Literature DB >> 30637607

An inter-centre statistical scale standardisation for quantitatively evaluating prostate tissue on T2-weighted MRI.

Neda Gholizadeh1, Todsaporn Fuangrod2, Peter B Greer3,4, Peter Lau5,6, Saadallah Ramadan7,5, John Simpson3,4.   

Abstract

Magnetic resonance images (MRI) require intensity standardisation if they are used for the purpose of quantitative analysis as inherent variations in image intensity levels between different image sets are manifest due to technical factors. One approach is to standardise the image intensity values using a statistically applied biological reference tissue. The aim of this study is to compare the performance of differing candidate biological reference tissues for standardising T2WI intensity distributions. Fifty-one prostate cancer patients across two centres with different scanners were evaluated using the percentage interpatient coefficient of variation (%interCV) for four different biological references; femoral bone marrow, ischioanal fossa, obturator-internus muscle and bladder urine. The tissue with the highest reproducibility (lowest %interCV) in both centres was used for intensity standardisation of prostate T2WI using three different statistical measures (mean, Z-score, median + Interquartile Range). The performance of different standardisation methods was evaluated from the assessment of image intensity histograms and the percentage normalised root mean square error (%NRSME) of the healthy peripheral zone tissue. Ischioanal fossa as a reference tissue demonstrated the highest reproducibility with %interCV of 18.9 for centre1 and 11.2 for centre2. Using ischioanal fossa for statistical intensity standardisation and the median + Interquartile Range method demonstrated the lowest %NRMSE across centres for healthy peripheral zone tissues. This study demonstrates ischioanal fossa as a preferred reference tissue for standardising intensity values from T2WI of the prostate. Subsequent image standardisation using the median + Interquartile Range intensity of the reference tissue demonstrated a robust and reliable standardisation method for quantitative image assessment.

Entities:  

Keywords:  CV; MRI; NRMSE; Prostate cancer; Quantitative imaging; Standardisation; T2WI

Mesh:

Year:  2019        PMID: 30637607     DOI: 10.1007/s13246-019-00720-1

Source DB:  PubMed          Journal:  Australas Phys Eng Sci Med        ISSN: 0158-9938            Impact factor:   1.430


  3 in total

1.  A Patient-Specific Autosegmentation Strategy Using Multi-Input Deformable Image Registration for Magnetic Resonance Imaging-Guided Online Adaptive Radiation Therapy: A Feasibility Study.

Authors:  Ying Zhang; Eric Paulson; Sara Lim; William A Hall; Ergun Ahunbay; Nikolai J Mickevicius; Michael W Straza; Beth Erickson; X Allen Li
Journal:  Adv Radiat Oncol       Date:  2020-05-16

2.  Voxel-based supervised machine learning of peripheral zone prostate cancer using noncontrast multiparametric MRI.

Authors:  Neda Gholizadeh; John Simpson; Saadallah Ramadan; Jim Denham; Peter Lau; Sabbir Siddique; Jason Dowling; James Welsh; Stephan Chalup; Peter B Greer
Journal:  J Appl Clin Med Phys       Date:  2020-08-08       Impact factor: 2.102

3.  Motor and higher-order functions topography of the human dentate nuclei identified with tractography and clustering methods.

Authors:  Fulvia Palesi; Matteo Ferrante; Marta Gaviraghi; Anastasia Misiti; Giovanni Savini; Alessandro Lascialfari; Egidio D'Angelo; Claudia A M Gandini Wheeler-Kingshott
Journal:  Hum Brain Mapp       Date:  2021-06-04       Impact factor: 5.038

  3 in total

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