Lesion characterization in spectral photon-counting tomosynthesisShow others and affiliations
2017 (English)In: Medical Imaging 2017: Physics of Medical Imaging, SPIE - International Society for Optical Engineering, 2017, Vol. 10132, article id 1013205Conference paper, Published paper (Refereed)
Abstract [en]
It has previously been shown that 2D spectral mammography can be used to discriminate between (likely benign) cystic and (potentially malignant) solid lesions in order to reduce unnecessary recalls in mammography. One limitation of the technique is, however, that the composition of overlapping tissue needs to be interpolated from a region surrounding the lesion. The purpose of this investigation was to demonstrate that lesion characterization can be done with spectral tomosynthesis, and to investigate whether the 3D information available in tomosynthesis can reduce the uncertainty from the interpolation of surrounding tissue. A phantom experiment was designed to simulate a cyst and a tumor, where the tumor was overlaid with a structure that made it mimic a cyst. In 2D, the two targets appeared similar in composition, whereas spectral tomosynthesis revealed the exact compositional difference. However, the loss of discrimination signal due to spread from the plane of interest was of the same strength as the reduction of anatomical noise. Results from a preliminary investigation on clinical tomosynthesis images of solid lesions yielded results that were consistent with the phantom experiments, but were still to some extent inconclusive. We conclude that lesion characterization is feasible in spectral tomosynthesis, but more data, as well as refinement of the calibration and discrimination algorithms, are needed to draw final conclusions about the benefit compared to 2D.
Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2017. Vol. 10132, article id 1013205
Series
Progress in Biomedical Optics and Imaging - Proceedings of SPIE, ISSN 1605-7422 ; 10132
Keywords [en]
Lesion characterization, Mammography, Photon counting, Spectral imaging, Tomosynthesis
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:kth:diva-210010DOI: 10.1117/12.2253966ISI: 000405562100004Scopus ID: 2-s2.0-85020434176ISBN: 9781510607095 (print)OAI: oai:DiVA.org:kth-210010DiVA, id: diva2:1116846
Conference
Medical Imaging 2017: Physics of Medical Imaging, Orlando, United States, 13 February 2017 through 16 February 2017
Note
QC 20170628
2017-06-282017-06-282024-03-15Bibliographically approved