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| Home > Publications database > Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer. > print |
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| 005 | 20240229145643.0 | ||
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| 100 | 1 | _ | |a Tavakoli, Anoshirwan Andrej |0 P:(DE-He78)c6d2d9aa8c2d4ecd0dd6f96d2f40b7c3 |b 0 |e First author |
| 245 | _ | _ | |a Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer. |
| 260 | _ | _ | |a Oak Brook, Ill. |c 2023 |b Soc. |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 500 | _ | _ | |a #EA:E010#LA:E010# / 2023 Jan;306(1):186-199 |
| 520 | _ | _ | |a Background Prostate Imaging Reporting and Data System (PI-RADS) version 2.0 requires multiparametric MRI of the prostate, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging sequences; however, the contribution of DCE imaging remains unclear. Purpose To assess whether DCE imaging in addition to apparent diffusion coefficient (ADC) and normalized T2 values improves PI-RADS version 2.0 for prediction of clinically significant prostate cancer (csPCa). Materials and Methods In this retrospective study, clinically reported PI-RADS lesions in consecutive men who underwent 3-T multiparametric MRI (T2-weighted, DWI, and DCE MRI) from May 2015 to September 2016 were analyzed quantitatively and compared with systematic and targeted MRI-transrectal US fusion biopsy. The normalized T2 signal (nT2), ADC measurement, mean early-phase DCE signal (mDCE), and heuristic DCE parameters were calculated. Logistic regression analysis indicated the most predictive DCE parameters for csPCa (Gleason grade group ≥2). Receiver operating characteristic parameter models were compared using the Obuchowski test. Recursive partitioning analysis determined ADC and mDCE value ranges for combined use with PI-RADS. Results Overall, 260 men (median age, 64 years [IQR, 58-69 years]) with 432 lesions (csPCa [n = 152] and no csPCa [n = 280]) were included. The mDCE parameter was predictive of csPCa when accounting for the ADC and nT2 parameter in the peripheral zone (odds ratio [OR], 1.76; 95% CI: 1.30, 2.44; P = .001) but not the transition zone (OR, 1.17; 95% CI: 0.81, 1.69; P = .41). Recursive partitioning analysis selected an ADC cutoff of 0.897 × 10-3 mm2/sec (P = .04) as a classifier for peripheral zone lesions with a PI-RADS score assessed on the ADC map (hereafter, ADC PI-RADS) of 3. The mDCE parameter did not differentiate ADC PI-RADS 3 lesions (P = .11), but classified lesions with ADC PI-RADS scores greater than 3 with low ADC values (less than 0.903 × 10-3 mm2/sec, P < .001) into groups with csPCa rates of 70% and 97% (P = .008). A lesion size cutoff of 1.5 cm and qualitative DCE parameters were not defined as classifiers according to recursive partitioning (P > .05). Conclusion Quantitative or qualitative dynamic contrast-enhanced MRI was not relevant for Prostate Imaging Reporting and Data System (PI-RADS) 3 lesion risk stratification, while quantitative apparent diffusion coefficient (ADC) values were helpful in upgrading PI-RADS 3 and PI-RADS 4 lesions. Quantitative ADC measurement may be more important for risk stratification than current methods in future versions of PI-RADS. © RSNA, 2022 Online supplemental material is available for this article See also the editorial by Goh in this issue. |
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| 700 | 1 | _ | |a Hielscher, Thomas |b 1 |
| 700 | 1 | _ | |a Badura, Patrick |0 P:(DE-He78)98f3f4d9279b90a4fc6aa36dce929576 |b 2 |
| 700 | 1 | _ | |a Görtz, Magdalena |b 3 |
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| 700 | 1 | _ | |a Hohenfellner, Markus |0 0000-0003-3798-2039 |b 7 |
| 700 | 1 | _ | |a Schlemmer, Heinz-Peter |0 P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec |b 8 |
| 700 | 1 | _ | |a Bonekamp, David |b 9 |e Last author |
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