Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report

ObjectiveTo evaluate the feasibility and effectivity of deep learning (DL) plus three-dimensional (3D) printing in the management of giant sporadic renal angiomyolipoma (RAML).MethodsThe medical records of patients with giant (>15 cm) RAML were retrospectively reviewed from January 2011 to De...

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Autores principales:	Yunliang Gao, Yuanyuan Tang, Da Ren, Shunhua Cheng, Yinhuai Wang, Lu Yi, Shuang Peng
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	deep learning three-dimensional printing giant kidney angiomyolipoma partial nephrectomy Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/dcb4f0715ac547ad9ab026375e452b10
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spelling	oai:doaj.org-article:dcb4f0715ac547ad9ab026375e452b102021-11-15T04:31:29ZDeep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report2234-943X10.3389/fonc.2021.724986https://doaj.org/article/dcb4f0715ac547ad9ab026375e452b102021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.724986/fullhttps://doaj.org/toc/2234-943XObjectiveTo evaluate the feasibility and effectivity of deep learning (DL) plus three-dimensional (3D) printing in the management of giant sporadic renal angiomyolipoma (RAML).MethodsThe medical records of patients with giant (>15 cm) RAML were retrospectively reviewed from January 2011 to December 2020. 3D visualized and printed kidney models were performed by DL algorithms and 3D printing technology, respectively. Patient demographics and intra- and postoperative outcomes were compared between those with 3D-assisted surgery (3D group) or routine ones (control group).ResultsAmong 372 sporadic RAML patients, 31 with giant ones were eligible for analysis. The median age was 40.6 (18–70) years old, and the median tumor size was 18.2 (15–28) cm. Seventeen of 31 (54.8%) had a surgical kidney removal. Overall, 11 underwent 3D-assisted surgeries and 20 underwent routine ones. A significant higher success rate of partial nephrectomy (PN) was noted in the 3D group (72.7% vs. 30.0%). Patients in the 3D group presented a lower reduction in renal function but experienced a longer operation time, a greater estimated blood loss, and a higher postoperative morbidity. Subgroup analysis was conducted between patients undergoing PN with or without 3D assistance. Despite no significant difference, patients with 3D-assisted PN had a slightly larger tumor size and higher nephrectomy score, possibly contributing to a relatively higher rate of complications. However, 3D-assisted PN lead to a shorter warm ischemia time and a lower renal function loss without significant difference. Another subgroup analysis between patients under 3D-assisted PN or 3D-assisted RN showed no statistically significant difference. However, the nearness of tumor to the second branch of renal artery was relatively shorter in 3D-assisted PN subgroup than that in 3D-assisted RN subgroup, and the difference between them was close to significant.Conclusions3D visualized and printed kidney models appear to be additional tools to assist operational management and avoid a high rate of kidney removal for giant sporadic RAMLs.Yunliang GaoYuanyuan TangDa RenShunhua ChengYinhuai WangLu YiLu YiShuang PengFrontiers Media S.A.articledeep learningthree-dimensional printinggiantkidneyangiomyolipomapartial nephrectomyNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	deep learning three-dimensional printing giant kidney angiomyolipoma partial nephrectomy Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	deep learning three-dimensional printing giant kidney angiomyolipoma partial nephrectomy Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Yunliang Gao Yuanyuan Tang Da Ren Shunhua Cheng Yinhuai Wang Lu Yi Lu Yi Shuang Peng Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report
description	ObjectiveTo evaluate the feasibility and effectivity of deep learning (DL) plus three-dimensional (3D) printing in the management of giant sporadic renal angiomyolipoma (RAML).MethodsThe medical records of patients with giant (>15 cm) RAML were retrospectively reviewed from January 2011 to December 2020. 3D visualized and printed kidney models were performed by DL algorithms and 3D printing technology, respectively. Patient demographics and intra- and postoperative outcomes were compared between those with 3D-assisted surgery (3D group) or routine ones (control group).ResultsAmong 372 sporadic RAML patients, 31 with giant ones were eligible for analysis. The median age was 40.6 (18–70) years old, and the median tumor size was 18.2 (15–28) cm. Seventeen of 31 (54.8%) had a surgical kidney removal. Overall, 11 underwent 3D-assisted surgeries and 20 underwent routine ones. A significant higher success rate of partial nephrectomy (PN) was noted in the 3D group (72.7% vs. 30.0%). Patients in the 3D group presented a lower reduction in renal function but experienced a longer operation time, a greater estimated blood loss, and a higher postoperative morbidity. Subgroup analysis was conducted between patients undergoing PN with or without 3D assistance. Despite no significant difference, patients with 3D-assisted PN had a slightly larger tumor size and higher nephrectomy score, possibly contributing to a relatively higher rate of complications. However, 3D-assisted PN lead to a shorter warm ischemia time and a lower renal function loss without significant difference. Another subgroup analysis between patients under 3D-assisted PN or 3D-assisted RN showed no statistically significant difference. However, the nearness of tumor to the second branch of renal artery was relatively shorter in 3D-assisted PN subgroup than that in 3D-assisted RN subgroup, and the difference between them was close to significant.Conclusions3D visualized and printed kidney models appear to be additional tools to assist operational management and avoid a high rate of kidney removal for giant sporadic RAMLs.
format	article
author	Yunliang Gao Yuanyuan Tang Da Ren Shunhua Cheng Yinhuai Wang Lu Yi Lu Yi Shuang Peng
author_facet	Yunliang Gao Yuanyuan Tang Da Ren Shunhua Cheng Yinhuai Wang Lu Yi Lu Yi Shuang Peng
author_sort	Yunliang Gao
title	Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report
title_short	Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report
title_full	Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report
title_fullStr	Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report
title_full_unstemmed	Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report
title_sort	deep learning plus three-dimensional printing in the management of giant (>15 cm) sporadic renal angiomyolipoma: an initial report
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/dcb4f0715ac547ad9ab026375e452b10
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Deep Learning Plus Three-Dimensional Printing in the Management of Giant (>15 cm) Sporadic Renal Angiomyolipoma: An Initial Report

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