and compared with H\&E-stained slides from traditional frozen section procedures to see if the rapid fresh digital pathology can be used as an alternative method for intraoperative frozen section procedure.

Moreover, the potential to use rapid fresh digital pathology in the detection of lung cancer biomarkers (including low-grade or high-grade patterns, invasive or in situ lesions, and STAS) and three-dimensional pathology will also be evaluated.

Eligibility criteria: Inclusion Criteria:

* (1) Adults aged 20 and above.
* (2) Patients diagnosed with lung cancer or lung tumors, scheduled for surgical resection.

A total of 300 patients are expected to be included.

Exclusion Criteria:

* (1) Patients unable to provide consent. (e.g., inability to speak, inability to communicate in Chinese, etc.).
* (2) Patients for whom a definitive pathological diagnosis cannot be established.
* (3) Patients suitable only for biopsy and not for surgical resection.
* (4) Exclude specimens that are too small or lesions that are too small to retain extra tissue.

Primary outcomes:
measure: Evaluate the feasibility of replacing frozen section pathology with rapid digital pathology diagnosis.
timeFrame: 1 years
Secondary outcomes:
measure: Utilize rapid digital pathology for biomarker detection and 3D pathology in lung cancer.
timeFrame: 1 year
Other outcomes:
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