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Abstract: Breast cancer-related lymphedema (BCRL) presents as swelling in the arm, hand, trunk, or breast at varying times after completion of breast cancer treatment. The reported incidence of BCRL varies widely in part due to its dependence on the type and extent of the treatment, pre-treatment risk factors, and the criteria used to define its presence. Central to this issue are the various quantitative measures that are used to specify lymphedema thresholds for its detection and tracking over time and during treatment. The goal of this chapter is to discuss these issues and the methods available for the non-invasive quantitative assessment of BCRL. Operational principles, advantages and limitations of the various methods, their clinical history of use, and effectiveness are discussed. Covered methods include those used to assess and monitor lymphedema-related changes in tissue water at any anatomical site and also methods used to assess changes only in limbs.

Keywords: breast cancer-related lymphedema; dielectric constant; measuring lymphedema; impedance; limb volume

INTRODUCTION

Breast cancer-related lymphedema (BCRL) has a variable reported incidence that depends on the objective criteria used and, on the type and extent of a patient’s treatment (1–5). When BCRL occurs, it manifests itself as increased fluid anywhere in the at-risk arm (6–8) or thorax (9, 10) or other areas. Most portable and readily accessible noninvasive methods that assess its presence and extent are restricted to those that measure arm size change or the difference between at-risk arm and contralateral arms. These methods include manual (11–13) and automated (8, 14–16) circumference and volume measurements, arm fluid changes assessed by electrical impedance (17–19), and volume changes assessed by water displacement measurements (WDM). These are discussed after a brief description of BCRL incidence, and the factors affecting it. Subsequently, a fully portable measurement method, used to assess localized lymphedema at any anatomical site via tissue dielectric constant measurements (20–24) is described. Other non-invasive methods, including photographic and scanning methods (25–27), magnetic resonance imaging (28, 29), and ultrasound (30–32) are also briefly discussed.

BCRl INCIDENCE

BCRL presents as swelling in the arm, hand, trunk, or breast after breast cancer treatment that, among other more serious outcomes, causes discomfort, distress, disability and anxiety (33). Factors that influence the incidence of BCRL depend on tumor stage, body mass index, axillary lymph node dissection (ALND), number of nodes dissected, axillary radiation, surgery type (34), and the diagnostic criteria used.

BCRL incidence is about 20% at one year and 40% at ten years post-treatment (35–37). Thus, at least one in five female breast cancer survivors will develop BCRL. According to a meta-analysis (36), BCRL incidence was 10.3% between 3–6 months post-surgery, 13.8% between 6–12 months, 18.9% between 12–24 months, 18.6% between 24–60 months, and 15.6% beyond 60 months. BCRL is more prevalent in stage III and stage IV breast cancer since more nodes are generally removed (38, 39). A 15-year prospective study found that 24% of early (stage I and II) and 35.3% of advanced (stage III and IV) breast cancer patients were diagnosed with BCRL (39). Increased body mass index is another important risk factor for BCRL, with obese patients being almost twice as likely to develop BCRL (36, 38, 40, 41).

When comparing the two main surgical treatment options, mastectomy and lumpectomy, breast cancer survivors who had a mastectomy are more likely to get BCRL (38) with incidence reported as 24–49% among mastectomy survivors, and 4–28% among lumpectomy survivors (42). Survivors who had lymph node dissection, with or without axillary radiation, had an increased risk for BCRL (38, 39, 43). BCRL among survivors who had both ALND and radiation was 41%, and in those who did not have radiation, it was 17% (43). BCRL also occurs following sentinel lymph node biopsy (SLNB) without ALND (36, 44). BCRL incidence in breast cancer survivors who had only SLNB was 11.5% but was 39.7% in those with both SLNB and ALND (44). Increased incidence of BCRL is greater with ALND (36, 45, 46) and with more nodes removed. Removing 1–5 nodes was not a significant risk factor for BCRL whereas BCRL was 5-times more likely if 6–15 nodes were removed, and 10-times more likely if 16 or more nodes were removed (47).

ARM VOLUMES BASED ON MANUAL CIRCUMFERENCE MEASUREMENTS

The circumference of the non-compressed and relaxed arm is measured with a tape-measure that is optimally pulled with a constant tension using a spring-loaded calibrated tape measure at all measured sites (Figure 1). Practical measurement issues include the number of circumferential measurements to be made, their longitudinal separation, the volume calculation model, and how the volumes or circumferences are optimally used to assess initial lymphedema status and its subsequent change due to either time or therapy.

Figure 1. Illustrating arm circumference measurement with a tape measure. The arm circumference is pictured being measured with a tape measure that is equipped with a tension gauge so that measurements at multiple arm sites are made with uniform tension. If two longitudinal separated sites have their circumferences measured the volume of the limb between these segments can be reliably calculated using geometric formulas.

Measurement Details and Volume Calculations

The preceding measurement issues have been investigated in healthy and lymphedematous arms. Casley-Smith was among the first to systematically study these issues (48). An approach was to calculate segment volumes (V_S) between two circumferences (c_1,2) separated by a distance L using a truncated cone model as . The formula was used in 150 unilateral BCRL patients with circumferences measured at mid-hand, narrowest part of the wrist, and at 10 cm intervals starting from the middle fingertip. By summing segment volumes, arm volumes of interest were determined. Percentage edema volume (%EV) was calculated as the volume difference between affected and contralateral arms divided by contralateral arm volume. The %EV determined this way was compared to edema volumes determined via water displacement (%EV_W), considered as the gold-standard. A high correlation between methods was reported (r = 0.925) with a regression equation %EV = 1.096 %EV_W + 0.007. These authors suggested that rather than using a truncated-cone model, a summation-of-disks model might be better (49).

Measurements in 15 BCRL patients compared segment lengths of 10-cm vs. about 4-cm in which the 4-cm start was the most distal portion of the wrist and the end at about 45 cm (13). Calculated %EV was similar for both, but shorter segments had a statistically greater %EV that was most evident at greater arm volumes and had better accuracy. The circumference-volume method was also compared to WDM on 14-women with unilateral BCRL using 4-cm segment lengths (12). Small differences in arm volumes were reported depending on method, but inter-arm differentials were highly correlated (r = 0.79). A subsequent reliability and validity study compared the circumference-volume method with WDM on 66 women in which 19 had unilateral BCRL (50). Measured arm length was standardized to start at the wrist (mid-ulnar styloid) and extend to 65% of the distance from olecranon (elbow) to acromion (shoulder tip). Circumferential measurements were made at specified anatomical sites or standardized distances, with four segments used to calculate volume and compared to WDM. Results indicated good correlation between methods but based on limits of agreement, the methods could not reliably be interchanged since calculated volumes were up to 5% greater than WDM values. Based on reliability analyses they concluded that the minimal detectible change in volume that could be used as a clinical threshold representing a real change due to time or treatment was 150 ml.

LIMB VOLUMES FROM AUTOMATED ARM CIRCUMFERENCE MEASUREMENTS

Automation of manual circumference measurements emerged with the arrival of a device commercially known as the Perometer. Its basic operating principle is illustrated in Figure 2.

Figure 2. Illustrating automated optoelectronic measurement of arm circumferences. A limb (arm or leg) is placed within a movable frame that contains infrared light sources that illuminate the limb and allow acquisition of limb projected perpendicular dimensions D₁ and D₂. From these measurements the cross-sectional area of the limb slices is calculated for slices of about 2 mm in length. The sum of these slices is used to calculate the limb volume.

Measurement Details and Volume Calculations

A sliding frame with imbedded infrared (IR) light sources scans the arm and the “shadow” dimensions D₁ and D₂ are detected and used calculate cross-sectional areas as a constant (k) multiplied by D₁ and D₂. Segment volumes are determined similarly to the manual method with segment volumes summed to produce the arm volume of interest. This method has the advantage of rapidly estimating cross-sectional areas using as low as 0.5 cm segment lengths and an automatic calculation of arm volumes. Disadvantages include device set-up, space requirements, patient positioning, service maintenances and initial cost as compared manual methods.

Initial evaluations on 17 lymphedematous arms indicated an arm volume 6.8 ± 4.3% greater than manual tape-measure values (16). Subsequent tests on 37 lymphedematous arms compared automated volumes vs. tape-measure (5-cm intervals) vs. WDM (51). Reproducibility of each method was assessed as satisfactory with inter and intra-class correlation coefficients ranging from 0.937 to 0.997. Repeated measurements by the same rater (intra-rater variation) yielded volume percentage differences of 1.5 ± 1.4% for the Perometer, 2.9 ± 2.9% for WDM and 3.2 ± 4.6% for the tape-measure method. Using perometry to pre-operatively screen 1028 women with unilateral BCRL emphasized the importance of pre-surgical volumes (15). Perometer measurement utility for pre-operative screening and follow-up in large volume centers is supported by findings in which large numbers of patients have been evaluated (8, 15). Perometer usefulness to assess hand volume was evaluated in 20 patients with hand lymphedema and 20 without lymphedema and compared to values determined using WDM (52). It is unclear what calculation method was used but an approximate Perometer volume overestimate of about 7.5% was reported. Other methods to estimate hand volume not requiring sophisticated systems have been reported (53, 54) as well as methods based on bioimpedance spectroscopy (55–57).

BCRL THRESHOLDS BASED ON ARM DIFFERENTIALS OR CHANGES

Beyond clinical assessments and patient symptoms, various quantitative parameters have been developed to help define BCRL presence in its early subclinical stage and later clinical stage. Parameters based on arm metrics were the earliest and remain in use now, but other methods such as bioimpedance and tissue dielectric constant measurements are now also available as discussed later in this chapter.

Metric Thresholds

Most BCRL cases are unilateral, so it is common to compare at-risk arms to contralateral arms with respect to inter-arm differentials. Arm circumferences are measured bilaterally at corresponding anatomical sites and inter-arm circumferences, or inter-arm volumes compared. Untreated BCRL progresses in volume and grade rapidly at first and slowly thereafter (48). Untreated BCRL, quantified as inter-limb volume ratios (V_R), increased by 40.6% in the first year, 12.4% from year one to five, and 4.22% from five to 30 years (58). Problems of BCRL measurements and accurate BCRL incidence assessments were raised by early investigators (59) and parameter values that best reflect BCRL presence were studied by comparing three lymphedema thresholds based on arm metric measurements (60). Arm circumferences were tape-measured at 4-cm intervals and also measured by perometry prior to breast surgery and at 6 and 12-months post-surgery in 110 breast cancer survivors. Incidence was assessed in three ways based on at-risk arms vs. contralateral arms, 2-cm circumference change at any site, and 200 ml volume change and 10% volume change. These thresholds yielded quite different estimated one-year incidence rates of 46%, 24%, and 8%, respectively.

Further study on 236 patients followed for up to 5-years (5) indicated the 2-cm difference predicted a 94% incidence whereas the 10% volume difference criterion predicted a 45% incidence. More recently, 1100 women with breast cancer who had ALND were followed for up to 5-years (8). BCRL thresholds used in this multicenter study were a relative arm volume increase of ≥10% (Perometer determined) and an L-Dex value (8, 14) >10 based on bioimpedance spectroscopy (BIS). By 24 months, 22.8% had BCRL based on volume but 45.6% had it based on L-Dex. Early detection of relative volume increases between 5–10% were strong predictors of BCRL occurring by 36 months. Analyses of the primary study data (61) indicated a median time to develop BCRL was 11.3 months. For women followed to 5 years (n = 156), 31.9% had BCRL as assessed by volume, whereas 77.2% had BCRL according to the 200 ml threshold.

BCRL ASSESSMENTS BASED ON WATER DISPLACEMENT METHODS

WDM is considered by many to be the “gold standard” for volume measurements (50, 62, 63). Insertion of the arm into a water-filled volumeter causes a water volume equal to the inserted arm volume to be displaced and captured as overflow. Although accurate, the method is time-consuming and messy and depends on patient mobility to implement and is not routinely used in clinic. However, it can provide comparisons against which other methods may be assessed and provide reference values against which BCRL thresholds are developed. Absolute arm volume thresholds are most useful if pre-surgery values are not available.

Water Displacement BCRL Thresholds

Using WDM, arm volumes were measured in 112 women (50.6 ± 18.2 years) with a BMI of 24.5 ± 3.9 Kg/m² (64). Most were right-handed (n = 100) with right arm volumes about 3% greater than the left. Such handedness differences should be taken into account. Prediction equations extrapolating back to what an arm volume would have been prior to BCRL may be applied based on normative values. For right-handed women, right arm volume (RAV) in terms of left arm volume (LAV) can be expressed as RAV = 0.979 LAV + 96.66 ml. Contrastingly, for LAV of right-handed women the relationship is LAV = 0.991 RAV – 33.3 ml. In each case, a 95% confidence interval was about 148 ml. It was suggested that the equations, together with upper confidence limits, be used for thresholds.

As an example, consider a right-handed woman with a left arm at-risk who has a measured RAV of 3000 ml. Her normal (predicted) LAV is 2940 ml to which is added 148 ml resulting in a 2SD threshold of 3088 ml and an inter-arm ratio of 1.029. Contrastingly, if the right-arm were at-risk with the left arm measured at 3000 ml, the predicted threshold is 3182 ml with an inter-arm ratio of 1.06.

Inter-arm differentials of 200 ml, determined by WDM, were used as a threshold defining sustained BCRL in 85 women 24 months post-surgery (65). Accordingly, 19 (22.4%) had BCRL at 24 months. Contrastingly, based on two inter-arm circumference measurements made at 6 months post-surgery differing by ≥ 2 cm, the calculated probability of sustained BCRL at 24 months was 60%.

BCRL ASSESSMENTS WITH BIOIMPEDANCE SPECTROSCOPY (BIS)

BIS refers to measuring electrical impedance at multiple frequencies. This method is widely used but it has been argued that it is not a proper substitute for volumes or for localized assessments of limb lymphedema and is also not applicable to other body areas (49). Contrastingly, it has been argued that it should be adopted as a gold standard (66). In some quarters it has become common to use a surrogate parameter called the L-Dex (67). There is some controversy whether this parameter and its threshold for BCRL is adequate (68).

BIS Measurement Details

Application of a sinusoidally varying voltage causes a time-varying current that depends on frequency and the current’s pathway (Figure 3A). At low frequencies, cell membranes pass little or no current due to the membrane’s high electrical capacitance whereas at high frequencies current passes through the cell. As a consequence, the composite pathway may be represented by an equivalent electrical circuit (Figure 3B). The quantities R_e and R_i represent external and internal electrical resistances. These resistance values are inversely related to the amounts of extracellular water (ECW) and intracellular water (ICW) through which the currents flow. Because of the low electrical resistance of body fluids relative to other body components such as fat and connective tissue, the overall measured impedance (Z), which is the ratio of the voltage difference (V) to current (I), is strongly dependent on fluid content. A schematized version of the measurement of arm impedance is shown in Figure 3C in which electrodes are illustrated in accordance with previously evaluated positioning (69).

Figure 3. Illustrating basic elements of bioimpedance spectroscopy procedure. A, Applied low frequency currents do not well penetrate cells due to the membrane capacitance whereas high frequency currents do penetrate allowing for an estimate of intra and extracellular water. B, An approximate equivalent electrical circuit depicting the various elements of the cellular and extra-cellular current pathways. C, Illustrates one configuration of the way in which the excitation and measuring electrodes are applied. The current (I) flows as indicated in the dashed pathway and the voltage difference is measured as V. From these values the arm impedance Z is calculated as the ratio of V/I.

In Figure 3A, the applied voltage (red lines) causes an exciting current to flow (dashed lines). Right arm impedance is determined by the ratio of V (between right and left hands) divided by current (I). In practice, it is possible to separate components attributable to ICW and ECW. In assessing BCRL the concept is that excess arm fluid causes the affected arm to have a reduced impedance vs. a pre-surgery baseline or vs. the contralateral arm. Devices are available for such measurements (Impedimed Ltd, Brisbane, Australia). One version (model SFB7) uses 256 frequencies that range between 3–5 KHz (low frequency) to 1000 KHz (high frequency). Use of multiple frequencies allows extrapolations to evaluate theoretical zero and infinite frequencies based on Cole-Cole plots (70, 71) that describe resistance vs. reactance as a function of frequency (72). These yield estimates of ECW and ICW.

To determine changes only in ECW, which is the dominant fluid change compartment associated with lymphedema, multiple frequencies are much less important and a single frequency of less than 30 KHz (73) may be sufficient. An excellent correlation between single frequency and BIS--determined values was obtained for frequencies ≤ 50 KHz (74). However, whether using single or multiple frequencies, such measurements may not capture the full lymphedema picture because of a non-measured contribution of bound water (75, 76). Some BIS technology is now incorporated in a system allowing BIS measurements while standing.

BCRL Thresholds Based on BIS

Impedance measurements have been used for many years with applications ranging from studying peripheral vasculature (77) to cardiac assessments with impedance cardiography (78). However, its early description in the assessment of lymphedema can be traced to the early-to mid-1990’s (79, 80). BCRL thresholds were originally based on inter-limb impedance ratios obtained in healthy persons (dominant/non-dominant) arms, with thresholds defined as inter-arm impedance ratios (contralateral/at-risk) exceeding a mean ratio + 3SD as determined in 60 healthy women (81). The mean and SD of this healthy ratio was 0.964 ± 0.034 that led to a threshold of 1.066. Strictly speaking, this threshold applies to detecting BCRL in women in whom their dominant arm was at-risk. An adjustment to this threshold ratio made for women whose at-risk arm was their non-dominant arm was reported as 1.139 (82). The use of the 3SD threshold is arbitrary but represents a conservative estimate that yields a better sensitivity. This threshold was refined from measurements in 172 healthy women in which dominant/non-dominant impedance ratios were 0.986 ± 0.040 yielding a threshold of 1.106.

BCRL ASSESSMENTS BASED ON TISSUE DIELECTRIC CONSTANT (TDC)

The term tissue dielectric constant (TDC) was coined in 2007 (24) to represent the value of the relative permittivity of skin-to-fat tissue measured in vivo using the open-ended coaxial line method (83–85). To assess edema or lymphedema, it’s use is based on the fact that its value strongly depends on tissue water content (86–88). In contrast to lymphedema assessment methods useful only for limbs, TDC measurements are localized and usable to measure skin water or skin-to-fat water at most anatomical sites including breast (20, 89) and trunk (9, 90). Tissue dielectric properties are dependent on their water content and use of the Debye relationship can describe frequency dependence of tissue dielectric properties (91, 92). In this formulation the real part of a complex permittivity (e*) is denoted as e’ and its ratio to a vacuum’s permittivity (e’/e₀) is relative permittivity (e_r). From a physical perspective, tissue permittivity may be thought of as the electric flux density (D) produced when the tissue experiences an applied electric field (E). In this formulation, the permittivity or TDC may be defined as the ratio of the flux density produced to the electric field causing it (e’ = D/E).

TDC Measurement Details

TDC is measured by touching the skin with a probe that has concentric inner and outer electrodes (conductors) that functions as an open-ended coaxial line (Figure 4A-top). The probe inserts a 300 MHz electric field from a battery-operated control box or within the probe itself for a compact version (Figure 4B-bottom). One of the multiprobe types is shown in Figure 4B-top. For both, a time-varying electric field penetrates the tissue (Figure 4A-bottom). For a given frequency, the depth of penetration depends on the probe’s radial dimensions (93, 94) with larger diameter probes penetrating deeper (95). Some incident electromagnetic energy is reflected (Figure 4C) and from an analysis of this component, TDC is determined via algorithms based on the physics of the process (85).

Figure 4. Basic principle and elements of tissue dielectric constant (TDC) measurements of BCRL. A, Cross-section of the TDC measurement probe surface and an illustration of the electric field lines that penetrate the skin. B, Illustrates the placement of two different probe systems onto the skin surface. The top probe is connected to a control box that generates the 300 MHz signal and also processes the reflected wave as conceptualized in C. The bottom part of B shows the compact probe that has all electronics and processing within the hand-held device.

Devices are available (Delfin Technologies, Kuopio, Finland) that provide probes for effective measurement depths between 0.5 mm and 5.0 mm (multiprobe system) or fixed depths (compact versions). In some tissues, TDC values depend on measurement depth because of depth-dependent tissue heterogeneity (96, 97). Increased fat with increasing depth tends to lower the TDC value due to low water content of fat (87, 98). Variations in TDC values are also expected based on sex (99–101), age (102, 103), body habitus (104), and at different anatomical sites along the arm (105, 106). These normal biological variations do not importantly impact TDC use as a lymphedema assessment method because of various normalization processes. For unilateral BCRL, inter-arm (107, 108) or inter-trunk (9, 10) or inter-breast (20, 109) ratios are used with the added advantage that specific localized targets can be tracked. The method permits assessing head-and-neck-related lymphedema (110) and lower extremity lymphedema (111, 112) based on individualized inter-site normalizations.

BCRL Thresholds Based on TDC

TDC measurements to a depth of 2.5 mm in 30 healthy pre- and 30 post-menopausal women yielded an inter-arm TDC ratio of 1.040 ± 0.040 vs. 1.640 ± 0.300 in 18 patients with BCRL (24). In that study, no healthy control had an inter-arm ratio as great as 1.200 and no patient had a ratio as low as 1.200. It was suggested that an inter-arm TDC-ratio of 1.200 should be a BCRL threshold-value. Had they used a threshold based on 3SD greater than the mean, it would have been 1.160. Other work supported the 1.200 threshold ratio (113). Inter-arm TDC-ratios were compared between 60 healthy women and 30 patients with unilateral BCRL (114). The healthy group’s inter-arm TDC-ratio (dominant/non-dominant) was 1.006 ± 0.085 with a 3SD TDC-threshold-ratio of 1.26. This was initially used to define arm BCRL and were insignificantly affected by patient body mass index, age, measurement depth (96, 108) or hand-dominance (115). Subsequent inter-side measurements made with a compact-type TDC device in 112 breast cancer survivors without BCRL had at-risk to contralateral side ratios for forearm, upper arm and middle lateral thorax of 1.00 ± 0.09, 1.01 ± 0.15, and 1.06 ± 0.10, respectively (90). These ratios differed from those similarly measured in 78 breast cancer survivors diagnosed with BCRL in whom corresponding inter-side ratios were 1.29 ± 0.36, 1.25 ± 0.41, and 1.07 ± 0.12, respectively (90). In this study, time since breast surgery was 8.4 ± 6.7 years with 12.8 ± 8.7 nodes removed. The non-BCRL control patients were 6.9 ± 6.7 years post-surgery and had 6.1 ± 7.3 nodes removed. Based on a 3SD threshold for control ratios, an inter-arm BCRL threshold may be calculated as 1.27, 1.46 and 1.36 for forearm, upper arm and thorax. A slightly lower thorax-to-thorax inter-side ratio of 1.38 has been reported from measurements on 120 women awaiting breast cancer surgery (10). A reference range for inter-hand TDC ratios has been determined via measurements in 70 healthy women to be 1.326 (116).

IMAGING-BASED MEASUREMENT METHODS

There have been several reports describing efforts to use 3-D photography and whole-body scanning systems to assess arm volumes (25–27, 117–120). Future progress in these areas is likely but currently are probably not suitable for routine clinical application. Ultrasound provides an additional potential diagnostic modality. It has been used to detect changes in cutaneous water (121, 122) and thickness changes (32, 123) and, when used in combination with shear wave elastography (124–126), shows promise to assess BCRL features based on cutaneous and subcutaneous dermal thickening and stiffness increases detectable by increased shear-wave velocity resulting from an increased shear modulus. Magnetic resonance imaging (MRI) is another imaging modality with potential efficacy in characterizing aspects of BCRL. A recent study used a multi-echo spin echo protocol to evaluate T2-relaxation times in upper arms of women with and without BCRL (127). On the basis that these T2 values reflect relative tissue fluid content, a 7–13% greater fluid amount in BCRL arms was reported. However, major limitations of MRI include its cost and accessibility and the absence of currently defined diagnostic threshold criteria. Another promising approach is that of non-contrast magnetic resonance lymphography (NMRL) that visualizes lymphatic vessels (128, 129) for which a partial scoring system has recently been suggested (130). However, as with any MRI-related approach, cost, required patient time for measurement, and availability are major limitations when compared with the portable hands-on methods of measurement previously discussed. However, MRI-related procedures can valuably add to the understanding of lymphatic physiology and pathophysiology as in BCRL.

CONCLUSION

It has been long recognized (48, 49) that in addition to changes in interstitial fluid content accompanying developing lymphedema, there are progressive changes in tissue content, structure, and physical properties. Such changes include increases in arm fat, muscle, and bone as has been demonstrated via dual energy x-ray absorptiometry (DXA) in a group of 18 women with BCRL (131). It is thus likely that such complex changes, that do contribute to arm volume increases, will not directly be reflected as decreases in measured arm impedance. These complexities have been more recently investigated using MRI (132) in which excess fat volume was observed in both intra- and inter muscular compartments of seven patients with BCRL. An increasing relative amount of fat accumulation would increase measured arm impedance even though arm volume was increasing further suggesting a limitation to BIS tracking in such cases. Other factors to be considered relevant to BCRL portable or semi-portable measurement techniques is their relative initial cost, continuing supply needs and operating costs, maintenance needs, ease of use, and difficulties with measurement. Based on such considerations, the relatively non-portable Perometer system cost (350NT) of at least $33,000 may be most useful for high volume screening facilities. Contrastingly, the hand-held TDC device, costing about $4000 with no subsequent operating costs, may be most useful for rapid routine physician or therapist initial detection and follow-up assessments of localized BCRL or for such measurements at any other anatomical site related to BCRL such as breast or thorax. Use of BIS may also be most useful for high volume screening and follow-up purposes in which sensitivity to small-to-moderate free and bound water increases are not important. Initial unit cost is about $8000 with a continuing electrode cost per patient. A comparison between BIS and TDC methods in 100 women with BCRL has reported TDC having a greater sensitivity at detecting early lymphedema (133). This is in part due to lymphedema that is more superficial. They also suggest complementary use of TDC and volume assessments and indicate a number of practical advantages of TDC. These are reported to include the contradictory use of BIS in patients who are pregnant, have pacemakers or metal implants and patients being in contact with a metal surface. However, a case has been put forward that BIS should be considered as a gold standard for assessing limb lymphedema (66) and a summary of historical estimates of its sensitivity and specificity have recently been reported (18). From the point of view of cost, tape measure procedures with volume conversion and limb volumes via water displacement require the least for equipment, but measurement time and patient acceptance need to be considered. Tape measurements are well accepted by patients but may require extended therapist measurement time. In the case of water-displacement measurements, patient positioning and discomfort as with all methods are to be considered. The shorter the required measurement time and the less intrusive to the patient, the better tolerated is the measurement process.

Acknowledgment: The helpful contributions of Claudia Admoun and Evelina Arzanova are gratefully acknowledged.

Conflict of Interest: The author confirms that the materials included in this chapter do not violate copyright laws. Where relevant, appropriate permissions have been obtained from the original copyright holder(s), and all original sources have been appropriately acknowledged or referenced.

Copyright and Permission Statement: The author confirms that the materials included in this chapter do not violate copyright laws. Where relevant, appropriate permissions have been obtained from the original copyright holder(s), and all original sources have been appropriately acknowledged or referenced.

REFERENCES

1. Liu YF, Liu JE, Mak YW, Zhu Y, Qiu H, Liu LH, et al. Prevalence and predictors of breast cancer-related arm lymphedema over a 10-year period in postoperative breast cancer patients: A cross-sectional study. Eur J Oncol Nurs. 2021;51:101909. https://doi.org/10.1016/j.ejon.2021.101909
2. Ganju RG, Savvides G, Korentager S, Ward MJ, TenNapel M, Amin A, et al. Incidence of breast lymphedema and predictors of its development in patients receiving whole breast radiation therapy after breast-conservation surgery. Lymphology. 2019;52(3):126–33. https://doi.org/10.2458/lymph.4633
3. Bulley C, Gaal S, Coutts F, Blyth C, Jack W, Chetty U, et al. Comparison of breast cancer-related lymphedema (upper limb swelling) prevalence estimated using objective and subjective criteria and relationship with quality of life. Biomed Res Int. 2013;2013:807569. https://doi.org/10.1155/2013/807569
4. Hayes S, Di Sipio T, Rye S, Lopez JA, Saunders C, Pyke C, et al. Prevalence and prognostic significance of secondary lymphedema following breast cancer. Lymphat Res Biol. 2011;9(3):135–41. https://doi.org/10.1089/lrb.2011.0007
5. Armer JM, Stewart BR. Post-breast cancer lymphedema: incidence increases from 12 to 30 to 60 months. Lymphology. 2010;43(3):118–27.
6. Karlsson K, Johansson K, Nilsson-Wikmar L, Brogardh C. Tissue Dielectric Constant and Water Displacement Method Can Detect Changes of Mild Breast Cancer-Related Arm Lymphedema. Lymphat Res Biol. 2021. https://doi.org/10.1089/lrb.2021.0010
7. Liu Y, Long X, Guan J. Tissue Dielectric Constant Combined With Arm Volume Measurement as Complementary Methods in Detection and Assessment of Breast Cancer-Related Lymphedema. Lymphat Res Biol. 2021. https://doi.org/10.1089/lrb.2020.0065
8. Keeley V. The Early Detection of Breast Cancer Treatment-Related Lymphedema of the Arm. Lymphat Res Biol. 2021;19(1):51–5. https://doi.org/10.1089/lrb.2020.0097
9. Koehler LA, Mayrovitz HN. Tissue Dielectric Constant Measures in Women With and Without Clinical Trunk Lymphedema Following Breast Cancer Surgery: A 78-Week Longitudinal Study. Phys Ther. 2020;100(8):1384–92. https://doi.org/10.1093/ptj/pzaa080
10. Mayrovitz HN, Weingrad DN. Tissue dielectric constant ratios as a method to characterize truncal lymphedema. Lymphology. 2018;51(3):125–31.
11. Meijer RS, Rietman JS, Geertzen JH, Bosmans JC, Dijkstra PU. Validity and intra- and interobserver reliability of an indirect volume measurements in patients with upper extremity lymphedema. Lymphology. 2004;37(3):127–33.
12. Karges JR, Mark BE, Stikeleather SJ, Worrell TW. Concurrent validity of upper-extremity volume estimates: comparison of calculated volume derived from girth measurements and water displacement volume. Phys Ther. 2003;83(2):134–45. https://doi.org/10.1093/ptj/83.2.134
13. Latchford S, Casley-Smith JR. Estimating limb volumes and alterations in peripheral edema from circumferences measured at different intervals. Lymphology. 1997;30(4):161–4.
14. Gillespie TC, Roberts SA, Brunelle CL, Bucci LK, Bernstein MC, Daniell KM, et al. Comparison of perometry-based volumetric arm measurements and bioimpedance spectroscopy for early identification of lymphedema in a prospectively-screened cohort of breast cancer patients. Lymphology. 2021;54(1):1–11. https://doi.org/10.2458/lymph.4677
15. Sun F, Hall A, Tighe MP, Brunelle CL, Sayegh HE, Gillespie TC, et al. Perometry versus simulated circumferential tape measurement for the detection of breast cancer-related lymphedema. Breast Cancer Res Treat. 2018;172(1):83–91. https://doi.org/10.1007/s10549-018-4902-z
16. Stanton AW, Northfield JW, Holroyd B, Mortimer PS, Levick JR. Validation of an optoelectronic limb volumeter (Perometer). Lymphology. 1997;30(2):77–97.
17. Liu S, Zhao Q, Ren X, Cui Y, Yang H, Wang S, et al. Determination of Bioelectrical Impedance Thresholds for Early Detection of Breast Cancer-related Lymphedema. Int J Med Sci. 2021;18(13):2990–6. https://doi.org/10.7150/ijms.53812
18. Dylke ES, Ward LC. Three Decades of Bioelectrical Impedance Spectroscopy in Lymphedema Assessment: An Historical Perspective. Lymphat Res Biol. 2021;19(3):206–14. https://doi.org/10.1089/lrb.2020.0085
19. Merli P, Furnari R, Fadda M, De Francesco A, McConnell R, Massazza G. Role of Bioelectrical Impedance Analysis in the Evaluation of Patients with Upper Limb Lymphedema. Lymphat Res Biol. 2020;18(6):555–9. https://doi.org/10.1089/lrb.2019.0085
20. Mayrovitz HN, Somarriba C, Weingrad DN. Breast Tissue Dielectric Constant as a Potential Breast Edema Assessment Parameter. Lymphat Res Biol. 2021. https://doi.org/10.1089/lrb.2020.0137
21. De Vrieze T, Gebruers N, Nevelsteen I, De Groef A, Tjalma WAA, Thomis S, et al. Reliability of the MoistureMeterD Compact Device and the Pitting Test to Evaluate Local Tissue Water in Subjects with Breast Cancer-Related Lymphedema. Lymphat Res Biol. 2020;18(2):116–28. https://doi.org/10.1089/lrb.2019.0013
22. Mayrovitz HN, Mikulka A, Woody D. Minimum Detectable Changes Associated with Tissue Dielectric Constant Measurements as Applicable to Assessing Lymphedema Status. Lymphat Res Biol. 2019;17(3):322–8. https://doi.org/10.1089/lrb.2018.0052
23. Mayrovitz HN, Arzanova E, Somarriba S, Eisa S. Factors affecting interpretation of tissue dielectric constant (TDC) in assessing breast cancer treatment related lymphedema (BCRL). Lymphology. 2019;52(2):92–102. https://doi.org/10.2458/lymph.4630
24. Mayrovitz HN. Assessing local tissue edema in postmastectomy lymphedema. Lymphology. 2007;40(2):87–94.
25. Mastick J, Smoot BJ, Paul SM, Kober KM, Cooper BA, Madden LK, et al. Assessment of Arm Volume Using a Tape Measure Versus a 3D Optical Scanner in Survivors with Breast Cancer-Related Lymphedema. Lymphat Res Biol. 2021. https://doi.org/10.1089/lrb.2020.0119
26. Preuss M, Killaars R, Piatkowski de Grzymala A, Binnebosel M, Neumann U. Validity and Reliability of Three-Dimensional Imaging for Measuring Breast Cancer-Related Lymphedema in the Upper Limb: A Cross-Sectional Study. Lymphat Res Biol. 2018;16(6):525–32. https://doi.org/10.1089/lrb.2017.0076
27. Erends M, van der Aa T, de Grzymala AP, van der Hulst R. Validity and reliability of three-dimensional imaging for measuring the volume of the arm. Lymphat Res Biol. 2014;12(4):275–81. https://doi.org/10.1089/lrb.2014.0007
28. Forte AJ, Boczar D, Kassis S, Huayllani MT, McLaughlin SA. Use of magnetic resonance imaging for evaluation of therapeutic response in breast cancer-related lymphedema: A systematic review. Arch Plast Surg. 2020;47(4):305–9. https://doi.org/10.5999/aps.2020.00115
29. Sheng L, Zhang G, Li S, Jiang Z, Cao W. Magnetic Resonance Lymphography of Lymphatic Vessels in Upper Extremity With Breast Cancer-Related Lymphedema. Ann Plast Surg. 2020;84(1):100–5. https://doi.org/10.1097/SAP.0000000000001994
30. Kim SY, Lee CH, Heo SJ, Moon MH. The Clinical Usefulness of Lymphedema Measurement Technique Using Ultrasound. Lymphat Res Biol. 2021;19(4):340–6. https://doi.org/10.1089/lrb.2019.0070
31. Dylke ES, Benincasa Nakagawa H, Lin L, Clarke JL, Kilbreath SL. Reliability and Diagnostic Thresholds for Ultrasound Measurements of Dermal Thickness in Breast Lymphedema. Lymphat Res Biol. 2018;16(3):258–62. https://doi.org/10.1089/lrb.2016.0067
32. Mellor RH, Bush NL, Stanton AW, Bamber JC, Levick JR, Mortimer PS. Dual-frequency ultrasound examination of skin and subcutis thickness in breast cancer-related lymphedema. Breast J. 2004;10(6):496–503. https://doi.org/10.1111/j.1075-122X.2004.21458.x
33. Fu MR, Rosedale M. Breast cancer survivors’ experiences of lymphedema-related symptoms. J Pain Symptom Manage. 2009;38(6):849–59. https://doi.org/10.1016/j.jpainsymman.2009.04.030
34. Nguyen TT, Hoskin TL, Habermann EB, Cheville AL, Boughey JC. Breast Cancer-Related Lymphedema Risk is Related to Multidisciplinary Treatment and Not Surgery Alone: Results from a Large Cohort Study. Ann Surg Oncol. 2017;24(10):2972–80. https://doi.org/10.1245/s10434-017-5960-x
35. Rebegea L, Firescu D, Dumitru M, Anghel R. The incidence and risk factors for occurrence of arm lymphedema after treatment of breast cancer. Chirurgia (Bucur). 2015;110(1):33–7.
36. Disipio T, Rye S, Newman B, Hayes S. Incidence of unilateral arm lymphoedema after breast cancer: a systematic review and meta-analysis. Lancet Oncol. 2013;14(6):500–15. https://doi.org/10.1016/S1470-2045(13)70076-7
37. Pappalardo M, Starnoni M, Franceschini G, Baccarani A, De Santis G. Breast Cancer-Related Lymphedema: Recent Updates on Diagnosis, Severity and Available Treatments. J Pers Med. 2021;11(5). https://doi.org/10.3390/jpm11050402
38. Kwan ML, Darbinian J, Schmitz KH, Citron R, Partee P, Kutner SE, et al. Risk factors for lymphedema in a prospective breast cancer survivorship study: the Pathways Study. Arch Surg. 2010;145(11):1055–63. https://doi.org/10.1001/archsurg.2010.231
39. Ugur S, Arici C, Yaprak M, Mesci A, Arici GA, Dolay K, et al. Risk factors of breast cancer-related lymphedema. Lymphat Res Biol. 2013;11(2):72–5. https://doi.org/10.1089/lrb.2013.0004
40. Wu R, Huang X, Dong X, Zhang H, Zhuang L. Obese patients have higher risk of breast cancer-related lymphedema than overweight patients after breast cancer: a meta-analysis. Ann Transl Med. 2019;7(8):172. https://doi.org/10.21037/atm.2019.03.44
41. Armer JM, Ballman KV, McCall L, Ostby PL, Zagar E, Kuerer HM, et al. Factors Associated With Lymphedema in Women With Node-Positive Breast Cancer Treated With Neoadjuvant Chemotherapy and Axillary Dissection. JAMA Surg. 2019;154(9):800–9. https://doi.org/10.1001/jamasurg.2019.1742
42. Ayre K, Parker C. Lymphedema after treatment of breast cancer: a comprehensive review Journal of Unexplored Medical Data. 2019.
43. Erickson VS, Pearson ML, Ganz PA, Adams J, Kahn KL. Arm edema in breast cancer patients. J Natl Cancer Inst. 2001;93(2):96–111. https://doi.org/10.1093/jnci/93.2.96
44. Bucci LK, Brunelle CL, Bernstein MC, Shui AM, Gillespie TC, Roberts SA, et al. Subclinical Lymphedema After Treatment for Breast Cancer: Risk of Progression and Considerations for Early Intervention. Ann Surg Oncol. 2021. https://doi.org/10.1245/s10434-021-10196-7
45. Stout NL, Binkley JM, Schmitz KH, Andrews K, Hayes SC, Campbell KL, et al. A prospective surveillance model for rehabilitation for women with breast cancer. Cancer. 2012;118(8 Suppl):2191–200. https://doi.org/10.1002/cncr.27476
46. Kaufman DI, Shah C, Vicini FA, Rizzi M. Erratum to: Utilization of bioimpedance spectroscopy in the prevention of chronic breast cancer-related lymphedema. Breast Cancer Res Treat. 2017;166(3):817. https://doi.org/10.1007/s10549-017-4505-0
47. Yen TW, Fan X, Sparapani R, Laud PW, Walker AP, Nattinger AB. A contemporary, population-based study of lymphedema risk factors in older women with breast cancer. Ann Surg Oncol. 2009;16(4):979–88. https://doi.org/10.1245/s10434-009-0347-2
48. Casley-Smith JR. Measuring and representing peripheral oedema and its alterations. Lymphology. 1994;27(2):56–70.
49. Casley-Smith JR. Measuring Peripheral Edema and Bioimpedance. Lymphology. 1995;28:41–7.
50. Taylor R, Jayasinghe UW, Koelmeyer L, Ung O, Boyages J. Reliability and validity of arm volume measurements for assessment of lymphedema. Phys Ther. 2006;86(2):205–14. https://doi.org/10.1093/ptj/86.2.205
51. Czerniec SA, Ward LC, Refshauge KM, Beith J, Lee MJ, York S, et al. Assessment of breast cancer-related arm lymphedema--comparison of physical measurement methods and self-report. Cancer Invest. 2010;28(1):54–62. https://doi.org/10.3109/07357900902918494
52. Lee MJ, Boland RA, Czerniec S, Kilbreath SL. Reliability and concurrent validity of the perometer for measuring hand volume in women with and without lymphedema. Lymphat Res Biol. 2011;9(1):13–8. https://doi.org/10.1089/lrb.2010.0021
53. Borthwick Y, Paul L, Sneddon M, McAlpine L, Miller C. Reliability and validity of the figure-of-eight method of measuring hand size in patients with breast cancer-related lymphoedema. Eur J Cancer Care (Engl). 2013;22(2):196–201. https://doi.org/10.1111/ecc.12024
54. Mayrovitz HN, Sims N, Hill CJ, Hernandez T, Greenshner A, Diep H. Hand volume estimates based on a geometric algorithm in comparison to water displacement. Lymphology. 2006;39(2):95–103.
55. Edwick DO, Hince DA, Rawlins JM, Wood FM, Edgar DW. Alternate Electrode Positions for the Measurement of Hand Volumes Using Bioimpedance Spectroscopy. Lymphat Res Biol. 2020;18(6):560–71. https://doi.org/10.1089/lrb.2019.0078
56. Edwick DO, Hince DA, Rawlins JM, Wood FM, Edgar DW. Bioimpedance Spectroscopy Is a Valid and Reliable Measure of Edema Following Hand Burn Injury (Part 1-Method Validation). J Burn Care Res. 2020;41(4):780–7. https://doi.org/10.1093/jbcr/iraa071
57. Ward LC, Dylke ES, Kilbreath SL. Measurement of hand volume by bioelectrical impedance spectroscopy. Lymphat Res Biol. 2012;10(2):81–6. https://doi.org/10.1089/lrb.2012.0005
58. Casley-Smith JR. Alterations of untreated lymphedema and it’s grades over time. Lymphology. 1995;28(4):174–85.
59. Armer JM. The problem of post-breast cancer lymphedema: impact and measurement issues. Cancer Invest. 2005;23(1):76–83. https://doi.org/10.1081/CNV-48707
60. Armer JM, Stewart BR. A comparison of four diagnostic criteria for lymphedema in a post-breast cancer population. Lymphat Res Biol. 2005;3(4):208–17. https://doi.org/10.1089/lrb.2005.3.208
61. Bundred N, Foden P, Todd C, Morris J, Watterson D, Purushotham A, et al. Increases in arm volume predict lymphoedema and quality of life deficits after axillary surgery: a prospective cohort study. Br J Cancer. 2020;123(1):17–25. https://doi.org/10.1038/s41416-020-0844-4
62. Deltombe T, Jamart J, Recloux S, Legrand C, Vandenbroeck N, Theys S, et al. Reliability and limits of agreement of circumferential, water displacement, and optoelectronic volumetry in the measurement of upper limb lymphedema. Lymphology. 2007;40(1):26–34.
63. Sander AP, Hajer NM, Hemenway K, Miller AC. Upper-extremity volume measurements in women with lymphedema: a comparison of measurements obtained via water displacement with geometrically determined volume. Phys Ther. 2002;82(12):1201–12. https://doi.org/10.1093/ptj/82.12.1201
64. Gebruers N, Truijen S, Engelborghs S, De Deyn PP. Volumetric evaluation of upper extremities in 250 healthy persons. Clin Physiol Funct Imaging. 2007;27(1):17–22. https://doi.org/10.1111/j.1475-097X.2007.00708.x
65. Furlan C, Matheus CN, Jales RM, Derchain SFM, Bennini JR, Jr., Sarian LO. Longitudinal, Long-Term Comparison of Single- versus Multipoint Upper Limb Circumference Periodical Measurements as a Tool to Predict Persistent Lymphedema in Women Treated Surgically for Breast Cancer: An Optimized Strategy to Early Diagnose Lymphedema and Avoid Permanent Sequelae in Breast Cancer Survivors. Ann Surg Oncol. 2021. https://doi.org/10.1245/s10434-021-10290-w
66. Ward L. Is BIS Ready for Prime Time as the Gold Standard Measure. Lymphoedema. 2009;4(2):52–6.
67. Ridner SH, Shah C, Boyages J, Koelmeyer L, Ajkay N, DeSnyder SM, et al. L-Dex, arm volume, and symptom trajectories 24 months after breast cancer surgery. Cancer Med. 2020;9(14):5164–73. https://doi.org/10.1002/cam4.3188
68. Spitz JA, Chao AH, Peterson DM, Subramaniam V, Prakash S, Skoracki RJ. Bioimpedance spectroscopy is not associated with a clinical diagnosis of breast cancer-related lymphedema. Lymphology. 2019;52(3):134–42. https://doi.org/10.2458/lymph.4634
69. Cornish BH, Jacobs A, Thomas BJ, Ward LC. Optimizing electrode sites for segmental bioimpedance measurements. Physiol Meas. 1999;20(3):241–50. https://doi.org/10.1088/0967-3334/20/3/302
70. Cornish BH, Ward LC, Thomas BJ, Jebb SA, Elia M. Evaluation of multiple frequency bioelectrical impedance and Cole-Cole analysis for the assessment of body water volumes in healthy humans. Eur J Clin Nutr. 1996;50(3):159–64.
71. Stroud DB, Cornish BH, Thomas BJ, Ward LC. The use of Cole-Cole plots to compare two multifrequency bioimpedance instruments. Clin Nutr. 1995;14(5):307–11. https://doi.org/10.1016/S0261-5614(95)80069-7
72. Cornish B. Bioimpedance analysis: scientific background. Lymphat Res Biol. 2006;4(1):47–50. https://doi.org/10.1089/lrb.2006.4.47
73. Hayes S, Cornish B, Newman B. Preoperative assessment enables the early detection and successful treatment of lymphedema. Cancer. 2010;116(1):260. https://doi.org/10.1002/cncr.24733
74. York SL, Ward LC, Czerniec S, Lee MJ, Refshauge KM, Kilbreath SL. Single frequency versus bioimpedance spectroscopy for the assessment of lymphedema. Breast Cancer Res Treat. 2009;117(1):177–82. https://doi.org/10.1007/s10549-008-0090-6
75. Pennock BE, Schwan HP. Further observations on the electrical properties of hemoglobin-bound water. J Phys Chem. 1969;73(8):2600–10. https://doi.org/10.1021/j100842a024
76. Schwan HP. Electrical Properties of Bound Water. Ann NY Acad Sci. 1965;125:344–54. https://doi.org/10.1111/j.1749-6632.1965.tb45401.x
77. Nyboer J. Electrical impedance plethysmography; a physical and physiologic approach to peripheral vascular study. Circulation. 1950;2(6):811–21. https://doi.org/10.1161/01.CIR.2.6.811
78. Kubicek WG, From AH, Patterson RP, Witsoe DA, Castaneda A, Lillehei RC, et al. Impedance cardiography as a noninvasive means to monitor cardiac function. J Assoc Adv Med Instrum. 1970;4(2):79–84.
79. Ward LC, Bunce IH, Cornish BH, Mirolo BR, Thomas BJ, Jones LC. Multi-frequency bioelectrical impedance augments the diagnosis and management of lymphoedema in post-mastectomy patients. Eur J Clin Invest. 1992;22(11):751–4. https://doi.org/10.1111/j.1365-2362.1992.tb01440.x
80. Cornish BH, Bunce IH, Ward LC, Jones LC, Thomas BJ. Bioelectric impedance for monitoring the efficacy of lymphoedema treatment programmes. Breast Cancer Research and Treatment. 1996;38:169–76. https://doi.org/10.1007/BF01806671
81. Cornish BH, Chapman M, Hirst C, Mirolo B, Bunce IH, Ward LC, et al. Early diagnosis of lymphedema using multiple frequency bioimpedance. Lymphology. 2001;34(1):2–11.
82. Ward LC, Dylke E, Czerniec S, Isenring E, Kilbreath SL. Confirmation of the reference impedance ratios used for assessment of breast cancer-related lymphedema by bioelectrical impedance spectroscopy. Lymphat Res Biol. 2011;9(1):47–51. https://doi.org/10.1089/lrb.2010.0014
83. Stuchly MA, Athey TW, Samaras GM, Taylor GE. Measurement of radio frequency permittivity of biological tissues with an open-ended coaxial line: Part II - Experimental Results. IEEE Trans Microwave Therory and Techniques,. 1982;30(1):87–92. https://doi.org/10.1109/TMTT.1982.1131022
84. Gabriel S, Lau RW, Gabriel C. The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. Phys Med Biol. 1996;41(11):2251–69. https://doi.org/10.1088/0031-9155/41/11/002
85. Alanen E, Lahtinen T, Nuutinen J. Variational formulation of open-ended coaxial line in contact with layered biological medium. IEEE Trans Biomed Eng. 1998;45(10):1241–8. https://doi.org/10.1109/10.720202
86. Grant JP, Clarke RN, Symm GT, Spyrou NM. In vivo dielectric properties of human skin from 50 MHz to 2.0 GHz. Phys Med Biol. 1988;33(5):607–12. https://doi.org/10.1088/0031-9155/33/5/008
87. Alanen E, Lahtinen T, Nuutinen J. Measurement of dielectric properties of subcutaneous fat with open-ended coaxial sensors. Phys Med Biol. 1998;43(3):475-85. https://doi.org/10.1088/0031-9155/43/3/001
88. Nuutinen J, Ikaheimo R, Lahtinen T. Validation of a new dielectric device to assess changes of tissue water in skin and subcutaneous fat. Physiol Meas. 2004;25(2):447–54. https://doi.org/10.1088/0967-3334/25/2/004
89. Johansson K, Jonsson C, Bjork-Eriksson T. Compression Treatment of Breast Edema: A Randomized Controlled Pilot Study. Lymphat Res Biol. 2020;18(2):129–35. https://doi.org/10.1089/lrb.2018.0064
90. Mazor M, Smoot BJ, Mastick J, Mausisa G, Paul SM, Kober KM, et al. Assessment of local tissue water in the arms and trunk of breast cancer survivors with and without upper extremity lymphoedema. Clin Physiol Funct Imaging. 2019;39(1):57–64. https://doi.org/10.1111/cpf.12541
91. Foster KR, Schwan HP. Dielectric properties of tissues and biological materials: a critical review. Crit Rev Biomed Eng. 1989;17(1):25–104.
92. Schwan HP, Foster KR. Microwave dielectric properties of tissue. Some comments on the rotational mobility of tissue water. Biophys J. 1977;17(2):193–7. https://doi.org/10.1016/S0006-3495(77)85637-3
93. Alanen E, Lahtinen T, Nuutinen J. Penetration of electromagnetic fields of an open-ended coaxial probe between 1 MHz and 1 GHz in dielectric skin measurements. Phys Med Biol. 1999;44(7):N169–76. https://doi.org/10.1088/0031-9155/44/7/404
94. Meaney PM, Gregory AP, Seppala J, Lahtinen T. Open-Ended Coaxial Dielectric Probe Effective Penetration Depth Determination. IEEE Trans Microw Theory Tech. 2016;64(3):915–23. https://doi.org/10.1109/TMTT.2016.2519027
95. Lahtinen T, Nuutinen J, Alanen E. Dielectric properties of the skin. Phys Med Biol. 1997;42(7):1471–2. https://doi.org/10.1088/0031-9155/42/7/020
96. Mayrovitz HN. Local tissue water assessed by measuring forearm skin dielectric constant: dependence on measurement depth, age and body mass index. Skin Res Technol. 2010;16(1):16–22. https://doi.org/10.1111/j.1600-0846.2009.00398.x
97. Mayrovitz HN, Davey S, Shapiro E. Local tissue water assessed by tissue dielectric constant: anatomical site and depth dependence in women prior to breast cancer treatment-related surgery. Clin Physiol Funct Imaging. 2008;28(5):337–42. https://doi.org/10.1111/j.1475-097X.2008.00814.x
98. Mayrovitz HN, Forbes J, Vemuri A, Krolick K, Rubin S. Skin tissue dielectric constant in women with high body fat content. Skin Res Technol. 2020;26(2):226–33. https://doi.org/10.1111/srt.12784
99. Mayrovitz HN, Grammenos A, Corbitt K, Bartos S. Young adult gender differences in forearm skin-to-fat tissue dielectric constant values measured at 300 MHz. Skin Res Technol. 2016;22(1):81–8. https://doi.org/10.1111/srt.12232
100. Mayrovitz HN, Bernal M, Carson S. Gender differences in facial skin dielectric constant measured at 300 MHz. Skin Res Technol. 2012;18(4):504–10. https://doi.org/10.1111/j.1600-0846.2011.00582.x
101. Mayrovitz HN, Carson S, Luis M. Male-female differences in forearm skin tissue dielectric constant. Clin Physiol Funct Imaging. 2010;30(5):328–32. https://doi.org/10.1111/j.1475-097X.2010.00946.x
102. Mayrovitz HN, Grammenos A, Corbitt K, Bartos S. Age-related changes in male forearm skin-to-fat tissue dielectric constant at 300 MHz. Clin Physiol Funct Imaging. 2017;37(2):198–204. https://doi.org/10.1111/cpf.12286
103. Mayrovitz HN, Singh A, Akolkar S. Age-related differences in tissue dielectric constant values of female forearm skin measured noninvasively at 300 MHz. Skin Res Technol. 2016;22(2):189–95. https://doi.org/10.1111/srt.12249
104. Mayrovitz H. Impact of body fat and obesity on tissue dielectric constant (TDC) as a method to assess breast cancer treatment-related lymphedema (BCRL). Lymphology. 2019;52(1):18–24. https://doi.org/10.2458/lymph.4621
105. Koehler LA, Mayrovitz HN. Spatial and Temporal Variability of Upper Extremity Edema Measures After Breast Cancer Surgery. Lymphat Res Biol. 2019;17(3):308–15. https://doi.org/10.1089/lrb.2018.0022
106. Mayrovitz HN, Luis M. Spatial variations in forearm skin tissue dielectric constant. Skin Res Technol. 2010;16(4):438–43. https://doi.org/10.1111/j.1600-0846.2010.00456.x
107. Mayrovitz HN, Weingrad DN, Lopez L. Assessing localized skin-to-fat water in arms of women with breast cancer via tissue dielectric constant measurements in pre- and post-surgery patients. Ann Surg Oncol. 2015;22(5):1483–9. https://doi.org/10.1245/s10434-014-4185-5
108. Mayrovitz HN, Weingrad DN, Lopez L. Tissue Dielectric Constant (TDC) as an Index of Skin Water in Women With and Without Breast Cancer: Upper Limb Assessment Via a Self-Contained Compact Measurement Device. Lymphology. 2016;49(1):27–35.
109. Johansson K, Darkeh MH, Lahtinen T, Bjork-Eriksson T. Two-Year Follow-up of Temporal Changes of Breast Edema After Breast Cancer Treatment with Surgery and Radiation Evaluated by Tissue Dielectric Constant (TDC). The European Journal of Lymphology. 2015;27(73):15–21.
110. Mayrovitz HN, Patel A, Kavadi R, Khan Z, Bartolone S. An Approach Toward Assessing Head-and-Neck Lymphedema Using Tissue Dielectric Constant Ratios: Method and Normal Reference Values. Lymphat Res Biol. 2021. https://doi.org/10.1089/lrb.2020.0107
111. Mayrovitz HN, Alvarez A, Labra M, Mikulka A, Woody D. Possible applications of normative lower to upper limb ratios of tissue dielectric constant to lower extremity edema. Int Angiol. 2019;38(1):70–5. https://doi.org/10.23736/S0392-9590.18.04088-9
112. Mayrovitz HN. Assessing Lower Extremity Lymphedema Using Upper and Lower Extremity Tissue Dielectric Constant Ratios: Method and Normal Reference Values. Lymphat Res Biol. 2019;17(4):457–64. https://doi.org/10.1089/lrb.2018.0039
113. Mayrovitz HN, Weingrad DN, Davey S. Tissue Dielectric Constant (TDC) Measurements as a Means of Characterizing Localized Tissue Water in Arms of Women With and Without Breast Cancer Treatment Releated Lymphedema. Lymphology. 2014;47:142–50.
114. Mayrovitz HN, Weingrad DN, Davey S. Local tissue water in at-risk and contralateral forearms of women with and without breast cancer treatment-related lymphedema. Lymphat Res Biol. 2009;7(3):153–8. https://doi.org/10.1089/lrb.2009.0008
115. Mayrovitz HN, Fasen M, Spagna P, Wong J. Role of handedness on forearm skin tissue dielectric constant (TDC) in relation to detection of early-stage breast cancer-related lymphedema. Clin Physiol Funct Imaging. 2018;38(4):670–5. https://doi.org/10.1111/cpf.12466
116. Mayrovitz HN, Arzanova E, Somarriba S, Eisa S. Reference Values for Assessing Localized Hand Lymphedema Using Interhand Tissue Dielectric Constant Ratios. Lymphat Res Biol. 2018;16(5):442–5. https://doi.org/10.1089/lrb.2017.0065
117. Cau N, Galli M, Cimolin V, Grossi A, Battarin I, Puleo G, et al. Quantitative comparison between the laser scanner three-dimensional method and the circumferential method for evaluation of arm volume in patients with lymphedema. J Vasc Surg Venous Lymphat Disord. 2018;6(1):96–103. https://doi.org/10.1016/j.jvsv.2017.08.014
118. Hameeteman M, Verhulst AC, Vreeken RD, Maal TJ, Ulrich DJ. 3D stereophotogrammetry in upper-extremity lymphedema: An accurate diagnostic method. J Plast Reconstr Aesthet Surg. 2016;69(2):241–7. https://doi.org/10.1016/j.bjps.2015.10.011
119. Landau MJ, Kim JS, Gould DJ, Patel KM. Vectra 3D Imaging for Quantitative Volumetric Analysis of the Upper Limb: A Feasibility Study for Tracking Outcomes of Lymphedema Treatment. Plast Reconstr Surg. 2018;141(1):80e-4e. https://doi.org/10.1097/PRS.0000000000003912
120. Ohberg F, Zachrisson A, Holmner-Rocklov A. Three-dimensional camera system for measuring arm volume in women with lymphedema following breast cancer treatment. Lymphat Res Biol. 2014;12(4):267–74. https://doi.org/10.1089/lrb.2014.0026
121. Gniadecka M, Quistorff B. Assessment of dermal water by high-frequency ultrasound: comparative studies with nuclear magnetic resonance. Br J Dermatol. 1996;135(2):218–24. https://doi.org/10.1111/j.1365–2133.1996.tb01150.x
122. Gniadecka M. Localization of dermal edema in lipodermatosclerosis, lymphedema, and cardiac insufficiency. High-frequency ultrasound examination of intradermal echogenicity. J Am Acad Dermatol. 1996;35(1):37–41. https://doi.org/10.1016/S0190-9622(96)90493-4
123. Mander A, Venosi S, Menegatti E, Byung-Boong L, Neuhardt D, Maietti E, et al. Upper limb secondary lymphedema ultrasound mapping and characterization. Int Angiol. 2019;38(4):334–42. https://doi.org/10.23736/S0392-9590.19.04176-2
124. Polat AV, Ozturk M, Polat AK, Karabacak U, Bekci T, Murat N. Efficacy of Ultrasound and Shear Wave Elastography for the Diagnosis of Breast Cancer-Related Lymphedema. J Ultrasound Med. 2020;39(4):795–803. https://doi.org/10.1002/jum.15162
125. Bustos SS, Zhou B, Huang TCT, Shao J, Ciudad P, Forte AJ, et al. Ultrasound Vibroelastography for Evaluation of Secondary Extremity Lymphedema: A Clinical Pilot Study. Ann Plast Surg. 2020;85(S1 Suppl 1):S92-S6. https://doi.org/10.1097/SAP.0000000000002448
126. Hashemi HS, Fallone S, Boily M, Towers A, Kilgour RD, Rivaz H. Assessment of Mechanical Properties of Tissue in Breast Cancer-Related Lymphedema Using Ultrasound Elastography. IEEE Trans Ultrason Ferroelectr Freq Control. 2019;66(3):541–50. https://doi.org/10.1109/TUFFC.2018.2876056
127. Donahue PMC, Crescenzi R, Lee C, Garza M, Patel NJ, Petersen KJ, et al. Magnetic resonance imaging and bioimpedance evaluation of lymphatic abnormalities in patients with breast cancer treatment-related lymphedema. Breast Cancer Res Treat. 2020;183(1):83–94. https://doi.org/10.1007/s10549-020-05765-5
128. Cellina M, Gibelli D, Martinenghi C, Giardini D, Soresina M, Menozzi A, et al. Non-contrast magnetic resonance lymphography (NCMRL) in cancer-related secondary lymphedema: acquisition technique and imaging findings. Radiol Med. 2021. https://doi.org/10.1007/s11547-021-01410-3
129. Cellina M, Oliva G, Menozzi A, Soresina M, Martinenghi C, Gibelli D. Non-contrast Magnetic Resonance Lymphangiography: an emerging technique for the study of lymphedema. Clin Imaging. 2019;53:126–33. https://doi.org/10.1016/j.clinimag.2018.10.006
130. Franconeri A, Ballati F, Panzuto F, Raciti MV, Smedile A, Maggi A, et al. A proposal for a semiquantitative scoring system for lymphedema using Non-contrast Magnetic Resonance Lymphography (NMRL): Reproducibility among readers and correlation with clinical grading. Magn Reson Imaging. 2020;68:158–66. https://doi.org/10.1016/j.mri.2020.02.004
131. Brorson H, Ohlin K, Olsson G, Karlsson MK. Breast cancer-related chronic arm lymphedema is associated with excess adipose and muscle tissue. Lymphat Res Biol. 2009;7(1):3–10. https://doi.org/10.1089/lrb.2008.1022
132. Trinh L, Peterson P, Brorson H, Mansson S. Assessment of Subfascial Muscle/Water and Fat Accumulation in Lymphedema Patients Using Magnetic Resonance Imaging. Lymphat Res Biol. 2019;17(3):340–6. https://doi.org/10.1089/lrb.2018.0027
133. Lahtinen T, Seppala J, Viren T, Johansson K. Experimental and Analytical Comparisons of Tissue Dielectric Constant (TDC) and Bioimpedance Spectroscopy (BIS) in Assessment of Early Arm Lymphedema in Breast Cancer Patients after Axillary Surgery and Radiotherapy. Lymphat Res Biol. 2015;13(3):176–85.