BACKGROUND: Treatment for @entity0 has increased @entity1 survivorship exponentially over the past few decades. With increased survivorship, more @entity1 are living with the longstanding effects of @entity0 treatment, such as @entity4269 . @entity1 , health care providers, and payers depend on practical and efficient clinical measures to accurately diagnose and monitor disease progression or regression. However, current clinical measures do not include objective measures that assess lymphedetamous tissue accurately. This study compared current measures to a novel use of ultrasound (US) imaging to quantify tissue texture. METHODS AND RESULTS: Seventeen @entity1 diagnosed with @entity4269 completed self-report questionnaires and then were tested twice by two @entity4269 physical therapists who measured @entity4 , @entity82 , and limb volume differences. One therapist measured subjects' limbs using US imaging and derived measures of entropy and average pixel intensity. Volume measures were consistent between therapists (p   <   0.01) but palpation was not (0.01   <   p   <   0.72). Therapists' measures correlated better to subjects' self-report of @entity4 (0.01   <   p   >   0.32) as compared to @entity82 (0.23   <   p   >   0.90). US measures were reliable (Cronbachs's a   =   0.7 and 0.91 for entropy and API, respectively). Entropy measures demonstrated significant differences between subjects' involved versus uninvolved forearms (p   =   0.03). CONCLUSIONS: Therapists were not consistent with each other when rating @entity4 or @entity82 ; however, they were consistent when measuring limb volume differences. US measures (entropy) demonstrated a significant difference between involved and uninvolved. US imaging, as a tool to quantify subcutaneous tissues, holds promise to be a safe, mobile, and effective method to measure @entity4269 tissue texture.

Ultrasound and Clinical Measures for XXXX .

@entity1 :: ('9606', 'Species') :: ['women', 'Patients', 'patient'] @entity82 :: ('MESH:D005355', 'Disease') :: ['fibrosis'] @entity0 :: ('MESH:D001943', 'Disease') :: ['breast cancer'] @entity4 :: ('MESH:D004487', 'Disease') :: ['edema'] @entity4269 :: ('MESH:D008209', 'Disease') :: ['lymphedema']
@entity4269 :: (MESH:D008209,Disease) :: ['Lymphedema']
