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Preoperative assessment of retroperitoneal Liposarcoma using volume-based 18F-FDG PET/CT: implications for surgical strategy and prognosis
- Source :
- BMC Medical Imaging, Vol 23, Iss 1, Pp 1-8 (2023)
- Publication Year :
- 2023
- Publisher :
- BMC, 2023.
-
Abstract
- Abstract Purpose Retroperitoneal liposarcoma (RLPS) poses a challenging scenario for surgeons due to its unpredictable biological behavior. Surgery remains the primary curative option for RLPS; however, the need for additional information to guide surgical strategies persists. Volume-based 18F-FDG PET/CT may solve this issue. Methods We analyzed data from 89 RLPS patients, measuring metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum standardized uptake value (SUVmax) and explored their associations with clinical, prognostic, and pathological factors. Results MTV, TLG of multifocal and recurrent RLPS were significantly higher than unifocal and primary ones (P < 0.001, P < 0.001, P = 0.003 and P = 0.002, respectively). SUVmax correlated with FNCLCC histological grade, mitotic count and Ki-67 index (P for G1/G2 = 0.005, P for G2/G3 = 0.017, and P for G1/G3 = 0.001, P < 0.001 and P = 0.024, respectively). MTG, TLG and SUVmax of WDLPS were significantly lower than DDLPS and PLPS (P for MTV were 0.009 and 0.022, P for TLG were 0.028 and 0.048, and P for SUVmax were 0.027 and < 0.001, respectively). Multivariable Cox analysis showed that MTV > 457.65 (P = 0.025), pathological subtype (P = 0.049) and FNCLCC histological grade (P = 0.033) were related to overall survival (OS). Conclusions Our findings indicate that MTV is an independent prognostic factor for RLPS, while MTV, TLG, and SUVmax can preoperatively predict multifocal lesions, histological grade, and pathological subtype. Volume-based 18F-FDG PET/CT offers valuable information to aid in the decision-making process for RLPS surgical strategies.
Details
- Language :
- English
- ISSN :
- 14712342
- Volume :
- 23
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Medical Imaging
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.890f43520e5f4ffd8f8c3e62ea7aee4f
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12880-023-01179-z