Literature DB >> 32228293

Kinetic Heterogeneity of Breast Cancer Determined Using Computer-aided Diagnosis of Preoperative MRI Scans: Relationship to Distant Metastasis-Free Survival.

Jin You Kim1, Jin Joo Kim1, Lee Hwangbo1, Hie Bum Suh1, Suk Kim1, Ki Seok Choo1, Kyung Jin Nam1, Taewoo Kang1.   

Abstract

Background Higher peak enhancement and washout component values measured on preoperative breast MRI scans with computer-aided diagnosis (CAD) are presumed to be associated with worse recurrence-free survival. Purpose To investigate whether CAD-extracted kinetic features of breast cancer and the heterogeneity of these features at preoperative MRI are associated with distant metastasis-free survival in women with invasive breast cancer. Materials and Methods Consecutive women with newly diagnosed invasive breast cancer who underwent preoperative MRI were retrospectively evaluated between 2011 and 2012. A commercially available CAD system was used to extract the peak enhancement and delayed enhancement profiles of each breast cancer case from preoperative MRI data. The kinetic heterogeneity of these features (a measure of heterogeneity in the proportions of tumor pixels with delayed washout, plateau, and persistent components within a tumor) was calculated to evaluate intratumoral heterogeneity. Cox proportional hazards models were used to investigate the associations between CAD-extracted kinetic features and distant metastasis-free survival after adjusting for clinical-pathologic factors. Results A total of 276 consecutive women (mean age, 53 years) were evaluated. In 28 of 276 (10.1%) women, distant metastasis developed at a median follow-up of 79 months. A higher degree of kinetic heterogeneity was observed in women with distant metastases than in those without distant metastases (mean, 0.70 ± 0.2 vs 0.43 ± 0.3; P < .001). Multivariable Cox proportional hazards analysis revealed that a higher degree of kinetic heterogeneity (hazard ratio [HR], 19.2; 95% confidence interval [CI]: 4.2, 87.1; P < .001), higher peak enhancement (HR, 1.001; 95% CI: 1.000, 1.002; P = .045), the presence of lymphovascular invasion (HR, 3.3; 95% CI: 1.5, 7.5; P = .004), and a higher histologic grade (ie, grade 3) (HR, 2.2; 95% CI: 1.0, 4.9; P = .044) were associated with worse distant metastasis-free survival. Conclusion Higher values of kinetic heterogeneity and peak enhancement as determined with computer-aided diagnosis of preoperative MRI were associated with worse distant metastasis-free survival in women with invasive breast cancer. © RSNA, 2020 See also the editorial by El Khouli and Jacobs in this issue.

Entities:  

Year:  2020        PMID: 32228293     DOI: 10.1148/radiol.2020192039

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


  8 in total

1.  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

Review 2.  Mucoepidermoid carcinoma of the breast: A case report and literature review focused on radiological findings.

Authors:  Seongjun Bak; Hye Young Choi; Jeong-Hee Lee; Jae Beom Na; Dae Seob Choi; Jae Min Cho; Ho Cheol Choi; Mi Jung Park; Ji Eun Kim; Hwa Seon Shin; Jung Ho Won; Ju-Yeon Kim; Jae-Myung Kim
Journal:  Medicine (Baltimore)       Date:  2022-07-01       Impact factor: 1.817

3.  Development and Validation of an MRI Radiomics-Based Signature to Predict Histological Grade in Patients with Invasive Breast Cancer.

Authors:  Shihui Wang; Yi Wei; Zhouli Li; Jingya Xu; Yunfeng Zhou
Journal:  Breast Cancer (Dove Med Press)       Date:  2022-10-14

4.  Measurement of Perfusion Heterogeneity within Tumor Habitats on Magnetic Resonance Imaging and Its Association with Prognosis in Breast Cancer Patients.

Authors:  Hwan-Ho Cho; Haejung Kim; Sang Yu Nam; Jeong Eon Lee; Boo-Kyung Han; Eun Young Ko; Ji Soo Choi; Hyunjin Park; Eun Sook Ko
Journal:  Cancers (Basel)       Date:  2022-04-07       Impact factor: 6.575

5.  Contrast enhanced ultrasound quantitative parameters for assessing neoadjuvant chemotherapy response in patients with locally advanced breast cancer.

Authors:  Anant Sharma; Shabnam Bhandari Grover; Chinta Mani; Charanjeet Ahluwalia
Journal:  Br J Radiol       Date:  2021-04-16       Impact factor: 3.039

6.  Machine Learning Models That Integrate Tumor Texture and Perfusion Characteristics Using Low-Dose Breast Computed Tomography Are Promising for Predicting Histological Biomarkers and Treatment Failure in Breast Cancer Patients.

Authors:  Hyun-Soo Park; Kwang-Sig Lee; Bo-Kyoung Seo; Eun-Sil Kim; Kyu-Ran Cho; Ok-Hee Woo; Sung-Eun Song; Ji-Young Lee; Jaehyung Cha
Journal:  Cancers (Basel)       Date:  2021-11-29       Impact factor: 6.639

7.  Impact of Preoperative Magnetic Resonance Imaging on Surgical Outcomes in Women with Invasive Breast Cancer: A Systematic Review and Meta-Analysis.

Authors:  Li Li; Qinghong Zhang; Chunrui Qian; Huien Lin
Journal:  Int J Clin Pract       Date:  2022-08-25       Impact factor: 3.149

8.  Characterization of breast cancer subtypes based on quantitative assessment of intratumoral heterogeneity using dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging.

Authors:  Jin Joo Kim; Jin You Kim; Hie Bum Suh; Lee Hwangbo; Nam Kyung Lee; Suk Kim; Ji Won Lee; Ki Seok Choo; Kyung Jin Nam; Taewoo Kang; Heeseung Park
Journal:  Eur Radiol       Date:  2021-08-04       Impact factor: 5.315

  8 in total

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