The in vivo estimation of tissue elasticity parameters is important for realistic tissue deformation modelling and diagnosis tasks such as cancer mass detection and characterization. Elastography (strain imaging) provides non-quantitative information about tissue stiffness and is becoming well established clinically. Acoustic radiation force imaging, supersonic shear wave imaging and (Young's) modulus imaging are all evolving as quantitative methods. This paper concerns the latter. The established approach to Young's modulus reconstruction involves solving the so-called inverse elasticity problem of recovering elastic parameters by comparing the displacement field from the measurements and the theoretical tissue deformation modelling. In this paper, a new modulus imaging pathway is proposed in which the inverse problem of elasticity reconstruction has been converted into a global optimization problem involving an image similarity measure. This approach is applied to ultrasound images and the tissue elasticity distribution is recovered by adaptively adding new regions based on the local mismatch of the images using a multiscaled split-and-merge approach. For this experimental evaluation of the performance of the proposed method, first synthetic images are used with different Gaussian noise levels. The reconstructed elasticity shows good agreement with the ground-truth. A comparison of the proposed method with a conventional displacement-based method is made using a gelatine phantom. The results using both methods agree remarkably well with the theoretical prediction. A further in vivo study on 19 breast cancer masses was performed. The present method estimated an elasticity contrast of 6.41 ¡ 0.98 between cancerous tissue and normal tissue, which is consistent with values reported elsewhere in the literature.

Objective: This pilot study investigates the role of assisted-freehand ultrasound (AFUSON) elasticity imaging of the breast in assessing the contour, size and area of 23 early breast cancers by making comparison of AFUSON with the equivalent B-mode ultrasound images and gold standard histopathology slides. Methods: The B-mode, AFUSON and digitised histopathology slides of three early breast cancers were compared for contour, size and area with histopathology scans. AFUSON features that corresponded to areas of known malignant change on the histopathology slides were regarded as diagnostic. These diagnostic criteria were then applied to the B-mode and AFUSON elasticity images of all 23 breast cancers in the pilot study without having the availability of the histopathology scans for reference. Corresponding diameters were measured and the results were compared with the equivalent measurements on the scans of the histology slides. The results were tabulated in histogram form. Diagnostic confidence levels were evaluated. Results: Size dimension accuracy increased from 66% using B-mode alone to 82% using combined B-mode and AFUSON elasticity images. Tumour area accuracy was also increased. A small number of cases had a striking visual similarity of shape on AFUSON elasticity scans and histopathology slides. Conclusion: In spite of the shortfalls in this study, AFUSON elasticity imaging was capable of acquiring some high-quality images that showed strong correlation between AFUSON elasticity and scans of histology slides. Further studies will be carried out to refine the technique and determine if it has a role in the diagnosis and management of breast cancer. Breast cancer is the most common cancer occurring in women in the Western world. Currently, the lifetime risk of developing breast cancer for UK women is 1:9, and on average 126 new cases are diagnosed each day [1]. Current trends in cancer imaging are aimed towards technological development of non-invasive techniques that provide high diagnostic sensitivity and specificity and also prognostic information about the primary tumour upon which to base treatment regimens. Such developments are taking place notably in ultrasound, CT, MRI and positron emission tomography (PET).Ultrasound elasticity imaging of soft tissues has been developed over the last 20 years and is under evaluation as an additional tool in the ultrasound armamentarium to supplement the diagnostic information obtained during conventional B-mode scanning. It is now found on several currently commercially available ultrasound systems [2][3][4]. These systems rely on freehand ultrasound scanning for its flexibility and simplicity [4][5][6][7][8][9] but like all freehand systems there is significant inter-and intraobserver error [10,11]. During the last 5 years we have developed an elasticity scanning system called assistedfreehand ultrasound (AFUSON) elasticity imaging as a method of reducing this variability by applying semiautomated, measurable external compression during an ultrasound scan. It sho...

)Purpose To validate the predictive power for determining breast cancer risk of an automated breast density measurement system with full-fi eld digital mammography (FFDM). Materials and methods Two hundred cancers and 200 controls were imaged with FFDM. Density was measured separately on MLO and CC images using an integral automated volumetric breast density measurement system (Hologic, Quantra). For each cancer, the contralateral mammogram was used. Each cancer was matched to a control case by date of birth, age at examination and laterality of mammogram used for density determination. Breast density (percentage of fi broglandular tissue) was analyzed by Quantra. Data were analyzed by conditional logistic regression to determine the eff ect on breast cancer risk. Results The percentage of breast density ranged from 6% to 63%. Density declined signifi cantly with age (P <0.001). Overall, there was no signifi cant association of density with risk of breast cancer (P = 0.4). There was a suggestive increase in risk with dense volume higher than 35% (OR = 1.80, 95% CI = 0.96 to 3.39, P = 0.07). There was signifi cant heterogeneity by age in the eff ect of density on risk (P = 0.04). In women aged <50, density was signifi cantly associated with increased risk (P = 0.02), with odds ratios of 6.06, 3.98 and 10.59 for density volumes of 15 to 24%, 25 to 34% and ≥35% respectively, relative to those with <15%. In women aged ≥50 years there was no association of density with risk (P = 0.5). Conclusions Quantra automated volumetric breast density measurement is strongly associated with breast cancer risk in women aged under 50, but not in women aged ≥50 years or over. O2Ultrasound elastography as an adjuvant to conventional ultrasound in the preoperative assessment of axillary lymph nodes in suspected breast cancer: a pilot study K Taylor Introduction NICE guidelines recommend conventional ultrasound (CU) of the axilla as preliminary staging in patients with breast cancer. However, up to one-third of nodes showing normal morphology are metastatic on surgical histology [1]. Ultrasound elastography (UE) uses received radiofrequency data to produce an elastogram depicting tissue stiff ness. UE has been researched in the breast but there are no published data regarding UE of the axilla. Methods Fifty women attending the breast unit as symptomatic GP referrals with breast lesions sonographically suspicious of breast cancer underwent UE of the axilla simultaneously with routine CU examination. Elastograms were visually scored, strain measurements calculated and nodal perimeter and area measurements recorded. UE was compared with CU with histology as the reference standard. Results Twenty-nine nodes were histologically normal, 21 were metastatic. Normal nodes were indistinguishable from surrounding tissue on UE. Using cut-off points for biopsy selected for the study, sensitivity was 90% for UE visual scoring, 100% for strain scoring and 76% for CU. Specifi cities were 86%, 48% and 78% respectively. ROC analysis yielded AUC values ...