Dataset Information

Total metabolic lesion volume of lymph nodes measured by ¹⁸F-FDG PET/CT: a new predictor of macrophage activation syndrome in adult-onset Still's disease.

ABSTRACT:

Background

To investigate the potential utility of quantitative parameters obtained by ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in the assessment of disease severity and the occurrence of macrophage activation syndrome (MAS) in adult-onset Still's disease (AOSD).

Methods

Fifty-seven patients with AOSD who underwent pre-treatment ¹⁸F-FDG PET/CT were recruited in this study and compared with 60 age- and sex-matched healthy controls. Clinical features and laboratory data were recorded. The systemic score was assessed to determine the disease severity. The maximal standardized uptake value (SUV_max), metabolic lesion volume (MLV), and total lesion glycolysis (TLG) were used to evaluate the involved organs and tissues that abnormally accumulated ¹⁸F-FDG. Multivariate analysis was performed to identify the PET/CT-derived risk factors contributing to the AOSD-related MAS, and their diagnostic efficiency was evaluated.

Results

High ¹⁸F-FDG accumulation was observed in the bone marrow (SUV_max median, 5.10), spleen (SUV_max median, 3.70), and lymph nodes (LNs, SUV_max median, 5.55). The SUV_max of the bone marrow (rho = 0.376, p = 0.004), SUV_max of the spleen (rho = 0.450, p < 0.001), TLG_total of LNs (rho = 0.386, p = 0.017), and MLV_total of LNs (rho = 0.391, p = 0.015) were correlated with the systemic score. The SUV_max of the spleen (p = 0.017), TLG_total of LNs (p = 0.045), and MLV_total of LNs (p = 0.012) were higher in patients with MAS than in those without MAS. A MLV_total of LNs > 62.2 (OR 27.375, p = 0.042) was an independent predictive factor for MAS with a sensitivity of 80.0% and a specificity of 93.9%.

Conclusions

The glucose metabolic level of the spleen could be an effective and easy-to-use imaging indicator of disease severity, and MLV_total of LNs > 62.2 was a strong predictor of MAS occurrence in patients with AOSD.

SUBMITTER: Wan L

PROVIDER: S-EPMC8008587 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesThe accurate assessment of lymph node metastases (LNMs) and the preoperative nodal (N) stage are critical for the precise treatment of patients with gastric cancer (GC). The diagnostic performance, however, of current imaging procedures used for this assessment is sub-optimal. Our aim was to investigate the value of preoperative 18F-FDG PET/CT radiomic features to predict LNMs and the N stage.MethodsWe retrospectively collected clinical and 18F-FDG PET/CT imaging data of 185 patients with GC who underwent total or partial radical gastrectomy. Patients were allocated to training and validation sets using the stratified method at a fixed ratio (8:2). There were 2,100 radiomic features extracted from the 18F-FDG PET/CT scans. After selecting radiomic features by the random forest, relevancy-based, and sequential forward selection methods, the BalancedBagging ensemble classifier was established for the preoperative prediction of LNMs, and the OneVsRest classifier for the N stage. The performance of the models was primarily evaluated by the AUC and accuracy, and validated by the independent validation methods. Analysis of the feature importance and the correlation were also conducted. We also compared the predictive performance of our radiomic models to that with the contrast-enhanced CT (CECT) and 18F-FDG PET/CT.ResultsThere were 185 patients-127 men, 58 women, with the median age of 62, and an age range of 22-86 years. One CT feature and one PET feature were selected to predict LNMs and achieved the best performance (AUC: 82.2%, accuracy: 85.2%). This radiomic model also detected some LNMs that were missed in CECT (19.6%) and 18F-FDG PET/CT (35.7%). For predicting the N stage, four CT features and one PET feature were selected (AUC: 73.7%, accuracy: 62.3%). Of note, a proportion of patients in the validation set whose LNMs were incorrectly staged by CECT (57.4%) and 18F-FDG PET/CT (55%) were diagnosed correctly by our radiomic model.ConclusionWe developed and validated two machine learning models based on the preoperative 18F-FDG PET/CT images that have a predictive value for LNMs and the N stage in GC. These predictive models show a promise to offer a potentially useful adjunct to current staging approaches for patients with GC.

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:This study aimed to compare CE-CT and 2-[18F]FDG-PET/CT for response monitoring metastatic breast cancer (MBC). The primary objective was to predict progression-free and disease-specific survival for responders vs. non-responders on CE-CT and 2-[18F]FDG-PET/CT. The secondary objective was to assess agreement between response categorization for the two modalities. Treatment response in women with MBC was monitored prospectively by simultaneous CE-CT and 2-[18F]FDG-PET/CT, allowing participants to serve as their own controls. The standardized response evaluation criteria in solid tumors (RECIST 1.1) and PET response criteria in solid tumors (PERCIST) were used for response categorization. For prediction of progression-free and disease-specific survival, treatment response was dichotomized into responders (partial and complete response) and non-responders (stable and progressive disease) at the first follow-up scan. Progression-free survival was defined as the time from baseline until disease progression or death from any cause. Disease-specific survival was defined as the time from baseline until breast cancer-specific death. Agreement between response categorization for both modalities was analyzed for all response categories and responders vs. non-responders. At the first follow-up, tumor response was reported more often by 2-[18F]FDG-PET/CT than CE-CT, with only fair agreement on response categorization between the two modalities (weighted Kappa 0.28). Two-year progression-free survival for responders vs. non-responders by CE-CT was 54.2% vs. 46.0%, compared with 59.1% vs. 14.3% by 2-[18F]FDG-PET/CT. Correspondingly, 2-year disease-specific survival were 83.3% vs. 77.8% for CE-CT and 84.6% vs. 61.9% for 2-[18F]FDG-PET/CT. Tumor response on 2-[18F]FDG-PET/CT was significantly associated with progression-free (HR: 3.49, P < 0.001) and disease-specific survival (HR 2.35, P = 0.008), while no association was found for tumor response on CE-CT. In conclusion, 2-[18F]FDG-PET/CT appears a better predictor of progression-free and disease-specific survival than CE-CT when used to monitor metastatic breast cancer. In addition, we found low concordance between response categorization between the two modalities.Trial registrationClinical.Trialsgov. NCT03358589. Registered 30/11/2017-Retrospectively registered, http://www.Clinicaltrialsgov.

Project description:This study assessed whether preoperative maximum standardized uptake value (SUVmax) of metastatic lymph nodes (LNs) measured by F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT) could improve the prediction of prognosis in gastric cancer.One hundred fifty-one patients with gastric cancer and pathologically confirmed LN involvement who had undergone preoperative F-FDG PET/CT prior to curative surgical resection were retrospectively enrolled. To obtain nodal SUVmax, a transaxial image representing the highest F-FDG uptake was carefully selected, and a region of interest was manually drawn on the highest F-FDG accumulating LN. Conventional prognostic parameters and PET findings (primary tumor and nodal SUVmax) were analyzed for prediction of recurrence-free survival (RFS) and overall survival (OS). Furthermore, prognostic accuracy of survival models was assessed using c-statistics.Of the 151 patients, 38 (25%) experienced recurrence and 34 (23%) died during follow-up (median follow-up, 48 months; range, 5-74 months). Twenty-seven patients (18%) showed positive F-FDG nodal uptake (range, 2.0-22.6). In these 27 patients, a receiver-operating characteristic curve demonstrated a nodal SUVmax of 2.8 to be the optimal cutoff for predicting RFS and OS. The univariate and multivariate analyses showed that nodal SUVmax (hazard ratio [HR]?= 2.71, P < 0.0001), pathologic N (pN) stage (HR = 2.58, P = 0.0058), and pathologic T (pT) stage (HR = 1.77, P = 0.0191) were independent prognostic factors for RFS. Also, nodal SUVmax (HR = 2.80, P < 0.0001) and pN stage (HR = 2.28, P = 0.0222) were independent prognostic factors for OS. A predictive survival model incorporating conventional risk factors (pT/pN stage) gave a c-statistic of 0.833 for RFS and 0.827 for OS, whereas a model combination of nodal SUVmax with pT/pN stage gave a c-statistic of 0.871 for RFS (P = 0.0355) and 0.877 for OS (P = 0.0313).Nodal SUVmax measured by preoperative F-FDG PET/CT is an independent prognostic factor for RFS and OS. Combining nodal SUVmax with pT/pN staging can improve survival prediction precision in patients with gastric cancer.

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.

Dataset Information

Total metabolic lesion volume of lymph nodes measured by ¹⁸F-FDG PET/CT: a new predictor of macrophage activation syndrome in adult-onset Still's disease.

Background

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Total metabolic lesion volume of lymph nodes measured by 18F-FDG PET/CT: a new predictor of macrophage activation syndrome in adult-onset Still's disease.

Background

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Total metabolic lesion volume of lymph nodes measured by ¹⁸F-FDG PET/CT: a new predictor of macrophage activation syndrome in adult-onset Still's disease.