Measured multipoint ultra-high b-value diffusion MRI in the assessment of MRI-detected prostate lesions
Objectives - The aim of this study was to assess quantitative ultra-high b-value (UHB) diffusion magnetic resonance imaging (MRI)-derived parameters in comparison to standard clinical apparent diffusion coefficient (SD-ADC-2b-1000, SD-ADC-2b-1500) for the prediction of clinically significan...
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| Hauptverfasser: | , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
February 2021
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| In: |
Investigative radiology
Year: 2021, Jahrgang: 56, Heft: 2, Pages: 94-102 |
| ISSN: | 1536-0210 |
| DOI: | 10.1097/RLI.0000000000000712 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1097/RLI.0000000000000712 Verlag, lizenzpflichtig, Volltext: https://journals.lww.com/investigativeradiology/Abstract/2021/02000/Measured_Multipoint_Ultra_High_b_Value_Diffusion.4.aspx |
| Verfasserangaben: | Tavakoli, Anoshirwan Andrej MD; Kuder, Tristan Anselm PhD; Tichy, Diana PhD; Radtke, Jan Philipp MD; Görtz, Magdalena MD; Schütz, Viktoria MD; Stenzinger, Albrecht MD; Hohenfellner, Markus MD; Schlemmer, Heinz-Peter MD, PhD; Bonekamp, David MD |
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| 245 | 1 | 0 | |a Measured multipoint ultra-high b-value diffusion MRI in the assessment of MRI-detected prostate lesions |c Tavakoli, Anoshirwan Andrej MD; Kuder, Tristan Anselm PhD; Tichy, Diana PhD; Radtke, Jan Philipp MD; Görtz, Magdalena MD; Schütz, Viktoria MD; Stenzinger, Albrecht MD; Hohenfellner, Markus MD; Schlemmer, Heinz-Peter MD, PhD; Bonekamp, David MD |
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| 520 | |a Objectives - The aim of this study was to assess quantitative ultra-high b-value (UHB) diffusion magnetic resonance imaging (MRI)-derived parameters in comparison to standard clinical apparent diffusion coefficient (SD-ADC-2b-1000, SD-ADC-2b-1500) for the prediction of clinically significant prostate cancer, defined as Gleason Grade Group greater than or equal to 2. - Materials and Methods - Seventy-three patients who underwent 3-T prostate MRI with diffusion-weighted imaging acquired at b = 50/500/1000/1500s/mm2 and b = 100/500/1000/1500/2250/3000/4000 s/mm2 were included. Magnetic resonance lesions were segmented manually on individual sequences, then matched to targeted transrectal ultrasonography/MRI fusion biopsies. Monoexponential 2-point and multipoint fits of standard diffusion and of UHB diffusion were calculated with incremental b-values. Furthermore, a kurtosis fit with parameters Dapp and Kapp with incremental b-values was obtained. Each parameter was examined for prediction of clinically significant prostate cancer using bootstrapped receiver operating characteristics and decision curve analysis. Parameter models were compared using Vuong test. - Results - Fifty of 73 men (age, 66 years [interquartile range, 61-72]; prostate-specific antigen, 6.6 ng/mL [interquartile range, 5-9.7]) had 64 MRI-detected lesions. The performance of SD-ADC-2b-1000 (area under the curve, 0.82) and SD-ADC-2b-1500 (area under the curve, 0.82) was not statistically different (P = 0.99), with SD-ADC-2b-1500 selected as reference. Compared with the reference model, none of the 19 tested logistic regression parameter models including multipoint and 2-point UHB-ADC, Dapp, and Kapp with incremental b-values of up to 4000 s/mm2 outperformed SD-ADC-2b-1500 (all P's > 0.05). Decision curve analysis confirmed these results indicating no higher net benefit for UHB parameters in comparison to SD-ADC-2b-1500 in the clinically important range from 3% to 20% of cancer threshold probability. Net reduction analysis showed no reduction of MR lesions requiring biopsy. - Conclusions - Despite evaluation of a large b-value range and inclusion of 2-point, multipoint, and kurtosis models, none of the parameters provided better predictive performance than standard 2-point ADC measurements using b-values 50/1000 or 50/1500. Our results suggest that most of the diagnostic benefits available in diffusion MRI are already represented in an ADC composed of one low and one 1000 to 1500 s/mm2 b-value. | ||
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