Literature DB >> 19652611

A combined high temporal and high spatial resolution 3 Tesla MR imaging protocol for the assessment of breast lesions: initial results.

Katja Pinker1, Gunther Grabner, Wolfgang Bogner, Stephan Gruber, Pavol Szomolanyi, Siegfried Trattnig, Gertraud Heinz-Peer, Michael Weber, Florian Fitzal, Ursula Pluschnig, Margarethe Rudas, Thomas Helbich.   

Abstract

PURPOSE: To develop a 3.0 Tesla breast imaging protocol that combines high temporal and spatial resolution three-dimensional MR sequences for quantitative time course and morphologic analysis of breast lesions.
MATERIALS AND METHODS: Thirty-four patients were included in the study (age range, 31-82; mean age, 54.3). The study protocol was approved by the Institutional Review Board and written informed consent was obtained from all patients. The magnetic resonance imaging protocol included: a coronal T1-weighted volume-interpolated-breathhold-examination sequence, focused on high temporal resolution for optimal assessment of the contrast-enhancement behavior of lesions (SI 1.7 mm isotropic; TA 3.45 minutes for 17 measurements); a coronal T1-weighted turbo fast-low-angle-shot-three-dimensional sequence, with water-excitation and fat suppression, focused on high spatial resolution for morphologic analysis (SI 1 mm isotropic; TA 2 minutes); and a repeated coronal volume-interpolated-breathhold-examination sequence for detection of washout. Lesion size and morphology were assessed. Region-of-interests for suspicious areas were manually drawn and evaluated for contrast-enhancement behavior by plotting intensity courses against time. Sensitivity and specificity with a 95% confidence interval and the negative predictive value and positive predictive value were calculated. Diagnostic accuracy was assessed. The histopathological diagnoses were used as a standard of reference.
RESULTS: Fifty-five lesions were detected in 34 patients. All malignant breast lesions were identified correctly. There were 5 false-positive lesions. The sensitivity of contrast-enhanced magnetic resonance imaging of the breast at 3 T was 100%, with a 95% confidence interval (CI) of 90.6% to 100%. The specificity was 72.2%, with a 95% CI of 49.1% to 87.5%. The positive predictive value was 0.88 and the negative predictive value was 1. Diagnostic accuracy was 91% with a 95% CI of 80.4% to 96.1%.
CONCLUSION: Our prospective study demonstrates that the presented 3 Tesla MR imaging protocol, comprising both high temporal and high spatial resolution, enables accurate detection and assessment of breast lesions.

Entities:  

Mesh:

Year:  2009        PMID: 19652611     DOI: 10.1097/RLI.0b013e3181b4c127

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  41 in total

1.  Non-contrast enhanced MRI for evaluation of breast lesions: comparison of non-contrast enhanced high spectral and spatial resolution (HiSS) images versus contrast enhanced fat-suppressed images.

Authors:  Milica Medved; Xiaobing Fan; Hiroyuki Abe; Gillian M Newstead; Abbie M Wood; Akiko Shimauchi; Kirti Kulkarni; Marko K Ivancevic; Lorenzo L Pesce; Olufunmilayo I Olopade; Gregory S Karczmar
Journal:  Acad Radiol       Date:  2011-10-01       Impact factor: 3.173

2.  Computer-Aided Diagnosis Scheme for Distinguishing Between Benign and Malignant Masses in Breast DCE-MRI.

Authors:  Emi Honda; Ryohei Nakayama; Hitoshi Koyama; Akiyoshi Yamashita
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

3.  Clinical application of bilateral high temporal and spatial resolution dynamic contrast-enhanced magnetic resonance imaging of the breast at 7 T.

Authors:  K Pinker; W Bogner; P Baltzer; S Trattnig; S Gruber; O Abeyakoon; M Bernathova; O Zaric; P Dubsky; Z Bago-Horvath; M Weber; D Leithner; T H Helbich
Journal:  Eur Radiol       Date:  2013-12-05       Impact factor: 5.315

4.  Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping for Breast Cancer Detection as a Stand-Alone Parameter: Comparison With Dynamic Contrast-Enhanced and Multiparametric Magnetic Resonance Imaging.

Authors:  Katja Pinker; Linda Moy; Elizabeth J Sutton; Ritse M Mann; Michael Weber; Sunitha B Thakur; Maxine S Jochelson; Zsuzsanna Bago-Horvath; Elizabeth A Morris; Pascal At Baltzer; Thomas H Helbich
Journal:  Invest Radiol       Date:  2018-10       Impact factor: 6.016

5.  Molecular Imaging in Breast Cancer - Potential Future Aspects.

Authors:  Katja Pinker; Wolfgang Bogner; Stephan Gruber; Peter Brader; Siegfried Trattnig; Georgios Karanikas; Thomas H Helbich
Journal:  Breast Care (Basel)       Date:  2011-04-29       Impact factor: 2.860

6.  3.0 Tesla breast magnetic resonance imaging in patients with nipple discharge when mammography and ultrasound fail.

Authors:  Nóra Lubina; Ulla Schedelbeck; Anne Roth; Andreas Max Weng; Eva Geissinger; Arnd Hönig; Dietbert Hahn; Thorsten Alexander Bley
Journal:  Eur Radiol       Date:  2014-11-30       Impact factor: 5.315

7.  [Researcher of the month, December 2012. Dr. Wolfgang Bogner].

Authors:  Wolfgang Bogner
Journal:  Wien Klin Wochenschr       Date:  2012-12       Impact factor: 1.704

8.  Combined contrast-enhanced magnetic resonance and diffusion-weighted imaging reading adapted to the "Breast Imaging Reporting and Data System" for multiparametric 3-T imaging of breast lesions.

Authors:  K Pinker; H Bickel; T H Helbich; S Gruber; P Dubsky; U Pluschnig; M Rudas; Z Bago-Horvath; M Weber; S Trattnig; W Bogner
Journal:  Eur Radiol       Date:  2013-03-16       Impact factor: 5.315

9.  Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.

Authors:  Amirhessam Tahmassebi; Georg J Wengert; Thomas H Helbich; Zsuzsanna Bago-Horvath; Sousan Alaei; Rupert Bartsch; Peter Dubsky; Pascal Baltzer; Paola Clauser; Panagiotis Kapetas; Elizabeth A Morris; Anke Meyer-Baese; Katja Pinker
Journal:  Invest Radiol       Date:  2019-02       Impact factor: 6.016

10.  Current and future trends in magnetic resonance imaging assessments of the response of breast tumors to neoadjuvant chemotherapy.

Authors:  Lori R Arlinghaus; Xia Li; Mia Levy; David Smith; E Brian Welch; John C Gore; Thomas E Yankeelov
Journal:  J Oncol       Date:  2010-09-29       Impact factor: 4.375

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.