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Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping

Institution:
Case Western University School of Medicine, Departments of.
Publisher:
Wolters Kluwer
Publication Date:
Aug-2019
Journal:
Invest Radiol
Volume Number:
54
Issue Number:
8
Pages:
485-93
Citation:
Invest Radiol. 2019 Aug;54(8):485-93.
PubMed ID:
30985480
PMCID:
PMC6602844
Appears in Collections:
SPL, NCIGT
Sponsors:
R01 CA208236/CA/NCI NIH HHS/United States
R01 DK098503/DK/NIDDK NIH HHS/United States
R01 EB016728/EB/NIBIB NIH HHS/United States
R01 EB017219/EB/NIBIB NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
Generated Citation:
Panda A., Lo W.C., Jiang Y., Margevicius S., Schluchter M., Ponsky L.E., Gulani V. Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping. Invest Radiol. 2019 Aug;54(8):485-93. PMID: 30985480. PMCID: PMC6602844.
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OBJECTIVE: This study aims for targeted biopsy validation of magnetic resonance fingerprinting (MRF) and diffusion mapping for characterizing peripheral zone (PZ) prostate cancer and noncancers. MATERIALS AND METHODS: One hundred four PZ lesions in 85 patients who underwent magnetic resonance imaging were retrospectively analyzed with apparent diffusion coefficient (ADC) mapping, MRF, and targeted biopsy (cognitive or in-gantry). A radiologist blinded to pathology drew regions of interest on targeted lesions and visually normal peripheral zone on MRF and ADC maps. Mean T1, T2, and ADC were analyzed using linear mixed models. Generalized estimating equations logistic regression analyses were used to evaluate T1 and T2 relaxometry combined with ADC in differentiating pathologic groups. RESULTS: Targeted biopsy revealed 63 cancers (low-grade cancer/Gleason score 6 = 10, clinically significant cancer/Gleason score ≥7 = 53), 15 prostatitis, and 26 negative biopsies. Prostate cancer T1, T2, and ADC (mean ± SD, 1660 ± 270 milliseconds, 56 ± 20 milliseconds, 0.70 × 10 ± 0.24 × 10 mm/s) were significantly lower than prostatitis (mean ± SD, 1730 ± 350 milliseconds, 77 ± 36 milliseconds, 1.00 × 10 ± 0.30 × 10 mm/s) and negative biopsies (mean ± SD, 1810 ± 250 milliseconds, 71 ± 37 milliseconds, 1.00 × 10 ± 0.33 × 10 mm/s). For cancer versus prostatitis, ADC was sensitive and T2 specific with comparable area under curve (AUC; (AUCT2 = 0.71, AUCADC = 0.79, difference between AUCs not significant P = 0.37). T1 + ADC (AUCT1 + ADC = 0.83) provided the best separation between cancer and negative biopsies. Low-grade cancer T2 and ADC (mean ± SD, 75 ± 29 milliseconds, 0.96 × 10 ± 0.34 × 10 mm/s) were significantly higher than clinically significant cancers (mean ± SD, 52 ± 16 milliseconds, 0.65 ± 0.18 × 10 mm/s), and T2 + ADC (AUCT2 + ADC = 0.91) provided the best separation. CONCLUSIONS: T1 and T2 relaxometry combined with ADC mapping may be useful for quantitative characterization of prostate cancer grades and differentiating cancer from noncancers for PZ lesions seen on T2-weighted images. PMID: 30985480 PMCID: P