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Performance of Artificial Intelligence-Aided Diagnosis System for Clinically Significant Prostate Cancer with MRI: A Diagnostic Comparison Study.
Jiang, Ke-Wen; Song, Yang; Hou, Ying; Zhi, Rui; Zhang, Jing; Bao, Mei-Ling; Li, Hai; Yan, Xu; Xi, Wei; Zhang, Cheng-Xiu; Yao, Ye-Feng; Yang, Guang; Zhang, Yu-Dong.
Afiliação
  • Jiang KW; Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Song Y; AI Imaging Lab, Medical Imaging College, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Hou Y; Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, People's Republic of China.
  • Zhi R; Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Zhang J; AI Imaging Lab, Medical Imaging College, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Bao ML; Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Li H; AI Imaging Lab, Medical Imaging College, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Yan X; Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Xi W; AI Imaging Lab, Medical Imaging College, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Zhang CX; Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Yao YF; Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.
  • Yang G; MR Scientific Marketing, Siemens Healthcare, Shanghai, People's Republic of China.
  • Zhang YD; Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, People's Republic of China.
J Magn Reson Imaging ; 57(5): 1352-1364, 2023 05.
Article em En | MEDLINE | ID: mdl-36222324
ABSTRACT

BACKGROUND:

The high level of expertise required for accurate interpretation of prostate MRI.

PURPOSE:

To develop and test an artificial intelligence (AI) system for diagnosis of clinically significant prostate cancer (CsPC) with MRI. STUDY TYPE Retrospective.

SUBJECTS:

One thousand two hundred thirty patients from derivation cohort between Jan 2012 and Oct 2019, and 169 patients from a publicly available data (U-Net 423 for training/validation and 49 for test and TrumpeNet 820 for training/validation and 579 for test). FIELD STRENGTH/SEQUENCE 3.0T/scanners, T2 -weighted imaging (T2 WI), diffusion-weighted imaging, and apparent diffusion coefficient map. ASSESSMENT Close-loop AI system was trained with an Unet for prostate segmentation and a TrumpetNet for CsPC detection. Performance of AI was tested in 410 internal and 169 external sets against 24 radiologists categorizing into junior, general and subspecialist group. Gleason score >6 was identified as CsPC at pathology. STATISTICAL TESTS Area under the receiver operating characteristic curve (AUC-ROC); Delong test; Meta-regression I2 analysis.

RESULTS:

In average, for internal test, AI had lower AUC-ROC than subspecialists (0.85 vs. 0.92, P < 0.05), and was comparable to junior (0.84, P = 0.76) and general group (0.86, P = 0.35). For external test, both AI (0.86) and subspecialist (0.86) had higher AUC than junior (0.80, P < 0.05) and general reader (0.83, P < 0.05). In individual, it revealed moderate diagnostic heterogeneity in 24 readers (Mantel-Haenszel I2  = 56.8%, P < 0.01), and AI outperformed 54.2% (13/24) of readers in summary ROC analysis. In multivariate test, Gleason score, zonal location, PI-RADS score and lesion size significantly impacted the accuracy of AI; while effect of data source, MR device and parameter settings on AI performance is insignificant (P > 0.05). DATA

CONCLUSION:

Our AI system can match and to some case exceed clinicians for the diagnosis of CsPC with prostate MRI. EVIDENCE LEVEL 3 TECHNICAL EFFICACY Stage 2.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans / Male Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans / Male Idioma: En Ano de publicação: 2023 Tipo de documento: Article