Journal of the Korean Society of Radiology (한국방사선학회논문지)

The Korean Society of Radiology (한국방사선학회)
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Correlation Analysis of Diffusion Metrics (FA and ADC) Values Derived from Diffusion Tensor Magnetic Resonance Imaging in Breast Cancer

유방암의 확산텐서 자기공명 영상에서 유도된 확산 지표(FA, ADC) 값의 연관성 분석

  • Lee, Jae-Heun (Department of Biomedical Health Science, Graduate School of Dongeui University) ;
  • Lee, Hyo-Yeong (Department of Biomedical Health Science, Graduate School of Dongeui University)
  • 이재흔 (동의대학교 대학원 보건의과학과) ;
  • 이효영 (동의대학교 대학원 보건의과학과)
  • Received : 2018.10.06
  • Accepted : 2018.11.30
  • Published : 2018.11.30
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Abstract

The purpose of this study was to compare the FA(faractional anisotropy) and ADC(apparent diffusion coefficient) values, which were derived from diffusion tensor imaging in breast cancer patients. The diffusion gradient used in this study was derived from quantitative diffusion indices using 20 directions(b-value, 0 and $1,000s/mm^2$). Quantitative analysis was analyzed using Pearson's correction and qualitative analysis using for correction coefficients. As a result, $FA_{min}$, $FA_{mean}$ and $FA_{max}$ were $0.098{\pm}0.065$, $0.302{\pm}0.142$ and $0.634{\pm}0.236$, respectively(p > 0.05). The $ADC_{min}$, $ADC_{mean}$ and $ADC_{max}$ were $0.741{\pm}0.403$, $1.095{\pm}0.394$ and $1.530{\pm}0.447$, respectively(p > 0.05). The $FA_{min}$, $FA_{mean}$, and $FA_{max}$ mean values were $0.132{\pm}0.050$, $0.418{\pm}0.094$, and $0.770{\pm}0.164$ for Category 6 and Kinetic Curve Pattern III, respectively. $ADC_{min}$, $ADC_{mean}$, and $ADC_{max}$ were $0.753{\pm}0.189$, $1.120{\pm}0.236$, and $1.615{\pm}0.372$, respectively. Quantitative analysis showed negative correlation between $ADC_{mean}-FA_{mean}$ and $ADC_{max}-FA_{max}$(p = 0.001, 0.003). The qalitative analysis showed ADC 0.628(p = 0.001), FA 0.620(p = 0.001) in the internal evaluations, ADC 0.677(p = 0.001), FA 0.695(p = 0.001) in external evaluations. In conclusion, based on the morphological examination, time to signal intensity graph is the form of wash-out(pattern III) in the dynamic contrast enhance examination, As a result, the $ADC_{mean}$ $1.120{\pm}0.236$ and $FA_{mean}$ values were $0.032{\pm}0.142$ with a negative correlation (Y=1.44-1.12X). Therefore, If we understand the shape of time to signal intensity graph and the relationship between ADC and FA, It will be a criterion for distinguishing malignant diseases in breast cancer.

유방암을 진단받고 수술 전 확산텐서영상에서 도출된 정량적 확산 지표인 비등방성 확산의 크기(FA)와 현성 확산계수(ADC) 값을 비교하고, 상관관계를 분석하여 보기로 하였다. 확산 그레디언트는 20방향(b-value, 0 및 $1,000s/mm^2$)을 사용하여 정량적 확산 지표를 도출하였다. 정량적 분석은 피어슨의 상관분석, 정성적 분석은 급내 상관계수를 적용하여 분석하였다. 연구 결과는 FAmin, FAmean, FAmax 평균값은 $0.098{\pm}0.065$, $0.302{\pm}0.142$, $0.634{\pm}0.236$이고 ADCmin, ADCmean, ADCmax은 $0.741{\pm}0.403$, $1.095{\pm}0.394$, $1.530{\pm}0.447$로 나타났다(p > 0.05). 병변 평가에서 Category 6이면서 시간대 신호 강도 그래프가 유실형(Pattern III)의 경우는 $FA_{min}$, $FA_{mean}$, $FA_{max}$ 평균값은 $0.132{\pm}0.050$, $0.418{\pm}0.094$, $0.770{\pm}0.164$이고 $ADC_{min}$, $ADC_{mean}$, $ADC_{max}$는 $0.753{\pm}0.189$, $1.120{\pm}0.236$, $1.615{\pm}0.372$로 나타났다. 정량적 분석 결과 $ADC_{mean}-FA_{mean}$, $ADC_{maximal}-FA_{max}$는 음의 상관관계가 나타났다(p = 0.001, 0.003). 정성적 분석 결과 내부 평가자의 경우 ADC 0.628(p = 0.001), FA 0.620(p = 0.001)이고, 외부 평가자의 경우 ADC 0.677(p = 0.001), FA 0.695(p = 0.001)로 나타났다. 결론적으로 형태학적 조직 검사를 바탕으로 동적 조영 검사에서 시간대 신호 강도 그래프는 유실(pattern III: wash out) 형태이며, $ADC_{mean}$ $1.120{\pm}0.236$, $FA_{mean}$값이 $0.032{\pm}0.142$로 피어슨 상관분석의 결과 음의 상관관계(Y=1.44-1.12X)로 나타났다. 따라서, 시간대 신호강도 그래프의 형태와 ADC와 FA의 상호관계를 파악한다면 유방암에서 악성 질환을 구분하는 기준이 되리라 생각된다.

Keywords

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Fig. 1. Recomendation for interpretation of Breast MRI Morphological features and dynamics characteristics are comblined and interpreted. If lesions are found to be morphologically cancerous, tissue examinations should be performed regardless of the type of contrast enhancement. If there is any indication of morphological ambiguity, conduct biopsy and monitor short-term n\monitoring if continuous.

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Fig. 2 region of interest (a) and time to signal intensity curve (b).

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Fig. 3. Quantitative diffusion indicators derived from DTI.

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Fig. 4. ADC to FA map relationship graph for Breast cancer.

Table 1. Result of qualitative analysis of breast cancer patients with final assessments.

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Table 2. Result of quantitative analysis of breast cancer between IDC and DCIS.

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Table 3. Result of quantitative analysis of breast cancer patients with category 5 & pattern III.

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Table 4. Result of qualitative analysis of breast cancer patients with final assessments.

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Table 5. Statistical Results of quantitative analysis using pearson correlation analysis.

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