<p>Three-dimensional (3D) histopathology is an important expansion to histopathology, as a complete understanding of the 3D structure of tissues can lead to better diagnoses and treatments. For certain highly deformable tissues like carotid plaques, 3D histology reconstructions are a challenging endeavor, requiring context-dependent corrections of artifacts that undergo more significant deformations during histological processing. Currently, there is no method of 3D reconstruction specifically designed for highly deformed histology that contains multiple spatially disconnected tissue components. To address this, we present ARONG, an Artifact-correcting Reconstruction Of Nonrigidly-deformed Geometries. ARONG is a pipeline that allows the user to reconstruct highly deformed histology in 3D. ARONG provides a methodology for iteratively aligning 2D histology slides through a set of affine transformations, while providing guidance on the mechanism of correction and order of priority for fixing common artifacts that appear in highly deformable tissue histology. Since highly deformable tissue histology often contains distorted local features, shapes, and edges, we also outline our matching criteria for aligning regions within neighboring slides. Using ARONG, we reconstructed slides from twenty human atheromatous carotid plaques, which are often highly deformable, and computed intersection over union with ex vivo ultrasound for four of the specimens (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">$0.64\pm 0.19$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>0.64</mn> <mo>±</mo> <mn>0.19</mn> </mrow> </math></EquationSource> </InlineEquation>). ARONG outperformed the next best transformation method (CODA, a state-of-the-art 3D reconstruction program) with a <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$\approx 14\%$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>≈</mo> <mn>14</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation> higher Jaccard index. We also validated this pipeline with two human FaDu xenograft tumors, three murine hearts, and two murine carotid arteries sectioned at different intervals, with comparable or improved metrics compared to CODA and other relevant 3D reconstruction methods.</p>

Introducing ARONG, A 3D Reconstruction Method for Highly Deformed Histology

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2026年3月31日

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Yurim Lee,
Kwangok P. Nickel,
Maxwell J. Kiernan,
Rashid Al Mukaddim,
Yuming Liu,
Viktor Mitchell,
Tenzin Ngawang,
Shahriar Salamat,
Stephanie M. Wilbrand,
Melissa Graham,
Kevin W. Eliceiri,
Randall J. Kimple,
Robert J. Dempsey,
Tomy Varghese

摘要

Three-dimensional (3D) histopathology is an important expansion to histopathology, as a complete understanding of the 3D structure of tissues can lead to better diagnoses and treatments. For certain highly deformable tissues like carotid plaques, 3D histology reconstructions are a challenging endeavor, requiring context-dependent corrections of artifacts that undergo more significant deformations during histological processing. Currently, there is no method of 3D reconstruction specifically designed for highly deformed histology that contains multiple spatially disconnected tissue components. To address this, we present ARONG, an Artifact-correcting Reconstruction Of Nonrigidly-deformed Geometries. ARONG is a pipeline that allows the user to reconstruct highly deformed histology in 3D. ARONG provides a methodology for iteratively aligning 2D histology slides through a set of affine transformations, while providing guidance on the mechanism of correction and order of priority for fixing common artifacts that appear in highly deformable tissue histology. Since highly deformable tissue histology often contains distorted local features, shapes, and edges, we also outline our matching criteria for aligning regions within neighboring slides. Using ARONG, we reconstructed slides from twenty human atheromatous carotid plaques, which are often highly deformable, and computed intersection over union with ex vivo ultrasound for four of the specimens ( $0.64\pm 0.19$ $0.64 \pm 0.19$ ). ARONG outperformed the next best transformation method (CODA, a state-of-the-art 3D reconstruction program) with a $\approx 14\%$ $\approx 14 %$ higher Jaccard index. We also validated this pipeline with two human FaDu xenograft tumors, three murine hearts, and two murine carotid arteries sectioned at different intervals, with comparable or improved metrics compared to CODA and other relevant 3D reconstruction methods.