Literature DB >> 30892807

Repeatability and reproducibility of 3D MR fingerprinting relaxometry measurements in normal breast tissue.

Ananya Panda1, Yong Chen2,3, Kathleen Ropella-Panagis4, Satyam Ghodasara5, Marcie Stopchinski6, Nicole Seyfried5, Katherine Wright4, Nicole Seiberlich4,6,7, Mark Griswold4,6,7, Vikas Gulani4,6,7.   

Abstract

BACKGROUND: The 3D breast magnetic resonance fingerprinting (MRF) technique enables T1 and T2 mapping in breast tissues. Combined repeatability and reproducibility studies on breast T1 and T2 relaxometry are lacking.
PURPOSE: To assess test-retest and two-visit repeatability and interscanner reproducibility of the 3D breast MRF technique in a single-institution setting. STUDY TYPE: Prospective.
SUBJECTS: Eighteen women (median age 29 years, range, 22-33 years) underwent Visit 1 scans on scanner 1. Ten of these women underwent test-retest scan repositioning after a 10-minute interval. Thirteen women had Visit 2 scans within 7-15 days in same menstrual cycle. The remaining five women had Visit 2 scans in the same menstrual phase in next menstrual cycle. Five women were also scanned on scanner 2 at both visits for interscanner reproducibility. FIELD STRENGTH/SEQUENCE: Two 3T MR scanners with the 3D breast MRF technique. ASSESSMENT: T1 and T2 MRF maps of both breasts. STATISTICAL TESTS: Mean T1 and T2 values for normal fibroglandular tissues were quantified at all scans. For variability, between and within-subjects coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability was assessed with Bland-Altman analysis and coefficient of repeatability (CR). Reproducibility was assessed with interscanner coefficient of variation (CoV) and Wilcoxon signed-rank test.
RESULTS: The bCV at test-retest scans was 9-12% for T1 , 7-17% for T2 , wCV was <4% for T1 , and <7% for T2 . For two visits in same menstrual cycle, bCV was 10-15% for T1 , 13-17% for T2 , wCV was <7% for T1 and <5% for T2 . For two visits in the same menstrual phase, bCV was 6-14% for T1 , 15-18% for T2 , wCV was <7% for T1 , and <9% for T2 . For test-retest scans, CR for T1 and T2 were 130 msec and 11 msec. For two visit scans, CR was <290 msec for T1 and 10-14 msec for T2 . Interscanner CoV was 3.3-3.6% for T1 and 5.1-6.6% for T2 , with no differences between interscanner measurements (P = 1.00 for T1 , P = 0.344 for T2 ). DATA
CONCLUSION: 3D breast MRF measurements are repeatable across scan timings and scanners and may be useful in clinical applications in breast imaging. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1133-1143.
© 2019 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  breast; magnetic resonance fingerprinting; quantitative imaging; relaxometry; repeatability

Year:  2019        PMID: 30892807      PMCID: PMC6750981          DOI: 10.1002/jmri.26717

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  24 in total

1.  Relaxation times of breast tissue at 1.5T and 3T measured using IDEAL.

Authors:  Rebecca Rakow-Penner; Bruce Daniel; Huanzhou Yu; Anne Sawyer-Glover; Gary H Glover
Journal:  J Magn Reson Imaging       Date:  2006-01       Impact factor: 4.813

2.  Lesion T(2) relaxation times and volumes predict the response of malignant breast lesions to neoadjuvant chemotherapy.

Authors:  P Clara Tan; Martin D Pickles; Martin Lowry; David J Manton; Lindsay W Turnbull
Journal:  Magn Reson Imaging       Date:  2007-06-15       Impact factor: 2.546

3.  Imaging as a quantitative science.

Authors:  Daniel C Sullivan
Journal:  Radiology       Date:  2008-08       Impact factor: 11.105

4.  Diffusion weighted imaging of the normal breast: reproducibility of apparent diffusion coefficient measurements and variation with menstrual cycle and menopausal status.

Authors:  Elizabeth A M O'Flynn; Veronica A Morgan; Sharon L Giles; Nandita M deSouza
Journal:  Eur Radiol       Date:  2012-02-26       Impact factor: 5.315

5.  Repeatability of quantitative MRI measurements in normal breast tissue.

Authors:  Sheye O Aliu; Ella F Jones; Ania Azziz; John Kornak; Lisa J Wilmes; David C Newitt; Sachiko A Suzuki; Catherine Klifa; Jessica Gibbs; Evelyn C Proctor; Bonnie N Joe; Nola M Hylton
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

6.  Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI.

Authors:  S C Partridge; G C McKinnon; R G Henry; N M Hylton
Journal:  J Magn Reson Imaging       Date:  2001-10       Impact factor: 4.813

7.  Longitudinal and multi-echo transverse relaxation times of normal breast tissue at 3 Tesla.

Authors:  Richard A E Edden; Seth A Smith; Peter B Barker
Journal:  J Magn Reson Imaging       Date:  2010-10       Impact factor: 4.813

8.  Physiologic changes in breast magnetic resonance imaging during the menstrual cycle: perfusion imaging, signal enhancement, and influence of the T1 relaxation time of breast tissue.

Authors:  Jean-Paul Delille; Priscilla J Slanetz; Eren D Yeh; Daniel B Kopans; Leoncio Garrido
Journal:  Breast J       Date:  2005 Jul-Aug       Impact factor: 2.431

9.  Radiological interpretation 2020: toward quantitative image assessment.

Authors:  John M Boone
Journal:  Med Phys       Date:  2007-11       Impact factor: 4.071

10.  Neoadjuvant chemotherapy in breast cancer: early response prediction with quantitative MR imaging and spectroscopy.

Authors:  D J Manton; A Chaturvedi; A Hubbard; M J Lind; M Lowry; A Maraveyas; M D Pickles; D J Tozer; L W Turnbull
Journal:  Br J Cancer       Date:  2006-02-13       Impact factor: 7.640

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  10 in total

Review 1.  Magnetic resonance fingerprinting: an overview.

Authors:  Charit Tippareddy; Walter Zhao; Jeffrey L Sunshine; Mark Griswold; Dan Ma; Chaitra Badve
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-05-26       Impact factor: 9.236

Review 2.  Magnetic resonance fingerprinting review part 2: Technique and directions.

Authors:  Debra F McGivney; Rasim Boyacıoğlu; Yun Jiang; Megan E Poorman; Nicole Seiberlich; Vikas Gulani; Kathryn E Keenan; Mark A Griswold; Dan Ma
Journal:  J Magn Reson Imaging       Date:  2019-07-25       Impact factor: 4.813

3.  Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification.

Authors:  Jesse I Hamilton; Nicole Seiberlich
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2019-09-11       Impact factor: 10.961

4.  Repeatability of MR fingerprinting in normal cervix and utility in cervical carcinoma.

Authors:  Mandi Wang; Jose A U Perucho; Peng Cao; Varut Vardhanabhuti; Di Cui; Yiang Wang; Pek-Lan Khong; Edward S Hui; Elaine Y P Lee
Journal:  Quant Imaging Med Surg       Date:  2021-09

Review 5.  MR fingerprinting of the prostate.

Authors:  Wei-Ching Lo; Ananya Panda; Yun Jiang; James Ahad; Vikas Gulani; Nicole Seiberlich
Journal:  MAGMA       Date:  2022-04-13       Impact factor: 2.533

Review 6.  Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer.

Authors:  Apekshya Chhetri; Xin Li; Joseph V Rispoli
Journal:  Front Med (Lausanne)       Date:  2020-05-12

7.  Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma.

Authors:  Thomaz R Mostardeiro; Ananya Panda; Robert J Witte; Norbert G Campeau; Kiaran P McGee; Yi Sui; Aiming Lu
Journal:  MAGMA       Date:  2021-05-04       Impact factor: 2.310

Review 8.  Magnetic resonance fingerprinting: from evolution to clinical applications.

Authors:  Jean J L Hsieh; Imants Svalbe
Journal:  J Med Radiat Sci       Date:  2020-06-28

9.  Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging.

Authors:  Bjoern H Menze; Marion I Menzel; Juan A Hernandez-Tamames; Carolin M Pirkl; Laura Nunez-Gonzalez; Florian Kofler; Sebastian Endt; Lioba Grundl; Mohammad Golbabaee; Pedro A Gómez; Matteo Cencini; Guido Buonincontri; Rolf F Schulte; Marion Smits; Benedikt Wiestler
Journal:  Neuroradiology       Date:  2021-04-09       Impact factor: 2.804

10.  Repeatability and reproducibility of human brain morphometry using three-dimensional magnetic resonance fingerprinting.

Authors:  Shohei Fujita; Guido Buonincontri; Matteo Cencini; Issei Fukunaga; Naoyuki Takei; Rolf F Schulte; Akifumi Hagiwara; Wataru Uchida; Masaaki Hori; Koji Kamagata; Osamu Abe; Shigeki Aoki
Journal:  Hum Brain Mapp       Date:  2020-10-22       Impact factor: 5.399

  10 in total

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