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Development and validation of a logistic regression model to distinguish transition zone cancers from benign prostatic hyperplasia on multi-parametric prostate MRI

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Purpose

To develop a prediction model to distinguish between transition zone (TZ) cancers and benign prostatic hyperplasia (BPH) on multi-parametric prostate magnetic resonance imaging (mp-MRI).

Materials and methods

This retrospective study enrolled 60 patients with either BPH or TZ cancer, who had undergone 3 T-MRI. We generated ten parameters for T2-weighted images (T2WI), diffusion-weighted images (DWI) and dynamic MRI. Using a t-test and multivariate logistic regression (LR) analysis to evaluate the parameters’ accuracy, we developed LR models. We calculated the area under the receiver operating characteristic curve (ROC) of LR models by a leave-one-out cross-validation procedure, and the LR model’s performance was compared with radiologists’ performance with their opinion and with the Prostate Imaging Reporting and Data System (Pi-RADS v2) score.

Results

Multivariate LR analysis showed that only standardized T2WI signal and mean apparent diffusion coefficient (ADC) maintained their independent values (P < 0.001). The validation analysis showed that the AUC of the final LR model was comparable to that of board-certified radiologists, and superior to that of Pi-RADS scores.

Conclusion

A standardized T2WI and mean ADC were independent factors for distinguishing between BPH and TZ cancer. The performance of the LR model was comparable to that of experienced radiologists.

Key Points

• It is difficult to diagnose transition zone (TZ) cancer.

• We performed quantitative image analysis in multi-parametric MRI.

• Standardized-T2WI and mean-ADC were independent factors for diagnosing TZ cancer.

• We developed logistic-regression analysis to diagnose TZ cancer accurately.

• The performance of the logistic-regression analysis was higher than PIRADSv2.

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Abbreviations

BPH:

Benign prostatic hyperplasia

PZ:

Peripheral zone

T2WI:

T2-weighted images

TZ:

Transition zone

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Acknowledgements

The scientific guarantor of this publication is Takeshi Nakaura. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Methodology: retrospective, diagnostic or prognostic study, performed at one institution.

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Authors and Affiliations

  1. Department of Diagnostic Radiology, Kumamoto Chuo Hospital, Tainoshima 1-5-1, Kumamoto, Kumamoto, 862-0965, Japan

    Yuji Iyama, Kazuhiro Katahira & Seitaro Oda

  2. Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto, 860-8556, Japan

    Yuji Iyama, Takeshi Nakaura, Yasunori Nagayama, Daisuke Utsunomiya & Yasuyuki Yamashita

  3. Department of Diagnostic Radiology, National Hospital Organization Kumamoto Medical Center, Ninomaru 1-5, Kumamoto, Kumamoto, 860-0008, Japan

    Ayumi Iyama

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  1. Yuji Iyama
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  2. Takeshi Nakaura
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  3. Kazuhiro Katahira
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  4. Ayumi Iyama
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Correspondence to Yuji Iyama.

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Iyama, Y., Nakaura, T., Katahira, K. et al. Development and validation of a logistic regression model to distinguish transition zone cancers from benign prostatic hyperplasia on multi-parametric prostate MRI. Eur Radiol 27, 3600–3608 (2017). https://doi.org/10.1007/s00330-017-4775-2

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  • DOI: https://doi.org/10.1007/s00330-017-4775-2

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