Cribriform architecture is a histological pattern reminiscent of Swiss cheese that is commonly recognized in ductal carcinoma in situ (DCIS) of the breast observed by microscope. However, there are only a few three-dimensional studies to elucidate whether each glandular cavities of cribriform pattern are connected or not. The main reason for paucity of three-dimensional studies is that the conventional reconstruction based on histological sections requires laborious and time-consuming works. In this research, we first performed three-dimensional reconstruction of the cribriform pattern using crystal analyzer-based phase contrast technique, X-ray dark field computed tomography (XDFI-CT), which provides high contrast image of biological soft tissue with non-destructive and non-staining approach. Then, we propose a machine-learning-based method to extract the cavity from XDFI-CT images. Finally, we show that the useful information to analyze the cribriform patterns in DCIS such as the density and volume of the cavity can be obtained from the XDFI-CT images.
Purpose: High-resolution cardiac imaging and fiber analysis methods are required to understand cardiac anatomy. Although refraction-contrast x-ray CT (RCT) has high soft tissue contrast, it cannot be commonly used because it requires a synchrotron system. Microfocus x-ray CT (μCT) is another commercially available imaging modality.
Approach: We evaluate the usefulness of μCT for analyzing fibers by quantitatively and objectively comparing the results with RCT. To do so, we scanned a rabbit heart by both modalities with our original protocol of prepared materials and compared their image-based analysis results, including fiber orientation estimation and fiber tracking.
Results: Fiber orientations estimated by two modalities were closely resembled under the correlation coefficient of 0.63. Tracked fibers from both modalities matched well the anatomical knowledge that fiber orientations are different inside and outside of the left ventricle. However, the μCT volume caused incorrect tracking around the boundaries caused by stitching scanning.
Conclusions: Our experimental results demonstrated that μCT scanning can be used for cardiac fiber analysis, although further investigation is required in the differences of fiber analysis results on RCT and μCT.
High-resolution cardiac imaging and fiber analysis methods are desired for deeper understanding cardiac anatomy. Although refraction-contrast X-ray CT (RCT) has high contrast for soft tissues, its scanning cost is very high. On the other hand, micro-focus X-ray CT (μCT) is a modality that is commercially available with lower cost, but its contrast for soft tissue is not as high as RCT. To investigate the efficacy of μCT for fiber analysis, we scanned a common rabbit heart with both modalities with our original protocol of preparing materials, and compared their image-based analysis results. Their results were very similar, with correlation coefficient of 0.95. We confirmed that µCT volumes prepared by our protocol are useful for fiber analysis as well as RCT.