The dynamic flow imaging phantom is capable of producing accurate and reproducible results which can be predicted and quantified. This results in a unique tool for perfusion DCE-CT validation under realistic flow conditions which can be applied not only to compare different CT scanners and imaging protocols but also to provide a ground truth across multimodality dynamic imaging given its MRI and PET compatibility.

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Simple and robust techniques are lacking to assess performance of flow quantification using dynamic imaging. We therefore developed a method to qualify flow quantification technologies using a physical compartment exchange phantom and image analysis tool. We validate and demonstrate utility of this method using dynamic PET and SPECT. Dynamic image sequences were acquired on two PET/CT and a cardiac dedicated SPECT (with and without attenuation and scatter corrections) systems. A two-compartment exchange model was fit to image derived time-activity curves to quantify flow rates. Flowmeter measured flow rates (20-300 mL/min) were set prior to imaging and were used as reference truth to which image derived flow rates were compared. Both PET cameras had excellent agreement with truth ( [Formula: see text]). High-end PET had no significant bias (p > 0.05) while lower-end PET had minimal slope bias (wash-in and wash-out slopes were 1.02 and 1.01) but no significant reduction in precision relative to high-end PET (<15% vs. <14% limits of agreement, p > 0.3). SPECT (without scatter and attenuation corrections) slope biases were noted (0.85 and 1.32) and attributed to camera saturation in early time frames. Analysis of wash-out rates from non-saturated, late time frames resulted in excellent agreement with truth ( [Formula: see text], slope = 0.97). Attenuation and scatter corrections did not significantly impact SPECT performance. The proposed phantom, software and quality assurance paradigm can be used to qualify imaging instrumentation and protocols for quantification of kinetic rate parameters using dynamic imaging.

BackgroundThe rabbit VX2 lung cancer model is a large animal model useful for preclinical lung cancer imaging and interventional studies. However, previously reported models had issues in terms of invasiveness of tumor inoculation, control of tumor aggressiveness and incidence of complications.PurposeWe aimed to develop a minimally invasive rabbit VX2 lung cancer model suitable for imaging and transbronchial interventional studies.MethodsNew Zealand white rabbits and VX2 tumors were used in the study. An ultra-thin bronchoscope was inserted through a miniature laryngeal mask airway into the bronchus. Different numbers of VX2 tumor cells were selectively inoculated into the lung parenchyma or subcarinal mediastinum to create a uniform tumor with low incidence of complications. The model was characterized by CT, FDG-PET, and endobronchial ultrasound (EBUS). Liposomal dual-modality contrast agent was used to evaluate liposome drug delivery system in this model.ResultsBoth peripheral and mediastinal lung tumor models were created. The tumor making success rate was 75.8% (25/33) in the peripheral lung tumor model and 60% (3/5) in the mediastinal tumor model. The group of 1.0×106 of VX2 tumor cells inoculation showed a linear growth curve with less incidence of complications. Radial probe EBUS visualized the internal structure of the tumor and the size measurement correlated well with CT measurements (r2 = 0.98). Over 7 days of continuous enhancement of the lung tumor by liposomal contrast in the lung tumor was confirmed both CT and fluorescence imaging.ConclusionOur minimally invasive bronchoscopic rabbit VX2 lung cancer model is an ideal platform for lung cancer imaging and preclinical bronchoscopic interventional studies.