Best Practice for MRI Diagnostic Accuracy Research With Lessons and Examples from the LI-RADS Individual Participant Data Group

被引：3

作者：

van der Pol, Christian B. ^{[1
,2
,3
]}

Costa, Andreu F. ^{[4
,5
]}

Lam, Eric ^{[6
]}

Dawit, Haben ^{[6
,7
]}

Bashir, Mustafa R. ^{[8
,9
,10
,11
]}

McInnes, Matthew D. F. ^{[6
,12
,13
]}

机构：

[1] McMaster Univ, Dept Diagnost Imaging, Juravinski Hosp & Canc Ctr, Hamilton Hlth Sci, 711 Concess St, Hamilton, ON, Canada

[2] Hamilton Hlth Sci, Juravinski Hosp & Canc Ctr, Dept Diagnost Imaging, Hamilton, ON, Canada

[3] McMaster Univ, Hamilton, ON, Canada

[4] Queen Elizabeth 2 Hlth Sci Ctr, Dept Diagnost Radiol, Halifax, NS, Canada

[5] Dalhousie Univ, Halifax, NS, Canada

[6] Ottawa Hosp Res Inst, Clin Epidemiol Program, Ottawa, ON, Canada

[7] Univ Toronto, Temerty Fac Med, Toronto, ON, Canada

[8] Duke Univ, Med Ctr, Dept Radiol, Durham, NC USA

[9] Duke Univ, Med Ctr, Dept Med, Durham, NC USA

[10] Duke Univ, Med Ctr, Ctr Adv Magnet Resonance Dev, Durham, NC USA

[11] Univ N Carolina, Dept Radiol, Chapel Hill, NC USA

[12] Ottawa Hosp Civ Campus, Dept Radiol, Rm C-159, Ottawa, ON, Canada

[13] Ottawa Hosp Civ Campus, Dept Epidemiol, Rm C-159, Ottawa, ON, Canada

来源：

JOURNAL OF MAGNETIC RESONANCE IMAGING | 2024年 / 60卷 / 01期

关键词：

diagnostic imaging; diagnostic tests; liver; methods; research; research design; routine; HEPATOCELLULAR-CARCINOMA; MAJOR FEATURES; VERSION; 2018; TESTS; BIAS; REVIEWS; TIME;

D O I：

10.1002/jmri.29049

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：

Medical imaging diagnostic test accuracy research is strengthened by adhering to best practices for study design, data collection, data documentation, and study reporting. In this review, key elements of such research are discussed, and specific recommendations provided for optimizing diagnostic accuracy study execution to improve uniformity, minimize common sources of bias and avoid potential pitfalls. Examples are provided regarding study methodology and data collection practices based on insights gained by the liver imaging reporting and data system (LI-RADS) individual participant data group, who have evaluated raw data from numerous MRI diagnostic accuracy studies for risk of bias and data integrity. The goal of this review is to outline strategies for investigators to improve research practices, and to help reviewers and readers better contextualize a study's findings while understanding its limitations.Level of Evidence5Technical EfficacyStage 3

引用

页码：21 / 28

页数：8

共 26 条

[1] Individual Participant Data Meta-Analyses for Diagnostic Accuracy Research: Challenges and Lessons Learned from the LI-RADS IPD Group
Costa, Andreu F.
Mcinnes, Matthew D. F.
Pol, Christian B. van der
Lam, Eric
Dawit, Haben
Salameh, Jean -Paul
Levis, Brooke
Bashir, Mustafa R.
RADIOLOGY-IMAGING CANCER, 2024, 6 (03):
[2] LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis
Dawit, Haben
Lam, Eric
McInnes, Matthew D. F.
van der Pol, Christian B.
Bashir, Mustafa R.
Salameh, Jean -Paul
Levis, Brooke
Sirlin, Claude B.
Chernyak, Victoria
Choi, Sang Hyun
Kim, So Yeon
Fraum, Tyler J.
Tang, An
Jiang, Hanyu
Song, Bin
Wang, Jin
Wilson, Stephanie R.
Kwon, Heejin
Kierans, Andrea S.
Joo, Ijin
Ronot, Maxime
Song, Ji Soo
Podgorska, Joanna
Rosiak, Grzegorz
Kang, Zhen
Allen, Brian C.
Costa, Andreu F.
RADIOLOGY, 2024, 310 (02)
[3] Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis
Goins, Stacy M.
Jiang, Hanyu
van der Pol, Christian B.
Salameh, Jean-Paul
Lam, Eric
Adamo, Robert G.
McInnes, Matthew D. F.
Costa, Andreu F.
Tang, An
Alhasan, Ayman S.
Allen, Brian C.
Reiner, Caecilia S.
Clarke, Christopher
Cerny, Milena
Wang, Jin
Choi, Sang Hyun
Fraum, Tyler J.
Ludwig, Daniel R.
Song, Bin
Joo, Ijin
Kang, Zhen
Kierans, Andrea S.
Kim, So Yeon
Kwon, Heejin
Ronot, Maxime
Podgorska, Joanna
Rosiak, Grzegorz
Song, Ji Soo
Bashir, Mustafa R.
RADIOLOGY, 2023, 309 (03)
[4] Diagnostic accuracy of prospective application of the Liver Imaging Reporting and Data System (LI-RADS) in gadoxetate-enhanced MRI
Kim, Yeun-Yoon
An, Chansik
Kim, Sungwon
Kim, Myeong-Jin
EUROPEAN RADIOLOGY, 2018, 28 (05) : 2038 - 2046
[5] Diagnostic accuracy of prospective application of the Liver Imaging Reporting and Data System (LI-RADS) in gadoxetate-enhanced MRI
Yeun-Yoon Kim
Chansik An
Sungwon Kim
Myeong-Jin Kim
European Radiology, 2018, 28 : 2038 - 2046
[6] Comparative Performance of 2018 LI-RADS versus Modified LIRADS (mLI-RADS): An Individual Participant Data Meta-Analysis
Goins, Stacy M.
Jiang, Hanyu
van der Pol, Christian B.
Salameh, Jean-Paul
Lam, Eric
Adamo, Robert G.
McInnes, Matthew D. F.
Costa, Andreu F.
Clarke, Christopher
Choi, Sang Hyun
Fraum, Tyler J.
Ludwig, Daniel R.
Song, Bin
Joo, Ijin
Kierans, Andrea S.
Kim, So Yeon
Kwon, Heejin
Podgorska, Joanna
Rosiak, Grzegorz
Bashir, Mustafa R.
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2024, 60 (03) : 1082 - 1091
[7] Editorial for "Comparative Performance of 2018 LI-RADS versus Modified LIRADS (mLI-RADS): An Individual Participant Data Meta-Analysis"
Takehara, Yasuo
Hyodo, Ryota
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2024, 60 (03) : 1092 - 1093
[8] Pitfalls and problems to be solved in the diagnostic CT/MRI Liver Imaging Reporting and Data System (LI-RADS)
Kim, Yeun-Yoon
Choi, Jin-Young
Sirlin, Claude B.
An, Chansik
Kim, Myeong-Jin
EUROPEAN RADIOLOGY, 2019, 29 (03) : 1124 - 1132
[9] Pitfalls and problems to be solved in the diagnostic CT/MRI Liver Imaging Reporting and Data System (LI-RADS)
Yeun-Yoon Kim
Jin-Young Choi
Claude B. Sirlin
Chansik An
Myeong-Jin Kim
European Radiology, 2019, 29 : 1124 - 1132
[10] Liver Imaging Reporting and Data System (LI-RADS) v2018: Review of the CT/MRI Diagnostic Categories
Kanmaniraja, Devaraju
Dellacerra, Gary
Holder, Justin
Erlichman, David
Chernyak, Victoria
CANADIAN ASSOCIATION OF RADIOLOGISTS JOURNAL-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES, 2021, 72 (01): : 142 - 149

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