Literature DB >> 28273747

Histogram analysis of volume-based apparent diffusion coefficient in breast cancer.

Ga Eun Park1, Sung Hun Kim1, Eun Jeong Kim1, Bong Joo Kang1, Mi Sun Park2.   

Abstract

Background Breast cancer is a heterogeneous disease. Recent studies showed that apparent diffusion coefficient (ADC) values have various association with tumor aggressiveness and prognosis. Purpose To evaluate the value of histogram analysis of ADC values obtained from the whole tumor volume in invasive ductal cancer (IDC) and ductal carcinoma in situ (DCIS). Material and Methods This retrospective study included 201 patients with confirmed DCIS (n = 37) and IDC (n = 164). The IDC group was divided into two groups based on the presence of a DCIS component: IDC-DCIS (n = 76) and pure IDC (n = 88). All patients underwent preoperative breast magnetic resonance imaging (MRI) with diffusion-weighted images at 3.0 T. Histogram parameters of cumulative ADC values, skewness, and kurtosis were calculated and statistically analyzed. Results The differences between DCIS, IDC-DCIS, and pure IDC were significant in all percentiles of ADC values, in descending order of DCIS, IDC-DCIS, and pure IDC. IDC showed significantly lower ADC values than DCIS, and ADC50 was the best indicator for discriminating IDC from DCIS, with a threshold of 1.185 × 10-3 mm2/s (sensitivity of 82.9%, specificity of 75.7%). However, multivariate analysis of obtained ADC values showed no significant differences between DCIS, IDC-DCIS, and pure IDC ( P > 0.05). Conclusion Volume-based ADC values showed association with heterogeneity of breast cancer. However, there was no additional diagnostic performance in histogram analysis for differentiating between DCIS, IDC-DCIS, and pure IDC.

Entities:  

Keywords:  Breast cancer; apparent diffusion coefficient (ADC); diffusion-weighted imaging (DWI); magnetic resonance imaging (MRI)

Mesh:

Year:  2017        PMID: 28273747     DOI: 10.1177/0284185117694507

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  7 in total

1.  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

2.  Diffusional kurtosis imaging for differentiation of additional suspicious lesions on preoperative breast MRI of patients with known breast cancer.

Authors:  Vivian Youngjean Park; Sungheon G Kim; Eun-Kyung Kim; Hee Jung Moon; Jung Hyun Yoon; Min Jung Kim
Journal:  Magn Reson Imaging       Date:  2019-07-16       Impact factor: 2.546

3.  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

4.  Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging with Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers.

Authors:  Joao V Horvat; Aditi Iyer; Elizabeth A Morris; Aditya Apte; Blanca Bernard-Davila; Danny F Martinez; Doris Leithner; Olivia M Sutton; R Elena Ochoa-Albiztegui; Dilip Giri; Katja Pinker; Sunitha B Thakur
Journal:  Contrast Media Mol Imaging       Date:  2019-11-22       Impact factor: 3.161

5.  Pure Ductal Carcinoma In Situ of the Breast: Analysis of 270 Consecutive Patients Treated in a 9-Year Period.

Authors:  Corrado Chiappa; Alice Bonetti; Giulio Jad Jaber; Valentina De Berardinis; Veronica Bianchi; Francesca Rovera
Journal:  Cancers (Basel)       Date:  2021-01-23       Impact factor: 6.639

6.  Whole-lesion histogram analysis of apparent diffusion coefficient for the assessment of non-mass enhancement lesions on breast MRI.

Authors:  Natsuko Kunimatsu; Akira Kunimatsu; Yoshihiro Uchida; Ichiro Mori; Shigeru Kiryu
Journal:  J Clin Imaging Sci       Date:  2022-03-23

7.  The Utility of ADC First-Order Histogram Features for the Prediction of Metachronous Metastases in Rectal Cancer: A Preliminary Study.

Authors:  Bianca Boca Petresc; Cosmin Caraiani; Loredana Popa; Andrei Lebovici; Diana Sorina Feier; Carmen Bodale; Mircea Marian Buruian
Journal:  Biology (Basel)       Date:  2022-03-16
  7 in total

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