用于磨玻璃结节鉴别诊断的三维亚结构测量。
Three-dimensional substructure measurements for the differential diagnosis of ground glass nodules.
机构信息
Shanghai Key Laboratory of Orthopaedic Implant, Department of Orthopaedic Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School Of Medicine, Room 703, No. 3 Building, 693 Zhizaoju Road, Shanghai, 200011, China.
Department of Anesthesiology, Binzhou Central Hospital, Binzhou Medical College, Binzhou, China.
出版信息
BMC Pulm Med. 2017 Jun 19;17(1):93. doi: 10.1186/s12890-017-0438-y.
BACKGROUND
We analyzed the differences between maximum and peak computed tomography (CT) numbers (M-P), respectively representing the densities of the solid center and the main periphery of ground-glass nodules (GGNs), and the average change in M-P velocity (V(M-P)) during follow-up to differentiate between pre-invasive (PIA) and invasive adenocarcinoma (IAC).
METHODS
Data of 102 patients were retrospectively collected and analyzed in our study including 43 PIAs and 59 IACs. Diameters, total volumes, and the maximum and peak CT numbers in CT number histograms were measured and followed for at least 3 months. This study was registered retrospectively.
RESULTS
The M-P values for IACs were higher than those for PIAs (p = 0.001), with an area under the curve (AUC) of 0.810 and a threshold of 489.5 Hounsfield units (HU) in ROC analysis. The V(M-P) values for IACs were smaller than those for PIAs (p = 0.04), with an AUC of 0.805 and a threshold of 11.01 HU/day.
CONCLUSIONS
M-P and V(M-P) values may help distinguish IACs from PIAs by representing the changes in the sub-structural densities of GGNs during follow-up.
背景
我们分析了最大和峰值计算机断层扫描（CT）数（M-P）之间的差异，分别代表磨玻璃结节（GGN）的实性中心和主要周边的密度，以及随访过程中 M-P 速度（V（M-P））的平均变化，以区分非浸润性腺癌（PIA）和浸润性腺癌（IAC）。
方法
本研究回顾性收集了 102 名患者的数据，包括 43 名 PIA 和 59 名 IAC。在 CT 数直方图中测量并随访了直径、总体积以及最大和峰值 CT 数，至少随访 3 个月。本研究是回顾性注册的。
结果
IAC 的 M-P 值高于 PIA（p=0.001），ROC 分析的曲线下面积（AUC）为 0.810，阈值为 489.5 亨氏单位（HU）。IAC 的 V（M-P）值小于 PIA（p=0.04），AUC 为 0.805，阈值为 11.01 HU/天。
结论
M-P 和 V（M-P）值可以通过代表 GGN 亚结构密度在随访期间的变化，帮助区分 IAC 和 PIA。
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