Pancreatic TumorDNCT06641947
Differentiation Benign and Malignant Pancreatic Lesions
An observational study of Pancreatic Tumor, run by First Affiliated Hospital of Chongqing Medical University at 1 site in China.
Trial summary
The MVIT-MLKA model, with its complex architecture combining CNNs and Transformers, excels in image feature extraction and capturing long-range dependencies. This gives it strong adaptability and robustness in lesion detection and classification tasks. Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- Pancreatic Tumor
- What is being tested?
- Whipple procedure
- Type of treatment
- Surgery or procedure
- How many people
- 864 participants
- Where
- 1 siteChina
- Study dates
- 11 Jan 2022to 20 Sep 2024
- 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 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: all people were selected from three medical centers in chongqing province
Who may be able to join
- All patients with malignant pancreatic lesions had confirmed histopathology according to the 8th edition of the American Joint Committee on Cancer TNM staging system [25]; Lesions were classified as benign if they had either histopathologic confirmation or demonstrated benign characteristics with stability over at least one year of follow-up on CT or MRI imaging; (2) Patients underwent preoperative abdominal contrast-enhanced CT scans; (3) No anti-tumor treatment was conducted before the CT scan
Who cannot join
- Patients with significant motion artifacts or other imaging issues; (2) A time gap of one month or more between the CT scan and subsequent surgery; (3) Tumors less than 10 mm in maximum diameter.
Trial locations and contacts
1 site in 1 country.
China1 site
the First Affiliated Hospital of Chongqing Medical University
Chongqing, Chongqing Municipality, 400016
About this study
Official title: Enhancing the Accuracy of Classifying Benign and Malignant Pancreatic Lesions Using the MVIT-MLKA Model: A Comprehensive Evaluation and Comparative Study
The MVIT-MLKA model, with its complex architecture combining CNNs and Transformers, excels in image feature extraction and capturing long-range dependencies. This gives it strong adaptability and robustness in lesion detection and classification tasks. Compared to traditional machine learning methods and other deep learning models, MVIT-MLKA not only performs better in terms of accuracy, sensitivity, and specificity but also helps reduce inter-observer variability, enhancing diagnostic consistency among physicians.
Although the model showed slight fluctuations in performance on external datasets, it still outperforms other models overall and holds significant potential for clinical applications. With further optimization to improve its generalization capabilities, MVIT-MLKA could become a powerful tool for diagnosing benign and malignant lesions, providing more consistent and accurate support in clinical practice.
Read the detailed description
Accurate differentiation between benign and malignant pancreatic lesions is critical for patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography images to predict benign and malignant pancreatic lesions. This retrospective study across three medical centers constituted a training cohort, an internal testing cohort, and an external validation cohorts. A novel hybrid model, Multi-Scale Large Kernel Attention with Mobile Vision Transformer (MVIT-MLKA), integrating CNN and Transformer architectures, was developed to classify pancreatic lesions. We compared the model's performance with traditional machine learning and deep learning methods. Moreover, we evaluated radiologists' diagnostic accuracy with and without the optimal model assistance.The MVIT-MLKA model demonstrated superior performance for predicting pancreatic lesions, outperforming traditional models and standard CNNs and Transformers. Radiologists assisted by the MVIT-MLKA model showed significant improvements in diagnostic performance compared to those without model assistance, with notable increases in both accuracy and sensitivity. Model interpretability was enhanced through Grad-CAM visualization, effectively highlighting key lesion areas.The MVIT-MLKA model effectively differentiates between benign and malignant pancreatic lesions, surpassing traditional methods and enhancing radiologist performance. This suggests that integrating advanced deep learning model into clinical practice has the potential to reduce diagnostic errors and optimize treatment strategies in clinical practices.
- Conditions
- Pancreatic Tumor
- Being tested
- Whipple procedure
- Medical subject headings
- Pancreatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Whipple procedureProcedure or surgery
Typically used for treating pancreatic cancer, particularly tumors located in the head of the pancreas.
| Study group | Role | What they receive |
|---|---|---|
| benign and malignant | Benign Lesion Group: This cohort includes patients diagnosed with benign pancreatic lesions, such as pancreatic cysts or neuroendocrine tumors. These patients typically do not require aggressive treatments like surgery or chemotherapy and are managed with regular monitoring and non-invasive interventions. Histopathological confirmation or stability over a minimum of one year of follow-up without progression is used to classify lesions as benign.
Malignant Lesion Group: This cohort comprises patients diagnosed with malignant pancreatic lesions, such as pancreatic ductal adenocarcinoma (PDAC). These patients often require more aggressive treatment options, including surgery, chemotherapy, and radiotherapy. The malignancy of the lesions is confirmed through histopathological analysis, and the cohort focuses on cases with clear evidence of tumor growth and progression. Receives: Procedure: Whipple procedure |
What is being measured
The primary outcome is the main question the study is designed to answer.
overall survival time
The main outcome measure in this study was overall survival (OS), calculated from the date of the initial surgery to the date of death from any cause or the last follow-up.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Oct 2024
- Study start11 Jan 2022
- Primary completion5 Mar 2024
- Study completion20 Sep 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pancreatic TumorStudies of the same condition, open and under way.
- 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
- Retrospective
- Enrolment
- 864 participants (actual)
Sponsor and investigators
- Lead sponsor
- First Affiliated Hospital of Chongqing Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Liao Hongfan, First Affiliated Hospital of Chongqing Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06641947
- Sponsor's protocol ID
- observational
- Acronym
- D
- Status last verified
- Oct 2024
- First submitted
- 12 Oct 2024
- Last updated
- 15 Oct 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: We intend to make the IPD available to qualified researchers upon request. This will be subject to ethical approval and adherence to relevant data protection regulations.
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Enhancing the Accuracy of Classifying Benign and Malignant Pancreatic Lesions Using the MVIT-MLKA Model: A Comprehensive Evaluation and Comparative Study
- ClinicalTrials.gov ID
- NCT06641947
- Acronym / sponsor ID
- D / observational
- Conditions
- Pancreatic Tumor
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 864 participants (actual)
- Lead sponsor
- First Affiliated Hospital of Chongqing Medical UniversityUniversity, hospital or other
- Study start
- 11 Jan 2022 (actual)
- Primary completion
- 5 Mar 2024 (actual)
- Study completion
- 20 Sep 2024 (actual)
- First posted
- 15 Oct 2024 (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.
The MVIT-MLKA model, with its complex architecture combining CNNs and Transformers, excels in image feature extraction and capturing long-range dependencies. This gives it strong adaptability and robustness in lesion detection and classification tasks. Compared to traditional machine learning methods and other deep learning models, MVIT-MLKA not only performs better in terms of accuracy, sensitivity, and specificity but also helps reduce inter-observer variability, enhancing diagnostic consistency among physicians.
Although the model showed slight fluctuations in performance on external datasets, it still outperforms other models overall and holds significant potential for clinical applications. With further optimization to improve its generalization capabilities, MVIT-MLKA could become a powerful tool for diagnosing benign and malignant lesions, providing more consistent and accurate support in clinical practice.
Detailed description
Accurate differentiation between benign and malignant pancreatic lesions is critical for patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography images to predict benign and malignant pancreatic lesions. This retrospective study across three medical centers constituted a training cohort, an internal testing cohort, and an external validation cohorts. A novel hybrid model, Multi-Scale Large Kernel Attention with Mobile Vision Transformer (MVIT-MLKA), integrating CNN and Transformer architectures, was developed to classify pancreatic lesions. We compared the model's performance with traditional machine learning and deep learning methods. Moreover, we evaluated radiologists' diagnostic accuracy with and without the optimal model assistance.The MVIT-MLKA model demonstrated superior performance for predicting pancreatic lesions, outperforming traditional models and standard CNNs and Transformers. Radiologists assisted by the MVIT-MLKA model showed significant improvements in diagnostic performance compared to those without model assistance, with notable increases in both accuracy and sensitivity. Model interpretability was enhanced through Grad-CAM visualization, effectively highlighting key lesion areas.The MVIT-MLKA model effectively differentiates between benign and malignant pancreatic lesions, surpassing traditional methods and enhancing radiologist performance. This suggests that integrating advanced deep learning model into clinical practice has the potential to reduce diagnostic errors and optimize treatment strategies in clinical practices.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| benign and malignant | – | Procedure: Whipple procedureBenign Lesion Group: This cohort includes patients diagnosed with benign pancreatic lesions, such as pancreatic cysts or neuroendocrine tumors. These patients typically do not require aggressive treatments like surgery or chemotherapy and are managed with regular monitoring and non-invasive interventions. Histopathological confirmation or stability over a minimum of one year of follow-up without progression is used to classify lesions as benign. Malignant Lesion Group: This cohort comprises patients diagnosed with malignant pancreatic lesions, such as pancreatic ductal adenocarcinoma (PDAC). These patients often require more aggressive treatment options, including surgery, chemotherapy, and radiotherapy. The malignancy of the lesions is confirmed through histopathological analysis, and the cohort focuses on cases with clear evidence of tumor growth and progression. |
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- all people were selected from three medical centers in chongqing province
Key inclusion criteria (1 listed)
- All patients with malignant pancreatic lesions had confirmed histopathology according to the 8th edition of the American Joint Committee on Cancer TNM staging system [25]; Lesions were classified as benign if they had either histopathologic confirmation or demonstrated benign characteristics with stability over at least one year of follow-up on CT or MRI imaging; (2) Patients underwent preoperative abdominal contrast-enhanced CT scans; (3) No anti-tumor treatment was conducted before the CT scan
Key exclusion criteria (1 listed)
- Patients with significant motion artifacts or other imaging issues; (2) A time gap of one month or more between the CT scan and subsequent surgery; (3) Tumors less than 10 mm in maximum diameter.
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 |
|---|---|---|
| Whipple procedureTypically used for treating pancreatic cancer, particularly tumors located in the head of the pancreas. | Procedure or surgery | benign and malignant |
Primary outcome
overall survival time
Time frame: 1 year
The main outcome measure in this study was overall survival (OS), calculated from the date of the initial surgery to the date of death from any cause or the last follow-up.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2024.
- Individual participant dataSharing planned: No. We intend to make the IPD available to qualified researchers upon request. This will be subject to ethical approval and adherence to relevant data protection regulations.
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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.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pancreatic Tumor, run by First Affiliated Hospital of Chongqing Medical University at 1 site in China.
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: finished, as of the sponsor's last update on 15 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
overall survival time (time frame: 1 year). 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 15 Oct 2024.