Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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WITHDRAWN
OBSERVATIONAL
2024-07-31
2024-10-31
Brief Summary
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Detailed Description
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The Lung Cancer Screening Clinic is a new program that screens a group of patients that meet a predetermined criteria, set by the program, for lung cancer. At this time primary care providers, within the UIowa network, have the ability to place an order for this screening process for their patients. The hope is to expand this program to any primary care provider in the future. Clinic staff look over the patients past medical history to determine if they fit the clinic criteria.
For this study, the study team will ask the patients seen in the lung cancer screening clinic at the University of Iowa to undergo an additional standard dose CT scan during that same visit(for comparison/validation of the software performance). For those subjects that agree to participate, the study team will also ask to collect the data and CT scans that were also collected for their clinical Lung Cancer Screening visit. For this group the study team will also ask to collect all medical records associated with nodules found at this Lung Cancer Screening visit.
The study team propose to test the performance of VIDA's existing image analysis tools for the assessment of chronic obstructive pulmonary disease (COPD), when applied to the LDCT data acquired for lung cancer screening. The study team will also develop new lung nodule evaluation functions to specifically address the clinical needs within the at-risk lung cancer patient population.
To carry out the work, the study team propose two specific aims:
1. Validate VIDA's quantitative computed tomography (QCT) metrics for COPD and emphysema utilizing the lung cancer LDCT screening cohort as compared to the standard quantitative high resolution computed tomography (HRCT) scanning protocol. With collaboration between the University of Iowa and VIDA, the study team will establish a tightly controlled, CT data acquisition protocol in our local lung cancer screening program. Data collected will incorporate thin-slice and iterative reconstructions, breath coaching to target lung inflation levels for patients and HRCT data acquisition in a sub-cohort. The VIDA analysis will be refined and the appropriate reconstruction setting identified such that the outputs from the LDCT data correlate to the HRCT (current standard) outputs.
2. Complete and refine development of VIDA's novel lung nodule segmentation algorithm for solid and non-solid nodules using the standardized lung cancer LDCT screening protocol. Automated nodule segmentation in CT scans is challenging due to border ambiguity with neighboring structures (such as vessels and the pleura), poor boundary contrast of more subtle nodules, and noise associated with LDCT. The study team will develop a novel method that robustly segments pulmonary lesions by allowing mutual interaction between the nodules and surrounding structures, leading to a highly accurate segmentation with less manual corrective actions for a high volume lung cancer screening workflow.
Conditions
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Study Design
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COHORT
CROSS_SECTIONAL
Study Groups
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Lung Cancer Screening Cohort
Patients who are seen in the UIHC lung cancer screening clinic will be asked to undergo an additional standard chest CT scan during their UIHC clinical lung cancer screening CT scan. Additionally, data from that clinical scan and all medical records associated with nodules that were discovered by the Lung Cancer Screening, will also be collected.
Chest CT scan
Standard dose chest CT scan
Interventions
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Chest CT scan
Standard dose chest CT scan
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
50 Years
74 Years
ALL
No
Sponsors
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Vida Diagnostics, Inc
UNKNOWN
Jessica Sieren
OTHER
Responsible Party
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Jessica Sieren
Assistant Professor
Principal Investigators
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Jessica Sieren, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Iowa
Other Identifiers
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201603824
Identifier Type: -
Identifier Source: org_study_id
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