ArticleScientific reports2017
A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Diffusion-weighted Imaging Distortion in Prostate MRI: A Cross-sectional Study Comparing Supine and Prone Positioning.Investigative radiology · 2026Article
- Anatomical zone and tissue type impacts the repeatability of quantitative MRI parameters and radiomic features for longitudinal monitoring of treatment response in the prostate.Magma (New York, N.Y.) · 2025Article
- Reduced field-of-view and multi-shot DWI acquisition techniques: Prospective evaluation of image quality and distortion reduction in prostate cancer imaging.Magnetic resonance imaging · 2022Article
- Quantifying the effect of biopsy lateral decubitus patient positioning compared to supine prostate magnetic resonance image scanning on prostate translocation and distortion.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2020Article
- Three-dimensional MRI evaluation of the effect of bladder volume on prostate translocation and distortion.Radiology and oncology · 2020Article
- Diffusion kurtosis MRI as a predictive biomarker of response to neoadjuvant chemotherapy in high grade serous ovarian cancer.Scientific reports · 2019Article
- Multiparametric MRI - local staging of prostate cancer and beyond.Radiology and oncology · 2019Review
- Model-based reconstruction framework for correction of signal pile-up and geometric distortions in prostate diffusion MRI.Magnetic resonance in medicine · 2019Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
A computational algorithm was designed to produce a measure of DW image distortion across the prostate. This algorithm was tested and validated on virtual phantoms incorporating known degrees and distributions of distortion. A study was then carried out on DW image volumes from three sets of 10 patients who had been imaged previously. These volumes had been radiologically assessed to have, respectively, 'no distortion' or 'significant distortion' or the potential for 'significant distortion' due to susceptibility effects from hip prostheses. Prostate outlines were drawn on a T2-weighted (T2W) image 'gold-standard' volume and on an ADC image volume derived from DW images acquired over the same region. The algorithm was then applied to these outlines to quantify and map image distortion. The proposed method correctly reproduced known distortion values and distributions in virtual phantoms. It also successfully distinguished between the three groups of patients: mean distortion in 'non-distorted' image volumes, 1.942 ± 0.582 mm; 'distorted', 4.402 ± 1.098 mm; and 'hip patients' 8.083 ± 4.653 mm; P < 0.001. This work has demonstrated and validated a means of quantifying and mapping image distortion in clinical prostate MRI cases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.