Literature DB >> 30543851

Novel distortion correction method for diffusion-weighted imaging based on non-rigid image registration between low b value image and anatomical image.

Yasuo Takatsu1, Hajime Sagawa2, Masafumi Nakamura3, Yuichi Suzuki4, Tosiaki Miyati5.   

Abstract

PURPOSE: This study aimed to develop a novel technique for retrospective distortion correction based on non-rigid image registration in magnetic resonance diffusion image.
METHODS: A 3.0 T MRI scanner with an 18-channel dedicated breast coil and the outer shell of the original breast phantom, which provided images with non-uniform fat-suppression based on clinical data were used. The diffusion-weighted imaging with and without parallel imaging (PI) was used. The proposed study included several steps, which are FOV size matching, matrix size matching, image segmentation, edge detection, non-rigid image registration, and image wrap. We compared the results obtained using the proposed method with that obtained using TOPUP images. The correlation was assessed between T1-weighted image with fat suppression (FS-T1WI) and b1000 image with the help of cross-correlation coefficient (CCC). Shape-error analysis of tumor model and apparent diffusion coefficient (ADC) was calculated. The Steel-Dwass multiple-comparison tests were used for all comparisons and statistical analysis (P < 0.05).
RESULTS: The novel method of CCC showed the highest correlation between FS-T1WI and b1000 images. In the Steel-Dwass multiple-comparison test, significant differences were found (P < 0.05) except between non-correction and TOPUP (P = 0.99). The novel method was the lowest degree of error. With PI in the right breast, no significant differences, whereas in the left breast, significant differences were observed except for between novel method and TOPUP (P = 0.73). Without PI in the right breast, significant differences were observed. In the left breast, no significant differences were observed between any combinations. The ADC value, no significant differences were observed for non-correction and novel methods.
CONCLUSIONS: We developed a novel technique for retrospective distortion correction based on non-rigid image registration. The high degree of accuracy of this method combined with the lack of requirement for additional scans renders it a promising tool for application in clinical practice.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Breast; Diffusion-weighted imaging; Distortion; Magnetic resonance imaging; Non-rigid image registration

Mesh:

Year:  2018        PMID: 30543851     DOI: 10.1016/j.mri.2018.12.002

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  4 in total

1.  Diffusion-weighted MRI for Unenhanced Breast Cancer Screening.

Authors:  Nita Amornsiripanitch; Sebastian Bickelhaupt; Hee Jung Shin; Madeline Dang; Habib Rahbar; Katja Pinker; Savannah C Partridge
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

2.  Identification of a Suitable Untargeted Agent for the Clinical Translation of ABY-029 Paired-Agent Imaging in Fluorescence-Guided Surgery.

Authors:  Cheng Wang; Xiaochun Xu; Sassan Hodge; Eunice Y Chen; P Jack Hoopes; Kenneth M Tichauer; Kimberley S Samkoe
Journal:  Mol Imaging Biol       Date:  2021-10-12       Impact factor: 3.484

3.  Dynamic Contrast-enhanced and Diffusion-weighted Magnetic Resonance Imaging for Response Evaluation After Single-Dose Ablative Neoadjuvant Partial Breast Irradiation.

Authors:  Jeanine E Vasmel; Maureen L Groot Koerkamp; Stefano Mandija; Wouter B Veldhuis; Maaike R Moman; Martijn Froeling; Bas H M van der Velden; Ramona K Charaghvandi; Celien P H Vreuls; Paul J van Diest; A M Gijs van Leeuwen; Joost van Gorp; Marielle E P Philippens; Bram van Asselen; Jan J W Lagendijk; Helena M Verkooijen; H J G Desirée van den Bongard; Antonetta C Houweling
Journal:  Adv Radiat Oncol       Date:  2021-11-20

4.  Extracellular volume fraction measurement correlates with lymphocyte abundance in thymic epithelial tumors.

Authors:  Chao-Chun Chang; Chia-Ying Lin; Chang-Yao Chu; Yi-Cheng Hsiung; Ming-Tsung Chuang; Yau-Lin Tseng; Yi-Ting Yen
Journal:  Cancer Imaging       Date:  2020-10-07       Impact factor: 3.909

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.