Dataset Information

Reproducibility of compartmental modelling of 18F-FDG PET/CT to evaluate lung inflammation.

ABSTRACT: INTRODUCTION:Compartmental modelling is an established method of quantifying 18F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of 18F-FDG; in this paper, we address this unmet need. METHODS:Retrospective subject data were obtained from the EVOLVE observational study: Ten COPD patients (age =66±9; 8M/2F), 10 ?1ATD patients (age =63±8; 7M/3F) and 10 healthy volunteers (age =68±8; 9M/1F) never smokers. PET and CT images were co-registered, and whole lung regions were extracted from CT using an automated algorithm; the descending aorta was defined using a manually drawn region. Subsequent stages of the compartmental analysis were performed by two independent operators using (i) a MIAKATTM based pipeline and (ii) an in-house developed pipeline. We evaluated the metabolic rate constant of 18F-FDG (Kim) and the fractional blood volume (Vb); Bland-Altman plots were used to compare the results. Further, we adjusted the in-house pipeline to identify the salient features in the analysis which may help improve the standardisation of this technique in the lung. RESULTS:The initial agreement on a subject level was poor: Bland-Altman coefficients of reproducibility for Kim and Vb were 0.0031 and 0.047 respectively. However, the effect size between the groups (i.e. COPD, ?1ATD and healthy subjects) was similar using either pipeline. We identified the key drivers of this difference using an incremental approach: ROI methodology, modelling of the IDIF and time delay estimation. Adjustment of these factors led to improved Bland-Altman coefficients of reproducibility of 0.0015 and 0.027 for Kim and Vb respectively. CONCLUSIONS:Despite similar methodology, differences in implementation can lead to disparate results in the outcome parameters. When reporting the outcomes of lung compartmental modelling, we recommend the inclusion of the details of ROI methodology, input function fitting and time delay estimation to improve reproducibility.

SUBMITTER: Vass LD

PROVIDER: S-EPMC6915187 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Reproducibility of compartmental modelling of <sup>18</sup>F-FDG PET/CT to evaluate lung inflammation.

Vass Laurence D LD Lee Sarah S Wilson Frederick J FJ Fisk Marie M Cheriyan Joseph J Wilkinson Ian I

EJNMMI physics 20191216 1

<h4>Introduction</h4>Compartmental modelling is an established method of quantifying <sup>18</sup>F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of ...[more]

PMID: 31844995

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Project description:BackgroundAn inflammatory reaction in the airways and lung parenchyma, comprised mainly of neutrophils and alveolar macrophages, is present in some patients with chronic obstructive pulmonary disease (COPD). Thoracic fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) has been proposed as a promising imaging biomarker to assess this inflammation. We sought to introduce a fully quantitative analysis method and compare this with previously published studies based on the Patlak approach using a dataset comprising 18F-FDG PET scans from COPD subjects with elevated circulating inflammatory markers (fibrinogen) and matched healthy volunteers (HV). Dynamic 18F-FDG PET scans were obtained for high-fibrinogen (>2.8 g/l) COPD subjects (N = 10) and never smoking HV (N = 10). Lungs were segmented using co-registered computed tomography images and subregions (upper, middle and lower) were semi-automatically defined. A quantitative analysis approach was developed, which corrects for the presence of air and blood in the lung (qABL method), enabling direct estimation of the metabolic rate of FDG in lung tissue. A normalised Patlak analysis approach was also performed to enable comparison with previously published results. Effect sizes (Hedge's g) were used to compare HV and COPD groups.ResultsThe qABL method detected no difference (Hedge's g = 0.15 [-0.76 1.04]) in the tissue metabolic rate of FDG in the whole lung between HV (μ = 6.0 ± 1.9 × 10-3 ml cm-3 min-1) and COPD (μ = 5.7 ± 1.7 × 10-3 ml cm-3 min-1). However, analysis with the normalised Patlak approach detected a significant difference (Hedge's g = -1.59 [-2.57 -0.48]) in whole lung between HV (μ = 2.9 ± 0.5 × 10-3 ml cm-3 min-1) and COPD (μ = 3.9 ± 0.7 × 10-3 ml cm-3 min-1). The normalised Patlak endpoint was shown to be a composite measure influenced by air volume, blood volume and actual uptake of 18F-FDG in lung tissue.ConclusionsWe have introduced a quantitative analysis method that provides a direct estimate of the metabolic rate of FDG in lung tissue. This work provides further understanding of the underlying origin of the 18F-FDG signal in the lung in disease groups and helps interpreting changes following standard or novel therapies.

Project description:Knowledge of the within-subject variability of 18F-FDG PET/MRI measurements is necessary for proper interpretation of quantitative PET or MRI metrics in the context of therapeutic efficacy assessments with integrated PET/MRI scanners. The goal of this study was to determine the test-retest repeatability of these metrics on PET/MRI, with comparison to similar metrics acquired by PET/CT. Methods: This prospective study enrolled subjects with pathology-proven pelvic malignancies. Baseline imaging consisted of PET/CT immediately followed by PET/MRI, using a single 370-MBq 18F-FDG dose. Repeat imaging was performed within 7 d using an identical imaging protocol, with no oncologic therapy between sessions. PET imaging on both scanners consisted of a list-mode acquisition at a single pelvic station. The MRI consisted of 2-point Dixon imaging for attenuation correction, standard sequences for anatomic correlation, and diffusion-weighted imaging. PET data were statically reconstructed using various frame durations and minimizing uptake time differences between sessions. SUV metrics were extracted for both PET/CT and PET/MRI in each imaging session. Apparent diffusion coefficient (ADC) metrics were extracted for both PET/MRI sessions. Results: The study cohort consisted of 14 subjects (13 female, 1 male) with various pelvic cancers (11 cervical, 2 rectal, 1 endometrial). For SUVmax, the within-subject coefficient of variation (wCV) appeared higher for PET/CT (8.5%-12.8%) than PET/MRI (6.6%-8.7%) across all PET reconstructions, though with no significant repeatability differences (all P values ≥ 0.08) between modalities. For lean body mass-adjusted SUVpeak, the wCVs appeared similar for PET/CT (9.9%-11.5%) and PET/MRI (9.2%-11.3%) across all PET reconstructions, again with no significant repeatability differences (all P values ≥ 0.14) between modalities. For PET/MRI, the wCV for ADCmedian of 3.5% appeared lower than the wCVs for SUVmax (6.6%-8.7%) and SULpeak (9.2%-11.3%), though without significant repeatability differences (all P values ≥ 0.23). Conclusion: For solid tumors of the pelvis, the repeatability of the evaluated SUV and ADC metrics on 18F-FDG PET/MRI is both acceptably high and similar to previously published values for 18F-FDG PET/CT and MRI, supporting the use of 18F-FDG PET/MRI for quantitative oncologic treatment response assessments.

Project description:Calibration and reproducibility of quantitative 18F-FDG PET measures are essential for adopting integral 18F-FDG PET/CT biomarkers and response measures in multicenter clinical trials. We implemented a multicenter qualification process using National Institute of Standards and Technology-traceable reference sources for scanners and dose calibrators, and similar patient and imaging protocols. We then assessed SUV in patient test-retest studies. Methods: Five 18F-FDG PET/CT scanners from 4 institutions (2 in a National Cancer Institute-designated Comprehensive Cancer Center, 3 in a community-based network) were qualified for study use. Patients were scanned twice within 15 d, on the same scanner (n = 10); different but same model scanners within an institution (n = 2); or different model scanners at different institutions (n = 11). SUVmax was recorded for lesions, and SUVmean for normal liver uptake. Linear mixed models with random intercept were fitted to evaluate test-retest differences in multiple lesions per patient and to estimate the concordance correlation coefficient. Bland-Altman plots and repeatability coefficients were also produced. Results: In total, 162 lesions (82 bone, 80 soft tissue) were assessed in patients with breast cancer (n = 17) or other cancers (n = 6). Repeat scans within the same institution, using the same scanner or 2 scanners of the same model, had an average difference in SUVmax of 8% (95% confidence interval, 6%-10%). For test-retest on different scanners at different sites, the average difference in lesion SUVmax was 18% (95% confidence interval, 13%-24%). Normal liver uptake (SUVmean) showed an average difference of 5% (95% confidence interval, 3%-10%) for the same scanner model or institution and 6% (95% confidence interval, 3%-11%) for different scanners from different institutions. Protocol adherence was good; the median difference in injection-to-acquisition time was 2 min (range, 0-11 min). Test-retest SUVmax variability was not explained by available information on protocol deviations or patient or lesion characteristics. Conclusion: 18F-FDG PET/CT scanner qualification and calibration can yield highly reproducible test-retest tumor SUV measurements. Our data support use of different qualified scanners of the same model for serial studies. Test-retest differences from different scanner models were greater; more resolution-dependent harmonization of scanner protocols and reconstruction algorithms may be capable of reducing these differences to values closer to same-scanner results.

Project description:BackgroundMagnetic resonance imaging (MRI) plays an important role in the diagnosis of leptomeningeal metastases (LM); however, some sub-centimeter lesions may be missed. Positron emission tomography/computed tomography (PET/CT) has a high sensitivity and may play a synergistic role with MRI in diagnosing spinal LM (SLM). We aimed to retrospectively evaluate the detection of SLM with 18F-fluorodeoxyglucose PET/CT (18F-FDG PET/CT) compared to that of whole spinal cord MRI in a single center.MethodsPatients with SLM who had undergone 18F-FDG PET/CT and MRI were enrolled. 18F-FDG PET/CT imaging findings were independently reviewed by 2 nuclear medicine physicians. 18F-FDG PET/CT findings of SLMs were described. A consistency test was conducted to assess the patient-based diagnostic results obtained by the 2 physicians. Patient-based sensitivity, accuracy, and specificity in diagnosing SLM between 18F-FDG PET/CT and MRI of the whole spinal cord were compared using the chi-square or Fisher's exact test. A P value of <0.05 was considered statistically significant. The receiver operating characteristic (ROC) curve was obtained to assess the diagnostic performance of maximum standardized uptake value (SUVmax) to diagnose SLM.ResultsA total of 16 patients with SLM were included in this study from October 2010 to April 2022. The primary tumor involved the lungs, liver, ovaries, prostate, esophagus, and unknown primary site. The mean age of patients, including 13 males and 3 females, was 57.8±11.2 (range, 34-73) years. Of 16 patients with SLM, 10 had nodular diseases, 2 had linear diseases, and 4 had mixed diseases. The kappa value of the consistency test of the 2 radiologists' diagnostic results was 0.765. The patient-based sensitivity, specificity, and accuracy of 18F-FDG PET/CT in diagnosing SLM were 87.5%, 89.2%, and 88.7%, respectively and those of whole spinal cord MRI were 75.0%, 100.0%, and 92.5%, respectively. There were no significant differences in sensitivity, specificity, and accuracy between the 2 methods, with P values of 0.654, 0.115, and 0.506, respectively. However, more nodular diseases were observed on PET/CT. The area under the ROC curve (AUC) for the prediction of SLM by SUVmax was 0.907 [95% confidence interval (CI): 0.831-0.983]. When SUVmax ≥2.45, the Youden index was the largest, and the sensitivity and specificity were 89.3% and 75.7%, respectively.Conclusions18F-FDG PET/CT is a good choice of imaging modality for assessing SLM. In the diagnosis of SLMs, PET/CT and enhanced MRI can play a better synergistic role.

Project description:Backgroundsignificance of incidental thyroid 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) uptake on positron emission tomography/computed tomography (PET/CT) scans remains controversial. We aimed to evaluate the ability of [18F]FDG-PET/CT texture analysis to predict final diagnosis in thyroid incidentaloma.MethodsWe retrospectively evaluated medical records of all patients who performed a [18F]FDG-PET/CT from January 2012 to October 2016. Those patients who presented a thyroid incidentaloma described in the medical records and performed a fine needle aspiration in our institution were considered for the analysis. Cytological and/or histological results were used as reference standard to define the final diagnosis. In case of negative cytology, the nodule was considered benign. In case of non-diagnostic or inconclusive results ultrasound, follow-up and further cytology/histology were used as final diagnosis. For suspected or positive cytological result, histology was used as reference standard. PET images were segmented using a General Electric AW workstation running PET VCAR software (GE Healthcare, Waukesha, WI, USA) settled with a threshold of 40% SUVmax. LifeX software (http://www.lifexsoft.org) was used to perform texture analysis. Statistical analysis was performed with R package (https://www.r-project.org).ResultsWe identified 55 patients with incidental thyroid [18F]FDG uptake. Five patients were excluded from the analysis because a final diagnosis was not available. Thirty-two out of 50 patients had benign nodules while in 18/50 cases a malignancy (primary thyroid cancer = 15, metastases = 3) was diagnosed. Conventional PET parameters and histogram-based features were calculated for all 50 patients, while other matrices-based features were available for 28/50 patients. SUVmax and skewness resulted significantly different in benign and malignant nodules (p = 0.01 and = 0.02, respectively). Using ROC analysis, seven features were identified as potential predictors. Among all the textural features tested, skewness showed the best area under the curve (=?0.66). SUV-based parameters resulted in the highest specificity while MTV, TLG, skewness and kurtosis, as well as correlationGLCM resulted better in sensitivity.Conclusions[18F]FDG-PET/CT texture analysis seems to be a promising approach to stratify the patients with thyroid incidentaloma identified on PET scans, with respect to the risk of the diagnosis of a malignant thyroid nodule and thus, could refine the selection of the patients to be referred for cytology.

Dataset Information

Reproducibility of compartmental modelling of 18F-FDG PET/CT to evaluate lung inflammation.

Publications

Reproducibility of compartmental modelling of <sup>18</sup>F-FDG PET/CT to evaluate lung inflammation.

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