ASSESSMENT OF BACKGROUND PARENCHYMAL ENHANCEMENT AT DYNAMIC CONTRAST-ENHANCED MRI IN PREDICTING BREAST CANCER RECURRENCE RISK

Main Article Content

Muhammad Imran Farid
Muhammad Taha Khalil
Dr. Nada Ullah
Amanullah Khan
Muhammad Imran Siddiqui
Kamran Illahi Memon
Syed Abdullah Haider
Naheed Akhtar

Keywords

breast cancer recurrence, DCE MRI, BPE, risk stratification, personalized treatment

Abstract

Introduction: Potential as a prognostic tool for breast cancer recurrence risk is the evaluation of background parenchymal enhancement (BPE) using dynamic contrast-enhanced (DCE) MRI. BPE has been identified as a possible marker of therapy responsiveness and disease aggressiveness, reflecting the vascular and hormonal milieu of breast tissue. This research uses information from DCE-MRI scans to assess how well BPE values predict the probability of breast cancer recurrence.


Methodology: The retrospective cohort study was conducted and included fifty eligible participants, diagnosed with breast cancer and undergoing MRI between January and December 2023. Data on demographics, clinical features, and MRI results were collected from medical records of a Tertiary Care hospital in Pakistan. BPE was quantitatively assessed using an in-house algorithm, and statistical analysis included descriptive statistics, logistic regression, and Cox proportional hazards regression. MRI protocols followed standard procedures. The study aimed to assess the prognostic value of BPE in guiding personalized breast cancer treatment and risk stratification.


Results: The research highlights the wide age representation with an average participant age of 48.5 years (±7.2 years). The fact that premenopausal state accounted for 65% of participants is noteworthy and highlights the importance of hormonal status in breast cancer research and treatment approaches. There was a significant degree of heterogeneity in the tumor's size and grade, with an average tumor size of 3.8 cm (±1.2 cm) and a heterogeneous distribution across grades. Treatment choices were guided by the results of a hormone receptor status study, which showed prevalence rates of estrogen receptor (ER) positive at 37%, progesterone receptor (PR) positive at 52%, and HER2 positive at 11%. The majority of treatment options for breast cancer were surgery, chemotherapy, and radiation therapy, which demonstrated the interdisciplinary nature of breast cancer care. The results of the follow-up showed a 20% recurrence rate, underscoring the significance of risk stratification according to Oncotype DX scores. greater BPE readings were linked to a greater likelihood of high-risk recurrence scores. The results of MRI, in particular, showed a substantial correlation with recurrence risk. The predictive efficacy of BPE evaluation was further highlighted by Cox proportional hazards regression analysis, indicating its potential prognostic relevance in clinical practice.


Conclusion: Our research shows a strong relationship between breast cancer recurrence risk and BPE in DCE-MRI. We discovered significant differences in tumor features, hormone receptor status, and treatment modalities after analyzing a heterogeneous sample, underscoring the difficulty in managing breast cancer. Elevated BPE levels were linked to heightened chances of high-risk recurrence scores, indicating the predictive significance of BPE evaluation for customized therapy and risk classification. Recurrence prediction and patient outcomes may be improved by incorporating BPE examination into clinical practice.

Abstract 145 | PDF Downloads 41

References

1. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394-424.
2. Francies FZ, Hull R, Khanyile R, Dlamini Z. Breast cancer in low-middle income countries: abnormality in splicing and lack of targeted treatment options. American journal of cancer research. 2020;10(5):1568. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269781/
3. Yoda S, Theeke LA. A scoping review of factors contributing to late-stage diagnosis of breast cancer in racial and ethnic minority (African American and Hispanic) women. SAGE Open. 2022 Dec;12(4):21582440221140297. https://journals.sagepub.com/doi/pdf/10.1177/21582440221140297
4. Aziz Z, Naseer H, Altaf A. Challenges in access to new therapeutic agents: Marginalized patients with cancer in Pakistan and the need for new guidelines. JCO Global Oncology. 2022 Feb;8:e2100132. https://ascopubs.org/doi/pdfdirect/10.1200/GO.21.00132
5. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. https://acsjournals.onlinelibrary.wiley.com/doi/pdf/10.3322/caac.21660
6. DeSantis CE, Ma J, Gaudet MM, Newman LA, Miller KD, Goding Sauer A, Jemal A, Siegel RL. Breast cancer statistics, 2019. CA: a cancer journal for clinicians. 2019 Nov;69(6):438-51. https://acsjournals.onlinelibrary.wiley.com/doi/pdf/10.3322/caac.21583
7. Giess CS, Yeh ED, Raza S, Birdwell RL. BPE at breast MR imaging: normal patterns, diagnostic challenges, and potential for false-positive and false-negative interpretation. Radiographics. 2014 Jan;34(1):234-47. https://mrionline.com/wp-content/uploads/sfwd-topic/rg.341135034.pdf
8. King V, Brooks JD, Bernstein JL, Reiner AS, Pike MC, Morris EA. BPE at breast MR imaging and breast cancer risk. Radiology. 2011 Jul;260(1):50-60. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939979/
9. You C, Kaiser AK, Baltzer P, Krammer J, Gu Y, Peng W, Schönberg SO, Kaiser CG. The assessment of BPE in a high-risk population: what causes BPE?. Translational Oncology. 2018 Apr 1;11(2):243-9.
10. Nisar A, Siddiqi MN, Ur Rehman N, Ur Rahman R. BREAST CANCER;: FREQUENCY OF RISK FACTORS. The Professional Medical Journal. 2014 Dec 10;21(06):1128-32.
11. Gulzar F, Akhtar MS, Sadiq R, Bashir S, Jamil S, Baig SM. Identifying the reasons for delayed presentation of Pakistani breast cancer patients at a tertiary care hospital. Cancer management and research. 2019 Jan 29:1087-96.
12. Khokher S, Qureshi W, Mahmood S, Saleem A, Mahmud S. Knowledge, attitude and preventive practices of women for breast cancer in the educational institutions of Lahore, Pakistan. Asian Pac J Cancer Prev. 2011 Jan 1;12(9):2419-.
13. Royaidar J, Khalid H, Fatima H. Development of Novel Biomarkers for Early Detection of Cancer. Innovative Research in Applied, Biological and Chemical Sciences. 2023 Jul 1;1(1):9-13. https://irabcs.com/ojs/article/download/9/7
14. Malik SS, Masood N, Asif M, Ahmed P, Shah ZU, Khan JS (2019) Expressional analysis of MLH1 and MSH2 in breast cancer. Curr Probl Cancer 43(2):97–105
15. Khan Y, Khan NU, Ali I, Khan S, Khan AU, Iqbal A, Adams BD. Significant association of BRCA1 (rs1799950), BRCA2 (rs144848) and TP53 (rs1042522) polymorphism with breast cancer risk in Pashtun population of Khyber Pakhtunkhwa, Pakistan. Molecular Biology Reports. 2023 Jul;50(7):6087-96.
16. American Cancer Society. Breast Cancer Facts & Figures 2021-2022. Atlanta: American Cancer Society, Inc.
17. Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98(19):10869-10874. https://www.pnas.org/doi/full/10.1073/pnas.191367098
18. Rastelli F, Crispino S. Factors predictive of response to hormone therapy in breast cancer. Tumori Journal. 2008 May;94(3):370-83.
19. Abbas S, Linseisen J, Slanger T, Kropp S, Mutschelknauss EJ, Flesch-Janys D, Chang-Claude J. Serum 25-hydroxyvitamin D and risk of post-menopausal breast cancer—results of a large case–control study. Carcinogenesis. 2008 Jan 1;29(1):93-9.
20. Olopade OI, Grushko TA, Nanda R, Huo D. Advances in breast cancer: pathways to personalized medicine. Clinical Cancer Research. 2008 Dec 15;14(24):7988-99.
21. Abdel-Rahman O. Prognostic value of primary tumor size in patients with operable breast cancer. BMC Surg. 2018;18(1):1-5.
22. Tambasco M, Magliocco AM. Relationship between tumor grade and computed architectural complexity in breast cancer specimens. Human pathology. 2008 May 1;39(5):740-6.
23. Li Z, Zhang L, Zhao Y, et al. Tumor size and survival in breast cancer: A meta-analysis. Medicine (Baltimore). 2019;98(46):e18007.
24. Anderson WF, Chatterjee N, Ershler WB, Brawley OW. Estrogen receptor breast cancer phenotypes in the Surveillance, Epidemiology, and End Results database. Breast cancer research and treatment. 2002 Nov;76:27-36. https://link.springer.com/article/10.1023/A:1020299707510
25. Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, Fleming T, Eiermann W, Wolter J, Pegram M, Baselga J. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. New England journal of medicine. 2001 Mar 15;344(11):783-92.
26. Wood DE. National Comprehensive Cancer Network (NCCN) clinical practice guidelines for lung cancer screening. Thoracic surgery clinics. 2015 May 1;25(2):185-97.
27. Rudnicka H, Niwińska A, Murawska M. Breast cancer leptomeningeal metastasis—the role of multimodality treatment. Journal of neuro-oncology. 2007 Aug;84:57-62.
28. Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, Geyer Jr CE, Dees EC, Goetz MP, Olson Jr JA, Lively T. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. New England Journal of Medicine. 2018 Jul 12;379(2):111-21.
29. King V, Brooks JD, Bernstein JL, Reiner AS, Pike MC, Morris EA. BPE at breast MR imaging and breast cancer risk. Radiology. 2011 Jul;260(1):50-60.
30. Kuhl CK, Bieling HB, Gieseke J, Kreft BP, Sommer T, Lutterbey G, Schild HH. Healthy premenopausal breast parenchyma in DCE MR imaging of the breast: normal contrast medium enhancement and cyclical-phase dependency. Radiology. 1997 Apr;203(1):137-44. https://pubs.rsna.org/doi/abs/10.1148/radiology.203.1.9122382
31. Giess CS, Yeh ED, Raza S, Birdwell RL. BPE at breast MR imaging: normal patterns, diagnostic challenges, and potential for false-positive and false-negative interpretation. Radiographics. 2014 Jan;34(1):234-47.
32. Saleh GA, Batouty NM, Gamal A, Elnakib A, Hamdy O, Sharafeldeen A, Mahmoud A, Ghazal M, Yousaf J, Alhalabi M, AbouEleneen A. Impact of imaging biomarkers and AI on breast cancer management: A brief review. Cancers. 2023 Oct 30;15(21):5216.
33. Cho GY, Moy L, Kim SG, Baete SH, Moccaldi M, Babb JS, Sodickson DK, Sigmund EE. Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors. European radiology. 2016 Aug;26:2547-58.
34. Morris EA, Comstock CE, Lee CH, Lehman CD, Ikeda DM, Newstead GM. ACR BI-RADS® magnetic resonance imaging. ACR BI-RADS® atlas, breast imaging reporting and data system. 2013;5.

Most read articles by the same author(s)

1 2 > >>