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Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma

BACKGROUND: To describe grayscale ultrasound (US) features of metastatic ovarian tumors (MOTs) based on origin of the primary tumor in a large sample size study. METHODS: This retrospective cross-sectional single-center study included 112 patients with 190 histopathologically confirmed MOTs. Among t...

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Autores principales: Liu, Junying, Chang, Cai, Zhang, Haixian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816721/
https://www.ncbi.nlm.nih.gov/pubmed/36620168
http://dx.doi.org/10.21037/qims-21-1149
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author Liu, Junying
Chang, Cai
Zhang, Haixian
author_facet Liu, Junying
Chang, Cai
Zhang, Haixian
author_sort Liu, Junying
collection PubMed
description BACKGROUND: To describe grayscale ultrasound (US) features of metastatic ovarian tumors (MOTs) based on origin of the primary tumor in a large sample size study. METHODS: This retrospective cross-sectional single-center study included 112 patients with 190 histopathologically confirmed MOTs. Among the patients, 102 collectively had 144 masses, which were detected via US. The clinical data and static US images of MOTs were collected. RESULTS: The MOTs were mostly bilateral (78.9%) but had a lower rate of bilaterality when detected by US (55.6%). Breast cancer metastasis had the highest nondetection rate (69.6%), because its focal metastasis could only be recognized using histology or immunohistochemistry. The stomach was the most common origin of metastasis (45.3% and 50.7% detected via pathology and US, respectively). The US images were classified into three subtypes: multilocular solid (Type A), purely solid (Type B), and solid with several round or oval cysts (Type C). The MOTs that originated from the colon mostly belonged to Type A (65.1%) and closely mimicked primary epithelial ovarian tumor morphologically. The MOTs that originated from the stomach predominantly belonged to Types B (31.5%) and C (57.5%). Signet-ring cell carcinoma (SRCC) corresponded to Types B and C regardless of origin. CONCLUSIONS: The developed novel typing method provides more vivid images for classifying MOTs compared with existing typing methods. Given that no specific sonographic parameters have been established to distinguish MOTs from primary invasive ovarian tumors, these images may be helpful in diagnosing these masses.
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spelling pubmed-98167212023-01-07 Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma Liu, Junying Chang, Cai Zhang, Haixian Quant Imaging Med Surg Original Article BACKGROUND: To describe grayscale ultrasound (US) features of metastatic ovarian tumors (MOTs) based on origin of the primary tumor in a large sample size study. METHODS: This retrospective cross-sectional single-center study included 112 patients with 190 histopathologically confirmed MOTs. Among the patients, 102 collectively had 144 masses, which were detected via US. The clinical data and static US images of MOTs were collected. RESULTS: The MOTs were mostly bilateral (78.9%) but had a lower rate of bilaterality when detected by US (55.6%). Breast cancer metastasis had the highest nondetection rate (69.6%), because its focal metastasis could only be recognized using histology or immunohistochemistry. The stomach was the most common origin of metastasis (45.3% and 50.7% detected via pathology and US, respectively). The US images were classified into three subtypes: multilocular solid (Type A), purely solid (Type B), and solid with several round or oval cysts (Type C). The MOTs that originated from the colon mostly belonged to Type A (65.1%) and closely mimicked primary epithelial ovarian tumor morphologically. The MOTs that originated from the stomach predominantly belonged to Types B (31.5%) and C (57.5%). Signet-ring cell carcinoma (SRCC) corresponded to Types B and C regardless of origin. CONCLUSIONS: The developed novel typing method provides more vivid images for classifying MOTs compared with existing typing methods. Given that no specific sonographic parameters have been established to distinguish MOTs from primary invasive ovarian tumors, these images may be helpful in diagnosing these masses. AME Publishing Company 2022-10-08 2023-01-01 /pmc/articles/PMC9816721/ /pubmed/36620168 http://dx.doi.org/10.21037/qims-21-1149 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Liu, Junying
Chang, Cai
Zhang, Haixian
Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
title Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
title_full Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
title_fullStr Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
title_full_unstemmed Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
title_short Grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
title_sort grayscale ultrasound feature typing of metastatic ovarian tumors, particularly signet-ring cell carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816721/
https://www.ncbi.nlm.nih.gov/pubmed/36620168
http://dx.doi.org/10.21037/qims-21-1149
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