Department of Nuclear Medicine, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris APHP, Clichy, France.
J Nucl Med. 2013 Feb;54(2):236-43. doi: 10.2967/jnumed.112.105825. Epub 2012 Dec 18.
Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method.
This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression.
The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced.
This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.
评价使用剂量核卷积(DK)方法时组织密度异质性(TDH)对剂量计算的影响,并提出一种简单的密度校正方法。
本研究共纳入 3 个临床病例:病例 1,采用(131)I-替妥莫单抗治疗非霍奇金淋巴瘤;病例 2,采用(177)Lu-肽模拟神经内分泌肿瘤治疗;病例 3,采用(90)Y 微球治疗肝细胞癌。采用直接蒙特卡罗方法(3D-RD)考虑 TDH 进行吸收剂量计算,并采用 DK 方法(VoxelDose,VD)进行计算。对于每个体素,假设均匀密度计算的 VD 吸收剂量 D(VD),根据密度进行校正,得到 D(VDd)。比较个体素水平上的 3D-RD 吸收剂量值 D(3DRD)与 D(VD)和 D(VDd),使用相对差异 Δ(VD/3DRD)。在体素水平上,对密度分类的 Δ(VD/3DRD)和 Δ(VDd/3DRD)与 ρ 进行绘图,并采用线性回归拟合。
VD 计算与 D(3DRD)吻合良好。除病例 1 的肿瘤(5.9%)和病例 2 的肾皮质(5.6%)外,Δ(VD/3DRD)均小于 3.5%。在体素水平上,病例 1 和 2 的 Δ(VD/3DRD)范围为 0%-14%,病例 3 为-3%至 7%。所有 3 个病例均显示体素平均 Δ(VD/3DRD)与密度 ρ 之间存在线性关系:病例 1(Δ=-0.56ρ+0.62,R2=0.93),病例 2(Δ=-0.91ρ+0.96,R2=0.99)和病例 3(Δ=-0.69ρ+0.72,R2=0.91)。DK 方法的密度校正改善了与蒙特卡罗方法的一致性(Δ(VDd/3DRD)<1.1%),但对病例 1 的肿瘤影响较小(3.1%)。在体素水平上,3 个临床病例的 Δ(VDd/3DRD)范围均减小(病例 1:-1%至 4%;病例 2:-0.5%至 1.5%,-1.5%至 2%)。病例 2 和 3 不再存在线性回归,而病例 1 则存在(Δ=0.41ρ-0.38,R2=0.88),尽管病例 1 的斜率不那么明显。
本研究显示腹部区域 TDH 对 3 个有代表性的临床病例的影响较小。提出了一种简单的密度校正方法,并在使用我们的体素 S 值实现方法进行吸收剂量计算时改善了比较。