Dataset Information

Prognostic role of computed tomography-based, artificial intelligence-driven waist skeletal muscle volume in uterine endometrial carcinoma.

ABSTRACT:

Objectives

To investigate the impact of computed tomography (CT)-based, artificial intelligence-driven waist skeletal muscle volume on survival outcomes in patients with endometrial cancer.

Methods

We retrospectively identified endometrial cancer patients who received primary surgical treatment between 2014 and 2018 and whose pre-treatment CT scans were available (n = 385). Using an artificial intelligence-based tool, the skeletal muscle area (cm²) at the third lumbar vertebra (L3) and the skeletal muscle volume (cm³) at the waist level were measured. These values were converted to the L3 skeletal muscle index (SMI) and volumetric SMI by normalisation with body height. The relationships between L3, volumetric SMIs, and survival outcomes were evaluated.

Results

Setting 39.0 cm²/m² of L3 SMI as cut-off value for sarcopenia, sarcopenia (< 39.0 cm²/m², n = 177) and non-sarcopenia (≥ 39.0 cm²/m², n = 208) groups showed similar progression-free survival (PFS; p = 0.335) and overall survival (OS; p = 0.241). Using the median value, the low-volumetric SMI group (< 206.0 cm³/m³, n = 192) showed significantly worse PFS (3-year survival rate, 77.3% vs. 88.8%; p = 0.004) and OS (3-year survival rate, 92.8% vs. 99.4%; p = 0.003) than the high-volumetric SMI group (≥ 206.0 cm³/m³, n = 193). In multivariate analyses adjusted for baseline body mass index and other factors, low-volumetric SMI was identified as an independent poor prognostic factor for PFS (adjusted HR, 1.762; 95% CI, 1.051-2.953; p = 0.032) and OS (adjusted HR, 5.964; 95% CI, 1.296-27.448; p = 0.022).

Conclusions

Waist skeletal muscle volume might be a novel prognostic biomarker in patients with endometrial cancer. Assessing body composition before treatment can provide important prognostic information for such patients.

SUBMITTER: Kim SI

PROVIDER: S-EPMC8688657 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Prognostic role of computed tomography-based, artificial intelligence-driven waist skeletal muscle volume in uterine endometrial carcinoma.

Kim Se Ik SI Chung Joo Yeon JY Paik Haerin H Seol Aeran A Yoon Soon Ho SH Kim Taek Min TM Kim Hee Seung HS Chung Hyun Hoon HH Cho Jeong Yeon JY Kim Jae-Weon JW Lee Maria M

Insights into imaging 20211220 1

<h4>Objectives</h4>To investigate the impact of computed tomography (CT)-based, artificial intelligence-driven waist skeletal muscle volume on survival outcomes in patients with endometrial cancer.<h4>Methods</h4>We retrospectively identified endometrial cancer patients who received primary surgical treatment between 2014 and 2018 and whose pre-treatment CT scans were available (n = 385). Using an artificial intelligence-based tool, the skeletal muscle area (cm<sup>2</sup>) at the third lumbar v ...[more]

PMID: 34928453

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Dataset Information

Prognostic role of computed tomography-based, artificial intelligence-driven waist skeletal muscle volume in uterine endometrial carcinoma.

Objectives

Methods

Results

Conclusions

Publications

Prognostic role of computed tomography-based, artificial intelligence-driven waist skeletal muscle volume in uterine endometrial carcinoma.

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