Johan Nuyts

FDG-PET scan in potentially operable non-small cell lung cancer : Do anatometabolic PET-CT fusion images improve the localisation of regional lymph node metastases?

Abstract Exact localisation of thoracic lymph nodes (LNs) on fluorine-18 fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET) can be hampered by the paucity of anatomical landmarks. In non-small cell lung cancer (NSCLC) patients referred for locoregional LN staging, we prospectively examined to what extent localisation of LNs at PET reading could be improved by visual correlation with computed tomography (CT), or by anatometabolic PET+CT fusion images. Fifty-six patients with potentially operable NSCLC underwent CT, PET and surgical staging. Prospective reading was performed for CT, PET without CT, PET+CT visual correlation and PET+CT fusion. Reading was blinded to surgical pathology data and noted on a standard LN map. Surgical staging was available for 493 LN stations. In the evaluation per individual LN station, CT was accurate in 87%, PET in 91% and visual correlation and fusion in 93%. In the identification of the nodal stage, CT was correct in 28/56 patients (50%), PET in 37/56 (66%), visual correlation in 40/56 (71%), and fusion in 41/56 (73%). It is concluded that in the exact localisation of metastatic thoracic LNs, the accuracy of reading of PET is increased if the PET images can be visually correlated with CT images. PET+CT anatometabolic fusion images add only a marginal benefit compared with visual correlation.

Variability of integrated backscatter: simulations and measurements in vitro

Absolute integrated backscatter (IB) levels and other derived parameters such as cyclic variation (CV) have been used for ultrasonic tissue characterization. Ideally, such a parameter would provide information on the scattering structure and would be independent of the acquisition or the equipment used. It is well known however, that the measured reflected signal of a scattering structure depends on the precise position of the individual scatterers. In order to estimate the sensitivity of IB to this stochastical process, the authors analyzed backscattered data from structures with fixed scatterer densities but with a random distribution, Several independent measurements were made and the variability in IB was calculated. In order to produce the radio frequency (RF) data the authors firstly used computer simulations. Secondly, a real-time RF acquisition system was used to acquire RF data from a tissue mimicking phantom. Finally, an adapted imaging approach was evaluated using mathematical simulations in order to see if it can reduce the measured variability of IB.