18F-FDG PET-CT的新型惩罚似然重建能否改善结直肠癌肝转移灶的信号背景比？

Does a novel penalized likelihood reconstruction of 18F-FDG PET-CT improve signal-to-background in colorectal liver metastases?

作者信息

Parvizi Nassim, Franklin James M, McGowan Daniel R, Teoh Eugene J, Bradley Kevin M, Gleeson Fergus V

机构信息

Department of Clinical Radiology, Oxford University Hospitals NHS Trust, Churchill Hospital, Old Road, Headington, Oxford, Oxfordshire OX3 7LE, UK.

Department of Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Headington, Oxford, Oxfordshire OX3 7DQ,UK; Radiation Physics and Protection, Oxford University Hospitals NHS Trust, Churchill Hospital, Old Road, Headington, Oxford, Oxfordshire OX3 7LE, UK.

出版信息

Eur J Radiol. 2015 Oct;84(10):1873-8. doi: 10.1016/j.ejrad.2015.06.025. Epub 2015 Jun 29.

DOI:10.1016/j.ejrad.2015.06.025

PMID:26163992

Abstract

PURPOSE

Iterative reconstruction algorithms are widely used to reconstruct positron emission tomography computerised tomography (PET/CT) data. Lesion detection in the liver by 18F-fluorodeoxyglucose PET/CT (18F-FDG-PET/CT) is hindered by 18F-FDG uptake in background liver parenchyma. The aim of this study was to compare semi-quantitative parameters of histologically-proven colorectal liver metastases detected by 18F-FDG-PET/CT using data based on a Bayesian penalised likelihood (BPL) reconstruction, with data based on a conventional time-of-flight (ToF) ordered subsets expectation maximisation (OSEM) reconstruction.

METHODS

A BPL reconstruction algorithm was used to retrospectively reconstruct sinogram PET data. This data was compared with OSEM reconstructions. A volume of interest was placed within normal background liver parenchyma. Lesions were segmented using automated thresholding. Lesion maximum standardised uptake value (SUVmax), standard deviation of background liver parenchyma SUV, signal-to-background ratio (SBR), and signal-to-noise ratio (SNR) were collated. Data was analysed using paired Student's t-tests and the Pearson correlation.

RESULTS

Forty-two liver metastases from twenty-four patients were included in the analysis. The average lesion SUVmax increased from 8.8 to 11.6 (p<0.001) after application of the BPL algorithm, with no significant difference in background noise. SBR increased from 4.0 to 4.9 (p<0.001) and SNR increased from 10.6 to 13.1 (p<0.001) using BPL. There was a statistically significant negative correlation between lesion size and the percentage increase in lesion SUVmax (p=0.03).

CONCLUSIONS

This BPL reconstruction algorithm improved SNR and SBR for colorectal liver metastases detected by 18F-FDG-PET/CT, increasing the lesion SUVmax without increasing background liver SUV or image noise. This may improve the detection of FDG-avid focal liver lesions and the diagnostic performance of clinical 18F-FDG-PET/CT in this setting, with the largest impact for small foci.

摘要

目的

迭代重建算法广泛应用于正电子发射断层扫描计算机断层扫描（PET/CT）数据的重建。肝脏实质内的18F-氟脱氧葡萄糖摄取会干扰18F-氟脱氧葡萄糖PET/CT（18F-FDG-PET/CT）对肝脏病变的检测。本研究的目的是比较基于贝叶斯惩罚似然（BPL）重建的数据与基于传统飞行时间（ToF）有序子集期望最大化（OSEM）重建的数据，以评估18F-FDG-PET/CT检测到的经组织学证实的结直肠癌肝转移的半定量参数。

方法

使用BPL重建算法对PET数据的正弦图进行回顾性重建。将此数据与OSEM重建数据进行比较。在正常肝脏实质背景内放置感兴趣区。使用自动阈值分割病变。整理病变最大标准化摄取值（SUVmax）、肝脏实质背景SUV的标准差、信号与背景比值（SBR）以及信噪比（SNR）。使用配对学生t检验和Pearson相关性分析数据。

结果

分析纳入了24例患者的42个肝转移灶。应用BPL算法后，病变平均SUVmax从8.8增加到11.6（p<0.001），背景噪声无显著差异。使用BPL时，SBR从4.0增加到4.9（p<0.001），SNR从10.6增加到13.1（p<0.001）。病变大小与病变SUVmax的增加百分比之间存在统计学显著的负相关性（p=0.03）。