What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom.

What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom.
复制标题

DOI:
10.1016/j.ijrobp.2010.12.055
复制
发表时间:
2012-03-01
影响因子:
7
通讯作者:
Nelson, Aaron S.
Nelson, Aaron S.
中科院分区:
医学1区
文献类型:
--
作者:
Werner-Wasik, Maria;Nelson, Arden D.;Choi, Walter;Arai, Yoshio;Faulhaber, Peter F.;Kang, Patrick;Almeida, Fabio D.;Xiao, Ying;Ohri, Nitin;Brockway, Kristin D.;Piper, Jonathan W.;Nelson, Aaron S.

文献摘要

参考文献

被引文献

相似文献

与手动 (MANUAL) 和恒定阈值 (THRESHOLD) 方法相比,评估基于梯度的 PET 分割方法 GRADIENT 的准确性和一致性。使用球形体模和临床真实的胸部蒙特卡洛 PET 体模评估轮廓准确性。球体模型直径为 10-37 毫米,是在 5 个模拟临床条件的机构获得的。一家机构还获得了一个球体模型,其多种源背景比 (SBR) 为 2:1、5:1、10:1、20:1 和 70:1。一名观察者使用梯度和阈值从 25% 到 50% 以 5% 的增量对每个球体进行分割(绘制轮廓)。随后,七名医生使用梯度、阈值和手动从 25 个数字胸部模型中分割病灶 (7-264ml)。对于直径 < 20 mm 的球体,GRADIENT 是最准确的,直径的平均绝对误差百分比为 8.15% (10.2%SD),而 45% THRESHOLD 的平均绝对误差百分比为 49.2% (51.1%SD) (p < 0.005)。对于较大的球体,这些方法在统计上是等效的。对于不同的 SBR,GRADIENT 对于 > 20 mm (p < 0.065) 和 < 20 mm (p < 0.015) 的球体最准确。对于数字胸部模型,梯度是最准确的(p 值 < 0.01),体积的平均绝对误差百分比为 10.99% (11.9%SD),其次是 25% 阈值,为 17.5% (29.4%SD),而手动为 19.5% (17.2%SD)。梯度的系统偏差最小,4 的平均体积误差百分比为 -0.05% (16.2%SD),而 25% 阈值为 - 2.1% (34.2%SD),手动为 -16.3% (20.2%SD)(p 值 < 0.01)。与 25% 阈值和手动相比,使用 GRADIENT 减少了观察者间的变异性(p 值 < 0.01,Levene 检验)。 GRADIENT 是最准确且一致的目标体积轮廓技术。对于不同的成像条件,GRADIENT 也是最稳健的。 GRADIENT 有潜力在放射治疗计划和反应评估中的肿瘤描绘中发挥重要作用。
To evaluate the accuracy and consistency of a gradient-based PET segmentation method, GRADIENT, as compared to manual (MANUAL) and constant threshold (THRESHOLD) methods. Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10–37 mm in diameter and were acquired at 5 institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios (SBR) of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25–50% at 5% increments. Subsequently, seven physicians segmented lessions (7–264ml) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL. For spheres < 20 mm in diameter, GRADIENT was the most accurate with a mean absolute %error in diameter of 8.15% (10.2%SD) compared to 49.2% (51.1%SD) for 45% THRESHOLD (p < 0.005). For larger spheres the methods were statistically equivalent. For varying SBR, GRADIENT was the most accurate for spheres > 20 mm, (p < 0.065) and < 20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate, (p-value < 0.01), with a mean absolute %error in volume of 10.99% (11.9%SD) followed by 25% THRESHOLD at 17.5% (29.4%SD), and MANUAL, at 19.5% (17.2%SD). GRADIENT had the least systematic bias, 4 with a mean %error in volume of −0.05% (16.2%SD) compared with 25% THRESHOLD at - 2.1% (34.2%SD) and MANUAL at −16.3% (20.2%SD) (p-value < 0.01). Inter-observer variability was reduced using GRADIENT compared to both 25% THRESHOLD and MANUAL (p-value < 0.01, Levene's Test). GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in radiation therapy planning and response assessment.
DOI: 10.1016/j.ijrobp.2004.06.254
发表时间: 2004-11-15
影响因子: 7
作者:
Black, QC;Grills, IS;Yan, D
通讯作者: Yan, D
DOI: 10.1016/s0360-3016(01)01722-9
发表时间: 2001-11-15
影响因子: 7
作者:
Caldwell, CB;Mah, K;Ehrlich, LE
通讯作者: Ehrlich, LE
DOI: 10.2967/jnumed.108.055780
发表时间: 2009-10
期刊: Journal of nuclear medicine : official publication, Society of Nuclear Medicine
影响因子: --
作者:
Ford EC;Herman J;Yorke E;Wahl RL
通讯作者: Wahl RL
DOI: 10.1118/1.597290
发表时间: 1994-02-01
期刊: MEDICAL PHYSICS
影响因子: 3.8
作者:
ZUBAL, IG;HARRELL, CR;HOFFER, PB
通讯作者: HOFFER, PB
DOI: 10.1118/1.2938518
发表时间: 2008-07-01
期刊: MEDICAL PHYSICS
影响因子: 3.8
作者:
Aristophanous, Michalis;Penney, Bill C.;Pelizzari, Charles A.
通讯作者: Pelizzari, Charles A.