Prostate cancer MRI methodological radiomics score: a EuSoMII radiomics auditing group initiative

被引:1
|
作者
Cavallo, Armando Ugo [1 ]
Stanzione, Arnaldo [2 ]
Ponsiglione, Andrea [2 ]
Trotta, Romina [3 ]
Fanni, Salvatore Claudio [4 ]
Ghezzo, Samuele [5 ]
Vernuccio, Federica [6 ]
Klontzas, Michail E. [7 ,8 ,9 ]
Triantafyllou, Matthaios [7 ,8 ]
Ugga, Lorenzo [2 ]
Kalarakis, Georgios [9 ,10 ]
Cannella, Roberto [6 ]
Cuocolo, Renato [11 ]
机构
[1] Ist Dermopat Immacolata IDI IRCCS, Rome, Italy
[2] Univ Naples Federico II, Dept Adv Biomed Sci, Naples, Italy
[3] Hosp Fatima, Dept Cardiol, Seville, Spain
[4] Univ Pisa, Dept Translat Res, Acad Radiol, Pisa, Italy
[5] Univ Vita Salute San Raffaele, Milan, Italy
[6] Univ Palermo, Dept Biomed Neurosci & Adv Diagnost BiND, Sect Radiol, Palermo, Italy
[7] Univ Crete, Sch Med, Dept Radiol, Iraklion, Greece
[8] Univ Hosp Heraklion, Dept Med Imaging, Iraklion, Greece
[9] Karolinska Inst, Dept Clin Sci Intervent & Technol CLINTEC, Div Radiol, Stockholm, Sweden
[10] Karolinska Univ Hosp, Dept Neuroradiol, Stockholm, Sweden
[11] Univ Salerno, Dept Med Surg & Dent, Baronissi, Italy
关键词
Prostate; Radiomics; Magnetic resonance imaging; Systematic review;
D O I
10.1007/s00330-024-11299-x
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectivesTo evaluate the quality of radiomics research in prostate MRI for the evaluation of prostate cancer (PCa) through the assessment of METhodological RadiomICs (METRICS) score, a new scoring tool recently introduced with the goal of fostering further improvement in radiomics and machine learning methodology.Materials and methodsA literature search was conducted from July 1st, 2019, to November 30th, 2023, to identify original investigations assessing MRI-based radiomics in the setting of PCa. Seven readers with varying expertise underwent a quality assessment using METRICS. Subgroup analyses were performed to assess whether the quality score varied according to papers' categories (diagnosis, staging, prognosis, technical) and quality ratings among these latter.ResultsFrom a total of 1106 records, 185 manuscripts were available. Overall, the average METRICS total score was 52% +/- 16%. ANOVA and chi-square tests revealed no statistically significant differences between subgroups. Items with the lowest positive scores were adherence to guidelines/checklists (4.9%), handling of confounding factors (14.1%), external testing (15.1%), and the availability of data (15.7%), code (4.3%), and models (1.6%). Conversely, most studies clearly defined patient selection criteria (86.5%), employed a high-quality reference standard (89.2%), and utilized a well-described (85.9%) and clinically applicable (87%) imaging protocol as a radiomics data source.ConclusionThe quality of MRI-based radiomics research for PCa in recent studies demonstrated good homogeneity and overall moderate quality.Key PointsQuestionTo evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score.FindingsThe average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups.Clinical relevanceEnhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.Key PointsQuestionTo evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score.FindingsThe average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups.Clinical relevanceEnhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.Key PointsQuestionTo evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score.FindingsThe average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups.Clinical relevanceEnhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.
引用
收藏
页码:1157 / 1165
页数:9
相关论文
共 50 条
  • [1] Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative
    Spadarella, Gaia
    Stanzione, Arnaldo
    D'Antonoli, Tugba Akinci
    Andreychenko, Anna
    Fanni, Salvatore Claudio
    Ugga, Lorenzo
    Kotter, Elmar
    Cuocolo, Renato
    EUROPEAN RADIOLOGY, 2023, 33 (03) : 1884 - 1894
  • [2] Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative
    Gaia Spadarella
    Arnaldo Stanzione
    Tugba Akinci D’Antonoli
    Anna Andreychenko
    Salvatore Claudio Fanni
    Lorenzo Ugga
    Elmar Kotter
    Renato Cuocolo
    European Radiology, 2023, 33 : 1884 - 1894
  • [3] Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative
    Cannella, Roberto
    Vernuccio, Federica
    Klontzas, Michail E.
    Ponsiglione, Andrea
    Petrash, Ekaterina
    Ugga, Lorenzo
    dos Santos, Daniel Pinto
    Cuocolo, Renato
    INSIGHTS INTO IMAGING, 2023, 14 (01)
  • [4] Ovarian imaging radiomics quality score assessment: an EuSoMII radiomics auditing group initiative
    Ponsiglione, Andrea
    Stanzione, Arnaldo
    Spadarella, Gaia
    Baran, Agah
    Cappellini, Luca Alessandro
    Lipman, Kevin Groot
    Van Ooijen, Peter
    Cuocolo, Renato
    EUROPEAN RADIOLOGY, 2023, 33 (03) : 2239 - 2247
  • [5] Ovarian imaging radiomics quality score assessment: an EuSoMII radiomics auditing group initiative
    Andrea Ponsiglione
    Arnaldo Stanzione
    Gaia Spadarella
    Agah Baran
    Luca Alessandro Cappellini
    Kevin Groot Lipman
    Peter Van Ooijen
    Renato Cuocolo
    European Radiology, 2023, 33 : 2239 - 2247
  • [6] Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative
    Roberto Cannella
    Federica Vernuccio
    Michail E. Klontzas
    Andrea Ponsiglione
    Ekaterina Petrash
    Lorenzo Ugga
    Daniel Pinto dos Santos
    Renato Cuocolo
    Insights into Imaging, 14
  • [7] METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
    Kocak, Burak
    Akinci D'Antonoli, Tugba
    Mercaldo, Nathaniel
    Alberich-Bayarri, Angel
    Baessler, Bettina
    Ambrosini, Ilaria
    Andreychenko, Anna E.
    Bakas, Spyridon
    Beets-Tan, Regina G. H.
    Bressem, Keno
    Buvat, Irene
    Cannella, Roberto
    Cappellini, Luca Alessandro
    Cavallo, Armando Ugo
    Chepelev, Leonid L.
    Chu, Linda Chi Hang
    Demircioglu, Aydin
    deSouza, Nandita M.
    Dietzel, Matthias
    Fanni, Salvatore Claudio
    Fedorov, Andrey
    Fournier, Laure S.
    Giannini, Valentina
    Girometti, Rossano
    Groot Lipman, Kevin B. W.
    Kalarakis, Georgios
    Kelly, Brendan S.
    Klontzas, Michail E.
    Koh, Dow-Mu
    Kotter, Elmar
    Lee, Ho Yun
    Maas, Mario
    Marti-Bonmati, Luis
    Muller, Henning
    Obuchowski, Nancy
    Orlhac, Fanny
    Papanikolaou, Nikolaos
    Petrash, Ekaterina
    Pfaehler, Elisabeth
    Pinto dos Santos, Daniel
    Ponsiglione, Andrea
    Sabater, Sebastia
    Sardanelli, Francesco
    Seeboeck, Philipp
    Sijtsema, Nanna M.
    Stanzione, Arnaldo
    Traverso, Alberto
    Ugga, Lorenzo
    Vallieres, Martin
    van Dijk, Lisanne V.
    INSIGHTS INTO IMAGING, 2024, 15 (01)
  • [8] METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
    Burak Kocak
    Tugba Akinci D’Antonoli
    Nathaniel Mercaldo
    Angel Alberich-Bayarri
    Bettina Baessler
    Ilaria Ambrosini
    Anna E. Andreychenko
    Spyridon Bakas
    Regina G. H. Beets-Tan
    Keno Bressem
    Irene Buvat
    Roberto Cannella
    Luca Alessandro Cappellini
    Armando Ugo Cavallo
    Leonid L. Chepelev
    Linda Chi Hang Chu
    Aydin Demircioglu
    Nandita M. deSouza
    Matthias Dietzel
    Salvatore Claudio Fanni
    Andrey Fedorov
    Laure S. Fournier
    Valentina Giannini
    Rossano Girometti
    Kevin B. W. Groot Lipman
    Georgios Kalarakis
    Brendan S. Kelly
    Michail E. Klontzas
    Dow-Mu Koh
    Elmar Kotter
    Ho Yun Lee
    Mario Maas
    Luis Marti-Bonmati
    Henning Müller
    Nancy Obuchowski
    Fanny Orlhac
    Nikolaos Papanikolaou
    Ekaterina Petrash
    Elisabeth Pfaehler
    Daniel Pinto dos Santos
    Andrea Ponsiglione
    Sebastià Sabater
    Francesco Sardanelli
    Philipp Seeböck
    Nanna M. Sijtsema
    Arnaldo Stanzione
    Alberto Traverso
    Lorenzo Ugga
    Martin Vallières
    Lisanne V. van Dijk
    Insights into Imaging, 15
  • [9] Explanation and Elaboration with Examples for CLEAR (CLEAR-E3): an EuSoMII Radiomics Auditing Group Initiative
    Kocak, Burak
    Borgheresi, Alessandra
    Ponsiglione, Andrea
    Andreychenko, Anna E.
    Cavallo, Armando Ugo
    Stanzione, Arnaldo
    Doniselli, Fabio M.
    Vernuccio, Federica
    Triantafyllou, Matthaios
    Cannella, Roberto
    Trotta, Romina
    Ghezzo, Samuele
    D'Antonoli, Tugba Akinci
    Cuocolo, Renato
    EUROPEAN RADIOLOGY EXPERIMENTAL, 2024, 8 (01)
  • [10] Role of MRI radiomics analysis and Pi-RADS score in prostate cancer
    Angrisani, A.
    D'Alessandro, L.
    Grassi, R.
    Nardone, V.
    D'Ippolito, E.
    Guida, C.
    Reginelli, A.
    Cappabianca, S.
    RADIOTHERAPY AND ONCOLOGY, 2022, 170 : S1201 - S1201