Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT05565677 |
| Other study ID # |
5039 |
| Secondary ID |
|
| Status |
Not yet recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
October 1, 2022 |
| Est. completion date |
October 1, 2025 |
Study information
| Verified date |
October 2022 |
| Source |
Aristotle University Of Thessaloniki |
| Contact |
Andreas S Papazoglou, MD |
| Phone |
+306945317584 |
| Email |
anpapazoglou[@]yahoo.com |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial 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.
Description:
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.
Sample preparation Following surgical resection, human lung tissue specimens will be placed
in a sterile container by the surgeon in the operating room. Choice of container will be
based on specimen size. Right after the end of the operation, each specimen will be fixed in
neutral buffered formalin for 48 hours in tissue cassettes and will be embedded in paraffin
wax following a standardized protocol.
Imaging protocol After the collection of the formalin-fixed and paraffin-embedded (FFPE)
surgically resected lung cancer specimens, these will be transported to the μ-VIS X-ray
Imaging Centre at the University of Southampton in accordance with particular biological
material transfer agreement. The FFPE lung samples will be scanned at the μ-VIS X-ray Imaging
Centre using a custom-built Nikon Metrology micro-CT scanner according to standardized
protocol.
Histological assessment Following non-destructive micro-CT imaging, the scanned FFPE
specimens will be transported to the Pathology Laboratory of the First Pathology Department
of the National and Kapodistrian University of Athens in accordance with particular
biological material transfer agreement. The specimens will be set in paraffin blocks for
sectioning. After sectioning, sections will be de-paraffinized and stained using Movat's
pentachrome stain. The sections will be imaged and assessed histologically by an experienced
and "blinded" pulmonary pathologist (S.T.). The pathologist will also assess a number of
non-scanned FFPE lung cancer specimens to confirm the non-destructive nature of micro-CT
imaging for the resected specimens. Identification of radiation-induced or ischemic
alterations, deviant necrosis or cellular degeneration could be indicative outcomes of a
destructive imaging method.
Statistical analysis The generated imaging data will be statistically analyzed using
Bland-Altman plots to determine intra- and inter-observer variability in the interpretation
of micro-CT imaging data. Wilcoxon's rank sum test or Kruskal Wallis's test will be utilized
to evaluate any differences within specific morphometric measurements (percent object volume,
object surface/volume ratio, object surface density, structure model index, structure
thickness, structure linear density, structure separation, connectivity, connectivity
density) 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.
