Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, and Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
Centre for Imaging Science, School of Health Sciences, Faculty of Biology, Medicine and Health, and Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
Pancreatology. 2018 Jun;18(4):429-437. doi: 10.1016/j.pan.2018.04.001. Epub 2018 Apr 3.
Excess body adiposity is associated with increased risk of pancreatic cancer, and in animal models excess intra-pancreatic fat is a driver of pancreatic carcinogenesis. Within a programme to evaluate pancreatic fat and PC risk in humans, we assessed whether MR-quantified pancreatic fat fraction (PFF) was 'fit for purpose' as an imaging biomarker.
We determined PFF using MR spectroscopy (MRS) and MR chemical shift imaging (CS-MR), in two groups. In Group I, we determined accuracy of MR-derived PFF with histological digital fat quantification in 12 patients undergoing pancreatic resection. In a second study, we assessed reproducibility in 15 volunteers (Group IIa), and extended to 43 volunteers (Group IIa & IIb) to relate PFF with MR-derived hepatic fat fraction (HFF), body mass index (BMI), and waist circumference (WC) using linear regression models. We assessed intra- and inter-observer, and between imaging modality levels of agreement using Bland-Altman plots.
In Group I patients, we found strong levels of agreement between MRS and CS-MR derived PFF and digitally quantified fat on histology (rho: 0.781 and 0.672 respectively). In Group IIa, there was poor reproducibility in initial assessments. We refined our protocols to account for 3D dimensionality of the pancreas, and found substantially improved intra-observer agreements. In Group II, HFF and WC were significantly correlated with PFF (p values < 0.05).
Both CS-MR and MRS (after accounting for pancreatic 3D dimensionality) were 'fit for purpose' to determine PFF and might add information on cancer prediction independent from measures of general body adiposity.
体脂肪过多与胰腺癌风险增加有关，在动物模型中，胰腺内脂肪过多是胰腺癌发生的驱动因素。在评估人类胰腺脂肪和 PC 风险的计划中，我们评估了磁共振定量胰腺脂肪分数（PFF）是否适合作为成像生物标志物。
我们使用磁共振波谱（MRS）和磁共振化学位移成像（CS-MR）在两组中确定 PFF。在第 I 组中，我们在 12 名接受胰腺切除术的患者中确定了 MR 衍生的 PFF 的准确性与组织学数字脂肪定量。在第二项研究中，我们在 15 名志愿者（第 IIa 组）中评估了可重复性，并扩展到 43 名志愿者（第 IIa 和 IIb 组），使用线性回归模型将 PFF 与 MR 衍生的肝脂肪分数（HFF）、体重指数（BMI）和腰围（WC）相关联。我们使用 Bland-Altman 图评估了观察者内、观察者间和不同成像方式之间的一致性水平。
在第 I 组患者中，我们发现 MRS 和 CS-MR 衍生的 PFF 与组织学上数字化定量脂肪之间具有很强的一致性（rho 值分别为 0.781 和 0.672）。在第 IIa 组中，初步评估的可重复性较差。我们改进了方案以考虑到胰腺的 3D 维度，发现观察者内的一致性有了显著提高。在第 II 组中，HFF 和 WC 与 PFF 显著相关（p 值均<0.05）。
CS-MR 和 MRS（在考虑到胰腺 3D 维度后）都“适合”确定 PFF，并且可能会提供与一般身体肥胖程度无关的癌症预测信息。
