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MR-T2-weighted signal intensity: a new imaging biomarker of prostate cancer aggressiveness

MR-T2-weighted signal intensity: a new imaging biomarker of prostate cancer aggressiveness Prostate cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Behaviour of PCa is dichotomous, as patients may either have an indolent clinical course or rapidly progress towards metastatic disease. Unfortunately, biopsy Gleason score (GS) may fail to predict cancer aggressiveness; tumour heterogeneity and inaccurate sampling during biopsy are major causes of underestimation. As a consequence, this frequently results in over-treatment, i.e. low-risk patients overcautiously undergo radical prostatectomy or radiotherapy, frequently with devastating side-effects. Some patients with PCa could be offered a more conservative approach if it were possible to predict patient risk confidently, especially in subjects lying in the grey zone of intermediate risk (i.e. GS = 7), which are in the majority. Recent studies have demonstrated that magnetic resonance (MR) imaging may help improve risk stratification in patients with PCa, providing imaging biomarkers of cancer aggressiveness. The aim of this study is to implement an automatic algorithm pipeline to discriminate different risks of progression from T2-weighted (T2-w) MR imaging. The obtained results confirm that T2-w signal intensity, together with other imaging biomarkers, may represent a new non-invasive approach to assess cancer aggressiveness, potentially helping to plan personalised treatments, and thus dramatically limiting over-diagnosis and over-treatment risks, and reducing the costs for the national healthcare system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Taylor & Francis

MR-T2-weighted signal intensity: a new imaging biomarker of prostate cancer aggressiveness

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References (24)

Publisher
Taylor & Francis
Copyright
© 2014 Informa UK Limited, trading as Taylor & Francis Group
ISSN
2168-1171
eISSN
2168-1163
DOI
10.1080/21681163.2014.910476
Publisher site
See Article on Publisher Site

Abstract

Prostate cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Behaviour of PCa is dichotomous, as patients may either have an indolent clinical course or rapidly progress towards metastatic disease. Unfortunately, biopsy Gleason score (GS) may fail to predict cancer aggressiveness; tumour heterogeneity and inaccurate sampling during biopsy are major causes of underestimation. As a consequence, this frequently results in over-treatment, i.e. low-risk patients overcautiously undergo radical prostatectomy or radiotherapy, frequently with devastating side-effects. Some patients with PCa could be offered a more conservative approach if it were possible to predict patient risk confidently, especially in subjects lying in the grey zone of intermediate risk (i.e. GS = 7), which are in the majority. Recent studies have demonstrated that magnetic resonance (MR) imaging may help improve risk stratification in patients with PCa, providing imaging biomarkers of cancer aggressiveness. The aim of this study is to implement an automatic algorithm pipeline to discriminate different risks of progression from T2-weighted (T2-w) MR imaging. The obtained results confirm that T2-w signal intensity, together with other imaging biomarkers, may represent a new non-invasive approach to assess cancer aggressiveness, potentially helping to plan personalised treatments, and thus dramatically limiting over-diagnosis and over-treatment risks, and reducing the costs for the national healthcare system.

Journal

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization – Taylor & Francis

Published: Jul 3, 2016

Keywords: prostate cancer; endorectal MR imaging; tumour aggressiveness; T2-weighted MR images

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