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Prognostic Value of Lung Cancer MicroAnatomy in 3D

NCT05565677 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 50

Last updated 2022-10-04

No results posted yet for this study

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

Interventions

DEVICE

micro-computed tomography scanning of lung tissue specimens

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

Sponsors & Collaborators

  • National and Kapodistrian University of Athens

    collaborator OTHER

  • University of Southampton

    collaborator OTHER

  • Aristotle University Of Thessaloniki

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-10-01
Primary Completion
2024-10-01
Completion
2025-10-01
FDA Device
Yes

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Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05565677 on ClinicalTrials.gov