Literature DB >> 28253106

Computer-aided Diagnosis-generated Kinetic Features of Breast Cancer at Preoperative MR Imaging: Association with Disease-free Survival of Patients with Primary Operable Invasive Breast Cancer.

Jin Joo Kim1, Jin You Kim1, Hyun Jung Kang1, Jong Ki Shin1, Taewoo Kang1, Seok Won Lee1, Young Tae Bae1.   

Abstract

Purpose To retrospectively investigate the relationship between the kinetic features of breast cancer assessed with computer-aided diagnosis (CAD) at preoperative magnetic resonance (MR) imaging and disease-free survival in patients with primary operable invasive breast cancer. Materials and Methods This retrospective study was approved by the institutional review board. The requirement to obtain informed consent was waived. The authors identified 329 consecutive women (mean age, 52.9 years; age range, 32-88 years) with newly diagnosed invasive breast cancer who had undergone preoperative MR imaging and surgery between January 2012 and February 2013. All MR images were retrospectively reviewed by using a commercially available CAD system, and the following kinetic parameters were noted for each lesion: peak enhancement (highest pixel signal intensity in the first series obtained after administration of contrast material), angio-volume (total volume of the enhancing lesion), and delayed enhancement profiles (the proportions of washout, plateau, and persistently enhancing component within a tumor). Cox proportional hazards modeling was used to identify the relationship between CAD-generated kinetics and disease-free survival after adjusting for clinical-pathologic variables. Results A total of 36 recurrences developed at a median follow-up of 50 months (range, 15-55 months). CAD-measured peak enhancement at preoperative MR imaging enabled differentiation between patients with and patients without recurrence (area under the receiver operating characteristic curve = 0.728; 95% confidence interval [CI]: 0.676, 0.775; P < .001). Multivariate Cox analysis showed that a higher peak enhancement (hazard ratio [HR] = 1.001; 95% CI: 1.000, 1.002; P = .004), a higher washout component (HR = 1.029; 95% CI: 1.005, 1.054; P = .017), and lymphovascular invasion at histopathologic examination (HR = 3.011; 95% CI: 1.302, 6.962; P = .010) were associated with poorer disease-free survival. Conclusion Higher values of CAD-measured peak enhancement and washout component at preoperative MR imaging were significantly associated with poorer disease-free survival of patients with primary operable breast cancer. © RSNA, 2017.

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Year:  2017        PMID: 28253106     DOI: 10.1148/radiol.2017162079

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  12 in total

1.  Association of distant recurrence-free survival with algorithmically extracted MRI characteristics in breast cancer.

Authors:  Maciej A Mazurowski; Ashirbani Saha; Michael R Harowicz; Elizabeth Hope Cain; Jeffrey R Marks; P Kelly Marcom
Journal:  J Magn Reson Imaging       Date:  2019-01-22       Impact factor: 4.813

2.  A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.

Authors:  Ashirbani Saha; Michael R Harowicz; Weiyao Wang; Maciej A Mazurowski
Journal:  J Cancer Res Clin Oncol       Date:  2018-02-09       Impact factor: 4.553

3.  Use of MRI for Personalized Treatment of More Aggressive Tumors.

Authors:  Riham H El Khouli; Michael A Jacobs
Journal:  Radiology       Date:  2020-03-31       Impact factor: 11.105

4.  A retrospective review of MRI features associated with metastasis-free survival in women with breast cancer: focusing on skin thickening and skin enhancement.

Authors:  Valentine Mberu; Jennifer McFarlane; E Jane Macaskill; Andrew Evans
Journal:  Br J Radiol       Date:  2021-10-05       Impact factor: 3.039

5.  Kinetic volume analysis on dynamic contrast-enhanced MRI of triple-negative breast cancer: associations with survival outcomes.

Authors:  Yoko Hayashi; Hiroko Satake; Satoko Ishigaki; Rintaro Ito; Mariko Kawamura; Hisashi Kawai; Shingo Iwano; Shinji Naganawa
Journal:  Br J Radiol       Date:  2019-12-16       Impact factor: 3.039

6.  Kinetic Features of Invasive Breast Cancers on Computer-Aided Diagnosis Using 3T MRI Data: Correlation with Clinical and Pathologic Prognostic Factors.

Authors:  Sung Eun Song; Kyu Ran Cho; Bo Kyoung Seo; Ok Hee Woo; Seung Pil Jung; Deuk Jae Sung
Journal:  Korean J Radiol       Date:  2019-03       Impact factor: 3.500

7.  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

8.  Three-dimensional radiomics of triple-negative breast cancer: Prediction of systemic recurrence.

Authors:  Jieun Koh; Eunjung Lee; Kyunghwa Han; Sujeong Kim; Dong-Kyu Kim; Jin Young Kwak; Jung Hyun Yoon; Hee Jung Moon
Journal:  Sci Rep       Date:  2020-02-19       Impact factor: 4.379

9.  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.

Authors:  Sang Yu Nam; Eun Sook Ko; Yaeji Lim; Boo-Kyung Han; Eun Young Ko; Ji Soo Choi; Jeong Eon Lee
Journal:  PLoS One       Date:  2018-04-12       Impact factor: 3.240

10.  Automated volumetric radiomic analysis of breast cancer vascularization improves survival prediction in primary breast cancer.

Authors:  Matthias Dietzel; Rüdiger Schulz-Wendtland; Stephan Ellmann; Ramy Zoubi; Evelyn Wenkel; Matthias Hammon; Paola Clauser; Michael Uder; Ingo B Runnebaum; Pascal A T Baltzer
Journal:  Sci Rep       Date:  2020-02-28       Impact factor: 4.379

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