Breast histoscanning: the development of a novel technique to improve tissue characterization during breast ultrasound

Abstract

)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 ...

Using imaging biomarkers to improve the planning of radical prostatectomies

“…This CAD technology has been tested in clinical trials aimed to distinguish benign from malignant tissue in the breast and the ovary, but its widespread clinical use has not been adopted for these tissues [10][11][12]. According to published data, it has the potential to predict cancer lesion location within the prostate at 90% sensitivity and 72% specificity for tumors that are more than 0.2 cm 3 in volume compared to RP specimens [1,9].…”