PLUS: Plug-and-Play Enhanced Liver Lesion Diagnosis Model on Non-Contrast CT Scans

TL;DR

This paper introduces PLUS, a versatile framework that significantly improves liver lesion diagnosis on non-contrast CT scans, aiding early detection of malignancies with enhanced accuracy across existing segmentation models.

Contribution

The study presents a novel plug-and-play approach that enhances 3D liver lesion analysis on NCCT, addressing limitations of current methods and improving diagnostic performance.

Findings

Improved lesion-level F1 score by 5.66%

Enhanced malignant patient-level F1 score by 6.26%

Boosted benign patient-level F1 score by 4.03%

Abstract

Focal liver lesions (FLL) are common clinical findings during physical examination. Early diagnosis and intervention of liver malignancies are crucial to improving patient survival. Although the current 3D segmentation paradigm can accurately detect lesions, it faces limitations in distinguishing between malignant and benign liver lesions, primarily due to its inability to differentiate subtle variations between different lesions. Furthermore, existing methods predominantly rely on specialized imaging modalities such as multi-phase contrast-enhanced CT and magnetic resonance imaging, whereas non-contrast CT (NCCT) is more prevalent in routine abdominal imaging. To address these limitations, we propose PLUS, a plug-and-play framework that enhances FLL analysis on NCCT images for arbitrary 3D segmentation models. In extensive experiments involving 8,651 patients, PLUS demonstrated a significant improvement with existing methods, improving the lesion-level F1 score by 5.66%, the malignant patient-level F1 score by 6.26%, and the benign patient-level F1 score by 4.03%. Our results demonstrate the potential of PLUS to improve malignant FLL screening using widely available NCCT imaging substantially.