Detection and PI-RADS classification of focal lesions in prostate MRI: Performance comparison between a deep learning-based algorithm (DLA) and radiologists with various levels of experience.
Eur J Radiol
; 142: 109894, 2021 Sep.
Article
em En
| MEDLINE
| ID: mdl-34388625
ABSTRACT
PURPOSE:
To compare the performance of lesion detection and Prostate Imaging-Reporting and Data System (PI-RADS) classification between a deep learning-based algorithm (DLA), clinical reports and radiologists with different levels of experience in prostate MRI.METHODS:
This retrospective study included 121 patients who underwent prebiopsy MRI and prostate biopsy. More than five radiologists (Reader groups 1, 2 residents; Readers 3, 4 less-experienced radiologists; Reader 5 expert) independently reviewed biparametric MRI (bpMRI). The DLA results were obtained using bpMRI. The reference standard was based on pathologic reports. The diagnostic performance of the PI-RADS classification of DLA, clinical reports, and radiologists was analyzed using AUROC. Dichotomous analysis (PI-RADS cutoff value ≥ 3 or 4) was performed, and the sensitivities and specificities were compared using McNemar's test.RESULTS:
Clinically significant cancer [CSC, Gleason score ≥ 7] was confirmed in 43 patients (35.5%). The AUROC of the DLA (0.828) for diagnosing CSC was significantly higher than that of Reader 1 (AUROC, 0.706; p = 0.011), significantly lower than that of Reader 5 (AUROC, 0.914; p = 0.013), and similar to clinical reports and other readers (p = 0.060-0.661). The sensitivity of DLA (76.7%) was comparable to those of all readers and the clinical reports at a PI-RADS cutoff value ≥ 4. The specificity of the DLA (85.9%) was significantly higher than those of clinical reports and Readers 2-3 and comparable to all others at a PI-RADS cutoff value ≥ 4.CONCLUSIONS:
The DLA showed moderate diagnostic performance at a level between those of residents and an expert in detecting and classifying according to PI-RADS. The performance of DLA was similar to that of clinical reports from various radiologists in clinical practice.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Próstata
/
Aprendizado Profundo
Tipo de estudo:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
Limite:
Humans
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Male
Idioma:
En
Revista:
Eur J Radiol
Ano de publicação:
2021
Tipo de documento:
Article