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Rationale and objectivesBreast cancer occurs more frequently in the upper outer (UO) quadrant, but whether this higher cancer incidence is related to the greater amount of dense tissue is not known. Magnetic resonance imaging acquires three-dimensional volumetric images and is the most suitable among all breast imaging modalities for regional quantification of density. This study applied a magnetic resonance imaging-based method to measure quadrant percent density (QPD), and evaluated its association with the quadrant location of the developed breast cancer.Materials and methodsA total of 126 cases with pathologically confirmed breast cancer were reviewed. Only women who had unilateral breast cancer located in a clear quadrant were selected for analysis. A total of 84 women, including 47 Asian women and 37 western women, were included. An established computer-aided method was used to segment the diseased breast and the contralateral normal breast, and to separate the dense and fatty tissues. Then, a breast was further separated into four quadrants using the nipple and the centroid as anatomic landmarks. The tumor was segmented using a computer-aided method to determine its quadrant location. The distribution of cancer quadrant location, the quadrant with the highest QPD, and the proportion of cancers occurring in the highest QPD were analyzed.ResultsThe highest incidence of cancer occurred in the UO quadrant (36 out of 84, 42.9%). The highest QPD was also noted most frequently in the UO quadrant (31 out of 84, 36.9%). When correlating the highest QPD with the quadrant location of breast cancer, only 17 women out of 84 (20.2%) had breast cancer occurring in the quadrant with the highest QPD.ConclusionsThe results showed that the development of breast cancer in a specific quadrant could not be explained by the density in that quadrant, and further studies are needed to find the biological reasons accounting for the higher breast cancer incidence in the UO quadrant.

The infiltrative nature of lesions is a significant feature of malignant breast lesion on ultrasound image. Characterizing the infiltrative nature of lesions with computationally inexpensive and highly efficacious features is crucial for the realization of a computer-aided diagnosis system. In this study, the infiltrative nature is regarded as an energy that produces irregularly and considerably local variances in a 1-D signal. The local variances can be characterized by a few high octave energies (i.e., the channel energies close to low-frequency bands) in a 1-D discrete periodic wavelet transform. For computational cost reduction, high octave decomposition is performed by a reversible round-off 1-D nonrecursive discrete periodic wavelet transform. A test dataset of breast sonograms with the lesion contour delineated by an experienced physician and two inexperienced persons is built for feature efficacy evaluation. High individual performance results imply that the proposed feature is well correlated with the diagnosis of the experienced physician. Experimental results also reveal that with a great performance improvement, the proposed feature is suitable for the combination with some morphometric parameters. Index Terms--Breast lesion classification, octave energy, reversible round-off 1-D nonrecursive discrete periodic wavelet transform (RRO-NRDPWT), roughness description.

The article discusses that the COVID-19 has spread rapidly in China and other parts of the world since December 31, 2019. It mentions that the first reported COVID-19 case in Taiwan was confirmed on January 21, 2020; and Taiwan experienced hospital-acquired severe acute respiratory syndrome (SARS) infections in 2003, so people hesitated to come to hospitals and risked SARS transmission and many people in Taiwan have been afraid to visit hospitals during the COVID-19 pandemic.