Role of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography as survival predictor in amyotrophic lateral sclerosis.
Purpose: The identification of prognostic tools in amyotrophic lateral sclerosis (ALS) would improve the design of clinical trials, the management of patients, and life planning. We aimed to evaluate the accuracy of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography (2-[18F]FDG-PET)...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 50; no. 3; pp. 784 - 792 |
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| Autores principales: | , , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=161397712&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161397712 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Feb2023 vid: 50 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 161397712 159894397 10.1007/s00259-022-05987-3 161397712 ppf: 784 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Role of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography as survival predictor in amyotrophic lateral sclerosis. aug: au: Canosa, Antonio Martino, Alessio Manera, Umberto Vasta, Rosario Grassano, Maurizio Palumbo, Francesca Cabras, Sara Di Pede, Francesca Arena, Vincenzo Moglia, Cristina Giuliani, Alessandro Calvo, Andrea Chiò, Adriano Pagani, Marco affil: ALS Centre, "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Via Cherasco 15, 10126, Turin, Italy sug: ab: Purpose: The identification of prognostic tools in amyotrophic lateral sclerosis (ALS) would improve the design of clinical trials, the management of patients, and life planning. We aimed to evaluate the accuracy of brain 2-[18F]fluoro-2-deoxy-D-glucose-positron-emission tomography (2-[18F]FDG-PET) as an independent predictor of survival in ALS. Methods: A prospective cohort study enrolled 418 ALS patients, who underwent brain 2-[18F]FDG-PET at diagnosis and whose survival time was available. We discretized the survival time in a finite number of classes in a data-driven fashion by employing a k-means-like strategy. We identified "hot brain regions" with maximal power in discriminating survival classes, by evaluating the Laplacian scores in a class-aware fashion. We retained the top-m features for each class to train the classification systems (i.e., a support vector machine, SVM), using 10% of the ALS cohort as test set. Results: Data were discretized in three survival profiles: 0–2 years, 2–5 years, and > 5 years. SVM resulted in an error rate < 20% for two out of three classes separately. As for class one, the discriminant clusters included left caudate body and anterior cingulate cortex. The most discriminant regions were bilateral cerebellar pyramid in class two, and right cerebellar dentate nucleus, and left cerebellar nodule in class three. Conclusion: Brain 2-[18F]FDG-PET along with artificial intelligence was able to predict with high accuracy the survival time range in our ALS cohort. Healthcare professionals can benefit from this prognostic tool for planning patients' management and follow-up. 2-[18F]FDG-PET represents a promising biomarker for individual patients' stratification in clinical trials. The lack of a multicentre external validation of the model warrants further studies to evaluate its generalization capability. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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