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Improving reader accuracy and specificity with the addition of hybrid multidimensional-MRI to multiparametric-MRI in diagnosing clinically significant prostate cancers

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Abstract

Purpose

Compare reader performance when adding the Hybrid Multidimensional-MRI (HM-MRI) map to multiparametric MRI (mpMRI+HM-MRI) versus mpMRI alone and inter-reader agreement in diagnosing clinically significant prostate cancers (CSPCa).

Methods

All 61 patients who underwent mpMRI (T2-, diffusion-weighted (DWI), and contrast-enhanced scans) and HM-MRI (with multiple TE/b-value combinations) before prostatectomy or MRI-fused-transrectal ultrasound-guided biopsy between August, 2012 and February, 2020, were retrospectively analyzed. Two experienced readers (R1, R2) and two less-experienced readers (less than 6-year MRI prostate experience) (R3, R4) interpreted mpMRI without/with HM-MRI in the same sitting. Readers recorded the PI-RADS 3-5 score, lesion location, and change in score after adding HM-MRI. Each radiologist’s mpMRI+HM-MRI and mpMRI performance measures (AUC, sensitivity, specificity, PPV, NPV, and accuracy) based on pathology, and Fleiss’ kappa inter-reader agreement was calculated and compared.

Results

Per-sextant R3 and R4 mpMRI+HM-MRI accuracy (82% 81% vs. 77%, 71%; p=.006, <.001) and specificity (89%, 88% vs. 84%, 75%; p=.009, <.001) were higher than with mpMRI. Per-patient R4 mpMRI+HM-MRI specificity improved (48% from 7%; p<.001). R1 and R2 mpMRI+HM-MRI specificity per-sextant (80%, 93% vs. 81%, 93%; p=.51,>.99) and per-patient (37%, 41% vs. 48%, 37%; p=.16, .57) remained similar to mpMRI. R1 and R2 per-patient AUC with mpMRI+HM-MRI (0.63, 0.64 vs. 0.67, 0.61; p=.33, .36) remained similar to mpMRI, but R3 and R4 mpMRI+HM-MRI AUC (0.73, 0.62) approached R1 and R2 AUC. Per-patient inter-reader agreement, mpMRI+HM-MRI Fleiss Kappa, was higher than mpMRI (0.36 [95% CI 0.26, 0.46] vs. 0.17 [95% CI 0.07, 0.27]); p=.009).

Conclusion

Adding HM-MRI to mpMRI (mpMRI+HM-MRI) improved specificity and accuracy for less-experienced readers, improving overall inter-reader agreement.

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Abbreviations

ADC:

Apparent diffusion coefficient

CAD:

Computer-aided diagnosis

CSPCa:

Clinically significant prostate cancer

AUC:

Area under the receiver operating characteristic curve

DCE:

Dynamic contrast enhancement

DWI:

Diffusion-weighted imaging

HM-MRI:

Hybrid multidimensional-MRI

MpMRI:

Multiparametric MRI

PI-RADS:

Prostate Imaging Reporting and Data System

PPV:

Positive predictive value

NPV:

Negative predictive value

PSA:

Prostate-specific antigen

TRUS:

Transrectal US

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Authors and Affiliations

  1. Department of Diagnostic Radiology, University of Chicago, Chicago, Illinois, 60637, USA

    Grace Lee, Aritrick Chatterjee, Carla Harmath, Ibrahim Karademir, Roger Engelmann, Ambereen Yousuf, Salman Islam, Gregory Karczmar & Aytekin Oto

  2. Department of Public Health, University of Chicago, Chicago, Illinois, 60637, USA

    Mihai Giurcanu

  3. Department of Pathology, University of Chicago, Chicago, Illinois, 60637, USA

    Tatjana Antic

  4. Department of Surgery, Section of Urology, University of Chicago, Chicago, Illinois, 60637, USA

    Scott Eggener

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Correspondence to Grace Lee.

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Drs Aytekin Oto, Aritrick Chatterjee, and Gregory Karczmar report equity in QMIS LLC, outside the submitted work.

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Lee, G., Chatterjee, A., Harmath, C. et al. Improving reader accuracy and specificity with the addition of hybrid multidimensional-MRI to multiparametric-MRI in diagnosing clinically significant prostate cancers. Abdom Radiol 48, 3216–3228 (2023). https://doi.org/10.1007/s00261-023-03969-z

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