Reconstruction Interval Z-Phase Dependence of AI Detection Sensitivity in CT Lung Nodule Screening
Dan Soliman

TL;DR
This study investigates how the detection sensitivity of AI in CT lung nodule screening varies with the nodule's position within the reconstruction cycle, revealing a significant dependence on the ratio of reconstruction interval to nodule diameter.
Contribution
It characterizes the previously unstudied dependence of AI detection sensitivity on z-phase and the ratio of reconstruction interval to nodule size in CT scans.
Findings
Detection sensitivity decreases with larger reconstruction intervals.
Sensitivity varies significantly across z-phase bins, especially when the ratio exceeds 1.0.
Z-phase is a major source of detection variance for certain nodule sizes.
Abstract
Background: Sensitivity of AI-assisted lung nodule detection systems is known to vary with CT acquisition parameters including radiation dose, reconstruction kernel, and slice thickness. However, the dependence of detection probability on nodule position within the reconstruction cycle -- the z-phase -- has not, to the author's knowledge, been characterized for deep learning-based detection systems. Methods: A retrospective analysis was performed using the LIDC-IDRI dataset. Detection results from a previously validated 154-case perturbation study were re-analyzed. For each consensus nodule (>=4-reader agreement), z-phase was defined as the fractional position of the nodule center within the reconstruction cycle, folded to [0, 0.5]. Detection sensitivity was stratified by z-phase bin, reconstruction interval (1mm, 3mm, 5mm), and by the ratio of reconstruction interval to nodule diameter…
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