Advancing Lung Cancer Screening: Artificial Intelligence, Multimodal Imaging and Cutting-Edge Technologies for Early Detection and Characterization

Trial Title: Advancing Lung Cancer Screening: Artificial Intelligence, Multimodal Imaging and Cutting-Edge Technologies for Early Detection and Characterization

NCT ID: NCT06531343

Condition: Lung Cancer Screening

Conditions: Official terms:
Lung Neoplasms

Study type: Interventional

Study phase: N/A

Overall status: Not yet recruiting

Study design:

Allocation: Non-Randomized

Intervention model: Parallel Assignment

Primary purpose: Screening

Masking: Single (Participant)

Intervention:

Intervention type: Procedure
Intervention name: LDCT scan and simultaneous [18F]FDG PET/CT on new-generation long axial field of view scanner
Description: 18F]FDG will be injected intravenously, and PET/CT images will be acquired after 60 minutes (± 10 minutes). PET/CT images will be first analysed with the lung window to detect any findings suggestive of a lung tumour. Whole-body PET/CT images will be then analysed to detect any incidental finding in the chest as well as other anatomical areas included in the field of view. PET/CT images will be considered positive if there is at least one non-calcified lung nodule or any suspicious finding on CT scan characterised by focal [18F]FDG uptake deviating from physiological distribution or above physiological background activity.
Arm group label: LDCT scan and simultaneous [18F]FDG PET/CT on new-generation long axial field of view scanner

Intervention type: Procedure
Intervention name: LDTC only
Description: The LDCT scan will be performed in single deep inspiratory breath hold. No intravenous contrast will be administered.
Arm group label: low LDCT only

Summary: Currently available screening programmes for lung cancer are limited by many challenges including low diagnostic accuracy, radiation exposure and high costs. New technologies in PET/CT scanners can allow cheaper and more sensitive exams with low radiation exposure. AI can be used to denoise LDCT to enhance the accuracy of imaging tests and build riskassessment models. This project aims to develop a new approach exploiting both these revolutionary advancements to bridge the existing gap in lung cancer screening. Patients in a high-risk population will be enrolled into two different cohorts undergoing LDCT scan and simultaneous [18F]FDG PET/CT on new-generation long axial field of view scanner (UO1) or screening with low LDCT only (UO2). AI will assist in image enhancement and interpretation and will develop a personalised risk-model guiding the following steps of clinical management, significantly improving early diagnosis of lung cancer, reducing mortality and healthcare costs.

Detailed description: Assessment of the potential added value of low dose [18F]FDG PET/CT in the early detection of lung cancer in the screening work-up of the high-risk population. The target population (cohort 1) for the multimodal screening programme will be identified at UO1 on the basis of the PLCOM2012 prediction risk model. All patients enrolled in cohort 1 will undergo a LDCT and a simultaneous low dose [18F]FDG PET scan. Whole body [18F]FDG PET/CT will be performed according to EANM Guidelines for tumour imaging. Briefly, patients will be instructed to fast for 6 hours and to avoid strenuous physical activity for 48 hours prior to the PET/CT scan. Diabetic patients will be instructed to fast for 4 hours prior to the scan and will be instructed on the use of medications according to the institution's protocol. Blood glucose levels will be checked, [18F]FDG will be injected intravenously, and PET/CT images will be acquired after 60 minutes (± 10 minutes). A new generation long axial field of view PET/CT scanner (Omni Legend, General Electric Healthcare, Waukesha, WI, USA) will be used for whole body imaging. The control population (cohort 2) will be identified in UO2 on the basis of the PLCOM2012 prediction risk model as previously described for cohort 1. The LDCT scan will be performed in single deep inspiratory breath hold. No intravenous contrast will be administered. LDCT images will be assessed and interpreted by at least two experienced radiologists. LDCT will be defined as positive if at least one non-calcified lung nodule >5 mm in any diameter is detected. LDCT will be defined as negative if no clinically significant morphological alterations are detected. Non-calcified nodules of 3-5mm detected by LDCT will be reported. Lung-RADS criteria will be used to classify detected lung nodules. Any other suspicious morphological alteration will be reported. The number, size, characteristics, and location of any lesion detected will be recorded for each LDCT scan. Any abnormality suggestive of clinically significant conditions other than cancer will be also reported. Sensitivity, specificity, and accuracy will be calculated by per-patient and per-lesion analysis.

Criteria for eligibility:
Criteria:
Inclusion Criteria: - Age > 50 years - PLCOm2012 risk prediction > 4% - Be willing to adhere to the study intervention through [18F]FDG PET/CT or LDCT imaging - Signed written informed consent form Exclusion Criteria: - Blood glucose levels >200 mg/dl, - Ongoing pregnancy and breastfeeding - Unwillingness to participate, - Previous diagnosis of lung cancer, - Previous CT scan within the last 24 months - Concomitant severe clinical conditions and any condition that preclude the feasibility of the study

Gender: All

Minimum age: 50 Years

Maximum age: N/A

Healthy volunteers: No

Locations:

Facility:
Name: Irccs San Raffaele

Address:
City: Milano
Country: Italy

Contact:
Last name: Arturo Chiti

Phone: 0226432716
Email: chiti.arturo@hsr.it

Contact backup:
Last name: Rachele Di Donato

Phone: 0226433639
Email: didonato.rachele@hsr.it

Start date: October 30, 2024

Completion date: August 30, 2026

Lead sponsor:
Agency: IRCCS San Raffaele
Agency class: Other

Collaborator:
Agency: Fondazione Policlinico Universitario Campus Bio-Medico
Agency class: Other

Collaborator:
Agency: University of Calabria
Agency class: Other

Collaborator:
Agency: University of Salerno
Agency class: Other

Source: IRCCS San Raffaele

Record processing date: ClinicalTrials.gov processed this data on November 12, 2024

Source: ClinicalTrials.gov page: https://clinicaltrials.gov/ct2/show/NCT06531343