Literature DB >> 29165847

Breast lesion characterization using whole-lesion histogram analysis with stretched-exponential diffusion model.

Chunling Liu1, Kun Wang2, Xiaodan Li1, Jine Zhang1, Jie Ding3, Karl Spuhler3, Timothy Duong4, Changhong Liang1, Chuan Huang4,5,3.   

Abstract

BACKGROUND: Diffusion-weighted imaging (DWI) has been studied in breast imaging and can provide more information about diffusion, perfusion and other physiological interests than standard pulse sequences. The stretched-exponential model has previously been shown to be more reliable than conventional DWI techniques, but different diagnostic sensitivities were found from study to study.
PURPOSE: This work investigated the characteristics of whole-lesion histogram parameters derived from the stretched-exponential diffusion model for benign and malignant breast lesions, compared them with conventional apparent diffusion coefficient (ADC), and further determined which histogram metrics can be best used to differentiate malignant from benign lesions. STUDY TYPE: This was a prospective study. POPULATION: Seventy females were included in the study. FIELD STRENGTH/SEQUENCE: Multi-b value DWI was performed on a 1.5T scanner. ASSESSMENT: Histogram parameters of whole lesions for distributed diffusion coefficient (DDC), heterogeneity index (α), and ADC were calculated by two radiologists and compared among benign lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma confirmed by pathology. STATISTICAL TESTS: Nonparametric tests were performed for comparisons among invasive carcinoma, DCIS, and benign lesions. Comparisons of receiver operating characteristic (ROC) curves were performed to show the ability to discriminate malignant from benign lesions.
RESULTS: The majority of histogram parameters (mean/min/max, skewness/kurtosis, 10-90th percentile values) from DDC, α, and ADC were significantly different among invasive carcinoma, DCIS, and benign lesions. DDC10% (area under curve [AUC] = 0.931), ADC10% (AUC = 0.893), and αmean (AUC = 0.787) were found to be the best metrics in differentiating benign from malignant tumors among all histogram parameters derived from ADC and α, respectively. The combination of DDC10% and αmean , using logistic regression, yielded the highest sensitivity (90.2%) and specificity (95.5%). DATA
CONCLUSION: DDC10% and αmean derived from the stretched-exponential model provides more information and better diagnostic performance in differentiating malignancy from benign lesions than ADC parameters derived from a monoexponential model. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1701-1710.
© 2017 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  apparent diffusion coefficient; breast neoplasm; diffusion-weighted magnetic resonance imaging; distributed diffusion coefficient; histogram analysis; stretched-exponential diffusion

Mesh:

Year:  2017        PMID: 29165847     DOI: 10.1002/jmri.25904

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  9 in total

1.  Evaluation of microvascular invasion of hepatocellular carcinoma using whole-lesion histogram analysis with the stretched-exponential diffusion model.

Authors:  Hongxiang Li; LiLi Wang; Jing Zhang; Qing Duan; Yikai Xu; Yunjing Xue
Journal:  Br J Radiol       Date:  2022-01-07       Impact factor: 3.629

2.  Parsimonious modeling of skeletal muscle perfusion: Connecting the stretched exponential and fractional Fickian diffusion.

Authors:  David A Reiter; Fatemeh Adelnia; Donnie Cameron; Richard G Spencer; Luigi Ferrucci
Journal:  Magn Reson Med       Date:  2021-03-16       Impact factor: 3.737

3.  Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

Authors:  Masaoki Kusunoki; Kazufumi Kikuchi; Osamu Togao; Koji Yamashita; Daichi Momosaka; Yoshitomo Kikuchi; Daisuke Kuga; Nobuhiro Hata; Masahiro Mizoguchi; Koji Iihara; Satoshi O Suzuki; Toru Iwaki; Yuta Akamine; Akio Hiwatashi
Journal:  Neuroradiology       Date:  2020-05-18       Impact factor: 2.804

4.  Based on Histogram Analysis: ADCaqp Derived from Ultra-high b-Value DWI could be a Non-invasive Specific Biomarker for Rectal Cancer Prognosis.

Authors:  Guangwen Zhang; Wanling Ma; Hui Dong; Jun Shu; Weihuan Hou; Yong Guo; Mian Wang; Xiaocheng Wei; Jialiang Ren; Jinsong Zhang
Journal:  Sci Rep       Date:  2020-06-23       Impact factor: 4.379

5.  The volumetric-tumour histogram-based analysis of intravoxel incoherent motion and non-Gaussian diffusion MRI: association with prognostic factors in HER2-positive breast cancer.

Authors:  Chao You; Jianwei Li; Wenxiang Zhi; Yanqiong Chen; Wentao Yang; Yajia Gu; Weijun Peng
Journal:  J Transl Med       Date:  2019-07-02       Impact factor: 5.531

6.  Comparison of the Diagnostic Value of Mono-exponential, Bi-exponential, and Stretched Exponential Signal Models in Diffusion-weighted MR Imaging for Differentiating Benign and Malignant Hepatic Lesions.

Authors:  Yoshifumi Noda; Satoshi Goshima; Keita Fujimoto; Yuta Akamine; Kimihiro Kajita; Nobuyuki Kawai; Masayuki Matsuo
Journal:  Magn Reson Med Sci       Date:  2020-03-12       Impact factor: 2.471

Review 7.  Diffusion Breast MRI: Current Standard and Emerging Techniques.

Authors:  Ashley M Mendez; Lauren K Fang; Claire H Meriwether; Summer J Batasin; Stéphane Loubrie; Ana E Rodríguez-Soto; Rebecca A Rakow-Penner
Journal:  Front Oncol       Date:  2022-07-08       Impact factor: 5.738

8.  Quantitative differentiation of malignant and benign thyroid nodules with multi-parameter diffusion-weighted imaging.

Authors:  Xiang Zhu; Jia Wang; Yan-Chun Wang; Ze-Feng Zhu; Jian Tang; Xiao-Wei Wen; Ying Fang; Jun Han
Journal:  World J Clin Cases       Date:  2022-08-26       Impact factor: 1.534

9.  Evaluation of Monoexponential, Stretched-Exponential and Intravoxel Incoherent Motion MRI Diffusion Models in Early Response Monitoring to Neoadjuvant Chemotherapy in Patients With Breast Cancer-A Preliminary Study.

Authors:  Zyad M Almutlaq; Daniel J Wilson; Sarah E Bacon; Nisha Sharma; Samuel Stephens; Tatendashe Dondo; David L Buckley
Journal:  J Magn Reson Imaging       Date:  2022-02-14       Impact factor: 5.119

  9 in total

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