ArticlePloS one2019
Comparison of a novel algorithm quantitatively estimating epifascial fibrosis in three-dimensional computed tomography images to other clinical lymphedema grading methods.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The diagnostic accuracy of soft tissue oedema measurements: a systematic review and best-evidence synthesis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Pooled it
- Automated CT segmentation for lower extremity tissues in lymphedema evaluation using deep learning.European radiology · 2025Article
- Advances in etiology, pathophysiology, diagnosis, and management of lymphedema: a comprehensive review.Frontiers in medicine · 2025Review
- Reply.Journal of vascular surgery. Venous and lymphatic disorders · 2024Article
- Deep learning-based quantitative estimation of lymphedema-induced fibrosis using three-dimensional computed tomography images.Scientific reports · 2022Observational
- Relationship between lymphedema after breast cancer treatment and biophysical characteristics of the affected tissue.PloS one · 2022Article
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6 authors.
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Abstract
No method has yet been approved for detecting lymphedema fibrosis before its progression. This study assessed the feasibility of computed tomography-based estimation of fibrosis. This observational, cross-sectional study included patients with lymphedema affecting one limb. Three types (maximum, mean, minimum) of computed tomography reticulation indexes were digitally calculated from trans-axial images using absorptive values, and the computed tomography reticulation indexes compared with clinical scales and measurements. Of 326 patients evaluated by at least one of lymphoscintigraphy, bio-electrical impedance, and computed tomography, 24 were evaluated by all three. The mean number of computed tomography scans in these patients was 109. Sixteen patients had breast cancer, seven had gynecologic cancers, and one had primary lymphedema. Mean computed tomography reticulation index (r = 0.52, p < 0.01) and maximal computed tomography reticulation index (r = 0.45, p < 0.05) were significantly associated with time from initial limb swelling to computed tomography. Mean computed tomography reticulation index (r = 0.86, p < 0.01), minimal computed tomography reticulation index (r = 0.79, p < 0.01), and maximal computed tomography reticulation index (r = 0.68, p < 0.01) were significantly associated with International Society of Lymphedema substage. Minimal computed tomography reticulation index correlated with 1-kHz-based bio-electrical impedance ratio (r = -0.46, p < 0.05) and with standardized proximal limb circumference difference ratio (r = 0.45, p < 0.05) of both limbs. Maximal computed tomography reticulation index had a sensitivity of 0.78, specificity of 0.60, and areas under the curve of 0.66 in detecting lymphoscintigraphic stage IV. The algorithm utilizing three-dimensional computed tomography images of epifascial fibrosis may be used as a marker for lymphedema duration, limb swelling, International Society of Lymphedema substage, and interstitial lymphatic fluids of lymphedema. The current approach shows promise in providing an additional method to assist in characterizing and monitoring lymphedema patients.
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