Literature DB >> 25785918

Comparison of dynamic contrast-enhanced MRI parameters of breast lesions at 1.5 and 3.0 T: a pilot study.

F D Pineda1, M Medved, X Fan, M K Ivancevic, H Abe, A Shimauchi, G M Newstead, G S Karczmar.   

Abstract

OBJECTIVE: To compare dynamic contrast-enhanced (DCE) MRI parameters from scans of breast lesions at 1.5 and 3.0 T.
METHODS: 11 patients underwent paired MRI examinations in both Philips 1.5 and 3.0 T systems (Best, Netherlands) using a standard clinical fat-suppressed, T1 weighted DCE-MRI protocol, with 70-76 s temporal resolution. Signal intensity vs time curves were fit with an empirical mathematical model to obtain semi-quantitative measures of uptake and washout rates as well as time-to-peak enhancement (TTP). Maximum percent enhancement and signal enhancement ratio (SER) were also measured for each lesion. Percent differences between parameters measured at the two field strengths were compared.
RESULTS: TTP and SER parameters measured at 1.5 and 3.0 T were similar; with mean absolute differences of 19% and 22%, respectively. Maximum percent signal enhancement was significantly higher at 3 T than at 1.5 T (p = 0.006). Qualitative assessment showed that image quality was significantly higher at 3 T (p = 0.005).
CONCLUSION: Our results suggest that TTP and SER are more robust to field strength change than other measured kinetic parameters, and therefore measurements of these parameters can be more easily standardized than measurements of other parameters derived from DCE-MRI. Semi-quantitative measures of overall kinetic curve shape showed higher reproducibility than do discrete classification of kinetic curve early and delayed phases in a majority of the cases studied. ADVANCES IN KNOWLEDGE: Qualitative measures of curve shape are not consistent across field strength even when acquisition parameters are standardized. Quantitative measures of overall kinetic curve shape, by contrast, have higher reproducibility.

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Year:  2015        PMID: 25785918      PMCID: PMC4628483          DOI: 10.1259/bjr.20150021

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  24 in total

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Authors:  C K Kuhl; P Mielcareck; S Klaschik; C Leutner; E Wardelmann; J Gieseke; H H Schild
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2.  Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer.

Authors:  Christiane K Kuhl; Simone Schrading; Claudia C Leutner; Nuschin Morakkabati-Spitz; Eva Wardelmann; Rolf Fimmers; Walther Kuhn; Hans H Schild
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3.  Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL.

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Journal:  Radiology       Date:  2012-06       Impact factor: 11.105

Review 4.  Dynamic contrast-enhanced magnetic resonance imaging as an imaging biomarker.

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Journal:  J Clin Oncol       Date:  2006-07-10       Impact factor: 44.544

5.  Contrast-Enhanced Magnetic Resonance Imaging to Assess Tumor Histopathology and Angiogenesis in Breast Carcinoma.

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7.  Kinetic curves of malignant lesions are not consistent across MRI systems: need for improved standardization of breast dynamic contrast-enhanced MRI acquisition.

Authors:  Sanaz A Jansen; Akiko Shimauchi; Lindsay Zak; Xiaobing Fan; Abbie M Wood; Gregory S Karczmar; Gillian M Newstead
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8.  New model for analysis of dynamic contrast-enhanced MRI data distinguishes metastatic from nonmetastatic transplanted rodent prostate tumors.

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9.  Kinetic assessment of breast tumors using high spatial resolution signal enhancement ratio (SER) imaging.

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10.  Increasing accuracy of detection of breast cancer with 3-T MRI.

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  6 in total

1.  Dynamic Contrast-Enhanced MRI-Derived Intracellular Water Lifetime (τ i ): A Prognostic Marker for Patients with Head and Neck Squamous Cell Carcinomas.

Authors:  S Chawla; L A Loevner; S G Kim; W-T Hwang; S Wang; G Verma; S Mohan; V LiVolsi; H Quon; H Poptani
Journal:  AJNR Am J Neuroradiol       Date:  2017-11-16       Impact factor: 3.825

2.  Preoperative predicting malignancy in breast mass-like lesions: value of adding histogram analysis of apparent diffusion coefficient maps to dynamic contrast-enhanced magnetic resonance imaging for improving confidence level.

Authors:  Hong-Li Liu; Min Zong; Han Wei; Jian-Juan Lou; Si-Qi Wang; Qi-Gui Zou; Hai-Bin Shi; Yan-Ni Jiang
Journal:  Br J Radiol       Date:  2017-09-06       Impact factor: 3.039

3.  Improved value of whole-lesion histogram analysis on DCE parametric maps for diagnosing small breast cancer (≤ 1 cm).

Authors:  Tianwen Xie; Qiufeng Zhao; Caixia Fu; Robert Grimm; Yajia Gu; Weijun Peng
Journal:  Eur Radiol       Date:  2021-09-09       Impact factor: 7.034

4.  The diagnostic performance of routinely acquired and reported computed tomography imaging in patients presenting with suspected pleural malignancy.

Authors:  Selina Tsim; David B Stobo; Laura Alexander; Caroline Kelly; Kevin G Blyth
Journal:  Lung Cancer       Date:  2016-11-18       Impact factor: 5.705

5.  Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths.

Authors:  Heather M Whitney; Karen Drukker; Alexandra Edwards; John Papaioannou; Milica Medved; Gregory Karczmar; Maryellen L Giger
Journal:  Magn Reson Imaging       Date:  2021-06-24       Impact factor: 3.130

6.  Preoperative dynamic breast magnetic resonance imaging kinetic features using computer-aided diagnosis: Association with survival outcome and tumor aggressiveness in patients with invasive breast cancer.

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  6 in total

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