Literature DB >> 23397543

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

Liuquan Cheng1, Yuhan Bai, Jing Zhang, Mei Liu, Xiru Li, Ailiang Zhang, Xiaojing Zhang, Lin Ma.   

Abstract

The purpose of this study was to investigate the diagnostic value of the apparent diffusion coefficient (ADC), measured by diffusion-weighted magnetic resonance imaging (MRI), for the diagnosis of breast lesions presenting as mass and non-mass-like enhancement (NMLE). The breast MRI studies of 174 patients were reviewed retrospectively. A total of 188 histologically confirmed lesions were analyzed and classified into 127 mass enhancement (86 malignant and 41 benign) and 61 NMLE (42 malignant and 19 benign). The ADC values were measured using a spin-echo echo-planner-imaging (SE-EPI) sequence with b=1,000 s/mm(2). Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. The mean ADC was 0.99 ± 0.22 × 10(-3)mm(2)/s for invasive cancer, 1.23 ± 0.33 × 10(-3)mm(2)/s for ductal carcinoma in situ (DCIS), and 1.52 ± 0.35 × 10(-3)mm(2)/s for benign adenosis. The mean ADC of all NMLE lesions was 1.44 ± 0.41 × 10(-3)mm(2)/s, which is higher than the mean ADC of all mass lesions, 1.12 ± 0.33 × 10(-3)mm(2)/s. In the ROC analysis, the optimal cutoff ADC value for differentiating benign from malignant lesions was 1.05 × 10(-3)mm(2)/s for mass lesions and 1.35 × 10(-3)mm(2)/s for NMLE. In conclusion, ADC values can be used for the diagnosis of invasive and DCIS as well as benign tumors. The NMLE lesions tend to have higher ADC values than mass lesions; therefore, the morphological appearance of a lesion needs to be considered when using the ADC value for diagnosis.

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Year:  2013        PMID: 23397543     DOI: 10.1007/s13277-013-0682-6

Source DB:  PubMed          Journal:  Tumour Biol        ISSN: 1010-4283


  28 in total

1.  Diagnostic performance of ADC for Non-mass-like breast lesions on MR imaging.

Authors:  Tsugumi Imamura; Ichiro Isomoto; Eijun Sueyoshi; Hiroshi Yano; Tatsuya Uga; Kuniko Abe; Tomayoshi Hayashi; Sumihisa Honda; Takuma Yamaguchi; Masataka Uetani
Journal:  Magn Reson Med Sci       Date:  2010       Impact factor: 2.471

2.  Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value.

Authors:  Savannah C Partridge; Wendy B DeMartini; Brenda F Kurland; Peter R Eby; Steven W White; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2009-12       Impact factor: 3.959

3.  Sensitivity and specificity of unenhanced MR mammography (DWI combined with T2-weighted TSE imaging, ueMRM) for the differentiation of mass lesions.

Authors:  Pascal A T Baltzer; Matthias Benndorf; Matthias Dietzel; Mieczyslaw Gajda; Oumar Camara; Werner A Kaiser
Journal:  Eur Radiol       Date:  2009-11-20       Impact factor: 5.315

4.  The physical and biological basis of quantitative parameters derived from diffusion MRI.

Authors:  Gavin P Winston
Journal:  Quant Imaging Med Surg       Date:  2012-12

5.  Apparent diffusion coefficient values for discriminating benign and malignant breast MRI lesions: effects of lesion type and size.

Authors:  Savannah C Partridge; Christiane D Mullins; Brenda F Kurland; Michael D Allain; Wendy B DeMartini; Peter R Eby; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2010-06       Impact factor: 3.959

6.  Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging.

Authors:  Riham H Ei Khouli; Michael A Jacobs; Sarah D Mezban; Peng Huang; Ihab R Kamel; Katarzyna J Macura; David A Bluemke
Journal:  Radiology       Date:  2010-07       Impact factor: 11.105

Review 7.  Diffusion weighted MR imaging of the breast.

Authors:  Ahmed Abdel Khalek Abdel Razek; Gada Gaballa; Adel Denewer; Ismail Tawakol
Journal:  Acad Radiol       Date:  2009-12-11       Impact factor: 3.173

8.  Breast cancer manifested by hematologic disorders.

Authors:  Takashi Ishikawa; Daisuke Shimizu; Ayako Kito; Ikuko Ota; Takeshi Sasaki; Mikiko Tanabe; Akimitsu Yamada; Hitoshi Arioka; Satoru Shimizu; Junichi Wakasugi; Ryutaro Mori; Takashi Chishima; Yasushi Ichikawa; Itaru Endo
Journal:  J Thorac Dis       Date:  2012-12       Impact factor: 2.895

9.  Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging.

Authors:  Seiko Kuroki-Suzuki; Yoshifumi Kuroki; Katsuhiro Nasu; Shigeru Nawano; Noriyuki Moriyama; Masatoshi Okazaki
Journal:  Magn Reson Med Sci       Date:  2007       Impact factor: 2.471

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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  7 in total

1.  Diffusion-weighted magnetic resonance imaging of breast lesions: the influence of different fat-suppression techniques on quantitative measurements and their reproducibility.

Authors:  P Mürtz; M Tsesarskiy; A Kowal; F Träber; J Gieseke; W A Willinek; C C Leutner; A Schmiedel; H H Schild
Journal:  Eur Radiol       Date:  2014-06-05       Impact factor: 5.315

2.  Contribution of Diffusion-Weighted Imaging and ADC Values to Papillary Breast Lesions.

Authors:  Wenjie Lv; Dawen Zheng; Wenbin Guan; Ping Wu
Journal:  Front Oncol       Date:  2022-06-30       Impact factor: 5.738

3.  Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors.

Authors:  Paolo Belli; Melania Costantini; Enida Bufi; Giuseppe Giovanni Giardina; Pierluigi Rinaldi; Gianluca Franceschini; Lorenzo Bonomo
Journal:  Radiol Med       Date:  2014-08-06       Impact factor: 3.469

Review 4.  Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications.

Authors:  Savannah C Partridge; Elizabeth S McDonald
Journal:  Magn Reson Imaging Clin N Am       Date:  2013-06-10       Impact factor: 2.266

5.  Multiparametric evaluation of breast lesions using PET-MRI: initial results and future perspectives.

Authors:  Almir G V Bitencourt; Eduardo N P Lima; Rubens Chojniak; Elvira F Marques; Juliana A Souza; Wesley P Andrade; Marcos D Guimarães
Journal:  Medicine (Baltimore)       Date:  2014-11       Impact factor: 1.889

6.  Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-10-15       Impact factor: 4.430

7.  Diffusion-Weighted Imaging in 3.0 Tesla Breast MRI: Diagnostic Performance and Tumor Characterization Using Small Subregions vs. Whole Tumor Regions of Interest.

Authors:  Otso Arponen; Otso Arponent; Mazen Sudah; Amro Masarwah; Mikko Taina; Suvi Rautiainen; Mervi Könönen; Reijo Sironen; Veli-Matti Kosma; Anna Sutela; Juhana Hakumäki; Ritva Vanninen
Journal:  PLoS One       Date:  2015-10-12       Impact factor: 3.240

  7 in total

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