Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer




Julkaisun tekijät: Perez IM, Merisaari H, Jambor I, Ettala O, Taimen P, Knaapila J, Kekki H, Khan FL, Syrjälä E, Steiner A, Syvänen KT, Verho J, Seppänen M, Rannikko A, Riikonen J, Mirtti T, Lamminen T, Saunavaara J, Falagario U, Martini A, Pahikkala T, Pettersson K, Boström PJ, Aronen HJ

Kustantaja: WILEY

Julkaisuvuosi: 2021

Journal: Journal of Magnetic Resonance Imaging

Tietokannassa oleva lehden nimi: JOURNAL OF MAGNETIC RESONANCE IMAGING

Lehden akronyymi: J MAGN RESON IMAGING

Sivujen määrä: 13

ISSN: 1053-1807

eISSN: 1522-2586

DOI: http://dx.doi.org/10.1002/jmri.27811

Rinnakkaistallenteen osoite: http://research.utu.fi/converis/portal/detail/Publication/66523683


Tiivistelmä

Background: Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group >= 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI).

Purpose: To develop and validate radiomics and kallikrein models for the detection of csPCa. Study Type Retrospective.

Population: A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated.

Field strength/Sequence: A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI.

Assessment: In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores.

Statistical Tests: For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant.

Results: The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488). Data Conclusion The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains.

Level of Evidence: 1

Technical Efficacy: Stage 2


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Last updated on 2021-15-09 at 12:08