Feasibility Study Incorporating Lung Function Imaging Into Radiation Therapy for Lung Cancer Patients
NCT ID: NCT02528942
Last Updated: 2021-07-22
Study Results
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View full resultsBasic Information
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COMPLETED
NA
101 participants
INTERVENTIONAL
2016-04-22
2021-01-25
Brief Summary
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Detailed Description
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Conditions
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Study Design
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NA
SINGLE_GROUP
TREATMENT
NONE
Study Groups
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Radiation therapy
The functional avoidance radiation therapy plan will be delivered using a standard course of radiation treatment on a linear accelerator. Patients will receive daily radiation treatment for 15-35 days.
Radiation therapy
Radiation therapy will be given to study patients.
Interventions
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Radiation therapy
Radiation therapy will be given to study patients.
Eligibility Criteria
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Inclusion Criteria
2. Lung Cancer patients that will undergo definitive radiation therapy defined as 45-75 Gy as part of standard of care for their disease
3. 18 years of age or older
4. Signed informed consent
5. Planned curative intent chemotherapy, delivered concurrently or sequentially in combination with radiotherapy
6. The patient's 4DCT-ventilation image meets image heterogeneity criteria
Exclusion Criteria
2. Patient receiving palliative radiation therapy (defined as less than 45 Gy)
18 Years
ALL
No
Sponsors
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National Cancer Institute (NCI)
NIH
University of Colorado, Denver
OTHER
Responsible Party
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Principal Investigators
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Yevgeniy Vinogradskiy, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Colorado, Denver
Locations
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University of Colorado Cancer Center
Aurora, Colorado, United States
Beaumont Health System
Royal Oak, Michigan, United States
Countries
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References
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Poiset SJ, Lombardo J, Castillo E, Castillo R, Jones B, Miften M, Kavanagh B, Dicker AP, Boyle C, Simone NL, Movsas B, Grills I, Rusthoven CG, Vinogradskiy Y, Wilson L. Patient-Reported Outcomes: Comparing Functional Avoidance and Standard Thoracic Radiation Therapy in Lung Cancer. JCO Clin Cancer Inform. 2025 Feb;9:e2400202. doi: 10.1200/CCI-24-00202. Epub 2025 Feb 4.
Porter EM, Myziuk NK, Quinn TJ, Lozano D, Peterson AB, Quach DM, Siddiqui ZA, Guerrero TM. Synthetic pulmonary perfusion images from 4DCT for functional avoidance using deep learning. Phys Med Biol. 2021 Aug 23;66(17). doi: 10.1088/1361-6560/ac16ec.
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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14-1856.cc
Identifier Type: -
Identifier Source: org_study_id
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