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Bin Xu (1), Alexei Teplov (1), Kareem Ibrahim (1), Takashi Inoue (1), Ben Stueben (1), Nora Katabi (1), Meera Hameed (1), Yukako Yagi (1), Ronald Ghossein (1)
Modern Pathology, July 2020. DOI: 10.1038/s41379-020-0605-1
In the modern era, detailed pathologic characteristics of a thyroid tumor are crucial to achieve accurate diagnosis and guide treatment. The presence of capsular invasion (CI) is diagnostic for carcinoma, whereas vascular invasion (VI) and nodal metastasis (NM) are included in risk stratification. However, the very definition of CI and VI is surrounded by controversies and an accurate assessment of NM is lacking. Whole Block Imaging (WBI) by microCT is a new imaging modality to create 3D reconstruction of whole tissue block with microscopic level resolution without the need for tissue sectioning. In this study, we aimed to define CI, VI, and NM volume using WBI by microCT. Twenty-eight paraffin blocks (PBs) from 26 thyroid tumors were scanned. Ten PBs contained CI, whereas 7 had VI. 3D microCT images were compared with whole slide images (WSI) of corresponding H&E slides. In 2 cases with VI and/or CI, WSI of serial H&E slides were obtained and underwent 3D-reconstruction to be compared with the WBI. Satellite tumor nodules beyond tumor capsule were shown to be CI by demonstrating the point of penetration using microCT and 3D reconstruction. Additional foci of CI were detected using microCT. VI was seen using microCT. Fibrin associated with tumor thrombus was not always present on serially sectioned H&E slides. WBI by microCT scanner was able to assess the volume of NM. In conclusion, WBI is able to detect CI, VI, and assess the volume of NM in thyroid carcinoma without tissue sectioning. It is the ultimate method for the complete sampling of the tumor capsule. It has the potential to increase the detection rate of CI, better define criteria for CI and VI, and provide an accurate assessment of the volume of nodal disease. This technology may impact the future practice of surgical pathology.
Dragonfly was used to visualize and analyse reconstructed imaging data.
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