Pre-operative Surgical Difficulty Stratification Using Predicted Tumor Perfusion and Consistency
Study on Preoperative Imaging for Precise Prediction of Surgical Difficulty, Efficacy, and Risks in Pituitary Adenoma Surgeries
Pituitary adenomas (PAs) are among the most prevalent lesions of the sella turcica, accounting for 10%-25% of all intracranial neoplasms. Pituitary macroadenomas (PMAs) are defined with a maximum diameter of over 1 cm. Tumor characteristics are key factors influencing surgical effectiveness and complications of PMAs, with tumor perfusion and consistency identified as major predictive factors in literature. Conventional sequences provide limited information for predicting the perfusion and consistency of pituitary adenomas. Advanced sequences offer additional insights. However, the efficacy of combining radiomic features from multiparametric sequences, incorporating both conventional and advanced sequences, has not yet been proved.
We aim to develop machine learning models that combines radiomic features developed from both conventional and advanced sequences to predict the perfusion and consistency of PMAs. Furthermore, we aim to demonstrate the clinically applicability of these models by constructing a MR-PIT stratification (Multiparametric Radiomic derived and tumor Perfusion and consIsTency based surgical difficulty stratification), which correlated with the surgical strategy and outcomes.
Study Overview
Status
Conditions
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
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Shanghai
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Shanghai, Shanghai, China, 200000
- Huashan Hospital
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- patients with tumor more than 2.5 cm of maximal diameter in the coronal plane
- Functional and non-functional pituitary tumors
Exclusion Criteria:
- incomplete image data
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
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Extent of resection
Time Frame: From enrollment to the end of treatment at 12 weeks
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From enrollment to the end of treatment at 12 weeks
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Secondary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
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Severe postoperative complications
Time Frame: From enrollment to the end of treatment at 12 weeks
|
From enrollment to the end of treatment at 12 weeks
|
Collaborators and Investigators
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Endocrine System Diseases
- Brain Diseases
- Central Nervous System Diseases
- Nervous System Diseases
- Neoplasms by Site
- Neoplasms
- Neoplasms by Histologic Type
- Endocrine Gland Neoplasms
- Neoplasms, Glandular and Epithelial
- Nervous System Neoplasms
- Central Nervous System Neoplasms
- Hypothalamic Diseases
- Hypothalamic Neoplasms
- Supratentorial Neoplasms
- Brain Neoplasms
- Adenoma
- Pituitary Neoplasms
- Pituitary Diseases
Other Study ID Numbers
- KY2022-709
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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