CC BY-NC-ND 4.0 · Indian J Radiol Imaging 2017; 27(02): 229-236
DOI: 10.4103/ijri.IJRI_405_16
Breast

Role of exponential apparent diffusion coefficient in characterizing breast lesions by 3.0 Tesla diffusion-weighted magnetic resonance imaging

Shweta Kothari
Department of Radio Diagnosis, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India
,
Archana Singh
Department of Radio Diagnosis, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India
,
Utpalendu Das
Department of Radio Diagnosis, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India
,
Diptendra K Sarkar
Department of Surgery, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India
,
Chhanda Datta
Department of Pathology, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India
,
Avijit Hazra
Department of Pharmacology, IPGME and R and SSKM Hospital, Kolkata, West Bengal, India
› Author Affiliations
Financial support and sponsorship Nil.

Abstract

Objective: To evaluate the role of exponential apparent diffusion coefficient (ADC) as a tool for differentiating benign and malignant breast lesions. Patients and Methods: This prospective observational study included 88 breast lesions in 77 patients (between 18 and 85 years of age) who underwent 3T breast magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) using b-values of 0 and 800 s/mm2 before biopsy. Mean exponential ADC and ADC of benign and malignant lesions obtained from DWI were compared. Receiver operating characteristics (ROC) curve analysis was undertaken to identify any cut-off for exponential ADC and ADC to predict malignancy. P value of <0.05 was considered statistically significant. Histopathology was taken as the gold standard. Results: According to histopathology, 65 lesions were malignant and 23 were benign. The mean ADC and exponential ADC values of malignant lesions were 0.9526 ± 0.203 × 10−3 mm2/s and 0.4774 ± 0.071, respectively, and for benign lesions were 1.48 ± 0.4903 × 10−3 mm2/s and 0.317 ± 0.1152, respectively. For both the parameters, differences were highly significant (P < 0.001). Cut-off value of ≤0.0011 mm2/s (P < 0.0001) for ADC provided 92.3% sensitivity and 73.9% specificity, whereas with an exponential ADC cut-off value of >0.4 (P < 0.0001) for malignant lesions, 93.9% sensitivity and 82.6% specificity was obtained. The performance of ADC and exponential ADC in distinguishing benign and malignant breast lesions based on respective cut-offs was comparable (P = 0.109). Conclusion: Exponential ADC can be used as a quantitative adjunct tool for characterizing breast lesions with comparable sensitivity and specificity as that of ADC.



Publication History

Article published online:
27 July 2021

© 2017. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Thieme Medical and Scientific Publishers Private Ltd.
A-12, Second Floor, Sector -2, NOIDA -201301, India

 
  • References

  • 1 Tan SL, Rahmat K, Rozalli FI, Mohd-Shah MN, Aziz YF, Yip CH, et al. Differentiation between benign and malignant breast lesions using quantitative diffusion-weighted sequence on 3 T MRI. Clin Radiol 2014;69:63-71.
  • 2 Woodhams R, Ramadan S, Stanwell P, Sakamoto S, Hata H, Ozaki M, et al. Diffusion-weighted imaging of the breast: Principles and clinical applications. Radiographics 2011;31:1059-84.
  • 3 Melsaether A1, Gudi A. Breast magnetic resonance imaging performance: Safety, techniques, and updates on diffusion-weighted imaging and magnetic resonance spectroscopy. Top Magn Reson Imaging 2014;23:373-84.
  • 4 Kul S, Cansu A, Alhan E, Dinc H, Gunes G, Reis A. Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors. AJR Am J Roentgenol 2011;196:210-7.
  • 5 Park MY, Byun JY. Understanding the mathematics involved in calculating apparent diffusion coefficient maps. AJR Am J Roentgenol 2012;199:W784.
  • 6 Taouli B, Thakur RK, Mannelli L, Babb JS, Kim S, Hecht EM, et al. Renal lesions: Characterization with diffusion-weighted imaging versus contrast-enhanced MR imaging. Radiology 2009;251:398-407.
  • 7 Wenkel E, Geppert C, Schulz-Wendtland R, Uder M, Kiefer B, Bautz W, et al. Diffusion weighted imaging in breast MRI: Comparison of two different pulse sequences. Acad Radiol 2007;14:1077-83.
  • 8 Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988;168:497-505.
  • 9 Peters NH, Vincken KL, van den Bosch MA, Luijten PR, Mali WP, Bartels LW. Quantitative diffusion weighted imaging for differentiation of benign and malignant breast lesions: The influence of the choice of b-values. J Magn Reson Imaging 2010;31:1100-5.
  • 10 Pereira FP1, Martins G, Figueiredo E, Domingues MN, Domingues RC, da Fonseca LM, et al. Assessment of breast lesions with diffusion-weighted MRI: Comparing the use of different b values. AJR Am J Roentgenol 2009;193:1030-5.
  • 11 Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C. Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol 2007;17:2646-55.
  • 12 Provenzale JM, Engelter ST, Petrella JR, Smith JS, MacFall JR. Use of MR exponential diffusion-weighted images to eradicate T2 “shine-through” effect. AJR Am J Roentgenol 1999;172:537-9.
  • 13 Paran Y, Bendel P, Margalit R, Degani H. Water diffusion in the different microenvironments of breast cancer. NMR Biomed 2004;17:170-80.
  • 14 Zhang YL, Yu BL, Ren J, Qu K, Wang K, Qiang YQ, et al. EADC Values in Diagnosis of Renal Lesions by 3.0 T Diffusion-Weighted Magnetic Resonance Imaging: Compared with the ADC Values. Appl Magn Reson 2013;44349-63.
  • 15 Park SY, Kim CK, Park JJ, Park BK. Exponential apparent diffusion coefficient in evaluating prostate cancer at 3 T: Preliminary experience. Br J Radiol 2016;89:20150470.
  • 16 Woodhams R, Matsunaga K, Kan S, Hata H, Ozaki M, Iwabuchi K, et al. ADC mapping of benign and malignant breast tumors. Magn Reson Med Sci 2005;4:35-42.
  • 17 Abdulghaffar W, Tag-Aldeen MM. Role of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) in differentiating between benign and malignant breast lesions. Egypt J Radiol Nucl Med 2013;44:945-51.
  • 18 Park MJ, Cha ES, Kang BJ, Ihn YK, Baik JH. The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors. Korean J Radiol 2007;8:390-6.
  • 19 Bansal R, Shah V, Aggarwal B. Qualitative and quantitative diffusion-weighted imaging of the breast at 3T-A useful adjunct to contrast-enhanced MRI in characterization of breast lesions. Indian J Radiol Imaging 2015;25:397-403.
  • 20 Palle L, Reddy B. Role of diffusion MRI in characterizing benign and malignant breast lesions. Indian J Radiol Imaging 2009;19:287-90.
  • 21 Jin G, An N, Jacobs MA, Li K. The role of parallel diffusion-weighted imaging and apparent diffusion coefficient (ADC) maP values for evaluating breast lesions: Preliminary results. Acad Radiol 2010;17:456-63.
  • 22 Woodhams R1, Kakita S, Hata H, Iwabuchi K, Umeoka S, Mountford CE, et al. Diffusion-weighted imaging of mucinous carcinoma of the breast: Evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings. AJR Am J Roentgenol 2009;193:260-6.