Radiograph accelerated detection and identification of cancer in the lung (RADICAL): a mixed methods study to assess the clinical effectiveness and acceptability of Qure.ai artificial intelligence software to prioritise chest X-ray (CXR) interpretation.

INTRODUCTION: Diagnosing and treating lung cancer in early stages is essential for survival outcomes. The chest X-ray (CXR) remains the primary screening tool to identify lung cancers in the UK; however, there is a shortfall of radiologists, while demand continues to increase. Image analysis by machine-learning software has the potential to support radiology workflows with a focus on immediate triage of suspicious X-rays. The RADICAL study will evaluate Qure.ai's 'qXR' software in reducing reporting time for suspicious X-rays in NHS Greater Glasgow & Clyde. METHODS AND ANALYSIS: This is a stepped-wedge cluster-randomised study consisting of a retrospective technical evaluation and prospective clinical effectiveness study alongside the assessment of acceptability via qualitative work and evaluation of cost-effectiveness via a cost utility analysis. The primary objective is to assess the clinical effectiveness of qXR to prioritise patients suspected with lung cancer on CXR for follow-up CT. Secondary objectives will look at the utility, safety, technical performance, health economics and acceptability of the intervention. The study period is 24 months, consisting of an initial 12 month data collection period and a 12 month follow-up period. All the standard care CXRs from outpatient and primary care requests will be securely transmitted to Qure.ai software 'qXR' for interpretation. Images with features of cancer will be flagged as 'Urgent Suspicion of Cancer' and be prioritised for radiologist review within the existing reporting workflow. ETHICS AND DISSEMINATION: The study will follow the principles of Good Clinical Practice. The protocol was granted REC approval in August 2023 from North West-Greater Manchester West Research Ethics Committee (REC 23/NW/0211). This study was registered on clinicaltrials.gov (NCT06044454). An interim report will be produced for use by the Scottish Government. The results from this study will be presented at artificial intelligence, radiology and respiratory meetings and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT06044454.

Concurrent validity of an online version of the Timeline Followback assessment.

The Timeline Followback (TLFB) interview has been used extensively in the assessment of alcohol and other substance use. While this methodology has been validated in multiple formats for multiple behaviors, to date no systematic comparisons have been conducted between the traditional interview format and online versions. The present research employed a randomized within-subjects design to compare interview versus online-based TLFB assessments of alcohol and marijuana use among 102 college students. Participants were randomly assigned to receive either the online version first or the in-person interview format first. Participants subsequently completed the second format within 3 days. While we expected few overall differences between formats, we hypothesized that differences might emerge to the extent that participants are more comfortable and willing to answer honestly in an online format, which provides a degree of anonymity. Results were consistent with expectations in suggesting relatively few differences between the online version and the in-person version. Participants did report feeling more comfortable in completing the online version. Moreover, greater discomfort during the in-person assessment was associated with reporting more past-month marijuana use on the online assessment, but reported discomfort did not moderate differences between formats in reported alcohol consumption.