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Performance of an ultra-fast deep-learning accelerated MRI screening protocol for prostate cancer compared to a standard multiparametric protocol.
Oerther, B; Engel, H; Nedelcu, A; Strecker, R; Benkert, T; Nickel, D; Weiland, E; Mayrhofer, T; Bamberg, F; Benndorf, M; Weiß, J; Wilpert, C.
Afiliação
  • Oerther B; Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany. benedict.oerther@uniklinik-freiburg.de.
  • Engel H; Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.
  • Nedelcu A; Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.
  • Strecker R; MR Application Predevelopment, Siemens Healthineers GmbH, Erlangen, Germany.
  • Benkert T; EMEA Scientific Partnerships, Siemens Healthineers GmbH, Erlangen, Germany.
  • Nickel D; MR Application Predevelopment, Siemens Healthineers GmbH, Erlangen, Germany.
  • Weiland E; MR Application Predevelopment, Siemens Healthineers GmbH, Erlangen, Germany.
  • Mayrhofer T; MR Application Predevelopment, Siemens Healthineers GmbH, Erlangen, Germany.
  • Bamberg F; School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany.
  • Benndorf M; Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Weiß J; Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.
  • Wilpert C; Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.
Eur Radiol ; 2024 May 23.
Article em En | MEDLINE | ID: mdl-38780766
ABSTRACT

OBJECTIVES:

To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa) in comparison to the standard multiparametric (mp) protocol, reducing scan time and maintaining adequate diagnostic performance. MATERIALS AND

METHODS:

This prospective single-center study included consecutive biopsy-naïve patients with suspected PCa between December 2022 and March 2023. A PI-RADSv2.1 conform mpMRI protocol was acquired in a 3 T scanner (scan time 25 min 45 sec). In addition, two deep-learning (DL) accelerated sequences (T2- and diffusion-weighted) were acquired, serving as a screening protocol (scan time 3 min 28 sec). Two readers evaluated image quality and the probability of PCa regarding PI-RADSv2.1 scores in two sessions. The diagnostic performance of the screening protocol with mpMRI serving as the reference standard was derived. Inter- and intra-reader agreements were evaluated using weighted kappa statistics.

RESULTS:

We included 77 patients with 97 lesions (mean age 66 years; SD 7.7). Diagnostic performance of the screening protocol was excellent with a sensitivity and specificity of 100%/100% and 89%/98% (cut-off ≥ PI-RADS 4) for reader 1 (R1) and reader 2 (R2), respectively. Mean image quality was 3.96 (R1) and 4.35 (R2) for the standard protocol vs. 4.74 and 4.57 for the screening protocol (p < 0.05). Inter-reader agreement was moderate (κ 0.55) for the screening protocol and substantial (κ 0.61) for the multiparametric protocol.

CONCLUSION:

The ultra-fast screening protocol showed similar diagnostic performance and better imaging quality compared to the mpMRI in under 15% of scan time, improving efficacy and enabling the implementation of screening protocols in clinical routine. CLINICAL RELEVANCE STATEMENT The ultra-fast protocol enables examinations without contrast administration, drastically reducing scan time to 3.5 min with similar diagnostic performance and better imaging quality. This facilitates patient-friendly, efficient examinations and addresses the conflict of increasing demand for examinations at currently exhausted capacities. KEY POINTS Time-consuming MRI protocols are in conflict with an expected increase in examinations required for prostate cancer screening. An ultra-fast MRI protocol shows similar performance and better image quality compared to the standard protocol. Deep-learning acceleration facilitates efficient and patient-friendly examinations, thus improving prostate cancer screening capacity.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article