Stanzel Susanne, Nazerani-Zemann Tina, Weitzer Friedrich, Weinke Roland, Plhak Elisabeth, Aigner Reingard Maria
Division of Nuclear Medicine, Department of Radiology, Medical University of Graz, Auenbruggerplatz 9A, 8036, Graz, Austria.
Division of General Radiology, Department of Radiology, Medical University of Graz, Auenbruggerplatz 9A, 8036, Graz, Austria.
Sci Rep. 2025 Jul 14;15(1):25433. doi: 10.1038/s41598-025-10740-5.
Demarcation of small pancreatic and metastatic abdominal lesions is challenging due to the noisy background. We evaluated the impact of time-of-flight (TOF) in conjunction with TrueX (= point spread function (PSF)-based algorithm) or Q.Clear (= Bayesian penalized likelihood reconstruction algorithm) in dual-phase (DP) F-FDG-PET/CT on image quality (IQ) and lesion detection rate in staging suspected pancreatic cancer. This prospective single-center study included 120 patients. A total of 908 lesions were evaluated by three board-certified nuclear medicine physicians. IQ, SUV, and lesion volume (V) of pancreatic lesions, lymph node metastases, organ metastases, and other benign lesions were compared between TOF and non-TOF. All pancreatic lesions were histopathologically confirmed, and all other lesions were confirmed either histopathologically or radiologically. IQ and lesion demarcation were scored on a 6-point Likert-type scale. Overall IQ and demarcation of pancreatic lesions (PLD) were very good in TOF-images (overall IQ, non-TOF, 2.2; TOF, 1.8, P = 0.017; PLD, non-TOF, 2.6, TOF, 2.2, P < 0.001). Thirty-four additional lesions in 23 (19%) patients were detected using TOF alone (mean [SD] SUV 4.6 [1.5]; mean [SD] V 2.6 cm [1.3]). 18/23 metastatic lesions identified with TOF alone led to treatment change in 8 patients. SUV was significantly increased (P< 0.001), whereas V was significantly decreased in TOF images (P = 0.002). Application of TOF poses additional value in detecting small pancreatic and metastatic lesions, which has an impact on further treatment, avoiding unnecessary surgery.
由于背景噪声，对胰腺小病变和腹部转移灶进行区分具有挑战性。我们评估了飞行时间（TOF）结合TrueX（基于点扩散函数（PSF）的算法）或Q.Clear（贝叶斯惩罚似然重建算法）在双期（DP）F-FDG-PET/CT中对疑似胰腺癌分期时的图像质量（IQ）和病变检出率的影响。这项前瞻性单中心研究纳入了120例患者。三位获得董事会认证的核医学医师共评估了908个病变。比较了TOF和非TOF情况下胰腺病变、淋巴结转移、器官转移及其他良性病变的IQ、SUV和病变体积（V）。所有胰腺病变均经组织病理学证实，所有其他病变经组织病理学或放射学证实。IQ和病变区分度采用6分李克特量表评分。TOF图像中胰腺病变的总体IQ和区分度（PLD）非常好（总体IQ，非TOF为2.2；TOF为1.8，P = 0.017；PLD，非TOF为2.6，TOF为2.2，P < 0.001）。仅使用TOF检测出23例（19%）患者中的34个额外病变（平均[标准差]SUV为4.6[1.5]；平均[标准差]V为2.6 cm[1.3]）。仅通过TOF识别出的18/23个转移病变导致8例患者的治疗方案改变。在TOF图像中，SUV显著增加（P < 0.001），而V显著减小（P = 0.－－原文此处有误，推测应为0.002）。应用TOF在检测胰腺小病变和转移病变方面具有额外价值，这对进一步治疗有影响，可避免不必要的手术。
