Post-Operative Prediction of PulmonarY Function
ConditionLung Cancer
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity of Sydney
About this trial
Prediction of postoperative lung function is currently based on anatomical segment counting (ASC), which incorporates pulmonary function test (PFT) results. Standard PFTs such as spirometry can only measure pulmonary capacity as an average over the entire lung and do not take regional function differences into account. Nuclear medicine is recommended where regional functional imaging is required to inform surgical decisions. However, nuclear medicine scans are expensive, time consuming and not available in all institutions. CT-ventilation imaging is a cheaper and more accessible alternative to nuclear medicine for informing lung cancer patient treatment choices.
The primary aim is to quantify the difference between predicted postoperative values of pulmonary function metrics derived from CT ventilation imaging and standard anatomical segment counting method.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Aged 18 years or older.
ECOG performance status 0-2.
Lung cancer surgical candidates.
Undergo SPECT V/Q scans within 8 weeks of registration.
Disqualifiers
Interstitial lung disease.
Pregnant women.
Trial population
A pilot study is not a hypothesis testing study. Although this design has patients being their own control, the small sample size of 15 patients is unlikely to capture the full diversity of the population. Therefore, the statistical tests are for hypothesis generation and not definitive.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
The accuracy of CT ventilation imaging compared to ASC in predicting postoperative values of the pulmonary function metric FEV1
The accuracy of CT ventilation imaging compared to ASC in predicting postoperative values of the pulmonary function metric FEV1 will be assessed via a comparison with actual postoperative values measured from PFTs. CT ventilation images will be used to produce regionally-informed ppoFEV1 by proportionally reducing the pre-surgery FEV1 by the proportion of ventilation lost by removal of the surgical target section of lung. As this is an investigative study, it is not powered for a statistical analysis. Bland-Altman analysis will be used to quantify the ability of ASC and CT ventilation to predict ppoFEV1
Time frame
1 weekSecondary outcomes
1
The accuracy of CT ventilation imaging in predicting ppoFEV1
The accuracy of CT ventilation imaging in predicting ppoFEV1will be compared to that of SPECT ventilation imaging. Bland-Altman analysis will be used to quantify the ability of SPECT and CT ventilation to predict ppoFEV1
Time frame
1 week2
The regional pattern of ventilation from CT ventilation imaging will be compared to ventilation from SPECT using Spearman correlation.
The average Spearman correlation across all patients will be \> 0.6.
Time frame
1 week3
The regional pattern of perfusion from CT perfusion imaging will be compared to perfusion from SPECT using Spearman correlation.
The average Spearman correlation across all patients will be \> 0.6.
Time frame
1 weekLocations
1Map coordinates are unavailable for these locations. Locations are shown below instead.
Royal North Shore HospitalRecruiting2065, Saint Leonards, New South Wales
Australia
AustraliaSponsors and contacts
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University of Sydney
Lead sponsor
Royal North Shore Hospital
Collaborator
Source ClinicalTrials.gov