scholarly journals Improving non-invasive detection of prostate cancer using diffusion-weighted MRI

2016 ◽  
Vol 2 (6) ◽  
pp. 309
Author(s):  
Michelle Leech ◽  
John Gaffney ◽  
Laure Marignol
Keyword(s):  
Prostate Cancer ◽  
Peripheral Zone ◽  
Diffusion Weighted Mri ◽  
The European Union ◽  
Journal Articles ◽  
Non Invasive ◽  
Search Terms ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
T2 Weighted Images

Prostate cancer represents 11% of all cancers in the European Union and 9% of all cancer deaths. Standard MRI for prostate cancer includes high-resolution T2-weighted images, which allow for the assessment of the prostate and the tumour, as tumours arising from the peripheral zone appear dark compared to the expected normally bright peripheral gland tissue. Over the past number of years, the application of diffusion-weighted MRI (DW-MRI) has progressed to include both diagnostic and prognostic roles in oncology. DW-MRI images should be analysed together with the T2-weighted images and the corresponding apparent diffusion coefficient (ADC) maps. We searched PubMed, Cochrane, and Science Direct for relevant journal articles and reviews published up until April 2015 using the search terms “functional MRI” OR “multiparametric MRI” OR “MRSI” AND “diagnosis” AND “prostate cancer” OR “prostate”. The literature indicates that DW-MRI is an important parameter in the identification of prostate cancer. It has the ability to improve sensitivity and specificity, relative to T2-weighted images alone, and has been demonstrated to correlate with tumour grade.

scholarly journals Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1539 ◽  
Author(s):  
Chris Dulhanty ◽  
Linda Wang ◽  
Maria Cheng ◽  
Hayden Gunraj ◽  
Farzad Khalvati ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
B Value ◽  
Invasive Approach ◽  
Non Invasive ◽  
High B Value ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Critical Regions

Prostate cancer is the most commonly diagnosed cancer in North American men; however, prognosis is relatively good given early diagnosis. This motivates the need for fast and reliable prostate cancer sensing. Diffusion weighted imaging (DWI) has gained traction in recent years as a fast non-invasive approach to cancer sensing. The most commonly used DWI sensing modality currently is apparent diffusion coefficient (ADC) imaging, with the recently introduced computed high-b value diffusion weighted imaging (CHB-DWI) showing considerable promise for cancer sensing. In this study, we investigate the efficacy of ADC and CHB-DWI sensing modalities when applied to zone-level prostate cancer sensing by introducing several radiomics driven zone-level prostate cancer sensing strategies geared around hand-engineered radiomic sequences from DWI sensing (which we term as Zone-X sensing strategies). Furthermore, we also propose Zone-DR, a discovery radiomics approach based on zone-level deep radiomic sequencer discovery that discover radiomic sequences directly for radiomics driven sensing. Experimental results using 12,466 pathology-verified zones obtained through the different DWI sensing modalities of 101 patients showed that: (i) the introduced Zone-X and Zone-DR radiomics driven sensing strategies significantly outperformed the traditional clinical heuristics driven strategy in terms of AUC, (ii) the introduced Zone-DR and Zone-SVM strategies achieved the highest sensitivity and specificity, respectively for ADC amongst the tested radiomics driven strategies, (iii) the introduced Zone-DR and Zone-LR strategies achieved the highest sensitivities for CHB-DWI amongst the tested radiomics driven strategies, and (iv) the introduced Zone-DR, Zone-LR, and Zone-SVM strategies achieved the highest specificities for CHB-DWI amongst the tested radiomics driven strategies. Furthermore, the results showed that the trade-off between sensitivity and specificity can be optimized based on the particular clinical scenario we wish to employ radiomic driven DWI prostate cancer sensing strategies for, such as clinical screening versus surgical planning. Finally, we investigate the critical regions within sensing data that led to a given radiomic sequence generated by a Zone-DR sequencer using an explainability method to get a deeper understanding on the biomarkers important for zone-level cancer sensing.

Non-invasive estimation of prostate cancer aggressiveness using diffusion-weighted MRI and 3D proton MR spectroscopy at 3.0 T

2015 ◽  
Vol 56 (1) ◽  
pp. 121-128 ◽  
Author(s):  
Gregor Thörmer ◽  
Josephin Otto ◽  
Lars-Christian Horn ◽  
Nikita Garnov ◽  
Minh Do ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mr Spectroscopy ◽  
Diffusion Weighted Mri ◽  
Proton Mr Spectroscopy ◽  
Non Invasive ◽  
Diffusion Weighted ◽  
Cancer Aggressiveness ◽  
3.0 T

scholarly journals Non-Invasive Prostate Cancer Characterization with Diffusion-Weighted MRI: Insight from In silico Studies of a Transgenic Mouse Model

2017 ◽  
Vol 7 ◽  
Author(s):  
Deborah K. Hill ◽  
Andreas Heindl ◽  
Konstantinos Zormpas-Petridis ◽  
David J. Collins ◽  
Leslie R. Euceda ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mouse Model ◽  
Transgenic Mouse ◽  
In Silico ◽  
Transgenic Mouse Model ◽  
Diffusion Weighted Mri ◽  
Non Invasive ◽  
Diffusion Weighted ◽  
In Silico Studies

Geometric distortion correction in prostate diffusion‐weighted MRI and its effect on quantitative apparent diffusion coefficient analysis

2017 ◽  
Vol 79 (5) ◽  
pp. 2524-2532 ◽  
Author(s):  
Gabriel Nketiah ◽  
Kirsten M Selnæs ◽  
Elise Sandsmark ◽  
Jose R. Teruel ◽  
Brage Krüger‐Stokke ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Distortion Correction ◽  
Geometric Distortion ◽  
Diffusion Weighted Mri ◽  
Diffusion Weighted ◽  
Apparent Diffusion
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