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Detecting Prostate Cancer Using MRI Data

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Detecting Prostate Cancer Using MRI Data. David Anderson, Bruce Golden, Ed Wasil, Howard Zhang. INFORMS Annual Meeting October, 2013. Prostate Cancer. The NCI estimates that 15% of men born today will be diagnosed with prostate cancer Average costs of $10,000 in the first year after diagnosis

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Detecting Prostate Cancer Using MRI Data

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  1. Detecting Prostate Cancer Using MRI Data David Anderson, Bruce Golden, Ed Wasil, Howard Zhang INFORMS Annual Meeting October, 2013

  2. Prostate Cancer • The NCI estimates that 15% of men born today will be diagnosed with prostate cancer • Average costs of $10,000 in the first year after diagnosis • Hard to diagnose

  3. Prostate Cancer Diagnosis Methods • PSA Test • Non-intrusive • High false positive rate • 67% sensitivity, 58% specificity (Thompson et al. 2005) • Digital Exam • Inconsistent • Biopsy • Painful • Expensive • Possibly severe side effects

  4. MRIs to the Rescue?

  5. Research Question • Can we use MRIs to screen for prostate cancer? • Will doing so be more cost effective than the current system?

  6. Data • 223 slices of prostates from radical prostatectomy patients • 3 types of MRIs on each slice (Dynamic Contrast Enhanced, Diffusion Weighted, and Magnetic Resonance Spectroscopic Imaging) • 119 had cancer (Gleason score of 5 or above)

  7. Independence of Slices • Slices from the same prostate may have similar cancer status and MRI data • Correlation between slices of the same prostate would bias our performance upwards • Correlation in Gleason scores of adjacent slices is 0.30, and for slices two apart it is 0.004

  8. Distribution of Cancer

  9. Three Methods • Logistic Regression • Nearest Neighbors Clustering • Augmented Logistic Regression

  10. Results – Logistic Regression

  11. Results – Nearest Neighbors

  12. Augmented Logistic Regression Results

  13. Augmented Logistic Regression Results The combined model achieves 82% sensitivity and 76% specificity

  14. High Severity Cancer • Many prostate cancers are slow growing • “More men die ‘with’ prostate cancer than ‘from’ it” • Identifying high severity cancer (scores of 7 or 8) is important

  15. High Severity Results

  16. High Severity Results For high severity cancers, the combined model achieves 81% sensitivity and 86% specificity

  17. Cost Effectiveness • Prices for medical services vary widely • Biopsies average ~$2100 • MRIs average ~$700 • If MRIs can reduce the number of biopsies by at least 1/3 they will reduce costs

  18. Conclusions • MRIs can be used to identify prostate cancer • By looking at each slice of a prostate we can identify where to biopsy • MRIs offer possibly better predictive power than PSA tests, and are less invasive than biopsies

  19. Contribution • Combine MRI types • Automated prediction • Distinguish between high and medium severity cancers

  20. Future Work • Collect more data • Healthy patients and cancerous • Build models for whole prostates, not slices • Predict specific Gleason scores

  21. Questions? David.Anderson@Baruch.CUNY.edu

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