Assessment of germinal matrix hemorrhage on head ultrasound with deep learning algorithms.
Pediatr Radiol
; 52(3): 533-538, 2022 Mar.
Article
en En
| MEDLINE
| ID: mdl-35064324
ABSTRACT
BACKGROUND:
Germinal matrix hemorrhage-intraventricular hemorrhage is among the most common intracranial complications in premature infants. Early detection is important to guide clinical management for improved patient prognosis.OBJECTIVE:
The purpose of this study was to assess whether a convolutional neural network (CNN) can be trained via transfer learning to accurately diagnose germinal matrix hemorrhage on head ultrasound. MATERIALS ANDMETHODS:
Over a 10-year period, 400 head ultrasounds performed in patients ages 6 months or younger were reviewed. Key sagittal images at the level of the caudothalamic groove were obtained from 200 patients with germinal matrix hemorrhage and 200 patients without hemorrhage; all images were reviewed by a board-certified pediatric radiologist. One hundred cases were randomly allocated from the total for validation and an additional 100 for testing of a CNN binary classifier. Transfer learning and data augmentation were used to train the model.RESULTS:
The median age of patients was 0 weeks old with a median gestational age of 30 weeks. The final trained CNN model had a receiver operating characteristic area under the curve of 0.92 on the validation set and accuracy of 0.875 on the test set, with 95% confidence intervals of [0.86, 0.98] and [0.81, 0.94], respectively.CONCLUSION:
A CNN trained on a small set of images with data augmentation can detect germinal matrix hemorrhage on head ultrasounds with strong accuracy.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Aprendizaje Profundo
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Screening_studies
Límite:
Humans
/
Infant
/
Newborn
Idioma:
En
Revista:
Pediatr Radiol
Año:
2022
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
ALEMANHA
/
ALEMANIA
/
DE
/
DEUSTCHLAND
/
GERMANY