Borghesi Andrea, Michelini Silvia, Bertagna Francesco, Scrimieri Alessandra, Pezzotti Stefania, Maroldi Roberto
Department of Radiology, University and Spedali Civili of Brescia, Brescia, Italy.
Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy.
Eur J Radiol Open. 2018 Oct 2;5:177-182. doi: 10.1016/j.ejro.2018.09.004. eCollection 2018.
Persistent pure ground-glass nodules (pGGNs) typically show an indolent course with very slow growth rates. These slow-growing lesions exhibit different growth patterns regardless of their initial computed tomography (CT) features. Therefore, predicting the aggressive behavior of pGGNs on initial CT remains a diagnostic challenge. The literature reports that computerized analysis and various quantitative features have been tested to improve the risk stratification for pGGNs. The present article describes the long-term follow-up of two pGGNs with different behavior and introduces, for the first time, a new computerized method of analysis that could be helpful for predicting the future behavior of pGGNs.
持续性纯磨玻璃结节(pGGN)通常病程进展缓慢,生长速度极慢。这些生长缓慢的病变无论其初始计算机断层扫描(CT)特征如何,都表现出不同的生长模式。因此,在初始CT上预测pGGN的侵袭性行为仍然是一项诊断挑战。文献报道,已经对计算机分析和各种定量特征进行了测试,以改善pGGN的风险分层。本文描述了两个具有不同行为的pGGN的长期随访情况,并首次介绍了一种新的计算机分析方法,该方法可能有助于预测pGGN的未来行为。