Deep learning for fully automatic detection, segmentation, and Gleason grade estimation of prostate cancer in multiparametric magnetic resonance images.
Sci Rep
; 12(1): 2975, 2022 02 22.
Article
en En
| MEDLINE
| ID: mdl-35194056
ABSTRACT
Although the emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), analyzing these images remains still complex even for experts. This paper proposes a fully automatic system based on Deep Learning that performs localization, segmentation and Gleason grade group (GGG) estimation of PCa lesions from prostate mpMRIs. It uses 490 mpMRIs for training/validation and 75 for testing from two different datasets ProstateX and Valencian Oncology Institute Foundation. In the test set, it achieves an excellent lesion-level AUC/sensitivity/specificity for the GGG[Formula see text]2 significance criterion of 0.96/1.00/0.79 for the ProstateX dataset, and 0.95/1.00/0.80 for the IVO dataset. At a patient level, the results are 0.87/1.00/0.375 in ProstateX, and 0.91/1.00/0.762 in IVO. Furthermore, on the online ProstateX grand challenge, the model obtained an AUC of 0.85 (0.87 when trained only on the ProstateX data, tying up with the original winner of the challenge). For expert comparison, IVO radiologist's PI-RADS 4 sensitivity/specificity were 0.88/0.56 at a lesion level, and 0.85/0.58 at a patient level. The full code for the ProstateX-trained model is openly available at https//github.com/OscarPellicer/prostate_lesion_detection . We hope that this will represent a landmark for future research to use, compare and improve upon.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Próstata
/
Neoplasias de la Próstata
/
Bases de Datos Factuales
/
Aprendizaje Profundo
/
Imágenes de Resonancia Magnética Multiparamétrica
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
/
Male
Idioma:
En
Revista:
Sci Rep
Año:
2022
Tipo del documento:
Article
País de afiliación:
España