Lung CancerLungCaMa3DNCT05565677
Prognostic Value of Lung Cancer MicroAnatomy in 3D
An observational study of Lung Cancer and Adenocarcinoma of Lung, run by Aristotle University Of Thessaloniki.
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Lung Cancer, Adenocarcinoma of Lung, Pathology
- What is being tested?
- micro-computed tomography scanning of lung tissue specimens
- Type of treatment
- Medical device
- How many people
- 50 participants
- Where
- No sites listed yet
- Study dates
- 1 Oct 2022to 1 Oct 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- Patients with a presumptive diagnosis of lung cancer for whom surgical resection or sampling will be clinically indicated.
Who cannot join
- Patients with altered mental status and those who are unable or unwilling to provide informed consent for specimen imaging.
Trial locations and contacts
No sites are listed yet.
About this study
Official title: Prognostic Value of Lung Cancer MicroAnatomy in Three Dimensions: a Micro-CT Based Trial
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.
Read more
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.
Read the detailed 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.
- Conditions
- Lung Cancer, Adenocarcinoma of Lung, Pathology, Micro-computed Tomography, X-ray Histology, Digital Pathology
- Being tested
- micro-computed tomography scanning of lung tissue specimens
- Keywords
- micro-CT, lung cancer, digital pathology
- Medical subject headings
- Lung Neoplasms, Adenocarcinoma of Lung
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
micro-computed tomography scanning of lung tissue specimensDevice
Micro-computed tomography will be utilized to scan surgically resected lung tissue specimens.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Device: micro-computed tomography scanning of lung tissue specimens |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Oct 2022
- Study start1 Oct 2022 (estimated)
- Primary completion1 Oct 2024 (estimated)
- Study completion1 Oct 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- More trials run by Aristotle University Of ThessalonikiThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Aristotle University Of Thessaloniki
- Sponsor type
- University, hospital or other
- Collaborators
- National and Kapodistrian University of Athens, University of Southampton
- Responsible party
- Principal investigator, Dimitrios Moysidis, Aristotle University Of Thessaloniki
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05565677
- Sponsor's protocol ID
- 5039
- Acronym
- LungCaMa3D
- Status last verified
- Oct 2022
- First submitted
- 29 Sep 2022
- Last updated
- 4 Oct 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 4 Oct 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prognostic Value of Lung Cancer MicroAnatomy in Three Dimensions: a Micro-CT Based Trial
- ClinicalTrials.gov ID
- NCT05565677
- Acronym / sponsor ID
- LungCaMa3D / 5039
- Conditions
- Lung Cancer, Adenocarcinoma of Lung, Pathology, Micro-computed Tomography, X-ray Histology, Digital Pathology
- Keywords
- micro-CT, lung cancer, digital pathology
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- Aristotle University Of ThessalonikiUniversity, hospital or other
- Collaborators
- National and Kapodistrian University of Athens, University of Southampton
- Study start
- 1 Oct 2022 (estimated)
- Primary completion
- 1 Oct 2024 (estimated)
- Study completion
- 1 Oct 2025 (estimated)
- First posted
- 4 Oct 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with lung cancer | – | Device: micro-computed tomography scanning of lung tissue specimensPatients 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (1 listed)
- Patients with a presumptive diagnosis of lung cancer for whom surgical resection or sampling will be clinically indicated.
Key exclusion criteria (1 listed)
- Patients with altered mental status and those who are unable or unwilling to provide informed consent for specimen imaging.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| micro-computed tomography scanning of lung tissue specimensMicro-computed tomography will be utilized to scan surgically resected lung tissue specimens. | Device | Patients with lung cancer |
Primary outcome
Correlation between micro-CT and histopathological findings
Time frame: 2 years
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.
Evaluation of specific morphometric measurements according to lung cancer type
Time frame: 2 years
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.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Oct 2022.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer and Adenocarcinoma of Lung, run by Aristotle University Of Thessaloniki.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 4 Oct 2022. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Andreas S Papazoglou, MD (+306945317584, anpapazoglou@yahoo.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Correlation between micro-CT and histopathological findings (time frame: 2 years). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Oct 2022.