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International Journal of Computer Assisted Radiology and Surgery

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01-06-2016 | Original Article

Detection of prostate cancer using temporal sequences of ultrasound data: a large clinical feasibility study

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 6/2016

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Abstract

Purpose

This paper presents the results of a large study involving fusion prostate biopsies to demonstrate that temporal ultrasound can be used to accurately classify tissue labels identified in multi-parametric magnetic resonance imaging (mp-MRI) as suspicious for cancer.

Methods

We use deep learning to analyze temporal ultrasound data obtained from 255 cancer foci identified in mp-MRI. Each target is sampled in axial and sagittal planes. A deep belief network is trained to automatically learn the high-level latent features of temporal ultrasound data. A support vector machine classifier is then applied to differentiate cancerous versus benign tissue, verified by histopathology. Data from 32 targets are used for the training, while the remaining 223 targets are used for testing.

Results

Our results indicate that the distance between the biopsy target and the prostate boundary, and the agreement between axial and sagittal histopathology of each target impact the classification accuracy. In 84 test cores that are 5 mm or farther to the prostate boundary, and have consistent pathology outcomes in axial and sagittal biopsy planes, we achieve an area under the curve of 0.80. In contrast, all of these targets were labeled as moderately suspicious in mp-MR.

Conclusion

Using temporal ultrasound data in a fusion prostate biopsy study, we achieved a high classification accuracy specifically for moderately scored mp-MRI targets. These targets are clinically common and contribute to the high false-positive rates associated with mp-MRI for prostate cancer detection. Temporal ultrasound data combined with mp-MRI have the potential to reduce the number of unnecessary biopsies in fusion biopsy settings.

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Canadian cancer society: http://www.cancer.ca/, and American cancer society: http://www.cancer.org/.

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Title: Detection of prostate cancer using temporal sequences of ultrasound data: a large clinical feasibility study
Publication date: 01-06-2016
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 6/2016
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-016-1395-2

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Abstract

Purpose

Methods

Results

Conclusion

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