Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Centre Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Department of Cardiology - Electrophysiology, University Heart Centre, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
J Nucl Cardiol. 2018 Feb;25(1):208-216. doi: 10.1007/s12350-016-0708-8. Epub 2016 Nov 1.
Iodine-123-metaiodobenzylguanidine (I-MIBG) imaging with estimation of the heart-to-mediastinum ratio (HMR) has been established for risk assessment in patients with chronic heart failure. Our aim was to evaluate the effect of different methods of ROI definition on the renderability of HMR to normal or decreased sympathetic innervation.
The results of three different methods of ROI definition (clinical routine (CLI), simple standardization (STA), and semi-automated (AUT) were compared. Ranges of 95% limits of agreement (LoA) of inter-observer variabilities were 0.28 and 0.13 for STA and AUT, respectively. Considering a HMR of 1.60 as the lower limit of normal, 13 of 32 (41%) for method STA and 5 of 32 (16%) for method AUT of all HMR measurements could not be classified to normal or pathologic. Ranges of 95% LoA of inter-method variabilities were 0.72 for CLI vs AUT, 0.65 for CLI vs STA, and 0.31 for STA vs AUT.
Different methods of ROI definition result in different ranges of the LoA of the measured HMR with relevance for rendering the results to normal or pathological innervation. We could demonstrate that standardized protocols can help keep methodological variabilities limited, narrowing the gray zone of renderability.
碘-123-间碘苄胍(I-MIBG)成像并估计心脏与纵隔的比值(HMR)已被确立用于慢性心力衰竭患者的风险评估。我们的目的是评估不同 ROI 定义方法对正常或降低的交感神经支配的 HMR 可再现性的影响。
比较了三种不同 ROI 定义方法(临床常规(CLI)、简单标准化(STA)和半自动(AUT))的结果。观察者间变异性的 95%置信区间(LoA)范围分别为 STA 和 AUT 的 0.28 和 0.13。考虑 HMR 为 1.60 作为正常下限,所有 HMR 测量中,STA 方法的 13 个(41%)和 AUT 方法的 5 个(16%)无法分类为正常或病理。CLI 与 AUT、CLI 与 STA 和 STA 与 AUT 之间的 95%LoA 范围分别为 0.72、0.65 和 0.31。
不同的 ROI 定义方法导致测量的 HMR 的 LoA 范围不同,这对于呈现正常或病理神经支配的结果具有重要意义。我们可以证明,标准化方案可以帮助将方法学变异性保持在有限范围内,缩小可再现性的灰色区域。