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Research ArticleARTIFICIAL INTELLIGENCE

Evaluating Biases and Quality Issues in Intermodality Image Translation Studies for Neuroradiology: A Systematic Review

Shannon L. Walston, Hiroyuki Tatekawa, Hirotaka Takita, Yukio Miki and Daiju Ueda
American Journal of Neuroradiology April 2024, DOI: https://doi.org/10.3174/ajnr.A8211
Shannon L. Walston
aFrom the Department of Diagnostic and Interventional Radiology (S.L.W., H.Tatekawa, H.Takita, Y.M., D.U.), Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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  • ORCID record for Shannon L. Walston
Hiroyuki Tatekawa
aFrom the Department of Diagnostic and Interventional Radiology (S.L.W., H.Tatekawa, H.Takita, Y.M., D.U.), Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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  • ORCID record for Hiroyuki Tatekawa
Hirotaka Takita
aFrom the Department of Diagnostic and Interventional Radiology (S.L.W., H.Tatekawa, H.Takita, Y.M., D.U.), Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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  • ORCID record for Hirotaka Takita
Yukio Miki
aFrom the Department of Diagnostic and Interventional Radiology (S.L.W., H.Tatekawa, H.Takita, Y.M., D.U.), Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
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Daiju Ueda
aFrom the Department of Diagnostic and Interventional Radiology (S.L.W., H.Tatekawa, H.Takita, Y.M., D.U.), Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan
bSmart Life Science Lab (D.U.), Center for Health Science Innovation, Osaka Metropolitan University, Osaka, Japan
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  • FIG 1.
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    FIG 1.

    PRISMA flow chart.

  • FIG 2.
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    FIG 2.

    CLAIM evaluation. Each vertical bar shows the adherence for all studies for one of the CLAIM criteria. Within each bar, green represents the percentage of studies appropriately adhering to the CLAIM criteria, gray represents studies for which that question was not applicable, and orange represents studies that did not adhere to that CLAIM criteria. A, Overall adherence for 102 studies. B, Adherence for medically-focused studies (n = 64). C, Adherence for engineering-focused studies (n = 38). NA indicates not applicable.

  • FIG 3.
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    FIG 3.

    Bias evaluation. Each horizontal bar shows the risk of bias for all studies for one of the PROBAST criteria. Within each bar, green represents the percentage of studies with a low risk of bias and gray represents studies for which there was an unclear risk of bias, and orange represents studies with a high risk of bias for the question. Question 1.1 asks if the data source matched the target population. Question 1.2 asks if the inclusion and exclusion criteria were appropriate. Question 4.1 asks if the test data set was appropriately sized. Question 4.8 asks if the model was tested on an external data set to account for overfitting or optimism in the model. A, Overall adherence per question for all 102 studies. B, Adherence for engineering-focused studies (n = 38). C, Adherence for medically-focused studies (n = 64).

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    Table 1:

    Included studies

    Number of StudiesAverage CLAIM AdherenceAverage PROBAST Score
    Image-generation direction
     MR imaging-CT6371%38%
     MR imaging-PET1374%49%
     CT-MR imaging1263%41%
     PET-CT367%33%
     PET-MR274%56%
     MR imaging-x-ray164%31%
     US-MR imaging167%31%
     Bidirectional765%33%
    Total10270%39%
    • Note:—US indicates ultrasound.

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    Table 2:

    CLAIM adherence results

    Medically-FocusedEngineering-FocusedP Value
    Title/abstract99%95%.0652
    Introduction100%100%1
    Methods72%63%<.001
    Results53%39%.0046
    Discussion73%59%.0629
    Other90%85%.2023
    Total73%65%<.001
    • View popup
    Table 3:

    Bias risk results

    LowUnclearHigh
    All studies
     Question 1.197 (95%)2 (2%)3 (3%)
     Question 1.223 (23%)79 (77%)0 (0%)
     Question 4.19 (9%)10 (10%)83 (81%)
     Question 4.89 (9%)0 (0%)93 (91%)
     Overall bias4 (4%)4 (4%)94 (92%)
    Medically-focused adherence
     Question 1.164 (100%)0 (0%)0 (0%)
     Question 1.218 (28%)46 (72%)0 (0%)
     Question 4.17 (11%)3 (5%)54 (84%)
     Question 4.88 (13%)0 (0%)56 (88%)
     Overall bias3 (5%)4 (6%)55 (86%)
    Engineering-focused adherence
     Question 1.133 (87%)2 (5%)3 (8%)
     Question 1.25 (13%)33 (87%)0 (0%)
     Question 4.12 (5%)7 (18%)29 (77%)
     Question 4.81 (3%)0 (0%)37 (97%)
     Overall bias1 (3%)0 (0%)37 (97%)
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Shannon L. Walston, Hiroyuki Tatekawa, Hirotaka Takita, Yukio Miki, Daiju Ueda
Evaluating Biases and Quality Issues in Intermodality Image Translation Studies for Neuroradiology: A Systematic Review
American Journal of Neuroradiology Apr 2024, DOI: 10.3174/ajnr.A8211

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Evaluating Biases and Quality Issues in Intermodality Image Translation Studies for Neuroradiology: A Systematic Review
Shannon L. Walston, Hiroyuki Tatekawa, Hirotaka Takita, Yukio Miki, Daiju Ueda
American Journal of Neuroradiology Apr 2024, DOI: 10.3174/ajnr.A8211
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