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Deep Learning-Based T2-weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates

Lin, Yue ; Belue, Mason J ; Yilmaz, Enis C ; Harmon, Stephanie A ; An, Julie ; Law, Yan Mee ; Hazen, Lindsey ; Garcia, Charisse ; Merriman, Katie M ; Phelps, Tim E ; Lay, Nathan S ; Toubaji, Antoun ; Merino, Maria J ; Wood, Bradford J ; Gurram, Sandeep ; Choyke, Peter L ; Pinto, Peter A ; Turkbey, Baris

Journal of magnetic resonance imaging, 2023-10 [Periódico revisado por pares]

United States

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  • Título:
    Deep Learning-Based T2-weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates
  • Autor: Lin, Yue ; Belue, Mason J ; Yilmaz, Enis C ; Harmon, Stephanie A ; An, Julie ; Law, Yan Mee ; Hazen, Lindsey ; Garcia, Charisse ; Merriman, Katie M ; Phelps, Tim E ; Lay, Nathan S ; Toubaji, Antoun ; Merino, Maria J ; Wood, Bradford J ; Gurram, Sandeep ; Choyke, Peter L ; Pinto, Peter A ; Turkbey, Baris
  • É parte de: Journal of magnetic resonance imaging, 2023-10
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: Image quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis. To examine the impact of image quality on prostate cancer detection using an in-house previously developed artificial intelligence (AI) algorithm. Retrospective. 615 consecutive patients (median age 67 [interquartile range [IQR]: 61-71] years) with elevated serum PSA (median PSA 6.6 [IQR: 4.6-9.8] ng/mL) prior to prostate biopsy. 3.0T/T2-weighted turbo-spin-echo MRI, high b-value echo-planar diffusion-weighted imaging, and gradient recalled echo dynamic contrast-enhanced. Scans were prospectively evaluated during clinical readout using PI-RADSv2.1 by one genitourinary radiologist with 17 years of experience. For each patient, T2-weighted images (T2WIs) were classified as high-quality or low-quality based on evaluation of both general distortions (eg, motion, distortion, noise, and aliasing) and perceptual distortions (eg, obscured delineation of prostatic capsule, prostatic zones, and excess rectal gas) by a previously developed in-house AI algorithm. Patients with PI-RADS category 1 underwent 12-core ultrasound-guided systematic biopsy while those with PI-RADS category 2-5 underwent combined systematic and targeted biopsies. Patient-level cancer detection rates (CDRs) were calculated for clinically significant prostate cancer (csPCa, International Society of Urological Pathology Grade Group ≥2) by each biopsy method and compared between high- and low-quality images in each PI-RADS category. Fisher's exact test. Bootstrap 95% confidence intervals (CI). A P value <0.05 was considered statistically significant. 385 (63%) T2WIs were classified as high-quality and 230 (37%) as low-quality by AI. Targeted biopsy with high-quality T2WIs resulted in significantly higher clinically significant CDR than low-quality images for PI-RADS category 4 lesions (52% [95% CI: 43-61] vs. 32% [95% CI: 22-42]). For combined biopsy, there was no significant difference in patient-level CDRs for PI-RADS 4 between high- and low-quality T2WIs (56% [95% CI: 47-64] vs. 44% [95% CI: 34-55]; P = 0.09). Higher quality T2WIs were associated with better targeted biopsy clinically significant cancer detection performance for PI-RADS 4 lesions. Combined biopsy might be needed when T2WI is lower quality. 2 TECHNICAL EFFICACY: Stage 1.
  • Editor: United States
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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