Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model.
J Cutan Pathol
; 48(12): 1455-1462, 2021 Dec.
Article
em En
| MEDLINE
| ID: mdl-34151458
ABSTRACT
BACKGROUND:
The definitive diagnosis of melanocytic neoplasia using solely histopathologic evaluation can be challenging. Novel techniques that objectively confirm diagnoses are needed. This study details the development and validation of a melanoma prediction model from spatially resolved multivariate protein expression profiles generated by imaging mass spectrometry (IMS).METHODS:
Three board-certified dermatopathologists blindly evaluated 333 samples. Samples with triply concordant diagnoses were included in this study, divided into a training set (n = 241) and a test set (n = 92). Both the training and test sets included various representative subclasses of unambiguous nevi and melanomas. A prediction model was developed from the training set using a linear support vector machine classification model.RESULTS:
We validated the prediction model on the independent test set of 92 specimens (75 classified correctly, 2 misclassified, and 15 indeterminate). IMS detects melanoma with a sensitivity of 97.6% and a specificity of 96.4% when evaluating each unique spot. IMS predicts melanoma at the sample level with a sensitivity of 97.3% and a specificity of 97.5%. Indeterminate results were excluded from sensitivity and specificity calculations.CONCLUSION:
This study provides evidence that IMS-based proteomics results are highly concordant to diagnostic results obtained by careful histopathologic evaluation from a panel of expert dermatopathologists.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias Cutâneas
/
Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz
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Melanoma
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article