PET with
F-FDG has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and to monitor disease progression and treatment outcomes in lung ...diseases that interfere with gas exchange through alterations of the pulmonary parenchyma, airways, or vasculature. To date, however, there are no widely accepted standard acquisition protocols or imaging data analysis methods for pulmonary
F-FDG PET/CT in these diseases, resulting in disparate approaches. Hence, comparison of data across the literature is challenging. To help harmonize the acquisition and analysis and promote reproducibility, we collated details of acquisition protocols and analysis methods from 7 PET centers. From this information and our discussions, we reached the consensus recommendations given here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting.
Thirty patients with proven colorectal cancer prospectively underwent integrated 18F-FDG PET/DCE-CT to assess the metabolic-flow phenotype. Both CT blood flow parametric maps and PET images were ...analyzed. Correlations between PET heterogeneity and perfusion CT were assessed by Spearman's rank correlation analysis.
Blood flow visualization provided by DCE-CT images was significantly correlated with 18F-FDG PET metabolically active tumor volume as well as with uptake heterogeneity for patients with stage III/IV tumors (|ρ|:0.66 to 0.78; p-value<0.02).
The positive correlation found with tumor blood flow indicates that intra-tumor heterogeneity of 18F-FDG PET accumulation reflects to some extent tracer distribution and consequently indicates that 18F-FDG PET intra-tumor heterogeneity may be associated with physiological processes such as tumor vascularization.
PET with 18F-FDG has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and to monitor disease progression and treatment outcomes in lung ...diseases that interfere with gas exchange through alterations of the pulmonary parenchyma, airways, or vasculature. To date, however, there are no widely accepted standard acquisition protocols or imaging data analysis methods for pulmonary 18F-FDG PET/CT in these diseases, resulting in disparate approaches. Hence, comparison of data across the literature is challenging. To help harmonize the acquisition and analysis and promote reproducibility, we collated details of acquisition protocols and analysis methods from 7 PET centers. From this information and our discussions, we reached the consensus recommendations given here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting.
Primary central nervous system lymphoma (PCNSL) has variable imaging appearances, which overlap with those of glioblastoma (GBM), thereby necessitating invasive tissue diagnosis. We aimed to ...investigate whether a rapid filtration histogram analysis of clinical MRI data supports the distinction of PCNSL from GBM. Ninety tumours (PCNSL n = 48, GBM n = 42) were analysed using pre-treatment MRI sequences (T1-weighted contrast-enhanced (T1CE), T2-weighted (T2), and apparent diffusion coefficient maps (ADC)). The segmentations were completed with proprietary texture analysis software (TexRAD version 3.3). Filtered (five filter sizes SSF = 2–6 mm) and unfiltered (SSF = 0) histogram parameters were compared using Mann-Whitney U non-parametric testing, with receiver operating characteristic (ROC) derived area under the curve (AUC) analysis for significant results. Across all (n = 90) tumours, the optimal algorithm performance was achieved using an unfiltered ADC mean and the mean of positive pixels (MPP), with a sensitivity of 83.8%, specificity of 8.9%, and AUC of 0.88. For subgroup analysis with >1/3 necrosis masses, ADC permitted the identification of PCNSL with a sensitivity of 96.9% and specificity of 100%. For T1CE-derived regions, the distinction was less accurate, with a sensitivity of 71.4%, specificity of 77.1%, and AUC of 0.779. A role may exist for cross-sectional texture analysis without complex machine learning models to differentiate PCNSL from GBM. ADC appears the most suitable sequence, especially for necrotic lesion distinction.
Although approval for a routine role for preoperative PET in breast carcinoma may yet require further supportive evidence, the potential is clearly there to add a new dimension to the noninvasive ...evaluation of patients with the disease, and reveal new biological information to facilitate selection of the best possible therapy.
Inflammation and angiogenesis are hypothesized to be important factors contributing to plaque vulnerability, whereas calcification is suggested to confer stability. To investigate this in vivo, we ...combined CT angiography and PET and compared the findings with immunohistochemistry for patients undergoing carotid endarterectomy.
Twenty-one consecutive patients (18 men, 3 women; mean age ± SD, 68.3 ± 7.3) undergoing carotid endarterectomy were recruited for combined carotid (18)F-FDG PET/CT angiography. Plaque (18)F-FDG uptake was quantified with maximum standardized uptake value, and CT angiography quantified percentage plaque composition (calcium and lipid). Surgical specimens underwent ex vivo CT aiding image registration, followed by immunohistochemical staining for CD68 (macrophage density) and vascular endothelial growth factor (angiogenesis). Relationships between imaging and immunohistochemistry were assessed with Spearman rank correlation and multivariable regression.
The mean (±SD) surgically excised carotid plaque (18)F-FDG metabolism was 2.4 (±0.5) versus 2.2 (±0.3) contralaterally (P = 0.027). There were positive correlations between plaque (18)F-FDG metabolism and immunohistochemistry with CD68 (ρ = 0.55; P = 0.011) and vascular endothelial growth factor (ρ = 0.47; P = 0.031). There was an inverse relationship between plaque (18)F-FDG metabolism and plaque percentage calcium composition on CT (ρ = -0.51; P = 0.018) and between calcium composition and immunohistochemistry with CD68 (ρ = -0.57; P = 0.007). Regression showed that maximum standardized uptake value and calcium composition were independently significant predictors of angiogenesis, and calcium composition was a predictor of macrophage density.
We provide in vivo evidence that increased plaque metabolism is associated with increased biomarkers of angiogenesis and inflammation, whereas plaque calcification is inversely related to PET and histologic biomarkers of inflammation.
Abstract Objective There is a need for prognostic biomarkers for risk assessment of small abdominal aortic aneurysm (AAA). Since CT textural analysis of tissue is a recognized feature of adverse ...biology and patient outcome in other diseases, we investigated it as a possible biomarker in small AAA. Methods Fifty consecutive patients (46-men, 4-woman, median-age 75y, range 56–85) with small AAA (3–5.5 cm) under surveillance undergoing serial ultrasound were prospectively recruited and assessed at baseline with CT texture analysis (CTTA) and18 F-Fluorodeoxyglucose positron emission tomography (18 F-FDG-PET). We followed forty patients (36-men, 4-woman, median-age = 74 y, range 60–85, participation rate = 80% for 1 year. For each axial image, CTTA using the filtration-histogram technique was carried out using a software algorithm that selectively extracts texture features of different coarseness (fine, medium and coarse) and intensity variation. Standard-deviation (SD) and kurtosis (K) at each feature-scale were measured. The maximum standardized uptake value (SUVmax ) of18 F-FDG in each axial image of the AAA was also measured with corrections for blood pool18 F-FDG activity to assess AAA metabolic activity. Specificity, sensitivity, and c-statistics were calculated with 95% confidence intervals for prediction of significant AAA expansion (≥2 mm) by CTTA measures before and after adjusting for clinical variables. Results The median aneurysm expansion at 12 months was 2.0 mm, (IQR 0.0–4.0). Coarse texture SD correlated inversely with AAA SUVmax ( rs = −0.456, P = 0.003). Medium coarse texture K correlated significantly with future AAA expansion adjusted for baseline size ( rs = 0.343, P = 0.030). AAA SUVmax correlated inversely with AAA expansion corrected for baseline size ( rs = −0.383, P = 0.015). Medium texture K was a strong predictor of significant AAA expansion (area under the Receiver-operating-characteristic (ROC) curve was 0.813) after adjusting for clinical variables. Conclusion We have shown evidence that CT signal heterogeneity measurements in small aortic aneurysm may be considered as a risk stratification tool in future prospective studies to identify aneurysms at risk of significant expansion. CT textural data appears to reflect AAA metabolism measured by PET.
Inflammation drives atherosclerotic plaque rupture. Although inflammation can be measured using fluorine-18-labeled fluorodeoxyglucose positron emission tomography (
FFDG PET),
FFDG lacks cell ...specificity, and coronary imaging is unreliable because of myocardial spillover.
This study tested the efficacy of gallium-68-labeled DOTATATE (
Ga-DOTATATE), a somatostatin receptor subtype-2 (SST
)-binding PET tracer, for imaging atherosclerotic inflammation.
We confirmed
Ga-DOTATATE binding in macrophages and excised carotid plaques.
Ga-DOTATATE PET imaging was compared to
FFDG PET imaging in 42 patients with atherosclerosis.
Target SSTR2 gene expression occurred exclusively in "proinflammatory" M1 macrophages, specific
Ga-DOTATATE ligand binding to SST
receptors occurred in CD68-positive macrophage-rich carotid plaque regions, and carotid SSTR2 mRNA was highly correlated with in vivo
Ga-DOTATATE PET signals (r = 0.89; 95% confidence interval CI: 0.28 to 0.99; p = 0.02).
Ga-DOTATATE mean of maximum tissue-to-blood ratios (mTBR
) correctly identified culprit versus nonculprit arteries in patients with acute coronary syndrome (median difference: 0.69; interquartile range IQR: 0.22 to 1.15; p = 0.008) and transient ischemic attack/stroke (median difference: 0.13; IQR: 0.07 to 0.32; p = 0.003).
Ga-DOTATATE mTBR
predicted high-risk coronary computed tomography features (receiver operating characteristics area under the curve ROC AUC: 0.86; 95% CI: 0.80 to 0.92; p < 0.0001), and correlated with Framingham risk score (r = 0.53; 95% CI: 0.32 to 0.69; p <0.0001) and
FFDG uptake (r = 0.73; 95% CI: 0.64 to 0.81; p < 0.0001).
FFDG mTBR
differentiated culprit from nonculprit carotid lesions (median difference: 0.12; IQR: 0.0 to 0.23; p = 0.008) and high-risk from lower-risk coronary arteries (ROC AUC: 0.76; 95% CI: 0.62 to 0.91; p = 0.002); however, myocardial
FFDG spillover rendered coronary
FFDG scans uninterpretable in 27 patients (64%). Coronary
Ga-DOTATATE PET scans were readable in all patients.
We validated
Ga-DOTATATE PET as a novel marker of atherosclerotic inflammation and confirmed that
Ga-DOTATATE offers superior coronary imaging, excellent macrophage specificity, and better power to discriminate high-risk versus low-risk coronary lesions than
FFDG. (Vascular Inflammation Imaging Using Somatostatin Receptor Positron Emission Tomography VISION; NCT02021188).
Objective
To determine how commercial software platform upgrades impact on derived parameters for colorectal cancer.
Materials and methods
Following ethical approval, 30 patients with suspected ...colorectal cancer underwent Perfusion CT using integrated 64 detector PET/CT before surgery. Analysis was performed using software based on modified distributed parameter analysis (Perfusion software version 4; Perfusion 4.0), then repeated using the previous version (Perfusion software version 3; Perfusion 3.0). Tumour blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface area product (PS) were determined for identical regions-of-interest. Slice-by-slice and ‘whole tumour’ variance was assessed by Bland-Altman analysis.
Results
Mean BF, BV and PS was 20.4%, 59.5%, and 106% higher, and MTT 14.3% shorter for Perfusion 4.0 than Perfusion 3.0. The mean difference (95% limits of agreement) were +13.5 (−44.9 to 72.0), +2.61 (−0.06 to 5.28), −1.23 (−6.83 to 4.36), and +14.2 (−4.43 to 32.8) for BF, BV, MTT and PS respectively. Within subject coefficient of variation was 36.6%, 38.0%, 27.4% and 60.6% for BF, BV, MTT and PS respectively indicating moderate to poor agreement.
Conclusion
Software version upgrades of the same software platform may result in significantly different parameter values, requiring adjustments for cross-version comparison.
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