Relationships of body habitus and SUV indices with signal-to-noise ratio of hepatic (18)F-FDG PET

Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor

INTRODUCTION

Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics.

METHODS

PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans.

RESULTS

Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15-18% and 9-18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images.

CONCLUSION

SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies.

TRIAL REGISTRATION

EudraCT: 2006-005,174-42, 01-08-2008.

Correlation between 18F-FDG dosage and SNR on various BMI patient groups tested in NEMA IEC PET phantom

The present study was conducted to determine quantitatively the correlation between injected radiotracer and signal-to-noise ratio (SNR) based on differences in physiques and stages of cancer. Eight different activities were evaluated with modelled National Electrical Manufacturers Association (NEMA) of the International Electrotechnical Commission (IEC) PET's phantom with nine different tumour-to-background ratio (TBR). The findings suggest that the optimal value of dosage is required for all categories of patients in the early stages of cancer diagnosis.

The appropriate whole body metric for calculating standardised uptake value and the influence of sex

Aim

To compare weight, lean body mass and body surface area for calculation of standardised uptake value (SUV) in fluorine-18-fluorodeoxyglucose PET/computed tomography, taking sex into account.

Patients and methods

This was a retrospective study of 161 (97 men) patients. Maximum standardised uptake value (SUV_max) and mean standardised uptake value (SUV_mean) were obtained from a 3-cm region of interest over the right lobe of the liver and scaled to weight, scaled to lean body mass (SUL) and scaled to body surface area (SUA). Mean hepatic computed tomography density was used to adjust SUV_mean for hepatic fat (SUV_FA). Hepatic SUV indices were divided by SUV from left ventricular cavity, thereby, eliminating whole body metric, to obtain a surrogate of blood fluorine-18-fluorodeoxyglucose clearance into liver, and multiplied by blood glucose to give a surrogate of hepatic glucose uptake rate (mSUV).

Results

SUL_max, SUA_max and all scaled to weight indices correlated strongly with weight. SUL_mean, SUL_FA, SUA_mean and SUA_FA, however, correlated weakly or not at all with weight, nor with their corresponding whole body metric in men or women, but correlated strongly when the sexes were combined into one group. This was the result of sex differences in SUL (greater in men) and SUA (greater in women). There was, however, no sex difference in mSUV.

Conclusion

Weight is unsuitable for calculating SUV. SUL and SUA are also inappropriate as maxima but appropriate as mean and fat-adjusted values. However, SUL is recommended for both sexes because SUA is influenced by both body fat and weight. Sex differences in SUL and SUA give rise to misleading correlations when sexes are combined into one group.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET is less promising. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. This paper aims to identify the optimal dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen patients with nonalcoholic fatty liver disease were included. Each patient underwent 1 h dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: the traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), a model with population-based dual-blood input function (DBIF), and a new model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation score. Results showed that the optimization-derived DBIF model improved liver time activity curve fitting and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for dynamic liver FDG-PET kinetic analysis in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation.

Effectiveness of Repeat 18F-Fluorodeoxyglucose Positron Emission Tomography Computerized Tomography (PET-CT) Scan in Identifying Interval Metastases for Patients with Esophageal Cancer

INTRODUCTION

An 18F-fluorodeoxyglucose positron emission tomography-computerized tomography (PET-CT) scan is performed after neoadjuvant chemoradiation (nCRT) to restage esophageal cancer. The purpose of this study was to determine the ability of PET-CT to accurately identify interval metastatic disease following nCRT.

METHODS

This was a single-institution retrospective review (January 2005-February 2012) of patients with esophageal cancer treated with nCRT who underwent pre- and post-nCRT PET-CT.

RESULTS

A total of 283 patients were treated with nCRT, of whom 258 (91.2%) had both a pre- and post-nCRT PET-CT. On the post-nCRT PET-CT, 64 patients (24.8%) had interval findings concerning for metastatic disease. Of these patients, only 10 (15.6%) had true-positive findings of metastatic disease (six biopsy proven). The sites of interval metastases included bone (4), liver (3), peritoneum (1), mediastinal lymph nodes (1), and cervical lymph nodes (1). The positive predictive value of post-nCRT PET-CT for interval metastases was 15.6% (10/64), and the yield for detecting metastases since the pre-nCRT PET-CT was 3.9% (10/258). The work-up of the 54 patients (20.9% of the initial starting group) with false-positive post-nCRT findings included biopsy (24.6%) and immediate additional imaging (45.2%). A total of 208 patients proceeded with surgery: 163 (78.4%) had no new findings on post-nCRT PET-CT, and 45 (21.6%) had new false-positive findings. False-positive sites mainly included the lung (15) and liver (14).

CONCLUSIONS

The yield of post-nCRT PET-CT for the detection of new metastatic disease was 3.9%. Post-nCRT PET-CT often leads to a high proportion of false positives and subsequent investigational work-up.

Hepatic glucose utilization in hepatic steatosis and obesity

Hepatic steatosis is associated with obesity and insulin resistance. Whether hepatic glucose utilization rate (glucose phosphorylation rate; MRglu) is increased in steatosis and/or obesity is uncertain. Our aim was to determine the separate relationships of steatosis and obesity with MRglu. Sixty patients referred for routine PET/CT had dynamic PET imaging over the abdomen for 30 min post-injection of F-18-fluorodeoxyglucose (FDG), followed by Patlak-Rutland graphical analysis of the liver using abdominal aorta for arterial input signal. The plot gradient was divided by the intercept to give hepatic FDG clearance normalized to hepatic FDG distribution volume (ml/min per 100 ml) and multiplied by blood glucose to give hepatic MRglu (μmol/min per 100 ml). Hepatic steatosis was defined as CT density of ≤40 HU measured from the 60 min whole body routine PET/CT and obesity as body mass index of ≥30 kg/m² Hepatic MRglu was higher in patients with steatosis (3.3±1.3 μmol/min per 100 ml) than those without (1.7±1.2 μmol/min per 100 ml; P<0.001) but there was no significant difference between obese (2.5±1.6 μmol/min per 100 ml) and non-obese patients (2.1±1.3 μmol/min per 100 ml). MRglu was increased in obese patients only if they had steatosis. Non-obese patients with steatosis still had increased MRglu. There was no association between MRglu and chemotherapy history. We conclude that MRglu is increased in hepatic steatosis probably through insulin resistance, hyperinsulinaemia and up-regulation of hepatic hexokinase, irrespective of obesity.