Öz
Aim: The aim of this study is to research the seperation benign and malign breast masses with diffusion-weighted magnetic resonance imaging (MRI).
Material and Method: 66 patients (26 benign, 40 malign) who have taken MRG for any purpose have been incorporated to the research. Rutin contrast enhancement dinamic MRI and diffusion weighted imaging (DWI) applied on 66 lesions. Contrast enhancement MRI and DWI charecteristics of lesions have been evaluated as retrospective for each lesion. Kinetic curves of contrast enhancement pattern of lesions have been evaluated in accordance with BI-RADS classifications. Apparent diffusion coefficient (ADC) measurements have been obtained numerical from DWI's at work stations. Also, ADC values of normal fibrogranduler tissue (NFT) at opposite breast of each patient have been measured. ADC values of NFT, benign and malign lesions have been compared.
Results: Avarage ADC values of benign and malign lesions, NFT in benign and malign patients, were respectively: 1.535x10-3 mm2/s, 1.169x10-3 mm2/s, 1.879x10-3 mm2/s, 1.852x10-3 mm2/s. Avarage ADC values of NFT were statistically significant higher than values of bening and malign lesions. Avarage ADC values of malign lesions were statistically significant lower than ADC rates of bening lesions (p<0.001).
Conclusion: Distinguish between bening and malign breast lesions with ADC values is an auxiliary paremeter which can be used together with dinamic contrast enhancement curves of lesions and morphological criterias. In our study, we found that the use of DWI in addition to contrast-enhanced MRI can easily distinguish between NFT, benign and malignant masses. We suggest routinely usage of DWI during breast MRI.
Anahtar Kelimeler
Magnetic resonance imaging diffusion breast cancer malign benign
Etik Beyan
Ethical approved for the study was obtained from Dicle University Faculty of Medicine, Non-Interventional Clinical Research Ethics Committee (Ethics Committee approval no: 12.06.2015/346).
Kaynakça
- Parkin DM, Bray FI, Devesa SS. Cancer burden in the year 2000. The global picture. Eur J Cancer. 2001;37:S4-66.
- Rohan TZ, Mandel JL, Yang HY, et al. Identifying subsets of cancer patients with an increased risk of developing cutaneous melanoma: a surveillance, epidemiology, and end results-based analysis. JID Innov. 2024;5:100323.
- Leung JWT. Screening mammography reduced morbidity of breast cancer treatment. Am J Roentgenol. 2005;184:1508-9.
- Berg WA. Tailored supplemental screening for breast cancer: what now and what next?. AJR Am J Roentgenol. 2009;192:390-9.
- Wolfe JN. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer. 1976;37:2486-92.
- Jamshidi MH, Karami A, Keshavarz A, et al. Magnetic resonance elastography for breast cancer diagnosis through the assessment of tissue biomechanical properties. Health Sci Rep. 2024;7:e70253.
- Kolb TM, Lichy J, Newhouse JH. Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology. 2002;225:165-75.
- Goscin CP, Berman CG, Clark RA. Magnetic resonance imaging of the breast. Cancer Control. 2001;8:399-406.
- Illustrated breast imaging reporting and data system (BI-RADS). 5th edition. American College of Radiology (ACR), Reston, VA. 2013.
- Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci. 2008;7:23-9.
- Tsushima Y, Takahashi-Taketomi A, Endo K. Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficient (ADC) on 1. 5-T. J Magn Reson Imaging. 2009;30:249-55.
- Englander SA, Ulug AM, Brem R, et al. Diffusion imaging of human breast. NMR Biomed. 1997;10:b348-52.
- Cho E, Baek HJ, Jung EJ, et al. Clinical feasibility of a deep learning approach for conventional and synthetic diffusion-weighted imaging in breast cancer: qualitative and quantitative analyses. Eur J Radiol. 2025;182:111855.
- Sinha S, Lucas-Quesada FA, Sinha U, et al. In vivo diffusion-weighted MRI of the breast: potential for lesion characterization. J Magn Reson Imaging. 2002;15:693-704.
- Chen X, Li WL, Zhang YL, et al. Meta-analysis of quantitativediffusion-weighted MR imaging in the differential diagnosis of breast lesions. BMC Cancer. 2010;10:693.
- Iima M, Honda M, Satake H, et al. Standardization and advancements efforts in breast diffusion-weighted imaging. Jpn J Radiol. 2025;43:347-54.
- Rajagopal V, Lee A, Chung JH, et al. Creating individual-specific biomechanical models of the breast for medical image analysis. Acad Radiol. 2008;15:1425-36.
- Khaled W, Reichling S, Bruhns OT, et al. Ultrasonic strain imaging and reconstructive elastography for biological tissue. Ultrasonics. 2006;44:199-202.
- Luo J, Ying K, Bai J. Elasticity reconstruction for ultrasound elastography using a radial compression: an inverse approach. Ultrasonics. 2006;44:e195-8.
- Havre RH, Elde E, Gilja OH, et al. Freehand real-time elastography: impact of scanning parameters of image quality and in vitro intra and interobserver validations. Ultrasound Med Biol. 2008;34:1638-50.
- Guo Y, Cai YQ, Cai ZL, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 2002;16:172-8.
- Anwar R Padhani, Guoying Liu, Dow Mu-Koh, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations neoplasia. 2009;11:102-25.
- Wenkel W, Geppert C, Uder M, et al. Diffusion-weighted imaging in breast MRI-an easy way to improve specificity. Clinical Woman's Health. 2007;3:28-32.
- Pereira FP, Martins G, Carvalhaes de Oliveira Rde V. Diffusion magnetic resonance imaging of the breast. Magn Reson Imaging Clin N Am. 2011;19:95-110.
- Nicky H.G.M. Peters, Koen L. Vincken, et al. Quantitative Diffusion-Weighted Imaging for differantiation of the benign and malignant breast lesions: The influence of the choice of b-values. J Magn Reson Imaging. 2010;31:1100-5.
- Imamura T, Isomoto I, Sueyoshi E, et al. Diagnostic performance of ADC for Non-mass-like breast lesions on MR imaging. Magn Reson Med Sci. 2010;9:217-25.
- Partridge SC, Demartini WB, Kurland BF, et al. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion-weighted MRI. J Magn Reson Imaging. 2010;31:562-70.
- DelPriore MR, Biswas D, Hippe DS, et al. Breast cancer conspicuity on computed versus acquired high b-value diffusion-weighted MRI. AcadRadiol. 2021;28:1108-17.
- Partridge SC, Steingrimsson J, Newitt DC, et al. Impact of alternate b-value combinations and metrics on the predictive performance and repeatability of diffusion-weighted MRI in breast cancer treatment: results from the ECOG-ACRIN A6698 trial. Tomography. 2022;8:701-17.
- Palle L, Reddy B. Role of diffusion MRI in characterizing benign and malignant breast lesions. Indian J Radiol Imaging. 2009;19:287-90.
- Kul S, Cansu A, Alhan E, et al. Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors. AJR Am J Roentgenol. 2011;196:210-7.
- Tozaki M, Fukuma E. 1H MR spectroscopy and diffusion-weighted imaging of the breast: are they useful tools for characterizing breast lesions before biopsy?. AJR Am J Roentgenol. 2009;193:840-9.
- Luo JD, Liu YY, Zhang XL, Shi LC. Application of diffusion weighted magnetic resonance imaging to differential diagnosis of breast diseases. Ai Zheng. 2007;26:168-71.
- Yabuuchi H, Matsuo Y, Kamitani T, et al. Non-mass-like enhancement on contrast-enhanced breast MR imaging: lesion characterization using combination of dynamic contrast-enhanced and diffusion-weighted MR images. Eur J Radiol. 2010;75:e126-32.
- Choi BB. Effectiveness of ADC difference value on pre-neoadjuvant chemotherapy mri for response evaluation of breast cancer. Technol Cancer Res Treat. 2021;20:15330338211039129.
- Hottat NA, Badr DA, Lecomte S, et al. Value of diffusion-weighted MRI in predicting early response to neoadjuvant chemotherapy of breast cancer: comparison between ROI-ADC and whole-lesion-ADC measurements. Eur Radiol. 2022;32:4067-78.
Öz
Kaynakça
- Parkin DM, Bray FI, Devesa SS. Cancer burden in the year 2000. The global picture. Eur J Cancer. 2001;37:S4-66.
- Rohan TZ, Mandel JL, Yang HY, et al. Identifying subsets of cancer patients with an increased risk of developing cutaneous melanoma: a surveillance, epidemiology, and end results-based analysis. JID Innov. 2024;5:100323.
- Leung JWT. Screening mammography reduced morbidity of breast cancer treatment. Am J Roentgenol. 2005;184:1508-9.
- Berg WA. Tailored supplemental screening for breast cancer: what now and what next?. AJR Am J Roentgenol. 2009;192:390-9.
- Wolfe JN. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer. 1976;37:2486-92.
- Jamshidi MH, Karami A, Keshavarz A, et al. Magnetic resonance elastography for breast cancer diagnosis through the assessment of tissue biomechanical properties. Health Sci Rep. 2024;7:e70253.
- Kolb TM, Lichy J, Newhouse JH. Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology. 2002;225:165-75.
- Goscin CP, Berman CG, Clark RA. Magnetic resonance imaging of the breast. Cancer Control. 2001;8:399-406.
- Illustrated breast imaging reporting and data system (BI-RADS). 5th edition. American College of Radiology (ACR), Reston, VA. 2013.
- Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci. 2008;7:23-9.
- Tsushima Y, Takahashi-Taketomi A, Endo K. Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficient (ADC) on 1. 5-T. J Magn Reson Imaging. 2009;30:249-55.
- Englander SA, Ulug AM, Brem R, et al. Diffusion imaging of human breast. NMR Biomed. 1997;10:b348-52.
- Cho E, Baek HJ, Jung EJ, et al. Clinical feasibility of a deep learning approach for conventional and synthetic diffusion-weighted imaging in breast cancer: qualitative and quantitative analyses. Eur J Radiol. 2025;182:111855.
- Sinha S, Lucas-Quesada FA, Sinha U, et al. In vivo diffusion-weighted MRI of the breast: potential for lesion characterization. J Magn Reson Imaging. 2002;15:693-704.
- Chen X, Li WL, Zhang YL, et al. Meta-analysis of quantitativediffusion-weighted MR imaging in the differential diagnosis of breast lesions. BMC Cancer. 2010;10:693.
- Iima M, Honda M, Satake H, et al. Standardization and advancements efforts in breast diffusion-weighted imaging. Jpn J Radiol. 2025;43:347-54.
- Rajagopal V, Lee A, Chung JH, et al. Creating individual-specific biomechanical models of the breast for medical image analysis. Acad Radiol. 2008;15:1425-36.
- Khaled W, Reichling S, Bruhns OT, et al. Ultrasonic strain imaging and reconstructive elastography for biological tissue. Ultrasonics. 2006;44:199-202.
- Luo J, Ying K, Bai J. Elasticity reconstruction for ultrasound elastography using a radial compression: an inverse approach. Ultrasonics. 2006;44:e195-8.
- Havre RH, Elde E, Gilja OH, et al. Freehand real-time elastography: impact of scanning parameters of image quality and in vitro intra and interobserver validations. Ultrasound Med Biol. 2008;34:1638-50.
- Guo Y, Cai YQ, Cai ZL, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 2002;16:172-8.
- Anwar R Padhani, Guoying Liu, Dow Mu-Koh, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations neoplasia. 2009;11:102-25.
- Wenkel W, Geppert C, Uder M, et al. Diffusion-weighted imaging in breast MRI-an easy way to improve specificity. Clinical Woman's Health. 2007;3:28-32.
- Pereira FP, Martins G, Carvalhaes de Oliveira Rde V. Diffusion magnetic resonance imaging of the breast. Magn Reson Imaging Clin N Am. 2011;19:95-110.
- Nicky H.G.M. Peters, Koen L. Vincken, et al. Quantitative Diffusion-Weighted Imaging for differantiation of the benign and malignant breast lesions: The influence of the choice of b-values. J Magn Reson Imaging. 2010;31:1100-5.
- Imamura T, Isomoto I, Sueyoshi E, et al. Diagnostic performance of ADC for Non-mass-like breast lesions on MR imaging. Magn Reson Med Sci. 2010;9:217-25.
- Partridge SC, Demartini WB, Kurland BF, et al. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion-weighted MRI. J Magn Reson Imaging. 2010;31:562-70.
- DelPriore MR, Biswas D, Hippe DS, et al. Breast cancer conspicuity on computed versus acquired high b-value diffusion-weighted MRI. AcadRadiol. 2021;28:1108-17.
- Partridge SC, Steingrimsson J, Newitt DC, et al. Impact of alternate b-value combinations and metrics on the predictive performance and repeatability of diffusion-weighted MRI in breast cancer treatment: results from the ECOG-ACRIN A6698 trial. Tomography. 2022;8:701-17.
- Palle L, Reddy B. Role of diffusion MRI in characterizing benign and malignant breast lesions. Indian J Radiol Imaging. 2009;19:287-90.
- Kul S, Cansu A, Alhan E, et al. Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors. AJR Am J Roentgenol. 2011;196:210-7.
- Tozaki M, Fukuma E. 1H MR spectroscopy and diffusion-weighted imaging of the breast: are they useful tools for characterizing breast lesions before biopsy?. AJR Am J Roentgenol. 2009;193:840-9.
- Luo JD, Liu YY, Zhang XL, Shi LC. Application of diffusion weighted magnetic resonance imaging to differential diagnosis of breast diseases. Ai Zheng. 2007;26:168-71.
- Yabuuchi H, Matsuo Y, Kamitani T, et al. Non-mass-like enhancement on contrast-enhanced breast MR imaging: lesion characterization using combination of dynamic contrast-enhanced and diffusion-weighted MR images. Eur J Radiol. 2010;75:e126-32.
- Choi BB. Effectiveness of ADC difference value on pre-neoadjuvant chemotherapy mri for response evaluation of breast cancer. Technol Cancer Res Treat. 2021;20:15330338211039129.
- Hottat NA, Badr DA, Lecomte S, et al. Value of diffusion-weighted MRI in predicting early response to neoadjuvant chemotherapy of breast cancer: comparison between ROI-ADC and whole-lesion-ADC measurements. Eur Radiol. 2022;32:4067-78.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Radyoloji ve Organ Görüntüleme |
| Bölüm | Özgün Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 9 Mayıs 2025 |
| Gönderilme Tarihi | 13 Ocak 2025 |
| Kabul Tarihi | 11 Şubat 2025 |
| Yayımlandığı Sayı | Yıl 2025 Cilt: 7 Sayı: 2 |
Chief Editors
Assoc. Prof. Zülal Öner
Address: İzmir Bakırçay University, Department of Anatomy, İzmir, Turkey
Assoc. Prof. Deniz Şenol
Address: Düzce University, Department of Anatomy, Düzce, Turkey
Editors
Assoc. Prof. Serkan Öner
İzmir Bakırçay University, Department of Radiology, İzmir, Türkiye
E-mail: medrecsjournal@gmail.com
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