Literature DB >> 18697535

DCEMRI of breast lesions: is kinetic analysis equally effective for both mass and nonmass-like enhancement?

Sanaz A Jansen1, Xiaobing Fan, Gregory S Karczmar, Hiroyuki Abe, Robert A Schmidt, Maryellen Giger, Gillian M Newstead.   

Abstract

To perform a pilot study investigating whether the sensitivity and specificity of kinetic parameters can be improved by considering mass and nonmass breast lesions separately. The contrast media uptake and washout kinetics in benign and malignant breast lesions were analyzed using an empirical mathematical model (EMM), and model parameters were compared in lesions with mass-like and nonmass-like enhancement characteristics. 34 benign and 78 malignant breast lesions were selected for review. Dynamic MR protocol: 1 pre and 5 postcontrast images acquired in the coronal plane using a 3D T1-weighted SPGR with 68 s timing resolution. An experienced radiologist classified the type of enhancement as mass, nonmass, or focus, according to the BI-RADS lexicon. The kinetic curve obtained from a radiologist-drawn region within the lesion was analyzed quantitatively using a three parameter EMM. Several kinetic parameters were then derived from the EMM parameters: the initial slope (Slope(ini)), curvature at the peak (kappa(peak)), time to peak (T(peak)), initial area under the curve at 30 s (iAUC30), and the signal enhancement ratio (SER). The BI-RADS classification of the lesions yielded: 70 mass lesions, 38 nonmass, 4 focus. For mass lesions, the contrast uptake rate (alpha), contrast washout rate (beta), iAUC30, SER, Slope(ini), T(peak) and kappa(peak) differed substantially between benign and malignant lesions, and after correcting for multiple tests of significance SER and T(peak) demonstrated significance (p < 0.007). For nonmass lesions, we did not find statistically significant differences in any of the parameters for benign vs. malignant lesions (p > 0.5). Kinetic parameters could distinguish benign and malignant mass lesions effectively, but were not quite as useful in discriminating benign from malignant nonmass lesions. If the results of this pilot study are validated in a larger trial, we expect that to maximize diagnostic utility, it will be better to classify lesion morphology as mass or nonmass-like enhancement prior to kinetic analysis.

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Year:  2008        PMID: 18697535      PMCID: PMC2673559          DOI: 10.1118/1.2936220

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  44 in total

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Journal:  AJR Am J Roentgenol       Date:  2007-08       Impact factor: 3.959

Review 3.  The fourth EORTC DCIS Consensus meeting (Château Marquette, Heemskerk, The Netherlands, 23-24 January 1998)--conference report.

Authors:  A Recht; E J Rutgers; I S Fentiman; J M Kurtz; R E Mansel; J P Sloane
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4.  In situ and minimally invasive breast cancer: morphologic and kinetic features on contrast-enhanced MR imaging.

Authors:  P Viehweg; D Lampe; J Buchmann; S H Heywang-Köbrunner
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Review 5.  Patterns of enhancement on breast MR images: interpretation and imaging pitfalls.

Authors:  Katarzyna J Macura; Ronald Ouwerkerk; Michael A Jacobs; David A Bluemke
Journal:  Radiographics       Date:  2006 Nov-Dec       Impact factor: 5.333

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

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7.  Breast lesions detected on MR imaging: features and positive predictive value.

Authors:  Laura Liberman; Elizabeth A Morris; Melissa Joo-Young Lee; Jennifer B Kaplan; Linda R LaTrenta; Jennifer H Menell; Andrea F Abramson; Stephen M Dashnaw; Douglas J Ballon; D David Dershaw
Journal:  AJR Am J Roentgenol       Date:  2002-07       Impact factor: 3.959

8.  Analysis of dynamic MR breast images using a model of contrast enhancement.

Authors:  P Hayton; M Brady; L Tarassenko; N Moore
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9.  Quantitative analysis of dynamic Gd-DTPA enhancement in breast tumors using a permeability model.

Authors:  P S Tofts; B Berkowitz; M D Schnall
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  20 in total

1.  Kinetic analysis of lesions without mass effect on breast MRI using manual and computer-assisted methods.

Authors:  Tibor Vag; Pascal A T Baltzer; Matthias Dietzel; Ramy Zoubi; Mieczyslaw Gajda; Oumar Camara; Werner A Kaiser
Journal:  Eur Radiol       Date:  2010-11-10       Impact factor: 5.315

2.  Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis.

Authors:  Akiko Shimauchi; Hiroyuki Abe; David V Schacht; Jian Yulei; Federico D Pineda; Sanaz A Jansen; Rajiv Ganesh; Gillian M Newstead
Journal:  Eur Radiol       Date:  2015-02-20       Impact factor: 5.315

3.  Optimization of apparent diffusion coefficient measured by diffusion-weighted MRI for diagnosis of breast lesions presenting as mass and non-mass-like enhancement.

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Journal:  Tumour Biol       Date:  2013-02-10

4.  Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy.

Authors:  Tatsunori Asada; Takayuki Yamada; Yoshihide Kanemaki; Keishi Fujiwara; Satoko Okamoto; Yasuo Nakajima
Journal:  Jpn J Radiol       Date:  2017-12-29       Impact factor: 2.374

5.  Classification of breast lesions pre-contrast injection using water resonance lineshape analysis.

Authors:  Abbie M Wood; Milica Medved; Ian D Bacchus; Hania A Al-Hallaq; Akiko Shimauchi; Gillian M Newstead; Olufunmilayo I Olopade; Srirama S Venkataraman; Marko K Ivancevic; Greg S Karczmar
Journal:  NMR Biomed       Date:  2012-11-20       Impact factor: 4.044

6.  The diverse pathology and kinetics of mass, nonmass, and focus enhancement on MR imaging of the breast.

Authors:  Sanaz A Jansen; Akiko Shimauchi; Lindsay Zak; Xiaobing Fan; Gregory S Karczmar; Gillian M Newstead
Journal:  J Magn Reson Imaging       Date:  2011-06       Impact factor: 4.813

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
Journal:  AJR Am J Roentgenol       Date:  2009-09       Impact factor: 3.959

8.  Intravoxel incoherent motion diffusion-weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma.

Authors:  Louisa Bokacheva; Jennifer B Kaplan; Dilip D Giri; Sujata Patil; Merlin Gnanasigamani; C Gregory Nyman; Joseph O Deasy; Elizabeth A Morris; Sunitha B Thakur
Journal:  J Magn Reson Imaging       Date:  2013-11-22       Impact factor: 4.813

9.  Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702).

Authors:  Jennifer G Whisenant; Justin Romanoff; Habib Rahbar; Averi E Kitsch; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak E Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Lisa J Wilmes; Nola M Hylton; Karen Y Oh; Luminita A Tudorica; Colleen H Neal; Dariya I Malyarenko; Elizabeth S McDonald; Christopher E Comstock; Thomas E Yankeelov; Thomas L Chenevert; Savannah C Partridge
Journal:  J Breast Imaging       Date:  2020-12-24

10.  Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement.

Authors:  Dustin Newell; Ke Nie; Jeon-Hor Chen; Chieh-Chih Hsu; Hon J Yu; Orhan Nalcioglu; Min-Ying Su
Journal:  Eur Radiol       Date:  2009-09-30       Impact factor: 5.315

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