Slip imaging: reducing ambiguity in breast lesion assessment.

Ultrasound elasticity imaging (elastography) is gaining popularity as an adjunct to B-mode ultrasound for breast cancer diagnosis. Cancerous masses are usually stiffer than normal tissue, hence, using elasticity imaging should lead to better differentiation between benign and malignant masses than using B-mode alone. Clinicians assess the mobility of masses on palpation; cancers usually being less mobile.

Radiologic characteristics and management of screen-detected metastatic carcinoid tumor of the breast: a case report.

Carcinoid tumors are known to metastasize to the breast, but their appearance can mimic a primary breast carcinoma, making biopsy essential in order to give the correct preoperative diagnosis. It has been suggested that core biopsy might precipitate a carcinoid crisis and should be avoided. We describe a case of screen-detected carcinoid tumor metastasis in the breast safely diagnosed by core biopsy and present the imaging findings, including magnetic resonance imaging and elastography.

Assisted-freehand ultrasound elasticity imaging.

Good-quality elasticity imaging requires highly controlled compressions of the breast, which are often challenging to obtain with freehand, even by an experienced radiologist. This paper presents assisted-freehand ultrasound (AFUSON): a fusion of freehand and automated ultrasound systems designed to assisted elasticity imaging acquisition while remaining as flexible as freehand. In the form of a hand-held device, this semi-automatic solution delivers both increased acquisition precision and control.

Elasticity reconstruction from displacement and confidence measures of a multi-compressed ultrasound RF sequence.

Ultrasound elasticity imaging shows promise as a new way for early detection of cancers by assessing the elastic characteristics of soft tissue. So far the commonly used approach involves solving the so-called inverse elasticity problem of recovering elastic parameters from displacement measurements. We propose a finite-elementbased nonlinear scheme to estimate the elasticity distribution of soft tissue from multi-compressed ultrasound radio frequency (RF) data.