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Master Thesis

Détection et caractérisation des nodules pulmonaires : comparaison entre scanners ultra-basse dose et scanner basse dose utilisant la 3e génération de reconstruction itérative ASIR-V

Abstract : Purpose: The aim of this study is to assess the performances of ultra-low-dose (ULD) unenhanced chest computed tomography (CT) using third generation ASIR-V iterative reconstruction as compared to low-dose (LD) CT, for detection and characterisation of lung nodule ≥ 4mm in clinical conditions. Methods: This prospective study enrolled 150 patients who underwent two consecutive unenhanced CT scans including LD CT and ULD CT protocols with image reconstruction using AsirV 50% for both acquisitions and AsirV 100% for ULD CT. Blind reading was performed by two pair of radiologists. Nodules of longer diameter ≥ 4mm were identified and characterised. Sensitivity (Se), positive predicted value (PPV) were calculated with a confidence interval (CI) of 95%. The concordance and the inter-observer reproducibility were assessed using the Cohen Kappa coefficient (κ) with a 95% confidence interval. Results: 134 patients were finally included, with 200 nodules detected in LD scans. For ULD50 and ULD100, sensitivity were 76.5% (70%-82%) and 77% (71-83%), PPV were 73.9% [67%;80%] and 67.8% [61% ;74%], concordance was almost perfect for nodule’s size with κ=0.97 (CI : 0.96-0.98) and κ=0.95 (CI : 0.94-0.97), inter-observer reproducibility was almost perfect for nodule’s size with κ=0.98 (CI : 0.98-0.99) and κ=0.98 (CI : 0.98-0.99). Conclusion: According to our study, ULD CT scan using third generation iterative reconstruction showed insufficient sensitivity for detecting lung nodules in clinical practice.
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Master Thesis
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Submitted on : Wednesday, March 31, 2021 - 5:35:23 PM
Last modification on : Saturday, April 3, 2021 - 3:17:31 AM
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  • HAL Id : dumas-03187188, version 1

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Anthony Colé. Détection et caractérisation des nodules pulmonaires : comparaison entre scanners ultra-basse dose et scanner basse dose utilisant la 3e génération de reconstruction itérative ASIR-V. Médecine humaine et pathologie. 2020. ⟨dumas-03187188⟩

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