A Bioimpedance Spectroscopy-Based Method for Diagnosis of Lower-Limb Lymphedema

Megan L. Steele, PhD,1,2 Monika Janda, PhD,1,3 Dimitrios Vagenas, PhD,1 Leigh C. Ward, PhD,4 Bruce H. Cornish, PhD,1 Robyn Box, PhD,5 Susan Gordon, PhD,6,7 Melanie Matthews, Bphty(Hons),6 Sally D. Poppitt, PhD,8 Lindsay D. Plank, PhD,9 Wilson Yip, MSc,8 Angela Rowan, MNutr,10 Hildegard Reul-Hirche, DipPhty,11 Andreas Obermair, MD,12 and Sandra C. Hayes, PhD1. Lymphatic Research Biology 2019.


Background: This study aimed at testing whether arm-to-leg ratios of extracellular water (ECW) and ECW normalized to intracellular water (ICW), measured by bioimpedance spectroscopy (BIS), can accurately detect bilateral, lower-limb lymphedema, and whether accounting for sex, age, and body mass index (BMI) improves the diagnostic performance of cut-offs.

Methods and Results: We conducted a dual-approach, case–control study consisting of cases of bilateral, lower-limb lymphedema and healthy controls who self-reported absence of lymphedema. The diagnostic performance using normative data-derived cut-offs (i.e., mean+0.5 standard deviation [SD] to mean+3 SD; n=136, 66% controls) and receiver operating characteristic (ROC) curve-derived cut-offs (n=746, 94% controls) was assessed. The impact of sex, age, and BMI was investigated by comparing stratified and nonstratified normative data-derived cut-offs, and ROC curves generated from adjusted and unadjusted logistic regression models. Arm-to-leg ratios of ECW between mean+0.5 SD and mean+1 SD showed fair to good sensitivity (0.73–0.84) and poor to good specificity (0.64 to 0.84). Arm-to-leg ratios of ECW/ICW failed to detect lymphedema (sensitivity <0.5). Stratification by sex, or by sex and age, yielded similar results to nonstratified cut-offs. Cut-offs derived from adjusted ROC curves showed both good sensitivity (0.83–0.89) and specificity (0.8–0.84).

Conclusion: These findings represent new BIS criteria for diagnosing lower-limb lymphedema that do not rely on comparison to baseline measures or the presence of a nonaffected, contralateral limb

Main findings

  • Data from a total of 944 participants (controls=898, cases=46) were assessed in this study.
  • The detection of bilateral lymphedema is complicated by the unavailability of an unaffected comparable limb. This study investigated whether arm-to-leg ratios of ECW or ECW/ICW can be used to detect lymphedema in individuals at risk of bilateral lymphedema. Ratios differed significantly between individuals with and without bilateral lower-limb lymphedema, providing support for the use of arm-to-leg ratios. Diagnostic cut-off values were derived by using two different approaches.
  • The first approach used binary cut-offs derived from normative data using the normal (Gaussian) distribution method. This involved calculation of nonstratified, sex-stratified, and sex- and age-stratified cut-offs ranging from the normative mean+0.5 SD up to +3 SD. Arm-to-leg ratios of R0 performed relatively well at cut-offs between mean+0.5 SD and mean+1 SD, which equates to cut-off values of 1.209 to 1.289 on the dominant side of the body and 1.252 to 1.339 on the nondominant side. Neither stratification by demographic variables nor normalization of ECW to ICW improved the diagnostic performance of arm-to-leg ratios.
  • The second approach for deriving cut-offs involved the construction of ROC curves by using unadjusted and adjusted arm-to-leg ratios and selection of optimal cut-offs based on clinically informed decision making. Comparison of McFadden’s R2 values (as a measure of model fit) and AUCs (as a measure of accuracy)of unadjusted and adjusted logistic regression models suggests that adding sex, age, and BMI to the model significantly improves the diagnostic performance of arm-to-leg ratios. Indeed, unadjusted ratios produced AUCs of 0.79 to 0.86, indicative of fair to good accuracy; whereas adjusted models produced AUCs between 0.89 and 0.93, indicative of good to excellent accuracy.
  • Therefore, the authors propose that the following predictive equations based on regression coefficients from the adjusted logistic regression models, could be used for accurately detecting bilateral, lower-limb lymphedema: Dominant side of the body: predictor=-18.41+5.58(arm R0/leg R0) – 0.45(male=1jfemale=0) + 0.03(age) +0.24(BMI) probability=exp(predictor)/(1+exp(predictor)) probability >0.045=lymphedema
  • Nondominant side of the body: predictor=-18.59+6.11(arm R0/leg R0) – 0.44(male=1jfemale=0) + 0.02(age) +0.24(BMI) probability=exp(predictor)/(1+exp(predictor)) probability >0.042=lymphedema Further, despite having reduced sensitivity and specificity, the following raw arm-to-leg ratios of ECW could be used for detection of lower-limb lymphedema if demographic data were unavailable or as a quick and easy, but less reliable preliminary diagnostic tool. Dominant side of the body: arm R0/leg R0 > 1.217=lymphedema Nondominant side of the body: arm R0/leg R0 > 1.211=lymphedema.
  • Further, findings suggest that unstratified arm-to-leg ratios of ECW are sensitive and specific; whereas the prediction equations based on sex, age, and BMI-adjusted logistic regression models showed excellent sensitivity and specificity, and they are easily translatable to the clinic.