Contrast-enhanced digital mammography (CEDM) is used to detect iodine uptake in breast lesions. Iodine concentrations inside or around breast lesions could be used as a biomarker, provided a properly characterized quantification method is implemented. In this work, we have evaluated a method to quantify iodine concentrations in CEDM in terms of its intrinsic linearity, bias and variability. This evaluation was performed in a virtual clinical trial (VCT) environment, simulating anthropomorphic breast phantoms containing solid and liquid lesions with different iodine concentrations. Our results showed that anatomical variables such as breast size and lesion size and composition have a considerable effect on the iodine quantification. The method was linear in the clinical iodine concentration range, and showed an approximately constant 1 mg/cm2 bias in the 0 – 2 mg/cm2 range for both solid and liquid lesions. Corrections were proposed that reduced the variability due to breast size, lesion size, and composition.
KEYWORDS: Ultrasonography, Scattering, Signal to noise ratio, Breast cancer, Tissues, Breast, Data acquisition, Image processing, Statistical analysis, Signal processing
In this study we present a preliminary evaluation of the inter-operator (InterOp) and intra-operator (IntraOp) variability of Quantitative Ultrasound features based on first-order speckle statistics used in breast cancer characterization. Ultrasound echo signals from ten patients with biopsy-confirmed invasive ductal carcinomas were acquired in vivo in the radial and antiradial planes with a commercial ultrasound system using a linear array transducer. Each patient was scanned by three radiologists, each of which performed three acquisitions allowing the patient to reposition in between acquisitions. Parametric images of six QUS features obtained from the first order statistics of the speckle pattern of ultrasound images were computed, and the mean feature value within the lesion boundary was compared between pairs of images from different radiologists or acquisitions from the same radiologist. In general, the InterOp variability was 1.2 times larger than the IntraOp variability. These differences were not significant in the radial plane. In addition, features with similar InterOp and IntraOp variability were the ones with the largest overall variability.
Purpose: To investigate the potential of uncertainty analysis asthe first step to explore the relation between lesions texture, in single energy temporal contrast-enhanced mammography (SET), and immunohistochemistry (IHC) status of breast cancer. Methods: Texture features (TF) extracted from the co-occurrence matrix were considered. We studied three sources of uncertainty: stability of the mammography unit, misalignment between pre- and post-contrast images, and manual delineation of suspicious regions. The first two sources were analyzed using phantoms. For uncertainty due to manual delineation, three different radiologists segmented 33 malignant lesions on SET studies. Two segmentation criteria were evaluated: to draw around the lesion border, and to select a focal region with the greatest suspicion of malignancy. Inter- and intra-observer agreement were evaluated in terms of the intra-class correlation coefficient (ICC) and the Pearson correlation coefficient (PCC). The relation between texture features and IHC status was explored. Results: Misalignment was the major source of uncertainty, followed by lesion delineation and the stability of the mammography unit. There was good inter-observer (ICC>0.7) and intra-observer (PCC>0.8) agreement among TF obtained from regions around the lesion border; however, TF from focal regions only agreed in terms of mean value and correlation. Texture analysis predicted the presence of hormone receptors and a high proliferation rate moderately better than an educated. The texture features that conducted to the best prediction models were the mean value, Imc2 and average contrast. Conclusions: Uncertainty evaluation improves textures analysis and assessment of the prediction model. A wider range of imaging features could improve the prediction of (IHC) status.
Temporal contrast-enhanced digital mammography (CEDM) is an image technique that might improve detection of secondary breast lesions (multicentric and multifocal breast cancer) as an alternative to breast MRI. This work refers to its implementation using a commercial mammography unit and reports preliminary clinical results. Image acquisition parameters (beam quality and other radiological settings) were optimized to maximize iodine contrast to noise ratio in subtracted images acquired under single- and dual-energy techniques, limited to 2.4 mGy average glandular dose. An analytical formalism is presented to assess how optimization results are affected by breast thickness. Weighting factors were determined using a novel method, and a single value was proposed for each pair of beam qualities, regardless of breast thickness or dose distribution. Twenty-six patients with suspected multicentric breast cancer have been studied, applying results from this formalism, with temporal CEDM and MRI followed by biopsy of suspicious lesions. Preliminary results show that both procedures have a similar sensitivity to detect malignancy (90% and 89%). Additionally, the effect of compression on iodine uptake has been investigated, observing a significant increase in iodine when compression force was reduced from 40 N to 20 N (3.6 mg/cm2 vs. 1.6 mg/cm2, p=0.0004).
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.