TY - JOUR
T1 - Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins
T2 - A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer
AU - Montoya Perez, Ileana
AU - Merisaari, Harri
AU - Jambor, Ivan
AU - Ettala, Otto
AU - Taimen, Pekka
AU - Knaapila, Juha
AU - Kekki, Henna
AU - Khan, Ferdhos L.
AU - Syrjälä, Elise
AU - Steiner, Aida
AU - Syvänen, Kari T.
AU - Verho, Janne
AU - Seppänen, Marjo
AU - Rannikko, Antti
AU - Riikonen, Jarno
AU - Mirtti, Tuomas
AU - Lamminen, Tarja
AU - Saunavaara, Jani
AU - Falagario, Ugo
AU - Martini, Alberto
AU - Pahikkala, Tapio
AU - Pettersson, Kim
AU - Boström, Peter J.
AU - Aronen, Hannu J.
N1 - Funding Information:
This study was financially supported by grants from Instrumentarium Research Foundation, Sigrid Jusélius Foundation, Turku University Hospital, TYKS‐SAPA research fund, Finnish Cancer Society, Finnish Cultural Foundation, and Orion Research Foundation. H.M. was supported by the Cultural Foundation of Finland, and Orion Pharma Research Fellowship. P.T. was supported by a Clinical Researcher Funding from the Academy of Finland.
Publisher Copyright:
© 2021 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC. on behalf of International Society for Magnetic Resonance in Medicine.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - biparametric MRI
KW - diffusion weighted imaging
KW - kallikreins
KW - multi-institutional trial
KW - prostate cancer
KW - prostate cancer screening
KW - PSA
U2 - 10.1002/jmri.27811
DO - 10.1002/jmri.27811
M3 - Article
AN - SCOPUS:85109126299
SN - 1053-1807
VL - 55
JO - Journal of Magnetic Resonance Imaging
JF - Journal of Magnetic Resonance Imaging
IS - 2
ER -