Laffon E, Calcagni M L, Galli G, Giordano A, Capotosti A, Marthan R, Indovina L
Departments of Nuclear Medicine & Lung Function Testing, CHU de Bordeaux, Bordeaux, France.
Centre de Recherche Cardio-Thoracique, INSERM U-1045, Univ. Bordeaux, Bordeaux, France.
EJNMMI Res. 2018 Mar 27;8(1):24. doi: 10.1186/s13550-018-0369-5.
Patlak's graphical analysis can provide tracer net influx constant (Ki) with limitation of assuming irreversible tracer trapping, that is, release rate constant (k) set to zero. We compared linear Patlak's analysis to non-linear three-compartment three-parameter kinetic model analysis (3P-KMA) providing Ki, k, and fraction of free F-FDG in blood and interstitial volume (V).
Dynamic PET data of 21 lung cancer patients were retrospectively analyzed, yielding for each patient an F-FDG input function (IF) and a tissue time-activity curve. The former was fitted with a three-exponentially decreasing function, and the latter was fitted with an analytical formula involving the fitted IF data (11 data points, ranging 7.5-57.5 min post-injection). Bland-Altman analysis was used for Ki comparison between Patlak's analysis and 3P-KMA. Additionally, a three-compartment five-parameter KMA (5P-KMA) was implemented for comparison with Patlak's analysis and 3P-KMA.
We found that 3P-KMA Ki was significantly greater than Patlak's Ki over the whole patient series, + 6.0% on average, with limits of agreement of ± 17.1% (95% confidence). Excluding 8 out of 21 patients with k > 0 deleted this difference. A strong correlation was found between Ki ratio (=3P-KMA/Patlak) and k (R = 0.801; P < 0.001). No significant difference in Ki was found between 3P-KMA versus 5P-KMA, and between 5P-KMA versus Patlak's analysis, with limits of agreement of ± 23.0 and ± 31.7% (95% confidence), respectively.
Comparison between 3P-KMA and Patlak's analysis significantly showed that the latter underestimates Ki because it arbitrarily set k to zero: the greater the k value, the greater the Ki underestimation. This underestimation was not revealed when comparing 5P-KMA and Patlak's analysis. We suggest that further studies are warranted to investigate the 3P-KMA efficiency in various tissues showing greater F-FDG trapping reversibility than lung cancer lesions.
Patlak图形分析可提供示踪剂净流入常数(Ki),但存在假设示踪剂不可逆滞留的局限性,即释放速率常数(k)设为零。我们将线性Patlak分析与提供Ki、k以及血液和组织间液中游离F-FDG分数(V)的非线性三室三参数动力学模型分析(3P-KMA)进行了比较。
对21例肺癌患者的动态PET数据进行回顾性分析,为每位患者生成一个F-FDG输入函数(IF)和一条组织时间-活性曲线。前者用三指数递减函数拟合,后者用包含拟合IF数据的解析公式拟合(11个数据点,注射后7.5 - 57.5分钟)。采用Bland-Altman分析对Patlak分析和3P-KMA之间的Ki进行比较。此外,实施三室五参数KMA(5P-KMA)以与Patlak分析和3P-KMA进行比较。
我们发现,在整个患者系列中,3P-KMA的Ki显著大于Patlak的Ki,平均大6.0%,一致性界限为±17.1%(95%置信区间)。排除21例中k > 0的8例患者后,这种差异消失。发现Ki比值(=3P-KMA/Patlak)与k之间存在强相关性(R = 0.801;P < 0.001)。3P-KMA与5P-KMA之间以及5P-KMA与Patlak分析之间的Ki无显著差异,一致性界限分别为±23.0%和±31.7%(95%置信区间)。
3P-KMA与Patlak分析的比较显著表明,后者低估了Ki,因为它将k任意设为零:k值越大,Ki低估越严重。比较5P-KMA与Patlak分析时未发现这种低估情况。我们建议有必要进一步研究3P-KMA在各种比肺癌病变显示出更大F-FDG滞留可逆性的组织中的效率。