Dataset Information

Quantitative [¹⁸F]florbetapir PET/CT may identify lung involvement in patients with systemic AL amyloidosis.

ABSTRACT:

Purpose

The clinical diagnosis of pulmonary involvement in individuals with systemic AL amyloidosis remains challenging. [¹⁸F]florbetapir imaging has previously identified AL amyloid deposits in the heart and extra-cardiac organs. The aim of this study is to determine quantitative [¹⁸F]florbetapir pulmonary kinetics to identify pulmonary involvement in individuals with systemic AL amyloidosis.

Methods

We prospectively enrolled 58 subjects with biopsy-proven AL amyloidosis and 9 control subjects (5 without amyloidosis and 4 with ATTR cardiac amyloidosis). Pulmonary [¹⁸F]florbetapir uptake was evaluated visually and quantified as distribution volume of specific binding (Vs) derived from compartmental analysis and simpler semiquantitative metrics of maximum standardized uptake values (SUVmax), retention index (RI), and target-to-blood ratio (TBR).

Results

On visual analysis, pulmonary tracer uptake was absent in most AL subjects (40/58, 69%); 12% (7/58) of AL subjects demonstrated intense bilateral homogeneous tracer uptake. In this group, compared to the control group, Vs (median Vs 30-fold higher, 9.79 vs. 0.26, p < 0.001), TBR (median TBR 12.0 vs. 1.71, p < 0.001), and RI (median RI 0.310 vs. 0.033, p < 0.001) were substantially higher. Notably, the AL group without visually apparent pulmonary [¹⁸F]florbetapir uptake also demonstrated a > 3-fold higher Vs compared to the control group (median 0.99 vs. 0.26, p < 0.001). Vs was independently related to left ventricular SUVmax, a marker of cardiac AL deposition, but not to ejection fraction, a marker of cardiac dysfunction. Also, intense [¹⁸F]florbetapir lung uptake was not related to [¹¹C]acetate lung uptake, suggesting that intense [¹⁸F]florbetapir lung uptake represents AL amyloidosis rather than heart failure.

Conclusions

[¹⁸F]florbetapir PET/CT offers the potential to noninvasively identify pulmonary AL amyloidosis, and its clinical relevance warrants further study.

SUBMITTER: Khor YM

PROVIDER: S-EPMC8202062 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Immunoglobulin light-chain (AL) amyloidosis affects multiple systemic organs. However, determination of the precise extent of organ involvement remains challenging. Targeted amyloid imaging with 18F-florbetapir PET/CT offers the potential to detect AL deposits in multiple organs. The primary aim of this study was to determine the distribution and frequency of AL deposits in the various organs of subjects with systemic AL amyloidosis using 18F-florbetapir PET/CT. Methods: This prospective study included 40 subjects with biopsy-proven AL amyloidosis including active AL amyloidosis (n = 30) or AL amyloidosis in hematologic remission for more than 1 y (n = 10). All subjects underwent 18F-florbetapir PET/CT, skull base to below the kidney scan field, from 60 to 90 min after injection of radiotracer. Volume-of-interest measurements of SUVmax were obtained using Hermes software for the parotid gland, tongue, thyroid, lung, gastric wall, pancreas, spleen, kidney, muscle, abdominal fat, lower thoracic spine, vertebral body, and humeral head. Uptake in each organ was visually compared with that in spine bone marrow. An SUVmax of at least 2.5 was considered abnormal in all organs other than the liver. Results: Compared with the international consensus definition of organ involvement, 18F-florbetapir PET/CT identified amyloid deposits in substantially higher percentages of subjects for several organ systems, including parotid gland (50% vs. 3%), tongue (53% vs. 10%), and lung (35% vs. 10%). In several organ systems, including kidney (13% vs. 28%) and abdominal wall fat (10% vs. 13%), PET identified involvement in fewer subjects than did international consensus. Quantitative analysis of 18F-florbetapir PET/CT revealed more frequent organ involvement than did visual analysis in the tongue, thyroid, lung, pancreas, kidney, muscle, and humeral head. Extensive organ amyloid deposits were observed in active AL as well as in AL remission cohorts, and in both cardiac and noncardiac AL cohorts. Conclusion: 18F-florbetapir PET/CT detected widespread organ amyloid deposition in subjects with both active AL and AL hematologic remission. In most instances, amyloid deposits in the various organs were not associated with clinical symptoms and, thus, were unrecognized. Early recognition of systemic organ involvement may help tailor treatment, and noninvasive monitoring of organ-level disease may guide management with novel fibril-resorbing therapies.

Project description:The present study examined the predictive values of amyloid PET, 18F-FDG PET, and nonimaging predictors (alone and in combination) for development of Alzheimer dementia (AD) in a large population of patients with mild cognitive impairment (MCI). Methods: The study included 319 patients with MCI from the Alzheimer Disease Neuroimaging Initiative database. In a derivation dataset (n = 159), the following Cox proportional-hazards models were constructed, each adjusted for age and sex: amyloid PET using 18F-florbetapir (pattern expression score of an amyloid-β AD conversion-related pattern, constructed by principle-components analysis); 18F-FDG PET (pattern expression score of a previously defined 18F-FDG-based AD conversion-related pattern, constructed by principle-components analysis); nonimaging (functional activities questionnaire, apolipoprotein E, and mini-mental state examination score); 18F-FDG PET + amyloid PET; amyloid PET + nonimaging; 18F-FDG PET + nonimaging; and amyloid PET + 18F-FDG PET + nonimaging. In a second step, the results of Cox regressions were applied to a validation dataset (n = 160) to stratify subjects according to the predicted conversion risk. Results: On the basis of the independent validation dataset, the 18F-FDG PET model yielded a significantly higher predictive value than the amyloid PET model. However, both were inferior to the nonimaging model and were significantly improved by the addition of nonimaging variables. The best prediction accuracy was reached by combining 18F-FDG PET, amyloid PET, and nonimaging variables. The combined model yielded 5-y free-of-conversion rates of 100%, 64%, and 24% for the low-, medium- and high-risk groups, respectively. Conclusion: 18F-FDG PET, amyloid PET, and nonimaging variables represent complementary predictors of conversion from MCI to AD. Especially in combination, they enable an accurate stratification of patients according to their conversion risks, which is of great interest for patient care and clinical trials.

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:BackgroundThe aim of this study was to evaluate 18F-AlF-NOTA-PRGD2 positron emission tomography/computed tomography (18F-RGD PET/CT) and serum inflammation biomarkers for predicting outcomes of patients receiving combined antiangiogenic treatment for advanced non-small cell lung cancer (NSCLC).MethodsPatients with advanced NSCLC underwent 18F-RGD PET/CT examination and provided blood samples before treatments commenced. PET/CT parameters included maximum standard uptake value (SUVmax) and mean standard uptake value (SUVmean), peak standard uptake value (SUVpeak) and metabolic tumor volume (MTV) for all contoured lesions. Biomarkers for inflammation included pretreatment neutrophil-to-lymphocyte ratio (PreNLR), pretreatment platelet-to-lymphocyte ratio (PrePLR), and pretreatment lymphocyte-to-monocyte ratio (PreLMR). Receiver operating characteristic (ROC) curve analysis was used to describe response prediction accuracy. Logistic regression and Cox's regression analysis was implemented to identify independent factors for short-term responses and progression-free survival (PFS).ResultsThis study included 23 patients. According to ROC curve analysis, there were significant correlations between the SUVmax, SUVmean, and 18F-RGD PET/CT MTV and short-term responses (p<0.05). SUVmax was identified using logistic regression analysis as a significant predictor of treatment sensitivity (p=0.008). Cox's multivariate regression analysis suggested that high SUVpeak (p=0.021) and high PreLMR (p=0.03) were independent PFS predictors. Combining SUVpeak and PreLMR may also increase the prognostic value for PFS, enabling us to identify a subgroup of patients with intermediate PFS.Conclusion18F-RGD uptake on PET/CT and serum inflammation biomarker pretreatment may predict outcomes for combined antiangiogenic treatments for advanced NSCLC patients. Higher 18F-RGD uptake and higher PreLMR also appear to predict improved short-term responses and PFS. Combining biomarkers may therefore provide a basis for risk stratification, although further research is required.

Dataset Information

Quantitative [¹⁸F]florbetapir PET/CT may identify lung involvement in patients with systemic AL amyloidosis.

Purpose

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Quantitative [18F]florbetapir PET/CT may identify lung involvement in patients with systemic AL amyloidosis.

Purpose

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Quantitative [¹⁸F]florbetapir PET/CT may identify lung involvement in patients with systemic AL amyloidosis.