Literature DB >> 32780207

Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI.

Isaac Daimiel Naranjo1, Roberto Lo Gullo1,2, Carolina Saccarelli1, Sunitha B Thakur1,3, Almir Bitencourt1,4, Elizabeth A Morris1, Maxine S Jochelson1, Varadan Sevilimedu5, Danny F Martinez1, Katja Pinker-Domenig6,7.   

Abstract

OBJECTIVES: To assess DWI for tumor visibility and breast cancer detection by the addition of different synthetic b-values.
METHODS: Eighty-four consecutive women who underwent a breast-multiparametric-MRI (mpMRI) with enhancing lesions on DCE-MRI (BI-RADS 2-5) were included in this IRB-approved retrospective study from September 2018 to March 2019. Three readers evaluated DW acquired b-800 and synthetic b-1000, b-1200, b-1500, and b-1800 s/mm2 images for lesion visibility and preferred b-value based on lesion conspicuity. Image quality (1-3 scores) and breast composition (BI-RADS) were also recorded. Diagnostic parameters for DWI were determined using a 1-5 malignancy score based on qualitative imaging parameters (acquired + preferred synthetic b-values) and ADC values. BI-RADS classification was used for DCE-MRI and quantitative ADC values + BI-RADS were used for mpMRI.
RESULTS: Sixty-four malignant (average = 23 mm) and 39 benign (average = 8 mm) lesions were found in 80 women. Although b-800 achieved the best image quality score, synthetic b-values 1200-1500 s/mm2 were preferred for lesion conspicuity, especially in dense breast. b-800 and synthetic b-1000/b-1200 s/mm2 values allowed the visualization of 84-90% of cancers visible with DCE-MRI performing better than b-1500/b-1800 s/mm2. DWI was more specific (86.3% vs 65.7%, p < 0.001) but less sensitive (62.8% vs 90%, p < 0.001) and accurate (71% vs 80.7%, p = 0.003) than DCE-MRI for breast cancer detection, where mpMRI was the most accurate modality accounting for less false positive cases.
CONCLUSION: The addition of synthetic b-values enhances tumor conspicuity and could potentially improve tumor visualization particularly in dense breast. However, its supportive role for DWI breast cancer detection is still not definite. KEY POINTS: • The addition of synthetic b-values (1200-1500 s/mm2) to acquired DWI afforded a better lesion conspicuity without increasing acquisition time and was particularly useful in dense breasts. • Despite the use of synthetic b-values, DWI was less sensitive and accurate than DCE-MRI for breast cancer detection. • A multiparametric MRI modality still remains the best approach having the highest accuracy for breast cancer detection and thus reducing the number of unnecessary biopsies.

Entities:  

Keywords:  Breast tumors; Diagnostic imaging; Diffusion magnetic resonance imaging; Echo-planar imaging; Image analysis

Mesh:

Substances:

Year:  2020        PMID: 32780207      PMCID: PMC7755636          DOI: 10.1007/s00330-020-07094-z

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  40 in total

1.  Diffusion-weighted MRI in Multicenter Trials of Breast Cancer.

Authors:  Savannah C Partridge; David C Newitt; Thomas L Chenevert; Mark A Rosen; Nola M Hylton
Journal:  Radiology       Date:  2019-04-02       Impact factor: 11.105

2.  Breast cancer detection using double reading of unenhanced MRI including T1-weighted, T2-weighted STIR, and diffusion-weighted imaging: a proof of concept study.

Authors:  Rubina M Trimboli; Nicola Verardi; Francesco Cartia; Luca A Carbonaro; Francesco Sardanelli
Journal:  AJR Am J Roentgenol       Date:  2014-09       Impact factor: 3.959

Review 3.  Critical Questions Regarding Gadolinium Deposition in the Brain and Body After Injections of the Gadolinium-Based Contrast Agents, Safety, and Clinical Recommendations in Consideration of the EMA's Pharmacovigilance and Risk Assessment Committee Recommendation for Suspension of the Marketing Authorizations for 4 Linear Agents.

Authors:  Val M Runge
Journal:  Invest Radiol       Date:  2017-06       Impact factor: 6.016

Review 4.  Gadolinium deposition in the brain: summary of evidence and recommendations.

Authors:  Vikas Gulani; Fernando Calamante; Frank G Shellock; Emanuel Kanal; Scott B Reeder
Journal:  Lancet Neurol       Date:  2017-06-13       Impact factor: 44.182

5.  Gadolinium retention after administration of contrast agents based on linear chelators and the recommendations of the European Medicines Agency.

Authors:  Ilona A Dekkers; Rick Roos; Aart J van der Molen
Journal:  Eur Radiol       Date:  2017-10-23       Impact factor: 5.315

6.  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

Review 7.  Diffusion-weighted breast MRI: Clinical applications and emerging techniques.

Authors:  Savannah C Partridge; Noam Nissan; Habib Rahbar; Averi E Kitsch; Eric E Sigmund
Journal:  J Magn Reson Imaging       Date:  2016-09-30       Impact factor: 4.813

8.  Potential of Noncontrast Magnetic Resonance Imaging With Diffusion-Weighted Imaging in Characterization of Breast Lesions: Intraindividual Comparison With Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Authors:  Pascal A T Baltzer; Hubert Bickel; Claudio Spick; Georg Wengert; Ramona Woitek; Panagiotis Kapetas; Paola Clauser; Thomas H Helbich; Katja Pinker
Journal:  Invest Radiol       Date:  2018-04       Impact factor: 6.016

9.  Performance of DWI as a Rapid Unenhanced Technique for Detecting Mammographically Occult Breast Cancer in Elevated-Risk Women With Dense Breasts.

Authors:  Elizabeth S McDonald; Jill A Hammersley; Shinn-Huey S Chou; Habib Rahbar; John R Scheel; Christoph I Lee; Cheng-Liang Liu; Constance D Lehman; Savannah C Partridge
Journal:  AJR Am J Roentgenol       Date:  2016-04-14       Impact factor: 3.959

10.  Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions.

Authors:  Xin Chen; Wen-ling Li; Yi-li Zhang; Qian Wu; You-min Guo; Zhi-lan Bai
Journal:  BMC Cancer       Date:  2010-12-29       Impact factor: 4.430

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1.  Artificial Intelligence in Radiation Therapy.

Authors:  Yabo Fu; Hao Zhang; Eric D Morris; Carri K Glide-Hurst; Suraj Pai; Alberto Traverso; Leonard Wee; Ibrahim Hadzic; Per-Ivar Lønne; Chenyang Shen; Tian Liu; Xiaofeng Yang
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2021-08-24

2.  A survey by the European Society of Breast Imaging on the implementation of breast diffusion-weighted imaging in clinical practice.

Authors:  Laura Martincich; Katja Pinker; Roberto Lo Gullo; Varadan Sevilimedu; Pascal Baltzer; Denis Le Bihan; Julia Camps-Herrero; Paola Clauser; Fiona J Gilbert; Mami Iima; Ritse M Mann; Savannah C Partridge; Andrew Patterson; Eric E Sigmund; Sunitha Thakur; Fabienne E Thibault
Journal:  Eur Radiol       Date:  2022-05-04       Impact factor: 7.034

3.  Diffusion weighted imaging of the breast: Performance of standardized breast tumor tissue selection methods in clinical decision making.

Authors:  M Wielema; P E Sijens; H Dijkstra; G H De Bock; I G van Bruggen; J E Siegersma; E Langius; R M Pijnappel; M D Dorrius; M Oudkerk
Journal:  PLoS One       Date:  2021-01-25       Impact factor: 3.240

4.  Breast Lesion Classification with Multiparametric Breast MRI Using Radiomics and Machine Learning: A Comparison with Radiologists' Performance.

Authors:  Isaac Daimiel Naranjo; Peter Gibbs; Jeffrey S Reiner; Roberto Lo Gullo; Sunitha B Thakur; Maxine S Jochelson; Nikita Thakur; Pascal A T Baltzer; Thomas H Helbich; Katja Pinker
Journal:  Cancers (Basel)       Date:  2022-03-29       Impact factor: 6.575

5.  AI-enhanced simultaneous multiparametric 18F-FDG PET/MRI for accurate breast cancer diagnosis.

Authors:  V Romeo; P Clauser; S Rasul; P Kapetas; P Gibbs; P A T Baltzer; M Hacker; R Woitek; T H Helbich; K Pinker
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-08-10       Impact factor: 10.057

  5 in total

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