Prostate Cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Behavior 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 overtreatment, i.e. low risk patients that 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 insubject lying in the gray zone of intermediate risk (i.e. GS = 7), which are the majority. Recent studies have demonstrated that Magnetic Resonance Imaging (MRI) may help improving risk stratification in patients with PCa, providing imaging markers of cancer aggressiveness. The aim of this study is to implement an automatic algorithm pipeline to discriminate different risks of progression from T2-weighted (T2w) MRI. The obtained results confirm that T2w signal intensity, together with other imaging markers, may represent a new non-invasive approach to assess cancer aggressiveness, potentially helping to plan personalized treatments, and thus dramatically limiting overdiagnosis and overtreatment risks, and reducing the costs for the National Healthcare System.

MR-T2-weighted signal intensity: A new imaging marker of prostate cancer aggressiveness

Giannini V.;Vignati A.;Russo F.;Regge D.;Mazzetti S.;
2014-01-01

Abstract

Prostate Cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Behavior 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 overtreatment, i.e. low risk patients that 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 insubject lying in the gray zone of intermediate risk (i.e. GS = 7), which are the majority. Recent studies have demonstrated that Magnetic Resonance Imaging (MRI) may help improving risk stratification in patients with PCa, providing imaging markers of cancer aggressiveness. The aim of this study is to implement an automatic algorithm pipeline to discriminate different risks of progression from T2-weighted (T2w) MRI. The obtained results confirm that T2w signal intensity, together with other imaging markers, may represent a new non-invasive approach to assess cancer aggressiveness, potentially helping to plan personalized treatments, and thus dramatically limiting overdiagnosis and overtreatment risks, and reducing the costs for the National Healthcare System.
2014
4th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013
Funchal, Madeira Island, Portugal
14-16 October 2013
Computational Vision and Medical Image Processing IV
CRC Press/Balkema
25
29
Giannini V.; Vignati A.; Mirasole S.; Russo F.; Regge D.; Mazzetti S.; Bracco C.; Stasi M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1888437
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