Noncontrast-Enhanced MR-Based Conductivity Imaging for Breast Cancer Detection and Lesion Differentiation

June Suh, Jun Hyeong Kim, Soo Yeon Kim, Nariya Cho, Dong Hyun Kim, Rihyeon Kim, Eun Sil Kim, Myoung jin Jang, Su Min Ha, Su Hyun Lee, Jung Min Chang, Woo Kyung Moon

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: There is increasing interest in noncontrast-enhanced MRI due to safety concerns for gadolinium contrast agents. Purpose: To investigate the clinical feasibility of MR-based conductivity imaging for breast cancer detection and lesion differentiation. Study Type: Prospective. Subjects: One hundred and ten women, with 112 known cancers and 17 benign lesions (biopsy-proven), scheduled for preoperative MRI. Field Strength/Sequence: Non-fat-suppressed T2-weighted turbo spin-echo sequence (T2WI), dynamic contrast-enhanced MRI and diffusion-weighted imaging (DWI) at 3T. Assessment: Cancer detectability on each imaging modality was qualitatively evaluated on a per-breast basis: the conductivity maps derived from T2WI were independently reviewed by three radiologists (R1–R3). T2WI, DWI, and pre-operative digital mammography were independently reviewed by three other radiologists (R4–R6). Conductivity and apparent diffusion coefficient (ADC) measurements (mean, minimum, and maximum) were performed for 112 cancers and 17 benign lesions independently by two radiologists (R1 and R2). Tumor size was measured from surgical specimens. Statistical Tests: Cancer detection rates were compared using generalized estimating equations. Multivariable logistic regression analysis was performed to identify factors associated with cancer detectability. Discriminating ability of conductivity and ADC was evaluated by using the areas under the receiver operating characteristic curve (AUC). Results: Conductivity imaging showed lower cancer detection rates (20%–32%) compared to T2WI (62%–71%), DWI (85%–90%), and mammography (79%–88%) (all P < 0.05). Fatty breast on MRI (odds ratio = 11.8, P < 0.05) and invasive tumor size (odds ratio = 1.7, P < 0.05) were associated with cancer detectability of conductivity imaging. The maximum conductivity showed comparable ability to the mean ADC in discriminating between cancers and benign lesions (AUC = 0.67 [95% CI: 0.59, 0.75] vs. 0.84 [0.76, 0.90], P = 0.06 (R1); 0.65 [0.56, 0.73] vs. 0.82 [0.74, 0.88], P = 0.07 (R2)). Data Conclusion: Although conductivity imaging showed suboptimal performance in breast cancer detection, the quantitative measurement of conductivity showed the potential for lesion differentiation. Evidence Level: 1. Technical Efficacy: Stage 2.

Original languageEnglish
Pages (from-to)631-645
Number of pages15
JournalJournal of Magnetic Resonance Imaging
Volume54
Issue number2
DOIs
StatePublished - Aug 2021

Keywords

  • apparent diffusion coefficient
  • breast cancer
  • diffusion-weighted imaging
  • electric conductivity
  • noncontrast-enhanced MRI

Fingerprint

Dive into the research topics of 'Noncontrast-Enhanced MR-Based Conductivity Imaging for Breast Cancer Detection and Lesion Differentiation'. Together they form a unique fingerprint.

Cite this