{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Capitoli G"],"funding":["Regione Lombardia","Italian Association for Cancer Research","Ricerca Finalizzata","Fondazione Gigi &amp; Pupa Ferrari"],"pagination":["4156"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9028391"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(8)"],"pubmed_abstract":["Fine-needle aspiration biopsies (FNA) represent the gold standard to exclude the malignant nature of thyroid nodules. After cytomorphology, 20-30% of cases are deemed \"indeterminate for malignancy\" and undergo surgery. However, after thyroidectomy, 70-80% of these nodules are benign. The identification of tools for improving FNA's diagnostic performances is explored by matrix-assisted laser-desorption ionization mass spectrometry imaging (MALDI-MSI). A clinical study was conducted in order to build a classification model for the characterization of thyroid nodules on a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/malignant cells. The model had optimal performances in the internal validation set (<i>n</i> = 70), with 100.0% (95% CI = 83.2-100.0%) sensitivity and 96.0% (95% CI = 86.3-99.5%) specificity. The external validation (<i>n</i> = 170) showed a specificity of 82.9% (95% CI = 74.3-89.5%) and a sensitivity of 43.1% (95% CI = 30.9-56.0%). The performance of the model was hampered in the presence of poor and/or noisy spectra. Consequently, restricting the evaluation to the subset of FNAs with adequate cellularity, sensitivity improved up to 76.5% (95% CI = 58.8-89.3). Results also suggest the putative role of MALDI-MSI in routine clinical triage, with a three levels diagnostic classification that accounts for an indeterminate gray zone of nodules requiring a strict follow-up."],"journal":["International journal of molecular sciences"],"pubmed_title":["Cytomolecular Classification of Thyroid Nodules Using Fine-Needle Washes Aspiration Biopsies."],"pmcid":["PMC9028391"],"funding_grant_id":["Fondazione Gigi &amp; Pupa Ferrari 2021","Programma degli interventi per la ripresa economica: sviluppo di nuovi accordi di collaborazione con le università per la ricerca, l'innovazione e il trasferimento tecnologico: NephropaThy","Call HUB Ricerca ed Innovazione: ImmunHUB","MFAG grant 2016- Id. 18445","POR FESR 2014-2020","GR-2019-12368592"],"pubmed_authors":["Magni F","Pagni F","Clerici F","Galimberti S","Garancini M","Piga I","Leni D","Casati G","L'Imperio V","Capitoli G"],"additional_accession":[]},"is_claimable":false,"name":"Cytomolecular Classification of Thyroid Nodules Using Fine-Needle Washes Aspiration Biopsies.","description":"Fine-needle aspiration biopsies (FNA) represent the gold standard to exclude the malignant nature of thyroid nodules. After cytomorphology, 20-30% of cases are deemed \"indeterminate for malignancy\" and undergo surgery. However, after thyroidectomy, 70-80% of these nodules are benign. The identification of tools for improving FNA's diagnostic performances is explored by matrix-assisted laser-desorption ionization mass spectrometry imaging (MALDI-MSI). A clinical study was conducted in order to build a classification model for the characterization of thyroid nodules on a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/malignant cells. The model had optimal performances in the internal validation set (<i>n</i> = 70), with 100.0% (95% CI = 83.2-100.0%) sensitivity and 96.0% (95% CI = 86.3-99.5%) specificity. The external validation (<i>n</i> = 170) showed a specificity of 82.9% (95% CI = 74.3-89.5%) and a sensitivity of 43.1% (95% CI = 30.9-56.0%). The performance of the model was hampered in the presence of poor and/or noisy spectra. Consequently, restricting the evaluation to the subset of FNAs with adequate cellularity, sensitivity improved up to 76.5% (95% CI = 58.8-89.3). Results also suggest the putative role of MALDI-MSI in routine clinical triage, with a three levels diagnostic classification that accounts for an indeterminate gray zone of nodules requiring a strict follow-up.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Apr","modification":"2025-04-06T19:49:35.229Z","creation":"2025-04-06T19:49:35.229Z"},"accession":"S-EPMC9028391","cross_references":{"pubmed":["35456973"],"doi":["10.3390/ijms23084156"]}}