Evidence map›Paper›PMID 39498988›Full record

ArticleUrology research & practice2024

Hounsfield Unit on Preoperative Computed Tomography as an Indicator of Prognosis in Patients with Liposarcoma.

Ryo Andy Ogasawara, Shugo Yajima, Naoki Imasato, Kohei Hirose, Ken Sekiya, Madoka Kataoka, Yasukazu Nakanishi, Hitoshi Masuda

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Article in Urology research & practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ryo Andy OgasawaraDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Shugo YajimaDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Naoki ImasatoDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Kohei HiroseDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Ken SekiyaDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Madoka KataokaDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Yasukazu NakanishiDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.
Hitoshi MasudaDepartment of Urology, National Cancer Center Hospital East, Chiba, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Liposarcoma (LPS) is classified into 4 subtypes. As some subtypes have a high recurrence rate, knowing the risk of recurrence before surgery is important. Here, we aimed to investigate the relationship between Hounsfield units (HU) derived from preoperative computed tomography (CT) and the prognosis of patients undergoing surgery. Materials and Methods: We included 32 patients who underwent surgery for LPS between 2014 and 2022. Preoperative plain CT images were collected, and the HU value of each LPS was measured. The association between 2 HU categories (HU < cut-off vs. ≥ cut-off) and clinical variables was assessed. The optimal cut-off value was determined using statistical methods. We used the Kaplan-Meier method to determine the differences between the 2 HU categories at 2 endpoints: recurrence-free survival (RFS) and overall survival (OS). Results: The dedifferentiated subtype showed significantly higher HU values than the other subtypes (P < .001). The optimal cut-off value for HU was 20. HU < 20 was associated with young age, low-performance status, low Charlson Comorbidity Index, and well-differentiated pathology. The Kaplan-Meier curves demonstrated that RFS and OS were significantly shorter in patients with HU ≥ 20 than in those with HU < 20 (P = .007 and .04, respectively). However, when stratified based on subtype, no significant differences were observed between dedifferentiated and other subtypes. Conclusion: HU ≥ 20 on preoperative CT was associated with poor prognosis in LPS patients. Our findings suggest that preoperative CT-derived HU values may serve as useful predictors of prognosis.

Indexed as

Computed tomographydedifferentiated liposarcomaprognosiswell-differentiated liposarcomax-ray

Identifiers

PMID39498988
PMCPMC11562811

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