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Magnetic Resonance Materials in Physics, Biology and Medicine

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Open Access 01-04-2021 | Prostate Cancer | Research Article

Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition

Authors: Mohammed R. S. Sunoqrot, Gabriel A. Nketiah, Kirsten M. Selnæs, Tone F. Bathen, Mattijs Elschot

Published in: Magnetic Resonance Materials in Physics, Biology and Medicine | Issue 2/2021

Abstract

Objectives

To develop and evaluate an automated method for prostate T2-weighted (T2W) image normalization using dual-reference (fat and muscle) tissue.

Materials and methods

Transverse T2W images from the publicly available PROMISE12 (N = 80) and PROSTATEx (N = 202) challenge datasets, and an in-house collected dataset (N = 60) were used. Aggregate channel features object detectors were trained to detect reference fat and muscle tissue regions, which were processed and utilized to normalize the 3D images by linear scaling. Mean prostate pseudo T2 values after normalization were compared to literature values. Inter-patient histogram intersections of voxel intensities in the prostate were compared between our approach, the original images, and other commonly used normalization methods. Healthy vs. malignant tissue classification performance was compared before and after normalization.

Results

The prostate pseudo T2 values of the three tested datasets (mean ± standard deviation = 78.49 ± 9.42, 79.69 ± 6.34 and 79.29 ± 6.30 ms) corresponded well to T2 values from literature (80 ± 34 ms). Our normalization approach resulted in significantly higher (p < 0.001) inter-patient histogram intersections (median = 0.746) than the original images (median = 0.417) and most other normalization methods. Healthy vs. malignant classification also improved significantly (p < 0.001) in peripheral (AUC 0.826 vs. 0.769) and transition (AUC 0.743 vs. 0.678) zones.

Conclusion

An automated dual-reference tissue normalization of T2W images could help improve the quantitative assessment of prostate cancer.

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Title: Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition
Authors: Mohammed R. S. Sunoqrot
Gabriel A. Nketiah
Kirsten M. Selnæs
Tone F. Bathen
Mattijs Elschot
Publication date: 01-04-2021
Publisher: Springer International Publishing
Keywords: Prostate Cancer
Prostate Cancer
Published in: Magnetic Resonance Materials in Physics, Biology and Medicine / Issue 2/2021
Print ISSN: 0968-5243
Electronic ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-020-00871-3

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition

Abstract

Objectives

Materials and methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Materials and methods

Results

Conclusion

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