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Clinical Research

In vivo prostate cancer detection and grading using restriction spectrum imaging-MRI

Prostate Cancer and Prostatic Diseases volume 19, pages 168–173 (2016)Cite this article

Subjects

Abstract

Background:

Magnetic resonance imaging (MRI) is emerging as a robust, noninvasive method for detecting and characterizing prostate cancer (PCa), but limitations remain in its ability to distinguish cancerous from non-cancerous tissue. We evaluated the performance of a novel MRI technique, restriction spectrum imaging (RSI-MRI), to quantitatively detect and grade PCa compared with current standard-of-care MRI.

Methods:

In a retrospective evaluation of 33 patients with biopsy-proven PCa who underwent RSI-MRI and standard MRI before radical prostatectomy, receiver-operating characteristic (ROC) curves were performed for RSI-MRI and each quantitative MRI term, with area under the ROC curve (AUC) used to compare each term’s ability to differentiate between PCa and normal prostate. Spearman rank-order correlations were performed to assess each term’s ability to predict PCa grade in the radical prostatectomy specimens.

Results:

RSI-MRI demonstrated superior differentiation of PCa from normal tissue, with AUC of 0.94 and 0.85 for RSI-MRI and conventional diffusion MRI, respectively (P=0.04). RSI-MRI also demonstrated superior performance in predicting PCa aggressiveness, with Spearman rank-order correlation coefficients of 0.53 (P=0.002) and −0.42 (P=0.01) for RSI-MRI and conventional diffusion MRI, respectively, with tumor grade.

Conclusions:

RSI-MRI significantly improves upon current noninvasive PCa imaging and may potentially enhance its diagnosis and characterization.

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Acknowledgements

This study was funded by grant R01EB000790; American Cancer Society, Institutional Research Grant Number 70-002; DoD, Prostate Cancer Research Program, Idea Development Award W81XWH-13-1-0391, #PC120532; National Science Foundation, Grant Number 1430082; UCSD Clinician Scientist Program; and General Electric, Investigator-Initiated Research Award BOK92325.

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Author notes

  1. C J Kane and J K Parsons: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, University of California San Diego School of Medicine, San Diego, CA, USA

    K C McCammack, N S White, N M Schenker-Ahmed, J M Kuperman, H Bartsch, R S Desikan, R A Rakow-Penner, R F Mattrey, W G Bradley, A M Dale & D S Karow

  2. Department of Urology, University of California San Diego School of Medicine, San Diego, CA, USA

    C J Kane & J K Parsons

  3. Department of Pathology, University of California San Diego School of Medicine, San Diego, CA, USA

    D Adams & A Shabaik

  4. Department of Urology, University of Texas San Antonio School of Medicine, San Antonio, TX, USA

    M A Liss

  5. Department of Radiology, University of California Los Angeles Geffen School of Medicine, Los Angeles, CA, USA

    D J A Margolis & S S Raman

  6. Department of Neurosciences, University of California San Diego School of Medicine, San Diego, CA, USA

    A M Dale

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  1. K C McCammack
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Corresponding author

Correspondence to D S Karow.

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McCammack, K., Kane, C., Parsons, J. et al. In vivo prostate cancer detection and grading using restriction spectrum imaging-MRI. Prostate Cancer Prostatic Dis 19, 168–173 (2016). https://doi.org/10.1038/pcan.2015.61

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