Prognostic Value of Lung Cancer MicroAnatomy in 3D

NCT05565677 | Unknown FDA Device

• 1 other identifier: 5039
• Study Type: observational
• Target: 50
• Locations: 0 countries
• Sites: N/A

Brief Summary

Micro-computed tomography (micro-CT) is a novel biomedical non-destructive, slide-free digital imaging modality, which enables the rapid acquisition of accurate high-resolution, volumetric images of intact surgical tissue specimens. This imaging modality provides microscopic level of detail of intact tissues in three-dimensions without requiring any specimen preparation. Its non-destructive nature and the ongoing enhancement of imaging resolution and contrast renders micro-CT imaging particularly well suited for microanatomic studies in basic research across a wide range of interventional medical disciplines, including oncology. Our proposal concerns a multidisciplinary basic research effort which aims to facilitate the effective identification of different -and maybe challenging to differentiate- lung cancer patterns based on 3D X-ray histology. As an alternative for the use of hematoxylin \& eosin (H\&E) slides, optimized micro-CT scanning of soft tissues emerges as a promising tool to enable non-invasive 3D X-ray histology of formalin-fixed and paraffin-embedded (FFPE) lung cancer specimens. The objective of our proposal is to offer novel insights into the complex architecture of each lung cancer subtype after imaging FFPE surgical specimens, resected from lung cancer surgeries. The investigators aim to generate 3D datasets of FFPE lung cancer tissues which will be combined with the corresponding conventional 2D histology slides. Our study will be also adequately empowered to identify particular differences in morphometric measurements according to each particular lung cancer growth pattern. Finally, this proposal aims to delineate the different 3D microanatomy and morphology of some patterns that are challenging to interpret and differentiate through traditional 2D histological evaluation, such as papillary and lepidic adenocarcinoma growth patterns. Classification of the histological subtypes based on 2D histology sections can be ambiguous, as shown by suboptimal inter-observer consensus when determining predominant histological subtypes in FFPE lung adenocarcinoma tissue specimens. Hence, micro-CT-based 3D imaging of the lung specimens could aid classification of histological subtypes by providing more comprehensive sampling of the entire tissue block and yielding detail relevant for subtype classification that might not be visible in 2D sections alone.

Conditions

Lung Cancer; Adenocarcinoma of Lung; Pathology; Micro-computed Tomography; X-ray Histology; Digital Pathology

Keywords

micro-CT; lung cancer; digital pathology

Outcome Measures

Primary Outcomes (2)

• Correlation between micro-CT and histopathological findings

  After co-registration of micro-CT and histopathological images via relevant software (e.g., ImageJ plugin: UnwarpJ elastic registration), a blinded pathologist (S.T.) will assess the co-aligned images to assess whether the investigator can identify the presence of lung cancer based on the generated 3D micro-CT images. The outcomes of this qualitative analysis will be statistically analyzed using Bland-Altman plots to determine intra- and inter-observer variability in the interpretation of micro-CT imaging data.

  2 years

• Evaluation of specific morphometric measurements according to lung cancer type

  Wilcoxon's rank sum test or Kruskal Wallis's test will be utilized to evaluate any differences within specific morphometric micro-CT based measurements among different growth patterns. All statistical analyses will be performed with SPSS (version 27) and a p-value of less than 0.05 will be considered as the threshold of statistical significance.

  2 years

Study Arms (1)

Patients with lung cancer

Patients with a presumptive diagnosis of lung cancer for whom surgical resection or sampling will be clinically indicated according to the standard practices of the Cardiothoracic Department of AHEPA University Hospital of Thessaloniki, will be enrolled in this prospective study once they give written informed consent for specimen imaging. Surgical resections will be performed per standard of care and there will be no difference in patients' clinical management depending on the acquisition or not of surgical specimens. Patients with altered mental status and those who are unable or unwilling to provide informed consent will be excluded from this study.

Device: micro-computed tomography scanning of lung tissue specimens

Interventions

micro-computed tomography scanning of lung tissue specimens DEVICE

Micro-computed tomography will be utilized to scan surgically resected lung tissue specimens.

Patients with lung cancer

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with a presumptive diagnosis of lung cancer for whom surgical resection or sampling will be clinically indicated according to the standard practices of the Cardiothoracic Department of AHEPA University Hospital of Thessaloniki, will be enrolled in this prospective study once they give written informed consent for specimen imaging. Surgical resections will be performed per standard of care and there will be no difference in patients' clinical management depending on the acquisition or not of surgical specimens. Patients with altered mental status and those who are unable or unwilling to provide informed consent will be excluded from this study.

You may qualify if:

• Patients with a presumptive diagnosis of lung cancer for whom surgical resection or sampling will be clinically indicated.

You may not qualify if:

• Patients with altered mental status and those who are unable or unwilling to provide informed consent for specimen imaging.

Sponsors & Collaborators

• Aristotle University Of Thessaloniki: lead
• National and Kapodistrian University of Athens: collaborator
• University of Southampton: collaborator

Biospecimen

Retention: SAMPLES WITH DNA

Lung tissue specimens will be surgically resected according to clinical indications (per standard of care) in patients with presumptive clinical diagnosis of lung cancer.

MeSH Terms

Conditions

Lung Neoplasms; Adenocarcinoma of Lung

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases; Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type

Central Study Contacts

Andreas S Papazoglou, MD

CONTACT

+306945317584; anpapazoglou@yahoo.com

Dimitrios V Moysidis, MD

CONTACT

+306984383937; dimoysidis@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: September 29, 2022
• First Posted: October 4, 2022
• Study Start: October 1, 2022
• Primary Completion: October 1, 2024
• Study Completion: October 1, 2025
• Last Updated: October 4, 2022

Record last verified: 2022-10

Data Sharing

• IPD Sharing: Will not share