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The purpose of this work was to quantify 3.0 T (i) T(1) and T(2) relaxation times of in vivo human lymph nodes (LNs) and (ii) LN relaxometry differences between healthy LNs and LNs from patients with lymphatic insufficiency secondary to breast cancer treatment-related lymphedema (BCRL). MR relaxometry was performed over bilateral axillary regions at 3.0 T in healthy female controls (105 LNs from 20 participants) and patients with BCRL (108 LNs from 20 participants). Quantitative T(1) maps were calculated using a multi-flip-angle (20, 40, 60°) method with B(1) correction (dual-T(R) method, T(R1) /T(R2) = 30/130 ms), and T(2) maps using a multi-echo (T(E) = 9-189 ms; 12 ms intervals) method. T(1) and T(2) were quantified in the LN cortex and hilum. A Mann-Whitney U-test was applied to compare LN relaxometry values between patients and controls (significance, two sided, p < 0.05). Linear regression was applied to evaluate how LN relaxometry varied with age, BMI, and clinical indicators of disease. LN substructure relaxation times (mean ± standard deviation) in healthy controls were T(1) cortex, 1435 ± 391 ms; T(1) hilum, 714 ± 123 ms; T(2) cortex, 102 ± 12 ms, and T(2) hilum, 119 ± 21 ms. T(1) of the LN cortex was significantly reduced in the contralateral axilla of BCRL patients compared with the axilla on the surgical side (p < 0.001) and compared with bilateral control values (p < 0.01). The LN cortex T(1) asymmetry discriminated cases from controls (p = 0.004) in a multiple linear regression, accounting for age and BMI. Human 3.0 T T(1) and T(2) relaxation times in axillary LNs were quantified for the first time in vivo. Measured values are relevant for optimizing acquisition parameters in anatomical lymphatic imaging sequences, and can serve as a reference for novel functional and molecular LN imaging methods that require quantitative knowledge of LN relaxation times.
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Background: Breast cancer treatment-related lymphedema (BCRL) arises from a mechanical insufficiency following cancer therapies. Early BCRL detection and personalized intervention require an improved understanding of the physiological processes that initiate lymphatic impairment. Here, internal magnetic resonance imaging (MRI) measures of the tissue microenvironment were paired with clinical measures of tissue structure to test fundamental hypotheses regarding structural tissue and muscle changes after the commonly used therapeutic intervention of manual lymphatic drainage (MLD)., Methods and Results: Measurements to identify lymphatic dysfunction in healthy volunteers (n = 29) and patients with BCRL (n = 16) consisted of (1) limb volume, tissue dielectric constant, and bioelectrical impedance (i.e., non-MRI measures); (2) qualitative 3 Tesla diffusion-weighted, T1-weighted and T2-weighted MRI; and (3) quantitative multi-echo T2 MRI of the axilla. Measurements were repeated in patients immediately following MLD. Normative control and BCRL T2 values were quantified and a signed Wilcoxon Rank-Sum test was applied (significance: two-sided p < 0.05). Non-MRI measures yielded significant capacity for discriminating between arms with versus without clinical signs of BCRL, yet yielded no change in response to MLD. Alternatively, a significant increase in deep tissue T2 on the involved (pre T2 = 0.0371 ± 0.003 seconds; post T2 = 0.0389 ± 0.003; p = 0.029) and contralateral (pre T2 = 0.0365 ± 0.002; post T2 = 0.0395 ± 0.002; p < 0.01) arms was observed. Trends for larger T2 increases on the involved side after MLD in patients with stage 2 BCRL relative to earlier stages 0 and 1 BCRL were observed, consistent with tissue composition changes in later stages of BCRL manifesting as breakdown of fibrotic tissue after MLD in the involved arm. Contrast consistent with relocation of fluid to the contralateral quadrant was observed in all stages., Conclusion: Quantitative deep tissue T2 MRI values yielded significant changes following MLD treatment, whereas non-MRI measurements did not vary. These findings highlight that internal imaging measures of tissue composition may be useful for evaluating how current and emerging therapies impact tissue function.
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Lipedema is a chronic adipose tissue condition that primarily affects women. Despite increasing recognition of lipedema, the condition remains poorly understood and lacks standardized diagnostic criteria or confirmatory tests. Variability in definitions and measurement across clinical and research settings impedes comparability across studies, constraining the evidence base needed to support future advances in clinical practice and patient care. To address challenges associated with inconsistent definitions and data collection, the Lipedema Foundation (LF) partnered with clinicians, researchers, and biostatisticians to develop a Lipedema Common Case Report Form (CCRF). The CCRF was designed to be a research data harmonization tool and is not intended to define diagnostic standards or guide clinical treatment decisions. Its development involved review of published lipedema clinical guidelines and collaborative work to define data elements and attributes for inclusion. When they existed, validated or standardized measures were incorporated directly. When no suitable standardized measures were available, an iterative and collaborative process was used to develop lipedema-specific Common Data Elements (CDEs). The initial version of the CCRF was piloted in participants with and without lipedema, and updates based on participant and clinician feedback were incorporated into the CCRF. A biostatistical review evaluated data completeness, quality, and structure, leading to additional refinements. The final Version 1 instrument consists of 682 CDEs organized into four classifications: (1) Core, (2) Supplemental Highly Recommended, (3) Supplemental, and (4) Exploratory. The current version is prepared for dissemination in the field. By disseminating the CCRF broadly and encouraging adoption in all lipedema research beginning in 2026, including all newly initiated LF-funded projects, LF intends to evaluate its use with grantees and iterate systematically to achieve consistent and comparable data collection. The CCRF provides a structured framework for harmonized data collection that may facilitate comparability across studies and support future development of standardized diagnostic and research methodologies.
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