Presurgical Identification of Uterine Smooth Muscle Malignancies through the Characteristic FDG Uptake Pattern on PET Scans.
Kung-Chu HoYu-Hua Dean FangGigin LinShir-Hwa UengTzu-I WuChyong-Huey LaiHo-Yen ChuehAngel ChaoTing-Chang ChangTzu-Chen YenPublished in: Contrast media & molecular imaging (2018)
The unidentified presence of uterine smooth muscle malignancies poses a tremendous risk in women planning surgery for presumed benign leiomyomas. We sought to investigate whether preoperative FDG PET may be useful to identify leiomyosarcomas (LMS) and smooth muscle tumors of uncertain malignant potential (STUMP). Methods. We investigated patients with rapidly growing uterine masses which were suspected of being malignant on ultrasound or MRI. Among the 21 patients who underwent FDG PET, we identified 7 LMS, 1 STUMP, and 13 leiomyomas. PET-derived parameters and FDG uptake patterns were analyzed retrospectively. Results. The SUVmax values of LMS/STUMP (range: 3.7-11.8) were significantly higher than those observed in leiomyomas (range: 2.0-9.4; P=0.003) despite a significant overlap. The metabolic tumor/necrosis ratio was significantly higher in LMS/STUMP than in leiomyomas (P < 0.001), with no significant intergroup overlaps. All LMS/STUMP revealed a characteristic pattern of FDG uptake, identifying a specific "hollow ball" sign (corresponding to areas of coagulative tumor necrosis). In contrast, this sign was invariably absent in patients with leiomyomas. Conclusion. The characteristic FDG uptake pattern instead of SUV on PET images allows identifying LMS/STUMP in patients with rapidly growing uterine masses, avoiding the deleterious consequences of regular surgery for presumed benign leiomyomas.
Keyphrases
- smooth muscle
- pet ct
- positron emission tomography
- pet imaging
- computed tomography
- contrast enhanced
- minimally invasive
- magnetic resonance imaging
- end stage renal disease
- magnetic resonance
- ejection fraction
- newly diagnosed
- patients undergoing
- polycystic ovary syndrome
- type diabetes
- adipose tissue
- pregnant women
- deep learning
- pulmonary embolism
- insulin resistance
- fine needle aspiration
- climate change
- contrast enhanced ultrasound
- liquid chromatography
- high resolution
- pregnancy outcomes
- patient reported outcomes
- atomic force microscopy