Dataset Information

Brain metabolic changes across King's stages in amyotrophic lateral sclerosis: a ¹⁸F-2-fluoro-2-deoxy-D-glucose-positron emission tomography study.

ABSTRACT:

Purpose

To assess the brain metabolic correlates of the different regional extent of ALS, evaluated with the King's staging system, using brain ¹⁸F-2-fluoro-2-deoxy-D-glucose-PET (¹⁸F-FDG-PET).

Methods

Three hundred ninety ALS cases with King's stages 1, 2, and 3 (n = 390), i.e., involvement of 1, 2, and 3 body regions respectively, underwent brain ¹⁸F-FDG-PET at diagnosis. King's stage at PET was derived from ALSFRS-R and was regressed out against whole-brain metabolism in the whole sample. The full factorial design confirmed the hypothesis that differences among groups (King's 1, King's 2, King's 3, and 40 healthy controls (HC)) existed overall. Comparisons among stages and between each group and HC were performed. We included age at PET and sex as covariates.

Results

Brain metabolism was inversely correlated with stage in medial frontal gyrus bilaterally, and right precentral and postcentral gyri. The full factorial design resulted in a significant main effect of groups. There was no significant difference between stages 1 and 2. Comparing stage 3 to stage 1+2, a significant relative hypometabolism was highlighted in the former in the left precentral and medial frontal gyri, and in the right medial frontal, postcentral, precentral, and middle frontal gyri. The comparisons between each group and HC showed the extension of frontal metabolic changes from stage 1 to stage 3, with the larger metabolic gap between stages 2 and 3.

Conclusions

Our findings support the hypothesis that in ALS, the propagation of neurodegeneration follows a corticofugal, regional ordered pattern, extending from the motor cortex to posterior and anterior regions.

SUBMITTER: Canosa A

PROVIDER: S-EPMC8041703 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundInflammation of patients joints with severe disease activity of rheumatoid arthritis (RA) has already been visualized and quantified by 2-[18F]fluoro-2-deoxy-D-glucose positron emission computed tomography ([18F] FDG PET/CT), but little is known about the metabolic status and its relationship with clinical and ultrasonography (US) metrology in patients with low/moderate activity or in remission.MethodsClinical assessments [based on 28-joint disease activity score (DAS28-CRP) and Clinical Disease Activity Index (CDAI)], [18F] FDG PET/CT, US and X-ray were performed on 63 RA patients classified into remission or low/moderate or severe disease activity groups. PET/CT was visually and then semi-quantitatively analysed by determining the standardized uptake value (SUV) of positive joints.ResultsOf the 1764 joints, 21.1% were tender only, 13.7% swollen only, 27.6% tender or swollen, 7.3% tender and swollen, 20.5% PET/CT-positive and 8.6% US-positive. PET and US measurements were correlated, albeit with poor concordance. The positive predictive value of PET/CT for clinical evaluation (tender and/or swollen) was low, whereas its negative predictive value was high. Highly significant differences were found with the number of PET/CT-positive joints and with cumulative SUV between "severe" and "non-severe" patients (including those in remission and those with low/moderate activity) and not between those classified as "remission" and "non-remission" or "remission" and "low/moderate activity". Moreover, the correlation between PET/CT measurements and clinical activity was positive only in the CDAI severe disease group. In patients in remission or with low/moderate activity, only 20-30% of joints were PET/CT-negative. In remission, PET/CT and US were positive in different joints, and PET/CT-positive but US-negative joints mainly exhibited RA (38.1%) or normal (49.2%) and not osteoarthritic (12.7%) X-ray patterns.Conclusions[18F] FDG PET/CT was effective at distinguishing patients with severely active disease from other patients. In non-severe RA patients, including those in remission, PET/CT results are discordant from US and clinical observations. A longitudinal analysis is needed to explore the clinical relevance of such infra-clinical disease.

Project description:PurposeThe aim of this multi-center study was to discover and validate radiomics classifiers as image-derived biomarkers for risk stratification of non-small-cell lung cancer (NSCLC).Patients and methodsPre-therapy PET scans from a total of 358 Stage I-III NSCLC patients scheduled for radiotherapy/chemo-radiotherapy acquired between October 2008 and December 2013 were included in this seven-institution study. A semi-automatic threshold method was used to segment the primary tumors. Radiomics predictive classifiers were derived from a training set of 133 scans using TexLAB v2. Least absolute shrinkage and selection operator (LASSO) regression analysis was used for data dimension reduction and radiomics feature vector (FV) discovery. Multivariable analysis was performed to establish the relationship between FV, stage and overall survival (OS). Performance of the optimal FV was tested in an independent validation set of 204 patients, and a further independent set of 21 (TESTI) patients.ResultsOf 358 patients, 249 died within the follow-up period [median 22 (range 0-85) months]. From each primary tumor, 665 three-dimensional radiomics features from each of seven gray levels were extracted. The most predictive feature vector discovered (FVX) was independent of known prognostic factors, such as stage and tumor volume, and of interest to multi-center studies, invariant to the type of PET/CT manufacturer. Using the median cut-off, FVX predicted a 14-month survival difference in the validation cohort (N = 204, p = 0.00465; HR = 1.61, 95% CI 1.16-2.24). In the TESTI cohort, a smaller cohort that presented with unusually poor survival of stage I cancers, FVX correctly indicated a lack of survival difference (N = 21, p = 0.501). In contrast to the radiomics classifier, clinically routine PET variables including SUVmax, SUVmean and SUVpeak lacked any prognostic information.ConclusionPET-based radiomics classifiers derived from routine pre-treatment imaging possess intrinsic prognostic information for risk stratification of NSCLC patients to radiotherapy/chemo-radiotherapy.

Dataset Information

Brain metabolic changes across King's stages in amyotrophic lateral sclerosis: a ¹⁸F-2-fluoro-2-deoxy-D-glucose-positron emission tomography study.

Purpose

Methods

Results

Conclusions

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OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

Brain metabolic changes across King's stages in amyotrophic lateral sclerosis: a 18F-2-fluoro-2-deoxy-D-glucose-positron emission tomography study.

Purpose

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Brain metabolic changes across King's stages in amyotrophic lateral sclerosis: a ¹⁸F-2-fluoro-2-deoxy-D-glucose-positron emission tomography study.